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[ {"id":383461199041,"name":"Getting Started","type":"category","path":"/docs/getting-started","breadcrumb":"Getting Started","description":"","searchText":"getting started this section provides the fastest path to understanding how to set up and use analyticscreator. it focuses on how a data warehouse is generated, deployed, and executed based on metadata definitions. if you are new to analyticscreator, start with the quick start guide. it walks through the full workflow from repository creation to data consumption. recommended path quick start guide end-to-end implementation flow from metadata to deployed data warehouse understanding analyticscreator architecture, layers (stg, core, dm), and design principles installation and configuration system setup and environment configuration typical workflow create repository define connectors run data warehouse wizard refine model synchronize database deploy artifacts execute workflows consume data available sections installation system requirements download and installation understanding analyticscreator quick start guide"} ,{"id":383225948363,"name":"Quick Start Guide","type":"section","path":"/docs/getting-started/quick-start-guide","breadcrumb":"Getting Started › Quick Start Guide","description":"","searchText":"getting started quick start guide this quick start guide helps new and trial users understand how to set up, model, and automate a data warehouse using analyticscreator. it follows the actual execution flow of the application, from metadata definition to deployment and execution, and explains how sql-based warehouse structures are generated and processed. the guide assumes: strong sql and etl background familiarity with layered dwh design (stg, core, dm) core concept analyticscreator is a metadata-driven design application that generates sql-based data warehouse structures, transformation logic, and orchestration components. instead of manually implementing etl processes, developers define metadata, which is translated into executable database objects and pipelines. the process follows a generation-driven approach: connect to source systems import metadata (tables, columns, keys, relationships) generate a draft data warehouse model using the wizard refine transformations, keys, and historization generate and deploy sql artifacts and pipelines execute data loading and processing workflows a key architectural element is the persistent staging layer (stg): source data is stored persistently after extraction supports reprocessing without re-reading the source system decouples ingestion from transformation and historization in practice, staging is followed by a second layer where historization is applied before data is transformed into core structures (dimensions and facts). quick start flow the implementation process in analyticscreator follows a defined sequence: create repository initialize a metadata repository (sql server database) that stores all definitions of the data warehouse. create connectors define connections to source systems (e.g. sap, sql server) and enable metadata extraction. import metadata and run wizard automatically read source structures and generate a draft data warehouse model (stg, core, dm). refine the model adjust business keys, surrogate keys, relationships, historization behavior, and transformations. synchronize generate sql objects (tables, views, procedures) and materialize the structure in the target database. deploy generate and deploy deployment packages (dacpac, pipelines, semantic models). execute workflows run generated pipelines (e.g. ssis, azure data factory) to load and process data. consume data use generated data marts and semantic models in reporting tools (e.g. power bi). what this quick start covers create connectors and define relationships (foreign keys, references) import and persist source data in the stg layer understand historization and persistent staging behavior build and refine core transformations (dimensions and facts) define business keys and surrogate keys create data marts (dm layer) and calendar dimensions generate and deploy sql server, pipeline, and analytical model artifacts"} ,{"id":383985776833,"name":"Repository & Metadata Model","type":"subsection","path":"/docs/getting-started/quick-start-guide/repository-metadata-model","breadcrumb":"Getting Started › Quick Start Guide › Repository & Metadata Model","description":"","searchText":"getting started quick start guide repository & metadata model before any connector, transformation, or data warehouse object is created, analyticscreator requires a repository. the repository is a sql server database that stores the complete metadata definition of the data warehouse. all objects defined in analyticscreator—sources, transformations, keys, relationships, deployment settings, and workflows—are stored in this repository. it acts as the central control layer from which all sql code and artifacts are generated. purpose provide a persistent metadata foundation that defines the structure, logic, and behavior of the data warehouse independently of the generated sql artifacts. design principle analyticscreator follows a metadata-driven approach where the repository contains the full definition of the data warehouse model. the repository is not a runtime system; it is a design-time control layer. all generated objects (tables, views, procedures, pipelines) are derived from this metadata. once generated and deployed, these objects can run independently of analyticscreator. key principle: metadata stored in repository → sql and pipelines generated → deployed to target system inputs / outputs inputs repository name and sql server instance initial project configuration outputs sql server database containing metadata structured definitions of: connectors source objects transformations keys and relationships deployment configurations internal mechanics 1. repository creation when a new project is created, analyticscreator initializes a sql server database that serves as the repository. this database contains all metadata required to define the data warehouse. 2. metadata storage each object in analyticscreator is stored as structured metadata. this includes: source definitions (tables, columns, data types) transformation logic historization settings dependencies between objects the repository is fully accessible and can be queried or extended directly if required. 3. central control layer all design changes are written to the repository. no sql objects are created in the target system at this stage. the repository acts as the single source for: code generation deployment packaging dependency resolution 4. separation of design-time and runtime analyticscreator operates purely at design time. the repository defines what will be generated, but execution happens only after deployment in the target environment (sql server, azure, etc.). types / variants local sql server repository (development setup) shared repository (team collaboration) version-controlled repository (via acrepo / json export) example creating a new repository results in a sql server database that contains metadata tables describing the data warehouse model. conceptually: repository (sql server) ├── connectors ├── sources ├── transformations ├── keys / relationships ├── deployment config no stg, core, or dm tables exist yet in the target system. only their definitions are stored. when to use / when not to use use when starting a new data warehouse project managing metadata centrally working in a team with shared definitions do not use as a runtime system the repository does not store business data it is not queried by reporting tools performance & design considerations repository size grows with model complexity, not data volume changes in metadata trigger regeneration, not direct sql changes direct modifications in the target database can be overwritten during synchronization design trade-off: centralized metadata control vs direct sql flexibility integration with other ac features connectors: stored and managed in repository wizard: reads metadata and generates draft models synchronization: converts metadata into sql objects deployment: packages generated artifacts ci/cd: repository can be versioned and exported common pitfalls treating the repository as a data storage layer manually modifying generated sql instead of metadata ignoring repository versioning in team environments mixing multiple environments in a single repository key takeaway the repository is the central metadata store that defines the entire data warehouse and drives all code generation and deployment in analyticscreator."} ,{"id":385512338635,"name":"Synchronize (SQL Generation)","type":"subsection","path":"/docs/getting-started/quick-start-guide/synchronize-sql-generation","breadcrumb":"Getting Started › Quick Start Guide › Synchronize (SQL Generation)","description":"","searchText":"getting started quick start guide synchronize (sql generation) after the model has been refined, the next step is to synchronize the data warehouse. synchronization converts the metadata stored in the repository into physical sql objects in the target database. at this stage, analyticscreator materializes the designed warehouse structure. tables, views, and generated procedures become visible in the sql server database. this is the point where the model moves from design-time metadata to deployable database objects. purpose generate and materialize the physical database structure from the metadata model. design principle synchronization is the controlled transition from metadata definition to sql implementation. the repository remains the source of truth the target database is regenerated or updated from metadata developers do not manually create warehouse objects in the target database. instead, analyticscreator generates them consistently from the repository definitions. inputs / outputs inputs refined metadata model in the repository target database configuration naming conventions and generation settings outputs generated sql server database objects, including: stg tables persistent staging and historization tables core views and tables dm views and tables stored procedures for loading, historization, and persisting internal mechanics 1. metadata evaluation analyticscreator reads the current model definition from the repository and determines which sql objects must be created or updated. 2. object generation based on the metadata, the system generates sql artifacts such as: physical tables for staging and persistent layers views for generated transformations stored procedures for historization and persisting 3. schema materialization the generated structure is applied to the target sql server database. after synchronization, the database contains the warehouse objects defined in the model. 4. dependency-aware generation objects are generated in the required order so that dependent objects can reference upstream objects correctly. 5. re-synchronization behavior if the model changes, synchronization updates the target structure accordingly. this keeps the generated sql database aligned with the repository metadata. types / variants typical synchronized object types import tables historization tables transformation views persisted transformation tables stored procedures generation patterns view-based transformations table-based persisted layers procedure-driven loading and historization example a refined model contains: one source import table one historized customer table one fact transformation one customer dimension after synchronization, the target sql server database contains generated objects such as: stg.customer_import pst.customer_history core.vw_factsales dm.vw_dimcustomer sp_load_customer_import sp_historize_customer the model now exists as physical sql objects, but data is not yet loaded unless execution is triggered separately. when to use / when not to use use when the model has been refined and validated you want to materialize the current warehouse structure you need to inspect or test generated sql objects do not treat synchronization as execution synchronization creates structure, not loaded business data etl or pipeline execution happens later performance & design considerations synchronization affects schema, not data volume frequent changes to metadata can cause repeated structural updates manual database changes outside analyticscreator can be overwritten design trade-off: consistent generated structure vs manual database customization integration with other analyticscreator features repository: remains the source for all generated objects refinement: defines what is materialized persisting: adds generated persisted tables and procedures deployment: packages the synchronized structures for release common pitfalls assuming synchronization loads data editing generated database objects manually synchronizing before validating keys and joins forgetting that metadata, not the target database, is authoritative key takeaway synchronization materializes the metadata model as physical sql objects in the target database, but it does not execute data loading by itself."} ,{"id":385512401134,"name":"Consume Data in Data Marts and Semantic Models","type":"subsection","path":"/docs/getting-started/quick-start-guide/consume-data-in-data-marts-and-semantic-models","breadcrumb":"Getting Started › Quick Start Guide › Consume Data in Data Marts and Semantic Models","description":"","searchText":"getting started quick start guide consume data in data marts and semantic models after workflows have been executed, the data warehouse is populated and ready for consumption. the final step is to access the processed data through data marts and semantic models. analyticscreator generates structures that are optimized for analytical consumption. these include dimensional models and semantic layers that can be directly used by reporting and bi tools. purpose provide structured, query-ready data for analytical tools and reporting use cases. design principle analyticscreator separates data processing from data consumption. stg and core layers handle ingestion and transformation dm and semantic models provide consumption-ready structures consumers should not access staging or intermediate layers directly. inputs / outputs inputs processed core structures generated dm layer (facts and dimensions) deployed semantic model outputs queryable data marts semantic models with defined relationships and measures data available for reporting tools (e.g. power bi) internal mechanics 1. dm layer exposure the dm layer contains consumption-ready structures such as fact and dimension tables or views. these are generated based on the core transformations and are optimized for analytical queries. 2. semantic model generation analyticscreator can generate a semantic model that defines: relationships between facts and dimensions measures and calculated fields hierarchies and aggregation logic 3. data access reporting tools connect to the semantic model or directly to the dm layer. typical access patterns include: directquery or import into bi tools connection to tabular models 4. refresh behavior after workflow execution, the semantic model can be refreshed to reflect updated data. this ensures consistency between the data warehouse and reporting layer. types / variants consumption layers dm tables or views tabular models external bi tool connections access patterns direct query on dm layer semantic model (recommended) hybrid approaches example after execution, the following structures are available: dm.factsales dm.dimcustomer dm.dimproduct a semantic model defines relationships between these tables and exposes measures such as: totalsales = sum(factsales.amount) a reporting tool connects to this model and visualizes sales by customer, product, and time. when to use / when not to use use when data warehouse has been executed and populated users require analytical access to data reporting or dashboarding is required do not use lower layers when accessing stg or core directly for reporting building reports on non-finalized structures performance & design considerations dm layer should be optimized for query performance semantic models reduce complexity for end users pre-aggregations can improve performance for large datasets direct access to core can negatively impact performance and consistency design trade-off: direct access offers flexibility semantic models provide consistency and usability integration with other analyticscreator features core transformations: provide input for dm layer deployment: creates semantic models execution: ensures data is up to date macros and transformations: influence calculated fields and measures common pitfalls querying stg or core layers directly ignoring semantic model design missing refresh after data load overloading dm layer with unnecessary complexity key takeaway the dm layer and semantic model provide consumption-ready data for reporting tools and should be the primary access point for analytical workloads."} ,{"id":385512401131,"name":"Deploy","type":"subsection","path":"/docs/getting-started/quick-start-guide/deploy","breadcrumb":"Getting Started › Quick Start Guide › Deploy","description":"","searchText":"getting started quick start guide deploy after synchronization, the data warehouse structure exists in the target database. the next step is deployment, where analyticscreator generates and distributes deployment artifacts to the selected environment. deployment packages the generated database objects together with orchestration components such as pipelines and analytical models. this allows the data warehouse to be executed and used in a target environment such as sql server, azure or fabric. purpose package and deploy generated database structures, pipelines, and analytical models to a target environment. design principle deployment separates structure generation from environment distribution. synchronization creates the structure deployment distributes and activates it in a target system all deployment artifacts are generated from metadata and can be recreated at any time. inputs / outputs inputs synchronized data warehouse model deployment configuration (target server, database, credentials) selected components (database objects, pipelines, semantic models) outputs deployment package containing: sql scripts or dacpac ssis packages or azure data factory pipelines analytical models (e.g. tabular model for power bi) deployed artifacts in the target environment internal mechanics 1. deployment package creation analyticscreator generates a deployment package that contains all required components for the data warehouse. this includes database objects, pipeline definitions, and optional analytical models. 2. target configuration deployment settings define where the artifacts will be deployed. this includes: sql server or azure environment database name authentication details 3. database deployment the generated database structure is applied to the target system. this may include: creating or updating schemas deploying tables, views, and procedures 4. pipeline generation analyticscreator automatically generates orchestration components: ssis packages for on-premise environments azure data factory pipelines for cloud environments fabric data factory pipelines these pipelines define how data is extracted, transformed, and loaded. 5. analytical model generation if configured, a semantic model is generated and deployed. this includes: dimensions and measures relationships between tables compatibility with reporting tools such as power bi 6. deployment logging the deployment process produces logs that show which objects and components were created or updated. types / variants deployment targets on-premise sql server azure sql database azure synapse or fabric environments pipeline variants ssis packages azure data factory pipelines analytical outputs tabular models for power bi power bi project other supported analytical engines example a deployment is configured with: target sql server database ssis package generation enabled tabular model generation enabled after deployment: database objects are created in the target database ssis packages are generated and available in a visual studio project a tabular model is deployed and available for power bi at this stage, the system is fully deployed but not yet populated with data. when to use / when not to use use when the model is finalized and synchronized you want to move the data warehouse to a target environment pipelines and analytical models need to be generated do not assume deployment loads data deployment creates structure and pipelines data loading requires execution of pipelines performance & design considerations deployment time depends on model size and number of objects pipeline generation adds orchestration complexity but reduces manual work repeated deployments should be controlled via versioning design trade-off: automated deployment vs manual control of environment-specific configurations integration with other analyticscreator features synchronization: provides the generated structure workflows: define execution order within pipelines ci/cd: deployment packages can be integrated into pipelines repository: remains the source for regeneration common pitfalls deploying without validating the model incorrect connection configuration assuming deployment includes data loading not selecting required pipeline or model components key takeaway deployment packages and distributes the generated data warehouse structure, pipelines, and analytical models to a target environment, but does not execute data loading."} ,{"id":385512338634,"name":"Run Data Warehouse Wizard","type":"subsection","path":"/docs/getting-started/quick-start-guide/run-data-warehouse-wizard","breadcrumb":"Getting Started › Quick Start Guide › Run Data Warehouse Wizard","description":"","searchText":"getting started quick start guide run data warehouse wizard after connectors and metadata are available in the repository, the next step is to generate a draft data warehouse model using the analyticscreator wizard. this is the central step where the system translates metadata into a structured warehouse design. the wizard analyzes imported metadata and automatically creates a full model including staging, historization, and transformation layers. this provides a working baseline that can be refined instead of built manually from scratch. purpose generate a complete draft data warehouse model based on imported metadata, including stg, core, and dm structures. design principle analyticscreator follows a generation-first approach: the full data warehouse model is generated automatically from metadata developers refine and adjust the generated model instead of building it manually the wizard uses structural metadata such as tables, keys, and relationships to infer joins, dimensions, and fact structures. inputs / outputs inputs imported metadata from connectors selected source tables modeling approach (e.g. data vault, dimensional, mixed) optional configuration (naming conventions, defaults) outputs generated data warehouse model including: stg layer (import structures) persistent staging and historization structures core layer (dimensions and facts) dm layer (analytical structures) predefined joins and relationships initial transformation logic internal mechanics 1. metadata analysis the wizard reads all metadata stored in the repository, including tables, columns, and relationships. based on this, it determines how objects are related. 2. model generation analyticscreator generates a complete data warehouse structure. this includes: import tables in the stg layer persistent staging structures with historization core transformations for dimensions and facts dm structures for analytical consumption 3. relationship inference joins between tables are derived automatically based on source relationships. these joins are used to construct fact and dimension transformations. 4. default logic generation the wizard can apply default behaviors such as: including directly and indirectly related tables in facts creating standard transformations generating calendar dimensions 5. visual model creation the result is a fully structured data warehouse diagram that shows all layers and dependencies. at this stage, the model is defined but not yet deployed. types / variants modeling approaches data vault model (hubs, links, satellites) dimensional model (facts and dimensions) mixed approach (data vault foundation with dimensional output) configuration options naming conventions (prefixes, suffixes) default transformations inclusion rules for related tables example a set of source tables is selected: customer orders orderlines products after running the wizard: stg tables are created for each source relationships are detected automatically a fact table is generated based on transaction data dimensions are generated for related entities the resulting model already contains joins, transformation paths, and structural dependencies. when to use / when not to use use when starting a new data warehouse model rapidly generating a baseline structure working with well-defined source metadata do not rely on defaults when business logic is complex or non-standard source relationships are incomplete or incorrect fact and dimension definitions require domain-specific adjustments performance & design considerations the wizard accelerates initial modeling but does not replace design decisions generated joins should be reviewed for correctness and performance fact table scope depends on inclusion settings (direct vs indirect relationships) design trade-off: full automation provides speed manual refinement ensures correctness and performance integration with other analyticscreator features repository: provides metadata input for the wizard transformations: generated and refined after wizard execution synchronization: converts generated model into sql objects deployment: packages generated artifacts common pitfalls assuming the generated model is production-ready without review over-including tables leading to overly complex fact structures ignoring incorrect or missing source relationships not validating generated joins key takeaway the wizard generates a complete data warehouse model from metadata, which is then refined and deployed rather than built manually."} ,{"id":385512401101,"name":"Create Connectors","type":"subsection","path":"/docs/getting-started/quick-start-guide/create-connectors","breadcrumb":"Getting Started › Quick Start Guide › Create Connectors","description":"","searchText":"getting started quick start guide create connectors after initializing the repository, the next step is to define connectors to source systems. connectors provide the technical and structural foundation for importing metadata and generating the data warehouse model. a connector defines how analyticscreator accesses a source system and how metadata (tables, columns, keys, relationships) is retrieved. this metadata is then stored in the repository and used by the data warehouse wizard to generate a draft model. purpose establish access to source systems and import structural metadata required for automated data warehouse generation. design principle analyticscreator separates metadata acquisition from data extraction. metadata (structure) is imported first and stored in the repository data extraction happens later during execution (via pipelines) this means a data warehouse model can be designed and generated without requiring an active connection to the source system at runtime. inputs / outputs inputs connector type (e.g. sql server, sap, metadata connector) connection configuration (server, database, authentication) selected schemas, tables, or metadata source outputs connector definition stored in repository imported metadata: tables and views columns and data types primary keys foreign keys or references (if available) internal mechanics 1. connector definition the connector stores the configuration required to access a source system. this includes connection details and selection of relevant schemas or objects. 2. metadata extraction analyticscreator reads structural metadata from the source system or from a metadata connector. this includes: table structures column definitions key definitions relationships between tables in some cases (e.g. sap or metadata connectors), metadata can be imported without direct access to the operational system. 3. repository persistence all imported metadata is stored in the repository. at this stage: no sql objects are generated no data is extracted no pipelines are executed the system builds a structural model that will later drive code generation. 4. relationship availability if source systems expose foreign keys or references, these are imported and can be reused during modeling. if not, relationships must be defined manually in later steps. types / variants connector types direct database connectors (e.g. sql server) erp connectors (e.g. sap metadata extraction) metadata connectors (predefined structures without live connection) import modes full metadata import selective table import manual definition (if metadata is incomplete) example a connector is created for a sql server database containing the following tables: customer orders orderlines the system imports: column definitions (e.g. customerid, orderid) primary keys foreign key relationships (e.g. orders → customer) these definitions are stored in the repository and become available for automated model generation in the next step. when to use / when not to use use when starting a new data warehouse model importing metadata from source systems preparing for automated model generation do not rely on connectors alone when source metadata is incomplete or inconsistent business relationships differ from technical relationships required structures are not exposed in the source system performance & design considerations connector scope directly affects model complexity importing unnecessary tables increases modeling overhead metadata quality determines quality of generated model design trade-off: broad import (high coverage, more noise) selective import (cleaner model, more manual work later) integration with other analyticscreator features repository: stores connector and metadata definitions wizard: uses imported metadata to generate draft model stg generation: based on imported source structures transformations: reuse source metadata and relationships common pitfalls importing entire source systems without filtering assuming source relationships are suitable for analytical models using technical keys as business keys without validation skipping metadata validation before running the wizard key takeaway connectors import and persist source metadata in the repository, forming the structural basis for automated data warehouse generation."} ,{"id":385512401133,"name":"Execute Workflows (Load Data)","type":"subsection","path":"/docs/getting-started/quick-start-guide/execute-workflows-load-data","breadcrumb":"Getting Started › Quick Start Guide › Execute Workflows (Load Data)","description":"","searchText":"getting started quick start guide execute workflows (load data) after deployment, the data warehouse structure, pipelines, and analytical models exist in the target environment, but no business data has been loaded yet. the next step is to execute the generated workflows. workflow execution runs the generated load processes in the correct order. this is the stage where source data is extracted, written to staging, historized where required, transformed into core structures, and exposed through data marts and analytical models. purpose execute the generated loading and processing workflows so that the deployed data warehouse is populated with data. design principle analyticscreator separates execution from generation. generation defines structure and logic execution runs the actual data movement and processing this separation makes it possible to validate and deploy a model before loading any business data. inputs / outputs inputs deployed database objects generated workflows or pipeline packages configured source connections and linked services execution parameters and scheduling context outputs loaded stg tables historized persistent staging tables processed core structures updated dm structures refreshed analytical model content internal mechanics 1. workflow start execution begins by starting the generated workflow package or pipeline. this acts as the orchestration entry point for the full load process. 2. source extraction data is read from the configured source systems and written into the stg layer. import mappings, filters, and variables defined in the model are applied during this step. 3. persistent staging and historization after import, the data is written into the persistent staging layer. if historization is enabled, valid-from and valid-to handling or other configured historization logic is executed here. 4. core processing generated transformations are processed in dependency order. facts, dimensions, and other core structures are built from the persisted source data. 5. dm and semantic model refresh after core processing, the dm layer and the generated semantic model can be refreshed so that reporting tools can consume the updated data. 6. dependency handling the execution order is controlled by the generated workflow logic. upstream objects are processed before downstream objects so that dependencies are resolved automatically. types / variants execution variants ssis-based execution azure data factory pipeline execution manual execution for testing scheduled execution in production loading patterns full load incremental load historized load example a deployed workflow package contains the following sequence: load source table into stg.customer_import apply historization into pst.customer_history refresh fact and dimension transformations refresh the semantic model used by power bi at the end of execution: source data is available in staging historical versions are stored where configured reporting tools can access current analytical data when to use / when not to use use when the deployment has completed successfully source connections are configured correctly you want to populate or refresh the data warehouse do not execute before validating linked services and source access reviewing load filters and parameters confirming that required objects have been deployed performance & design considerations execution time depends on data volume, transformation complexity, and load pattern persistent staging supports reprocessing without re-reading source systems incremental loading reduces runtime but requires correct filter logic historization increases write volume and storage requirements design trade-off: full reloads are simpler to validate incremental and historized loads scale better but require stricter design control integration with other analyticscreator features connectors: provide source access used during execution stg and historization: form the first processing layers workflows: define orchestration and dependency order deployment: provides the executable packages and pipelines semantic models: can be refreshed after successful load common pitfalls assuming deployment already loaded data running workflows without validating linked services using incorrect filter logic for incremental loads ignoring dependency order in manually triggered runs confusing source staging with final analytical output key takeaway workflow execution is the step where deployed structures are populated with data and processed into usable analytical output."} ,{"id":385512401114,"name":"Refine the Model","type":"subsection","path":"/docs/getting-started/quick-start-guide/refine-the-model","breadcrumb":"Getting Started › Quick Start Guide › Refine the Model","description":"","searchText":"getting started quick start guide refine the model after generating the draft model with the wizard, the next step is to refine and adjust the data warehouse structure. the generated model provides a complete baseline, but it must be validated and adapted to match business logic, data quality, and performance requirements. this step focuses on defining keys, adjusting transformations, handling historization, and ensuring that the generated joins and structures reflect the intended analytical model. purpose validate and adjust the generated data warehouse model to ensure correct business logic, data relationships, and performance behavior. design principle analyticscreator generates a structurally complete model, but correctness is achieved through refinement. automation provides the structure manual refinement ensures semantic accuracy developers work on metadata definitions, not directly on sql, and all changes are reflected in generated code during synchronization. inputs / outputs inputs generated draft model (stg, core, dm) source metadata and relationships business requirements and logic outputs refined transformations defined business keys and surrogate keys adjusted joins and relationships configured historization behavior internal mechanics 1. column selection and cleanup generated transformations often include all available columns. unnecessary attributes should be removed to reduce model complexity and improve performance. 2. business key definition business keys must be validated or defined explicitly. these keys determine: uniqueness of entities join conditions between tables basis for historization 3. surrogate key generation analyticscreator generates surrogate keys automatically. depending on the modeling approach: identity-based keys (e.g. integer) hash-based keys (for data vault or hybrid models) hash keys are typically generated in the staging layer as calculated and persisted columns. 4. relationship validation automatically generated joins should be reviewed. this includes: correct join paths cardinality assumptions inclusion of required tables 5. historization configuration historization is applied in persistent staging and core layers. typical behavior includes: valid-from and valid-to columns tracking changes over time the historization strategy should be verified for correctness and performance impact. 6. macro usage reusable sql logic is implemented using macros. for example: hash key generation standard transformations macros allow centralized control of repeated logic without modifying generated sql directly. 7. dimension and fact adjustments fact tables and dimensions generated by the wizard should be refined: remove unnecessary joins add required attributes ensure correct grain of fact tables 8. calendar and date handling date columns should typically be replaced by references to a calendar dimension. this is often done using predefined macros. types / variants key strategies business keys only surrogate keys (identity) hash-based keys historization strategies scd2 (valid-from / valid-to) snapshot-based access current-state only transformation styles fully generated adjusted via metadata extended with custom sql logic example a generated fact table includes all columns from multiple related tables. refinement steps: remove unnecessary attributes validate join between orders and customers define surrogate key for dimension tables replace date columns with calendar dimension references example adjustment: -- before refinement select * from stg_orders o join stg_customer c on o.customer_id = c.customer_id; -- after refinement (conceptual) select o.order_id, c.customer_key, o.order_date_key, o.amount from core_orders o join dim_customer c on o.customer_key = c.customer_key; when to use / when not to use use when after running the wizard validating generated model structures aligning model with business logic do not skip when working with complex source systems data quality issues exist performance requirements are strict performance & design considerations reducing column count improves performance incorrect joins can cause data duplication historization increases storage and processing cost hash keys improve scalability but add computation overhead design trade-off: automation speed vs model accuracy flexibility vs standardization integration with other analyticscreator features wizard: provides initial model macros: define reusable sql logic synchronization: generates sql from refined metadata deployment: uses finalized model for artifact creation common pitfalls leaving generated joins unvalidated using incorrect business keys overloading fact tables with unnecessary attributes ignoring historization impact on performance mixing business logic directly into sql instead of metadata key takeaway the generated model must be refined to ensure correct business logic, keys, and performance before sql generation and deployment."} ,{"id":383225948362,"name":"Understanding AnalyticsCreator","type":"section","path":"/docs/getting-started/understanding-analytics-creator","breadcrumb":"Getting Started › Understanding AnalyticsCreator","description":"","searchText":"getting started understanding analyticscreator analyticscreator is a metadata-driven design application for building and automating data warehouses and analytical models. instead of manually implementing etl and sql logic, developers define metadata such as sources, keys, relationships, transformations, and loading behavior. analyticscreator uses these definitions to generate database objects, pipelines, and semantic models. how analyticscreator works the workflow in analyticscreator starts with a repository, continues with source metadata import, and then uses a wizard to generate a draft data warehouse model. that model is refined, synchronized into sql objects, deployed to the target environment, and finally executed through generated workflows or pipelines. create a repository define or import connectors import source metadata run the data warehouse wizard refine the generated model synchronize the structure deploy artifacts execute workflows consume data through data marts and semantic models repository and metadata every analyticscreator project is based on a repository. the repository is a sql server database that stores the full metadata definition of the data warehouse. this includes connectors, source objects, transformations, keys, relationships, deployment settings, and other object definitions. the repository is the design-time control layer and the source for all generated artifacts. this means the target database is not modeled manually. instead, analyticscreator reads the repository metadata and generates the required sql structures from it. generated code can run independently after deployment because analyticscreator is used as a design-time application, not as a runtime dependency. connectors and metadata import analyticscreator connects to source systems such as sql server or sap and imports structural metadata including tables, columns, keys, and references. in some scenarios, metadata can also be imported through metadata connectors, which makes it possible to model a data warehouse without an active connection to the live source system during design. imported metadata is stored in the repository and later used by the wizard to generate the draft warehouse model. at this stage, no warehouse data has been loaded yet. only structure and metadata are being captured. the wizard the data warehouse wizard is the central acceleration mechanism in analyticscreator. it analyzes source metadata and generates a draft warehouse model automatically. depending on the selected approach, this can be a dimensional model, a data vault model, or a mixed approach. the wizard can create staging structures, historization layers, dimensions, facts, calendar dimensions, and default relationships based on detected metadata. the generated model is not the end result. it is the baseline that developers refine and validate. the main engineering work happens after generation, when keys, joins, historization behavior, measures, and transformations are adjusted to fit the intended warehouse design. warehouse layers analyticscreator supports a layered warehouse architecture from source to presentation. in a typical setup, this includes source objects, staging, persistent staging or historization, core transformations, data marts, and semantic or reporting layers. it can also generate analytical models for tools such as power bi. persistent staging a key architectural concept is the persistent staging layer. source data is first imported into staging structures and then stored persistently for further processing. this persistent layer is used for historization and for decoupling source extraction from downstream transformations. it allows data to be reprocessed without repeatedly reading the source system. in dimensional scenarios, historized tables typically include surrogate keys together with valid-from and valid-to columns. in data vault and hybrid scenarios, additional hash-based keys and references can be generated in the staging layer as persisted calculated columns and then reused in later layers. transformations transformations in analyticscreator are usually generated as sql views based on metadata definitions. these definitions specify source tables, joins, selected columns, macros, and transformation rules. in many cases, the default generated view logic is sufficient as a starting point, but it can be refined through metadata rather than by rewriting generated sql directly. analyticscreator also supports reusable macros for standard sql logic, such as date-to-calendar-key conversion or hash key generation. this allows repeated logic to be defined once and reused consistently across the model. synchronization, deployment, and execution these three steps are related but different and should not be confused. synchronization synchronization materializes the metadata model into sql objects in the target database. this creates the database structure defined in analyticscreator, such as tables, views, and procedures. it does not mean that business data has already been loaded. :contentreference[oaicite:13]{index=13} deployment deployment creates and distributes deployable artifacts for the selected target environment. these can include sql database packages, ssis packages, azure data factory pipelines, and semantic models. deployment prepares the environment but still does not imply that source data has already been processed. execution execution runs the generated workflows and pipelines. this is the step where source data is actually extracted, written to staging, historized where required, transformed into core structures, and exposed through data marts and semantic models. in azure scenarios, this may happen through azure data factory. in on-premise scenarios, this may happen through ssis. consumption after execution, the data warehouse can be consumed through data marts and semantic models. these structures are intended for reporting and analytics, while lower layers such as staging and historization should remain implementation layers rather than direct reporting interfaces. analyticscreator can generate tabular models and structures for tools such as power bi. design implications the repository is the source of truth metadata drives generation, not manual sql-first development the wizard creates a baseline, not a final production model persistent staging is part of the architecture, not just a temporary landing area synchronization, deployment, and execution are separate steps consumption should happen from data marts or semantic models, not from staging layers key takeaway analyticscreator works by storing warehouse definitions as metadata, generating sql and orchestration artifacts from that metadata, and then deploying and executing those artifacts in the target environment."} ,{"id":383225948358,"name":"Installation","type":"section","path":"/docs/getting-started/installation","breadcrumb":"Getting Started › Installation","description":"","searchText":"getting started installation installing analyticscreator: 32-bit and 64-bit versions this guide offers step-by-step instructions for installing either the 32-bit or 64-bit version of analyticscreator, depending on your system requirements. ⓘ note: to ensure optimal performance, verify that your system meets the following prerequisites before installation."} ,{"id":383225948359,"name":"System Requirements","type":"section","path":"/docs/getting-started/system-requirements","breadcrumb":"Getting Started › System Requirements","description":"","searchText":"getting started system requirements to ensure optimal performance, verify that the following requirements are met: ⓘ note: if you already have sql server installed and accessible, you can proceed directly to the launching analyticscreator section. networking: communication over port 443 is where analytics communicates to the analyticscreator server. operating system: windows 10 or later. analyticscreator is compatible with windows operating systems starting from version 10. ⓘ warning: port 443 is the standard https port for secured transactions. it is used for data transfers and ensures that data exchanged between a web browser and websites remains encrypted and protected from unauthorized access. microsoft sql server: sql server on azure virtual machines azure sql managed instances"} ,{"id":383225948360,"name":"Download and Installation","type":"section","path":"/docs/getting-started/download-and-installation","breadcrumb":"Getting Started › Download and Installation","description":"","searchText":"getting started download and installation access the download page navigate to the analyticscreator download page download the installer locate and download the installation file. verify sql server connectivity before proceeding with the installation, confirm that you can connect to your sql server instance. connecting to sql server: to ensure successful connectivity: use sql server management studio (ssms), a tool for managing and configuring sql server. if ssms is not installed on your system, download it from the official microsoft site: download sql server management studio (ssms) install the software once connectivity is confirmed, follow the instructions below to complete the installation."} ,{"id":383225948361,"name":"Configuring AnalyticsCreator","type":"section","path":"/docs/getting-started/configuring-analyticscreator","breadcrumb":"Getting Started › Configuring AnalyticsCreator","description":"","searchText":"getting started configuring analyticscreator this guide will walk you through configuring analyticscreator with your system. provide the login and password that you received by e-mail from analyticscreator minimum requirements configuration settings the configuration of analyticscreator is very simple. the only mandatory configuration is the sql server settings. sql server settings use localdb to store repository: enables you to store the analyticscreator project (metadata only) on your localdb. sql server to store repository: enter the ip address or the name of your microsoft sql server. security integrated: authentication is based on the current windows user. standard: requires a username and password. azure ad: uses azure ad (now microsoft entra) for microsoft sql server authentication. trust server certificate: accepts the server's certificate as trusted. sql user: the sql server username. sql password: the corresponding password. optional requirements paths unc path to store backup: a network path to store project backups. local sql server path to store backup: a local folder to store your project backups. local sql server path to store database: a local folder to store your sql server database backups. repository database template: the alias format for your repositories. default: repo_{reponame}. dwh database template: the alias format for your dwh templates. default: dwh_{reponame}. proxy settings proxy address: the ip address or hostname of your proxy server. proxy port: the port number used by the proxy. proxy user: the username for proxy authentication. proxy password: the password for the proxy user. now you're ready to create your new data warehouse with analyticscreator."} , {"id":383461199042,"name":"User Guide","type":"category","path":"/docs/user-guide","breadcrumb":"User Guide","description":"","searchText":"user guide you can launch analyticscreator in two ways: from the desktop icon after installation or streaming setup, a desktop shortcut is created. double-click the icon to start analyticscreator. from the installer window open the downloaded analyticscreator installer. instead of selecting install, click launch (labeled as number one in the image below). a window will appear showing the available analyticscreator servers, which deliver the latest version to your system. this process launches analyticscreator without performing a full installation, assuming all necessary prerequisites are already in place."} ,{"id":383225948364,"name":"Desktop Interface","type":"section","path":"/docs/user-guide/desktop-interface","breadcrumb":"User Guide › Desktop Interface","description":"","searchText":"user guide desktop interface with analyticscreator desktop users can: data warehouse creation automatically generate and structure your data warehouse, including fact tables and dimensions. connectors add connections to various data sources and import metadata seamlessly. layer management define and manage layers such as staging, persisted staging, core, and datamart layers. package generation generate integration packages for ssis (sql server integration services) and adf (azure data factory). indexes and partitions automatically configure indexes and partitions for optimized performance. roles and security manage roles and permissions to ensure secure access to your data. galaxies and hierarchies organize data across galaxies and define hierarchies for better data representation. customizations configure parameters, macros, scripts, and object-specific scripts for tailored solutions. filters and predefined transformations apply advanced filters and transformations for data preparation and enrichment. snapshots and versioning create snapshots to track and manage changes in your data warehouse. deployments deploy your projects with flexible configurations, supporting on-premises and cloud solutions. groups and models organize objects into groups and manage models for streamlined workflows. data historization automate the process of creating historical data models for auditing and analysis."} ,{"id":383225948365,"name":"Working with AnalyticsCreator","type":"section","path":"/docs/user-guide/working-with-analyticscreator","breadcrumb":"User Guide › Working with AnalyticsCreator","description":"","searchText":"user guide working with analyticscreator understanding the fundamental operations in analyticscreator desktop is essential for efficiently managing your data warehouse repository and ensuring accuracy in your projects. below are key basic operations you can perform within the interface: edit mode and saving - data warehouse editor single object editing: in the data warehouse repository, you can edit one object at a time. this ensures precision and reduces the risk of unintended changes across multiple objects. how to edit: double-click on any field within an object to enter edit mode. the selected field becomes editable, allowing you to make modifications. save prompt: if any changes are made, a prompt will appear, reminding you to save your modifications before exiting the edit mode. this safeguard prevents accidental loss of changes. unsaved changes: while edits are immediately reflected in the repository interface, they are not permanently saved until explicitly confirmed by clicking the save button. accessing views in data warehouse explorer layer-specific views: each layer in the data warehouse contains views generated by analyticscreator. these views provide insights into the underlying data structure and transformations applied at that layer. how to access: navigate to the data warehouse explorer and click on the view tab for the desired layer. this displays the layer's contents, including tables, fields, and transformations. adding and deleting objects adding new objects: navigate to the appropriate section (e.g., tables, layers, or connectors) in the navigation tree. right-click and select add [object type] to create a new object. provide the necessary details, such as name, description, and configuration parameters. save the object. deleting objects: select the object in the navigation tree and right-click to choose delete. confirm the deletion when prompted. ⚠️ note: deleting an object may affect dependent objects or configurations. filtering and searching in data warehouse explorer filtering: use filters to narrow down displayed objects by criteria such as name, type, or creation date. searching: enter keywords or phrases in the search bar to quickly locate objects. benefits: these features enhance repository navigation and efficiency when working with large datasets. object dependencies and relationships dependency view: for any selected object, view its dependencies and relationships with other objects by accessing the dependencies tab. impact analysis: analyze how changes to one object might affect other parts of the data warehouse. managing scripts predefined scripts: add scripts for common operations like data transformations or custom sql queries. edit and run: double-click a script in the navigation tree to modify it. use run script to execute and view results. validating and testing changes validation tools: use built-in tools to check for errors or inconsistencies in your repository. evaluate changes: use the evaluate button before saving or deploying to test functionality and ensure correctness. locking and unlocking objects locking: prevent simultaneous edits by locking objects, useful in team environments. unlocking: release locks once edits are complete to allow further modifications by others. exporting and importing data export: export objects, scripts, or configurations for backup or sharing. use the export option in the toolbar or navigation tree. import: import previously exported files to replicate configurations or restore backups. use the import option and follow the prompts to load the data."} ,{"id":391011561704,"name":"Historization with AnalyticsCreator","type":"subsection","path":"/docs/user-guide/working-with-analyticscreator/historization-with-analyticscreator","breadcrumb":"User Guide › Working with AnalyticsCreator › Historization with AnalyticsCreator","description":"","searchText":"user guide working with analyticscreator historization with analyticscreator historization in analyticscreator is applied after source import and before downstream analytical modeling. source data is first loaded into staging, then written into a persistent staging or historization layer, and only then used in core and datamart transformations. historization in analyticscreator table historization stores changing records with validity periods and surrogate keys. this page focuses on that pattern. column historization individual columns can use full history, equal-only behavior, or no change tracking. transformation historization downstream transformations can consume historized data as current-state, snapshot-based, or full historical output. join historization historized joins can apply different validity rules when combining time-dependent structures. purpose explain how analyticscreator stores and processes changing data over time so that previous states remain available for analysis and downstream processing. design principle analyticscreator treats historization as a warehouse-layer concern, not a reporting-layer concern. source data is imported first historization is applied in persistent staging downstream transformations consume historized data this design separates source extraction from change tracking and allows historical states to be reused across multiple downstream transformations. inputs / outputs inputs imported source table or source query in staging key definition used to identify records across loads column-level historization settings missing-source behavior optional filters and variables outputs historized table in persistent staging valid-from column valid-to column generated surrogate key generated historization stored procedure optional snapshot-aware downstream transformations internal mechanics 1. import first, historize second analyticscreator first imports source data into a staging table. historization is executed after the import step, not during initial extraction. 2. historized table structure a historized table typically contains: business key or source key tracked attributes valid-from field valid-to field surrogate key field this is the standard scd type 2 structure used to preserve previous states of a record. 3. column-level historization behavior historization is configurable per column. analyticscreator supports different behaviors per attribute: full history – changes create new historical versions equal only / scd1-style – current value is updated without creating a history row none – the column is ignored for change tracking this allows mixed historization strategies within the same object. 4. missing-source behavior analyticscreator allows explicit handling of records that disappear from the source: close the current record by setting the end of validity leave the current record open optionally insert an empty record to avoid timeline gaps this is important when rows can temporarily disappear and reappear later. 5. generated historization procedure historization logic is generated as a stored procedure. the procedure is specific to the object configuration and can be reviewed or extended if required. 6. downstream consumption downstream transformations can consume historized data in different ways: actual only – only the currently valid row is used snapshot – rows are selected based on a snapshot date between valid-from and valid-to full historical – all historical states remain available types / variants column-level change tracking full history equal only none missing-source behavior close validity keep open add empty record consumption behavior current-state only snapshot-based full historical access example assume a staging table contains customer data: stg_customer ( customer_id, name, city ) a historized table generated from it may look like this: pst_customer_history ( sats_id bigint, customer_id int, name nvarchar(100), city nvarchar(100), date_from datetime, date_to datetime ) a representative scd type 2 pattern is: -- close current row when tracked attributes changed update tgt set date_to = @load_ts from pst_customer_history tgt join stg_customer src on tgt.customer_id = src.customer_id and tgt.date_to is null where isnull(tgt.name, '') <> isnull(src.name, '') or isnull(tgt.city, '') <> isnull(src.city, ''); -- insert new current row insert into pst_customer_history ( customer_id, name, city, date_from, date_to ) select src.customer_id, src.name, src.city, @load_ts, null from stg_customer src left join pst_customer_history tgt on tgt.customer_id = src.customer_id and tgt.date_to is null where tgt.customer_id is null or isnull(tgt.name, '') <> isnull(src.name, '') or isnull(tgt.city, '') <> isnull(src.city, ''); this pattern shows the core behavior: current rows are closed when tracked attributes change, and a new current row is inserted. when to use / when not to use use when attribute changes must remain traceable over time source systems overwrite current values point-in-time analysis is required previous business states must remain queryable do not use when only the latest state matters the source already provides reliable historized data and duplicate historization is unnecessary storage growth from history rows is not acceptable performance & design considerations historization increases write volume and storage usage over-tracking noisy columns creates unnecessary row churn wrong missing-source settings can produce incorrect history timelines snapshot-based downstream joins are more expensive than current-state joins design trade-off: full history gives maximum traceability selective tracking improves storage and runtime efficiency integration with other analyticscreator features import packages and pipelines provide the staging input for historization transformation historization types define how historized rows are consumed downstream macros can support key generation in hybrid and data vault scenarios persisting can materialize downstream historized views for performance datamarts and semantic models can consume current-state or snapshot-based outputs common pitfalls tracking all columns as scd type 2 even when some should be scd1 or ignored not defining missing-source behavior using current-state-only logic when point-in-time analysis is required overusing snapshot logic in scenarios where current-state output is sufficient changing generated sql directly instead of fixing metadata configuration metadata representation historization metadata in analyticscreator typically includes: source object reference key definition per-column historization mode missing-source behavior optional filters and variables downstream transformation historization mode these settings are stored in the repository and used to generate historization logic and dependent transformations. deployment behavior build reads metadata from the repository generates historized tables generates historization procedures builds downstream transformations deploy deploys historized table structures deploys generated procedures deploys orchestration assets refresh / execute imports source data into staging executes historization logic refreshes downstream core and datamart structures key design principle what is generated? historized tables, surrogate keys, validity columns, and historization procedures when is it executed? after source import and before downstream transformation processing where is it stored? in the persistent staging or historization layer how does it scale? through selective column tracking, explicit missing-source handling, filtered loads, and downstream consumption control key takeaway analyticscreator implements scd type 2 historization as a configurable warehouse-layer service that preserves previous states through validity windows, surrogate keys, and generated historization procedures."} ,{"id":383225948366,"name":"Advanced Features","type":"section","path":"/docs/user-guide/advanced-features","breadcrumb":"User Guide › Advanced Features","description":"","searchText":"user guide advanced features analyticscreator provides a rich set of advanced features to help you configure, customize, and optimize your data warehouse projects. these features extend the tool’s capabilities beyond standard operations, enabling more precise control and flexibility. scripts scripts in analyticscreator allow for detailed customization at various stages of data warehouse creation and deployment. they enhance workflow flexibility and enable advanced repository configurations. types of scripts object-specific scripts define custom behavior for individual objects, such as tables or transformations, to meet specific requirements. pre-creation scripts execute tasks prior to creating database objects. example: define sql functions to be used in transformations. pre-deployment scripts configure processes that run before deploying the project. example: validate dependencies or prepare the target environment. post-deployment scripts handle actions executed after deployment is complete. example: perform cleanup tasks or execute stored procedures. pre-workflow scripts manage operations that occur before initiating an etl workflow. example: configure variables or initialize staging environments. repository extension scripts extend repository functionality with user-defined logic. example: add custom behaviors to redefine repository objects. historization the historization features in analyticscreator enable robust tracking and analysis of historical data changes, supporting advanced time-based reporting and auditing. key components slowly changing dimensions (scd) automate the management of changes in dimension data. supports various scd types including: type 1 (overwrite) type 2 (versioning) others as needed time dimensions create and manage temporal structures to facilitate time-based analysis. example: build fiscal calendars or weekly rollups for time-series analytics. snapshots capture and preserve specific states of the data warehouse. use cases include audit trails, historical reporting, and rollback points. parameters and macros these tools provide centralized control and reusable logic to optimize workflows and streamline repetitive tasks. parameters dynamic management: centralize variable definitions for consistent use across scripts, transformations, and workflows. reusable configurations: update values in one place to apply changes globally. use cases: set default values for connection strings, table prefixes, or date ranges. macros reusable logic: create parameterized scripts for tasks repeated across projects or workflows. streamlined processes: use macros to enforce consistent logic in transformations and calculations. example: define a macro to calculate age from a birthdate and reuse it across transformations. summary analyticscreator’s advanced features offer deep customization options that allow you to: control object-level behavior through scripting track and manage historical data effectively streamline project-wide settings with parameters reuse logic with powerful macros these capabilities enable you to build scalable, maintainable, and highly flexible data warehouse solutions."} ,{"id":383225948367,"name":"Wizards","type":"section","path":"/docs/user-guide/wizards","breadcrumb":"User Guide › Wizards","description":"","searchText":"user guide wizards the wizards in analyticscreator provide a guided and efficient way to perform various tasks related to building and managing a data warehouse. below is an overview of the eight available wizards and their core functions. dwh wizard the dwh wizard is designed to quickly create a semi-ready data warehouse. it is especially useful when the data source contains defined table relationships or manually maintained references. supports multiple architectures: classic (kimball), data vault 1.0 & 2.0, or mixed. automatically creates imports, dimensions, facts, hubs, satellites, and links. customizable field naming, calendar dimensions, and sap deltaq integration. source wizard the source wizard adds new data sources to the repository. supports source types: table or query. retrieves table relationships and sap-specific metadata. allows query testing and schema/table filtering. import wizard the import wizard defines and manages the import of external data into the warehouse. configures source, target schema, table name, and ssis package. allows additional attributes and parameters. historization wizard the historization wizard manages how tables or transformations are historized. supports scd types: 0, 1, and 2. configures empty record behavior and vault id usage. supports ssis-based or stored procedure historization. transformation wizard the transformation wizard creates and manages data transformations. supports regular, manual, script, and external transformation types. handles both historized and non-historized data. configures joins, fields, persistence, and metadata settings. calendar transformation wizard the calendar transformation wizard creates calendar transformations used in reporting and time-based models. configures schema, name, start/end dates, and date-to-id macros. assigns transformations to specific data mart stars. time transformation wizard the time transformation wizard creates time dimensions to support time-based analytics. configures schema, name, time period, and time-to-id macros. assigns transformations to specific data mart stars. snapshot transformation wizard the snapshot transformation wizard creates snapshot dimensions for snapshot-based analysis. allows creation of one snapshot dimension per data warehouse. configures schema, name, and data mart star assignment. by using these eight wizards, analyticscreator simplifies complex tasks, ensures consistency, and accelerates the creation and management of enterprise data warehouse solutions."} ,{"id":384157771973,"name":"DWH Wizard","type":"subsection","path":"/docs/user-guide/wizards/dwh-wizard-function","breadcrumb":"User Guide › Wizards › DWH Wizard","description":"","searchText":"user guide wizards dwh wizard the dwh wizard allows for the rapid creation of a semi-ready data warehouse. it is especially effective when the data source includes predefined table references or manually maintained source references. prerequisites at least one source connector must be defined before using the dwh wizard. note: the dwh wizard support flat files using duckdb , in that case you should select the option \"use metadata of existing sources\" or use the source wizard instead. to launch the dwh wizard, click the “dwh wizard” button in the toolbar. instead, the user can use the connector context menu: using the dwh wizard select the connector, optionally enter the schema or table filter, and click \"apply\". then, the source tables will be displayed. optionally, select the \"existing sources\" radio button to work with already defined sources instead of querying the external system (ideal for meta connectors). if a table already exists, the \"exist\" checkbox will be selected. to add or remove tables: select them and click the ▶ button to add. select from below and click the ◀ button to remove. dwh wizard architecture options the wizard can generate the dwh using: classic or mixed architecture: supports imports, historization, dimensions, and facts. data vault architecture: supports hubs, satellites, links, dimensions, and facts with automatic classification when “auto” is selected. define name templates for dwh objects: set additional parameters: dwh wizard properties field name appearance: leave unchanged, or convert to upper/lowercase. retrieve relations: enable automatic relation detection from source metadata. create calendar dimension: auto-create calendar dimension and define date range. include tables in facts: include related tables in facts (n:1, indirect, etc.). use calendar in facts: include date-to-calendar references in fact transformations. sap deltaq transfer mode: choose between idoc or trfs. sap deltaq automatic synchronization: enable automatic deltaq sync. sap description language: select sap object description language. datavault2: do not create hubs: optionally suppress hub creation in dv2. historizing type: choose ssis package or stored procedure for historization. use friendly names in transformations as column names: use display names from sap/meta/manual connectors. default transformations: select default predefined transformations for dimensions. stars: assign generated dimensions and facts to data mart stars."} ,{"id":389871309037,"name":"DWH Wizard Calendar","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-calendar","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Calendar","description":"","searchText":"user guide wizards dwh wizard dwh wizard calendar overview dwh wizard calendar is a dwh wizard parameter that sets the option used for the dwh wizard calendar. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_calendar default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard calendar from parameters previous dwh wizard snapshot nextdwh wizard calendar transname"} ,{"id":389871309039,"name":"DWH Wizard Calendar From","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-calendar-from","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Calendar From","description":"","searchText":"user guide wizards dwh wizard dwh wizard calendar from overview dwh wizard calendar from is a dwh wizard parameter that controls the calendar start date. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 19800101 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_calendar_from default value 19800101 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard calendar dwh wizard calendar to parameters previous dwh wizard calendar transname nextdwh wizard calendar to"} ,{"id":389871309040,"name":"DWH Wizard Calendar To","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-calendar-to","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Calendar To","description":"","searchText":"user guide wizards dwh wizard dwh wizard calendar to overview dwh wizard calendar to is a dwh wizard parameter that controls the calendar end date. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 20401231 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_calendar_to default value 20401231 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard calendar from dwh wizard calendar transname parameters previous dwh wizard calendar from nextdwh wizard fact"} ,{"id":389871309038,"name":"DWH Wizard Calendar Transname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-calendar-transname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Calendar Transname","description":"","searchText":"user guide wizards dwh wizard dwh wizard calendar transname overview dwh wizard calendar transname is a dwh wizard parameter that controls the calendar dimension name. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value dim_calendar custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_calendar_transname default value dim_calendar custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard calendar to dwh wizard dimname parameters previous dwh wizard calendar nextdwh wizard calendar from"} ,{"id":389871309022,"name":"DWH Wizard Dimname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-dimname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Dimname","description":"","searchText":"user guide wizards dwh wizard dwh wizard dimname overview dwh wizard dimname is a dwh wizard parameter that defines the template for generated dimensions. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value dim_{src_name} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_dimname default value dim_{src_name} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard calendar transname dwh wizard dwhtype parameters previous dwh wizard transname nextdwh wizard factname"} ,{"id":389871309035,"name":"DWH Wizard Dwhtype","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-dwhtype","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Dwhtype","description":"","searchText":"user guide wizards dwh wizard dwh wizard dwhtype overview dwh wizard dwhtype is a dwh wizard parameter that sets the dwh type used by the dwh wizard. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_dwhtype default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard dimname dwh wizard fact parameters previous dwh wizard link table name nextdwh wizard snapshot"} ,{"id":389871309041,"name":"DWH Wizard Fact","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-fact","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Fact","description":"","searchText":"user guide wizards dwh wizard dwh wizard fact overview dwh wizard fact is a dwh wizard parameter that sets the fact generation option of the dwh wizard. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_fact default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard dwhtype dwh wizard fact calendar parameters previous dwh wizard calendar to nextdwh wizard fact calendar"} ,{"id":389871309042,"name":"DWH Wizard Fact Calendar","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-fact-calendar","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Fact Calendar","description":"","searchText":"user guide wizards dwh wizard dwh wizard fact calendar overview dwh wizard fact calendar is a dwh wizard parameter that sets the calendar option for generated facts. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_fact_calendar default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard fact dwh wizard factname parameters previous dwh wizard fact nextdwh wizard vaultlinksat"} ,{"id":389871309023,"name":"DWH Wizard Factname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-factname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Factname","description":"","searchText":"user guide wizards dwh wizard dwh wizard factname overview dwh wizard factname is a dwh wizard parameter that defines the template for generated facts. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value fact_{src_name} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_factname default value fact_{src_name} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard fact calendar dwh wizard histpackagename parameters previous dwh wizard dimname nextdwh wizard tablesperpackage"} ,{"id":389871309020,"name":"DWH Wizard Histpackagename","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-histpackagename","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Histpackagename","description":"","searchText":"user guide wizards dwh wizard dwh wizard histpackagename overview dwh wizard histpackagename is a dwh wizard parameter that defines the template for generated historization package names. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {connector_name}, {nr}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value hist_{connector_name}{nr} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_histpackagename default value hist_{connector_name}{nr} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard factname dwh wizard hub packagename parameters previous dwh wizard imppackagename nextdwh wizard transname"} ,{"id":389871309025,"name":"DWH Wizard Hub Packagename","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-hub-packagename","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Hub Packagename","description":"","searchText":"user guide wizards dwh wizard dwh wizard hub packagename overview dwh wizard hub packagename is a dwh wizard parameter that defines the template for generated hub packages. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {connector_name}, {nr}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value hist_{connector_name}_hub{nr} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_hub_packagename default value hist_{connector_name}_hub{nr} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard histpackagename dwh wizard hub table name parameters previous dwh wizard tablesperpackage nextdwh wizard sat packagename"} ,{"id":389871309032,"name":"DWH Wizard Hub Table Name","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-hub-table-name","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Hub Table Name","description":"","searchText":"user guide wizards dwh wizard dwh wizard hub table name overview dwh wizard hub table name is a dwh wizard parameter that defines the template for generated hub tables. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_hub custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_hub_tablename default value {src_name}_hub custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard hub packagename dwh wizard hub transname parameters previous dwh wizard linksat transname nextdwh wizard sat table name"} ,{"id":389871309028,"name":"DWH Wizard Hub Transname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-hub-transname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Hub Transname","description":"","searchText":"user guide wizards dwh wizard dwh wizard hub transname overview dwh wizard hub transname is a dwh wizard parameter that defines the template for generated hub transformations. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_hub custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_hub_transname default value {src_name}_hub custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard hub table name dwh wizard imppackagename parameters previous dwh wizard link packagename nextdwh wizard sat transname"} ,{"id":389871309019,"name":"DWH Wizard Imppackagename","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-imppackagename","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Imppackagename","description":"","searchText":"user guide wizards dwh wizard dwh wizard imppackagename overview dwh wizard imppackagename is a dwh wizard parameter that defines the template for generated import package names. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {connector_name}, {nr}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value imp_{connector_name}{nr} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_imppackagename default value imp_{connector_name}{nr} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard hub transname dwh wizard link packagename parameters previous dwh wizard table name nextdwh wizard histpackagename"} ,{"id":389871309027,"name":"DWH Wizard Link Packagename","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-link-packagename","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Link Packagename","description":"","searchText":"user guide wizards dwh wizard dwh wizard link packagename overview dwh wizard link packagename is a dwh wizard parameter that defines the template for generated link packages. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {connector_name}, {nr}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value hist_{connector_name}_link{nr} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_link_packagename default value hist_{connector_name}_link{nr} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard imppackagename dwh wizard link table name parameters previous dwh wizard sat packagename nextdwh wizard hub transname"} ,{"id":389871309034,"name":"DWH Wizard Link Table Name","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-link-table-name","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Link Table Name","description":"","searchText":"user guide wizards dwh wizard dwh wizard link table name overview dwh wizard link table name is a dwh wizard parameter that defines the template for generated link tables. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_link custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_link_tablename default value {src_name}_link custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard link packagename dwh wizard link transname parameters previous dwh wizard sat table name nextdwh wizard dwhtype"} ,{"id":389871309030,"name":"DWH Wizard Link Transname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-link-transname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Link Transname","description":"","searchText":"user guide wizards dwh wizard dwh wizard link transname overview dwh wizard link transname is a dwh wizard parameter that defines the template for generated link transformations. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_link custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_link_transname default value {src_name}_link custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard link table name dwh wizard linksat transname parameters previous dwh wizard sat transname nextdwh wizard linksat transname"} ,{"id":389871309031,"name":"DWH Wizard Linksat Transname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-linksat-transname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Linksat Transname","description":"","searchText":"user guide wizards dwh wizard dwh wizard linksat transname overview dwh wizard linksat transname is a dwh wizard parameter that defines the template for generated linksat transformations. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {link_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {link_name}sat custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_linksat_transname default value {link_name}sat custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard link transname dwh wizard predefined transformations parameters previous dwh wizard link transname nextdwh wizard hub table name"} ,{"id":389872719058,"name":"DWH Wizard Predefined Transformations","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-predefined-transformations","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Predefined Transformations","description":"","searchText":"user guide wizards dwh wizard dwh wizard predefined transformations overview dwh wizard predefined transformations is a dwh wizard parameter that sets the predefined transformations option of the dwh wizard. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 2 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_predefined_transformations default value 2 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard linksat transname dwh wizard sap deltaq parameters previous dwh wizard vaultlinksat nextdwh wizard sap tables"} ,{"id":389872719060,"name":"DWH Wizard SAP Deltaq","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-sap-deltaq","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard SAP Deltaq","description":"","searchText":"user guide wizards dwh wizard dwh wizard sap deltaq overview dwh wizard sap deltaq is a dwh wizard parameter that controls search in sap deltaq. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 0 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_sap_deltaq default value 0 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard predefined transformations dwh wizard sap odp parameters previous dwh wizard sap tables nextdwh wizard sap odp"} ,{"id":389872719061,"name":"DWH Wizard SAP ODP","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-sap-odp","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard SAP ODP","description":"","searchText":"user guide wizards dwh wizard dwh wizard sap odp overview dwh wizard sap odp is a dwh wizard parameter that controls search in sap odp. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_sap_odp default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard sap deltaq dwh wizard sap tables parameters previous dwh wizard sap deltaq nexttransformations"} ,{"id":389872719059,"name":"DWH Wizard SAP Tables","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-sap-tables","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard SAP Tables","description":"","searchText":"user guide wizards dwh wizard dwh wizard sap tables overview dwh wizard sap tables is a dwh wizard parameter that controls the search in sap tables. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_sap_tables default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard sap odp dwh wizard sat packagename parameters previous dwh wizard predefined transformations nextdwh wizard sap deltaq"} ,{"id":389871309026,"name":"DWH Wizard SAT Packagename","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-sat-packagename","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard SAT Packagename","description":"","searchText":"user guide wizards dwh wizard dwh wizard sat packagename overview dwh wizard sat packagename is a dwh wizard parameter that defines the template for generated sat packages. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {connector_name}, {nr}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value hist_{connector_name}_sat{nr} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_sat_packagename default value hist_{connector_name}_sat{nr} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard sap tables dwh wizard sat table name parameters previous dwh wizard hub packagename nextdwh wizard link packagename"} ,{"id":389871309033,"name":"DWH Wizard SAT Table Name","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-sat-table-name","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard SAT Table Name","description":"","searchText":"user guide wizards dwh wizard dwh wizard sat table name overview dwh wizard sat table name is a dwh wizard parameter that defines the template for generated sat tables. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_sat custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_sat_tablename default value {src_name}_sat custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard sat packagename dwh wizard sat transname parameters previous dwh wizard hub table name nextdwh wizard link table name"} ,{"id":389871309029,"name":"DWH Wizard SAT Transname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-sat-transname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard SAT Transname","description":"","searchText":"user guide wizards dwh wizard dwh wizard sat transname overview dwh wizard sat transname is a dwh wizard parameter that defines the template for generated sat transformations. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_sat custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_sat_transname default value {src_name}_sat custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard sat table name dwh wizard snapshot parameters previous dwh wizard hub transname nextdwh wizard link transname"} ,{"id":389871309036,"name":"DWH Wizard Snapshot","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-snapshot","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Snapshot","description":"","searchText":"user guide wizards dwh wizard dwh wizard snapshot overview dwh wizard snapshot is a dwh wizard parameter that controls whether the wizard creates snapshot objects. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_snapshot default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard sat transname dwh wizard table name parameters previous dwh wizard dwhtype nextdwh wizard calendar"} ,{"id":389871309018,"name":"DWH Wizard Table Name","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-table-name","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Table Name","description":"","searchText":"user guide wizards dwh wizard dwh wizard table name overview dwh wizard table name is a dwh wizard parameter that defines the template for generated table names. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name} custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_tablename default value {src_name} custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard snapshot dwh wizard tablesperpackage parameters previous dwh wizard nextdwh wizard imppackagename"} ,{"id":389871309024,"name":"DWH Wizard Tablesperpackage","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-tablesperpackage","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Tablesperpackage","description":"","searchText":"user guide wizards dwh wizard dwh wizard tablesperpackage overview dwh wizard tablesperpackage is a dwh wizard parameter that controls the number of tables included in each generated package. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 10 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_tablesperpackage default value 10 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard table name dwh wizard transname parameters previous dwh wizard factname nextdwh wizard hub packagename"} ,{"id":389871309021,"name":"DWH Wizard Transname","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-transname","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Transname","description":"","searchText":"user guide wizards dwh wizard dwh wizard transname overview dwh wizard transname is a dwh wizard parameter that defines the template for generated transformations. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {src_name}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value {src_name}_v custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_transname default value {src_name}_v custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard tablesperpackage dwh wizard vaultlinksat parameters previous dwh wizard histpackagename nextdwh wizard dimname"} ,{"id":389872719057,"name":"DWH Wizard Vaultlinksat","type":"topic","path":"/docs/user-guide/wizards/dwh-wizard-function/parameters-dwh-wizard-dwh-wizard-vaultlinksat","breadcrumb":"User Guide › Wizards › DWH Wizard › DWH Wizard Vaultlinksat","description":"","searchText":"user guide wizards dwh wizard dwh wizard vaultlinksat overview dwh wizard vaultlinksat is a dwh wizard parameter that controls whether the wizard generates link sat objects in data vault models. function use this setting to keep dwh wizard object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the dwh wizard group and is used when analyticscreator applies dwh wizard object generation. setting value technical parameter name dwhwizard_vaultlinksat default value 1 custom value not set. parameter groups group dwh wizard wizard defaults wizard related topics dwh wizard dwh wizard transname parameters previous dwh wizard fact calendar nextdwh wizard predefined transformations"} ,{"id":384138863824,"name":"Snapshot transformation wizard","type":"subsection","path":"/docs/user-guide/wizards/snapshot-transformation-wizard","breadcrumb":"User Guide › Wizards › Snapshot transformation wizard","description":"","searchText":"user guide wizards snapshot transformation wizard to create a snapshot transformation, select \"add → snapshot dimension\" from the diagram context menu. this will open the snapshot transformation wizard. ⚠️ note: only one snapshot dimension can exist in the data warehouse. as shown in the image below: parameters schema the schema in which the snapshot transformation resides. name the name assigned to the snapshot transformation. stars the data mart stars where this snapshot transformation will be included."} ,{"id":384159908072,"name":"Import wizard","type":"subsection","path":"/docs/user-guide/wizards/import-wizard","breadcrumb":"User Guide › Wizards › Import wizard","description":"","searchText":"user guide wizards import wizard to start the import wizard, use the source context menu: import status indicators sources marked with a \"!\" icon indicate that they have not yet been imported. attempting to launch the import wizard on a source that has already been imported will result in an error. typical import wizard window there is a typical import wizard window, as shown in the image below: options: source: the source that should be imported. target schema: the schema of the import table. target name: the name of the import table. package: the name of the ssis package where the import will be done. you can select an existing import package or add a new package name. click finish to proceed. the import definition window will open, allowing the configuration of additional import attributes and parameters, as shown in the image below: post-import actions refer to the \"import package\" description for more details. after creating a new import, refresh the diagram to reflect the changes, as shown in the image below:"} ,{"id":384140346566,"name":"Source Wizard","type":"subsection","path":"/docs/user-guide/wizards/source-wizard","breadcrumb":"User Guide › Wizards › Source Wizard","description":"","searchText":"user guide wizards source wizard the source wizard is used to add new data sources to the repository. to launch the source wizard, right-click on the \"sources\" branch of a connector in the context menu and select \"add source.\" source wizard functionality the appearance and functionality of the source wizard will vary depending on the selected source type (table or query): table: when selecting table as the data source, the wizard provides options to configure and view available tables. configuring a table data source when selecting \"table\" as the data source in the source wizard, click the \"apply\" button to display the list of available source tables. optionally, you can enter a schema or table filter to refine the results. configuration options: retrieve relations: enables the retrieval of relationships for the selected source table, if available. sap description language: specifies the language for object descriptions when working with sap sources. sap deltaq attributes: for sap deltaq sources, additional deltaq-specific attributes must be defined. configuring a query as a data source when selecting \"query\" as the data source in the source wizard, follow these steps: define schema and name: specify the schema and name of the source for the repository. enter the query: provide the query in the query language supported by the data source. test the query: click the “test query” button to verify its validity and ensure it retrieves the expected results. complete the configuration: click the “finish” button to add the new source to the repository. the source definition window will open, allowing further modifications if needed."} ,{"id":384159908073,"name":"Time transformation wizard","type":"subsection","path":"/docs/user-guide/wizards/time-transformation-wizard","breadcrumb":"User Guide › Wizards › Time transformation wizard","description":"","searchText":"user guide wizards time transformation wizard to create a time transformation, select \"add → time dimension\" from the diagram context menu. as shown in the image below: the time transformation wizard will then open, allowing you to configure a new time transformation: parameters schema the schema in which the time transformation resides. name the name assigned to the time transformation. period (minutes) the interval (in minutes) used to generate time dimension records. time-to-id function the macro function that converts a datetime value into the key value for the time dimension. use case: convert datetime fields in fact transformations into time dimension members. stars the data mart stars where the time transformation will be included."} ,{"id":384136118500,"name":"Historization wizard","type":"subsection","path":"/docs/user-guide/wizards/historization-wizard","breadcrumb":"User Guide › Wizards › Historization wizard","description":"","searchText":"user guide wizards historization wizard the historization wizard is used to historize a table or transformation. to start the historization wizard, use the object context menu: \"add\" → \"historization\" in the diagram, as shown in the image below: alternatively, the object context menu in the navigation tree can be used, as shown in the image below: parameters there is a typical historization wizard window, as shown in the image below: source table: the table that should be historized. target schema: the schema of the historized table. target name: the name of the historized table. package: the name of the ssis package where the historization will be done. you can select an existing historization package or add a new package name. historizing type: you can select between ssis package and stored procedure. scd type: the user can select between different historization types: scd 0, scd 1, and scd 2. empty record behavior: defines what should happen in case of a missing source record. use vault id as pk: if you are using datavault or mixed architecture, the user can use hashkeys instead of business keys to perform historization. after clicking \"finish\", the historization will be generated, and the diagram will be updated automatically. then, the user can select the generated historization package and optionally change some package properties (see \"historizing package\")."} ,{"id":384157771974,"name":"Persisting wizard","type":"subsection","path":"/docs/user-guide/wizards/persisting-wizard","breadcrumb":"User Guide › Wizards › Persisting wizard","description":"","searchText":"user guide wizards persisting wizard the content of any regular or manual transformation can be stored in a table, typically to improve access speed for complex transformations. persisting the transformation is managed through an ssis package. to persist a transformation, the user should select \"add → persisting\" from the object context menu in the diagram. as shown in the image below: persisting wizard options as shown in the image below: transformation: the name of the transformation to persist. persist table: the name of the table where the transformation will be persisted. this table will be created in the same schema as the transformation. persist package: the name of the ssis package that manages the persistence process."} ,{"id":384138863823,"name":"Transformation wizard","type":"subsection","path":"/docs/user-guide/wizards/transformation-wizard","breadcrumb":"User Guide › Wizards › Transformation wizard","description":"","searchText":"user guide wizards transformation wizard the transformation wizard is used to create a new transformation. to start it, use the object context menu and select: \"add → transformation\" in the diagram. typical transformation wizard window supported transformation types regular transformations: described in tabular form, results in a generated view. manual transformations: hand-created views defined manually by the user. script transformations: based on sql scripts, often calling stored procedures. external transformations: created outside analyticscreator as ssis packages. main page parameters type: transformation type: dimension: fullhist, creates unknown member, joinhisttype: actual fact: snapshot, no unknown member, joinhisttype: historical_to other: fullhist, no unknown member, joinhisttype: historical_to manual, external, script: as named schema: schema name name: transformation name historizing type: fullhist snapshothist snapshot actualonly none main table: only for regular transformations create unknown member: adds surrogate id = 0 (for dimensions) persist transformation: save view to a table persist table: name of persist table persist package: ssis package name result table: for external/script types ssis package: for external/script types table selection page allows selection of additional tables. tables must be directly or indirectly related to the main table. parameters table joinhisttype none actual historical_from historical_to full join options: all n:1 direct related all direct related all n:1 related all related use hash keys if available parameter page configure additional parameters (for regular transformations only). fields: none all key fields all fields field names (if duplicated): field[n] table_field field name appearance: no changes upper case lower case key fields null to zero: replaces null with 0 use friendly names as column names stars page stars: data mart stars for the transformation default transformations: no defaults (facts) all defaults (dimensions) selected defaults dependent tables: manage dependent tables script page used for script transformations. enter the sql logic that defines the transformation. insert into imp.lastpayment(businessentityid, ratechangedate, rate) select ph.businessentityid, ph.ratechangedate, ph.rate from ( select businessentityid, max(ratechangedate) lastratechangedate from [imp].[employeepayhistory] group by businessentityid ) t inner join [imp].[employeepayhistory] ph on ph.businessentityid = t.businessentityid and ph.ratechangedate = t.lastratechangedate"} ,{"id":384140346567,"name":"Calendar transformation wizard","type":"subsection","path":"/docs/user-guide/wizards/calendar-transformation-wizard","breadcrumb":"User Guide › Wizards › Calendar transformation wizard","description":"","searchText":"user guide wizards calendar transformation wizard to create a calendar transformation, select \"add → calendar dimension\" from the diagram context menu. as shown in the image below: the calendar transformation wizard will open. typically, only one calendar transformation is required in the data warehouse. as shown in the image below: parameters schema: the schema of the calendar transformation. name: the name of the calendar transformation. date from: the start date for the calendar. date to: the end date for the calendar. date-to-id function: the macro name that transforms a datetime value into the key value for the calendar dimension. this macro is typically used in fact transformations to map datetime fields to calendar dimension members. stars: the data mart stars where the calendar transformation will be included."} , {"id":383461199043,"name":"Reference","type":"category","path":"/docs/reference","breadcrumb":"Reference","description":"","searchText":"reference this section provides structured technical reference documentation for analyticscreator. it is intended for users who need detailed information about the user interface, entity types, entities, and configuration parameters. use this section when you already know which part of the application you want to understand and need a precise description of available objects, categories, and options. reference sections entities reference for the concrete entities used in analyticscreator and their roles in modeling, generation, and execution. modeling objects execution-related entities generated object definitions open entities entity types reference for the structural categories used in analyticscreator, such as connectors, sources, tables, transformations, packages, scripts, and schemas. connector and source categories table and transformation types schema, package, and script types open entity types parameters reference for configuration parameters and settings that control generation, execution, historization, and other system behavior. object-specific parameters execution and generation settings configuration options open parameters user interface reference information for the analyticscreator user interface and its structural elements. navigation and ui components windows, dialogs, and views interaction patterns open user interface how to use this section the reference section is organized by topic area rather than by workflow. use user interface when you need help locating or understanding specific interface elements use entity types when you need to understand the available structural categories in analyticscreator use entities when you need reference information about concrete objects used in the model use parameters when you need detailed information about settings and configurable behavior when to use reference instead of other sections use getting started for onboarding and step-by-step implementation flow use tutorials for guided example walkthroughs use reference for precise technical definitions and detailed lookup documentation key takeaway the reference section provides structured technical lookup documentation for analyticscreator user interface elements, entity categories, concrete entities, and configuration parameters. nextuser interface"} ,{"id":383461259456,"name":"Entities","type":"section","path":"/docs/reference/entities","breadcrumb":"Reference › Entities","description":"","searchText":"reference entities entities are the concrete objects used in analyticscreator projects. they represent the connectors, sources, schemas, tables, transformations, packages, models, scripts, and supporting objects that make up a generated data warehouse model. use this section when you need to understand what a specific object represents and how it fits into modeling, generation, deployment, or execution. entity groups connector represents a connection definition for a source system or external data provider. stores connection-related metadata groups source objects under a provider supports metadata import and source access open connector source represents a source object that can be imported or used as input for generated warehouse logic. source tables, views, or queries input metadata for imports basis for staging structures open source schema represents a database schema used to organize generated objects into warehouse layers. staging and persistent layers transformation and core layers datamart structures open schema table represents a generated or managed table object in the warehouse model. import and historized tables persisting tables fact, dimension, and data vault tables open table transformation represents transformation logic that shapes, combines, or prepares data for downstream use. generated transformation logic manual or script-based logic datamart-facing transformations open transformation package represents an execution unit used to load, historize, persist, export, or orchestrate data processing. import and workflow execution historization and persisting execution script, export, and external processing open package deployment represents deployment configuration and output used to move generated artifacts into a target environment. deployment package settings generated artifact delivery environment-specific release behavior open deployment model represents an analytical model or model-related definition used for reporting-facing structures. model dimensions and facts consumption-oriented structures semantic or analytical organization open model layer represents a logical warehouse layer used to organize objects by architectural purpose. source-oriented layers core transformation layers consumption layers open layer filter represents reusable filtering logic that can restrict or shape selected data in a model. selection conditions reusable constraints model-specific filtering behavior open filter index represents an index definition used to support database performance and generated object behavior. index metadata generated database support performance-oriented configuration open index hierarchy represents hierarchical relationships used for analytical navigation and structured reporting. parent-child organization analytical drill paths dimension-related structure open hierarchy partition represents partition-related metadata for analytical or database structures that are split into segments. partition definitions olap or table segmentation processing and maintenance support open partition macro represents reusable logic or text that can be applied across generated sql or model definitions. reusable expressions shared generation logic template-style model support open macro sql script represents custom sql logic that can run during creation, workflow execution, deployment, or repository extension. creation and deployment scripts workflow-related scripts repository extension logic open sql script object script / object group represents script logic associated with analyticscreator objects or object-level processing. object-specific execution custom processing steps advanced automation behavior open object script object group represents a named group of objects used to organize, select, or process related model elements together. grouped model objects shared organization batch-oriented selection support open object group how to use this section use connector, source, schema, and table when reviewing source-to-warehouse structure use transformation, filter, macro, and sql script when reviewing generated or custom logic use package, deployment, and object script / object group when reviewing execution and release behavior use model, hierarchy, partition, and object group when reviewing analytical organization and object grouping key takeaway entities are the concrete building blocks of an analyticscreator project. they describe the objects that are modeled, generated, deployed, executed, and consumed across the data warehouse lifecycle. previous datamart nextlayer"} ,{"id":383509396692,"name":"Connector","type":"subsection","path":"/docs/reference/entities/entities-connector","breadcrumb":"Reference › Entities › Connector","description":"","searchText":"reference entities connector overview a connector represents a connection to an external data source system. it provides the connection context from which analyticscreator discovers, refreshes, previews, imports, or exports source structures. function use connectors to store the connection type and settings required to communicate with a source system. each connector can contain sources and source references. connector-specific settings vary according to the selected technology. types connector types determine which connection settings and source-discovery operations are available. type use database connector connects to database platforms such as sql server, oracle, or other supported relational systems. file connector connects to file-based sources such as delimited text or cloud files. spreadsheet connector connects to spreadsheet-based sources. application connector connects to systems such as sap or supported web services. attributes attributes define the configuration, behavior, and relationships of the connector entity. attribute applies to description name all connector types identifies the connector in the navigation tree and connector list. connector type all connector types determines the technology and connection settings used by the connector. connection settings connector-specific server, path, endpoint, authentication, or other settings required by the selected connector type. sources connector contents source objects discovered or defined through the connector. source references connector contents relationships maintained between sources exposed by the connector. how it is used in analyticscreator use case description discover sources read or refresh source metadata from the connected system. preview data preview supported source data before it is used in processing. support imports and exports provide the external endpoint used by import or export definitions. move connector definitions export or import connector structures when supported. relationships related entity relationship source a connector contains one or more source entities. source reference a connector can contain relationships between its sources. import imports read source data through a connector. export exports can write to a source endpoint through a connector. where to configure configure or review this entity from the matching analyticscreator user-interface area. connector page connectors list connectors navigation tree related topics source entity package entity table entity previous schema next source"} ,{"id":383509396699,"name":"Deployment","type":"subsection","path":"/docs/reference/entities/entities-deployment","breadcrumb":"Reference › Entities › Deployment","description":"","searchText":"reference entities deployment overview a deployment is an analyticscreator object that defines a deployable or runnable set of generated package work. it provides the configuration used to prepare and execute selected packages outside the design editor. function use deployments to select package content for generation or execution and to maintain the deployment definition that can be edited or run later. the exact generation and run settings depend on the deployment target and the packages included in the deployment. attributes attributes define the configuration, behavior, and relationships of the deployment entity. attribute applies to description name deployment identifies the deployment in the list and navigation tree. packages deployment packages included in the deployment definition. selection and order deployment packages controls which packages participate and how they are handled by the deployment. generation settings deployment target-specific settings used when deployment output is generated. run settings runnable deployment settings used when the deployment is executed. how it is used in analyticscreator use case description collect packages define which packages belong to one deployable unit. generate deployment output prepare target-specific package artifacts. run a deployment execute a saved deployment definition. reuse deployment definitions edit and rerun an existing package selection. relationships related entity relationship package a deployment contains one or more packages. sql script pre- and post-deployment scripts can run around deployment processing. repository deployment generation uses the current repository design. where to configure configure or review this entity from the matching analyticscreator user-interface area. deployments list deployments navigation tree related topics package entity sql script entity transformation entity previous object script next object group"} ,{"id":389871310018,"name":"DACPAC Model Storage Type","type":"topic","path":"/docs/reference/entities/entities-deployment/parameters-deployment-dacpac-model-storage-type","breadcrumb":"Reference › Entities › Deployment › DACPAC Model Storage Type","description":"","searchText":"reference entities deployment dacpac model storage type overview dacpac model storage type is a deployment parameter that controls the dacpac model storage type: 0 - file, 1 - memory. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name dacpac_model_storage_type default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment deployment create subdirectory parameters previous deployment create subdirectory nextdwh metadata in extended properties"} ,{"id":388515715281,"name":"Deployment Create Subdirectory","type":"topic","path":"/docs/reference/entities/entities-deployment/parameters-deployment-deployment-create-subdirectory","breadcrumb":"Reference › Entities › Deployment › Deployment Create Subdirectory","description":"","searchText":"reference entities deployment deployment create subdirectory overview deployment create subdirectory is a deployment parameter that controls whether analyticscreator creates a subdirectory for every created deployment package. 0-no (all files in output directory will be deleted), 1-yes. default - 1. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name deployment_create_subdirectory default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment dacpac model storage type deployment do not drop object types parameters previous deployment do not drop object types nextdacpac model storage type"} ,{"id":389871310017,"name":"Deployment Do Not Drop Object Types","type":"topic","path":"/docs/reference/entities/entities-deployment/parameters-deployment-deployment-do-not-drop-object-types","breadcrumb":"Reference › Entities › Deployment › Deployment Do Not Drop Object Types","description":"","searchText":"reference entities deployment deployment do not drop object types overview deployment do not drop object types is a deployment parameter that controls the comma-separated list of object types (see the description of sqlpackage.exe). function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value aggregates,applicationroles,assemblies,asymmetrickeys,brokerpriorities,certificates,contracts,databaseroles,databasetriggers,fulltextcatalogs,fulltextstoplists,messagetypes,partitionfunctions,partitionschemes,permissions,queues,remoteservicebindings,rolemembership,rules,searchpropertylists,sequences,services,signatures,symmetrickeys,synonyms,userdefineddatatypes,userdefinedtabletypes,clruserdefinedtypes,users,xmlschemacollections,audits,credentials,cryptographicproviders,databaseauditspecifications,endpoints,errormessages,eventnotifications,eventsessions,linkedserverlogins,linkedservers,logins,routes,serverauditspecifications,serverrolemembership,serverroles,servertriggers custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name deployment_do_not_drop_object_types default value aggregates,applicationroles,assemblies,asymmetrickeys,brokerpriorities,certificates,contracts,databaseroles,databasetriggers,fulltextcatalogs,fulltextstoplists,messagetypes,partitionfunctions,partitionschemes,permissions,queues,remoteservicebindings,rolemembership,rules,searchpropertylists,sequences,services,signatures,symmetrickeys,synonyms,userdefineddatatypes,userdefinedtabletypes,clruserdefinedtypes,users,xmlschemacollections,audits,credentials,cryptographicproviders,databaseauditspecifications,endpoints,errormessages,eventnotifications,eventsessions,linkedserverlogins,linkedservers,logins,routes,serverauditspecifications,serverrolemembership,serverroles,servertriggers custom value not set. parameter groups group deployment database options storage related topics deployment deployment create subdirectory dwh metadata in extended properties parameters previous index compression type nextdeployment create subdirectory"} ,{"id":388515715283,"name":"DWH Metadata In Extended Properties","type":"topic","path":"/docs/reference/entities/entities-deployment/parameters-deployment-dwh-metadata-in-extended-properties","breadcrumb":"Reference › Entities › Deployment › DWH Metadata In Extended Properties","description":"","searchText":"reference entities deployment dwh metadata in extended properties overview dwh metadata in extended properties is a deployment parameter that controls whether metadata is stored as extended properties of database objects. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name dwh_metadata_in_extended_properties default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment deployment do not drop object types index compression type parameters previous dacpac model storage type nexthistorization"} ,{"id":389871310016,"name":"Index Compression Type","type":"topic","path":"/docs/reference/entities/entities-deployment/parameters-deployment-index-compression-type","breadcrumb":"Reference › Entities › Deployment › Index Compression Type","description":"","searchText":"reference entities deployment index compression type overview index compression type is a deployment parameter that controls the default index compression type when the table compression type is none or columnstore index (otherwise indexes will have the same compression type as tables): 1-none, 2-page, 3-row. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name index_compression_type default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment dwh metadata in extended properties table compression type parameters previous table compression type nextdeployment do not drop object types"} ,{"id":388515715288,"name":"Table Compression Type","type":"topic","path":"/docs/reference/entities/entities-deployment/parameters-deployment-table-compression-type","breadcrumb":"Reference › Entities › Deployment › Table Compression Type","description":"","searchText":"reference entities deployment table compression type overview table compression type is a deployment parameter that controls the default table compression type: 1 - none, 2 - page, 3 - row, 4 - columnstore index. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name table_compression_type default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment index compression type parameters previous deployment nextindex compression type"} ,{"id":383509396701,"name":"Filter","type":"subsection","path":"/docs/reference/entities/entities-filter","breadcrumb":"Reference › Entities › Filter","description":"","searchText":"reference entities filter overview a filter is an analyticscreator object that stores a reusable set of repository objects for focused diagram work. it captures the current object selection so that the same diagram scope can be applied again later. function use filters to save the current non-empty diagram filter under a name and to reapply that object set from the navigation tree. a filter does not define row-level sql filtering. it controls which analyticscreator objects are shown in the flow diagram. attributes attributes define the configuration, behavior, and relationships of the filter entity. attribute applies to description name filter required name used to identify the saved filter. objects filter repository objects included in the saved filter. how it is used in analyticscreator use case description save diagram scope store the current object selection for later reuse. focus architecture work apply a filter to show only the selected objects in the diagram. reuse object selections switch between saved object sets without rebuilding the selection manually. relationships related entity relationship repository object a filter contains references to selected repository objects. flow diagram applying the filter refreshes the diagram with the saved object set. object group both can focus work on object collections, but groups also support membership management and locking. where to configure configure or review this entity from the matching analyticscreator user-interface area. filters navigation tree flow diagram related topics object group entity table entity transformation entity previous object group next model"} ,{"id":383509396696,"name":"Hierarchy","type":"subsection","path":"/docs/reference/entities/entities-hierarchy","breadcrumb":"Reference › Entities › Hierarchy","description":"","searchText":"reference entities hierarchy overview a hierarchy is an analyticscreator analytical object that organizes table columns into ordered levels. it provides a reusable navigation path for olap and data mart analysis. function use hierarchies to define how users move from higher-level values to more detailed values in analytical output. each hierarchy belongs to one analytical table and contains an ordered list of hierarchy levels. attributes attributes define the configuration, behavior, and relationships of the hierarchy entity. attribute applies to description schema hierarchy schema that contains the analytical table. table hierarchy analytical table that provides the hierarchy columns. name hierarchy required hierarchy name. description hierarchy documents the purpose of the hierarchy. column hierarchy level table column used for the level. sequence number hierarchy level controls the level order. level name hierarchy level business-facing name of the level. level description hierarchy level documents the meaning of the level. how it is used in analyticscreator use case description create drill paths define ordered levels such as year, month, and day. standardize analytical navigation reuse the same level order across analytical output. document semantic structure assign business names and descriptions to hierarchy levels. relationships related entity relationship table a hierarchy belongs to one analytical table. column a hierarchy contains ordered table columns. schema the owning table determines the hierarchy schema context. partition hierarchies and partitions can both be defined for analytical tables. where to configure configure or review this entity from the matching analyticscreator user-interface area. olap hierarchy page hierarchies list hierarchies navigation tree related topics table entity partition entity model entity previous partition next macro"} ,{"id":383509340370,"name":"Index","type":"subsection","path":"/docs/reference/entities/entities-index","breadcrumb":"Reference › Entities › Index","description":"","searchText":"reference entities index overview an index is an analyticscreator design object that defines an index for a warehouse table. it combines index behavior with an ordered set of table columns. function use indexes to define primary-key, clustered, unique, columnstore, and supporting index structures for physical tables. index settings are validated against the owning table, including restrictions on multiple clustered or primary-key indexes and incompatible columnstore combinations. types index behavior is controlled by flags that can be combined where the database rules permit. type use standard index defines one or more ordered key columns. unique index requires unique key values. clustered index defines the table's clustered storage order. primary-key index implements the table's primary key. columnstore index uses columnstore storage for supported analytical scenarios. attributes attributes define the configuration, behavior, and relationships of the index entity. attribute applies to description table all indexes table that owns the index. name all indexes required index name. description all indexes documents the purpose of the index. compression type supported indexes compression option used when the index is generated. unique optional behavior requires unique key values. clustered optional behavior marks the index as clustered. primary key optional behavior marks the index as the table primary-key index. columnstore optional behavior marks the index as a columnstore index. columns all indexes ordered table columns included in the index. sort and include settings index columns descending direction and include-only behavior for each column. how it is used in analyticscreator use case description define table keys implement the primary key or a supporting unique key. improve generated database performance create ordered or included columns that support expected access patterns. support analytical storage define columnstore indexing where applicable. keep index metadata in the model generate index definitions consistently with the table design. relationships related entity relationship table an index belongs to one table. column an index contains one or more table columns. schema the owning table determines the schema in which the index is generated. where to configure configure or review this entity from the matching analyticscreator user-interface area. index page indexes list indexes navigation tree related topics table entity schema entity previous package next partition"} ,{"id":383509340365,"name":"Layer","type":"subsection","path":"/docs/reference/entities/entities-layer","breadcrumb":"Reference › Entities › Layer","description":"","searchText":"reference entities layer overview a layer is an analyticscreator design object that organizes schemas into an ordered logical stage of the data warehouse. layers help separate source-facing, integration, historization, transformation, and data mart structures without exposing internal repository storage. function use layers to structure the warehouse model and to control where schemas and their objects appear in the navigation tree. a layer contains one or more schemas. its sequence determines the order in which layers are presented and supports a clear progression through the warehouse architecture. attributes attributes define the configuration, behavior, and relationships of the layer entity. attribute applies to description name layer identifies the layer in the navigation tree and layer list. sequence layer controls the display order of the layer relative to other layers. schemas layer contents schemas assigned to the layer and displayed beneath it in the navigation tree. how it is used in analyticscreator use case description organize warehouse stages separate source, integration, historization, transformation, and data mart areas into understandable stages. structure navigation provide the top-level container under which schemas are browsed. support consistent modelling keep objects with a similar architectural purpose together. relationships related entity relationship schema a layer contains one or more schemas. table tables belong to schemas that are contained by a layer. transformation transformations belong to schemas that are contained by a layer. where to configure configure or review this entity from the matching analyticscreator user-interface area. layers navigation tree dwh toolbar related topics schema entity table entity transformation entity previous entities next schema"} ,{"id":383509340372,"name":"Macro","type":"subsection","path":"/docs/reference/entities/entities-macro","breadcrumb":"Reference › Entities › Macro","description":"","searchText":"reference entities macro overview a macro is an analyticscreator design object that stores reusable statement logic. other objects can call a macro instead of repeating the same expression, filter, or statement. function use macros to centralize reusable logic and to keep transformation or table expressions consistent. a macro has a language, an optional referenced-table context, and a statement body. macros can also call other macros. attributes attributes define the configuration, behavior, and relationships of the macro entity. attribute applies to description name macro required name used when the macro is referenced. description macro documents the purpose of the macro. language macro determines how the statement is interpreted. referenced table contextual macro optional table context used by the macro. statement macro reusable statement body. how it is used in analyticscreator use case description reuse expressions call the same logic from multiple transformation columns, filters, or table expressions. centralize changes update one macro to affect direct and indirect references. provide table-aware logic bind a macro to a table context when its logic depends on table metadata. trace usage review transformations, tables, and macros that reference a macro. relationships related entity relationship transformation transformation columns, filters, table settings, or subselects can reference macros. table calculated table columns can reference macros. macro a macro can reference another macro directly or indirectly. referenced table a macro can be bound to an optional table context. where to configure configure or review this entity from the matching analyticscreator user-interface area. macro page macros list macros navigation tree related topics transformation entity table entity sql script entity previous hierarchy next sql script"} ,{"id":383509396702,"name":"Model","type":"subsection","path":"/docs/reference/entities/entities-model","breadcrumb":"Reference › Entities › Model","description":"","searchText":"reference entities model overview a model is an analyticscreator data mart design object that contains dimensions and facts. it provides a business-oriented structure from which related transformation objects can be created. function use models to describe dimensional structures independently from the detailed transformation implementation. a model contains model dimensions and model facts. analyticscreator can create transformation objects from the model or add eligible model transformations to an existing model. attributes attributes define the configuration, behavior, and relationships of the model entity. attribute applies to description name model identifies the model in the list and navigation tree. dimensions model contents model dimension definitions contained by the model. facts model contents model fact definitions contained by the model. how it is used in analyticscreator use case description design a data mart define dimensions, facts, measures, attributes, and relationships in a business-oriented structure. create transformations generate dimension- and fact-oriented transformations from the model. build a model from transformation logic create a new model or add an eligible model transformation to an existing model. move model definitions import or export model structures when supported. relationships related entity relationship model dimension a model contains one or more model dimensions. model fact a model contains one or more model facts. transformation model transformations can create or update model content, and models can generate transformations. star or galaxy model creation can use eligible star-oriented transformation structures. where to configure configure or review this entity from the matching analyticscreator user-interface area. models list models navigation tree model dimension page model fact page related topics transformation entity table entity hierarchy entity previous filter"} ,{"id":383509396700,"name":"Object group","type":"subsection","path":"/docs/reference/entities/entities-object-group","breadcrumb":"Reference › Entities › Object group","description":"","searchText":"reference entities object group overview an object group is an analyticscreator object that groups repository objects under a reusable name. groups support organization, focused diagram work, locking, and workflow-related handling. function use object groups to maintain a named collection of repository objects. a group can be selected as the active group filter, its objects can be listed, and the group can be locked to coordinate repository work. types the workflow flag distinguishes general groups from groups intended for workflow-related use. type use standard group groups objects for organization, filtering, and locking. workflow group marks a group for workflow-related handling when that option is configured. attributes attributes define the configuration, behavior, and relationships of the object group entity. attribute applies to description name all groups identifies the group in the navigation tree and group selector. objects all groups repository objects assigned to the group. locked by lockable groups login that currently owns the group lock. workflow flag optional group behavior marks the group for workflow-related handling. how it is used in analyticscreator use case description organize repository objects keep a reusable collection of related objects. filter the diagram select the group to focus the diagram on its objects. coordinate editing lock a group to prevent conflicting work and unlock it when complete. review membership open the group-object list to inspect assigned objects. relationships related entity relationship repository object a group contains selected repository objects. filter groups and filters can both focus diagram content, but they are maintained differently. workflow a group can carry a workflow-related flag. user/login the locked by value identifies the current lock owner. where to configure configure or review this entity from the matching analyticscreator user-interface area. object groups dialog object group content list groups navigation tree related topics filter entity package entity model entity previous deployment next filter"} ,{"id":383509340375,"name":"Object script","type":"subsection","path":"/docs/reference/entities/entities-object-script","breadcrumb":"Reference › Entities › Object script","description":"","searchText":"reference entities object script overview an object script is an analyticscreator object that stores a parameterized script for a supported repository object type or as a table-independent script. object-scoped scripts can be listed, added, and run from supported object context menus. function use object scripts to perform reusable repository actions against selected analyticscreator objects. an object-scoped script receives the selected object id as its first runtime value. additional user-defined parameters can provide optional default values. types the object setting determines whether a script is object-scoped or table-independent. type use object-scoped script runs for a supported repository object type and receives the selected object id. table-independent script is not bound to a repository object type. attributes attributes define the configuration, behavior, and relationships of the object script entity. attribute applies to description name all object scripts required script name. description all object scripts documents the purpose of the script. object scope object-scoped scripts supported repository object type associated with the script. parameters all object scripts ordered user-defined parameters accepted by the script. default values optional parameters values used when checking or running the script. statement all object scripts script body executed by the object script. how it is used in analyticscreator use case description run repository maintenance actions execute a reusable statement for a selected repository object. provide object context automatically pass the selected object id as the first runtime value. expose reusable context-menu actions list, add, and run scripts from supported object context menus. validate before saving check the statement with the available parameter values. relationships related entity relationship repository object an object-scoped script is associated with a supported object type. object script parameter an object script contains ordered parameters. navigation tree scripts are grouped under all scripts, table-independent scripts, or object-type branches. where to configure configure or review this entity from the matching analyticscreator user-interface area. object script page object scripts list object scripts navigation tree related topics sql script entity macro entity object group entity previous sql script next deployment"} ,{"id":383509396694,"name":"Package","type":"subsection","path":"/docs/reference/entities/entities-package","breadcrumb":"Reference › Entities › Package","description":"","searchText":"reference entities package overview a package is an analyticscreator processing object that groups executable work. packages organize imports, historizations, persistings, workflows, external transformations, scripts, and exports into units that can be generated or run. function use packages to collect related processing steps and control their execution context. package content and settings vary by package type. workflow packages coordinate child packages, while import, historization, persisting, export, external, and script packages contain or launch type-specific work. types package type determines the content that can be assigned and the execution settings that are available. type use import package groups source-to-table import definitions. historization package groups table historization definitions. persisting package groups transformation-to-table persisting definitions. workflow package coordinates child packages and retry or error behavior. external package groups external transformation processing. script package groups script-launching transformation work. export package groups table-to-source export definitions. attributes attributes define the configuration, behavior, and relationships of the package entity. attribute applies to description name all package types identifies the package in lists and the navigation tree. package type all package types determines the package category and available content. description all package types documents the purpose of the package. manually created applicable package types indicates that the package is maintained manually. externally launched applicable non-workflow packages marks a package that is started outside the normal package sequence. content all package types imports, historizations, persistings, transformations, exports, or child packages assigned to the package. workflow settings workflow packages include, interrupt, retry count, and retry interval settings for child packages. dependencies applicable packages detected and manually selected package dependencies. how it is used in analyticscreator use case description group executable work collect related processing definitions under one package. generate processing output provide the unit used when processing packages are generated. coordinate workflows run child packages with inclusion, error, and retry settings. control execution order use detected and manual dependencies to influence sequencing. organize navigation present package contents under type-specific branches in the navigation tree. relationships related entity relationship import an import package contains import definitions. historization a historization package contains historization definitions. transformation persisting, external, script, and workflow packages can reference transformations. table package content can read from, write to, historize, persist, or export tables. deployment a deployment can include packages. sql script workflow and deployment lifecycle scripts can run around package processing. where to configure configure or review this entity from the matching analyticscreator user-interface area. package page packages list packages navigation tree related topics transformation entity deployment entity sql script entity table entity previous transformation next index"} ,{"id":383509396695,"name":"Partition","type":"subsection","path":"/docs/reference/entities/entities-partition","breadcrumb":"Reference › Entities › Partition","description":"","searchText":"reference entities partition overview a partition is an analyticscreator analytical object that divides an olap table into separately defined data segments. partitions are associated with analytical tables and are used to organize or process subsets of their data. function use partitions to define how an analytical table is split into meaningful processing units. a partition definition identifies the owning table and the selection logic or boundaries that determine which rows belong to the partition. attributes attributes define the configuration, behavior, and relationships of the partition entity. attribute applies to description name partition identifies the partition under its analytical table. table partition analytical table that owns the partition. description partition documents the business or processing purpose of the partition. selection definition partition filter, statement, or boundary logic used to identify the partition's rows. processing context partition settings used when the partition is generated or processed. how it is used in analyticscreator use case description split large analytical tables separate data into smaller processing units. align processing with business slices create partitions for time periods, regions, or other meaningful segments. control olap processing process or rebuild defined subsets rather than treating all data as one segment. relationships related entity relationship table a partition belongs to an analytical table. column partition logic can use columns from the owning table. deployment generated analytical output can include partition definitions. where to configure configure or review this entity from the matching analyticscreator user-interface area. olap partition page partitions list partitions navigation tree related topics table entity hierarchy entity deployment entity previous index next hierarchy"} ,{"id":383509340366,"name":"Schema","type":"subsection","path":"/docs/reference/entities/entities-schema","breadcrumb":"Reference › Entities › Schema","description":"","searchText":"reference entities schema overview a schema is an analyticscreator design object that provides a namespace and configuration context inside a layer. it groups tables, transformations, references, and package-related definitions that belong to the same warehouse area. function use schemas to organize generated database objects and to define the context in which table and transformation entities are maintained. the schema type influences which branches and actions are available, such as imports, historizations, exports, transformations, tables, and references. attributes attributes define the configuration, behavior, and relationships of the schema entity. attribute applies to description name schema technical schema name used for generated or maintained warehouse objects. layer schema layer that contains the schema. schema type schema controls the schema context and the object branches available beneath it. tables schema contents tables maintained in the schema. transformations schema contents transformations maintained in the schema. how it is used in analyticscreator use case description define a database namespace keep generated warehouse objects under a controlled schema name. group related objects organize tables, transformations, references, and processing definitions by purpose. drive available actions expose import, historization, export, transformation, table, or reference actions according to context. relationships related entity relationship layer a schema belongs to one layer. table a schema contains tables. transformation a schema contains transformations. table reference references can be listed and maintained for tables in a schema. package content import, historization, and export definitions can be associated with schema objects. where to configure configure or review this entity from the matching analyticscreator user-interface area. schemas list layers navigation tree dwh toolbar related topics layer entity table entity transformation entity previous layer next connector"} ,{"id":383509340368,"name":"Source","type":"subsection","path":"/docs/reference/entities/entities-source","breadcrumb":"Reference › Entities › Source","description":"","searchText":"reference entities source overview a source represents an external object that can provide data to analyticscreator through a connector. a source can describe a table, view, query, file, sap delta queue, or another connector-specific object. function use source entities to maintain source structure, columns, constraints, references, grouping, and connector-specific query or path information. sources can be refreshed from the external system and then used as inputs for imports or transformations. types the source type determines how analyticscreator reads metadata and previews or processes source data. type use table source represents a physical table exposed by the connector. view source represents a source-system view. query source uses a stored query or connector-specific statement as the source. sap delta queue represents a supported sap delta queue source. file or external source represents a connector-specific file, sheet, endpoint, or external object. attributes attributes define the configuration, behavior, and relationships of the source entity. attribute applies to description name all source types technical source name displayed under its connector. source schema or group applicable sources organizes the source within the external system or navigation tree. source type all source types identifies whether the source is a table, view, query, delta queue, file, or another connector-specific object. query or path query and file sources defines the statement, path, or endpoint used to read the source. columns all structured sources column metadata read from or defined for the source. constraints applicable structured sources source constraints discovered or maintained for the source. references applicable structured sources relationships between the source and other source entities. how it is used in analyticscreator use case description read source metadata define a source manually or read its structure from the connected system. refresh structure detect and apply changes to source columns and metadata. preview source data inspect supported source data before building processing logic. create imports use the source as the input side of an import definition. build transformations use the source as an input object in transformation logic. relationships related entity relationship connector a source belongs to one connector. source column a source contains source columns. source constraint a source can contain discovered constraints. source reference a source can participate in source-to-source references. table an import can map a source to a warehouse table. transformation a source can be used as a transformation input. where to configure configure or review this entity from the matching analyticscreator user-interface area. source page sources list sources navigation tree related topics connector entity table entity transformation entity package entity previous connector next table"} ,{"id":383509340373,"name":"SQL Script","type":"subsection","path":"/docs/reference/entities/entities-sql-script","breadcrumb":"Reference › Entities › SQL Script","description":"","searchText":"reference entities sql script overview a sql script is an analyticscreator object that stores sql for a defined repository, deployment, or workflow lifecycle stage. scripts are ordered within their type and can be enabled or disabled as required. function use sql scripts to run controlled custom sql before or after generation, deployment, or workflow processing. repository extension scripts are used to apply custom repository-side logic when that lifecycle action is run. types script type determines the lifecycle point at which the sql is applied. type use pre-creation script runs before object creation. post-creation script runs after object creation. pre-deployment script runs before deployment processing. post-deployment script runs after deployment processing. pre-workflow script runs before workflow processing. post-workflow script runs after workflow processing. repository extension script applies custom repository extension logic. attributes attributes define the configuration, behavior, and relationships of the sql script entity. attribute applies to description name all script types identifies the script. script type all script types determines when the script is executed. sequence number all script types controls execution order within the script type. inactive all script types prevents the script from running when selected. statement all script types sql body executed at the configured lifecycle stage. how it is used in analyticscreator use case description extend generated processing run custom sql around creation or deployment. prepare workflow execution run setup sql before workflow packages. finalize workflow execution run cleanup or follow-up sql after workflow packages. apply repository extensions execute custom repository-side scripts when requested. move script definitions import or export script structures when supported. relationships related entity relationship package workflow scripts run around workflow package processing. deployment deployment scripts run before or after deployment processing. repository repository extension scripts apply custom repository logic. macro script statements can use reusable logic where supported by the statement context. where to configure configure or review this entity from the matching analyticscreator user-interface area. sql script page scripts list scripts navigation tree related topics package entity deployment entity object script entity previous macro next object script"} ,{"id":383509340369,"name":"Table","type":"subsection","path":"/docs/reference/entities/entities-table","breadcrumb":"Reference › Entities › Table","description":"","searchText":"reference entities table overview a table is an analyticscreator design object that describes a warehouse table, view, dimension, fact, or related generated structure. it combines technical column definitions with business metadata, references, indexes, historization or persistence relationships, and semantic settings. function use table entities to define the physical and semantic structure of warehouse objects. a table can be created directly, produced by an import or transformation, linked to historization or persisting logic, and exposed to analytical models. types table roles determine which relationships, editor options, and analytical features are available. type use physical table represents a generated or maintained warehouse table. view represents a generated or maintained view. historized or persisted table stores historical or persisted results produced by processing logic. dimension table represents an analytical dimension structure. fact table represents an analytical fact structure. attributes attributes define the configuration, behavior, and relationships of the table entity. attribute applies to description name all table roles technical table name. schema all table roles schema that contains the table. table type all table roles determines the role and available behavior of the table. friendly name business-facing tables business name used in semantic or documentation contexts. description all table roles documents the purpose of the table. compression physical tables compression option used when the table is generated. columns all structured tables physical and semantic column definitions. primary key and indexes physical tables key and index definitions used by the table. references related tables relationships to other table entities. analytical metadata dimensions and facts friendly names, display folders, measures, hierarchies, partitions, and related semantic settings. how it is used in analyticscreator use case description define warehouse storage describe the columns, keys, indexes, and generation settings of a warehouse table. receive imported data act as the target of an import definition. store transformation results represent a transformation output or persisted result. support historization participate in source-to-history relationships. provide analytical structures serve as a dimension, fact, hierarchy owner, or partition owner. relationships related entity relationship schema a table belongs to one schema. column a table contains physical or calculated columns. index a physical table can contain indexes. table reference a table can reference or be referenced by another table. transformation a table can be an input, output, or persisted result of a transformation. package imports, historizations, persistings, and exports connect package work to tables. hierarchy analytical tables can own hierarchies. partition analytical tables can own olap partitions. where to configure configure or review this entity from the matching analyticscreator user-interface area. table page tables list tables navigation tree related topics schema entity transformation entity index entity hierarchy entity previous source next transformation"} ,{"id":383509396693,"name":"Transformation","type":"subsection","path":"/docs/reference/entities/entities-transformation","breadcrumb":"Reference › Entities › Transformation","description":"","searchText":"reference entities transformation overview a transformation is an analyticscreator design object that defines how data is selected, joined, calculated, filtered, or prepared for generated output. it is a configurable class of object with properties and relationships. it is not the internal repository table used to store transformation records. function use transformations to create reusable data logic inside a schema. different transformation types expose different attributes. depending on type, a transformation can use input tables or sources, sql or code statements, calculated columns, filters, references, persisted output, model settings, external processing, or union logic. types transformation type determines the editor sections, attributes, generated output, and available follow-up actions. type use standard transformation defines logic through input objects, references, filters, and calculated output columns. sql or code-based transformation defines transformation behavior through a maintained statement or view definition. model transformation represents dimension- or fact-oriented logic that can be used to create or update a model. external transformation represents transformation work handled outside the standard generated sql flow. file-to-table transformation loads or prepares file-based data for table-oriented output. union transformation combines compatible input structures into one output. attributes attributes define the configuration, behavior, and relationships of the transformation entity. attribute applies to description name all transformation types technical transformation name. schema all transformation types schema that contains the transformation. transformation type all transformation types controls the available settings and generated behavior. friendly name business-facing output business name used when the transformation output is exposed. description all transformation types documents the purpose of the transformation. input objects input-based types sources, tables, or transformations used as inputs. references and joins relational types relationships used to connect input objects. columns and expressions output-producing types output columns, calculations, defaults, and semantic metadata. filter filter-capable types limits the rows included in the output. output or persisted table materialized types table or view generated or maintained from the transformation. how it is used in analyticscreator use case description create generated output define a view, table-oriented result, or reusable transformation structure. prepare data for persisting provide transformation output that can be stored physically by a persisting package. create or update models use model transformations to create model dimensions and facts. reuse logic reference macros, filters, input tables, and table references. duplicate and adapt logic copy supported transformations and then adjust their inputs or output. relationships related entity relationship schema a transformation belongs to one schema. source a transformation can read from source entities. table a transformation can read from or generate table entities. table reference a transformation can use table relationships. macro a transformation can call reusable macro logic. package persisting, external, script, or workflow packages can include transformation-related work. model model transformations can create or update model dimensions and facts. where to configure configure or review this entity from the matching analyticscreator user-interface area. transformation page transformations list transformations navigation tree related topics table entity package entity macro entity model entity previous table next package"} ,{"id":383461259455,"name":"Entity types","type":"section","path":"/docs/reference/entity-types","breadcrumb":"Reference › Entity types","description":"","searchText":"reference entity types entity types define the structural categories used by analyticscreator to classify connectors, sources, tables, transformations, packages, scripts, schemas, and historization behavior. use this section when you need to understand which type controls a modeling object, execution unit, or generated warehouse structure. entity type groups connector types define how analyticscreator connects to source systems and external data providers. database connectors file and cloud storage connectors service and enterprise system connectors open connector types join historization types define how joins behave when historized data and validity periods are involved. current-state joins full historical joins valid-from and valid-to alignment open join historization types package types define the execution units used for loading, historization, persisting, workflows, scripts, exports, and external processing. import and workflow packages historization and persisting packages script, export, and external packages open package types schema types define the warehouse layers used to organize staging, transformation, core, and reporting-ready structures. staging and persisted staging transformation and core layers datamart layer open schema types source types define how source objects are read and how source data enters the loading process. table and view sources query-based sources sap source patterns open source types sql script types define when custom sql logic runs during creation, workflow execution, deployment, or repository extension. pre and post creation pre and post workflow pre and post deployment open sql script types table types define the role a table plays in staging, historization, persistence, dimensional modeling, or data vault modeling. import and historized tables dimension and fact tables data vault hubs, links, and satellites open table types transformation historization types transformation historization types define how a transformation handles time-dependent data and historical states. open transformation historization types transformation types define how transformation logic is generated, maintained, or executed. generated transformations manual and script-based logic datamart and union transformations open transformation types how to use this section use connector types and source types when working with source system integration use table types, schema types, and transformation types when designing warehouse structures use join historization types when historized data must be joined with validity-aware behavior use package types and sql script types when reviewing execution and lifecycle behavior key takeaway entity types provide the classification model behind analyticscreator objects and execution behavior, helping you understand how each object is created, organized, processed, and used in the generated data warehouse. previous run object script nextconnector types"} ,{"id":383509396685,"name":"Connector types","type":"subsection","path":"/docs/reference/entity-types/connector-types","breadcrumb":"Reference › Entity types › Connector types","description":"","searchText":"reference entity types connector types connector types define how analyticscreator connects to source systems and external data providers. they determine how metadata is accessed and how source data can be integrated into the generated data warehouse flow. use this section to understand the available connector types and choose the appropriate connector for your source technology and integration scenario. available connector types access connector for microsoft access source files and databases. legacy source support file-based database access useful for smaller existing data stores open access azure blob connector for file-based and object-based sources in azure blob storage. cloud storage integration useful for landing and exchange zones supports azure-based source scenarios open azure blob csv connector for delimited text file sources. flat file ingestion simple structured source format suitable for exchange files open csv direct connector type for direct source access scenarios. direct integration pattern reduced abstraction layer useful for specific source access cases open direct excel connector for excel-based source files. file-based source access structured spreadsheet input useful for departmental data sources open excel mssql connector for microsoft sql server sources and metadata import. relational source access table and metadata import common warehouse source type open mssql odata connector for odata-based service endpoints and api-style data access. service-oriented integration useful for api-style sources supports metadata-driven remote access open odata odbc generic connector based on odbc driver access. broad compatibility useful for many relational systems driver-based connection model open odbc oledb generic connector based on ole db provider access. flexible connectivity option useful for supported provider-based sources suitable for heterogeneous environments open oledb oledb.net connector based on ole db .net provider access. .net-based provider model useful for provider-specific integrations extends connectivity options open oledb.net oracle connector for oracle-based source systems. relational source integration metadata-driven access suitable for oracle source landscapes open oracle sap connector for sap metadata and source integration scenarios. sap metadata import relevant for erp integration supports sap-oriented modeling flows open sap how to choose a connector type use mssql or oracle for direct relational database integration use excel, csv, or access for file-based and desktop data sources use sap for sap-oriented metadata and source integration use odbc, oledb, or oledb.net for generic provider-based connectivity use azure blob for cloud storage-based source scenarios use odata for service-based or api-style access use direct when a direct connector pattern is required for the source integration scenario key takeaway connector types define how analyticscreator accesses metadata and source data across relational databases, files, enterprise systems, cloud storage, and service-based interfaces. previous entity types nextmssql"} ,{"id":386708347104,"name":"Access","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-access","breadcrumb":"Reference › Entity types › Connector types › Access","description":"","searchText":"reference entity types connector types access overview microsoft access is a connector type that connects analyticscreator to microsoft access database files. function use this type when source data is stored in an access database. selecting it uses access file and provider connection behavior. when to use choose microsoft access when source data is stored in an access database. behavior in analyticscreator area behavior configuration configure the database file path, provider, and access credentials when required. processing analyticscreator reads access tables, views, and supported queries through the installed provider. output the connector exposes access objects as analyticscreator sources. type-specific properties property description database file path to the access database. provider installed access or ace provider. credentials password or authentication settings when required. connection options additional provider-specific settings. compatibility and limitations a compatible access provider with matching application architecture is required. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous excel next ole db"} ,{"id":386708347105,"name":"Azure BLOB","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-azure-blob","breadcrumb":"Reference › Entity types › Connector types › Azure BLOB","description":"","searchText":"reference entity types connector types azure blob overview azure blob storage is a connector type that connects analyticscreator to files stored in azure blob storage. function use this type when source files are stored in an azure storage account or container. selecting it uses cloud-file discovery and retrieval behavior. when to use choose azure blob storage when source files are stored in an azure storage account or container. behavior in analyticscreator area behavior configuration configure the storage account or endpoint, container, path, and authentication method. processing analyticscreator retrieves supported files from the selected blob location. output the connector exposes cloud-hosted files as source objects. type-specific properties property description storage endpoint azure blob storage account or service endpoint. container container containing the source files. blob path folder or blob path used for source discovery. authentication credential, token, or key configuration used to access storage. compatibility and limitations file formats, authentication methods, and network access must be compatible with the configured connector. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous ole db .net (oledb.net) next odata"} ,{"id":386708347106,"name":"CSV","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-csv","breadcrumb":"Reference › Entity types › Connector types › CSV","description":"","searchText":"reference entity types connector types csv overview csv is a connector type that connects analyticscreator to delimited text files. function use this type when source data is supplied as csv or another supported delimited text format. selecting it uses file-based source discovery and text parsing. when to use choose csv when source data is supplied as csv or another supported delimited text format. behavior in analyticscreator area behavior configuration configure the file or folder path, delimiter, encoding, header behavior, and related text settings. processing analyticscreator parses rows from the configured text file according to the connector and source settings. output the connector exposes file-based sources and columns inferred or defined from the text structure. type-specific properties property description path file or folder location containing the source data. delimiter character used to separate values. encoding character encoding used to read the file. header handling controls whether column names are read from the file header. compatibility and limitations column detection and data conversion depend on consistent file structure, encoding, and delimiters. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous oracle next excel"} ,{"id":386708347107,"name":"Direct","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-direct","breadcrumb":"Reference › Entity types › Connector types › Direct","description":"","searchText":"reference entity types connector types direct overview direct is a connector type that provides a direct connector path for supported analyticscreator processing scenarios. function use this type when a transformation is designed to access connector data directly instead of using a conventional imported staging path. selecting it enables direct-connector processing behavior. when to use choose direct when a transformation is designed to access connector data directly instead of using a conventional imported staging path. behavior in analyticscreator area behavior configuration configure the underlying connector and the direct source or transformation settings. processing analyticscreator reads from the connector during the direct processing flow. output the connector supplies data directly to compatible transformations or generated operations. type-specific properties property description underlying connection connection information used by the direct access path. source selection source object or statement used by the direct operation. runtime options options that control direct access or execution. credentials authentication required by the source system. compatibility and limitations availability depends on the connector, transformation type, and supported direct-processing capabilities. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous odbc next ole db .net (oledb.net)"} ,{"id":386708347108,"name":"Excel","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-excel","breadcrumb":"Reference › Entity types › Connector types › Excel","description":"","searchText":"reference entity types connector types excel overview excel is a connector type that connects analyticscreator to microsoft excel workbooks. function use this type when source data is maintained in worksheets or named ranges. selecting it uses workbook-based source discovery. when to use choose excel when source data is maintained in worksheets or named ranges. behavior in analyticscreator area behavior configuration configure the workbook path and the worksheet, range, or header behavior required by the source. processing analyticscreator reads tabular values from the selected workbook object through the configured excel provider. output the connector exposes worksheets or ranges as source objects. type-specific properties property description workbook path location of the excel file. worksheet or range workbook object used as the data source. header handling controls whether the first row supplies column names. provider options excel provider settings where required. compatibility and limitations a compatible excel provider is required. mixed data types and irregular worksheet layouts can affect type inference. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous csv next microsoft access"} ,{"id":386708347109,"name":"MSSQL","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-mssql","breadcrumb":"Reference › Entity types › Connector types › MSSQL","description":"","searchText":"reference entity types connector types mssql overview microsoft sql server (mssql) is a connector type that connects analyticscreator to microsoft sql server-compatible relational databases. function use this type when the source or target data is hosted in microsoft sql server or a compatible sql server endpoint. selecting it uses sql server connection and metadata access behavior. when to use choose microsoft sql server (mssql) when the source or target data is hosted in microsoft sql server or a compatible sql server endpoint. behavior in analyticscreator area behavior configuration configure the server, database, authentication method, and connection options. processing analyticscreator reads relational metadata and executes supported sql server operations through the configured connection. output the connector exposes sql server sources that can be imported, queried, or referenced. type-specific properties property description server sql server host or endpoint. database database selected for source discovery and data access. authentication credentials or integrated authentication used by the connection. connection options additional provider and timeout settings where available. compatibility and limitations connectivity depends on network access, database permissions, and a compatible sql server provider. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous connector types next oracle"} ,{"id":386708347110,"name":"OData","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-odata","breadcrumb":"Reference › Entity types › Connector types › OData","description":"","searchText":"reference entity types connector types odata overview odata is a connector type that connects analyticscreator to an odata service. function use this type when source data is exposed through an odata endpoint. selecting it uses odata service metadata and query behavior. when to use choose odata when source data is exposed through an odata endpoint. behavior in analyticscreator area behavior configuration configure the service url, authentication, and supported query options. processing analyticscreator reads service metadata and requests entity data through odata operations. output the connector exposes odata entity sets or compatible endpoints as sources. type-specific properties property description service url base url of the odata service. authentication credentials or token settings used by the service. query options supported odata filtering, selection, or paging options. timeout request timeout where configurable. compatibility and limitations available operations depend on the odata service version, authentication, paging, and server-supported query options. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous azure blob storage next source types"} ,{"id":386708347111,"name":"ODBC","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-odbc","breadcrumb":"Reference › Entity types › Connector types › ODBC","description":"","searchText":"reference entity types connector types odbc overview odbc is a connector type that connects analyticscreator to data sources through an odbc driver. function use this type when the source platform is accessible through a compatible odbc driver or dsn. selecting it uses odbc driver-defined connection behavior. when to use choose odbc when the source platform is accessible through a compatible odbc driver or dsn. behavior in analyticscreator area behavior configuration configure the driver or dsn, connection string, and credentials. processing analyticscreator uses odbc metadata and query capabilities supplied by the configured driver. output the connector exposes the source objects returned by the odbc driver. type-specific properties property description driver or dsn odbc driver or data source name used for the connection. connection string odbc connection parameters. credentials authentication values used by the source. driver options additional settings supported by the driver. compatibility and limitations metadata quality and supported sql behavior depend on the selected odbc driver. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous sap next direct"} ,{"id":386708347112,"name":"OLEDB","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-oledb","breadcrumb":"Reference › Entity types › Connector types › OLEDB","description":"","searchText":"reference entity types connector types oledb overview ole db is a connector type that connects analyticscreator to data sources through an ole db provider. function use this type when the source system supplies a compatible ole db provider. selecting it uses provider-defined ole db connection behavior. when to use choose ole db when the source system supplies a compatible ole db provider. behavior in analyticscreator area behavior configuration select the provider and supply the provider-specific connection string or properties. processing analyticscreator uses the selected ole db provider for metadata discovery and data access. output the connector exposes the objects and capabilities returned by the provider. type-specific properties property description provider ole db provider used for the connection. connection string provider-specific connection information. credentials authentication values required by the provider. provider properties additional settings supported by the selected provider. compatibility and limitations available features depend on the installed provider and the metadata capabilities it exposes. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous microsoft access next sap"} ,{"id":386708347113,"name":"OLEDB.NET","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-oledb-net","breadcrumb":"Reference › Entity types › Connector types › OLEDB.NET","description":"","searchText":"reference entity types connector types oledb.net overview ole db .net (oledb.net) is a connector type that connects analyticscreator through the .net ole db data provider. function use this type when a source requires ole db access through the .net provider layer. selecting it uses .net ole db connection behavior. when to use choose ole db .net (oledb.net) when a source requires ole db access through the .net provider layer. behavior in analyticscreator area behavior configuration configure the ole db provider, .net connection string, and credentials. processing analyticscreator accesses metadata and data through the configured .net ole db provider. output the connector exposes the source objects supported by the provider. type-specific properties property description ole db provider underlying provider used by the .net connection. connection string provider and source connection settings. credentials authentication values required by the source. provider options additional .net or provider-specific properties. compatibility and limitations the required ole db provider must be installed and compatible with the analyticscreator process architecture. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous direct next azure blob storage"} ,{"id":386708347114,"name":"Oracle","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-oracle","breadcrumb":"Reference › Entity types › Connector types › Oracle","description":"","searchText":"reference entity types connector types oracle overview oracle is a connector type that connects analyticscreator to oracle databases. function use this type when the source data is stored in oracle and oracle metadata or sql access is required. selecting it uses oracle connection and metadata access behavior. when to use choose oracle when the source data is stored in oracle and oracle metadata or sql access is required. behavior in analyticscreator area behavior configuration configure the oracle host or service, credentials, and provider-specific settings. processing analyticscreator reads oracle metadata and executes supported oracle queries through the configured provider. output the connector exposes oracle tables, views, and query-based sources. type-specific properties property description server or service oracle host, service name, or connection identifier. authentication oracle credentials used by the connection. provider installed oracle client or provider used by analyticscreator. connection options additional oracle connection properties where available. compatibility and limitations a compatible oracle client or provider, network access, and sufficient database permissions are required. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous microsoft sql server (mssql) next csv"} ,{"id":386708347115,"name":"SAP","type":"topic","path":"/docs/reference/entity-types/connector-types/connector-types-sap","breadcrumb":"Reference › Entity types › Connector types › SAP","description":"","searchText":"reference entity types connector types sap overview sap is a connector type that connects analyticscreator to supported sap source interfaces. function use this type when source data must be read from sap through the sap connector capabilities available in the installation. selecting it uses sap-specific metadata and extraction behavior. when to use choose sap when source data must be read from sap through the sap connector capabilities available in the installation. behavior in analyticscreator area behavior configuration configure the sap system, client, user, authentication, and interface-specific settings. processing analyticscreator requests metadata and data through the configured sap interface. output the connector exposes supported sap source objects, including sap-specific source types where available. type-specific properties property description sap system sap host or system identifier. client sap client used by the connection. authentication sap user and credential settings. extraction settings interface-specific options such as record limits or delta behavior. compatibility and limitations sap connectivity depends on licensed components, compatible sap interfaces, permissions, and system configuration. relationships related entity relationship connector the selected connector type determines how the connector reaches an external system. source sources are discovered or defined through a connector and inherit the connector's access method. where to configure connector page connectors list page connector entity connector types related topics connector types connector entity previous ole db next odbc"} ,{"id":383509340362,"name":"Join historization types","type":"subsection","path":"/docs/reference/entity-types/join-historization-types","breadcrumb":"Reference › Entity types › Join historization types","description":"","searchText":"reference entity types join historization types join historization types define how joins behave when historized data is involved. use this section to understand how analyticscreator resolves joins between historized structures and which time-dependent behavior is applied in each case. available join historization types none use this join historization type when no historization-aware join behavior is required. no historical validity handling suitable for non-historized joins uses standard join logic open none actual use this join historization type when only the current valid state of the joined data should be considered. current-state join behavior ignores historical versions suitable for active-record scenarios open actual full use this join historization type when the join should consider the full historical range of the participating tables. full historical join behavior includes historical validity logic suitable for complete history analysis open full historical_from use this join historization type when the join should be aligned using the historical start of validity. based on valid-from logic useful for time-entry alignment supports start-point-based historized joins open historical_from historical_to use this join historization type when the join should be aligned using the historical end of validity. based on valid-to logic useful for time-exit alignment supports end-point-based historized joins open historical_to historical_from historical_from is a join historization type used in the transformation editor for joined tables. open historical_from historical_to historical_to is a join historization type used in the transformation editor for joined tables. open historical_to how to choose a join historization type use none when no historization-aware join handling is required use actual when only the current valid state should be joined use full when full historical validity should be respected use historical_from when joins should align on the start of validity use historical_to when joins should align on the end of validity key takeaway join historization types define how analyticscreator applies time-dependent validity logic when joining historized data structures. previous none nextnone"} ,{"id":386676751588,"name":"Actual","type":"topic","path":"/docs/reference/entity-types/join-historization-types/entity-types-join-historization-types-actual","breadcrumb":"Reference › Entity types › Join historization types › Actual","description":"","searchText":"reference entity types join historization types actual overview actual is a join historization type that uses the current or active version of the joined historical object. function use this type when the relationship should resolve against the current state. selecting it adds current-record matching behavior. when to use choose actual when the relationship should resolve against the current state. behavior in analyticscreator area behavior configuration select actual and ensure the joined source exposes current-record validity information. processing analyticscreator restricts the historical side to the active qualifying row. output the result joins against current-state records. type-specific properties property description type token actual. current-record rule validity or status rule identifying the active row. join keys business or surrogate keys used by the join. validity fields fields supporting current-state selection. compatibility and limitations current matching depends on accurate validity data. relationships related entity relationship transformation join the type changes temporal matching behavior for a configured join. historized table validity fields from historized records supply the time boundaries used by historical join modes. where to configure transformation page transformation entity historization page join historization types related topics join historization types transformation entity previous none next historical from"} ,{"id":386676751589,"name":"Full","type":"topic","path":"/docs/reference/entity-types/join-historization-types/entity-types-join-historization-types-full","breadcrumb":"Reference › Entity types › Join historization types › Full","description":"","searchText":"reference entity types join historization types full overview full is a join historization type that uses complete historical interval matching for the join. function use this type when records must be matched across their available validity periods. selecting it applies full temporal interval behavior. when to use choose full when records must be matched across their available validity periods. behavior in analyticscreator area behavior configuration select full and configure compatible valid-from, valid-to, and key fields on the joined inputs. processing analyticscreator evaluates historical intervals according to the configured join logic. output the result can represent relationships between historical versions. type-specific properties property description type token full. valid-from fields start boundaries of the compared intervals. valid-to fields end boundaries of the compared intervals. join keys keys linking versions of the logical records. compatibility and limitations exact overlap and boundary semantics depend on the maintained transformation logic. relationships related entity relationship transformation join the type changes temporal matching behavior for a configured join. historized table validity fields from historized records supply the time boundaries used by historical join modes. where to configure transformation page transformation entity historization page join historization types related topics join historization types transformation entity previous historical to next package types"} ,{"id":386676751590,"name":"Historical_from","type":"topic","path":"/docs/reference/entity-types/join-historization-types/entity-types-join-historization-types-historical-from","breadcrumb":"Reference › Entity types › Join historization types › Historical_from","description":"","searchText":"reference entity types join historization types historical_from overview historical from (historical_from) is a join historization type that uses the historical valid-from boundary when evaluating the join. function use this type when matching must be aligned to the start of a historical validity period. selecting it applies valid-from-oriented temporal matching. when to use choose historical from when matching must be aligned to the start of a historical validity period. behavior in analyticscreator area behavior configuration select historical_from and configure the relevant valid-from fields and join keys. processing analyticscreator evaluates the relationship using the configured historical start boundary. output the result associates rows according to valid-from-oriented history logic. type-specific properties property description type token historical_from. valid-from field start boundary used by the temporal match. join keys keys linking the logical records. comparison context date or validity expression compared with the start boundary. compatibility and limitations exact sql and boundary behavior depend on the transformation's validity fields and join configuration. relationships related entity relationship transformation join the type changes temporal matching behavior for a configured join. historized table validity fields from historized records supply the time boundaries used by historical join modes. where to configure transformation page transformation entity historization page join historization types related topics join historization types transformation entity previous actual next historical to"} ,{"id":386676751591,"name":"Historical_to","type":"topic","path":"/docs/reference/entity-types/join-historization-types/entity-types-join-historization-types-historical-to","breadcrumb":"Reference › Entity types › Join historization types › Historical_to","description":"","searchText":"reference entity types join historization types historical_to overview historical to (historical_to) is a join historization type that uses the historical valid-to boundary when evaluating the join. function use this type when matching must be aligned to the end of a historical validity period. selecting it applies valid-to-oriented temporal matching. when to use choose historical to when matching must be aligned to the end of a historical validity period. behavior in analyticscreator area behavior configuration select historical_to and configure the relevant valid-to fields and join keys. processing analyticscreator evaluates the relationship using the configured historical end boundary. output the result associates rows according to valid-to-oriented history logic. type-specific properties property description type token historical_to. valid-to field end boundary used by the temporal match. join keys keys linking the logical records. comparison context date or validity expression compared with the end boundary. compatibility and limitations exact sql and inclusive or exclusive boundary behavior depend on the transformation configuration. relationships related entity relationship transformation join the type changes temporal matching behavior for a configured join. historized table validity fields from historized records supply the time boundaries used by historical join modes. where to configure transformation page transformation entity historization page join historization types related topics join historization types transformation entity previous historical from next full"} ,{"id":386676751592,"name":"None","type":"topic","path":"/docs/reference/entity-types/join-historization-types/entity-types-join-historization-types-none","breadcrumb":"Reference › Entity types › Join historization types › None","description":"","searchText":"reference entity types join historization types none overview none is a join historization type that uses no history-specific join behavior. function use this type when the relationship should use ordinary join conditions only. selecting it disables temporal matching rules. when to use choose none when the relationship should use ordinary join conditions only. behavior in analyticscreator area behavior configuration select none and maintain the normal join condition. processing analyticscreator joins rows using the configured keys and conditions without adding historical logic. output the result follows ordinary join semantics. type-specific properties property description type token none. join keys columns used by the ordinary join. join condition additional matching expression. join kind inner, outer, or other supported join behavior. compatibility and limitations historized inputs can produce multiple matches when ordinary conditions do not restrict versions. relationships related entity relationship transformation join the type changes temporal matching behavior for a configured join. historized table validity fields from historized records supply the time boundaries used by historical join modes. where to configure transformation page transformation entity historization page join historization types related topics join historization types transformation entity previous join historization types next actual"} ,{"id":383509340363,"name":"Package types","type":"subsection","path":"/docs/reference/entity-types/package-types","breadcrumb":"Reference › Entity types › Package types","description":"","searchText":"reference entity types package types package types define how execution units are structured in analyticscreator and what role they play in data loading, historization, persisting, workflow orchestration, scripting, exports, and external processing. use this section to understand the available package types and choose the appropriate one for the execution pattern you want to implement. available package types exports used to move processed data or generated outputs to downstream targets. supports outbound data movement useful for interface and delivery scenarios can target external analytical or operational systems open exports external used when execution is handled outside the standard analyticscreator-generated package flow. external execution integration useful for non-standard processing scenarios separates generated logic from external runtime behavior open external historization used to execute historization logic and manage validity-based data changes over time. supports change tracking typical for persistent staging used with historized tables open historization import used to load data from source systems into the staging layer. supports source ingestion typical entry point for execution used in generated loading workflows open import persisting used to materialize transformation results physically for performance or architectural reasons. stores generated output physically useful for complex transformations supports persisted execution patterns open persisting script used when execution logic is implemented as a script instead of a standard generated package flow. script-based execution behavior useful for special-case processing supports custom runtime logic open script workflow used to orchestrate execution order and dependencies across multiple processing steps. coordinates execution flow handles dependencies between packages typical orchestration entry point open workflow how to choose a package type use import for source-to-staging data loading use historization for change tracking and validity-based updates use persisting when transformation results should be materialized physically use workflow to orchestrate package dependencies and execution order use script for script-based processing logic use exports for outbound delivery to downstream targets use external when execution is managed outside the standard generated package flow key takeaway package types define how execution is structured in analyticscreator, from loading and historization to workflow orchestration, scripting, exports, and external processing. previous historical_to nextimport"} ,{"id":386711825594,"name":"Exports","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-exports","breadcrumb":"Reference › Entity types › Package types › Exports","description":"","searchText":"reference entity types package types exports overview export is a package type that groups table-to-source export definitions. function use this type when warehouse data must be written to an external target. selecting it executes export content. when to use choose export when warehouse data must be written to an external target. behavior in analyticscreator area behavior configuration add export definitions that map source tables to external destinations. processing the package reads warehouse rows and writes them through the target connector. output external target objects receive the exported data. type-specific properties property description export content table-to-target export definitions assigned to the package. source table warehouse table supplying rows. target source external destination represented through a connector. load options export filters, scripts, and runtime settings. compatibility and limitations target compatibility, connector permissions, and mappings must be valid. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous script next external"} ,{"id":386711825595,"name":"External","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-external","breadcrumb":"Reference › Entity types › Package types › External","description":"","searchText":"reference entity types package types external overview external is a package type that groups external transformations for execution. function use this type when processing is performed by an external command, application, or service. selecting it executes external transformation content. when to use choose external when processing is performed by an external command, application, or service. behavior in analyticscreator area behavior configuration assign external transformations and configure their external execution details. processing the package starts the configured external operations. output the external process supplies the resulting data or side effect. type-specific properties property description external transformations transformations assigned to the package. command or service external operation being invoked. parameters values passed to the operation. dependencies required packages or objects. compatibility and limitations execution, logging, and failure behavior depend on the external process. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous export next sql script types"} ,{"id":386711825596,"name":"Historization","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-historization","breadcrumb":"Reference › Entity types › Package types › Historization","description":"","searchText":"reference entity types package types historization overview historization is a package type that groups table historization definitions. function use this type when source records must be loaded into historized target tables. selecting it executes historization content. when to use choose historization when source records must be loaded into historized target tables. behavior in analyticscreator area behavior configuration add historization definitions with scd, validity, and missing-source behavior. processing the package detects new, changed, and missing records and maintains history. output historized tables are updated with current and historical versions. type-specific properties property description historization content historization definitions assigned to the package. validity rules valid-from and valid-to behavior. scd settings column-level current and historical tracking. dependencies packages required before history processing. compatibility and limitations stable keys and valid historization rules are required. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous import next persisting"} ,{"id":386711825597,"name":"Import","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-import","breadcrumb":"Reference › Entity types › Package types › Import","description":"","searchText":"reference entity types package types import overview import is a package type that groups source-to-table import definitions. function use this type when external source data must be loaded into import tables. selecting it executes import content. when to use choose import when external source data must be loaded into import tables. behavior in analyticscreator area behavior configuration add import definitions that map sources to target import tables. processing the package runs the configured imports and their scripts or load options. output target import tables are populated from external sources. type-specific properties property description import content source-to-target import definitions assigned to the package. load options buffer, batch, logging, and related import settings. dependencies packages that must run before the import package. externally launched indicates whether normal package sequencing is bypassed. compatibility and limitations source connectors, mappings, and target table structures must be valid. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous package types next historization"} ,{"id":386711825598,"name":"Persisting","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-persisting","breadcrumb":"Reference › Entity types › Package types › Persisting","description":"","searchText":"reference entity types package types persisting overview persisting is a package type that groups transformation-to-table persisting definitions. function use this type when transformation output must be stored physically. selecting it executes persisting content. when to use choose persisting when transformation output must be stored physically. behavior in analyticscreator area behavior configuration add persisting definitions that connect transformations to target tables. processing the package evaluates the transformation and writes its result to the persisting table. output persisting tables are refreshed or loaded according to their definitions. type-specific properties property description persisting content transformation-to-table definitions assigned to the package. transformation source logic that produces the rows. target table physical table that receives the result. dependencies required upstream packages and transformations. compatibility and limitations transformation output must remain compatible with the target table. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous historization next workflow"} ,{"id":386711825599,"name":"Script","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-script","breadcrumb":"Reference › Entity types › Package types › Script","description":"","searchText":"reference entity types package types script overview script is a package type that groups script transformations for execution. function use this type when processing is implemented through script transformations. selecting it executes script-based transformation content. when to use choose script when processing is implemented through script transformations. behavior in analyticscreator area behavior configuration assign supported script transformations to the package. processing the package runs the maintained transformation scripts. output the scripts create their configured results or side effects. type-specific properties property description script transformations transformations assigned to the script package. execution order order controlled by package and dependency settings. dependencies packages or objects required before execution. externally launched indicates whether normal sequencing is bypassed. compatibility and limitations the package cannot fully validate arbitrary script side effects. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous workflow next export"} ,{"id":386711825600,"name":"Workflow","type":"topic","path":"/docs/reference/entity-types/package-types/entity-types-package-types-workflow","breadcrumb":"Reference › Entity types › Package types › Workflow","description":"","searchText":"reference entity types package types workflow overview workflow is a package type that coordinates the execution of child packages. function use this type when multiple packages must run in a controlled sequence. selecting it orchestrates package execution. when to use choose workflow when multiple packages must run in a controlled sequence. behavior in analyticscreator area behavior configuration select included packages and configure interruption and retry behavior. processing the workflow runs child packages according to dependencies and workflow settings. output a coordinated multi-package process is executed. type-specific properties property description include selects child packages included in the workflow. interrupt on error stops processing after a child-package failure. retry attempts number of retries after failure. retry interval delay between retry attempts. compatibility and limitations circular dependencies and incompatible package sequences must be avoided. relationships related entity relationship package the package type determines the package's allowed content and processing role. deployment deployments can include packages that must be generated or executed. workflow workflow packages coordinate other packages. where to configure package page packages list page package entity package types related topics package types package entity previous persisting next script"} ,{"id":383509340364,"name":"Schema types","type":"subsection","path":"/docs/reference/entity-types/schema-types","breadcrumb":"Reference › Entity types › Schema types","description":"","searchText":"reference entity types schema types schema types define how database schemas are organized in analyticscreator and what role each schema plays in the generated data warehouse architecture. use this section to understand the available schema types and how they structure staging, historization, transformation, core, and data mart layers. available schema types core used to store business-oriented structures such as integrated dimensions, facts, or data vault-based core models. central business logic layer contains integrated warehouse structures feeds downstream analytical layers open core datamart used to expose data in a form intended for analytical consumption and reporting. consumption-oriented layer typically contains facts and dimensions for reporting basis for semantic models and bi tools open datamart persisted staging used to store persistent and historized source data for further processing. persistent source-related layer supports historization and reprocessing separates source loading from downstream logic open persisted staging staging used to store imported source data before further processing. initial landing layer holds imported source structures basis for downstream historization and transformation open staging transformation used for generated transformation logic that shapes and combines source data. transformation-oriented layer typically contains generated views or logic objects used between source-related and business-oriented layers open transformation how to choose a schema type use staging for imported source data use persisted staging when persistent and historized source data is required use transformation for intermediate transformation logic use core for integrated business-oriented warehouse structures use datamart for reporting-ready analytical structures key takeaway schema types define the structural layers of the generated data warehouse, from source-oriented staging through core integration to reporting-ready data marts. previous repository extension nextstaging"} ,{"id":386676751594,"name":"Core","type":"topic","path":"/docs/reference/entity-types/schema-types/entity-types-schema-types-core","breadcrumb":"Reference › Entity types › Schema types › Core","description":"","searchText":"reference entity types schema types core overview core is a schema type that contains integrated, business-oriented warehouse structures. function use this type when data from multiple sources must be standardized and integrated into a stable warehouse core. selecting it supports integrated warehouse objects. when to use choose core when data from multiple sources must be standardized and integrated into a stable warehouse core. behavior in analyticscreator area behavior configuration create the schema in the core layer and assign the core type. processing upstream packages and transformations load or derive integrated core data. output the schema contains reusable business entities, relationships, or data vault structures. type-specific properties property description layer core warehouse layer containing the schema. integrated tables business-oriented tables shared by downstream consumers. references relationships connecting core entities. historization history behavior used by core structures where required. compatibility and limitations core structures should be source-independent and governed for reuse across data marts. relationships related entity relationship schema the schema type identifies the architectural role of the schema entity. layer schemas belong to layers that organize warehouse processing. table and transformation tables and transformations are created inside schemas according to their intended role. where to configure schemas list page schemas navigation tree schema entity schema types related topics schema types schema entity previous transformation next data mart"} ,{"id":386676751595,"name":"Datamart","type":"topic","path":"/docs/reference/entity-types/schema-types/entity-types-schema-types-datamart","breadcrumb":"Reference › Entity types › Schema types › Datamart","description":"","searchText":"reference entity types schema types datamart overview data mart is a schema type that contains analytical dimension, fact, and related semantic structures. function use this type when business-facing analytical data must be organized for reporting and olap use. selecting it supports data mart and semantic objects. when to use choose data mart when business-facing analytical data must be organized for reporting and olap use. behavior in analyticscreator area behavior configuration create the schema in the data mart layer and assign the data mart type. processing transformations and packages populate dimension and fact tables for analytical use. output the schema contains dimensions, facts, hierarchies, partitions, and related analytical metadata. type-specific properties property description layer data mart layer containing the schema. dimension tables descriptive analytical structures. fact tables measures and events analyzed through dimensions. olap metadata hierarchies, partitions, display metadata, and related settings. compatibility and limitations dimensions, facts, keys, grain, and semantic metadata must remain consistent. relationships related entity relationship schema the schema type identifies the architectural role of the schema entity. layer schemas belong to layers that organize warehouse processing. table and transformation tables and transformations are created inside schemas according to their intended role. where to configure schemas list page schemas navigation tree schema entity schema types related topics schema types schema entity previous core next entities"} ,{"id":386676751596,"name":"Persisted staging","type":"topic","path":"/docs/reference/entity-types/schema-types/entity-types-schema-types-persisted-staging","breadcrumb":"Reference › Entity types › Schema types › Persisted staging","description":"","searchText":"reference entity types schema types persisted staging overview persisted staging is a schema type that provides a durable staging area retained beyond a transient import step. function use this type when staging data must be stored persistently for reuse, auditing, or downstream processing. selecting it supports persistent staging structures. when to use choose persisted staging when staging data must be stored persistently for reuse, auditing, or downstream processing. behavior in analyticscreator area behavior configuration create the schema in the appropriate layer and assign the persisted staging type. processing import, historization, or persisting processes maintain durable staging data according to the architecture. output the schema contains retained staging structures used by later layers. type-specific properties property description layer warehouse layer containing the schema. persisted tables durable source-aligned or processed tables. load packages packages that maintain the persisted staging data. retention behavior architecture-specific rules for retaining or refreshing data. compatibility and limitations retention, historization, and refresh behavior must be defined consistently with downstream dependencies. relationships related entity relationship schema the schema type identifies the architectural role of the schema entity. layer schemas belong to layers that organize warehouse processing. table and transformation tables and transformations are created inside schemas according to their intended role. where to configure schemas list page schemas navigation tree schema entity schema types related topics schema types schema entity previous staging next transformation"} ,{"id":386676751597,"name":"Staging","type":"topic","path":"/docs/reference/entity-types/schema-types/entity-types-schema-types-staging","breadcrumb":"Reference › Entity types › Schema types › Staging","description":"","searchText":"reference entity types schema types staging overview staging is a schema type that provides a landing area for imported source data. function use this type when raw or lightly processed source data must be loaded before downstream processing. selecting it supports staging and import-oriented objects. when to use choose staging when raw or lightly processed source data must be loaded before downstream processing. behavior in analyticscreator area behavior configuration create the schema in the appropriate layer and assign the staging type. processing import processes load source rows into staging tables. output the schema contains staged source-aligned structures used by downstream logic. type-specific properties property description layer warehouse layer containing the schema. import tables tables populated from external sources. import definitions source-to-table mappings associated with the schema. naming and metadata schema name, description, and related settings. compatibility and limitations staging data should not be treated as the final integrated or analytical model. relationships related entity relationship schema the schema type identifies the architectural role of the schema entity. layer schemas belong to layers that organize warehouse processing. table and transformation tables and transformations are created inside schemas according to their intended role. where to configure schemas list page schemas navigation tree schema entity schema types related topics schema types schema entity previous schema types next persisted staging"} ,{"id":386676751598,"name":"Transformation","type":"topic","path":"/docs/reference/entity-types/schema-types/entity-types-schema-types-transformation","breadcrumb":"Reference › Entity types › Schema types › Transformation","description":"","searchText":"reference entity types schema types transformation overview transformation is a schema type that contains transformation objects and their generated outputs. function use this type when data must be combined, calculated, filtered, or reshaped between staging and core or data mart layers. selecting it supports transformation-oriented objects. when to use choose transformation when data must be combined, calculated, filtered, or reshaped between staging and core or data mart layers. behavior in analyticscreator area behavior configuration create the schema in the appropriate layer and assign the transformation type. processing transformations in the schema generate intermediate or reusable data logic. output the schema contains transformation views, related tables, or intermediate structures. type-specific properties property description layer warehouse layer containing the schema. transformations transformation definitions owned by the schema. generated views or tables objects produced from transformation logic. references relationships used by transformations. compatibility and limitations the schema's outputs should have clear ownership and dependency rules. relationships related entity relationship schema the schema type identifies the architectural role of the schema entity. layer schemas belong to layers that organize warehouse processing. table and transformation tables and transformations are created inside schemas according to their intended role. where to configure schemas list page schemas navigation tree schema entity schema types related topics schema types schema entity previous persisted staging next core"} ,{"id":383509396687,"name":"Source types","type":"subsection","path":"/docs/reference/entity-types/source-types","breadcrumb":"Reference › Entity types › Source types","description":"","searchText":"reference entity types source types source types define how data is read into analyticscreator and how the source object behaves during import and processing. use this section to understand the available source types and choose the appropriate one for your source system and loading pattern. available source types query use a query source when the input should be defined by a custom sql statement instead of a direct table reference. custom query-based source definition useful for filtered or pre-shaped input more flexible than direct table access open query sap deltaq use sap deltaq when loading sap extractor-based data with delta handling. sap-specific source type supports extractor-oriented loading scenarios relevant for delta-based sap integration open sap_deltaq sap_deltaq sap_deltaq is source type 3. it is used for sap delta queue sources on sap connectors. open sap_deltaq sap_odp sap_odp is source type 5. it is used for sap odp sources on sap connectors. open sap_odp table use a table source when data should be read directly from a physical source table. direct table-based import typical default source type suitable for standard relational loading open table view use a view source when data should be read from a database view instead of a physical table. view-based source access useful for predefined source abstraction suitable when logic is already encapsulated in the source open view how to choose a source type use table for standard relational source loading use view when the source system already exposes the required structure through a database view use query when the source needs custom filtering or shaping before import use sap deltaq for sap extractor scenarios with delta-oriented loading behavior key takeaway source types define how source data is accessed and should be selected based on the technical structure and loading behavior of the source system. previous odata nexttable"} ,{"id":386708347120,"name":"Query","type":"topic","path":"/docs/reference/entity-types/source-types/entity-types-source-types-query","breadcrumb":"Reference › Entity types › Source types › Query","description":"","searchText":"reference entity types source types query overview query is a source type that represents a source defined by a query rather than a named table or view. function use this type when source rows require custom selection, joins, or calculations at the source. selecting it executes the maintained query to produce source rows. when to use choose query when source rows require custom selection, joins, or calculations at the source. behavior in analyticscreator area behavior configuration configure the connector, query statement, and resulting column metadata. processing analyticscreator submits the query through the connector and reads the result set. output the source exposes the query result as a reusable analyticscreator source. type-specific properties property description query statement used to produce the source rows. columns result columns maintained for the query source. parameters or filters optional values supported by the connector or source definition. timeout execution timeout where configurable. compatibility and limitations the query must be valid for the source platform and may require manual metadata maintenance. relationships related entity relationship source the source type identifies how the source definition obtains its rows. connector the connector determines which source types and source objects are available. where to configure source page sources list page source entity source types related topics source types source entity previous view next sap delta queue (sap_deltaq)"} ,{"id":386708347121,"name":"SAP_DELTAQ","type":"topic","path":"/docs/reference/entity-types/source-types/entity-types-source-types-sap-deltaq","breadcrumb":"Reference › Entity types › Source types › SAP_DELTAQ","description":"","searchText":"reference entity types source types sap_deltaq overview sap delta queue (sap_deltaq) is a source type that represents an sap source that reads data through a supported delta queue. function use this type when incremental sap extraction is provided through the configured delta queue interface. selecting it uses sap delta extraction behavior. when to use choose sap delta queue (sap_deltaq) when incremental sap extraction is provided through the configured delta queue interface. behavior in analyticscreator area behavior configuration configure the sap connector, delta-enabled source, and extraction settings. processing analyticscreator requests available delta data through the sap connector. output the source supplies incremental records according to the sap delta queue state. type-specific properties property description sap source delta-enabled sap extraction object. delta settings settings that control delta queue processing. record limit maximum record count where configured. columns metadata returned by the sap source. compatibility and limitations requires compatible sap functionality, permissions, and a valid delta-enabled source. relationships related entity relationship source the source type identifies how the source definition obtains its rows. connector the connector determines which source types and source objects are available. where to configure source page sources list page source entity source types related topics source types source entity previous query next sap odp"} ,{"id":386708347122,"name":"SAP_ODP","type":"topic","path":"/docs/reference/entity-types/source-types/entity-types-source-types-sap-odp","breadcrumb":"Reference › Entity types › Source types › SAP_ODP","description":"","searchText":"reference entity types source types sap_odp overview sap odp is a source type that represents a source exposed through sap operational data provisioning. function use this type when the sap system publishes the required source through odp. selecting it uses odp metadata and extraction behavior. when to use choose sap odp when the sap system publishes the required source through odp. behavior in analyticscreator area behavior configuration configure the sap connector, odp context, provider, and extraction options. processing analyticscreator requests source metadata and data through the supported odp interface. output the source exposes records supplied by the selected odp provider. type-specific properties property description odp context operational data provisioning context. provider odp provider or object selected for extraction. extraction mode supported full or delta behavior where available. columns metadata returned by the odp provider. compatibility and limitations availability and delta behavior depend on the sap system, odp provider, permissions, and installed connector capabilities. relationships related entity relationship source the source type identifies how the source definition obtains its rows. connector the connector determines which source types and source objects are available. where to configure source page sources list page source entity source types related topics source types source entity previous sap delta queue (sap_deltaq) next table types"} ,{"id":386708347123,"name":"Table","type":"topic","path":"/docs/reference/entity-types/source-types/entity-types-source-types-table","breadcrumb":"Reference › Entity types › Source types › Table","description":"","searchText":"reference entity types source types table overview table is a source type that represents a physical table exposed by a connector. function use this type when the source system provides a relational or tabular table object. selecting it reads rows and metadata from a table object. when to use choose table when the source system provides a relational or tabular table object. behavior in analyticscreator area behavior configuration select the connector, source schema, table name, and relevant metadata settings. processing analyticscreator reads the table through the connector and can import or reference its columns. output the source exposes the selected table and its column metadata. type-specific properties property description source schema external schema or owner containing the table. source name name of the external table. columns column metadata discovered or maintained for the table. primary key metadata key information supplied by or defined for the source. compatibility and limitations available metadata depends on connector permissions and provider support. relationships related entity relationship source the source type identifies how the source definition obtains its rows. connector the connector determines which source types and source objects are available. where to configure source page sources list page source entity source types related topics source types source entity previous source types next view"} ,{"id":386708347124,"name":"VIEW","type":"topic","path":"/docs/reference/entity-types/source-types/entity-types-source-types-view","breadcrumb":"Reference › Entity types › Source types › VIEW","description":"","searchText":"reference entity types source types view overview view is a source type that represents a database view exposed by a connector. function use this type when the source system provides a reusable database view. selecting it reads rows from a view definition. when to use choose view when the source system provides a reusable database view. behavior in analyticscreator area behavior configuration select the connector, source schema, view name, and discovered columns. processing analyticscreator queries the view through the connector. output the source exposes the view result and its available column metadata. type-specific properties property description source schema external schema or owner containing the view. source name name of the external view. columns column metadata returned for the view. refresh behavior controls how source metadata is refreshed where available. compatibility and limitations views may not expose complete primary-key or constraint metadata. relationships related entity relationship source the source type identifies how the source definition obtains its rows. connector the connector determines which source types and source objects are available. where to configure source page sources list page source entity source types related topics source types source entity previous table next query"} ,{"id":383509396690,"name":"SQL script types","type":"subsection","path":"/docs/reference/entity-types/sql-script-types","breadcrumb":"Reference › Entity types › SQL script types","description":"","searchText":"reference entity types sql script types sql script types define when custom sql scripts are executed in analyticscreator and which phase of creation, workflow execution, deployment, or repository extension they belong to. use this section to understand the available sql script types and choose the correct execution point for custom sql logic. available sql script types post-creation used to execute sql logic after object creation has completed. runs after creation steps useful for follow-up logic supports post-processing after generated objects exist open post-creation post-deployment used to execute sql logic after deployment has completed. runs after deployment steps useful for finalization logic supports post-deployment adjustments open post-deployment post-workflow used to execute sql logic after a workflow or execution package has finished. runs after workflow execution useful for validation or cleanup supports follow-up logic after processing open post-workflow pre-creation used to execute sql logic before object creation takes place. runs before creation steps useful for preparation logic supports setup before generated objects are created open pre-creation pre-deployment used to execute sql logic before deployment starts. runs before deployment steps useful for environment preparation supports deployment-specific setup logic open pre-deployment pre-workflow used to execute sql logic before a workflow or execution package starts. runs before workflow execution useful for preparation or cleanup logic supports workflow-specific setup open pre-workflow repository extension used to extend or customize repository-related behavior with sql logic. repository-focused customization supports metadata extension scenarios useful for repository-specific enhancements open repository extension how to choose a sql script type use pre-creation or post-creation when the script belongs to object creation timing use pre-workflow or post-workflow when the script belongs to execution timing use pre-deployment or post-deployment when the script belongs to deployment timing use repository extension when the script is intended to extend repository behavior or metadata-related logic key takeaway sql script types define the lifecycle stage at which custom sql logic is executed in analyticscreator, from creation and workflow execution to deployment and repository extension. previous external nextpre-creation"} ,{"id":386708347125,"name":"Post-creation","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-post-creation","breadcrumb":"Reference › Entity types › SQL script types › Post-creation","description":"","searchText":"reference entity types sql script types post-creation overview post-creation is a sql script type that runs after warehouse object creation or synchronization work. function use this type when sql must finalize or adjust objects after creation. selecting it executes after creation processing. when to use choose post-creation when sql must finalize or adjust objects after creation. behavior in analyticscreator area behavior configuration assign the post-creation type, sequence number, statement, and active status. processing analyticscreator runs active scripts in sequence after the relevant creation phase. output the script can apply post-creation changes or cleanup. type-specific properties property description sequence number execution order among scripts of the same type. statement sql executed by the script. inactive controls whether the script is skipped. description purpose and expected effect of the script. compatibility and limitations the script must account for the final state of generated objects. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous pre-creation next pre-workflow"} ,{"id":386708347126,"name":"Post-deployment","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-post-deployment","breadcrumb":"Reference › Entity types › SQL script types › Post-deployment","description":"","searchText":"reference entity types sql script types post-deployment overview post-deployment is a sql script type that runs after deployment generation or execution. function use this type when sql must finalize a deployment after its main work. selecting it executes after deployment processing. when to use choose post-deployment when sql must finalize a deployment after its main work. behavior in analyticscreator area behavior configuration assign the post-deployment type, sequence number, statement, and active status. processing analyticscreator runs active scripts after the deployment stage. output the script can apply final configuration, validation, or cleanup. type-specific properties property description sequence number execution order among post-deployment scripts. statement sql executed after deployment. inactive controls whether the script is skipped. description purpose and expected deployment effect. compatibility and limitations the script must tolerate the state produced by the deployment and avoid conflicting changes. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous pre-deployment next repository extension"} ,{"id":386708347127,"name":"Post-workflow","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-post-workflow","breadcrumb":"Reference › Entity types › SQL script types › Post-workflow","description":"","searchText":"reference entity types sql script types post-workflow overview post-workflow is a sql script type that runs after workflow package execution. function use this type when sql must finalize processing after a workflow completes. selecting it executes after workflow processing. when to use choose post-workflow when sql must finalize processing after a workflow completes. behavior in analyticscreator area behavior configuration assign the post-workflow type, sequence number, statement, and active status. processing analyticscreator runs active post-workflow scripts after workflow processing. output the script can finalize, audit, or clean up workflow results. type-specific properties property description sequence number execution order among post-workflow scripts. statement sql executed after the workflow. inactive controls whether the script is skipped. description purpose and expected workflow effect. compatibility and limitations the script must account for workflow success or failure behavior defined by the runtime. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous pre-workflow next pre-deployment"} ,{"id":386708347128,"name":"Pre-creation","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-pre-creation","breadcrumb":"Reference › Entity types › SQL script types › Pre-creation","description":"","searchText":"reference entity types sql script types pre-creation overview pre-creation is a sql script type that runs before warehouse object creation or synchronization work. function use this type when sql must prepare the environment before objects are created. selecting it executes before creation processing. when to use choose pre-creation when sql must prepare the environment before objects are created. behavior in analyticscreator area behavior configuration assign the pre-creation type, sequence number, statement, and active status. processing analyticscreator runs active scripts in sequence before the relevant creation phase. output the script can prepare schemas, settings, or prerequisites. type-specific properties property description sequence number execution order among scripts of the same type. statement sql executed by the script. inactive controls whether the script is skipped. description purpose and expected effect of the script. compatibility and limitations failures can interrupt or affect creation. the script must be valid for the repository or target context. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous sql script types next post-creation"} ,{"id":386708347129,"name":"Pre-deployment","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-pre-deployment","breadcrumb":"Reference › Entity types › SQL script types › Pre-deployment","description":"","searchText":"reference entity types sql script types pre-deployment overview pre-deployment is a sql script type that runs before deployment generation or execution. function use this type when sql must prepare an environment before deployment work. selecting it executes before deployment processing. when to use choose pre-deployment when sql must prepare an environment before deployment work. behavior in analyticscreator area behavior configuration assign the pre-deployment type, sequence number, statement, and active status. processing analyticscreator runs active scripts before the deployment stage. output the script can create prerequisites or validate the deployment environment. type-specific properties property description sequence number execution order among pre-deployment scripts. statement sql executed before deployment. inactive controls whether the script is skipped. description purpose and expected deployment effect. compatibility and limitations the script must be valid for the deployment target and its security context. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous post-workflow next post-deployment"} ,{"id":386708348090,"name":"Pre-workflow","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-pre-workflow","breadcrumb":"Reference › Entity types › SQL script types › Pre-workflow","description":"","searchText":"reference entity types sql script types pre-workflow overview pre-workflow is a sql script type that runs before workflow package execution. function use this type when sql must prepare data or state before a workflow starts. selecting it executes before workflow processing. when to use choose pre-workflow when sql must prepare data or state before a workflow starts. behavior in analyticscreator area behavior configuration assign the pre-workflow type, sequence number, statement, and active status. processing analyticscreator runs active pre-workflow scripts before workflow packages. output the script can initialize workflow prerequisites. type-specific properties property description sequence number execution order among pre-workflow scripts. statement sql executed before the workflow. inactive controls whether the script is skipped. description purpose and expected workflow effect. compatibility and limitations the script should not leave the workflow in an inconsistent state when it fails. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous post-creation next post-workflow"} ,{"id":386708348091,"name":"Repository extension","type":"topic","path":"/docs/reference/entity-types/sql-script-types/entity-types-sql-script-types-repository-extension","breadcrumb":"Reference › Entity types › SQL script types › Repository extension","description":"","searchText":"reference entity types sql script types repository extension overview repository extension is a sql script type that extends or customizes the analyticscreator repository through sql. function use this type when repository-specific objects or logic must be added or updated. selecting it executes as repository extension processing. when to use choose repository extension when repository-specific objects or logic must be added or updated. behavior in analyticscreator area behavior configuration assign the repository extension type, sequence number, statement, and active status. processing analyticscreator can apply active repository extension scripts to the repository. output the repository receives the custom schema objects, procedures, or logic defined by the script. type-specific properties property description sequence number execution order among repository extension scripts. statement sql applied to the repository. inactive controls whether the script is skipped. description purpose and ownership of the repository extension. compatibility and limitations repository extension scripts can change repository behavior and must be reviewed carefully before execution. relationships related entity relationship sql script the script type defines the execution stage for the script. workflow pre- and post-workflow scripts run around workflow processing. deployment pre- and post-deployment scripts run around deployment processing. where to configure sql script page scripts list page sql script entity sql script types related topics sql script types sql script entity previous post-deployment next schema types"} ,{"id":383509396688,"name":"Table types","type":"subsection","path":"/docs/reference/entity-types/table-types","breadcrumb":"Reference › Entity types › Table types","description":"","searchText":"reference entity types table types table types define how tables behave in analyticscreator and what role they play in the generated data warehouse structure. use this section to understand the available table types and choose the appropriate one for staging, historization, persistence, dimensional modeling, or data vault modeling. available table types import table used to receive source data during import into the staging layer. entry point for source loading filled by generated workflows basis for downstream processing open import table historized table used to store historized data with validity periods and change tracking. supports history over time typical basis for persistent staging common for scd2-style processing open historized table persisting table used to materialize transformation results physically instead of keeping them only as views. improves performance for complex logic stores generated output physically maintained by generated procedures open persisting table dimension table used to store descriptive business entities for dimensional modeling. typical star schema component contains descriptive attributes referenced by fact tables open dimension table externally filled table used when table content is populated outside the standard analyticscreator-generated loading process. externally maintained data not filled by standard generated import logic useful for integration scenarios open externally filled table fact table used to store measurable business events and transactions in dimensional models. contains measures and foreign keys central table in star schemas supports analytical aggregation open fact table datavault hub used to store stable business keys in data vault models. represents core business entities key-centric structure foundation of hub-based modeling open datavault hub datavault link used to store relationships between business entities in data vault models. connects hubs represents business relationships supports scalable model design open datavault link datavault satellite used to store descriptive and changing attributes in data vault models. contains contextual attributes often historized by design separated from business keys open datavault satellite historized table historized table identifies a table that stores historical versions of another table in analyticscreator. use this table type when changes in a business object must be preserved instead of overwritten. open historized table how to choose a table type use import table for source ingestion into staging use historized table when changes over time must be tracked use persisting table when transformation results should be materialized physically use dimension table and fact table for dimensional modeling use externally filled table when data is maintained outside the generated loading process use datavault hub, datavault link, and datavault satellite for data vault models key takeaway table types define how data is stored and modeled in analyticscreator, from source ingestion and historization to dimensional and data vault structures. previous view nextimport table"} ,{"id":386676751600,"name":"DataVault Hub","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-datavault-hub","breadcrumb":"Reference › Entity types › Table types › DataVault Hub","description":"","searchText":"reference entity types table types datavault hub overview data vault hub is a table type that stores unique business keys in a data vault structure. function use this type when the warehouse uses data vault modeling and requires a stable record of business keys. selecting it acts as the central business-key entity for satellites and links. when to use choose data vault hub when the warehouse uses data vault modeling and requires a stable record of business keys. behavior in analyticscreator area behavior configuration configure the business key, hub identifier, load metadata, and related package behavior. processing hub processing inserts new business keys without replacing existing keys. output the hub provides stable identities used by related satellites and links. type-specific properties property description business key natural key represented by the hub. hub identifier surrogate or hash-based identifier used by relationships. load metadata technical columns describing the load. relationships satellite and link structures connected to the hub. compatibility and limitations a stable business key is required. descriptive attributes should normally be stored in satellites. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous dimension table next data vault satellite"} ,{"id":386676751601,"name":"DataVault Link","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-datavault-link","breadcrumb":"Reference › Entity types › Table types › DataVault Link","description":"","searchText":"reference entity types table types datavault link overview data vault link is a table type that stores relationships between data vault hubs. function use this type when a relationship between business keys must be represented independently. selecting it connects two or more hub identities. when to use choose data vault link when a relationship between business keys must be represented independently. behavior in analyticscreator area behavior configuration configure the participating hub references, link identifier, and load metadata. processing link processing inserts newly observed relationships without replacing existing relationships. output the link provides a stable representation of relationships between hubs. type-specific properties property description hub references participating data vault hubs. link identifier surrogate or hash-based relationship identifier. load metadata technical load and record-source information. link grain business meaning represented by one link row. compatibility and limitations the set and order of participating business keys must remain stable for consistent link identity. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous data vault satellite next transformation types"} ,{"id":386676751602,"name":"DataVault Satellite","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-datavault-satellite","breadcrumb":"Reference › Entity types › Table types › DataVault Satellite","description":"","searchText":"reference entity types table types datavault satellite overview data vault satellite is a table type that stores descriptive and historical attributes for a data vault parent. function use this type when data vault descriptive attributes or their changes must be retained. selecting it maintains attribute history linked to a hub or link. when to use choose data vault satellite when data vault descriptive attributes or their changes must be retained. behavior in analyticscreator area behavior configuration configure the parent reference, descriptive columns, validity or load metadata, and historization behavior. processing satellite processing inserts new versions when tracked attributes change. output the satellite provides descriptive history for its parent data vault object. type-specific properties property description parent reference hub or link associated with the satellite. descriptive attributes values whose changes are tracked. load metadata technical load and record-source information. historization rules used to identify new satellite versions. compatibility and limitations the parent key and tracked attribute set must be defined consistently. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous data vault hub next data vault link"} ,{"id":386676751603,"name":"Dimension table","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-dimension-table","breadcrumb":"Reference › Entity types › Table types › Dimension table","description":"","searchText":"reference entity types table types dimension table overview dimension table is a table type that stores descriptive attributes used to analyze facts. function use this type when a data mart requires reusable descriptive context such as customer, product, or date. selecting it participates as a dimension object in analytical and model structures. when to use choose dimension table when a data mart requires reusable descriptive context such as customer, product, or date. behavior in analyticscreator area behavior configuration configure dimension keys, attributes, friendly names, hierarchies, and semantic properties. processing warehouse or transformation processes populate descriptive dimension rows. output the table provides attributes and hierarchies used to filter and group measures. type-specific properties property description dimension key key used by fact relationships. attributes descriptive columns exposed for analysis. hierarchies ordered levels used for navigation. historization optional treatment of changing dimension attributes. compatibility and limitations keys and attributes must remain consistent with related fact data. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous fact table next data vault hub"} ,{"id":386676751604,"name":"Externally filled table","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-externally-filled-table","breadcrumb":"Reference › Entity types › Table types › Externally filled table","description":"","searchText":"reference entity types table types externally filled table overview externally filled table is a table type that represents a warehouse table populated outside the standard analyticscreator load flow. function use this type when an external process owns data loading but the table must participate in analyticscreator metadata and relationships. selecting it is not populated by a standard import, historization, or persisting definition. when to use choose externally filled table when an external process owns data loading but the table must participate in analyticscreator metadata and relationships. behavior in analyticscreator area behavior configuration configure the table metadata and ensure the external process maintains the physical table. processing analyticscreator can reference or generate dependent objects while the external process supplies the rows. output the table participates in the model without a standard analyticscreator loading package. type-specific properties property description external owner process or system responsible for loading the table. columns table structure maintained in analyticscreator. references relationships used by transformations and models. synchronization coordination between external ddl or loads and analyticscreator metadata. compatibility and limitations analyticscreator cannot guarantee data freshness or load consistency for externally controlled processes. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous persisting table next fact table"} ,{"id":386676751605,"name":"Fact table","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-fact-table","breadcrumb":"Reference › Entity types › Table types › Fact table","description":"","searchText":"reference entity types table types fact table overview fact table is a table type that stores measurable events or transactions for analytical use. function use this type when a data mart requires measures linked to descriptive dimensions. selecting it participates as a fact object in analytical and model structures. when to use choose fact table when a data mart requires measures linked to descriptive dimensions. behavior in analyticscreator area behavior configuration configure measures, keys, dimension references, partitions, and semantic properties. processing warehouse or transformation processes populate fact rows at the selected grain. output the table provides measures and dimension relationships for analytical output. type-specific properties property description grain level represented by one fact row. measures numeric or aggregatable values exposed by the table. dimension references relationships from the fact to dimension tables. partitions optional analytical partition definitions. compatibility and limitations measures and relationships must match the intended grain to avoid incorrect aggregation. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous externally filled table next dimension table"} ,{"id":386676751606,"name":"Historized table","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-historized-table","breadcrumb":"Reference › Entity types › Table types › Historized table","description":"","searchText":"reference entity types table types historized table overview historized table is a table type that stores current and historical versions of source records. function use this type when changes to business records must be retained over time. selecting it is populated by a historization definition. when to use choose historized table when changes to business records must be retained over time. behavior in analyticscreator area behavior configuration configure history keys, validity columns, scd behavior, and historization package settings. processing historization processing detects changes and maintains historical rows. output the table provides versioned records with current and historical states. type-specific properties property description business key columns used to identify the logical record. validity columns columns that identify the effective period. historization rules scd and missing-source behavior. package historization package that executes the load. compatibility and limitations correct history depends on stable keys, valid date logic, and consistent source data. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous import table next persisting table"} ,{"id":386676751607,"name":"Import table","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-import-table","breadcrumb":"Reference › Entity types › Table types › Import table","description":"","searchText":"reference entity types table types import table overview import table is a table type that stores data imported from an external source. function use this type when external source data needs a landing or staging table in the warehouse. selecting it is populated by an import definition or import package. when to use choose import table when external source data needs a landing or staging table in the warehouse. behavior in analyticscreator area behavior configuration configure the schema, columns, import relationship, and package settings. processing an import process loads source rows into the table. output the table provides staged data for transformations, historization, or downstream processing. type-specific properties property description source relationship import definition that supplies the table. columns physical columns populated by the import. package import package that executes the load. load options import behavior such as filters, scripts, and buffer settings. compatibility and limitations the source-to-target mapping and connector determine available data and conversion behavior. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous table types next historized table"} ,{"id":386676751608,"name":"Persisting table","type":"topic","path":"/docs/reference/entity-types/table-types/entity-types-table-types-persisting-table","breadcrumb":"Reference › Entity types › Table types › Persisting table","description":"","searchText":"reference entity types table types persisting table overview persisting table is a table type that stores the physical result of a transformation. function use this type when a transformation result must be materialized for reuse or performance. selecting it is populated by a persisting definition. when to use choose persisting table when a transformation result must be materialized for reuse or performance. behavior in analyticscreator area behavior configuration configure the source transformation, target table, package, and load options. processing persisting processing writes the transformation output into the physical table. output the table provides a stored copy of the transformation result. type-specific properties property description transformation transformation that supplies the rows. target columns physical table structure receiving the output. package persisting package that executes the load. load behavior options controlling replacement, append, or related processing. compatibility and limitations the table structure must remain compatible with the transformation output. relationships related entity relationship table the table type defines the purpose and behavior of the table entity. schema the schema type and warehouse architecture influence which table types are normally used. package import, historization, and persisting packages can populate specific table types. where to configure table page tables list page table entity table types related topics table types table entity previous historized table next externally filled table"} ,{"id":383509340361,"name":"Transformation historization types","type":"subsection","path":"/docs/reference/entity-types/transformation-historization-types","breadcrumb":"Reference › Entity types › Transformation historization types","description":"","searchText":"reference entity types transformation historization types transformation historization types define how a transformation handles time-dependent data and historical states. use this section to understand the available historization options for transformations and select the appropriate behavior for your modeling scenario. available historization types actualonly actualonly is a transformation historization type for transformations that should return only the currently valid result. use it when the output must reflect the actual business state without keeping a separate... open actualonly fullhist use this historization type when the full historical state of the transformation output must remain accessible. tracks historical states across time suitable for full historization scenarios useful when change history must remain queryable open fullhist none use this historization type when only the current state of the transformation output is required. no historical state tracking simplest execution behavior suitable for current-state transformations open none snapshot use this historization type when transformation output should be evaluated for specific snapshot dates. supports point-in-time views useful for historized transformation logic can be used with snapshot dimensions open snapshot snapshothist snapshothist is a transformation historization type for transformations that should be evaluated at predefined snapshot dates while still keeping a history-aware transformation result. use it when the output must... open snapshothist how to choose a historization type use none when only current-state output is needed use snapshot when data should be viewed at selected points in time use fullhist when the full historical output of the transformation must be preserved key takeaway transformation historization types control whether a transformation returns only current data, snapshot-based data, or fully historized output. previous external transformation nextfullhist"} ,{"id":386676752595,"name":"ActualOnly","type":"topic","path":"/docs/reference/entity-types/transformation-historization-types/entity-types-transformation-historization-types-actualonly","breadcrumb":"Reference › Entity types › Transformation historization types › ActualOnly","description":"","searchText":"reference entity types transformation historization types actualonly overview actual only (actualonly) is a transformation historization type that uses only the current or active version of historized records. function use this type when the transformation should expose current-state data without previous versions. selecting it filters processing to actual records. when to use choose actual only when the transformation should expose current-state data without previous versions. behavior in analyticscreator area behavior configuration select actualonly and ensure the source exposes a reliable current-record indicator or validity rule. processing analyticscreator selects the current qualifying version for each logical record. output the result contains current-state records rather than full history. type-specific properties property description type token actualonly. current-record rule validity or status logic identifying the active row. business key key used to group record versions. filter additional current-state selection logic. compatibility and limitations current-state accuracy depends on correct validity dates or active-record flags. relationships related entity relationship transformation the selected value changes how historical rows are represented by the transformation. historized table historized source structures provide the validity and version information used by these types. where to configure transformation page transformation entity historization page transformation historization types related topics transformation historization types transformation entity previous snapshot next none"} ,{"id":386676752596,"name":"FullHist","type":"topic","path":"/docs/reference/entity-types/transformation-historization-types/entity-types-transformation-historization-types-fullhist","breadcrumb":"Reference › Entity types › Transformation historization types › FullHist","description":"","searchText":"reference entity types transformation historization types fullhist overview full history (fullhist) is a transformation historization type that includes the complete available record history in transformation processing. function use this type when all available historical versions are required. selecting it retains full historical output behavior. when to use choose full history when all available historical versions are required. behavior in analyticscreator area behavior configuration select fullhist and configure compatible history keys and validity columns. processing analyticscreator processes all qualifying versions supplied by the historized inputs. output the result can contain multiple historical versions for one business key. type-specific properties property description type token fullhist. validity columns fields used to describe record validity. business key key identifying versions of the same logical record. history filter optional conditions limiting historical output. compatibility and limitations exact results depend on source historization, validity data, joins, and filters. relationships related entity relationship transformation the selected value changes how historical rows are represented by the transformation. historized table historized source structures provide the validity and version information used by these types. where to configure transformation page transformation entity historization page transformation historization types related topics transformation historization types transformation entity previous transformation historization types next snapshot history"} ,{"id":386676752597,"name":"None","type":"topic","path":"/docs/reference/entity-types/transformation-historization-types/entity-types-transformation-historization-types-none","breadcrumb":"Reference › Entity types › Transformation historization types › None","description":"","searchText":"reference entity types transformation historization types none overview none is a transformation historization type that applies no transformation historization behavior. function use this type when the transformation does not require history-specific record selection. selecting it leaves historization-specific processing disabled. when to use choose none when the transformation does not require history-specific record selection. behavior in analyticscreator area behavior configuration select none and define ordinary transformation inputs and filters. processing analyticscreator processes rows without applying a transformation historization mode. output the result follows the normal transformation logic. type-specific properties property description type token none. inputs tables or transformations used by the logic. filter ordinary row-selection logic. output columns columns produced without history-specific behavior. compatibility and limitations historized inputs can still contain multiple versions unless ordinary filters or joins restrict them. relationships related entity relationship transformation the selected value changes how historical rows are represented by the transformation. historized table historized source structures provide the validity and version information used by these types. where to configure transformation page transformation entity historization page transformation historization types related topics transformation historization types transformation entity previous actual only next join historization types"} ,{"id":386676752598,"name":"Snapshot","type":"topic","path":"/docs/reference/entity-types/transformation-historization-types/entity-types-transformation-historization-types-snapshot","breadcrumb":"Reference › Entity types › Transformation historization types › Snapshot","description":"","searchText":"reference entity types transformation historization types snapshot overview snapshot is a transformation historization type that produces a snapshot-oriented representation of transformation data. function use this type when one point-in-time or snapshot state is required. selecting it limits output to the configured snapshot state. when to use choose snapshot when one point-in-time or snapshot state is required. behavior in analyticscreator area behavior configuration select snapshot and configure the relevant snapshot date or context. processing analyticscreator evaluates source rows for the selected snapshot context. output the result represents the state selected for the snapshot. type-specific properties property description type token snapshot. snapshot context date or snapshot identifier used by the transformation. validity columns fields used to determine the applicable version. filter additional row-selection logic. compatibility and limitations the available snapshot state depends on the quality and range of source history. relationships related entity relationship transformation the selected value changes how historical rows are represented by the transformation. historized table historized source structures provide the validity and version information used by these types. where to configure transformation page transformation entity historization page transformation historization types related topics transformation historization types transformation entity previous snapshot history next actual only"} ,{"id":386676752599,"name":"SnapshotHist","type":"topic","path":"/docs/reference/entity-types/transformation-historization-types/entity-types-transformation-historization-types-snapshothist","breadcrumb":"Reference › Entity types › Transformation historization types › SnapshotHist","description":"","searchText":"reference entity types transformation historization types snapshothist overview snapshot history (snapshothist) is a transformation historization type that represents historical records in a snapshot-oriented transformation flow. function use this type when historical output must be evaluated at one or more snapshot points. selecting it applies snapshot-history behavior. when to use choose snapshot history when historical output must be evaluated at one or more snapshot points. behavior in analyticscreator area behavior configuration select snapshothist and configure the snapshot context and compatible validity information. processing analyticscreator evaluates historical source records according to the snapshot-oriented configuration. output the result provides historical values associated with snapshot processing. type-specific properties property description type token snapshothist. snapshot context date or snapshot information used by processing. validity columns fields used to select historical records. business key key linking versions of one logical record. compatibility and limitations exact snapshot selection depends on transformation configuration and available history fields. relationships related entity relationship transformation the selected value changes how historical rows are represented by the transformation. historized table historized source structures provide the validity and version information used by these types. where to configure transformation page transformation entity historization page transformation historization types related topics transformation historization types transformation entity previous full history next snapshot"} ,{"id":383509396689,"name":"Transformation types","type":"subsection","path":"/docs/reference/entity-types/transformation-types","breadcrumb":"Reference › Entity types › Transformation types","description":"","searchText":"reference entity types transformation types transformation types define how logic is implemented and executed in analyticscreator. they determine whether a transformation is generated automatically, maintained manually, executed externally, or used for a specific modeling purpose such as data marts or unions. use this section to understand the available transformation types and choose the appropriate one for your modeling and execution scenario. available transformation types datamart transformation used to expose data in a form intended for analytical consumption in the data mart layer. consumption-oriented structure typical basis for facts and dimensions used in reporting-facing models open datamart transformation direct-connector transformation used when transformation logic is tied directly to a connector-based source or source-side access pattern. connector-oriented processing useful for direct source integration scenarios bridges source access and transformation logic open direct-connector transformation external transformation used when transformation logic is implemented outside the standard generated sql transformation flow. external execution logic useful for integration with external processing suitable when logic is not managed as standard generated sql open external transformation manual transformation used when transformation logic is written manually instead of being generated automatically from metadata. manual sql definition maximum flexibility useful for special-case logic open manual transformation regular transformation standard generated transformation type used for typical sql-based transformation logic. common default transformation type usually generated as sql view logic suitable for most modeling scenarios open regular transformation script transformation used when transformation logic is implemented through script-based execution instead of standard generated sql view logic. script-driven transformation behavior useful for non-standard processing steps supports custom execution logic open script transformation union transformation used to combine multiple compatible inputs into a single transformation result. combines multiple sources or transformations useful for consolidation scenarios supports structurally aligned inputs open union transformation how to choose a transformation type use regular transformation for standard generated sql-based transformation logic use datamart transformation for reporting and analytical output structures use manual transformation when the logic must be written explicitly use script transformation or external transformation for non-standard execution patterns use union transformation when multiple inputs must be merged into one output use direct-connector transformation when the transformation is tightly coupled to connector-based source access key takeaway transformation types define how transformation logic is generated, maintained, and executed in analyticscreator, and should be selected based on the required level of automation, flexibility, and execution pattern. previous datavault satellite nextregular transformation"} ,{"id":386692502716,"name":"Datamart transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-datamart-transformation","breadcrumb":"Reference › Entity types › Transformation types › Datamart transformation","description":"","searchText":"reference entity types transformation types datamart transformation overview data mart transformation is a transformation type that represents transformation logic used to create or support data mart dimensions and facts. function use this type when the transformation should participate in dimensional model generation. selecting it adds data mart and model-oriented behavior. when to use choose data mart transformation when the transformation should participate in dimensional model generation. behavior in analyticscreator area behavior configuration configure whether the transformation represents a dimension or fact and maintain its model-facing properties. processing analyticscreator can use the transformation to create or update model dimensions, facts, and related outputs. output the transformation contributes dimension or fact structures to a data mart model. type-specific properties property description dimension or fact role model role represented by the transformation. friendly metadata business-facing names and descriptions. model relationships dimension and fact associations. output structure columns and keys used by the model. compatibility and limitations the transformation must provide suitable keys, attributes, measures, and relationships for its model role. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous script transformation next union transformation"} ,{"id":386692502717,"name":"Direct-connector transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-direct-connector-transformation","breadcrumb":"Reference › Entity types › Transformation types › Direct-connector transformation","description":"","searchText":"reference entity types transformation types direct-connector transformation overview direct-connector transformation is a transformation type that reads from a connector directly within a transformation flow. function use this type when connector data should be processed without first creating a conventional imported staging table. selecting it uses direct connector access during transformation processing. when to use choose direct-connector transformation when connector data should be processed without first creating a conventional imported staging table. behavior in analyticscreator area behavior configuration configure the connector, source selection or statement, output columns, and execution settings. processing analyticscreator requests source data from the connector as part of the transformation. output the transformation produces output directly from connector-provided data. type-specific properties property description connector connector used by the transformation. source or statement external data selection used by the direct flow. output columns columns produced from connector data. execution options runtime settings for direct access. compatibility and limitations availability and performance depend on the connector and supported direct-access capabilities. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous union transformation next transformation historization types"} ,{"id":386692502718,"name":"External transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-external-transformation","breadcrumb":"Reference › Entity types › Transformation types › External transformation","description":"","searchText":"reference entity types transformation types external transformation overview external transformation is a transformation type that represents transformation work executed outside the standard generated sql flow. function use this type when an external executable, service, or process performs the transformation. selecting it delegates processing to an external transformation mechanism. when to use choose external transformation when an external executable, service, or process performs the transformation. behavior in analyticscreator area behavior configuration configure the transformation metadata, external execution details, and package assignment. processing the external process performs the transformation when its package runs. output the resulting data or side effect is supplied by the external process. type-specific properties property description external command or process operation that performs the transformation. package external package that executes the transformation. parameters values passed to the external operation. dependencies objects that must exist before execution. compatibility and limitations runtime behavior, logging, and error handling depend on the external process. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous manual transformation next script transformation"} ,{"id":386692502719,"name":"Manual transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-manual-transformation","breadcrumb":"Reference › Entity types › Transformation types › Manual transformation","description":"","searchText":"reference entity types transformation types manual transformation overview manual transformation is a transformation type that defines transformation output through manually maintained sql or view text. function use this type when the required logic cannot or should not be modeled with the standard editor. selecting it uses user-maintained sql as the transformation definition. when to use choose manual transformation when the required logic cannot or should not be modeled with the standard editor. behavior in analyticscreator area behavior configuration maintain the transformation metadata and the manual sql or view definition. processing analyticscreator uses the supplied definition instead of composing all logic from standard metadata. output the transformation produces the result defined by the maintained sql. type-specific properties property description view definition manual sql or view text. schema and name location and technical name of the transformation. description business purpose of the manual transformation. dependencies objects referenced by the manual sql. compatibility and limitations analyticscreator cannot fully validate or infer all dependencies in manually maintained sql. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous regular transformation next external transformation"} ,{"id":386692502720,"name":"Regular transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-regular-transformation","breadcrumb":"Reference › Entity types › Transformation types › Regular transformation","description":"","searchText":"reference entity types transformation types regular transformation overview regular transformation is a transformation type that defines transformation logic through analyticscreator-managed inputs, joins, columns, filters, and references. function use this type when logic should be modeled using the standard transformation editor. selecting it generates standard transformation output from maintained metadata. when to use choose regular transformation when logic should be modeled using the standard transformation editor. behavior in analyticscreator area behavior configuration configure source tables, joins, output columns, filters, references, and related properties. processing analyticscreator composes the maintained metadata into executable transformation logic. output the transformation produces a generated result such as a view or compatible downstream input. type-specific properties property description source tables input tables used by the transformation. joins and references relationships connecting the inputs. output columns columns and expressions produced by the transformation. filter row-selection logic applied to the transformation. compatibility and limitations all selected inputs and expressions must be compatible with the target database platform. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous transformation types next manual transformation"} ,{"id":386692502721,"name":"Script transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-script-transformation","breadcrumb":"Reference › Entity types › Transformation types › Script transformation","description":"","searchText":"reference entity types transformation types script transformation overview script transformation is a transformation type that defines transformation work through a maintained script. function use this type when processing is best represented as a script rather than a generated relational view. selecting it executes maintained script logic. when to use choose script transformation when processing is best represented as a script rather than a generated relational view. behavior in analyticscreator area behavior configuration configure the script statement, package, and any required parameters or dependencies. processing the script package executes the transformation statement. output the output or side effect is determined by the script. type-specific properties property description script statement sql or supported script logic. package script package that executes the transformation. parameters values used by the script where supported. dependencies required upstream objects or packages. compatibility and limitations analyticscreator cannot guarantee the behavior of arbitrary script logic beyond available validation. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous external transformation next data mart transformation"} ,{"id":386692502722,"name":"Union transformation","type":"topic","path":"/docs/reference/entity-types/transformation-types/entity-types-transformation-types-union-transformation","breadcrumb":"Reference › Entity types › Transformation types › Union transformation","description":"","searchText":"reference entity types transformation types union transformation overview union transformation is a transformation type that combines compatible transformation inputs into a unified result. function use this type when multiple inputs share a compatible output structure and should be appended. selecting it uses union-style combination behavior. when to use choose union transformation when multiple inputs share a compatible output structure and should be appended. behavior in analyticscreator area behavior configuration configure the participating inputs, column alignment, and output metadata. processing analyticscreator combines rows from the configured inputs according to union semantics. output the transformation produces one result containing rows from all compatible inputs. type-specific properties property description inputs transformations or tables included in the union. column alignment mapping between corresponding output columns. union behavior duplicate-preserving or duplicate-removing behavior where supported. output columns unified result structure. compatibility and limitations input column counts and data types must be compatible. relationships related entity relationship transformation the transformation type determines the transformation's authoring and runtime behavior. table transformations can read from tables or create table-related output. package persisting, external, script, and workflow packages can process transformation work. where to configure transformation page transformations list page transformation entity transformation types related topics transformation types transformation entity previous data mart transformation next direct-connector transformation"} ,{"id":383461259457,"name":"Parameters","type":"section","path":"/docs/reference/parameters","breadcrumb":"Reference › Parameters","description":"","searchText":"reference parameters parameters are configuration values that control how analyticscreator imports metadata, generates objects, refreshes sources, builds packages, deploys artifacts, and applies project-wide conventions. use this section to look up a setting, understand the default value, and find the parameter group that controls a specific part of the data warehouse lifecycle. parameter groups connectors stores connector-specific defaults and connection-related values. open connectors csv import controls how csv files are scanned and interpreted during source import. open csv import data vault controls data vault generation behavior and relationship naming. open data vault deployment configures generated database objects and deployment artifacts. open deployment diagrams controls diagram export behavior and thumbnail diagram display settings. open diagrams dwh wizard defines defaults used when the dwh wizard creates generated structures. open dwh wizard engine timeout defines timeout behavior for engine-driven execution tasks. open engine timeout governance controls inheritance and anonymization behavior for governed metadata. open governance historization configures historization and persisting behavior. open historization logging controls diagnostic logging behavior. open logging naming & metadata defines naming, friendly-name, description, and display-folder patterns. open naming & metadata other parameters reserved for parameters that do not have a more specific functional group. open other parameters project limits controls project file-name and file-path restrictions. open project limits references configures generated references and relationship inheritance. open references repository names defines naming labels used for repository layers. open repository names sap connector configures sap connector defaults and sap-specific import behavior. open sap connector semantic model controls default semantic-model naming and display-folder behavior. open semantic model source import controls source import query behavior. open source import source refresh controls metadata refresh and source-preview behavior. open source refresh sql templates stores sql templates and variables used during generated sql execution. open sql templates ssis packages controls generated ssis package buffering, fast-load, and execution behavior. open ssis packages synchronization configures synchronization, retry, and metadata-update behavior. open synchronization technical configuration parameters highlights technical settings that also appear in functional parameter groups. open technical configuration parameters transformations controls transformation naming, relation use, calendar fields, and generated views. open transformations previous model nextdata vault"} ,{"id":389870784720,"name":"Connectors","type":"subsection","path":"/docs/reference/parameters/parameters-connectors","breadcrumb":"Reference › Parameters › Connectors","description":"","searchText":"reference parameters connectors stores connector-specific defaults and connection-related values. use this page to find the connectors settings, review their defaults, and open the detailed parameter pages. available parameters parameter technical name default value purpose azure blob connection string azure_blob_connection_string defaultendpointsprotocol=https;accountname={0};accountkey={1};endpointsuffix=core.windows.net connection string for azure blob storage. odata connection string odata_connection_string service document url={0};include atom elements=auto;include expanded entities=false;persist security info=false;time out=600;schema sample size=25;retry count=5;retry sleep=100;keep alive=false;max received message size=4398046511104 connection string for the odata service. oledb provider sql server oledbprovider_sqlserver msoledbsql oledb provider for sql server. previous delete unused references on delete columns nextoledb provider sql server"} ,{"id":389870937304,"name":"Azure BLOB Connection String","type":"topic","path":"/docs/reference/parameters/parameters-connectors/parameters-connectors-azure-blob-connection-string","breadcrumb":"Reference › Parameters › Connectors › Azure BLOB Connection String","description":"","searchText":"reference parameters connectors azure blob connection string overview azure blob connection string is a connectors parameter that stores the connection string for azure blob storage. function use this setting to keep connector setup and source connection defaults consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {0}, {1}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value defaultendpointsprotocol=https;accountname={0};accountkey={1};endpointsuffix=core.windows.net custom value not set. where it is used this parameter belongs to the connectors group and is used when analyticscreator applies connector setup and source connection defaults. setting value technical parameter name azure_blob_connection_string default value defaultendpointsprotocol=https;accountname={0};accountkey={1};endpointsuffix=core.windows.net custom value not set. parameter groups group connectors connections connector setup related topics connectors odata connection string parameters previous oledb provider sql server nextodata connection string"} ,{"id":389870937305,"name":"OData Connection String","type":"topic","path":"/docs/reference/parameters/parameters-connectors/parameters-connectors-odata-connection-string","breadcrumb":"Reference › Parameters › Connectors › OData Connection String","description":"","searchText":"reference parameters connectors odata connection string overview odata connection string is a connectors parameter that stores the connection string for the odata service. function use this setting to keep connector setup and source connection defaults consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {0}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value service document url={0};include atom elements=auto;include expanded entities=false;persist security info=false;time out=600;schema sample size=25;retry count=5;retry sleep=100;keep alive=false;max received message size=4398046511104 custom value not set. where it is used this parameter belongs to the connectors group and is used when analyticscreator applies connector setup and source connection defaults. setting value technical parameter name odata_connection_string default value service document url={0};include atom elements=auto;include expanded entities=false;persist security info=false;time out=600;schema sample size=25;retry count=5;retry sleep=100;keep alive=false;max received message size=4398046511104 custom value not set. parameter groups group connectors connections connector setup related topics connectors azure blob connection string oledb provider sql server parameters previous azure blob connection string nextrepository names"} ,{"id":388515715285,"name":"OLEDB Provider SQL Server","type":"topic","path":"/docs/reference/parameters/parameters-connectors/parameters-connectors-oledb-provider-sql-server","breadcrumb":"Reference › Parameters › Connectors › OLEDB Provider SQL Server","description":"","searchText":"reference parameters connectors oledb provider sql server overview oledb provider sql server is a connectors parameter that selects the oledb provider for sql server. function use this setting to keep connector setup and source connection defaults consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value msoledbsql custom value not set. where it is used this parameter belongs to the connectors group and is used when analyticscreator applies connector setup and source connection defaults. setting value technical parameter name oledbprovider_sqlserver default value msoledbsql custom value not set. parameter groups group connectors connections connector setup related topics connectors odata connection string parameters previous connectors nextazure blob connection string"} ,{"id":389870784711,"name":"CSV Import","type":"subsection","path":"/docs/reference/parameters/parameters-csv-import","breadcrumb":"Reference › Parameters › CSV Import","description":"","searchText":"reference parameters csv import controls how csv files are scanned and interpreted during source import. use this page to find the csv import settings, review their defaults, and open the detailed parameter pages. available parameters parameter technical name default value purpose csv empty string length csv_empty_string_length 50 length of empty string fields. csv min string length csv_min_string_length 50 minimum length of string fields. csv scan rows csv_scan_rows 500 count of rows scanned to get the field properties. previous ssis not store connection strings in package nextcsv scan rows"} ,{"id":389872720064,"name":"CSV Empty String Length","type":"topic","path":"/docs/reference/parameters/parameters-csv-import/parameters-csv-import-csv-empty-string-length","breadcrumb":"Reference › Parameters › CSV Import › CSV Empty String Length","description":"","searchText":"reference parameters csv import csv empty string length overview csv empty string length is a csv import parameter that sets the length of empty string fields. function use this setting to keep csv import profiling and field detection consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 50 custom value not set. where it is used this parameter belongs to the csv import group and is used when analyticscreator applies csv import profiling and field detection. setting value technical parameter name csv_empty_string_length default value 50 custom value not set. parameter groups group csv import csv profiling csv related topics csv import csv min string length parameters previous csv scan rows nextcsv min string length"} ,{"id":389872720065,"name":"CSV Min String Length","type":"topic","path":"/docs/reference/parameters/parameters-csv-import/parameters-csv-import-csv-min-string-length","breadcrumb":"Reference › Parameters › CSV Import › CSV Min String Length","description":"","searchText":"reference parameters csv import csv min string length overview csv min string length is a csv import parameter that sets the minimum length of string fields. function use this setting to keep csv import profiling and field detection consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 50 custom value not set. where it is used this parameter belongs to the csv import group and is used when analyticscreator applies csv import profiling and field detection. setting value technical parameter name csv_min_string_length default value 50 custom value not set. parameter groups group csv import csv profiling csv related topics csv import csv empty string length csv scan rows parameters previous csv empty string length nextsynchronization"} ,{"id":389872720063,"name":"CSV Scan Rows","type":"topic","path":"/docs/reference/parameters/parameters-csv-import/parameters-csv-import-csv-scan-rows","breadcrumb":"Reference › Parameters › CSV Import › CSV Scan Rows","description":"","searchText":"reference parameters csv import csv scan rows overview csv scan rows is a csv import parameter that sets the number of rows scanned to get the field properties. function use this setting to keep csv import profiling and field detection consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 500 custom value not set. where it is used this parameter belongs to the csv import group and is used when analyticscreator applies csv import profiling and field detection. setting value technical parameter name csv_scan_rows default value 500 custom value not set. parameter groups group csv import csv profiling csv related topics csv import csv min string length parameters previous csv import nextcsv empty string length"} ,{"id":389870784705,"name":"Data Vault","type":"subsection","path":"/docs/reference/parameters/parameters-data-vault","breadcrumb":"Reference › Parameters › Data Vault","description":"","searchText":"reference parameters data vault controls data vault generation behavior and relationship naming. use this page to find the data vault settings, review their defaults, and open the detailed parameter pages. available parameters parameter technical name default value purpose data vault 2 create hubs datavault2_create_hubs 1 data vault 2 create hubs: 0 - no, 1 - yes. show hub deps show_hub_deps 0 show vault hub dependencies. vault fk field name pattern vault_fk_fieldname_pattern vault_hub_id_{tablename} autogenerated foreign key field name corresponding to the vault hub id. you can use {schemaname}, {tablename}, {friendlyname}, {schemaid}, {tableid} and {columnname} placeholders. previous parameters nextvault fk field name pattern"} ,{"id":389871308995,"name":"Data Vault 2 Create Hubs","type":"topic","path":"/docs/reference/parameters/parameters-data-vault/parameters-data-vault-data-vault-2-create-hubs","breadcrumb":"Reference › Parameters › Data Vault › Data Vault 2 Create Hubs","description":"","searchText":"reference parameters data vault data vault 2 create hubs overview data vault 2 create hubs is a data vault parameter that controls whether data vault 2 hubs are created (0 - no, 1 - yes). function use this setting to keep data vault object generation consistent across the project. numeric values in this parameter act as choices; use the description to interpret each option. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the data vault group and is used when analyticscreator applies data vault object generation. setting value technical parameter name datavault2_create_hubs default value 1 custom value not set. parameter groups group data vault vault & deps vault related topics data vault show hub deps parameters previous show hub deps nextsap connector"} ,{"id":389871308994,"name":"Show Hub Deps","type":"topic","path":"/docs/reference/parameters/parameters-data-vault/parameters-data-vault-show-hub-deps","breadcrumb":"Reference › Parameters › Data Vault › Show Hub Deps","description":"","searchText":"reference parameters data vault show hub deps overview show hub deps is a data vault parameter that controls whether analyticscreator shows vault hub dependencies. function use this setting to keep data vault object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 0 custom value not set. where it is used this parameter belongs to the data vault group and is used when analyticscreator applies data vault object generation. setting value technical parameter name show_hub_deps default value 0 custom value not set. parameter groups group data vault vault & deps vault related topics data vault data vault 2 create hubs vault fk field name pattern parameters previous vault fk field name pattern nextdata vault 2 create hubs"} ,{"id":389871308993,"name":"Vault FK Field Name Pattern","type":"topic","path":"/docs/reference/parameters/parameters-data-vault/parameters-data-vault-vault-fk-field-name-pattern","breadcrumb":"Reference › Parameters › Data Vault › Vault FK Field Name Pattern","description":"","searchText":"reference parameters data vault vault fk field name pattern overview vault fk field name pattern is a data vault parameter that defines the autogenerated foreign key field name corresponding to the vault hub id. you can use {schemaname}, {tablename}, {friendlyname}, {schemaid}, {tableid} and {columnname} placeholders. function use this setting to keep data vault object generation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. keep placeholder names unchanged when adapting the pattern. this value supports placeholders such as {tablename}, {schemaname}, {friendlyname}, {schemaid}, {tableid}, {columnname}. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value vault_hub_id_{tablename} custom value not set. where it is used this parameter belongs to the data vault group and is used when analyticscreator applies data vault object generation. setting value technical parameter name vault_fk_fieldname_pattern default value vault_hub_id_{tablename} custom value not set. parameter groups group data vault vault & deps vault related topics data vault show hub deps parameters previous data vault nextshow hub deps"} ,{"id":389870784714,"name":"Deployment","type":"subsection","path":"/docs/reference/parameters/parameters-deployment","breadcrumb":"Reference › Parameters › Deployment","description":"","searchText":"reference parameters deployment configures generated database objects and deployment artifacts. use this page to find the deployment settings, review their defaults, and open the detailed parameter pages. available parameters parameter technical name default value purpose dacpac model storage type dacpac_model_storage_type 1 dacpac model storage type: 0-file, 1-memory. deployment create subdirectory deployment_create_subdirectory 1 create a subdirectory for every created deployment package. 0-no (all files in output directory will be deleted), 1-yes. default - 1. deployment do not drop object types deployment_do_not_drop_object_types aggregates,applicationroles,assemblies,asymmetrickeys,brokerpriorities,certificates,contracts,databaseroles,databasetriggers,fulltextcatalogs,fulltextstoplists,messagetypes,partitionfunctions,partitionschemes,permissions,queues,remoteservicebindings,rolemembership,rules,searchpropertylists,sequences,services,signatures,symmetrickeys,synonyms,userdefineddatatypes,userdefinedtabletypes,clruserdefinedtypes,users,xmlschemacollections,audits,credentials,cryptographicproviders,databaseauditspecifications,endpoints,errormessages,eventnotifications,eventsessions,linkedserverlogins,linkedservers,logins,routes,serverauditspecifications,serverrolemembership,serverroles,servertriggers comma-separated list of object types (see description of sqlpackage.exe). dwh metadata in extended properties dwh_metadata_in_extended_properties 1 store metadata as extended properties of database objects. index compression type index_compression_type 1 default index compression type in case table compression type is none or columnstore index (otherwise indexes will have the same compression type as tables): 1-none, 2-page, 3-row. table compression type table_compression_type 1 default table compression type: 1-none, 2-page, 3-row, 4-columnstore index. previous objectscript timeout nexttable compression type"} ,{"id":389871310018,"name":"DACPAC Model Storage Type","type":"topic","path":"/docs/reference/parameters/parameters-deployment/parameters-deployment-dacpac-model-storage-type","breadcrumb":"Reference › Parameters › Deployment › DACPAC Model Storage Type","description":"","searchText":"reference parameters deployment dacpac model storage type overview dacpac model storage type is a deployment parameter that controls the dacpac model storage type: 0 - file, 1 - memory. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name dacpac_model_storage_type default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment deployment create subdirectory parameters previous deployment create subdirectory nextdwh metadata in extended properties"} ,{"id":388515715281,"name":"Deployment Create Subdirectory","type":"topic","path":"/docs/reference/parameters/parameters-deployment/parameters-deployment-deployment-create-subdirectory","breadcrumb":"Reference › Parameters › Deployment › Deployment Create Subdirectory","description":"","searchText":"reference parameters deployment deployment create subdirectory overview deployment create subdirectory is a deployment parameter that controls whether analyticscreator creates a subdirectory for every created deployment package. 0-no (all files in output directory will be deleted), 1-yes. default - 1. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name deployment_create_subdirectory default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment dacpac model storage type deployment do not drop object types parameters previous deployment do not drop object types nextdacpac model storage type"} ,{"id":389871310017,"name":"Deployment Do Not Drop Object Types","type":"topic","path":"/docs/reference/parameters/parameters-deployment/parameters-deployment-deployment-do-not-drop-object-types","breadcrumb":"Reference › Parameters › Deployment › Deployment Do Not Drop Object Types","description":"","searchText":"reference parameters deployment deployment do not drop object types overview deployment do not drop object types is a deployment parameter that controls the comma-separated list of object types (see the description of sqlpackage.exe). function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value aggregates,applicationroles,assemblies,asymmetrickeys,brokerpriorities,certificates,contracts,databaseroles,databasetriggers,fulltextcatalogs,fulltextstoplists,messagetypes,partitionfunctions,partitionschemes,permissions,queues,remoteservicebindings,rolemembership,rules,searchpropertylists,sequences,services,signatures,symmetrickeys,synonyms,userdefineddatatypes,userdefinedtabletypes,clruserdefinedtypes,users,xmlschemacollections,audits,credentials,cryptographicproviders,databaseauditspecifications,endpoints,errormessages,eventnotifications,eventsessions,linkedserverlogins,linkedservers,logins,routes,serverauditspecifications,serverrolemembership,serverroles,servertriggers custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name deployment_do_not_drop_object_types default value aggregates,applicationroles,assemblies,asymmetrickeys,brokerpriorities,certificates,contracts,databaseroles,databasetriggers,fulltextcatalogs,fulltextstoplists,messagetypes,partitionfunctions,partitionschemes,permissions,queues,remoteservicebindings,rolemembership,rules,searchpropertylists,sequences,services,signatures,symmetrickeys,synonyms,userdefineddatatypes,userdefinedtabletypes,clruserdefinedtypes,users,xmlschemacollections,audits,credentials,cryptographicproviders,databaseauditspecifications,endpoints,errormessages,eventnotifications,eventsessions,linkedserverlogins,linkedservers,logins,routes,serverauditspecifications,serverrolemembership,serverroles,servertriggers custom value not set. parameter groups group deployment database options storage related topics deployment deployment create subdirectory dwh metadata in extended properties parameters previous index compression type nextdeployment create subdirectory"} ,{"id":388515715283,"name":"DWH Metadata In Extended Properties","type":"topic","path":"/docs/reference/parameters/parameters-deployment/parameters-deployment-dwh-metadata-in-extended-properties","breadcrumb":"Reference › Parameters › Deployment › DWH Metadata In Extended Properties","description":"","searchText":"reference parameters deployment dwh metadata in extended properties overview dwh metadata in extended properties is a deployment parameter that controls whether metadata is stored as extended properties of database objects. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name dwh_metadata_in_extended_properties default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment deployment do not drop object types index compression type parameters previous dacpac model storage type nexthistorization"} ,{"id":389871310016,"name":"Index Compression Type","type":"topic","path":"/docs/reference/parameters/parameters-deployment/parameters-deployment-index-compression-type","breadcrumb":"Reference › Parameters › Deployment › Index Compression Type","description":"","searchText":"reference parameters deployment index compression type overview index compression type is a deployment parameter that controls the default index compression type when the table compression type is none or columnstore index (otherwise indexes will have the same compression type as tables): 1-none, 2-page, 3-row. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name index_compression_type default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment dwh metadata in extended properties table compression type parameters previous table compression type nextdeployment do not drop object types"} ,{"id":388515715288,"name":"Table Compression Type","type":"topic","path":"/docs/reference/parameters/parameters-deployment/parameters-deployment-table-compression-type","breadcrumb":"Reference › Parameters › Deployment › Table Compression Type","description":"","searchText":"reference parameters deployment table compression type overview table compression type is a deployment parameter that controls the default table compression type: 1 - none, 2 - page, 3 - row, 4 - columnstore index. function use this setting to keep deployment and generated database artifact creation consistent across the project. analyticscreator uses this value when no custom value is saved for the project. access the parameter is maintained from the parameters list in analyticscreator. how to access navigation tree parameters->list parameters toolbar options->parameter diagram not opened from the diagram. visual element parameter list default value 1 custom value not set. where it is used this parameter belongs to the deployment group and is used when analyticscreator applies deployment and generated database artifact creation. setting value technical parameter name table_compression_type default value 1 custom value not set. parameter groups group deployment database options storage related topics deployment index compression type parameters previous deployment nextindex compression type"} ,{"id":389870784716,"name":"Diagrams","type":"subsection","path":"/docs/reference/parameters/parameters-diagrams","breadcrumb":"Reference › Parameters › Diagrams","description":"","searchText":"reference parameters diagrams controls diagram export behavior and thumbnail diagram display settings. use this page to find the diagrams settings, review their defaults, and open the detailed parameter pages. available parameters parameter technical name default value purpose diagram to picture scale diagram_to_picture_scale 1.0 scale of the diagram when saving it as a picture. floating number between 0.0 and 2.0 using dot as decimal separator. the higher the value, the better the picture quality and the greater the file size. when 0, the current diagram scale will be used. default: 1.0. thumbnail diagram dock thumbnail_diagram_dock 4 0 - no dock, 1 - left top corner, 2 - right top corner, 3 - left down corner, 4 - right down corner. thumbnail diagram height thumbnail_diagram_height 300 height (points). thumbnail diagram left thumbnail_diagram_left 0 left (points). thumbnail diagram margin thumbnail_diagram_margin 30 margin (points). thumbnail diagram show thumbnail_diagram_show 1 0 - do not show, 1 - show. thumbnail diagram top thumbnail_diagram_top 0 top (points). thumbnail diagram width thumbnail_diagram_width 300 width (points). previous hist empty record field name nextthumbnail diagram show"}