Functions & Features

• Full BI-Stack Automation: From source to data warehouse through to frontend.
• Holistic Data Model: Complete view of the entire Data Model. This also allows for rapid prototyping of various models.
• Data Warehouses: MS SQL Server 2012-2022, Azure SQL Database, Azure Synapse Analytics dedicated.
• Analytical Databases: SSAS Tabular Databases, SSAS Multidimensional Databases, Azure Synapse Analytics dedicated, Power BI, Power BI Premium, Tableau, and Qlik Sense.
• Data Lakes: MS Azure Blob Storage.
• Frontends: Power BI, Qlik Sense, Tableau, PowerPivot (Excel).
• Pipelines/ETL: SQL Server Integration Packages (SSIS), Azure Data Factory 2.0 pipelines, Azure Data Bricks.
• Azure: Azure SQL Server, Azure Data Factory Pipelines.
• Deployment: Visual Studio Solution (SSDT), Creation of DACPAC files, SSIS packages, Data Factory ARM templates, XMLA files.
• Modelling Approaches: Top-down modelling, Bottom-up modelling, import from external modelling tool, Dimensional/Kimball, Data Vault 2.0, Mixed approach of DV 2.0 and Kimball (A combination the best of both worlds by using elements of both Data Vault 2.0 and Kimball modelling), Inmon, 3NF, or any custom data model. The AnalyticsCreator wizard can help you create a data vault model automatically and also supports strict Dan Linstead techniques and data vaults.
• Historization Approaches: Slowly changing dimensions (SCD) type 0, type 1, type 2, mixed, SnapShot historization, Gapless historization, Change-based calculations.
• Surrogate Key: Auto-increment, long integer, Hash key, custom definition of hash algorithm.
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• Windows GUI Embedded version control Multi-user development supporting distributed development Manual object locking possible Predefined templates Cloud-based repository Cloud service support available Data Lineage Macro language for more flexible development Predefined, datatype-based transformations

  Calculated columns in each DWH table Single point development: the whole design is possible in AnalyticsCreator. External development not necessary Embedding external code Automatic documentation in Word and Visio Export to Microsoft DevOps, GitHub, .. AnalyticsCreator repository is stored in a MS SQL Server and can be modified and extended with additional functionality Online Wiki

• ETL procedure protocol
• Error handling on ETL procedures
• Consistency on ETL failure
• Rollback on ETL procedures
• Automatic recognition of source structure changes and automatic adaptation of connected DWH
• Entire DWH life-cycle support
• Delta and full load of data models
• Near real-time data loads possible
• External orchestration/scheduling for ETL process
• Internal orchestration/scheduling for ETL process with generated MS-SSIS packages
• Several workflow configurations
• No is necessary runtime for AnalyticsCreator
• Daily processing of created DHWs are run without AnalyticsCreator
• No additional licences necessary
• For design component no MS SQL Server necessary

• Build-in Connectivity: MS SQL Server, Oracle, SAP ERP, S4/HANA with Theobald Software (ODP, DeltaQ/Tables), SAP Business One with AnalyticsCreator own connectivity, SAP ODP objects, Excel, Access, CSV/Text, OLEDB (e.g. Terradata, Netezza, DB2..), ODBC (MySQL, …) , OData , Azure Blob Storage (CSV, Parquet, Avro), REST, MS Sharepoint, Google Ads, Amazon, Salesforce CRM, Hubspot CRM, MS Dynamics 365 Business Central, MS Dynamics Navision
• 3rd party Connectivity: Access to more than 250+ data source with C-Data connector [www.cdata.com/drivers]. This allows for connection to AnalyticsCreator directly by an ODBC, or OLE DB driver, or by connecting an ingest layer with externally filled tables.
• Define Your Own Connectivity: (Any data source, Hadoop, Google BigQuery/Analytics, Amazon, Shop solutions, Facebook, LinkedIn, X (formerly Twitter)) In all cases of access to source data an AnalyticsCreator-metadata-connector is created. The AnalyticsCreator -metadata-connector is a description of data-sources you use for more easy handling in AnalyticsCreator. AnalyticsCreator is able to automatically create a metadata connector by extracting the data definition from your source data. it contains information about key fields, referential integrity, name of fields and description.

• Azure blob storage, Text, CSV files, any target system using OLEDB or ODBC driver, automated type conversation, Export performed by SSIS packages or Azure Data Factory pipelines
• Export for example to Oracle, Snowflake, Synapse

Push Concept: Power BI, Tableau, and Qlik models will be created automatically. All models described here will be created at the same time.

Pull Concept: There are many BI Frontends around which allows you to connect with the specified Microsoft data. Check with your vendor or us what is possible. AnalyticsCreator allows you to develop a specific solution for your Analytics Frontend in the way that the model will be created automatically for your BI Frontend (Push concept).