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SQL Server Analysis Services (SSAS)

AnalyticsCreator generates SQL Server Analysis Services (SSAS) Tabular and Multidimensional analytical models from the metadata and analytical definitions maintained in the AnalyticsCreator project. The generated models are deployed to and executed by Microsoft Analysis Services without requiring an AnalyticsCreator production runtime.

Overview

AnalyticsCreator supports SQL Server Analysis Services as an analytical target for metadata-driven data warehouse implementations.

Dimensions, facts, relationships, measures, hierarchies, partitions, security definitions and other supported analytical metadata are maintained as part of the AnalyticsCreator design and used to generate the corresponding Analysis Services model.

AnalyticsCreator supports both SSAS Tabular and SSAS Multidimensional models. AnalyticsCreator provides the design and generation layer; Microsoft Analysis Services hosts, processes and serves the deployed analytical model.

Supported Analysis Services Models

  • SQL Server Analysis Services Tabular
  • SQL Server Analysis Services Multidimensional

The appropriate model type depends on the analytical architecture and Microsoft Analysis Services environment selected for the project.

Tabular and Multidimensional are separate Analysis Services server modes. The target Analysis Services instance must therefore be configured for the model type being deployed.

What AnalyticsCreator Generates

Depending on the selected analytical model and project configuration, AnalyticsCreator can generate analytical definitions including:

  • analytical tables and dimensions
  • facts and their analytical structures
  • relationships between analytical objects
  • measures
  • hierarchies
  • calculated analytical definitions where configured
  • partitions
  • perspectives
  • OLAP roles and supported security definitions
  • model metadata derived from the AnalyticsCreator design

For deployment, AnalyticsCreator can generate XMLA scripts for both Tabular and Multidimensional Analysis Services models.

SSAS Tabular

AnalyticsCreator can generate SSAS Tabular models from the analytical structures defined in the project.

The generated model can include tables, relationships, measures, hierarchies, calculated DAX columns, partitions, perspectives and other supported Tabular metadata.

AnalyticsCreator also provides configuration for the target Tabular server, database name, compatibility level, connector and model name, together with options for model creation and processing during deployment.

This keeps AnalyticsCreator-owned analytical definitions aligned with the wider data warehouse design rather than requiring the semantic structure to be recreated independently.

SSAS Multidimensional

AnalyticsCreator can generate SSAS Multidimensional models for projects that use multidimensional OLAP architectures.

The generated model can represent dimensions, facts, hierarchies, measures and other supported analytical structures as Microsoft Analysis Services multidimensional objects.

AnalyticsCreator provides deployment configuration for the target Multidimensional server and database, compatibility level, partitions, perspectives, model creation and processing.

This supports organisations that continue to operate established Multidimensional Analysis Services environments while maintaining the analytical design through AnalyticsCreator.

Measures and Calculated Definitions

Measures are maintained as analytical definitions within the AnalyticsCreator data mart design.

AnalyticsCreator measures can define aggregations or explicit analytical expressions and are used when generating the corresponding analytical model.

For Tabular models, AnalyticsCreator also supports DAX calculated-column definitions where required by the analytical design.

Saving a measure or calculated definition updates the AnalyticsCreator project metadata. Generation, deployment and processing of the analytical model remain separate steps.

Hierarchies

AnalyticsCreator can maintain OLAP hierarchy definitions for analytical navigation and reporting.

Hierarchy definitions are associated with the analytical model and can be included in the generated Analysis Services output where configured.

Partitions

AnalyticsCreator supports partition definitions for Analysis Services models.

For Multidimensional models, partitions apply to fact structures. For Tabular models, partitions can be defined for facts or dimensions according to the analytical design.

A partition definition identifies the analytical table and the source query used to select the rows assigned to that partition.

Partition creation can be enabled as part of the Tabular or Multidimensional deployment configuration.

Perspectives

AnalyticsCreator can include perspectives in generated Tabular and Multidimensional Analysis Services models where they are configured for the project.

Perspective generation is controlled separately for each analytical model type in the deployment configuration.

Roles and Security

AnalyticsCreator can maintain Analysis Services role definitions as part of the analytical design.

For Tabular models, role definitions can include overall model access, table availability and DAX filters for row-level filtering.

For Multidimensional models, role definitions can include database, cube, dimension and cube-dimension permissions according to the required security design.

The generated security definitions still depend on the identities, groups and permissions available in the target Microsoft environment.

Relationship to the Data Warehouse

The analytical model is generated from the data mart structures and analytical metadata maintained in the AnalyticsCreator project.

This creates a controlled path between the data warehouse design and the semantic structures used by reporting and analytical tools.

Changes to AnalyticsCreator-owned dimensions, facts, relationships, measures, hierarchies and other analytical definitions can therefore be reflected in the corresponding model through regeneration.

Generation does not imply bidirectional synchronisation of changes made directly to a deployed Analysis Services model back into AnalyticsCreator.

XMLA Generation

AnalyticsCreator can generate an XMLA deployment script for the configured Tabular or Multidimensional Analysis Services model.

The deployment definition specifies the relevant Analysis Services target information and model options, including server, database, authentication, compatibility level and optional model features.

Generating an XMLA script creates the deployment representation of the model. It does not by itself establish that the model has been successfully deployed, processed or validated against production data.

Generation, Deployment, Processing and Execution

Analytical model generation, deployment and processing are separate activities.

  1. Design. Define the analytical structures, measures, relationships, hierarchies, partitions, roles and other supported metadata in AnalyticsCreator.
  2. Generate. AnalyticsCreator generates the configured Analysis Services model and XMLA deployment script.
  3. Deploy. Apply the generated model to the appropriate Tabular or Multidimensional Analysis Services environment.
  4. Process. Analysis Services loads or refreshes the model data from the configured underlying data sources.
  5. Consume. Reporting and analytical tools connect to the deployed Analysis Services model.

AnalyticsCreator can also include Analysis Services processing in a generated workflow package where that option is configured.

AnalyticsCreator is not required as a production runtime after the analytical model has been generated and deployed.

Compatibility Levels

AnalyticsCreator provides compatibility-level configuration for both Tabular and Multidimensional Analysis Services deployment.

The selected compatibility level should match the target Microsoft Analysis Services environment and the model features required by the implementation.

Compatibility should be reviewed when upgrading SQL Server Analysis Services or moving a model to a different target environment.

Changes and Regeneration

When AnalyticsCreator-owned analytical definitions change, the corresponding Analysis Services model can be regenerated from the updated metadata.

This can include changes to:

  • facts and dimensions
  • relationships
  • measures
  • calculated analytical definitions
  • hierarchies
  • partitions
  • perspectives
  • roles and security definitions

Generated changes should be reviewed before deployment, particularly where the deployed model contains manually maintained extensions.

Where AnalyticsCreator owns a definition, maintaining the change in the AnalyticsCreator project helps keep subsequent generation aligned with the governed analytical design.

CI/CD and Version Control

AnalyticsCreator project definitions and generated Analysis Services deployment artefacts can participate in controlled development and release processes.

Teams can use this approach to:

  • version AnalyticsCreator project definitions
  • review analytical-model changes before generation
  • generate XMLA deployment scripts from an approved design
  • include generated analytical artefacts in controlled release workflows
  • manage development, test and production analytical environments separately
  • retain an auditable history of design and implementation changes

The exact release process depends on the customer's source-control system, Analysis Services environment and deployment tooling.

SSAS and Power BI

SQL Server Analysis Services and Power BI represent different analytical targets within the Microsoft data stack.

AnalyticsCreator supports established SSAS Tabular and Multidimensional architectures as well as native Power BI semantic-model generation.

For Power BI-specific implementations, see the Power BI platform support documentation for PBIP, native TMDL generation and the Git-connected Power BI development workflow.

Prerequisites, Limitations and Notes

  • A supported SQL Server Analysis Services environment is required for SSAS deployment and execution.
  • The Analysis Services instance must use the server mode required by the generated model.
  • The selected compatibility level must match the target Analysis Services environment.
  • Required data-source connections, credentials and permissions must be available to the deployed model.
  • Model processing occurs in Analysis Services and requires access to the underlying data source.
  • Model processing and query performance depend on the analytical design, data volume, partitions, server resources and selected Analysis Services architecture.
  • Generated model changes should be reviewed before deployment to production.
  • Manual changes to generated model definitions require an agreed ownership model to avoid conflicts during regeneration.
  • Project-specific functionality should be validated against the AnalyticsCreator and SQL Server Analysis Services versions used by the implementation.

Design Considerations

  • Select Tabular or Multidimensional according to the required analytical architecture and target Analysis Services environment.
  • Maintain AnalyticsCreator-owned measures, relationships, hierarchies, partitions and security definitions in the project design.
  • Use partitions where the analytical model requires separate processing or data segments.
  • Consider processing requirements, data volume and server resources when designing analytical models.
  • Review the selected compatibility level when the target Analysis Services environment changes.
  • Use native Power BI semantic-model generation where Power BI Projects are the selected analytical architecture.

Example Use Cases

  • Generate an SSAS Tabular model from an AnalyticsCreator data mart.
  • Generate a Multidimensional OLAP model for an established Analysis Services environment.
  • Generate measures, relationships and hierarchies from maintained analytical metadata.
  • Generate model partitions and perspectives where required.
  • Maintain Tabular or Multidimensional Analysis Services role definitions.
  • Generate XMLA scripts for controlled Analysis Services deployment.
  • Regenerate analytical models when the underlying governed design changes.
  • Support existing SSAS environments while using metadata-driven model development.

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