Audience
Data Engineers, Data Architects, BI Engineers, Analytics Engineers, Heads of Data, BI Leads, Microsoft Data Platform Teams
About AnalyticsCreator
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets.
AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes.
Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering.
Pricing
Integrations
Videos and Screen Captures
Product Details
AnalyticsCreator Frequently Asked Questions
AnalyticsCreator Product Features
Data Engineering
AnalyticsCreator is a metadata-driven design application for Microsoft data engineering teams. Engineers define structures, transformations, loading logic and dependencies centrally, then generate native SQL, SSIS, Azure Data Factory, Microsoft Fabric and Power BI assets. Repeatable patterns for ingestion, transformation, historisation, SCD processing and deployment reduce manual engineering while keeping lineage, documentation and change impact connected to the project design.
Data Integration
AnalyticsCreator provides metadata-driven design and generation for data integration across Microsoft environments. Teams define sources, mappings, transformations, dependencies and loading rules centrally, then generate native SQL, SSIS and Azure Data Factory implementation assets. This helps standardise recurring integration patterns while preserving lineage, documentation and ownership of the resulting Microsoft technology.
Data Lake
AnalyticsCreator helps Microsoft data teams design governed ingestion and transformation processes for data lake and analytical architectures. Metadata-defined sources, mappings, transformations and dependencies can be used to generate native Microsoft implementation assets for supported Azure and Microsoft Fabric scenarios. AnalyticsCreator provides the design and generation layer rather than acting as the data lake runtime itself.
Data Lineage
AnalyticsCreator captures lineage as part of the engineering model rather than as a separate documentation exercise. Sources, tables, transformations, references and downstream analytical structures remain connected through project metadata, allowing teams to trace data movement and understand dependencies across the solution. Lineage can also support impact analysis when models or transformations change.
Data Management
AnalyticsCreator helps Microsoft data teams manage the design and evolution of structured data estates through a central metadata model. Sources, schemas, tables, relationships, transformations and dependencies remain connected to the generated implementation. This provides greater visibility into project structure, lineage and change impact while helping teams apply consistent modelling and engineering standards.
Data Modeling
AnalyticsCreator provides model-driven design for data warehouses and data products across the Microsoft data stack. Teams can define dimensional, 3NF and hybrid models together with relationships, transformations, historisation rules and dependencies. The approved model then drives generation of native SQL, pipelines, documentation, semantic models and deployment artefacts, keeping design and implementation aligned as the project changes.
Data Warehouse
Accelerate the development of your data warehouses by automating complex model designs, including dimensional, data mart, and data vault architectures. AnalyticsCreator enhances scalability for large data environments and ensures better governance through its automated features. Generate optimized code for leading platforms such as Snowflake, Azure Synapse, and MS Fabric. Improve data quality, consistency, and governance throughout the data warehouse lifecycle with automated tools for schema evolution and historical data handling. Enhance collaboration with version control and automated documentation, enabling seamless teamwork and rapid iteration. Leverage AnalyticsCreator to meet the demands of modern data warehouse development with CI/CD and agile workflows, reducing development cycles significantly.
ETL
AnalyticsCreator provides metadata-driven design and generation for ETL and ELT processes across the Microsoft data stack. Data teams define mappings, transformations, loading logic, dependencies and historisation centrally, then generate native SQL procedures, SSIS packages and Azure Data Factory pipelines. Reusable patterns support ingestion, delta loading, SCD processing and repeatable transformations without introducing a proprietary production runtime.
Metadata Management
Metadata is the foundation of AnalyticsCreator. The central project model connects data structures, transformations, business rules, relationships, dependencies, lineage, documentation and generated implementation. This allows data teams to use metadata not only to describe a solution, but to actively drive generation, change analysis and controlled delivery across Microsoft data projects.
Semantic Layer
AnalyticsCreator can generate governed analytical and semantic models for Microsoft Power BI and Analysis Services from the same metadata used to design the underlying data warehouse. Relationships, dimensions and model structures remain connected to the wider project design, helping teams keep analytical models aligned with upstream data structures and dependencies.
AnalyticsCreator Additional Categories
Data Lakehouse
AnalyticsCreator supports governed design and generation for Microsoft Fabric-oriented lakehouse and warehouse architectures. Teams can use the central project model to define structures, transformations and dependencies and generate supported Microsoft Fabric and Power BI assets. AnalyticsCreator provides the design and governance layer while the resulting workloads operate in the Microsoft environment.
Data Warehouse Automation
AnalyticsCreator automates data warehouse engineering from governed design metadata. Teams model structures, transformations, historisation, loading patterns and dependencies centrally, then generate native Microsoft implementation assets including SQL, SSIS, Azure Data Factory, Microsoft Fabric, Power BI, documentation and deployment artefacts. Changes can be propagated across dependent project components, reducing repetitive engineering while keeping lineage and impact visible.