AnalyticsCreator | Blog and Insights

How Metadata Powers Both Automation and Governance in Microsoft Fabric

Written by Richard Lehnerdt | Aug 20, 2025 9:35:37 AM

Metadata is now both the input for automation and the anchor for governance. AnalyticsCreator builds with metadata; Microsoft Fabric governs with metadata. Together, they create a seamless flow from automated data product creation to governed analytics consumption.

Metadata as the Driver, Not a Byproduct

In the modern data stack, metadata is no longer just documentation—it defines how systems behave. AnalyticsCreator uses metadata to generate entire data warehouses, while Microsoft Fabric uses metadata to catalog and control access to datasets, reports, and models across OneLake and Power BI.

The Role of Metadata in Automation

With AnalyticsCreator, metadata drives:

  • Pipeline generation: Automatically builds ELT pipelines based on metadata, reducing manual effort and enabling rapid onboarding of new sources.
  • Data historization: Applies consistent rules across all entities using a metadata-defined pattern—ensuring auditability and compliance.
  • Lineage and governance: Maintains live visual lineage from source to semantic model, helping teams trace impacts and track transformations.
  • CI/CD alignment: Generates deployable artifacts for Azure DevOps or GitHub pipelines, enabling version-controlled releases.
  • Fabric integration: Seamlessly connects metadata-defined logic to Microsoft Fabric, which catalogs and governs the resulting assets (datasets, reports, models).

Metadata-Driven Data Products

AnalyticsCreator treats each data mart as a data product: traceable, governed, and business-ready. Metadata ensures that every product is built consistently, with transparent logic and adaptability to change. In Fabric, these products are discoverable, reusable, and integrated across Power BI, Synapse, and OneLake.

AnalyticsCreator’s Metadata-Driven Approach

AnalyticsCreator defines every stage of the data lifecycle via metadata. It auto-generates:

  • SQL-based artifacts and ELT workflows
  • Data pipelines for ADF and SSIS
  • Semantic models for Power BI, Tableau, and Qlik
  • Documentation and lineage diagrams

This metadata model flows directly into Microsoft Fabric, aligning governed lakehouse and warehouse strategies under one architecture—automated and transparent by design.

Conclusion

Metadata isn’t just an audit artifact—it’s a tool for automation and governance. With AnalyticsCreator and Microsoft Fabric, modern data teams can accelerate delivery, enforce consistency, and scale trusted analytics across domains—powered by metadata at every step.