SQL Server and Microsoft data platforms remain foundational to analytics in many enterprise organizations. As architectures extend across SQL Server, Azure SQL, Azure Synapse Analytics, and increasingly Microsoft Fabric, data teams often encounter recurring challenges: fragile pipelines, duplicated logic, long lead times for change, and governance gaps that can widen during modernization.

This session examines how end-to-end data automation can improve stability and maintainability across Microsoft data platforms without requiring large-scale rewrites or adding unnecessary tooling. Using established enterprise patterns, we will show how a metadata-driven approach can streamline data modeling, transformation, orchestration, and documentation across SQL Server, Azure SQL, and Synapse—while supporting a clear migration path to Fabric when appropriate.