AI and self-service analytics make enterprise data easier to consume—but they can also amplify bad data, unclear definitions, inappropriate access, and governance gaps. This session explores how Microsoft Fabric and Microsoft Purview can help organizations build a trusted foundation for analytics and AI. We will examine data lineage, discovery, ownership, access controls, classification, trusted data products, and governance across Fabric workloads and Power BI. The session connects governance to an increasingly important question: if an AI assistant or analytics user produces an answer from enterprise data, can we determine where that data came from and whether it should have been used?

Focus: Governance for Fabric and AI-ready analytics: lineage, data ownership, security, trusted datasets, metadata, and controlled access.