Microsoft Positions Fabric as a Governed Context Layer for Enterprise AI

Fabric IQ as the Core Context Engine

At FabCon and SQLCon in Barcelona, Microsoft introduced Fabric IQ, a preview capability that fuses OneLake data, Power BI semantic models, and real-time operational signals into reusable ontologies. Modelers can import trusted Power BI measures, attach condition-action rules via Fabric Activator, and expose the resulting knowledge graph to Microsoft’s operations agent. This shared layer of business meaning is positioned to ground Copilot, Foundry, GitHub Copilot, and custom agents, ensuring that AI responses reference the same definitions of entities, relationships, and metrics.

OneLake Expands from Data to Context Distribution

OneLake, previously a data-sharing lakehouse, now supports “IQ sharing” in preview, allowing governed tables, files, agent instructions, and RDF ontologies to be distributed together. The integration extends to Google BigQuery mirroring, bidirectional links with Salesforce Data 360, and deeper ties to Dynamics 365 Business Central. By treating ontologies as first-class assets, OneLake moves toward distributing reusable business context across teams, partners, and AI systems.

From Semantic Models to Operational Software

Power BI Desktop gains an agentic app-creation flow that starts with a trusted semantic model and lets users generate purpose-built applications via natural language. These Fabric Apps, also in preview, provision back-end services such as GraphQL APIs, hosting, and Entra ID authentication, enabling read-write interactions, state retention, and workflow automation. The shift demonstrates Microsoft’s intent to turn governed context into executable software rather than static reports.

Agents Tie Context to Controlled Execution

Microsoft deepened the link between database agents, Fabric data agents, and Fabric IQ ontologies, exposing a unified Database Hub. Agents can now perform root-cause analysis, trigger pre-approved actions, and even orchestrate long-running tasks like lakehouse modernization within defined permissions and guardrails. Complementary observability tools—workspace telemetry, job monitoring, and AI-assisted investigations—complete the governed context layer, ensuring that as more agents rely on shared meaning, the environment remains observable and controllable.