Build the semantic and data foundations that make agents reliable. This workshop translates modeling best practices into agent-ready guidance: naming and definitions, explicit measures, star schema discipline, and how to prevent ambiguous data surfaces. Includes common failure modes and Fabric-native remediation strategies to improve grounding quality.

This session is ideal for BI developers, semantic modelers, data engineers, and analytics architects who want to design data and models that produce reliable, grounded results when consumed by AI agents.