Fabric Data Agent

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Apr 26, 2026

Fabric Data Agents Series (2/4): Why Your Data Model Breaks AI in Microsoft Fabric

πŸ‘‰ If your data model isn’t solid, your AI won’t be either. In Part 2 of our Microsoft Fabric Data Agents series, we focus on the foundation that makes or breaks AI: your semantic model and data design. This session shows how to build AI-ready data foundations so Fabric Data Agents can deliver accurate, consistent, and trustworthy results β€” not hallucinations or ambiguity. 🎯 What you’ll learn: βœ”οΈ Why naming conventions and clear definitions are critical for AI reasoning βœ”οΈ How explicit measures improve consistency and trust βœ”οΈ The role of star schema design in scalable AI analytics βœ”οΈ Common failure modes that break Data Agents βœ”οΈ Practical Fabric-native fixes to improve grounding quality Most AI projects don’t fail because of AI β€” they fail because of bad data modeling. This session gives you the frameworks to fix that. πŸš€ Whether you're a Power BI developer, data engineer, or architect, this is your blueprint for moving from experiments β†’ production-ready AI systems. πŸ‘‰ Watch Part 1 to understand Fabric Data Agents fundamentals πŸ‘‰ Continue with Parts 3 & 4 to master architecture and governance at scale πŸ‘ Subscribe for more deep dives on Microsoft Fabric, Power BI, and AI-driven data platforms #MicrosoftFabric #PowerBI #DataModeling #FabricDataAgents #AIinAnalytics

Speaker: Jennifer Ratten