#howtodataagent

Apr 26, 2026

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

👉 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 — not hallucinations or ambiguity. 🎯 What you’ll learn: ✔️ Why naming conventions and clear definitions are critical for AI reasoning ✔️ How explicit measures improve consistency and trust ✔️ The role of star schema design in scalable AI analytics ✔️ Common failure modes that break Data Agents ✔️ Practical Fabric-native fixes to improve grounding quality Most AI projects don’t fail because of AI — they fail because of bad data modeling. This session gives you the frameworks to fix that. 🚀 Whether you're a Power BI developer, data engineer, or architect, this is your blueprint for moving from experiments → production-ready AI systems. 👉 Watch Part 1 to understand Fabric Data Agents fundamentals 👉 Continue with Parts 3 & 4 to master architecture and governance at scale 👍 Subscribe for more deep dives on Microsoft Fabric, Power BI, and AI-driven data platforms #MicrosoftFabric #PowerBI #DataModeling #FabricDataAgents #AIinAnalytics