I propose introducing a context-aware AI assistant integrated directly into Power BI and Microsoft Fabric workflows, extending beyond generic Copilot interactions. The idea is to enable an AI assistant (LLM-based) that is aware of the semantic model, measures, data sources, and visuals, and can assist users throughout the analytics lifecycle, including: Translating business questions into optimized DAX measures Explaining existing DAX, Power Query (M), SQL, or Spark logic in plain language Suggesting data modeling and performance optimization best practices Recommending appropriate visuals and layouts based on analytical intent Generating insight narratives tied to actual KPIs and report context Assisting users transitioning from Excel/Power BI into Fabric notebooks and Lakehouse workflows This integration would significantly lower the learning curve for Fabric adoption, improve governance-aware AI usage, and help analysts move from dashboards to decisions more effectively. It would be especially valuable for non-native English users and emerging analytics communities. This proposal is based on real-world training and community experience with large-scale Power BI and Fabric adoption, where users consistently need contextual, decision-focused guidance rather than generic AI responses.
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