
Mike & Tommy tackle the question of how to match the right LLM to the right Microsoft Fabric workload, exploring whether bigger always means better or just more expensive, and how teams can build a practical model-selection strategy across Power BI, notebooks, pipelines, and more.
They break down the planning and execution decisions behind agentic tooling in Fabric—covering Power BI Desktop Bridge, semantic models, and notebooks—and land on a framework for making model choice a deliberate, cost-aware decision rather than a default.
News: Fabric Data Warehouse Integration with Fabric User Data Functions (Preview) | Data Visualization in the Agentic Era
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