Getting the Same Answer from Power BI, Excel, and Your AI Agent

When your team asks the same question in Power BI, in Excel, and through an AI agent, the answers should match. That consistency comes from defining your business rules once, upstream in the lakehouse, so every tool reads from the same place. In this episode, Brick Thompson and Landon Ochs walk through the platinum layer, which takes the business logic sitting in your semantic models and the cleansed data in your gold layer and bakes both into materialized tables an LLM can query directly. They cover what stays in the report for runtime behavior like security and date slicers, how to settle a definition of revenue that sales, finance, and the CEO all recognize, and how role-based context can serve the right version of a metric to whoever is asking. They also get into authentication, since MCP servers can run on the same Entra security groups you already manage, and into the other agents that can read your data once it is in a consistent state. Chapters 00:00 Same question, same answer across Power BI, Excel, and NLQ 00:53 One place where the logic lives 01:40 Where the platinum layer sits in the medallion architecture 02:20 What belongs in the semantic model at runtime 03:00 Combining gold layer data with semantic business logic 03:39 Materialized tables and defining revenue for your business 04:46 Handling competing metric definitions, including role based 05:30 Context files, MCP servers, and measures in the lakehouse 05:54 Entra authentication, tool permissions, and agents beyond NLQ 07:35 Updating business logic in one place We're Blue Margin, a managed data services firm working with mid-market and PE-backed companies. Learn more: https://bluemargin.com