Once your LLM is connected to a data lakehouse, it can reach every table your permissions allow. Kate Eberle, Director of Sales at Blue Margin, and Brick Thompson, Blue Margin’s CEO, talk about how to govern data for BI and AI analytics so the right people see the right data and read it correctly.

Kate recently presented to a group of analytics practitioners in the legal industry, and governance took over about a third of the hour. She and Brick cover data governance committees, training for self-service users, role-based security in the lakehouse, and how documented context helps an LLM return reliable answers to business users.

Chapters
00:00 Governance for BI and AI
00:40 What legal analytics teams are asking about
01:46 Permissions in a single system vs. a lakehouse
02:55 Data governance committees
04:40 Training self-service users
06:17 Supporting business users with AI analytics
06:51 Building context for reliable LLM answers
09:07 Curation and the data team’s role
10:09 Why access control matters more with LLMs
12:33 Getting busy leaders to participate in governance

About Blue Margin
We build and manage data platforms for mid-market and PE-backed companies. Our managed data services cover everything from bringing your systems together in one place to reporting and AI analytics, all built on a single governed foundation that your whole leadership team can trust. Learn more at bluemargin.com.

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

Microsoft is folding AI into nearly every part of Fabric, and the Fabric Data Agent is now generally available after a long run in preview. Brick and Landon talk through what they've found in testing: where natural language querying holds up, what it takes to get consistent answers, and why we've been adding a platinum stage to the medallion architecture with context files that tell the model how the business actually works.

Landon also covers Microsoft's open-source Fabric skills, the PBIP and PBIR report format that finally puts Power BI into source control, and the validation loop where the AI generates a report, screenshots it, catches its own broken visuals, and corrects them. Both come back to the same conclusion: the results depend on a strong data foundation and someone who knows their way around Power BI.

The Dashboard Effect is hosted by Blue Margin. We build the data foundation that mid-market and PE-backed companies run their reporting and AI on.

Learn more: https://bluemargin.com