Multi-agent governance and engineering system for Power BI / Fabric
- 2 díasto validate, was days or weeks
- 16semantic models in scope
- 15agent-products, 3 already live
- 294+green tests on the technical base
The problem
A large organisation’s Power BI / Fabric ecosystem accumulates technical debt: inconsistent naming, slow semantic models, inefficient DAX, stale documentation and blurry KPI governance.
Validating a model took days or weeks of manual work across a scope of 16 models. A standalone assistant does not fix that.
The architecture
An agent adoption plan for the BI area, with progressive rollout prioritised by visible return.
A catalogue of specialised agents by layer: demand (dashboard copilot, mockup design), planning (effort estimation), development (model validation, DAX optimisation, semantic refactoring, relationship analysis), design (dashboard UX/UI, model layout), quality and governance (KPI consistency, RLS/OLS security), deployment and operations (Dev→Test→Prod, dataset dependencies, usage analytics) and document governance (automatic data dictionary and technical documentation).
Impact
- Model validation goes from days or weeks to a little over 2 days
- 15 agent-products rolled out over 4 quarters, 3 already live in the operational environment
- Technical base validated with more than 294 green tests
- Kicked off with 3 prioritised quick wins: estimation, validation and documentation
Stack
- Multi-Agent
- Microsoft Fabric
- Power BI
- XMLA / TOM
- DAX
- Azure AI Foundry