The Documentation Problem
Every Power BI developer knows they should document their models. But nobody does. It's tedious, it's always out of date the moment you finish, and there's no built-in tooling for it.
The result? Models become black boxes. When the original developer leaves, knowledge walks out the door.
What Good Documentation Looks Like
A well-documented Power BI model should have:
- Measure descriptions — What each measure calculates, in plain English
- Inline comments — DAX comments explaining the "why" behind complex logic
- Table descriptions — Purpose of each table in the model
- Display folders — Logical grouping of measures for end users
The AI Approach
AI can read your DAX expressions and generate all of this documentation automatically. It understands what CALCULATE(SUM(Sales[Amount]), DATESYTD('Date'[Date])) does and can describe it as "Calculates year-to-date sales revenue."
How DaxAudit Does It
When you run a DaxAudit AI analysis, we do three things:
- Generate descriptions — Every measure and calculated column gets a plain-English description
- Add inline comments — AI writes DAX comments explaining each section of complex measures
- Inject into your model — We rebuild your .pbit template with all descriptions and comments pre-populated
The result is a fully documented model that you can open in Power BI Desktop and immediately see descriptions in the Fields pane.
Time Saved
Manually documenting a 50-measure model takes 2-4 hours. DaxAudit does it in under 2 minutes. That's a 60x speedup.