AI wrote your DAX.
Counts wrong.

And you won't notice until it's too late.

A practical pre-flight checklist with 7 diagnostic queries you run in DAX Studio before any AI-generated measure goes into a report. Each one targets a specific class of silent error - the kind that compiles, runs, and returns plausible numbers while being wrong.

  • Q1 Grain mismatch - COUNTROWS vs DISTINCTCOUNT. Why AI always gets this wrong and how to catch it in 30 seconds
  • Q2 Filter context destroyed - ALL vs REMOVEFILTERS. The query that shows if your % will ever sum to 100%
  • Q3 Context transition missing - why every row returns the same number and how CALCULATE fixes it
  • Q4-7 Relationships, BLANKs, time intelligence, non-additive totals - each with a diagnostic query and corrected DAX
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brighter.so/checklist
Free checklist · DAX Studio
AI wrote your DAX.
Counts wrong.
7 questions - real diagnostic queries - before any measure ships
Q1
Is the metric definition unambiguous at the grain you plan to show?
Faulty COUNTROWS('SalesLine') Fixed DISTINCTCOUNT([OrderID])
Q2
Does it respect the intended filter context?
Faulty ALL('Product') Fixed REMOVEFILTERS([Name])
Q3
Are row and filter context handled correctly inside iterators?
Most confusing CALCULATE( COUNTROWS )
Q5
Are BLANKs and data types handled explicitly?
Faulty DISTINCTCOUNT([Key]) Fixed DISTINCTCOUNTNOBLANK
Error class
Symptom
Fix pattern
Grain mismatch
Counts inflated
DISTINCTCOUNT on key
Filter nuked
Ignores slicers
REMOVEFILTERS column
Time intelligence
YoY broken
Mark proper date table
+ 3 more questions inside
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