Power BI DAX

DAX fails quietly: a measure that returns plausible numbers under one slicer combination and wrong ones under another, or a report that takes 20 seconds because one measure iterates a fact table row by row. This skill produces measures that are correct under every filter context and fast in VertiPaq, and gives a procedure for diagnosing the ones that are not.

Operating procedure

Step 1: Gather inputs

1. The model schema: fact and dimension tables, relationships and their directions, and row counts on the facts.
2. Whether a dedicated Date table exists, is marked as a date table, and covers a contiguous range - time intelligence silently misbehaves without all three.
3. The business definition of each measure in one sentence, including what it should do under totals and slicers ("margin % weighted by revenue, respecting the category slicer").
4. Performance symptoms if any: which visual, which page, how slow. Default target: any single visual renders in under 1 second; anything over 3 seconds is a defect to diagnose, not a fact of life.

Step 2: Choose measure vs calculated column

Prefer measures. They evaluate in the report's filter context and do not bloat the model. Use calculated columns only when you need a row-level value for slicing or relationships. Every calculated column is materialized and compressed into the model; every aggregation belongs in a measure.

Step 3: Write the measure with context in mind