What is performance impact of poor transformation design?

< 1 min read

Poor transformation design mainly slows refresh and increases memory usage.
If filters are applied late, Power BI loads full dataset first — refresh becomes very slow.
Breaking query folding forces local processing instead of database processing.
Too many custom columns or row-by-row logic causes CPU spikes and gateway failures.
Unnecessary columns increase model size and report opening time.
Example: A report took 45 mins refresh because CSV merge happened before filtering.
After redesign — filter first, SQL view aggregation — refresh dropped to 7 mins.
It also impacts users: visuals load slowly and slicers lag.
So transformation design directly affects refresh reliability and user experience.

Power BI Essentials