What modeling mistakes commonly impact performance?

< 1 min read

Common modeling mistakes that impact performance include using too many calculated columns.
Calculated columns increase model size and slow refresh.
I prefer measures whenever aggregation is sufficient.
High-cardinality text columns in fact tables also reduce compression efficiency.
In one project, removing unused text fields improved performance significantly.
Using bidirectional relationships unnecessarily can create expensive filter propagation.
Poorly designed relationships or snowflake structures can slow queries.
Not defining proper data types and aggregations also affects speed and accuracy.

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