How does data model design affect dashboard performance?

Data model design has a direct impact on dashboard performance because it determines how efficiently visuals can retrieve and aggregate data.

Key points:

1. Table structure:
   • Star schemas (fact + dimension tables) are faster than flat, denormalized tables for aggregation.
2. Relationships:
   • Properly defined one-to-many relationships prevent expensive cross-joins.
   • Avoid complex many-to-many relationships if not needed.
3. Columns vs Measures:
   • Store calculations as measures rather than calculated columns where possible.
   • Reduces storage and improves query speed.
4. Data granularity:
   • Too detailed (high-granularity) data slows aggregations.
   • Use the appropriate grain for business questions.
5. Data volume:
   • Remove unnecessary columns or historical data not needed for analysis.
   • Use aggregated tables for large datasets.

In one project, redesigning the model from multiple flat tables to a clean star schema cut dashboard load time from 25s to 6s.

Well-designed models improve responsiveness, reduce calculation load, and make dashboards scalable.