Create calculated columns with Power Pivot so dynamic filters and good aggregation can serve Power BI reports. Here are the best practices to be observed:
Drive Home Data Model Optimization
A good data model is an unassailable data table linked one to another. You have to create calculated columns if your requirements fail at the point of availing measure results since, unlike measure, these calculated columns are evaluated at every demand. In most cases, it has a more severe effect on performance.
Reduce row-by-row evaluations.
Calculated Columns work like instruments of row-by-row evaluations entirely. Using calculated columns slows the model as it becomes loaded with data, which then stinks. Use calculated columns only when the result is needed at row level yet cannot be calculated using DAX measure or other data modeling techniques.
Extending Reusable Logic
Divide more complex logic into smaller, reusable measures. This gives room for improved reading, and less makes debugging possible. For example, calculate intermediate results by means of measures and reference them in your columns or visualizations.
Make formulas an exact science.
Use DAX functions smartly. The SWITCH() function is a great relief instead of using more than one conditional statement, even with conditions created by IF(). For performance enhancement in joins or lookups, make sure that you index columns appropriately. Avoid also using EARLIER().
Test and Validate Calculations
Test the calculated columns rigorously in different filter contexts to ensure the results are as expected. Validate against source data or other predefined scenarios to find errors early.
Limit the use of calculated columns.
Preprocess as much data as possible in Power Query or a source system. Use calculated columns in Power Pivot only for logic that cannot be computed anywhere else but inside the data model.
Monitor performance
Tools such as the Performance Analyzer in Power BI can detect bottlenecks caused by calculated columns. If necessary, optimize or refactor calculations in the report to maintain responsiveness.
By following these best practices, calculated columns can be prepared that support dynamic filtering and aggregations while ensuring that the reports' performance and accuracy are preserved.
