Before pushing to production, thoroughly validate reports using the Dev and Test stages of the deployment pipeline, making sure to check the data accuracy, visuals, and DAX logic.
Using distinct development and test workspaces is one of the best practices for testing Power BI reports.
In specialized Dev and Test workspaces that replicate production settings, create and test reports.
By doing this, changes are isolated, and live users are not impacted.
Verify the accuracy and freshness of the data.
Verify that datasets successfully refresh with the anticipated data.
Verify the accuracy of sample data and important metrics.
Examine the User Experience and Visuals
Verify that every image renders flawlessly.
Verify that drill-throughs, bookmarks, slicers, and filters work as intended.
Examine the DAX calculations and logic.
To validate complicated DAX expressions, use programs like Tabular Editor or DAX Studio.
Measure results should be compared to anticipated results.
Make Use of Power BI Analysis of Lineage and Impact
To comprehend data dependencies and make sure all linked datasets and reports are tested, use the lineage view.
Test Automation (Optional)
For automated refresh status checks and error alerts, integrate with programs like Power Automate or the Power BI REST API.
For automated deployment validation, use CI/CD tools such as Azure DevOps.
Obtain the approval of stakeholders during the test phase.
Before putting reports into production, formally approve them using approval workflows (through Power Automate or Azure DevOps).
