impact analysis

[powerbiexpert22]

how can i perform impact analysis of table or column changes on around 500 power bi reports? around 3-4 tables, 10-15 columns needs to be renamed and 5-6 tables and columns needs to be removed from database  

[Anonymous]

Hi @powerbiexpert22 

Data source impact analysis can helps you see where your data source is being used throughout your organization.

1. Go to the workspace that contains the data source you're interested in and open lineage view.

2. Find the data source's card and select the impact analysis icon.

The impact analysis side panel opens:

Data source impact analysis - Power BI | Microsoft Learn

Best Regards,
Jarvis Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[Kedar_Pande]

@powerbiexpert22 

To perform an impact analysis of table or column changes in Power BI reports:

Use the Power BI Dependency View: This built-in feature shows relationships between tables, queries, and reports, helping you identify impacted visuals.

Check All Queries: Review all Power Query steps where affected tables/columns are used. Renaming will require adjustments in the queries.

Update DAX Measures: Any DAX formulas referencing the renamed or deleted columns/tables will need to be updated.

Search for References: Use a Power BI tool (like DAX Studio or external tools) to search for direct references to tables/columns and update them accordingly.

Validate Reports: After updates, manually check reports for any errors or missing data.

[powerbiexpert22]

Hi @lbendlin , impact analysis meaning here which power reports would be impacted due to this change, since checking each and every report manually would not be feasible , what is alternate option to identify which reports would be impacted?

[lbendlin]

Use any of the tools available for this - Purview, Collibra, all the many "Measurekiller"  and "Column Identifier" projects.

None of these really answer the ultimate question. 

(Which is "How likely is it that the column I removed today will be needed tomorrow?")

[lbendlin]

You can use Query Diagnostics (or SQL Server Profiler) to measure the impact.

Just recently we went through that exercise and found that an innocent single column rename transform can have a massive performance impact.  We refactored it to swap ALL column names (even the ones that didn't change) which used a lot (A LOT) less resources.