Question

What steps do you follow when visuals don’t display the expected results, even when the underlying data is correct?

Some visuals in my Power BI report are not displaying the expected results, even though I’ve confirmed that the underlying data is correct. I’m uncertain if the issue is related to DAX calculations, filtering, or relationships between tables. What steps should I follow to troubleshoot visuals that aren’t displaying correctly to ensure they reflect the accurate data?

Answer 1

When it comes to displaying Power BI visuals, problems might be encountered even if the underlying data is correct. Therefore, it’s crucial to take a systematic approach to the troubleshooting of the particular issue encountered. Let’s see how the problem can be investigated and resolved step by step:

Check the DAX Calculations

In the first step, take a look at the DAX logic written within the visuals. Look for common problems such as wrong filter context or behavior between variables that were not intended. Measure each one separately instead of looking at the whole picture by creating a table visual to see what intermediate measures give. This can help you find the answer if some DAX proves to be working incorrectly. Also, some measures may lead to a different outcome if the filter context is altered using ALL, REMOVE FILTERS, CALCULATE functions, etc.

Verify Relationships Between Tables

At times, it is usual for inconsistent visuals to be a result of incorrect or missing relationships. Open your model and check that all relationships needed exist and that they have the right cardinality, for example, one to many or many to many, direction, and active/inactive status. If you are working with inactive relationships, ensure they are brought to action where necessary in your DAX using USERELATIONSHIP. Also, make sure to review bi-directional filtering, as that may affect some tables interacting with others without expectations.

Examine Visual-Level and Report-Level Filter

All too often, the presence of multiple filters results in counter-intuitive outcomes in Power BI visuals. Check visual-level and report-level filters to confirm their correct assumptions. In the event that the visual has slicers or cross-filters, try clearing filters to their ‘clean’ states and see if the problem persists. The feature ‘Edit Interactions’ also helps manage the interactions between various visuals and fine-tune the cross-filtering settings so that unwanted filters are not applied where they are not supposed to be.

It is believed that by taking the above steps, one will be able to systematically figure out what is going wrong with the elements included in the visuals of Power BI and hence assist in presenting data uniformly and appropriately throughout the report.

Answer 2

To burn out all the metaphors and sayings that seem to abound everywhere about why Visualizations fail to produce the expected statements in Power BI, these steps must be followed:

Check Filters and Slicers: Ensure that there are no filters or slicers that could restrict data in your visuals.

Relationship Verification: All relationships must be checked for tables to determine whether they hold the right cardinality and direction.

Verify DAX Measures: DAX Calculations should also be explored to ensure they are defined properly. Use tools such as DAX Studio to debug measures and optimize them.

Data Type Validity Check: Columns used in relationships or calculations should have compatible data types.

Check on Aggregation: All visual aggregation must be correctly set up. That is, measures or dimensions should be checked to ensure they are correctly employed.

View-Level Filters: Check again for any accidental visual-level filters.

One could carefully consider these concerns and solve incorrect visualizations.