Forum Discussion
Break out Multi-Select field into Slicer
- 1 year ago
Hello GabeFig,
Thanks for sharing the sample data.
I have reproduced your scenario using the sample data you shared and implemented the required filtering logic based on multi-valued Categories and Features columns (with delimiters like ;).
Output:- When “Application” is selected from the Categories slicer:
You will see only rows where “Application” is one of the multiple categories. - When “AI-Enabled” is selected from the Features slicer:
You will see only rows where “AI-Enabled” is one of the feature values.
For your reference, I’m attaching the .pbix file.
Best regards,
Ganesh Singamshetty - When “Application” is selected from the Categories slicer:
Hello GabeFig,
Thank you for reaching out to the Microsoft Fabric Forum Community.
Power BI treats these fields as text strings when imported, rather than recognizing them as separate selectable items.
To resolve this, you can use Power BI's "Split Column" feature to break the semicolon-separated values into rows. Here’s a general approach:
- Import the .csv file into Power BI and click on the Categories or Features column in the Power Query Editor.
- Go to the Home tab, click Split Column and choose By Delimiter and opt to split into rows (not columns) and Click OK and then Close & Apply to refresh the data model.
- Add slicers for the split Categories and Features columns.
If this information is helpful, please “Accept as solution” and give a "kudos" to assist other community members in resolving similar issues more efficiently.
Thank you.
I went through your steps as well as refreshed but the data seems to be the same. I do not see any new columns to use in the Slicer.
Maybe this has to be rebuild rom scratch
- v-ssriganesh1 year ago
Community Support
Hello GabeFig,
Thanks for the follow-up.The issue might be due to the field being split into columns instead of rows, or possibly a modeling step was skipped. Let me walk you through the approach again, this time with clarity on creating a slicer-ready field:
- In Power BI, go to Transform Data to open Power Query Editor and Select your Categories column.
- From the top ribbon, click Split Column > By Delimiter and Choose delimiter: ; (semicolon) also note that in the dialog, select Split into Rows, not columns.
- Repeat the same for the Features column (if needed) and Click Close & Apply to update the data model.
- After applying changes, return to your Power BI report canvas and drag the now “flattened” Categories column into a slicer visual.
Best Regards,
Ganesh singamshetty.- GabeFig1 year agoFrequent Visitor
Thanks Ganesh for the more detailed instruction BUT that seems to be what I did.
I could not tell there was anything different even after the original slicer was removed and recreated w/ Category field that was split (by rows).Below are some screenshots of what was done with the existing MS BI.I wonder that this needs to be done completely from scratch to work.
Both Catefory & Feature were done. The split was done by Row.
I also checked to see if there was a hidden CR or LF or CRLF but there were none.
- v-ssriganesh1 year ago
Community Support
Hello GabeFig,
Thanks for sharing your detailed screenshots and you’ve done a great job applying the split correctly. I now suspect the issue is not with the split step itself, but with how Power BI handles row-level filtering from slicers in a 1-to-many relationship scenario.To make the slicers work properly without affecting or duplicating your main data table:
- Duplicate your main table in Power Query call it CategoryMapping and Keep only ID and Categories columns.
- Apply Split Column by Delimiter Into Rows on Categories and Rename the result column to Category. Repeat same steps to create a FeatureMapping table.
- Create Relationships between CategoryMapping[ID] >> MainTable[ID] and FeatureMapping[ID]>> MainTable[ID]
- Then Use CategoryMapping[Category] in the Category slicer and FeatureMapping[Feature] in the Feature slicer
If the issue persists, try to share your .pbix file or sample data so I can better understand the scenario and give you the necessary solution.
Thank you.