Publish to Power BI workspace that is not in Premium version and visuals are not failing

[Mark-JZ-Yeap]

In Power BI Desktop, my table visuals are not failing even every slicer is set to "All".

When I publish it to the workspace that is not in premium version, all my table visuals are failing.

When I publish it to the workspace that is in premium version, all my table visuals are not failing.

Can you think of a better way to make all table visuals that are not failing even every slicer is set to "All" when publishing it to the workspace that is not in premium version?

Please advice.

[Anonymous]

Hi @Mark-JZ-Yeap ,
I hope the issue got resolved.If so,kindly acceping it as solution so others can easily find it.

Thank you.

[Anonymous]

Hi @Mark-JZ-Yeap ,
I wanted to check in on your situation regarding the issue. Have you resolved it? If you have, please consider marking the reply that helped you or sharing your solution. It would be greatly appreciated by others in the community who may have the same question.
Thank you.

[Mark-JZ-Yeap · Accepted solution]

Solution:
Go to Power Query and merge the tables as new.

[Anonymous]

Hi @Mark-JZ-Yeap ,
Thank you for sharing the solution.Kindly accept your answer as accept as solution.

Thank you for being a part of Microsoft Fabric Community Forum!

Regards,
Pallavi.

[Amar_Kumar]

@Mark-JZ-Yeap hi

This issue strongly suggests that your table visuals are hitting a resource or performance limitation in non-premium workspaces, particularly when slicers are set to "All" (i.e., no filters, resulting in large data loads). Premium workspaces handle larger data and more complex queries better due to higher capacity, which is why your visuals work there but fail in the non-premium workspace.

[Mark-JZ-Yeap]

Premium is basically very expensive.

[Amar_Kumar]

Try the below Ways to Avoid Failures in Non-Premium Workspaces :

1. Optimize the Data Model

a. Remove unused columns and tables.

b. Reduce cardinality (especially for columns used in slicers or relationships).

c. Use star schema design for better performance.

2. Limit Data with Filters

a. Instead of defaulting slicers to "All", set a default filter to show only a reasonable number of rows (e.g., current month or last 30 days).

b. You can use a relative date slicer to automatically limit data volume.

3. Add Summary Tables

a. Instead of showing large raw tables, create aggregated or summarized views using DAX or Power Query.

b.This drastically reduces the number of rows shown and improves performance.

4. Paginated Reporting (if needed)

a. If users need access to all raw data, consider exporting that as paginated reports or Excel, rather than rendering huge tables in Power BI visuals.

5. Switch to DirectQuery or Aggregations

a. If your dataset is large and you're using Import mode, switching to DirectQuery or creating aggregation tables can help.

[Mark-JZ-Yeap]

What about unpivoting?

[Amar_Kumar]

Unpivoting is great for transforming wide data into long format, which can improve flexibility and sometimes performance. But for your issue 

— table visuals failing when slicers are set to “All”

— the root cause is likely data volume, and unpivoting won’t solve that alone.

[Mark-JZ-Yeap]

If unpivoting won't solve alone, what will be the next step(s)?

[Anonymous]

Hi @Mark-JZ-Yeap ,
Thank you @Amar_Kumar for the helpful response!

Thank you for the follow-up.I would be happy to assist you!
If unpivoting alone does not solve the issue, the next steps are really about helping your visuals handle less data at once especially in non-premium workspaces, which have tighter limits. After unpivoting, try adding filters to reduce the data shown like last 30 days or top items, and avoid defaulting slicers to "All." You may also replace raw data tables with summary views using DAX, which are much lighter to render. These combined steps usually help visuals load smoothly without needing Premium.

Hope this resolve your query.If so,consider accepting it as solution.


Thank you for being a valued member in Microsoft Fabric Community Forum.

Regards,
Pallavi.

[Amar_Kumar]

hi @Mark-JZ-Yeap the next effective steps are aimed at reducing the volume of data rendered at once and optimizing the model

1. Reduce Default Data Volume in Visuals

a. When slicers are set to “All,” visuals may try to render millions of rows — especially in table/matrix visuals.
b.Set default slicers to limit data (e.g., last 30 days, or one process type).
Use DAX filters like:
IF (
  HASONEVALUE('Date'[Month]),
  [Your Measure],
  BLANK()
)
This will ensure that visuals don’t render when no slicer is applied.

2. Use Aggregated Tables Instead of Raw Data

a. Create summary tables using SUMMARIZE, GROUPBY, or in Power Query.
b.Display totals or averages at a higher level (e.g., per day, per region) rather than row-level records.

3. Optimize the Data Modela.Remove all unused columns and tables.
b. Avoid bi-directional relationships unless necessary.
c. Pre-calculate measures in Power Query where possible.

4. Avoid Table/Matrix Visuals - Instead use Card visuals for KPIs, Line/bar charts for trends, Drillthrough pages for detailed views.

If this solved your issue, please mark it as the accepted solution. ✅