The report should support reader-driven customization, there are 12 measure & 20 dimension columns where users can dynamically select the required dimensions and measures from the available dataset columns.
Based on the user’s selection, the visual must display only those rows where at least one of the selected measure values is greater than zero.
Rows where all selected measures have value equal to zero or are blank/null should be excluded from the display.
Brand
Payment
Total_Sales
Display
ABC
1000
4
Yes
CAB
0
0
No
DEF
3000
1
Yes
ABC
0
0
No
ABC
0
0
No
GHI
NULL
NULL
No
Rule Interpretation
Row should be displayed → if Payment > 0 OR Total_Sales > 0
Row should NOT be displayed → if Payment = 0 AND Total_Sales = 0
Blank / NULL values should be treated as zero for filtering logic
Hello @QS_User, are you just looking to filter the output of the rows or are you also looking to dynamically update the fields that are in the table visual?
If it is just the filtering, we can definitely manage this through one calculated field that can be implemented as a filter on the visual. I am not sure what all of the scenarios are that a user can select from, but I can build a simple version based on the example you gave above.
Now, 2 things to note. You can apply this calculated field as a filter, set it to no aggregation, and require it to be equal to 1. Then, you can change the dropdown at the bottom of the filter to exclude NULL values. One other thing is depending on how your Payment and Total_Sales fields are calculated, you may run into some issues. Are you directly importing these fields from your dataset or are they calculated fields? If one or both are calculated, we may want to use LAC-W aggregations like sumOver with the PRE_AGG/PRE_FILTER calculation levels to avoid any aggregation errors in the filter calculation. I’ll include some docs below to explain what I am talking about. I am also happy to write an example calculation if you can explain how you are aggregating those fields.
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