Dynamic/Maintainable Scoping for Calculation Group Logic on Measures

[TJ-9000]

In large Power BI semantic models, it’s common to need calculation groups (such as for currency conversion or time intelligence) that apply only to some measures—typically those with certain characteristics. Currently, the only way to scope calculation group logic (e.g., using ISSELECTEDMEASURE) is to manually list every affected measure. This is difficult to maintain as models grow and evolve.

Problem: there is no dynamic way in DAX to group or reference measures for calculation group logic:

• You can’t reference all measures in a given display folder.
• You can’t filter by metadata or custom tags.
• You can’t check for the existence of a measure or flag at runtime (e.g., with a TRY or IFERROR pattern).
• You can’t use naming conventions or wildcards in ISSELECTEDMEASURE.
• There’s no way for report authors to “opt out” of calculation group logic for new measures without requesting a central model change.

Impact:

• Calculation group maintenance becomes tedious and error-prone.
• Large or decentralized teams cannot easily adapt calculation group logic to evolving reporting needs.
• There’s no flexible, self-service way to manage calculation group scope.

Ideas for Improvement:

• Allow ISSELECTEDMEASURE to reference measures by folder, tag, or attribute (e.g., ISSELECTEDMEASURE(IN FOLDER "Currency Measures") or ISSELECTEDMEASURE(HAS TAG "Currency")).
• Introduce a DAX function to check for the existence of a measure or flag at runtime (e.g., TRY([MyFlagMeasure])).
• Support wildcards or naming patterns in measure selection.
• Enable more dynamic or metadata-driven scoping of calculation group logic, including per-report overrides.

Current Workarounds:

• Manually maintain long lists in ISSELECTEDMEASURE.
• Use external tools to regenerate calculation group DAX based on model structure (not dynamic).
• None of these are as flexible or maintainable as dynamic grouping would be.

Request:
Please consider adding support for more dynamic, maintainable, and metadata-driven approaches to scoping calculation group logic to measures in Power BI.