Dynamic Row-Level Calculation in Matrix (Different Logic per Row) - Scalable Approach?

Hi manvishah17 ,

For calculation groups, it’s key to note that they do not require a shared or base measure. The measure you add to the Values well acts as a trigger, and when the visual is evaluated, the engine substitutes each calculation item’s logic in place of the measure. This allows each row to have independent logic, even across different tables. SELECTEDMEASURE becomes relevant only when you need calculation groups to interact, such as passing logic between rows and columns. If that’s not required, each calculation item can remain self-contained, and you can disregard SELECTEDMEASURE.

Regarding the SWITCH and bucket method, your concern about execution is well-founded. While SWITCH appears to evaluate just one branch, the DAX engine doesn’t always short-circuit as traditional languages do. With many branches, especially across different tables, the engine may evaluate more logic than expected, leading to higher memory usage and possible resource errors.

By splitting logic into buckets, you help the engine focus on a smaller group of calculations, reducing the dependency tree and storage engine queries. Storing the selected specification in a variable further optimizes performance by avoiding repeated filter context evaluations.

Both approaches are valid and serve different needs. Calculation groups offer flexibility for scenarios requiring interaction between rows and columns in a visual. The bucketed measure approach is generally easier to manage and performs well if each bucket is kept to a reasonable size. If your column logic is relatively static, the bucketed approach is often more straightforward. 

Thank you.