DAX

Anonymous 

MAX vs SELECTEDVALUE: The choice between MAX and SELECTEDVALUE depends on the context of your data and what you are trying to achieve. MAX returns the maximum value in a column, which is useful when you need the highest value. SELECTEDVALUE returns the value when there is only one value in the context, otherwise it returns a specified alternate result (or BLANK if not specified). SELECTEDVALUE is often used in scenarios where you expect a single value in the context and want to handle cases where there might be multiple values more gracefully. If you are certain that there will always be a single value in the context, SELECTEDVALUE can be more intuitive and safer to use.

Comparing DateKey vs fullDate: Comparing a numeric DateKey (e.g., 20250531) is generally faster than comparing full date formats because numeric comparisons are less computationally intensive than date comparisons. However, the performance difference might be negligible unless you are performing a very large number of comparisons. Using DateKey can also simplify the logic and improve readability if your data model is designed around these keys.

Creating a separate measure vs using the function in a variable: Creating a separate measure with SELECTEDVALUE or MAX and then referring to it in all dependent measures can improve performance and maintainability. This approach avoids redundant calculations and makes your DAX code cleaner and easier to manage. Using variables within each measure can also be beneficial for performance, as it ensures that the calculation is performed only once per evaluation context. However, if the same logic is used across multiple measures, defining a separate measure is generally the better approach.

1. There in no optimal choice as they are different. MAX returns the maximum value among many values visibile in the filter context, SELECTEDVALUE returns either the only value visibile in the filter cotext or blank (or a chosen default value you can set when there are multiple values visibile)

2. Date is better if DateKey(20250531) is a text otherwise if it is a number DateKey(20250531) is better as numbers are always fastwer to manage for keys. Avoid please datetime unless really needed

3. Surely better separate measures and their reuse

Hi Anonymous 

Your questions touch on important DAX performance and modeling practices, especially when working with larger datasets and multiple interdependent measures. First, when choosing between MAX and SELECTEDVALUE, the key difference is that MAX returns the highest value in the current filter context, even if multiple values exist, while SELECTEDVALUE returns a value only if there's a single distinct value, otherwise it returns blank or a default. In most cases, if you’re expecting a single value (like a date selected via slicer), SELECTEDVALUE is safer as it helps catch unexpected multiple selections; however, MAX can be better when you're intentionally aggregating or want to tolerate multi-selection contexts. Second, comparing an integer-based DateKey (like 20250531) versus a full Date column can have minor performance differences. In general, comparing integers is slightly faster than comparing date values, especially in large models, but the difference is often negligible unless done inside expensive row iterations. Still, many teams prefer using DateKey in fact tables for performance and simplicity, particularly in star schema designs. Third, in terms of performance and maintainability, it's usually a good idea to centralize commonly used expressions—like a selected date or threshold—into separate helper measures rather than repeating logic across 40–50 other measures. This approach improves readability, reduces maintenance effort, and may benefit query plan reuse, though the performance difference might be minimal unless the logic is complex or involves context transitions. So while performance gains might be small individually, your instinct is right: in large-scale models with many measures, consistent and centralized logic can reduce redundancy, improve DAX maintainability, and lead to more stable performance over time.