Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
I've been stuck on this for a while, so I'm reaching out here for some help. I'm working with two calculated columns that take one value and turn it into another value 0-100 (from where we get the average of that value to represent performance). Then, I have a measure that counts a number of "True"s against "False"s to get a percentage of what falls into column A instead of column B, and then I use that percentage to weight column A v. column B into a kind of average.
With column A as "A", column B as "B", and the measure as "M", the formula I use looks like:
A * M + B * (1 - M)
With an example of an output for it being somewhere where column A averages to 80, column B averages to 40, and the value of M is 60%, so:
80 * .6 + 4 * (1 - .6) = 49.6
What I'm wondering is how do I make this work in DAX for a measure, and is it even something that's workable considering that M is a measure and I know there's limitations on calculating against a measure? Added to the fact that A and B are calculated columns but I'm interested in getting the average to work with the measure instead of just individual values in said columns.
Solved! Go to Solution.
I figured this out and am following up on my thread just because it was painfully obvious - I just needed to build individual measures for each value and then I was able to do the math as laid out above, replacing variables with the measures.
I figured this out and am following up on my thread just because it was painfully obvious - I just needed to build individual measures for each value and then I was able to do the math as laid out above, replacing variables with the measures.
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
107 | |
98 | |
77 | |
66 | |
53 |
User | Count |
---|---|
144 | |
104 | |
100 | |
86 | |
64 |