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'm not sure if this will make sense (so apologies in advance if this is gibberish) but I keep getting stuck on what initially seemed like a simple calculation. In essence, I have an existing DAX statement to calculate turnover. This represents the "true" turnover being measured. What I'd like to do is create another DAX, which can dynamically filter out a specific group from a specific timeperiod.
For example, if an entire location closes in calendar year 2018, I want to be able to show turnover without the one-time spike of the closure being factored into the equation for that year. The challenge is that it needs to be factored out only during that specific time period where it occurs. Turnover at that location should be still counted in prior time periods (calendar years prior to 2018) where the site was operational and experienced turnover like any other location.
Quick Facts = Data pulls from 3 tables: 1) Date Table; 2) Locations Table; 3) People Table
True turnover calculation
SUMX(ALLSELECTED('date'[fiscal_month]),[Term Total]/[Active Total MonthlyAvg])
Turnover Exclusion (This is the one I'd like to make dynamic instead of hardcoded)
CALCULATE(SUMX(ALLSELECTED('date'[fiscal_month]),[Term Total]/[Active Total MonthlyAvg]),(Locations[Site Name]="JobSiteX"),'date'[fiscal_year]=2018)
To end up with something like this
SUMX(ALLSELECTED('date'[fiscal_month]),[Term Total]/[Active Total MonthlyAvg])
-
CALCULATE(SUMX(ALLSELECTED('date'[fiscal_month]),[Term Total]/[Active Total MonthlyAvg]),(Locations[Site Name]="JobSiteX"),'date'[fiscal_year]=2018)
My revised calculation isn't dynamic though which ultimately is the problem. This means that when I look at calendar year 2017, I'll still be incorrectly subtracting 2018 turnover from JobSiteX when instead I want it to look at calendar year to determine whether to remove the one-time event.
Hi @Anonymous,
More details will be more helpful.
If it is convenient, could you share some data sample which could reproduce your scenario so that I can copy and test.
Best Regards,
Cherry
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 |
---|---|
114 | |
97 | |
85 | |
70 | |
61 |
User | Count |
---|---|
151 | |
120 | |
103 | |
87 | |
68 |