Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!Learn from the best! Meet the four finalists headed to the FINALS of the Power BI Dataviz World Championships! Register now
Hi everyone,
Apologies for reposting a similar issue. I've gone through several previous posts and solutions shared by others regarding this common problem, but unfortunately, I haven't been able to apply any of them successfully to my specific context.
Context: I'm trying to calculate the difference between the selected year (via slicer) and the prior year.
Problem: The matrix correctly displays data for the selected year but shows nothing for the prior year.
Attempts so far:
I've tried multiple approaches, including adding a prior_year column in the dim_time table and experimenting with various DAX formulas. Below is my latest DAX attempt, which still doesn’t work as expected.
UOM_difference =
VAR SelectedYear = SELECTEDVALUE(dim_time[year])
VAR PriorYear = SelectedYear - 1
VAR UOM_Selected_Year = CALCULATE(
SELECTEDVALUE(financial[UOM %]),
FILTER(dim_time, dim_time[year] = SelectedYear &&
(dim_time[period] = "FY" || dim_time[period] = "H1")),
FILTER(dim_region, dim_region[region_name] = "Global")
)
VAR Prior_Year = CALCULATE(
SELECTEDVALUE(financial[UOM %]),
REMOVEFILTERS(dim_time[year]),
FILTER(dim_time, dim_time[year] = PriorYear &&
(dim_time[period] = "FY" || dim_time[period] = "H1")),
FILTER(dim_region, dim_region[region_name] = "Global")
)
RETURN IF(NOT ISBLANK(UOM_Selected_Year) && NOT ISBLANK(Prior_Year),
(UOM_Selected_Year - Prior_Year) * 100,
BLANK()
)
Thank you for looking through my issue. I'd appreciate it if you could drop any explanation/hint/solution on this issue.
Solved! Go to Solution.
@Anonymous Try this:
UOM_Prior_Year 1 =
VAR SelectedYear = SELECTEDVALUE(dim_time[year])
VAR PriorYear = SelectedYear - 1
VAR __Company = MAX( 'dim_company'[company_id] )
VAR __Dates = SELECTCOLUMNS( FILTER( ALL( 'dim_time' ), [period] = "FY" || dim_time[period] = "H1"), "Date", [date_key] )
VAR __Regions = SELECTCOLUMNS( FILTER( ALL( 'dim_region' ), dim_region[region_name] = "Global" ), "Region", [region_id] )
VAR __Table = FILTER( ALL( 'financial' ), [date_key] IN __Dates && [region_id] IN __Regions && [company_id] = __Company )
VAR __Result = SUMX( __Table, [UOM %] )
RETURN
__Result
@Anonymous Try this:
UOM_Prior_Year 1 =
VAR SelectedYear = SELECTEDVALUE(dim_time[year])
VAR PriorYear = SelectedYear - 1
VAR __Company = MAX( 'dim_company'[company_id] )
VAR __Dates = SELECTCOLUMNS( FILTER( ALL( 'dim_time' ), [period] = "FY" || dim_time[period] = "H1"), "Date", [date_key] )
VAR __Regions = SELECTCOLUMNS( FILTER( ALL( 'dim_region' ), dim_region[region_name] = "Global" ), "Region", [region_id] )
VAR __Table = FILTER( ALL( 'financial' ), [date_key] IN __Dates && [region_id] IN __Regions && [company_id] = __Company )
VAR __Result = SUMX( __Table, [UOM %] )
RETURN
__Result
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
Check out the February 2026 Power BI update to learn about new features.
| User | Count |
|---|---|
| 50 | |
| 49 | |
| 35 | |
| 15 | |
| 14 |
| User | Count |
|---|---|
| 91 | |
| 75 | |
| 41 | |
| 26 | |
| 25 |