The ultimate Microsoft Fabric, Power BI, Azure AI, and SQL learning event: Join us in Stockholm, September 24-27, 2024.
Save €200 with code MSCUST on top of early bird pricing!
Find everything you need to get certified on Fabric—skills challenges, live sessions, exam prep, role guidance, and more. Get started
Hi Experts,
I'm trying to do a dynamic sum based on time periods selected to compare changes over the time period. The problem I'm having is that I need to be able to only sum sales when a store is present in both the pre and post time periods.
My data is structured as follows:
Store | Item | Sales | Time Period |
1 | Item A | 243 | Q2 2023 |
1 | Item B | 200 | Q2 2023 |
1 | Item C | 195 | Q2 2023 |
2 | Item A | 377 | Q2 2023 |
2 | Item B | 158 | Q2 2023 |
2 | Item C | 235 | Q2 2023 |
2 | Item D | 374 | Q2 2023 |
3 | Item A | 245 | Q2 2023 |
3 | Item B | 116 | Q2 2023 |
3 | Item C | 392 | Q2 2023 |
2 | Item A | 287 | Q1 2023 |
2 | Item B | 188 | Q1 2023 |
2 | Item C | 114 | Q1 2023 |
2 | Item D | 398 | Q1 2023 |
3 | Item A | 148 | Q1 2023 |
3 | Item B | 325 | Q1 2023 |
3 | Item C | 214 | Q1 2023 |
4 | Item A | 348 | Q1 2023 |
4 | Item B | 298 | Q1 2023 |
My tables are setup as follows:
Formulas for Post Period Sales and Pre Period Sales are as follows:
Post Period Sales =
CALCULATE(
SUM(FactSales[Sales]),
GROUPBY(DimItem, DimItem[Item])
)
Pre Period Sales =
CALCULATE(
SUM(FactSales[Sales]),
REMOVEFILTERS(DimTimePeriod[Time Period]),
GROUPBY(DimItem, DimItem[Item]),
USERELATIONSHIP(FactSales[Time Period], DimTimePeriodCompare[Time Period])
)
Layout on canvas for simple table would have the DimTimePeriod and DimTimePeriodComparison in slicers so the end user can select which time periods they want to compare.
How can I adjust my formulas to omit any stores that do not appear in both time periods? The above example currently shows sum of sales for all stores, but Stores 1 and 4 are not in both time periods.
Solved! Go to Solution.
For anyone that comes across this post, I was able to work out how to do it using an INTERSECT function and some clever filtering.
Pre Period Sales =
VAR PreStores =
CALCULATETABLE (
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
USERELATIONSHIP ( FactSales[Time Period], DimTimePeriodCompare[Time Period] ),
FILTERS(DimTimePeriodCompare[Time Period])
)
VAR PostStores =
CALCULATETABLE(
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
FILTERS(DimTimePeriod[Time Period]))
VAR CommonStores =
INTERSECT ( PreStores, PostStores )
RETURN
CALCULATE(
SUM(FactSales[Sales]),
REMOVEFILTERS(DimTimePeriod[Time Period]),
GROUPBY(DimItem, DimItem[Item]),
USERELATIONSHIP(FactSales[Time Period], DimTimePeriodCompare[Time Period]),
INTERSECT(CommonStores, VALUES(DimStore[Store])
))
Post Period Sales =
VAR PreStores =
CALCULATETABLE (
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
USERELATIONSHIP ( FactSales[Time Period], DimTimePeriodCompare[Time Period] ),
FILTERS(DimTimePeriodCompare[Time Period])
)
VAR PostStores =
CALCULATETABLE(
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
FILTERS(DimTimePeriod[Time Period]))
VAR CommonStores =
INTERSECT ( PreStores, PostStores )
RETURN
CALCULATE(
SUM( FactSales[Sales] ),
GROUPBY( DimItem, DimItem[Item] ),
INTERSECT(CommonStores, VALUES(DimStore[Store])))
For anyone that comes across this post, I was able to work out how to do it using an INTERSECT function and some clever filtering.
Pre Period Sales =
VAR PreStores =
CALCULATETABLE (
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
USERELATIONSHIP ( FactSales[Time Period], DimTimePeriodCompare[Time Period] ),
FILTERS(DimTimePeriodCompare[Time Period])
)
VAR PostStores =
CALCULATETABLE(
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
FILTERS(DimTimePeriod[Time Period]))
VAR CommonStores =
INTERSECT ( PreStores, PostStores )
RETURN
CALCULATE(
SUM(FactSales[Sales]),
REMOVEFILTERS(DimTimePeriod[Time Period]),
GROUPBY(DimItem, DimItem[Item]),
USERELATIONSHIP(FactSales[Time Period], DimTimePeriodCompare[Time Period]),
INTERSECT(CommonStores, VALUES(DimStore[Store])
))
Post Period Sales =
VAR PreStores =
CALCULATETABLE (
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
USERELATIONSHIP ( FactSales[Time Period], DimTimePeriodCompare[Time Period] ),
FILTERS(DimTimePeriodCompare[Time Period])
)
VAR PostStores =
CALCULATETABLE(
VALUES ( FactSales[Store] ),
ALLCROSSFILTERED(FactSales),
FILTERS(DimTimePeriod[Time Period]))
VAR CommonStores =
INTERSECT ( PreStores, PostStores )
RETURN
CALCULATE(
SUM( FactSales[Sales] ),
GROUPBY( DimItem, DimItem[Item] ),
INTERSECT(CommonStores, VALUES(DimStore[Store])))
For Post Period Sales, you can try and see if this works...
Post Period Sales =
var _stores = CALCULATETABLE( VALUES(FactSales[Store]),
REMOVEFILTERS(DimTimePeriod[Time Period]),
USERELATIONSHIP(FactSales[Time Period], DimTimePeriodCompare[Time Period]),
FactSales[Time Period] in VALUES(DimTimePeriodCompare[Time Period]))
RETURN CALCULATE( SUM(FactSales[Sales]), _stores)
Join the community in Stockholm for expert Microsoft Fabric learning including a very exciting keynote from Arun Ulag, Corporate Vice President, Azure Data.
Check out the August 2024 Power BI update to learn about new features.
User | Count |
---|---|
109 | |
79 | |
72 | |
48 | |
39 |
User | Count |
---|---|
138 | |
108 | |
69 | |
64 | |
57 |