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Hi everyone,
my dataset looks like this:
Customer ID | Amount | Amount Group | Type | Date |
1 | 55 | 100 | T | 02/2017 |
2 | 45 | 50 | TT | 02/2017 |
3 | 50 | 50 | TC | 02/2017 |
1 | 20 | 50 | TC | 02/2017 |
2 | 50 | 50 | T | 03/2017 |
3 | 45 | 50 | TT | 03/2017 |
4 | 55 | 100 | TC | 03/2017 |
1 | 20 | 50 | TC | 03/2017 |
3 | 10 | 50 | T | 03/2017 |
As you can see I have 3 unique Customer IDs in 02/2017 date and 4 unique Customer ID's in 03/2017. So the sum of distinct Customer IDs for these two months is 7.
How to get this sum dynamically, based of filtering across few/or more months?
What I get as result when filtering across these two months is 4, which is true since that is the number of distinct CustomerIDs.
Please note that I need filtering capability of the result with date, type and Amount Group…
Any ideas?
Thanks!
Solved! Go to Solution.
Hi @feyd
Try this MEASURE
measure = SUMX ( VALUES ( TableName[Date] ), CALCULATE ( DISTINCTCOUNT ( TableName[Customer ID] ) ) )
measure = SUMX ( VALUES ( Calendar[Month-Year] ), DISTINCTCOUNT ( Table[Customer ID] ) )
Thank you for quick reply!
I've created the measure and sumx returns 8 instead of 7...
Hi @feyd
Try this MEASURE
measure = SUMX ( VALUES ( TableName[Date] ), CALCULATE ( DISTINCTCOUNT ( TableName[Customer ID] ) ) )
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