I have a dataset with multiple user logins and multiple districts as follows:
| User | District | Region |
|---|---|---|
| UserA | HKG | China |
| UserA | PRG | Europe |
| UserA | CKG | China |
| UserB | LHR | Europe |
| UserB | AMS | Europe |
| UserB | TYO | Japan |
| UserA | CKG | China |
| UserC | SYD | Australia |
| UserC | MEL | Australia |
| UserD | SYD | Australia |
| UserD | MEL | Australia |
I want to see the count of users that have logged into more than a single district within a region
| Region | Created Measure |
|---|---|
| China | 1 |
| Europe | 1 |
| Japan | 0 |
| Australia | 2 |
China has 1, because only UserA has logged into multiple China Districts Europe has 1, because only UserB has logged into multiple Europe Districts Japan has 0, because no user has logged into more than 1 Japan District Australia has 2, because both User C & D have logged onto multiple Australia Districts
I have gotten close with creating a table, but I can only seem to get it to count the distinct values, not the values where the aggregate is greater than 1. This is the DAX I have so far:
DEFINE
TABLE UserGroup =
SUMMARIZECOLUMNS (
User[User],
User[Branch],
User[Region],
"UserCount", COUNT('User'[User]),
"User Distinct Count", DISTINCTCOUNT('User'[User])
)
EVALUATE
GROUPBY(
UserGroup,
UserGroup[Region],
"Failing Formula", SUMX(CURRENTGROUP(), [User Distinct Count])
)