Don't miss your chance to take the Fabric Data Engineer (DP-600) exam for FREE! Find out how by watching the DP-600 session on-demand now through April 28th.
Learn moreJoin the FabCon + SQLCon recap series. Up next: Power BI, Real-Time Intelligence, IQ and AI, and Data Factory take center stage. All sessions are available on-demand after the live show. Register now
Hi Forum,
Inspired by this article, I'd like to create automated unit tests to test measures within my Power BI Semantic Model (Dataset).
I'm planning to:
- Use Powershell to connect to and run through the tests
- DAX scripts to query the Semantic Model itself
Since these are unit tests, I want to contain "fake" data within the test itself (not have to worry about the underlying database changing).
A few approaches I've attempted.
1. Overwrite Existing Table for Test (Doesn't work; PBI won't let me overwrite the actual_table in the semantic model)
DEFINE
TABLE actual_table = UNION(ROW("order","A1"),ROW("order","B1")) -- attempt to update as a "local variable"
MEASURE 'Measures Table'[COUNT_ORDERS] = DISTINCTCOUNT('actual_table'[order]))
EVALUATE
ROW("COUNT_ORDERS",'Measures Table'[COUNT_ORDERS])Error: Table '<ccon>actual_table</ccon>' cannot be created because a table or variable with the same name already exists.
2. Update Table Reference (Pretty sure PBI was designed purposely not to do this)
DEFINE
TABLE test_table = UNION(ROW("order","A1"),ROW("order","B1"))
MEASURE 'Measures Table'[COUNT_ORDERS] = DISTINCTCOUNT('actual_table'[order])) -- somehow update table reference 'actual_table' to 'test_table'
EVALUATE
ROW("COUNT_ORDERS",'Measures Table'[COUNT_ORDERS])
3. SWITCH between actual table and test table (I don't like this approach because I'd have to duplicate the SWITCH across all measures)
DEFINE
TABLE test_table = UNION(ROW("order","A1"),ROW("order","B1"))
MEASURE 'Measures Table'[COUNT_ORDERS] =
SWITCH(2,
1,DISTINCTCOUNT('actual_table'[order]),
2,DISTINCTCOUNT('test_table'[order])
)
EVALUATE
ROW("COUNT_ORDERS",'Measures Table'[COUNT_ORDERS])
Do you have any alternative recommendations? Your help is greatly appreciated.
Have your test data be part of the regular data source refreshes. For production use a filter that excludes the test data. For unit testing flip the filter to exclude the production data.
Check out the April 2026 Power BI update to learn about new features.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
| User | Count |
|---|---|
| 7 | |
| 6 | |
| 4 | |
| 1 | |
| 1 |
| User | Count |
|---|---|
| 16 | |
| 8 | |
| 7 | |
| 6 | |
| 6 |