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!Vote for your favorite vizzies from the Power BI Dataviz World Championship submissions. Vote now!
Hi all,
I have a strange situation/model where the header has some sales ID records and amounts which have no corresponding lines in the child/many side. I need to sum all the values from the header where there are no matching lines. This is a one to many relationship between header and lines.
Example:
Sales Header (parent)
Sales Key Sales Amount
1 500
2 300
3 100
4 200
Sales Lines
Sales Key Line#
1 1
1 2
2 1
What I'd need is the sum amount from the header rows for Sales Key 3 and 4 in the above example, which would return 300. If we did a left outer join it would be the null rows.
Essentially I need to CALCULATE(SUM(SalesHeader[Amount]), FILTER(SalesHeader, SalesHeader[Sales Key]
NOT IN (SalesLines[Sales Key])
Obviosuly the above is incorrect as I'm not sure how to express NOT IN [list of values in related table] by using DAX. Any help is wonderful!
Solved! Go to Solution.
Then use VALUES(SalesLines[Sales Key]) to create a table of values for it to use.
NOT is available in DAX though. The syntax would look like this:
CALCULATE(SUM(SalesHeader[Amount]), FILTER(SalesHeader, NOT(SalesHeader[Sales Key] IN SalesLines[Sales Key])))
This doesn't seem to work, unfortunately.
After the IN statement, I cannot specify a column name, it's looking for a measure or table for some reason.
Then use VALUES(SalesLines[Sales Key]) to create a table of values for it to use.
Ah, of course. Worked like a charm, thank you!
Vote for your favorite vizzies from the Power BI World Championship submissions!
If you love stickers, then you will definitely want to check out our Community Sticker Challenge!
Check out the January 2026 Power BI update to learn about new features.
| User | Count |
|---|---|
| 59 | |
| 53 | |
| 42 | |
| 20 | |
| 16 |
| User | Count |
|---|---|
| 123 | |
| 106 | |
| 44 | |
| 32 | |
| 24 |