Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
I have the following excel formula that I need to convert to DAX for Power BI (Power BI column names are in italics within the excel formula):
Area Sell Contract Price = IFERROR(SUMIFS('Sell Contract Details'!$Z:$Z Sell Extended Price, 'Sell Contract Details'!$D:$D Area, 'Inbound Details'!$H14 Area, 'Sell Contract Details'!$L:$L Product Class, 'Inbound Details'!$B14 Material Grade) / SUMIFS('Sell Contract Details'!$Y:$Y Sell Order LB, 'Sell Contract Details'!$D:$D Area, 'Inbound Details'!$H14 Area, 'Sell Contract Details'!$L:$L Product Class, 'Inbound Details'!$B14 Material Grade), "")
Sell Contract Details and Inbound Details are unrelated tables in my Power BI report. I cannot create a relationship because neither table has a unique identifier (many:many). The join is on Inbound Details.Area = Sell Contract Details.Area and Inbound Details.Material Grade = Sell Contract Details.Product Class.
I was able to get the Average Sell Contract Price with the following DAX formula:
...but if there is more than 1 'Inbound Details'[Loads] per 'Inbound Detail'[Supplier], the result is the 'Sell Contract Detail'[Average Sell Price] * 'Inbound Detail'[Loads].
I tried DIVIDE('Sell Contract Detail'[Average Sell Price],'Inbound Detail'[Loads],0)), but the result is the same.
Any suggestions?
Hi @kekepania0529 ,
Without data is difficult to give any correct way of formulating the measure.
Can you please share a mockup data or sample of your PBIX file. You can use a onedrive, google drive, we transfer or similar link to upload your files.
If the information is sensitive please share it trough private message.
Regards
Miguel Félix
Proud to be a Super User!
Check out my blog: Power BI em PortuguêsCovering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
110 | |
94 | |
82 | |
66 | |
58 |
User | Count |
---|---|
151 | |
121 | |
104 | |
87 | |
67 |