The ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM.
Get registeredEnhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends September 15. Request your voucher.
I have some tables imported from different sources into Power BI using M. I have only learnt DAX expressions propoerly till now. I created a new table using DAX expressions directly.
Now, I am trying to write a M query but I am not sure how to import the table that I created using DAX.
I used Source = #"Table1". But it recognizes Table1 only if it was created using M. It doesn't recognize the one created using DAX.
Solved! Go to Solution.
Actually it is possible! But in a really round about way which I don't recommend.
Using Get Data use can specify Analysys Services as your source. If you have DAX Studio you can find the port number your PBI Desktop model is listening on. Simply connect to Localhost:63410 (or whatever port number your model is currently on)
You can then use your DAX tables as data sources to import in. Each time you open/close PBI Desktop the port number will change and you'll have to manually update it which is where it falls apart.
So it's ok for one off work but no good in reality. Mostly interesting.
Query Editor to DAX is a ONE WAY street!
Meaning DAX created tables are NOT accessible in the Query Editor!
Actually it is possible! But in a really round about way which I don't recommend.
Using Get Data use can specify Analysys Services as your source. If you have DAX Studio you can find the port number your PBI Desktop model is listening on. Simply connect to Localhost:63410 (or whatever port number your model is currently on)
You can then use your DAX tables as data sources to import in. Each time you open/close PBI Desktop the port number will change and you'll have to manually update it which is where it falls apart.
So it's ok for one off work but no good in reality. Mostly interesting.
Thanks for the workaround. For this time I will rewrite my queries. But it might come in handy when there are too many queries to be rewritten.
User | Count |
---|---|
65 | |
62 | |
60 | |
54 | |
30 |
User | Count |
---|---|
180 | |
88 | |
72 | |
48 | |
46 |