Currently, am working on the report server and am collecting data on cumulative bases which mean every district report it cumulative performances. My database has three different tables one for the performance, one for the date and the other Is for the district. So that my power bi takes the sum of the aggregate of all district under a region. But I need an aggregate of last value from each district summed up, instead of all the value under a district. How can I do that?
Please, can you share some data sample? Also, you can read this article it will help you to get questions answered faster.
@Mariusz thanks for your quick response and I don't know how much I am clear. I tried to depict it here.
Here is some description of the problem that I mentioned before.
The attached file, let me know if it works for you.
The below will fix the total.
Value 2 = SUMX( GROUPBY( 'Table 1', 'Table 1'[District Name], 'Table 1'[country Name] ), CALCULATE( SUM( 'Table 1'[Value] ), LASTDATE( 'Table 2'[Entry_Date] ) ) )
@Mariusz It works for imported mode and thanks to you. But am using direct query mode(In power bi server) in which I'm unable to get DAX for GROUP BY AND LAST DATE. Can you suggest me any other solution?
Thanks a lot,
Unfortunately, I'm not familiar with PIRS, I tried to find DAX functions supported and there is not much around.
The below is using SUMMARIZE instead of GROUPBY and MAX Instead LASTDATE, check if thats any better.
Value 3 = VAR _tbl = ADDCOLUMNS( SUMMARIZE( 'Table 1', 'Table 1'[District Name], 'Table 1'[country Name] ), "Max Date", CALCULATE( MAX( 'Table 2'[Entry_Date] ) ) ) RETURN CALCULATE( SUM( 'Table 1'[Value] ), TREATAS( _tbl, 'Table 1'[District Name], 'Table 1'[country Name], 'Table 2'[Entry_Date] ) )
I attached a link to the file. Can you share it with someone who is an expert in power bi report server
Sample data from direct quire mode
Thank you for your support,
Check out the changes to the Power BI Community announced at Build.
Find out more about the May 2023 update.
Visit our Data Stories Gallery and give kudos to your favorite Data Stories.