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Is this possible with Power BI?
If I understand RLS correctly, all of my data has a tenant-id which I can use to filter by customer....So I can give customer 1 their data, customer 2 theirs but Nobody linked to Customer 1 can see data for Customer 2.
However, I would like the customers to be able to compare their aggregates against "overall" aggregates obtained from all data from all customers.
Something like this:
Customer 1 sees:
No. of widgets this month: 20
Overall Average widgets this month: 16.8
Performance this month: +3.2
Customer 2 sees:
No of widgets this month: 15
Overall Average widgets this month: 16.8
Performance this month: -1.8
ie, all customers share the average number of widgets, but they only see their own widget totals
Solved! Go to Solution.
Hi @horizondave,
I'm afraid this is restricted by the way how RLS works. Maybe you can add many attributes in one calculated table like this:
Table =
ADDCOLUMNS (
{ "Summarized Values" },
"Total Sales Quantity", SUM ( 'Sales'[Quantity] ),
"Total Sales Amount", SUMX ( Sales, Sales[Net Price] * Sales[Quantity] ),
"Number of kinds of Products", DISTINCTCOUNT ( 'Product'[Brand] )
)
Best Regards!
Dale
Hi @horizondave,
The solution could be that you can add the Overall as a calculated column. Or create a summarized table. You can try it out.
Best Regards!
Dale
The trouble is I potentially have *lots* of these attributes I want to add as averages....It's a very time consuming option to have to create each one individually.
Hi @horizondave,
I'm afraid this is restricted by the way how RLS works. Maybe you can add many attributes in one calculated table like this:
Table =
ADDCOLUMNS (
{ "Summarized Values" },
"Total Sales Quantity", SUM ( 'Sales'[Quantity] ),
"Total Sales Amount", SUMX ( Sales, Sales[Net Price] * Sales[Quantity] ),
"Number of kinds of Products", DISTINCTCOUNT ( 'Product'[Brand] )
)
Best Regards!
Dale
Hi @horizondave,
Could you please mark a answer for this thread?
Best Regards,
Dale
I have accepted your answer as a potential solution, but my actual solution was to not use Power BI as it wasn't a good fit for my solution for other reasons.
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