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Hi there,
As the title suggests, I have two facts tables with different granularity, as indicated in the picture below. I would like to visualize the data from both fact tables while using attributes from all three dimension tables even though that one of these isn't related to the second fact table. Now the issue seems to be that Power BI's calculation engine goes banans when an attribute from the third dimension (manufacturer) is introduced to the list visual. I get the logic behind this, but is there any tricks to making the budget 'ignore' the manufacturer column? I tried the ALL and REMOVEFILTERS functions without any success.
And no, we can't make a nice little snowflake schema with the two somewhat related dimensions.
Any suggestion would be appreciated.
Thank you,
Solved! Go to Solution.
i would suggest to use a matrix .
then in your measure you can use the isinscope function to control the calculation per each level .
NB : when using isinscope , always start with the lowest level to the highst . example below :
matrix : product category --> product
measure =
switch(true() ,
isinscope(tbl_name[prodcut]) , calculation_1 ,
isinscope ( tbl_name[product category) , calculation_2
)
in your example, you can set, that if isinscope( dim_manufacturer[name] , to return blank() --> for budget .
let me know if this helps .
If my answer helped sort things out for you, i would appreciate a thumbs up 👍 and mark it as the solution ✅
It makes a difference and might help someone else too. Thanks for spreading the good vibes! 🤠
i would suggest to use a matrix .
then in your measure you can use the isinscope function to control the calculation per each level .
NB : when using isinscope , always start with the lowest level to the highst . example below :
matrix : product category --> product
measure =
switch(true() ,
isinscope(tbl_name[prodcut]) , calculation_1 ,
isinscope ( tbl_name[product category) , calculation_2
)
in your example, you can set, that if isinscope( dim_manufacturer[name] , to return blank() --> for budget .
let me know if this helps .
If my answer helped sort things out for you, i would appreciate a thumbs up 👍 and mark it as the solution ✅
It makes a difference and might help someone else too. Thanks for spreading the good vibes! 🤠
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