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Hi,
Hope you are doing well!
I want to add below filter criteria into my set analysis which includes multiple And/or conditions.
Can you please help me how to write set analysis for below query.
Measure: Count(ID's)
Filter Criteria:( ( Ind_Valid_Only
OR ( Ind_Valid_Only_With_PrivateData
AND Aff_Market_Access_Flag Equal Y
)
OR ( Ind_Status_cod Equal 9
AND Ind_Status_date Greater than_LastDayLast_Month
AND ( Aff_Private_Company Is Null
OR Aff_Market_Access_Flag Equal Y
)
)
)
AND Ind_Professional_Type_cod Equal M
AND Ind_Creation_date Less than or Equal to_LastDayLast_Month
)
Here I want to include my filter criteria into set analysis
Thanks in advance.
Thanks,
SP
Set analysis might not be the best fit for this. It looks like an advanced rule. What if you pre calculate this in the script.
If(( ( Ind_Valid_Only
OR ( Ind_Valid_Only_With_PrivateData
AND Aff_Market_Access_Flag Equal Y
)
OR ( Ind_Status_cod Equal 9
AND Ind_Status_date Greater than_LastDayLast_Month
AND ( Aff_Private_Company Is Null
OR Aff_Market_Access_Flag Equal Y
)
)
)
AND Ind_Professional_Type_cod Equal M
AND Ind_Creation_date Less than or Equal to_LastDayLast_Month
), 1, 0) as flag_field,
Then you could just use: count{<flag_field={1}>}ID)
Hi Vegar,
Thanks for your prompt response.
Attributes I am using in this query are coming from different tables, hence its difficult to implement in script and also I have to implement similar queries for other metrics as well with different attributes.
Thanks,
SP
Does your data-model support this kind of query? NULL for example couldn't be directly queried and in the most scenarios it would be useful to replace them with real values in the script.
A quite quick check would be to use the count-expression without a condition and then selecting all wanted values in the appropriate fields. Are these selections possible and the count returned the expected results an appropriate set analysis statement would be possible. If not you could place all these fields within a table-box and playing again with the selections to see the existing relationships and data which would hint a few directions to adjust the data-model.