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Hi All,
Issue is not exactly removing duplicates but possibility of removing repeated records for few IDs
For example:
I have 6 columns, am getting data for all IDs but few IDs have two records, user don't want to see the null value record for that particular ID.
Consider in below table ID 101 has two records with cust group AFGH value and null value as well. I want to eliminate null record for that particular ID. in the same way we have two records for ID 105 like that we have so many IDs have two records which we need to eliminate null value record. Please help me on this how to fix it, if requirement is not clear pls let me know so that i could explain you in detail.
Why user want to remove repeated record for the same ID bec'z when user summing up the net value, there is a chance for summing up the net value two times for the same ID.
For ID 101 net value USD should be 1000 only but when the record repeats it will become 2000 dollars which is wrong.
ID | company name | customer country | cust group | net value USD | net value EUR | |
101 | abc | UK | GRPUK | 1000 | 1500 | |
101 | abc | UK | null | 1000 | 1500 | |
102 | cognizant | USA | GRPUSA | 2000 | 2500 | |
103 | ibm | FRANCE | GRPFRA | 3000 | 3500 | |
104 | value labs | INDIA | GRPIND | 4000 | 4500 | |
105 | philips | GERMANY | GRPGER | 5000 | 5500 | |
105 | philips | GERMANY | null | 5000 | 5500 |
|
Highlight the "cust group" dimension and check the "Suppress When Value Is Null" box.
The single record also contains null values that should not be excluded by checking this option, bec'z i already tried this option and am getting very less count which is not correct. please tell me another approach. thank you.
If that's the case, it sounds like you're looking for a chart-level fix to a data/model problem (because the obvious solution is, fix the rows for which "cust group" is incorrectly showing as null.
Beyond that, you can change "cust group" to a calculated dimension where you write an IF statement that puts words to the logic that tells you which NULLs are good and which ones aren't.