Forum Discussion
Sum data after matching dates from 2 tables
- 7 years ago
Hi Anonymous,
create a 1-to-many relationship between concact_table and payment_table and then use this formula
= SUMX ( contact_table, VAR FailDate = contact_table[failed_payment_date] RETURN CALCULATE ( SUM ( payments_table[payment_amount] ), payments_table[payment_date] > FailDate ) )
Hi Anonymous,
create a 1-to-many relationship between concact_table and payment_table and then use this formula
=
SUMX (
contact_table,
VAR FailDate = contact_table[failed_payment_date]
RETURN
CALCULATE (
SUM ( payments_table[payment_amount] ),
payments_table[payment_date] > FailDate
)
)Hey LivioLanzo - Thank you sir. Yes with some additional pieces that did the trick.
- LivioLanzo7 years ago
Solution Sage
Hi Anonymous
can you post a screenshot of what is happening?
- Anonymous7 years agoNot applicable
Hi LivioLanzo
Sure
What im seeing is when drill down is on with a split by custom ID you can see it shows the right total by "cohort" meaning month, but behind the scenes its still totaling out to be sky high.
For Context the below is only showing 1 cohort which should show that 20k as the total in the grand total at the bottom, but it shoots to 126 million.
- LivioLanzo7 years ago
Solution Sage
hI Anonymous
what is difference between the contact table and IFS 1 table?
in my measure VAR FailDate is coming from the contact table, but i see it is not the case in your measure