I have a data-set that is made up of "accounts" and the dates at which various states of implementation are completed.
I am trying to aggregate them so that each account only has 1 row per account.
The data can have the same account undergoing 2 different implementations to the unique key and/or grouping is Account ID and Start date. If any of the rows in a column of the grouping have a non-null value, then all null fields should be changed to that value.
I was toying with various multi-row formulas, but I can't quite get it.
The data looks like this
| Account ID | Start Date | Implementation | Development | Staging | Production |
| ABC | 11/1/2020 | Null | Null | Null | Null |
| ABC | 11/1/2020 | Null | Null | 7/1/2020 | Null |
| ABC | 11/1/2020 | Null | 6/1/2020 | Null | Null |
| ABC | 11/1/2020 | 5/1/2020 | Null | Null | Null |
| ABC | 9/1/2020 | Null | Null | Null | 6/1/2020 |
| ABC | 9/1/2020 | Null | Null | 5/1/2020 | Null |
| ABC | 9/1/2020 | Null | 4/1/2020 | Null | Null |
| ABC | 9/1/2020 | 3/1/2020 | Null | Null | Null |
I'm trying to get it o look like this
| Account ID | Start Date | Implementation | Development | Staging | Production |
| ABC | 11/1/2020 | 5/1/2020 | 6/1/2020 | 7/1/2020 | Null |
| ABC | 9/1/2020 | 3/1/2020 | 4/1/2020 | 5/1/2020 | 6/1/2020 |
I've attached the same sample data-set as noted if needed.
Thanks for any help!
Craig