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Hi guys,
I've been banging my head against this challenge for a little over a week now, so I was hoping some of you smart people can help out! I have seen solutions relating to numerical values for snapshot comparisons that seem to work, but I can't figure out how to convert that when it's a boolean/string.
So I've got a Snowflake schema in my data model view in Power BI. My company is also using daily snapshots of the data so we can follow the progress over time. This especially relates to our forecasts. We have a boolean field that denotes whether we expect to order to come through or not. When we sum up the expected orders with a snapshot date at the beginning of the month, this number will change throughout the month because orders are moved in and out of the expected field. To easily surface and investigate what those moved orders are, I would like to give the user a comparison period slicer to chose and show them the expected deals along with deals that were changed. In terms of the slicer (having a relative date slicer or two separate slicers) I'm open to suggestions.
I've tried creating calculated columns showing the expected value at the first snapshot date (having a relative date slicer on snapshot date or two different slicers - one for a inactive relationship snapshot date dim and one for an active), but with no success because I can't get it to return the expected field in a CALCULATE function based on my conditions (USERELATIONSHIP to an inactive snapshot date dim, ALL(snapshot date dim) from primary relationship.
I would really appreciate any help!
Edit: I've added the data model and an example of the data and desired output
This is my essentially the desired output based on a snapshot date filter between 1-4. Expected start would show what the expected value is at the start period selected regardless of what snapshot date we are looking at now.
Snapshot Date | Record | Expected | Expected Start |
01-01-2020 | aaaa | TRUE | TRUE |
02-01-2020 | aaaa | TRUE | TRUE |
03-01-2020 | aaaa | FALSE | TRUE |
04-01-2020 | aaaa | FALSE | TRUE |
01-01-2020 | bbbb | FALSE | FALSE |
02-01-2020 | bbbb | TRUE | FALSE |
03-01-2020 | bbbb | TRUE | FALSE |
04-01-2020 | bbbb | TRUE | FALSE |
Hopefully that's enough to go by otherwise I'm happy to add more!
i dont think anyone will give you a solution without some sort of example data/model.
Thanks - first post I've made on here. I've added more info that hopefully provides better context.
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