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Hey guys, I have a table like this:
| Timestamp | | Day | | Event | | Shift |
| 14:00:00 | 01/03/2019 | Event C | Early Shift
| 13:03:00 | 01/03/2019 | Event B | Early Shift
| 08:34:24 | 01/03/2019 | Event A | Early Shift
| 15:12:21 | 01/03/2019 | Event A | Late Shift
| 24:02:12 | 01/03/2019 | Event A | Night Shift
| 03:03:11 | 01/03/2019 | Event A | Night Shift
So here is an explanation of what I need to do: every shift needs to do one "Event A"
So in this case it would be 100% completion for the day because early, late and night shift did an "Event A"
I want to count if there is an Event A in a shift. In my example table there are 2 Event A's in Night Shift but in order for it to be completed they only need one. So I want it to be counted as completed no matter if there are 1 or 5 of these Event A's.
And it should be counted in a way so that it is scalable. That means I need to be able to look at the last few days and see if everything got 100% completed or not.
Let me know if you need more clearification on what I want to do..
Thanks for your help guys.
Hi @Anonymous
try to normalize the data and adding 2 dimensions for shifts and events
then drop the day on the matrix rows and this measure, when it is equal to 3 then 100% is completed:
Measure = CALCULATE ( COUNTROWS ( SUMMARIZE ( Data, Events[Event], Shifts[Shift] ) ), TREATAS ( DATATABLE ( "event", STRING, "shift", STRING, { { "EventA", "EarlyShift" }, { "EventA", "NightShift" }, { "EventA", "LateShift" } } ), Events[Event], Shifts[Shift] ) )
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