Forum Discussion
Filter Measure Between Dates
I managed to created a count measure that works as I would like;
Count of Active =VAR __SelectedDate = [Selected Date]ReturnCALCULATE(COUNT('Risk Data'[Id]),__SelectedDate>'Risk Data'[FromTT], IF(ISBLANK('Risk Data'[ToTT]), TRUE(), __SelectedDate<'Risk Data'[ToTT]))
But I'm not sure how'd I go about turning this into a true/false filter measure of each risk IDhi Anonymous
Anonymous wrote:
I managed to created a count measure that works as I would like;
Count of Active =VAR __SelectedDate = [Selected Date]ReturnCALCULATE(COUNT('Risk Data'[Id]),__SelectedDate>'Risk Data'[FromTT], IF(ISBLANK('Risk Data'[ToTT]), TRUE(), __SelectedDate<'Risk Data'[ToTT]))
But I'm not sure how'd I go about turning this into a true/false filter measure of each risk IDI have test on my side, This formula works well, and what is " I'm not sure how'd I go about turning this into a true/false filter measure of each risk ID"?
Regards,
Lin
Ah sorry, I've just realized if I use my count of acting as the visual level filter, I just need to set it to is greater than 0 to get the effect I was looking for.
The previous response about setting the filter to true was confusing me since it wasn't an IF measure.
The issue with creating a relationship for the date is that I have several other tables with similar data with from and to date ranges, that all relate to each other, so I cant relate the date table to each other without creating circular references
I would be curious to see the relationship diagram
If you think about your several tables as fact tables... they should all be able to be joined by a single date table that had a one to many relationship to all of them
If you want to relate the the same date column in each table.
If you want to also relate the other date column, the one you don't seem to be using in your example, I can see that you might need to then have a second date table to relate to all of those columns. Then any filters or slicers should work on all the "fact" tables independantly.
The other option might be.. and I'm reaching here. To have tables which had the error condition and one record for each day it was operative. Then answering questions like, how many errors of each type were open on a certain day would be straightforward, without having to do a lot of equal to or less than style of logic.
I'd love to have a more extended conversation with you about the whole problem.
I managed to created a count measure that works as I would like;
Count of Active =VAR __SelectedDate = [Selected Date]ReturnCALCULATE(COUNT('Risk Data'[Id]),__SelectedDate>'Risk Data'[FromTT], IF(ISBLANK('Risk Data'[ToTT]), TRUE(), __SelectedDate<'Risk Data'[ToTT]))
But I'm not sure how'd I go about turning this into a true/false filter measure of each risk IDhi Anonymous
Anonymous wrote:
I managed to created a count measure that works as I would like;
Count of Active =VAR __SelectedDate = [Selected Date]ReturnCALCULATE(COUNT('Risk Data'[Id]),__SelectedDate>'Risk Data'[FromTT], IF(ISBLANK('Risk Data'[ToTT]), TRUE(), __SelectedDate<'Risk Data'[ToTT]))
But I'm not sure how'd I go about turning this into a true/false filter measure of each risk IDI have test on my side, This formula works well, and what is " I'm not sure how'd I go about turning this into a true/false filter measure of each risk ID"?
Regards,
Lin
Ah sorry, I've just realized if I use my count of acting as the visual level filter, I just need to set it to is greater than 0 to get the effect I was looking for.
The previous response about setting the filter to true was confusing me since it wasn't an IF measure.
A lot of them seem to be history tables... are they all histories of the same event ?
The Data is for BowTie Reporting. We have different hazards at our company, i.e. Vehicle accidents. Each of these hazards have different threats and consequences, example threats being crash as the result of employee intoxication, or crash as a result of third-party error. Different consequences being cost of destroyed vehicles, physical injury, loss of life. These threats and consequences have controls to mitigate these risks, such as license checks to take out company cars, sobriety checks, insurance to mitigate financial loss. All of these have different levels of severity and likelihood allocated to them, such as a crash resulting in loss of life being high severity and low likely hood, or a fender bender being moderate likelihood, low severity. These likelihoods are determined by the efficacy of the controls to prevent them such as the sobriety check and license reducing the likelihood of occurrence, so when new check are added in, likelihoods change, or if we implement more effective controls. I want to be able to see the number of risks over time, how effectively we've been covering them etc.