Hi, I currently have a rolling story point burndown report (timeline view) which we use to track progress and forecast completion. At the moment the filters to help refine the scope includes ‘Issue Type’, ‘Label’, ‘Fix Version’, along with a number of other options.
Obviously any selection here applies to the entire data set.
I’d like to be able to filter the data by combining some of the existing filters using OR rather than AND, which will (I believe) need a calculated measure…
For Example:
‘Issue Type’ = Task
OR
(‘Issue Type’ = Bug AND (‘Label’ = “Ignore” OR “NotTriaged”))
Any assistance would be gratefully received!!
Hi @AlphaBravo ,
The application of parallel filters from independent dimensions requires inspecting each issue separately to identify its relevance to the filters.
If the parallel conditions come from a separate dimension, you might apply them independently by resetting other dimensions within the filter.
The measure might look as follows.
Sum(
--set of issues
Filter(
DescendantsSet(
[Issue].CurrentMember,
[Issue].[Issue]),
--filter conditions
(
--condtion 1 - one dimension
([Measures].[Issues created],
--reset other dimension that is being ignored at this point
[Dimension 2].DefaultMember)
+
--condition 2 - another dimension
([Measures].[Issues created],
--reset other dimension that is being ignored at this point
[Dimension 1].DefaultMember)
)>0
),
--the numeric value for sum
[Measures].[Issues created]
)
However, if you need to apply combinations of specific dimension members, these options must be hard-coded into the calculation.
At some point, these calculations with iteration through the issues of the data cube become slow.
You might consider creating JavaScript-calculated customfield dimensions to categorize issues during the data import.
Please read more about that here - New calculated fields.
Such precalculated categories would allow more flexibility in changing the categories and would improve the reporting performance. The drawback of this approach is that it is hard-coded, and you would have to re-import all issues of the data cube after changing the conditions for the categories.
Each option has its pros and cons.
Please consider the following points to determine the solution best fitting for you:
1) the independence or the dependence of dimensions and their combinations
2) the number of categories and the requirement for the ability to switch between them
3) the number of issues within the dataset
Once you have considered these details, please get in touch with support directly over e-mail to see the best option for you.
Regards,
Oskars / support@eazyBI.com