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Average calculation _EazyBi

Smita Kalunge June 27, 2023

How to find the monthly average between 2 dates  in eazyBi i.e. issue created and issue last updated date?
The status is “closed”, “completed”, & “rejected”.

I need to calculate the days taken to close the issues. Then (sum of total days taken ) divided by the number of issues. 

so finally I need to show the monthly average in the dashboard.

2 answers

2 accepted

0 votes
Answer accepted
Ilze Mezite June 28, 2023

Hi, @Smita Kalunge 

Thank you for your question.

By default, Jira stores just the issue resolution date (resolved issues are counted in the Issues resolved measure) but not the final issue closing date. But frequently, it is important to analyze closed issues and not just resolved issues as you mentioned ("closed", "completed", & "rejected"). Consider defining "Closed statuses" in the Import options under "Statuses and history". And use that with the Average closing days.

Please read more on our documentation page: https://docs.eazybi.com/eazybi/data-import/data-from-jira/issues-closed-measure

Kindly,
Ilze
support@eazybi.com

Smita Kalunge June 28, 2023

Hi  @Ilze Mezite

Thanks a lot for the quick response.

I got the issues those are "closed", "completed", & "rejected" from status dimension.

Also, what is the difference between the measures "Average closing days"  and "Average Resolution days"?

What should I use to get an average between created date and last updated dates please?

 

Thanks,

Smita Kalunge

Ilze Mezite July 4, 2023

Hi, @Smita Kalunge 

 

Here are the differences between "Average closing days"  and "Average Resolution days" measures:

  • "Average closing days" calculates the duration between created date and the last status updated date of closed issues,
  • "Average Resolution days" calculates the duration between created date and the resolution date of resolved issues.

Kindly,

Ilze

0 votes
Answer accepted
Fabian Lim
Community Champion
June 27, 2023

tagging @eazyBI Support 

Ilze Mezite June 28, 2023

Thank you @Fabian Lim, for tagging us. 

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