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EazyBI: How to represent Pending Story Points in time domain

I am trying to represent pending story points due in the time domain.

By the moment I can have a table where I have the Storypoints due for each Fix Version (Fix version can have a Start Date and release date)

 

FixVersionStoryPointsDueTable.JPG

I need to represent it in the time domain.

 

Exporting and using excel dinamic graph from columns Version release date and Story Points due, I obtain a graph like the following.

 

 

ExcelDinamicTableSource.JPGDinamicGraph.JPG 

How can I obtain a similar graph in EazyBI (without the need of exporting data to excel)?

 

2 answers

Hi Ricard,

To repeat such report in eazyBI, you can add Time dimension on rows and select the level in which you wish to see the result, e.g., Month.

In Measures add new calculated measure with following formula

Sum(
Filter([Fix Version].[Version].Members,
DateInPeriod(
[Fix Version].CurrentHierarchyMember.get('Release date'),
[Time].CurrentHierarchyMember)
), ([Measures].[Story Points due],
[Time].CurrentHierarchy.DefaultMember)
)

This finds all Fix versions that have release date in the selected time period and sums the Story points due for those versions. You can see this as bar chart
Screen Shot 2018-02-06 at 11.17.59.png

 

While thinking about your requirement, I thought an interesting way of seeing this report might be scattered chart. To do this, you would use the Version release date and Story points due as well as Issues due.

Screen Shot 2018-02-06 at 11.19.34.png

Following is how the above table would look in scatter chart - the result is different than bars, but still might be an interesting chart with issues due and bubbles with story points due

Screen Shot 2018-02-06 at 11.20.33.png

 

Let me know if there is anything else I can assist you with!

Kind regards,
Lauma / support@eazybi.com

Thank you Lauma

 

I was looking for a solution for that for a long time and your solution works perfectly.

It gives me the possibility to design many reports mixing past and future project data.

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