The ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM.
Get registeredCompete to become Power BI Data Viz World Champion! First round ends August 18th. Get started.
I am trying to create cumulative view of when stories are added to a sprint using a table of data that contains the date the story was added to the sprint. I thought this would be easy, but its proving more of a head scratcher than I thought, and I'd welcome suggestions of where I am going wrong.
The data table I am using is as follows:
issue_id | sprint_id | name | state | start_date | end_date | complete_date | max_sprint_date | story_points | project_key | year_week | squad_sprint | date_added | in_scope | issue_key |
309266 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 17:09 | Yes | CUS-3017 |
428766 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 8 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 15:55 | Yes | CUS-3648 |
418234 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 2 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 09:38 | Yes | CUS-3577 |
428718 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 8 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 08/10/2024 16:07 | Yes | CUS-3646 |
316310 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 17:09 | Yes | CUS-3134 |
428689 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 08/10/2024 09:51 | Yes | CUS-3645 |
428498 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 3 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 17:09 | Yes | CUS-3642 |
429016 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 2 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 30/09/2024 13:14 | Yes | CUS-3652 |
329884 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 02/10/2024 08:56 | Yes | CUS-3259 |
307996 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 08/10/2024 09:55 | Yes | CUS-2994 |
430213 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 5 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 10/10/2024 09:56 | Yes | CUS-3662 |
281224 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 08/10/2024 09:55 | Yes | CUS-2100 |
428492 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 5 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 17:09 | Yes | CUS-3641 |
429493 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 2 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 15:44 | Yes | CUS-3656 |
429256 | 3714 | CS-Sprint 43 | closed | 02/10/2024 11:09 | 15/10/2024 20:00 | 2024-10-15T15:46:40.545Z | 14/10/2024 23:59 | 8 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 02/10/2024 12:11 | Yes | CUS-3655 |
424689 | 3714 | CS-Sprint 43 | future | 02/10/2024 00:00 | 15/10/2024 20:00 | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 15:47 | No | CUS-3617 | |
429500 | 3714 | CS-Sprint 43 | active | 02/10/2024 11:09 | 15/10/2024 20:00 | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 02/10/2024 08:58 | No | CUS-3657 | |
408811 | 3714 | CS-Sprint 43 | active | 02/10/2024 11:09 | 15/10/2024 20:00 | 14/10/2024 23:59 | 5 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 17:09 | No | CUS-3505 | |
428893 | 3714 | CS-Sprint 43 | active | 02/10/2024 11:09 | 15/10/2024 20:00 | 14/10/2024 23:59 | 2 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 01/10/2024 15:47 | No | CUS-3651 | |
428373 | 3714 | CS-Sprint 43 | active | 02/10/2024 11:09 | 15/10/2024 20:00 | 14/10/2024 23:59 | 0 | CUS | 2024_42 | CUS-14/10/2024 23:59:59 | 02/10/2024 09:43 | No | CUS-3636 |
My thoughts were to use the line graph visual, with the date added as the x-axis and then create a measure that counts all stories where the dateadded value is <= to each point on the x-axis. That way, I would get a nice view of the sprint and see as a cumulative view the stories getting added to the sprint.
However, I can't work out the date value of each point on the x-axis in my measure. Essentially, I want to say for each point on the x-axis:
count the number of stories where the date added <= the data point on the x-axis
If at all possible, I would really like to avoid having to create a date table for the x-axis - it feels like pbi should be clever enough to just use the dateadded field.
Thoughts?
Solved! Go to Solution.
Hi @chipchidster ,
I made a sample for you.
Hi @chipchidster ,
I made a sample for you.