Measure if value exists in connection with unique ID

[CauseAndEffect]

Hello there!

For context, we have a service department that sends work orders between each other, until now we have measured their volume based on who opens and who closes the work order, but we realized that sometimes, work orders are sent between departments and that we want to measure as "processed by".

We have a raw data table that gives us the following data:

In below example, with our past count only group A & B recieved stats for it.

We want to count to enable group C to get 1 processed for this record.

Thankful for any information that assists.

Bonus question: Can anyone point me to resources that can help in creating a timeline for a case, for below example that would be:

A->C->B with timestamps and duration on each group.

Unique ID	Open Group	Closed Group	Resolved Group	Current Assignment	History Assignment	History Previous Assignment	History Post Assignment	History Start Time	History End Time
884934	A	B	B	B	A		C	13 dec 2016 13:49:59	13 dec 2016 14:09:09
884934	A	B	B	B	A	C	B	13 dec 2016 15:57:44	13 dec 2016 15:58:18
884934	A	B	B	B	A	B	B	14 dec 2016 09:02:44	14 dec 2016 09:03:12

[Anonymous]

Hi @CauseAndEffect ,

If you still have the issue, then this might be a direction for a solution. 

I loosely translated your data model to the following: 

A TicketStats table was created using: 

TicketStats = filter(
distinct(
 Union( 
 SUMMARIZE ( 'Tickets', Tickets[ID], Tickets[Open] ) ,
 SUMMARIZE ( 'Tickets', Tickets[ID], Tickets[Step2] ) ,  
 SUMMARIZE ( 'Tickets', Tickets[ID], Tickets[Step3] ) ,
 SUMMARIZE ( 'Tickets', Tickets[ID], Tickets[Closed] )
)
), 
not ( [Open] ="") 
)

 The column name is [Open], because that is the column used in the first summarize. 

Hope this helps,

Jan