last 30 days count with condition

[blackbranded]

I'm searching for a calculation that involves conditional logic, depicting the number of tickets opened in the last 30 days.

Total Open Tickets days = CALCULATE(COUNT('Ticket_1673349003140 (1)'[Status]), 'Ticket_1673349003140 (1)'[Status] = "open"

, 'Ticket_1673349003140 (1)'[Created Time] >= NOW()-30 , 'Ticket_1673349003140 (1)'[Created Time] <= NOW())

[Ashish_Mathur]

Hi,

Assuming the created time column is a Date data type (and not a Date/Time data type), try this approach

1. Create a Calendar Table
2. Create a relationship (Many to One and Single) from the Created time column to the Date column of the Calendar Table
3. Write these measures
   1.  Count = COUNT('Ticket_1673349003140 (1)'[Status])
   2. Count in last 30 days = calculate([count],datesbetween(Calendar[date],today()-30,today()))

Hope this helps.

[v-zhangti · Accepted solution]

Hi, @blackbranded 

You can try the following methods.

Measure:

Total Open Tickets days = 
CALCULATE ( COUNT ( 'Ticket_1673349003140 (1)'[Status] ),
    FILTER ( ALL ( 'Ticket_1673349003140 (1)' ),
        [Status] = "open"
            && [Created Time] >= TODAY () - 30
            && [Created Time] <= TODAY ()
    )
)

Is this the result you expect?

Best Regards,

Community Support Team _Charlotte

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[Mikelytics]

Hi @blackbranded 

Can you please provide sample data?

I think there is a general problem in your logic because typically ticket systems have one line-item per ticket. But requesting on status field would ignore tickets which have been opened duting last 30 days and closed within these days because they do not have status opened. So typically you would go on the creation time to identify an opened ticket.

 
Total Open Tickets days = 
CALCULATE(
   COUNT('Ticket_1673349003140 (1)'[Status]), 
   'Ticket_1673349003140 (1)'[Created Time] >= NOW()-30
)

Or is it different in your case? Can you please check as well as some sample data incl. how your data model looks like? Because depending on your data mpdel looks like its possible that the emasure has to be adjsuted.

Best regards
Michael
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