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DanH1995's avatar
DanH1995
Frequent Visitor
3 years ago

Forecasting two tables & multiple date fields with one slicer

Hello,

 

I am looking for some guidance as to whether what I want to achieve is possible or not. I have two matrices in my report, both of which categorise each item in the table as to which support period the item is in based on dates using a conditional column, so each item is either in Normal Support, Extended Support, Extended Limited Support or beyond all of those periods in which case it is deemed End of Life. For this reason there are a total of 3 date columns in each table, so 6 in total. Note, these tables are linked via a 1:N relationship.

 

As seen in the image below, I have managed to get the overall counts displayed visually into a matrix for both of my tables which is working how I want it to. However, as a step further, I would like to introduce a forward forecasting element to this so that the user can interact with a slicer and change the quarter & year to a future date and then at the same time the data in the matrices updates so that the user can start to see how the support periods will evolve overtime depending on the date chosen.

 

 

I have tried to create this myself but to not avail so I am looking for some expert help to determine if a) what I want to achieve is actually possible, and b) if it is possible, how can I implement it?

 

Thanks very much in advance,

 

Dan

5 Replies

    • DanH1995's avatar
      DanH1995
      Frequent Visitor

      Hi Anonymous , sure, please follow the link below. I have created a sample report and included two source files.

       

      Power BI Sample File 

       

      Thanks,

       

      Dan

      • Anonymous's avatar
        Anonymous
        Not applicable

        HI DanH1995,

        I can't view the sample data, to required to sign in account for the following operations.

        Can you please fix that link or create some dummy data and paste it here in table format in your threads? Then we can copy and test locally.

        Notice: please remove sensitive data before sharing.

        Regards,

        Xiaoxin Sheng