Dimension Mapping

Hi all, 

 

I have some data with various dimensions - one of which includes 'Colours'. I've also got a matrix between Colours and Cities separately (e.g. in the attached) which allocates Colours to Cities on a percentage basis. 

 

What I need to do is convert my data using the mapping to go from Colours to Cities. I'd normally be able to do this just by adding Cities as a dimension, multiplying the data by the matrix and then stripping out Colours. Unfortunately I don't have the space to have both Colours, Cities all the other dimensions. 

 

Is there a way to get this allocation done without having all the dimensions in one line item?

 

Hope that makes sense. 

 

Thanks!

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Answers

  • @sd12901 The strategy to reduce sparsity in Anaplan is to create one list(dimension) as a result of the "valid combinations" of the dimensions. 

     

    From your example, it seems that the Cities and Colours are fully "dense" combinations meaning that every City has associated a percentage to every colour. Not sure if this is your real case.

    However, if this is the case, then you will not have a reduced space by combining in a list the Cities + Colours.

     

    Maybe you can explore the possiblity to create a list from the combinations of the Colour + other "various dimensions" in order to have in that combined list only the combinations with data and create a new module using that combined list adding the Cities. 

     

    Hope it helps

    Alex

     

     

  • Hi Alex, 

     

    Thanks for your response!

     

    Unfortunately, all of the dimensions have 'fully dense' combinations so no workaround would be able to save space in this instance. We'd also need to look at all dimensions quite dynamically and I fear that having combined lists would hamper that. 

     

    I would just need cities instead of colours as the dimension but just from using that mapping to convert all the numbers. Not sure if you can think of a formula or something similar that could help?

     

    Many thanks