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RRanks
Frequent Visitor

Filtering Slicer - Base on another tables Boolean value

Hi,

 

I have 3 imported tables and I am trying to show, and then filter the data joined in a table visual with a slicer.

Each table value has unique ID to make relationships easy.

 

Tables: 

- Building has [SiteID]
- Floors has [FloorID]+[SiteID]
- Spaces has [FloorID]+[SiteID]+[LocationID]

 

1 Building -> * Many Floors

1 Floor -> *Many Spaces

I have the relationships sorted and working fine. In the table visual, I can show the Spaces, thier Floor data and Building data, No problem.

 

RRanks_1-1717473146906.png

However...

I want to have a slicer or something so that you can select the Building as see what Active Spaces are in it as there is a lot of extra Building data that either has no active spaces, or no spaces at all. How do I go about either filtering the slicer so it only shows buildings with a Space in it that is Active.

 

Or.. would this be better done in Power Query first somehow?

 

Basically I want to now show buildings where it isn't a row in the Spaces table that has a: LocationActive = True

 

 

 

1 ACCEPTED SOLUTION
UlrikH
Regular Visitor

You have two options here: 
Switch the crossfilters to bidirectional, so that the building-table filters the floors and the floors filter the spaces. But be aware of all negative aspects of bidirectional filtering.
The other option ist to denormalize the dimensional tables to one in Power Query, so that you have all dimensional data in one place.

View solution in original post

2 REPLIES 2
RRanks
Frequent Visitor

I am a DAX complete newbie but I like use real world examples to learn 😛 Is it possible to have an inactive relationship and write some sort of DAX query to check it?
OR.. perhaps add a custom column in Transform Data?

UlrikH
Regular Visitor

You have two options here: 
Switch the crossfilters to bidirectional, so that the building-table filters the floors and the floors filter the spaces. But be aware of all negative aspects of bidirectional filtering.
The other option ist to denormalize the dimensional tables to one in Power Query, so that you have all dimensional data in one place.

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