Combine two identical columns from two tables within one slicer

[flowgistics]

Hi there,

I'm struggling with the following situation:

I have a ProductionData-table including production data from five machines with different names, which produce each month x-tons of goods. The [ProductionMonth] column from this table has a n:1 relation with my Date-table.

Additionally I have a ShippingData-table where the shipping amount is reported per month and per machine. The [ShippingMonth] has as well a n:1 relation with my Date-table.

So in my report I can show shipping amounts for each month, but I can not use my machine-slicer in order to slice down the monthly production amount to every machine.

Any thoughts how can I do that?? Thanks a lot in advance!

[Greg_Deckler]

@flowgistics Create a Machines table using something like:

Machines = DISTINCT('Table'[Machine])

Relate this to both of your fact tables and use this table as your slicer.

[flowgistics]

@Greg_Decklerthanks for your quick answer.

I already tried that, but I can't make the second relation active..? 

[flowgistics]

Alright I had to enable Single-Filter-Direction between DateTable and ShippingTable. Now it works! 🙂

Can anyone please explain which difference it makes, if I leave a single or both-filter-direction between DateTable and ProductionTable?

[V-lianl-msft · Accepted solution]

Bidirectional cross-filtering enables them to apply filters on both sides of a table relationship. 

They can negatively impact on model query performance, and possibly deliver confusing experiences for your report users.

There can only be one active filter propagation path between two model tables. 

When you use multiple both-filter-direction, it will cause a table to be affected by several filtering path at the same time, which is the reason why you cannot create an active relationship.