Forum Discussion
Slicer usage for two tables differently
Hi PrieleBI
This design does not align with best practices for relationships. Typically, relationships should flow from Dim to Fact tables in a one-to-many structure. However, in your model, the relationships flow from Fact to Dim. Moreover, your sales table will likely be on the many side of relationships, so the flow should be toward it in a one-to-many structure, not the other way around. Additionally, the Shop Plan table is another fact table. To properly link the two fact tables, you'll need to create additional dimension tables, such as Shop and Product, to act as bridges.
Once the model is properly setup, you should be able to create working measures with a simple logic.
Sales Qty all ID = CALCULATE ( SUM ( Sales[SalesQuant] ), REMOVEFILTERS ( Sales[ID] ) ) Plan Execution = DIVIDE ( [Sales Qty all ID], SUM ( ShopPlan[Shop Plan] ) )Please see the attached pbix.
Hi PrieleBI
This design does not align with best practices for relationships. Typically, relationships should flow from Dim to Fact tables in a one-to-many structure. However, in your model, the relationships flow from Fact to Dim. Moreover, your sales table will likely be on the many side of relationships, so the flow should be toward it in a one-to-many structure, not the other way around. Additionally, the Shop Plan table is another fact table. To properly link the two fact tables, you'll need to create additional dimension tables, such as Shop and Product, to act as bridges.
Once the model is properly setup, you should be able to create working measures with a simple logic.
Sales Qty all ID =
CALCULATE ( SUM ( Sales[SalesQuant] ), REMOVEFILTERS ( Sales[ID] ) )
Plan Execution =
DIVIDE ( [Sales Qty all ID], SUM ( ShopPlan[Shop Plan] ) )
Please see the attached pbix.
Thanks danextian ,
One thing is missing till 100 proc. solution, could you helo with it.
Is it possible, that second table would show only Shop X ? (because the selected ID is from Shop X, so only this Shop is needed in table data).
Logic: User choose ID -> Accoding to selection :
>> Table 1 shows detailed ID information
>> Tabel 2 shows the Shop information ( exactly that shop, where ID is from) and the shop data is from the same week as ID week.