Same slicer on two tables with different structures?

[naledi_h]

I am new to Power BI. I have two tables with the same information but in different structures. There might be better ways to set this up but this is the way it is at the moment. I need to use a single slicer to filter both of these tables at the same time. For instance on age > age range. The two tables currently have no relationship. I have seven different demographic categories, with around 5 response options in each. 

For table 1, the age filter will just filter out one of the values for that respondent but leave other values for that respondent in the view. The filter works at the demographic response level. 

For table 2, the age filter will filter out the whole respondent. The filter works at the respondent level. 

What is the best approach to doing this? 

[v-zhangti]

Hi, @naledi_h 

Can you provide a simple PBIX file for testing? What do you expect the output to look like, preferably with pictures. Looking forward to your response.

Best Regards,

Community Support Team _Charlotte

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[naledi_h]

Hi @lbendlin , thanks for your response. The problem is how to connect the two, since it's not just the age filter. It's several columns in one table that correspond to just one column in the other.

I believe a solution like this one might work, but not sure how to do this in Power BI https://naledi.co.uk/blog/next-level-lod-filtering

[lbendlin]

Same approach. This is called normalization. Extract dimension columns into their own tables.

[lbendlin]

The best approach is to treat both tables as independent fact tables.  Create a dimension table that distinctly combines the common field (in your case the age filter)* and then control both your fact tables from that dimension table.

* preferably in Power Query, but can also be done as a calculated table in DAX