Hi b-kopik 

order to get this dashboard working correctly, what needs to be done is to transition from a direct many-to-many relationship between your two data tables to a star schema structure with shared dimensions. The current issue exists because Power BI cannot effectively filter the Headcount table using the Campus table when an Employee ID appears in multiple months across both; this is why selecting January shows you the entire headcount instead of just the trainees. To fix this, the approach involves creating a unique Employee table and a dedicated Calendar table that both connect to your existing data. For the Employee table, you can use a DAX calculated table like Employees = DISTINCT(UNION(SELECTCOLUMNS('Headcount', "ID", 'Headcount'[Employee ID]), SELECTCOLUMNS('Campus', "ID", 'Campus'[Employee ID]))) to ensure every ID is represented only once. Similarly, a Calendar table should be generated using Calendar = CALENDARAUTO() so that your Month slicer comes from a single, neutral source.

Once these tables are created, you should connect the Employee ID from the new Employee table to both the Headcount and Campus tables with a one-to-many relationship, and do the same for the Date or Month columns from the Calendar table. When the slicers for Month and Agency are pulled from these new shared dimension tables, they will filter both fact tables simultaneously and accurately. To ensure the Demographics section specifically isolates only those who took training in the selected month, what needs to be done is to create a simple DAX measure such as IsParticipant = IF(ISBLANK(COUNTROWS('Campus')), 0, 1) and add it to the "Filters on this visual" pane for your demographic charts, setting the value to 1. This logic forces the demographic visuals—which pull their descriptive data like Age and Ethnicity from the Headcount table—to only display rows where a corresponding training record exists in the Campus table for that specific month and agency. This structure keeps your Headcount section independent while allowing the Campus and Demographics sections to sync perfectly without double-counting or over-reporting.

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Never create a relationship between fact tables, that goes completely against the star schema which is the best way to model data. Instead create dimension tables which have one-to-many relationships to your fact tables, this is much more efficient and it is much easier to manipulate the filters in the way that you want to.

As a minimum you will want a date dimension and an employee dimension, both linked to both your fact tables. You can create an employee dimension by retrieving a list of unique employee IDs. You can do this in Power Query or DAX, the only thing you need to be mindful of is whether or not it is possible for an employee ID to appear in the training data and not in the headcount data. If it is not possible then you can create an employee dimension with a simple DISTINCT(Headcount[EmployeeID] ). If there might be employees in training who are not in headcount then you could do something like

Employee =
DISTINCT (
    UNION (
        DISTINCT ( Headcount[Employee ID] ),
        DISTINCT ( Training[Employee ID] )
    )
)

Once you have the employee dimension, link it to both headcount and training.

You could also create dimensions for e.g. Agency, Gender, Ethnicity, Course etc, again by using DISTINCT. If you do create these extra dimensions, make sure that you use the dimension in all your visuals and filters.

You can now create a measure to show the number of employees who did training in the chosen month like

Num employees with training =
CALCULATE ( COUNTROWS ( Headcount ), Training )

Because this is counting from Headcount, you can break it down by any of the columns in that table, or by dimensions you have chosen to extract from that table. It works by using the expanded table of Training, so only employees who have rows in the Training table for the given month will be considered.

One thing to bear in mind is that this method needs to have only 1 month chosen in the slicer. If more than one month is chosen then employees will be counted multiple times. You can enable single select on the slicer to ensure that only 1 month can be chosen.

Hi b-kopik , hope you are doing great. May we know if your issue is solved or if you are still experiencing difficulties. Please share the details as it will help the community, especially others with similar issues.

Hi b-kopik , Hope you're doing okay! May we know if it worked for you, or are you still experiencing difficulties? Let us know — your feedback can really help others in the same situation.

Hello,

Can I create one table with one column for months and one for the years? I need a slicer that connects to the different datasets for each month - but then not sure how it will work if I have multiple years worth of data? So say I filter for April 2026 but I also have April 2025?

Hi b-kopik , Hope you're doing fine. Can you confirm if the problem is solved or still persists? Sharing your details will help others in the community.