There are a few key areas, which we call core and basic, which will guide you in determining the reason why your visualizations are not right when addressing problems in data model relationships within Power BI. To simplify it:
1. Assess The Types of Relationships Exist
Relationships in Power BI can either be one-to-one, one-to-many, or many-to-many. The type of relationship that has been modeled in the data model in the case of the wrong one (in the example, many to one or even many to many) may result in odd totals or wrong figures being presented in the visuals.
Go to Model View and look at the lines between tables. Presume that the key fields that uniquely identify a row are placed correctly (the field that currently has the sales product would contain all goods sold). For example, in a sales report, a one-to-many relationship should exist between your Sales table (many sides) and Product table (one side).
2. Relationships: Active and Inactive Ones
It's important to note that while Power BI supports many-to-many relationships, only one relationship can be active at a time. If your visuals are not displaying the correct results, it's crucial to verify whether the appropriate relationship is active.
Model view—relationships lines. A solid line indicates an active relationship, while a dotted line indicates an inactive relationship. It may also occur that the wrong relationship is active, and you are required to deactivate it and activate the correct one, or you can use DAX functions such as USERELATIONSHIP in your measure to indicate that the inactive relationship should be used.
3. The Path Of The Relationship
Understanding the direction of relationships in Power BI is key. Relationships can be uni-directional or bi-directional. If a relationship is one-way, filters may not work as expected. For instance, if a filter on the Product table doesn't affect the visual for the Sales measure, it may be time to change the relationship to a bi-directional one.
In the model view, right-click the relationship, select Properties, and check whether the data flows properly when you change the direction.
4. Mismatches in Cardinality
At times, data issues can result from the excessive presence or absence of data items in the key columns (for example, a particular product code occurs several times within the table instead of once as it should). When using visuals, if you come across wrong totals or duplicates, you are likely to have a problem with cardinality.
Examine the relevant columns that contain data supporting the relationship. Clean up the relationship-relevant data for any duplicates or missing values before populating the relationships again.
5. Filters and Slicers Testing
If your relationships are in order but the visuals are still inaccurate, this helps resolve the problem: non-content controls and content controls. Use filter and slicer options separately and in different combinations.
Notice how the visual changes. If some filters are not performing as expected, this may point to a filtering or relationship issue.
The above steps normally help in analyzing the problem and modifying the data model to produce proper visuals.
