Controlling and resolving the issues of ambiguous relationships in Power BI is very important for clean and consistent report generation. The cause for the occurrence of these ambiguous relationships is usually where there are several paths between tables, making it hard for Power BI to figure out the appropriate path for use in calculations. This creates interesting and dangerous results and or errors, especially in measures and visuals. Here is a handcrafted solution on how to deal with the problem:
Recognize Ambiguous Relationships: The first step is to look for possible circular references or multiple relationship paths between tables in the data model. This can be achieved with the help of the Relationship view in Power BI, where the user can examine the arrangement of various tables. Such confusion occurs mostly in cases where there are several one-to-many cardinal relationships between two tables or when two tables connect through so many junction tables, resulting in multiple pathways for Power BI to track.
Use “Inactive” Relationships Where Necessary: Power BI provides an option to set some relationships as “inactive.” This means that if a secondary relationship is made inactive, it is possible to indicate the relationship that the Power BI will pull by default on the primary. However, when you want to use these inactive relationships in your measures, it is possible to use them measure by measure while activating them through the USERELATIONSHIP function in DAX. This function gives control to the user on which relationship will be active for a specific
calculation, thereby reducing the level of ambiguity.
Create and Use Bridge Tables: In case of ambiguity remaining, there is a possibility of revising the model with the usage of bridge tables, which are simpler methods of joining…Bridge tables are normally designed to contain distinct values for every key. They can play the role of a central point connecting various relations in the table, hence avoiding unnecessary connections. This direction contributes to creating what is known as a “star schema,” which is one of the ways of modeling data in Power BI, and it reduces complexity and clears ambiguity provided in relations.
As such, the concern about avoiding ambiguous relationships becomes less pressing, and a better and neater Power Bi data model can be achieved.
