Power BI data modeling is about more than just connecting tables – the type of relationships you choose significantly affects the accuracy of your measures. Recently, a colleague believed that using a bidirectional many-to-many relationship was sufficient for a project analyzing course completion rates. At first glance, it seemed to make sense: it was quick, easy to implement, and allowed for flexible filter flow between tables. But once we started building measures like Completion Rate, we noticed unexpected results. The numbers seemed inflated, and the measures didn’t align with actual completion data.
This video breaks down why a bidirectional many-to-many relationship can cause issues in Power BI and how implementing a bridge table instead yields more exact metrics. Let’s explore these differences using Completion Rate as our example and see why the choice of relationship affects data accuracy.
