Fixing Many-to-Many Relationships in Power BI with Link or Join Tables

The Simple..

Imagine trying to organize a party where every guest is talking to every other guest at the same time. It’s chaotic! Now, imagine this same situation in your database. This is what happens with many-to-many relationships: lots of messy connections, no clarity, and things get confusing fast.

But just like a party can have better flow with a host guiding the conversation, a link table can bring order to your data. Let’s dive into what a many-to-many relationship is, why it’s a problem, and how you can fix it.

Problem Highlights

If you use PowerBI, then you know what following images are –

Solution Highlights:

Before Link Table (Many to Many)

• The relationship between Students and Courses was direct, with many-to-many connections. Power BI had trouble handling this complexity, leading to inaccurate reports.

After Link Table (One to Many)

• By introducing the Enrollments link table, the relationship becomes one-to-many between Students → Enrollments and Courses → Enrollments, solving the issue and making reporting easy.

Here, have you noticed Student_ID and Course_ID are defined as PKs?

This is the beauty of optimized RDBMS. No redundancies, proper relationship, no issues at all.

What is a Many-to-Many Relationship, and why it cause problem in RDBMS?

In a many-to-many (M:N) relationship, one record in Table A can be associated with multiple records in Table B, and vice versa. For example:

• A student can enroll in multiple courses.
• A course can have multiple students enrolled.

This creates an M:N relationship between the students and courses. Here’s what it looks like.

Issues with M: N relationship (i.e Without Link Table)

Issues:

• Data Redundancy: Repeating IDs leads to more rows and inefficient data handling.
• Complex Queries: Managing repeated IDs in both tables complicates SQL queries and Power BI relationships.
• Power BI Ambiguity: Power BI struggles with accurate calculations, often leading to incorrect totals.

The Solution: Using a Link Table (aka Junction Table/ Join Table/ Bridge Table)

To fix this, we create a link table that connects the Student_IDs and Course_IDs. This eliminates the need to repeat IDs in both tables and simplifies the model.

Enrollments Table (Link Table):

After Link Table:

• Students Table: Student_ID Student_Name 1 Alice 2 Bob 3 Charlie
• Courses Table: Course_ID Course_Name 101 Math 102 Science 103 History

Power BI Benefits:

• Clear Relationships: Now, Students and Courses are connected through the Enrollments link table, making it easier for Power BI to understand the relationships.
• Accurate Reporting: Power BI can now correctly calculate metrics like “Total Students per Course” or “Courses per Student” without ambiguity.
• Simplified Data Model: Cleaner relationships reduce query complexity and enhance performance.

Key Takeaways for Power BI:

• Link tables break down many-to-many relationships into one-to-many connections, simplifying data models.
• They improve Power BI performance, allowing for more accurate aggregations and reports.
• Always use a link/junction table when handling many-to-many relationships for cleaner and more efficient data models.

Resources and Codes

Tool I used to develop data model:

https://dbdiagram.io/d

Table Students {
  Student_ID integer [primary key]
  Student_Name varchar
}

Table Courses {
  Course_ID integer [primary key]
  Course_Name varchar
}
Table Enrollments {
    Student_ID varchar
    Course_ID integer
}

Ref: Students.Student_ID < Enrollments.Student_ID // many-to-one
Ref: Courses.Course_ID < Enrollments.Course_ID // many-to-one