Question

Your dataset contains multiple fact tables (Sales, Inventory, and Finance). Should you create relationships between them directly, or use a bridge table? Why?
You have multiple fact tables containing different types of business data, such as sales, inventory, and finance. To ensure accurate analysis and avoid relationship conflicts, should you create direct relationships between these fact tables, or use a bridge table? What factors should be considered when determining the best data modeling approach in Power BI?

Answer 1

In the handling of multiple fact tables (Sales, Inventory, and Finance) in Power BI, there should not be direct relationships made between fact tables. A bridge (or conformed dimension) table is a preferable mechanism to maintain data integrity and improve performance.

Why Use a Bridge Table?

Avoids Many-to-Many Relationships: Relating fact tables directly forms many-to-many relationships that lead to ambiguous queries and incorrect aggregations. A bridge would thus assist in standardizing those relationships using shared dimensions (e.g., Date, Product, or Customer).

Better Performance and Flexibility: A bridge table improves performance by reducing redundancy and rendering shared dimensions effectively for filtering and aggregation.

Ensures Data Consistency: It helps provide a single version of key business entities so that values are not mismatched while comparing metrics across different fact tables.

When to Use Direct Relationships?

Direct relationships between fact tables are appropriate in situations where there are highly related metrics, such as a sales and returns fact table, and when there is a one-to-one or one-to-many relationship between them. Most of the time, though, it is the best-practice scenario to go with an ideally structured star schema with a bridge table.