Calculating Weighted Average in Power BI

When working with data analytics, calculating an average is one of the most common operations. However, a simple arithmetic average is not always sufficient, particularly when different values contribute differently to the final result.

A weighted average addresses this problem by assigning different levels of importance (weights) to individual values before calculating the final average.

Consider a few practical examples:

• Education: Calculating student results when different subjects carry different credit values.

• Finance: Calculating portfolio returns based on different investment proportions.

• Business Analytics: Evaluating performance indicators with different levels of importance.

• Sales Analytics: Calculating average selling prices based on sales quantities.

Although Power BI provides the AVERAGE() function for calculating arithmetic averages, implementing weighted averages requires additional steps.

In my latest article published on SQLServerCentral, I demonstrate two practical approaches to calculating weighted averages using Power Query in Power BI.

What does the article cover?

1. Weighted Average Using Subject Credits – Combining student marks with a separate subject-credit table, calculating the product of marks and credits, and grouping the results to obtain weighted averages.

2. Weighted Average Using Assessment Components – Calculating final student marks when assessments such as presentations, assignments, and final papers contribute different percentages to the overall result.

3. Power Query Techniques – Using Merge, Custom Columns, Cross Join techniques, and Group By operations to implement the calculations.

The examples demonstrate how these techniques can be applied to real-world analytical requirements without relying on complicated DAX calculations.

Read the full article here:

Calculating Weighted Average in Power BI – SQLServerCentral

I hope this article will be useful for Power BI developers, data analysts, students, and anyone working with weighted calculations in analytical reporting.