In Power BI, calculating averages for measures can be a bit tricky, especially when dealing with the three types of measures which are the additive, semi-additive, and non-additive measures.

In this article, I will explore some helpful tips and tricks for calculating averages for additive, semi-additive, and non-additive measures in Power BI.

Read to find out.

**Table of Contents**show

## Understand the Difference Between Additive, Semi-additive, and Non-additive Measures

To calculate averages for these measures in Power BI, it is important to understand the difference between additive, semi-additive, and non-additive measures.

Additive measures are those that you can sum across all dimensions in a dataset. Examples include sales, revenue, profit, etc.

Semi-additive measures are measures you can sum across some dimensions but not all. Examples include inventory levels, account balances, customer count, etc.

Non-additive measures, both the other hand, are measures you cannot sum at all. Examples include averages, ratios, percentages, etc.

## Use the AVERAGE Function for Additive Measures

For additive measures, calculating the average is straightforward. You can simply use the

function to calculate the average of the measure across all dimensions. **AVERAGE **

For example, if you want to calculate the average sales per month, you will use the

function on the sales measure and group it by the month dimension. This will give you the average sales for each month in the dataset.**AVERAGE **

## Use the AVERAGEX Function for Semi-additive Measures

In semi-additive measures, such as inventory levels or bank balances, you cannot simply calculate an average across all dimensions like additive measures. Instead, you will use the

function.**AVERAGEX **

The

function lets you calculate the average of a measure for each dimension, and then average those averages to get the overall average. **AVERAGEX **

For example, if you want to calculate the average inventory level per month, you will use the

function on the inventory measure and group it by both the month and product dimensions. **AVERAGEX **

This will give you the average inventory level for each product in each month, which you can then average to get the overall average inventory level.

## Use the DIVIDE Function for Non-additive Measures

Non-additive measures, such as ratios or percentages, cannot be averaged at all. Instead, you need to use the

function. **DIVIDE **

This function allows you to divide one measure by another measure, and then aggregate the result using a different function, such as

or **SUM **

.**AVERAGE**

For example, if you want to calculate the average profit margin for each product category, you will use the

function to divide the total profit by the total revenue for each category, and then average those ratios to get the overall average profit margin.**DIVIDE **

## Consider Using a Custom Calculation for More Complex Scenarios

While the built-in aggregation functions in Power BI can handle many common scenarios, there may be times when you need to create a custom calculation to get the results you need.

For example, if you have a measure that you needs to be averaged over a specific time period, you can create a custom calculation that takes into account the number of days in that period.

This can be especially useful for non-additive measures that cannot be averaged using the built-in functions.

To create a custom calculation, you can use DAX formulas to define the calculation logic and then use that formula as a measure in your report.

## FAQs

### Why is it important to understand the type of measure when calculating averages?

It is important to understand the type of measure because the calculation method may differ depending on the type of measure. Failure to understand the type of measure can lead to inaccurate calculations and incorrect insights.

### What other software can help to calculate the average of measures?

Other than Power BI, there are other business intelligence tools and software with built-in functions that can help to calculate average measures such as Tableau, Google Data Studio, etc.

## Conclusion

Typically, measures are numerical values that helps to analyze and evaluate business performance in different areas.

By following these steps otlined in this article, you can easily calculate the average of the three measures: additive, semi-additive, and non-additive.

I hope you enjoyed reading this article. You can also read how to calculate percentage change in Power BI.

Thanks for reading!