The Definitive Guide to the Power BI Measure Field

Published:26 September 2022 - 8 min. read

Levis Masonde Image

Levis Masonde

Read more tutorials by Levis Masonde!

Block over 3 billion compromised passwords & strengthen your Active Directory password policy. Try Specops Password Policy for free!

Power BI is a formidable application due to its ability to visualize data and make complex relational table calculations. And if you need to handle aggregated data, the Power BI measure fields feature is all you need!

In this tutorial, you will learn how to add measure fields to your data to quickly aggregate and analyze data without going through complex tasks.

Stay tuned! Visualize, and dig through your data with Power BI measure fields!

Prerequisites

This tutorial will be a hands-on demonstration. If you’d like to follow along, be sure you have the following:

Calculating Columns Using Data Analysis Expression (DAX)

When creating a data model, you can add to your tables by creating new columns using existing ones. A new column uses DAX to make row-by-row calculations of the columns involved. DAX is a formula expression language used in Analysis Services, Power BI, and Power Pivot in Excel.

DAX allows you to perform advanced calculations using its functions, operators, and value, which is crucial in analyzing data.

To calculate data between columns in Power BI:

1. Double-click on the Contoso Sales sample data you downloaded to open it on Power BI.

2. Click on the Data icon (left toolbar) to access the data tab, which loads the data from the imported tables, as you will see in the following step.

Accessing data from the imported tables
Accessing data from the imported tables

3. Next, select the Sales tables under the Fields pane (right-most) to load the table’s data.

Selecting a field to load its data
Selecting a field to load its data

4. Now, click New column from the ribbon toolbar to create a new column. By default, a newly-created column is called Column, as shown below.

Creating a new column
Creating a new column

5. Replace the content of the DAX formula bar with the following formula.

This formula replaces the new column’s name from Column to TotalPrice, which returns the products of each UnitPrice and SalesQuantity column.

TotalPrice = [UnitPrice] * [SalesQuantity]

Click the check icon next to the DAX formula bar to apply the formula.

Changing column name and formula
Changing column name and formula

Like in the screenshot below, the new column (TotalPrice) appears as the last column.

Verifying the newly created column
Verifying the newly created column

6. Change the column’s format as you desire by selecting the column header and playing with different options under the Column tools ribbon tab.

Checking the data format of your column
Checking the data format of your column

7. Finally, create another column, populate the following formula to the DAX formula bar, and apply the formula.

This formula calculates and returns the profit of every sale (Sales[TotalPrice] – Sales[TotalCost]).

Profit = Sales[TotalPrice] - Sales[TotalCost]
Creating another column
Creating another column

Below, you can see the calculated result of profits under the Profit column.

Verifying the data in the Profit column
Verifying the data in the Profit column

Calculating Data with Power BI Measure Fields

You’ve seen that columns can help find a row with the most profit or any row-level query. But to answer more complex questions. Like, which store gained the most profit? Or which salesperson made the most profit? You will need a measure, and creating Power BI measure fields will do the trick.

There are three types of measures in Power BI, which are automatic measures, quick measures, and manual measures. But for a start, you will dive into creating manual measures first.

Creating Manual Measures

Creating manual measures can help nurture your DAX skills if you know the basics. But if you’re unsure how DAX works, start using automatic and quick measures in the following sections. That way, you can learn the DAX language practically without writing any DAX formula.

1. Click on New Measure and use DAX to create a new measure.

Creating a new measure
Creating a new measure

2. Next, apply the below formula to aggregate the profits data.

Profit_Measure = SUM(Sales[Profit])
power bi measure : Calculating profit measure
power bi measure : Calculating profit measure

3. After adding your measure, click the Report icon (left toolbar) to access the Report tab, where you can build visuals with your data.

Accessing the Report tab
Accessing the Report tab

4. Now, click the Matrix visual type icon under the Visualizations pane to add a visual to the dashboard, as shown below.

Inserting a Matrix visual
Inserting a Matrix visual

5. Add data to the Matrix visual with the following:

  • Expand the fields (Tables) under the Fields pane.
  • Drag and drop the columns from the Fields pane to the Rows, Columns, and Values dropdown inside the Visualizations pane.
Populating the Matrix visualization pane with data
Populating the Matrix visualization pane with data

After adding data to the Matrix, boom! You now see all the profits made by every store per month.

Viewing profits from the Matrix visual
Viewing profits from the Matrix visual

6. Finally, click on the Total column header to sort the data by the most profitable store in descending order.

Below, you can see that the Contoso Catalog Store is the most profitable.

Sorting data by profit in descending order
Sorting data by profit in descending order

Using Automatic Measures

Power BI creates automatic measures when your column’s data type is a Number. The default automatic measure is SUM. As a result, when you add a numeric column to a visual, Power BI automatically adds a “total” column.

This behavior is helpful when you want to make straightforward measures, but it also affects columns you do not want to be measured or summarized.

You can identify if a table has a measure by checking if there is a sigma symbol next to it, as shown below.

Spotting automatic measures
Spotting automatic measures

To see how automatic measures work:

1. Add a column you do not want to be summarized to your visual, in this case, SalesAmount.

Adding
Adding

2. Next, click on the arrow-down icon next to the column you added, and choose a different measure for the column. But for this example, select Average.

Choosing a different measure for a numeric column
Choosing a different measure for a numeric column

3. Lastly, look at the last column on your visual and see the change of measure.

Verifying change of measure
Verifying change of measure

Creating Quick Measures

A quick measure can be helpful when you are getting started with DAX. This measure lets you create calculations between your tables and show you the DAX expression on the calculation you picked afterward. All these without a need for DAX knowledge.

Perhaps you aim to get a total price in a column but are unsure how to write an equivalent DAX expression. If so, creating a quick measure will get the job done.

1. Click on the field/table to which you want to add the measure from the Fields pane and click Quick measure, as shown below. A pop-up window appears where you can choose which calculation to use for the quick measure (step two).

Creating a quick measure
Creating a quick measure

2. Next, select Multiplication in the Calculation dropdown field, which displays two fields for the values to multiply.

Selecting a calculation
Selecting a calculation

3. Finally, specify columns with values to multiple as follows:

  • Expand a field/table under the fields section that holds the value you plan to multiply. In this case, the Sales table.
  • Drag and drop the UnitPrice column to the Base value field, and add the SalesQuantity column to the Value to multiple with field.
  • Click OK after specifying the columns to add the new measure.
Populating the quick measure from Fields value
Populating the quick measure from Fields value

Now you have a new measure that you can add to your visual without having to write a DAX formula, as shown below.

Adding measure to visual
Adding measure to visual

Filtering Data by Slicing Visuals

Previously, you have answered which store is most profitable. As much as the answer was informative, it is not satisfying, or you are getting too much information.

What if you aim to analyze who made the most profits in the previous year? This part is where slicers become critical to your dashboard. Slicers help dice your data into smaller pieces, helping you gain more detail and information.

1. Add a slicer visual for the MonthName column with the following:

  • Click outside the currently selected slicer to de-select it.
  • Select the Slicer visual type icon under the Visualizations pane to add a slicer to your dashboard.
  • Tick the box in the MonthName column under the Calendar table to add it to the slicer.
Adding a slicer for the MonthName column
Adding a slicer for the MonthName column

2. Next, add another slicer for the Year column:

  • De-select the currently selected slicer, and click on the Slicer visual type icon again to add a new visual.
  • Tick the box in the Year column to add the column to the slicer.

Thanks to the slicer, you already have more information, where the data runs from 2005 to 2018, as shown below.

data runs from 2005 to 2018
data runs from 2005 to 2018

3. Drag the slider to scroll through the years. As soon as you release the slider, you will see the sales start from 2011 to 2018.

Scrolling through the years of sales
Scrolling through the years of sales

4. Now, filter the data on the Matrix visual with the following:

  • Now, tick the box on December in the MonthName slicer.
  • Put the year 2012 on the fields in the Year slicer.

After these changes, you can check which store made the most profit in December 2012, as shown below: Contoso North America Online Store.

Determining which store made the most profit in December 2012
Determining which store made the most profit in December 2012

5. Ultimately, add another slicer for the DayOfMonth column, and set field values to 5.

Check your Matrix slicer, and you will see which store made the most profit on December 5, 2012, which is still the Contoso North America Online Store.

Using multiple slicers to filter and analyze data better
Using multiple slicers to filter and analyze data better

Conclusion

Measures give you an edge when viewing data, especially those which include numbers. And in this tutorial, you have learned how Power BI lets you aggregate those numbers. At this point, you should be confident enough to answer quantity-driven questions by analyzing your data with Power BI measure fields.

As great as measures can be, you get more specific details from your data, as you did by adding slicer visuals. This information can influence business decisions in a good way and is quick to implement.

With this newfound knowledge, would you like to dive deep into DAX to create manual measures for a more personalized data visualization? Or would you opt for either quick or automatic measures?

Hate ads? Want to support the writer? Get many of our tutorials packaged as an ATA Guidebook.

Explore ATA Guidebooks

Looks like you're offline!