Google Data Studio Dimensions and Metrics: Made Easy

• January 12th, 2022

Google Data Studio Dimensions and Metrics


Google’s free visualization tool Data Studio allows you to import data from several sources. You can generate different types of charts using its drag-and-drop functionality & easy-to-use interface. A data source may have hundreds of fields containing different types of data. Fields such as ‘Country’, ‘City’ etc. contain texts. Fields such as ‘Sales Quantity’ contain numerical values. ‘Sales Amount’ contains currency and ‘Date’ contains dates. Depending on the type of data, they serve different purposes in the report. Based on their functions, fields in Google Data Studio are classified into two types namely, dimensions and reports.

In this blog, you will learn what Google Data Studio Dimensions and Metrics are, how they differ, how they interact with each other, and what properties they possess. You will also learn how you can add fields to a chart, create new fields, edit fields, and create informative reports.

Table of Contents

What is Google Data Studio Dimensions?

Dimensions are also known as unaggregated columns. (And Metrics are known as aggregated columns.). You can categorize your data on Dimensions, such as gender, country, date, age group, medium, device category, etc. They describe the data that you are trying to analyze.

Whenever you add a dimension to a chart in Google Data Studio, the data in the chart gets grouped by that dimension.

What is Google Data Studio Metrics

A Metric is a number. It can be used to measure the dimension in some way. ‘Country’ is a dimension that can be associated with many Metrics such as population, literacy rate, number of internet users, gender ratio, per capita income, etc. ‘Date’ is a dimension that can be associated with Metrics like the number of visits to the website, number of new subscribers, view time, bounce rate, etc.  

Metrics vs. Dimensions in Google Data Studio

Within Google Data Studio, you can easily differentiate between Dimensions and Metrics. In Google Data Studio, dimensions are always shown in green while metrics are depicted using the color blue. Both Dimensions and Metrics have types that describe how they can be leveraged to improve efficiency. A Metric in Google Data Studio usually consists of numbers, amount of currencies, percentages, or durations. A Dimension, on the other hand, could be a boolean choice, text, geographic coordinates, time, date, or even an URL.

Google Data Studio Dimensions and Metrics: Differences 1

Apart from these Google Data Studio Dimensions and Metrics differences, metrics can further be dissected on the basis of how you collate them. You can either leverage the “sum” as the yardstick, a count, an average, a count distinct, or the maximum/minimum values for the same. Here’s a table of Google Data Studio Dimensions and Metrics to help drive the point home:

Differentiating FactorMetricsDimensions
TypePercentage, Duration, Amount of Currency, NumbersBoolean Choice, Text, Geographic Coordinates, URL, Date/Time
Aggregation-based DissectionUsers can break down metrics based on how they are aggregated.Users cannot break down dimensions based on how they are aggregated.

Hevo, A Simpler Alternative to Integrate your Data for Analysis

Hevo Data, a No-code Data Pipeline, helps to transfer data from 100+ sources to your desired data warehouse/ destination and visualize it in a BI tool. Hevo is fully-managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using various tools such as Google Data Studio.

Check out some of the cool features of Hevo:

  • Completely Automated: The Hevo platform can be set up in just a few minutes and requires minimal maintenance.
  • Real-time Data Transfer: Hevo provides real-time data migration, so you can have analysis-ready data always.
  • 100% Complete & Accurate Data Transfer: Hevo’s robust infrastructure ensures reliable data transfer with zero data loss.
  • Scalable Infrastructure: Hevo has in-built integrations for 100 + sources that can help you scale your data infrastructure as required.
  • 24/7 Live Support: The Hevo team is available round the clock to extend exceptional support to you through chat, email, and support calls.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
  • Live Monitoring: Hevo allows you to monitor the data flow so you can check where your data is at a particular point in time.

You can try Hevo for free by signing up for a 14-day free trial.

How Google Data Studio Dimensions and Metrics Interact with Each Other

To put it simply, Dimensions group data and Metrics aggregate data. Adding the Dimension ‘Country’ to your website data will group the data into separate countries and aggregate the ‘PageViews’. 

If you further add another Dimension called ‘Device Category’, you will reduce the granularity of aggregation on the Metric ‘PageViews’ further, because now you are also grouping by ‘Device Category’. 

If you remove both the Dimensions, ‘Country’ and ‘Device Category’, you will get an ungrouped aggregate ‘PageView’.

Can a Dimension be used as a Metric?

Yes, for a Non-numeric Dimension, Count Distinct aggregation will be applied to that data, when you use the Dimension as a Metric. You cannot aggregate non-numeric data as a sum or an average.

For a Numeric Dimension, the aggregation that was specified in the data source by default will apply. If none was specified, the Sum aggregation will be used to aggregate the data.

In Google Data Studio, the Dimensions and Metrics are shown in green and blue respectively.

Google Data Studio Dimensions and Metrics.

Properties of Google Data Studio Dimensions and Metrics

All the fields have the following properties by default:

  • Name
  • Data type
  • Default Aggregation
  • Description
Properties of Dimension & Metrics
  • Name: It is just the name that appears on the box indicating the Dimension or Metric. Eg: Year, Country, PageViews, etc.
  • Data type: It represents the type of data that is present in that field. The data type can be a text, a number, a date, a country, a city, a currency, an image, a boolean, a hyperlink, a time period, a URL, etc. The data type determines the kind of operations that can be performed on a field. You can edit the data type using the drop-down menu.
  • Description: These are just annotations mentioned next to the field name describing it.
  • Aggregation: When you use any field as a Metric, the default aggregation method in the data source is applied to it.
Carrying out Aggregation operation on data.

The default aggregation can be changed in some cases and not in others. If the aggregation method is fixed and cannot be changed, then it is shown as Auto.

Calculated Fields

You can also create new fields in Google Data Studio to present more relevant information using the data that already exists. For example, if you have the yearly sales data, you can create a new field to measure the monthly average by creating a formula.

To create a calculated field, first, click on the ‘Add dimension’ symbol on the field.

Adding new dimensions to Google Data Studio.

Next, click on the create field option.

Creating a new field in Google Data Studio.

Now, you can create a calculated field by entering the formula using the existing fields. For example, in the below image a new calculated field to measure the monthly average, ‘sales_per_month’ is created by dividing the ‘sales_quantity’ by 12. This is a simple formula, but you can create complex formulas using multiple fields.

Creating fields based on formulas.

Calculated fields can be specific to a chart or the data source. You can also create calculated fields using CASE statements with ‘if/then/else logic.

How to Add Google Data Studio Dimensions and Metrics?

In order to add a Dimension to your chart from the data source, click on the ‘Add a Dimension’ button in the data panel. 

Adding new dimensions to Charts in Google Data Studio.

Next, choose from the options in the drop-down menu.

Choosing fields in Google Data Studio.

The process is similar to adding Metrics as well.

Adding metrics in Google Data Studio.

How to Edit Google Data Studio Dimensions and Metrics?

You can modify the names, aggregations, data types, etc. of a field in Google Data Studio. To edit a field, click on the chart and then click on the data type icon found in the data panel. You can also check the best google data studio templates.

Modifying a field in Google Data Studio.

You can now select the properties you want to modify.

Choosing properties to be modified.

You already know the role of ‘Name’, ‘Aggregation’, and ‘Type’. Let us now take a look at how comparison and running calculations let you edit the data in the rows of the field.

Comparison Metrics

This option lets you compare each row of your data to the total for that field. You can apply a comparator to a field by clicking on the edit button and then selecting the Comparison Metric from the drop-down list.

Comparing metrics with other values.

In the above example, the data in the field ‘Sales’ is represented as the percentage of the total. It can be seen from the image below, that the rows in ‘Sales’ are represented as percentages of the total.

Representing rows as a percentage of Sales.

Here is a list of options that you can apply.

  • Percent of total
  • Difference from total
  • Percent difference from total
  • Percent of max
  • Difference from max
  • Percent difference from max

You can learn more about applying Comparison Metrics for Google Data Studio Dimensions and Metrics here.

Running Calculation

Running calculation shows you the summary statistics for a given set of data, and they keep changing with each new input.

Carrying out calculations in Google Data Studio.

After selecting the ‘Running Sum’, you will see the cumulative values of the rows in the chart.

Cumulative values based on Sales.

Here is a list of options that you can select under this drop-down.

  • Running sum
  • Running min
  • Running max
  • Running count
  • Running average
  • Running delta


In this blog, you covered various properties of Google Data Studio Dimensions and Metrics. You also saw how you can edit fields to modify what you show and create new calculated fields using formulas.

To get the best results it is vital to look at data from multiple sources together. Use Hevo, a fully managed platform, that performs data integration seamlessly. Check it out by signing up for a 14-day free trial today. You can also have a look at our unbeatable pricing that will help you choose the right plan for you.

Share your thoughts on working with Google Data Studio Dimensions and Metrics in the comments below!

Easily visualize your data in Google Data Studio