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
- What is Google Data Studio Metrics
- How Google Data Studio Dimensions and Metrics Interact with Each Other
- Can a Dimension be used as a Metric?
- Properties of Google Data Studio Dimensions and Metrics
- Calculated Fields
- How to Add Google Data Studio Dimensions and Metrics?
- How to Edit Google Data Studio Dimensions and Metrics?
- Metrics vs. Dimensions in Google Data Studio
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.
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:
|Type||Percentage, Duration, Amount of Currency, Numbers||Boolean Choice, Text, Geographic Coordinates, URL, Date/Time|
|Aggregation-based Dissection||Users can break down metrics based on how they are aggregated.||Users cannot break down dimensions based on how they are aggregated.|
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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.
Properties of Google Data Studio Dimensions and Metrics
All the fields have the following properties by default:
- Data type
- Default Aggregation
- 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.
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.
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.
Next, click on the create field option.
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.
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.
Next, choose from the options in the drop-down menu.
The process is similar to adding Metrics as well.
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.
You can now select the properties you want to modify.
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.
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.
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.
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 shows you the summary statistics for a given set of data, and they keep changing with each new input.
After selecting the ‘Running Sum’, you will see the cumulative values of the rows in the chart.
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.
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Share your thoughts on working with Google Data Studio Dimensions and Metrics in the comments below!