Guide to Data Types in Google Data Studio

The data type of a data source field determines the kind of data to expect (in the connected data set) when processing the field. 

For example, when the data type of a field is ‘Number’, it tells Data Studio to expect a number when processing the field:

When the data type of a field is ‘Currency (US – Dollars) ’, it tells Data Studio to expect currency data in US dollars when processing the field:

Similarly, when the data type of a field is ‘Text’, it tells Data Studio to expect text data when processing the field:

The data type determines which operations are allowed and not allowed on a data source field.


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For example, you can’t apply an arithmetic function to a ‘Text’ field or use a ‘Number’ field as the date range dimension in a report. If you want to change the data type of a field then just click on the drop-down menu next to a data type.

Note: Changing the field type can have a considerable impact on how you see your data in reports.

Google Data Studio supports the following data types:

  • Numeric
  • Text
  • Date and Time
  • Boolean
  • Geo
  • Currency
  • URL

Numeric data types

There are three numeric data types in Google Data Studio:

  1. Number – select this data type if you want Data Studio to expect a number (includes floating-point number) when processing the field in the specified data set.
  2. Percent – select this data type if you want Data Studio to expect percentage data when processing the field in the specified data set.
  3. Duration – select this data type if you want Data Studio to expect time duration in seconds when processing the field in the specified data set. 

For example, consider the following data set:

The field ‘Number of orders’ is of type ‘number’. 

The field ‘Percentage of Sales’ is of type ‘percent’. 

The field ‘Duration’ is of type ‘duration’.

If we connect this data set to our data source schema then when deciding the data source schema (structure) we should:

  • set the data type of the field ‘Number of orders’ to ‘Numbers’.
  • set the data type of the field ‘Percentage of Sales’ to ‘Percent’.
  • set the data type of the field ‘Phone Call Duration’ to ‘Duration’.

To learn more about numeric data types in Google Data Studio read the following two articles:

#1 Google Data Studio Number Formats / Data Types

#2 Doing Basic Maths on Numeric Fields via Calculated Fields

Text data type

Select the ‘Text’ data type if you want Data Studio to expect text when processing a field in the specified data set. A text data type can include any combination of letters, numbers, special symbols (like [, }, @….) and other characters.

Consider the following data set:

Here all the values of the field ‘Customers Name’ are of type ‘Text’. So when defining the data source schema, we would set the data type of the field ‘Customers Name’ to ‘Text’:

To learn more about the text data types, read this article: How to Work with ‘Text’ Data Type in Google Data Studio

Date and time data types

As you can see from the screenshot, Google Data Studio supports several different types of date and time.

The data types for ‘date’ fields can be divided into the following two categories:

  • Absolute Dates
  • Relative Dates

The data types for ‘time’ fields can be divided into the following two categories:

  • Absolute time 
  • Relative time

Absolute date

An absolute date refers to a specific date that you can point to on a calendar. Following are examples of absolute dates in the context of Google Data Studio:

  • 2019
  • Q1 2019
  • Nov 2019
  • Nov 10, 2019

Absolute date types

These are the data types meant for absolute dates. Following are absolute date types:

You should select that data type for your absolute date which matches the date type in your data set. 

Absolute time

An absolute time refers to a specific time that you can point to on a clock. 

Following are examples of absolute time in the context of Google Data Studio:

  • Sept 10, 2019, 10 PM
  • Sept 10, 2019, 10:30 PM

Data types for absolute time

These are the data types meant for absolute times. Following are data types for absolute time:

You should select that data type for your absolute time that matches the time type in your data set. 

Relative date

The relative date is the date that does not refer to a specific date.

Following are examples of relative dates in the context of Google Data Studio:

  • Q1, Q2, Q3, Q4 – here we don’t know, we are referring to the quarter of which year. 
  • Jan, Feb, March, April… – here we don’t know, we are referring to the month of which year. 
  • Mon, Tue, Wed, Thu… – here we don’t know, we are referring to the day of which week or month or year. 

Relative date types

These are the data types meant for relative dates. Following are relative date types:

You should select that data type for your relative date which matches the date type in your data set. 

Relative time

Relative time is the time which does not refer to a specific point in time. 

Following are examples of relative time in the context of Google Data Studio:

  • 1 am, 3 am, 7 pm, etc – here we don’t know which day, month, or year the time occurred. 

Data types for relative time

These are the data types meant for relative times. Following are data types for relative time:

You should select that data type for your relative time which matches the time type in your data set. 

To learn more about the date and time data types in Data Studio read this article: Tutorial on Date and Time Data Types in Google Data Studio

Boolean data type

If a data field in your data set can have only one of the two possible values: true or false then you should use the Boolean data type while setting up your data source schema.

To learn more about working with the boolean data type, read this article: How to work with Boolean data type in Google Data Studio

Geo data types

Use ‘Geo’ data type if you want Data Studio to expect a geographic region (like a city, region, country, continent) when processing a field in the specified data set.

Following are the various Geo data types available in Google Data Studio:

To learn more about the geo data types, read this article: Geo Data – Country, Region, Latitude, Longitude in Google Data Studio

URL Data Type

Use the ‘URL’ data type if you want Data Studio to expect a URL when processing a field in the specified data set.

Currency Data Type

 Use the ‘Currency’ data type if you want Data Studio to expect a currency when processing a field in the specified data set.

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