Guide to Data Types in Google Data Studio
The data type of a data source schema field determines the kind of data to expect (in the connected data source) 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 also determines which operations are allowed and not allowed on a data source schema field.
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.
Get the ebook on Google Data Studio (50+ Pages)
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 a field in the underlying data source.
#2 Percent – select this data type if you want data studio to expect percentage data when processing a field in the underlying data source.
#3 Duration – select this data type if you want data studio to expect time duration in seconds when processing a field in the underlying data source.
For example, consider the following Google Sheets data source:
Here,
The field ‘Number of orders’ is of type ‘number’.
The field ‘Percentage of Sales’ is of type ‘percent’.
The field ‘Phone Call duration’ is of type ‘duration’.
When we connect this data source to our data source schema then while 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 underlying data source. A text data type can include any combination of letters, numbers, special symbols (like [, }, @….) and other characters.
Consider the following Google Sheets data source:
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:
#1 Absolute dates – It refers to a specific date that you can point to on a calendar.
#2 Relative dates – It refers to a date that you can not point to on a calendar.
The data types for ‘time’ fields can be divided into the following two categories:
#1 Absolute time – It refers to a specific time that is accompanied by an absolute date.
#2 Relative time – It refers to a specific time that is not accompanied by an absolute date.
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 source 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 underlying data source:
Currency Data Type
Use the ‘Currency’ data type if you want Data Studio to expect a currency when processing a field in the underlying data source.
Image data type
Use the ‘Image’ data type if you want data studio to expect the URLs of images when processing a field in the underlying data source:
Note(1): The ‘Image’ data type is used for only those fields which return data of type image. Such fields are called image fields.
Note(2): The image fields are used to display images in the data table of a report.
Image Link data type
The ‘Image Link’ data type is used for those fields which contain clickable images.
If you want to display clickable images in the data table of a report then you would need to use a field of the ‘Image Link’ data type.
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Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
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This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
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The data type of a data source schema field determines the kind of data to expect (in the connected data source) 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 also determines which operations are allowed and not allowed on a data source schema field.
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.
Get the ebook on Google Data Studio (50+ Pages)
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 a field in the underlying data source.
#2 Percent – select this data type if you want data studio to expect percentage data when processing a field in the underlying data source.
#3 Duration – select this data type if you want data studio to expect time duration in seconds when processing a field in the underlying data source.
For example, consider the following Google Sheets data source:
Here,
The field ‘Number of orders’ is of type ‘number’.
The field ‘Percentage of Sales’ is of type ‘percent’.
The field ‘Phone Call duration’ is of type ‘duration’.
When we connect this data source to our data source schema then while 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 underlying data source. A text data type can include any combination of letters, numbers, special symbols (like [, }, @….) and other characters.
Consider the following Google Sheets data source:
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:
#1 Absolute dates – It refers to a specific date that you can point to on a calendar.
#2 Relative dates – It refers to a date that you can not point to on a calendar.
The data types for ‘time’ fields can be divided into the following two categories:
#1 Absolute time – It refers to a specific time that is accompanied by an absolute date.
#2 Relative time – It refers to a specific time that is not accompanied by an absolute date.
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 source 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 underlying data source:
Currency Data Type
Use the ‘Currency’ data type if you want Data Studio to expect a currency when processing a field in the underlying data source.
Image data type
Use the ‘Image’ data type if you want data studio to expect the URLs of images when processing a field in the underlying data source:
Note(1): The ‘Image’ data type is used for only those fields which return data of type image. Such fields are called image fields.
Note(2): The image fields are used to display images in the data table of a report.
Image Link data type
The ‘Image Link’ data type is used for those fields which contain clickable images.
If you want to display clickable images in the data table of a report then you would need to use a field of the ‘Image Link’ data type.
Register for the FREE TRAINING...
"How to use Digital Analytics to generate floods of new Sales and Customers without spending years figuring everything out on your own."
Here’s what we’re going to cover in this training…
#1 Why digital analytics is the key to online business success.
#2 The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
#3 Why Google and Facebook ads don’t work for most businesses & how to make them work.
#4 Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
#5 The number 1 reason why conversion optimization is not working for your business.
#6 How to advertise on any marketing platform for FREE with an unlimited budget.
#7 How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com
