Google Data Studio Number Formats / Data Types
When you create or edit a data source in Google Data Studio, you get the option to select the data type of the data source field.
One of the data types supported by Google Data Studio is ‘numeric’:
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:
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’.
Now if we create a report from this data source schema then it would look like the one below:
This report matches with our data source:
The only difference here is that the values of the ‘phone call duration’ field are displayed in a different format.
For example, Data Studio displayed 230 seconds as 00:03:50
If you convert 230 seconds into minutes, it would be 230/60 = 3.83 minutes or 3 minutes 50 Seconds
Get the ebook on Google Data Studio (50+ Pages)
Using incorrect numeric data types
Consider the following Google Sheets data source:
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’.
But what if, when deciding the data source schema (structure):
- we set the data type of the field ‘Number of orders’ to ‘Duration’
- we set the data type of the field ‘Percentage of Sales’ to ‘Number’
- we set the data type of the field ‘Phone Call duration’ to ‘Percent’
Then this is what our Data Studio report would look like:
Data Studio will automatically convert all the values of the:
- ‘Number of Orders’ field to ‘Duration’ data type
- ‘Percentage of Sales’ field to ‘Number’ data type
- ‘Phone Call Duration’ field to ‘Percent’ data type
So, when you select an incorrect numeric data type while defining the data source schema, you get incorrect/unexpected data in your reports.
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#7 How to learn and master digital analytics and conversion optimization in record time.
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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.
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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.
About the Author
Himanshu Sharma
When you create or edit a data source in Google Data Studio, you get the option to select the data type of the data source field.
One of the data types supported by Google Data Studio is ‘numeric’:
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:
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’.
Now if we create a report from this data source schema then it would look like the one below:
This report matches with our data source:
The only difference here is that the values of the ‘phone call duration’ field are displayed in a different format.
For example, Data Studio displayed 230 seconds as 00:03:50
If you convert 230 seconds into minutes, it would be 230/60 = 3.83 minutes or 3 minutes 50 Seconds
Get the ebook on Google Data Studio (50+ Pages)
Using incorrect numeric data types
Consider the following Google Sheets data source:
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’.
But what if, when deciding the data source schema (structure):
- we set the data type of the field ‘Number of orders’ to ‘Duration’
- we set the data type of the field ‘Percentage of Sales’ to ‘Number’
- we set the data type of the field ‘Phone Call duration’ to ‘Percent’
Then this is what our Data Studio report would look like:
Data Studio will automatically convert all the values of the:
- ‘Number of Orders’ field to ‘Duration’ data type
- ‘Percentage of Sales’ field to ‘Number’ data type
- ‘Phone Call Duration’ field to ‘Percent’ data type
So, when you select an incorrect numeric data type while defining the data source schema, you get incorrect/unexpected data in your reports.
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.
About the Author
Himanshu Sharma