Calculated Fields in Google Data Studio – Tutorial
What is a calculated field?
A calculated field is a field that performs some action(s) on other field(s) in your data source or chart via a formula.
These actions could be:
- Arithmetic and math operations
- Manipulating text, date and geographic information
- Using branching logic to evaluate data
Through calculated fields, you can create new metrics and dimensions from your derived data.
Types of calculated fields
Calculated fields can be further categorized into:
#1 Data Source specific calculated field – It is the calculated field created in a data source. When you create a calculated field in a data source, the calculated field is available in any report that uses that data source. However, you can’t use a data source specific calculated field with blended data.
#2 Chart specific (or chart level) calculated field – It is the calculated field created in a specific chart in a report. When you create a calculated field in a chart, the calculated field is available only in the chart in which you create it. However, you can use a chart specific calculated field with blended data.
Note: When using a chart specific calculated field, you can not reference other chart-specific calculated fields in your formula, even if those fields are defined in the same chart. If you want to reference other calculated fields, use a data source calculated field.
Types of data source specific calculated fields
Data Source specific calculated field can be further categorized into:
#1 Data source specific Calculated dimension – It is a dimension that performs some action(s) on other field(s) in your data source via a formula.
#2 Data source specific Calculated metric – It is a metric that performs some action(s) on other field(s) in your data source via a formula.
Get the ebook on Google Data Studio (50+ Pages)
Types of chart specific calculated fields
Chart specific calculated field can be further categorized into:
#1 Chart specific Calculated dimension – It is a dimension that performs some action(s) on other field(s) in your chart via a formula.
#2 Chart specific Calculated metric – It is a metric that performs some action(s) on other field(s) in your chart via a formula.
How to identify calculated fields
All calculated dimensions appear in the data source editor with an ‘fx’ symbol:
All calculated metrics appear in the data source editor with an ‘fx’ symbol:
How to identify calculated fields in the report editor
It is not easy to identify calculated fields (whether calculated dimension or calculated metrics) in a report editor as they do not appear with an ‘fx’ symbol:
If the calculated field is created in a data source then you can not easily identify it in the report editor.
But if the calculated field is created in a specific chart then you can identify it by hovering your mouse over the edit section of the field:
Calculated fields’ data types
The data type assigned to a calculated field depends upon the type of action(s) it performs on other field(s) in your data source or chart.
If your calculated field perform an arithmetic operation on other field(s) then it returns data of type ‘number’. So the data type assigned to the calculated field would be ‘Number’.
Similarly, if your calculated field performs text operation on other field(s) then it returns data of type ‘text’. So the data type assigned to the calculated field would be ‘text’.
However, this is not always the case & sometimes you may need to manually change the data type of the calculated field.
Note: You can change the data type of your calculated fields using the ‘Type’ drop-down menu in the data source editor:
Creating and using calculated fields in Google Data Studio
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- Guide to Supermetrics queries for Google Sheets
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- Google Data Studio Tutorial – 2019
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- Guide to Data Source Fields in Google Data Studio
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- Understanding Data Freshness in Google Data Studio
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- Doing Basic Maths on Numeric Fields via Calculated Fields
- Google Data Studio Number Formats / Data Types
- Guide to Calculated Fields in Google Data Studio
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Do you know the difference between Web Analytics and Google Analytics?
99.99% of course creators themselves don’t know the difference between Web analytics, Google Analytics (GA) and Google Tag Manager (GTM).
So they are teaching GA and GTM in the name of teaching Web analytics.
They just copy each other. Monkey see, monkey do.
But Web analytics is not about GA, GTM.
It is about analyzing and interpreting data, setting up goals, strategies and KPIs.
It’s about creating strategic roadmap for your business.
Web Analytics is the core skill. Google Analytics is just a tool used to implement ‘Web Analytics’.
You can also implement ‘Web analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.
Using Google Analytics without the good understanding of ‘Web analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.
You are either likely to end up somewhere other than your destination or you get involved in an accident.
You learn data analysis and interpretation from Web analytics and not from Google Analytics.
The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.
You get that direction from ‘Web analytics’ and not from ‘Google Analytics’.
You learn to set up KPIs, strategies and measurement framework for your business from ‘Web analytics’ and not from ‘Google Analytics’.
So if you are taking a course only on 'Google Analytics’, you are learning to use one of the tools of ‘Web analytics’. You are not learning the ‘Web analytics’ itself.
Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.
You need to know lot more than GA in order to work in Web analytics and marketing field.
So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage web/digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.
Here what You'll Learn On This FREE Web Class!
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
What is a calculated field?
A calculated field is a field that performs some action(s) on other field(s) in your data source or chart via a formula.
These actions could be:
- Arithmetic and math operations
- Manipulating text, date and geographic information
- Using branching logic to evaluate data
Through calculated fields, you can create new metrics and dimensions from your derived data.
Types of calculated fields
Calculated fields can be further categorized into:
#1 Data Source specific calculated field – It is the calculated field created in a data source. When you create a calculated field in a data source, the calculated field is available in any report that uses that data source. However, you can’t use a data source specific calculated field with blended data.
#2 Chart specific (or chart level) calculated field – It is the calculated field created in a specific chart in a report. When you create a calculated field in a chart, the calculated field is available only in the chart in which you create it. However, you can use a chart specific calculated field with blended data.
Note: When using a chart specific calculated field, you can not reference other chart-specific calculated fields in your formula, even if those fields are defined in the same chart. If you want to reference other calculated fields, use a data source calculated field.
Types of data source specific calculated fields
Data Source specific calculated field can be further categorized into:
#1 Data source specific Calculated dimension – It is a dimension that performs some action(s) on other field(s) in your data source via a formula.
#2 Data source specific Calculated metric – It is a metric that performs some action(s) on other field(s) in your data source via a formula.
Get the ebook on Google Data Studio (50+ Pages)
Types of chart specific calculated fields
Chart specific calculated field can be further categorized into:
#1 Chart specific Calculated dimension – It is a dimension that performs some action(s) on other field(s) in your chart via a formula.
#2 Chart specific Calculated metric – It is a metric that performs some action(s) on other field(s) in your chart via a formula.
How to identify calculated fields
All calculated dimensions appear in the data source editor with an ‘fx’ symbol:
All calculated metrics appear in the data source editor with an ‘fx’ symbol:
How to identify calculated fields in the report editor
It is not easy to identify calculated fields (whether calculated dimension or calculated metrics) in a report editor as they do not appear with an ‘fx’ symbol:
If the calculated field is created in a data source then you can not easily identify it in the report editor.
But if the calculated field is created in a specific chart then you can identify it by hovering your mouse over the edit section of the field:
Calculated fields’ data types
The data type assigned to a calculated field depends upon the type of action(s) it performs on other field(s) in your data source or chart.
If your calculated field perform an arithmetic operation on other field(s) then it returns data of type ‘number’. So the data type assigned to the calculated field would be ‘Number’.
Similarly, if your calculated field performs text operation on other field(s) then it returns data of type ‘text’. So the data type assigned to the calculated field would be ‘text’.
However, this is not always the case & sometimes you may need to manually change the data type of the calculated field.
Note: You can change the data type of your calculated fields using the ‘Type’ drop-down menu in the data source editor:
Creating and using calculated fields in Google Data Studio
Related Articles
- How to use Supermetrics for Google Sheets Add-on
- How to extract data from Google Analytics into Google Sheets
- How to extract data from Google Ads into Google Sheets
- How to extract data from Facebook Ads into Google Sheets
- How to extract data from Google Search Console into Google Sheets
- Guide to Supermetrics queries for Google Sheets
- How to extract data from Excel or CSV file into Google Sheets
- Google Data Studio Tutorial – 2019
- How to format Google Sheets data for Google Data Studio
- How to use Google Data Studio with Google Sheets
- Community Visualization Access in Google Data Studio
- Data Source Version History in Google Data Studio
- Dimensions and metrics in Google Data Studio
- Field editing in reports – Google Data Studio
- Guide to Data Source Fields in Google Data Studio
- Guide to Data Source in Google Data Studio
- How to create and configure a data source in Google Data Studio
- How to Share Data Source with others in Google Data Studio
- Understanding Data Freshness in Google Data Studio
- Understanding Data Source Credentials in Google Data Studio
- How to use Google Data Studio in another language
- Doing Basic Maths on Numeric Fields via Calculated Fields
- Google Data Studio Number Formats / Data Types
- Guide to Calculated Fields in Google Data Studio
- Guide to Date and Time Data Types in Google Data Studio
- How to work with ‘Text’ data type in Google Data Studio
- How to work with Boolean data type in Google Data Studio
- The ‘Data Set Configuration Error’ in Google Data Studio
- Working with Timezones in Google Sheets and Google Data Studio
- Formula Rejection in Google Data Studio
- Understanding Functions in Google Data Studio
- How to Edit a Calculated Field in Google Data Studio
- Why You Should Avoid Using Functions and Calculated Fields in Data Studio
Do you know the difference between Web Analytics and Google Analytics?
99.99% of course creators themselves don’t know the difference between Web analytics, Google Analytics (GA) and Google Tag Manager (GTM).So they are teaching GA and GTM in the name of teaching Web analytics.
They just copy each other. Monkey see, monkey do.
But Web analytics is not about GA, GTM.
It is about analyzing and interpreting data, setting up goals, strategies and KPIs.
It’s about creating strategic roadmap for your business.
Web Analytics is the core skill. Google Analytics is just a tool used to implement ‘Web Analytics’.You can also implement ‘Web analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.
Using Google Analytics without the good understanding of ‘Web analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.
You are either likely to end up somewhere other than your destination or you get involved in an accident.
You learn data analysis and interpretation from Web analytics and not from Google Analytics.The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.
You get that direction from ‘Web analytics’ and not from ‘Google Analytics’.
You learn to set up KPIs, strategies and measurement framework for your business from ‘Web analytics’ and not from ‘Google Analytics’.So if you are taking a course only on 'Google Analytics’, you are learning to use one of the tools of ‘Web analytics’. You are not learning the ‘Web analytics’ itself.
Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.
You need to know lot more than GA in order to work in Web analytics and marketing field.
So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage web/digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.
Here what You'll Learn On This FREE Web Class!
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