Understanding Aggregation in Google Data Studio
In the context of Google Data Studio, aggregation is the process of summarizing tabular data.
Tabular data is data that is in the form of a table. Following is an example of tabular data:
You can aggregate/summarize tabular data in Google Data Studio by:
- Calculating the sum/total of all the values of a numeric field.
- Calculating the average of all the values of a numeric field.
- Finding the minimum value of a numeric field.
- Finding the maximum value of a numeric field.
- Calculating the median of the values of a numeric field.
- Counting the number of values in a field.
- Uniquely counting the number of values in a field.
- Calculating the standard deviation of the values of a numeric field.
- Calculating variance of the values of a numeric field.
There are three methods through which you can aggregate tabular data in Google Data Studio:
#1 You can aggregate data via a field’s default aggregation in the data source schema
The default aggregation determines how that field, by default, is aggregated and displayed in various charts of the report.
Get the ebook on Google Data Studio (50+ Pages)
#2 You can change the aggregation for a particular field in the report editor
The aggregation method changed via report editor can override the default aggregation and apply a different one to the field on a chart.
#3 You can use specific aggregation functions within a calculated field formula to create a new aggregated field
Here, COUNT_DISTINCT is an aggregation function used with a calculated field formula to create a new aggregated field called ‘Total number of customers’.
Default Aggregation
The default aggregation determines how a field, by default, is aggregated and displayed in one or more charts of a report.
You can apply the following default aggregations to fields in your data source schema:
- None – Use this aggregation type when you don’t want to apply any aggregation to a data source field.
- Sum – Use this aggregation type when you want a numeric field to be aggregated and displayed (in one or more charts of a report) by default, as the sum of all of the values of the field.
- Average – Use this aggregation type when you want a numeric field to be aggregated and displayed (in one or more charts of a report) by default, as the average of all of the values of the field.
- Count – Use this aggregation type when you want a field to be aggregated and displayed by default, as the total count of all of the values of the field.
- Count distinct – Use this aggregation type when you want a field to be aggregated and displayed by default, as the total count of all of the unique values of the field.
- Min – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the minimum value of the field.
- Max – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the maximum value of the field.
- Median – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the median value of the field. A median is a middle number in the sorted list of numbers.
- Standard Deviation – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the standard deviation of the values of the field. The standard deviation is a measure of the amount of variation of a set of values.
- Variance – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the variance of the values of the field. The variance measures how far a set of numbers are spread out from their average value.
How to do data aggregation in Google Data Studio
Auto Aggregation
The data source fields that are already aggregated have the default aggregation of ‘auto’ and you can not change the aggregation methods of such field.
Data Sources like ‘Google Analytics’ and ‘Google Ads’ show ‘None’ as the only available aggregation type for most dimensions and ‘Auto’ as the only available aggregation type for most metrics. And you can not change the aggregation methods of such fields:
A calculated field that uses an aggregation function in its formula becomes a pre-aggregated field. Therefore its default aggregation is set to ‘auto’ which can not be changed.
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#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.
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Maths and Stats for Web Analytics and Conversion Optimization
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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
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
In the context of Google Data Studio, aggregation is the process of summarizing tabular data.
Tabular data is data that is in the form of a table. Following is an example of tabular data:
You can aggregate/summarize tabular data in Google Data Studio by:
- Calculating the sum/total of all the values of a numeric field.
- Calculating the average of all the values of a numeric field.
- Finding the minimum value of a numeric field.
- Finding the maximum value of a numeric field.
- Calculating the median of the values of a numeric field.
- Counting the number of values in a field.
- Uniquely counting the number of values in a field.
- Calculating the standard deviation of the values of a numeric field.
- Calculating variance of the values of a numeric field.
There are three methods through which you can aggregate tabular data in Google Data Studio:
#1 You can aggregate data via a field’s default aggregation in the data source schema
The default aggregation determines how that field, by default, is aggregated and displayed in various charts of the report.
Get the ebook on Google Data Studio (50+ Pages)
#2 You can change the aggregation for a particular field in the report editor
The aggregation method changed via report editor can override the default aggregation and apply a different one to the field on a chart.
#3 You can use specific aggregation functions within a calculated field formula to create a new aggregated field
Here, COUNT_DISTINCT is an aggregation function used with a calculated field formula to create a new aggregated field called ‘Total number of customers’.
Default Aggregation
The default aggregation determines how a field, by default, is aggregated and displayed in one or more charts of a report.
You can apply the following default aggregations to fields in your data source schema:
- None – Use this aggregation type when you don’t want to apply any aggregation to a data source field.
- Sum – Use this aggregation type when you want a numeric field to be aggregated and displayed (in one or more charts of a report) by default, as the sum of all of the values of the field.
- Average – Use this aggregation type when you want a numeric field to be aggregated and displayed (in one or more charts of a report) by default, as the average of all of the values of the field.
- Count – Use this aggregation type when you want a field to be aggregated and displayed by default, as the total count of all of the values of the field.
- Count distinct – Use this aggregation type when you want a field to be aggregated and displayed by default, as the total count of all of the unique values of the field.
- Min – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the minimum value of the field.
- Max – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the maximum value of the field.
- Median – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the median value of the field. A median is a middle number in the sorted list of numbers.
- Standard Deviation – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the standard deviation of the values of the field. The standard deviation is a measure of the amount of variation of a set of values.
- Variance – Use this aggregation type when you want a numeric field to be aggregated and displayed by default, as the variance of the values of the field. The variance measures how far a set of numbers are spread out from their average value.
How to do data aggregation in Google Data Studio
Auto Aggregation
The data source fields that are already aggregated have the default aggregation of ‘auto’ and you can not change the aggregation methods of such field.
Data Sources like ‘Google Analytics’ and ‘Google Ads’ show ‘None’ as the only available aggregation type for most dimensions and ‘Auto’ as the only available aggregation type for most metrics. And you can not change the aggregation methods of such fields:
A calculated field that uses an aggregation function in its formula becomes a pre-aggregated field. Therefore its default aggregation is set to ‘auto’ which can not be changed.
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
