Google Data Studio Data Sources – Tutorial

Last Updated: March 10, 2022

What are Google Data Studio data sources?

A Google Data Studio data source is a place where your collected data actually resides.

A data source refers to a specific data set. 

The data source is not exactly a data platform, although these two terms are often used interchangeably. 

A data platform is made up of one or more data sources.

For example, Google Sheets is a data platform and it is made up of one or more spreadsheets. So a specific Google spreadsheet is an example of a data source:

data platform and data sources


Similarly, Google Analytics is a data platform and it is made up of one or more reporting views. So a specific Google Analytics reporting view is an example of a data source:

GA data platform and data sources
connectors

What is a data source schema?

A data source schema is a Data Studio file that is used to define how a connector should pull data from a data source and then send it to the Data Studio report(s).

When you log in to GDS (Google Data Studio), Google gives you the option to create a new data source or edit an existing data source: 

data source schemas

But this name ‘data source’ (in the context of GDS) is a misnomer. You are not creating a data source in GDS. 

What you are actually creating is the data source schema which defines how a connector should pull data from a data source and then send it to one or more reports.

This is what a data source schema looks like:

schema view

We create a data source schema for a specific data source

If you want to display data from a data source in your Data Studio report then you would need to first create a data source schema for that data source and then add the data source schema to your report:

We create a data source schema for a specific data source

The same data source schema can also be used for multiple data studio reports

The same data source schema can also be used for multiple data studio reports

Similarly, if you want to display data from multiple data sources in your Data Studio report then you would need to create a separate data source schema for each data source and then add each data source schema to your report:

display data from multiple data sources

These data sources can belong to one or more data platforms:

data sources can belong to one or more data platforms

For example, the Google Analytics platform is made up of one or more reporting views. So a specific Google Analytics reporting view is an example of a data source:

example of a data source

Similarly, the Google Sheets platform is made up of one or more spreadsheets. So a specific Google spreadsheet is an example of a data source:

specific Google spreadsheet is an example of a data source

The Cross-Platform Reports in Data Studio

The cross-platform reports are the report that you create from multiple data sources that belong to different data platforms.

The Cross Platform Reports in Data Studio

Find your way around the data source schema editor

#1 Navigate to the home page of the Google Data Studio.

#2 Click on the ‘Data Sources’ tab:

create data source

#3 Locate your data source schema and then click on its name in order to open it:

open file

Here is what the data source schema editor looks like:

schema legends

Data source schema editor legends

Following are the various data source schema editor legends:

#1 Data Studio logo 

Click on the logo to quickly navigate to the home page:

logo

Note: If you want to quickly navigate to the home page of your Data Studio account from any place within Data Studio then click on the Google Data Studio logo.

#2 Data source schema name

Double-click on the name to change the name of your data source schema.

Data source schema name

You can change the name of your data source as many times as you want.

#3 Data source schema credentials

Through this setting, you can decide who should be able to access data through this data source schema.

Data source schema credentials

#4 Data source schema freshness

Through this setting, you can decide how frequently the data source schema should check for fresh data from the connected data source.

Data source schema freshness

#5 Community visualization access

This setting allows or prevents community visualization to display data from the data source schema.

Community visualization access

#6 Field editing in reports

This setting allows or stops report editors from changing the definitions of the data source schema fields at the chart level.

field editing in report

#7 Make a copy of the data source schema

copy report

#8 Data source schema version history

data soure version

Through this setting, you can view or restore previous versions of the data source schema.

version history

#9 Share data source schema with other users

share data source

#10 Get help on Google Data Studio

help

#11 Switch account

switch account

#12 Create a new report from the data source schema

create report

#13 Create a new exploration from the data source schema

new

#14 Add a parameter

Add a parameter

Use this setting to pass user-supplied data to calculated fields and connectors.

#15 Add a new calculated field

add a field

A calculated field is a field that performs certain action(s) on another field(s) in your data source schema.

#16 Filter data by current viewer’s email address

filter by email

Use the ‘FILTER BY EMAIL’ setting if your data source contains an email field that stores the email addresses of your report viewers and you want the viewers of your report to see only that row(s) of data which is associated with the email address they used to sign in to their Google account.

#17 Edit data source schema connection

edit connection

A data source schema connection is the connection between your data source schema and the underlying data source. Editing a data source schema connection means changing how a data source schema connects to your data source.

#18 List of data source schema fields

list of fields

Dimensions, Metrics and parameters are all counted as fields in the data source schema.

#19 Data types of data source schema fields

data type

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.

#20 Default aggregation used for each data source schema field

default aggregation

In the context of Google Data Studio, aggregation is the process of summarizing tabular data. 

You can aggregate/summarize tabular data in Google data studio by carrying out the following operations on numeric fields:

  • Calculate the sum/total of all the values of a numeric field.
  • Calculate the average of all the values of a numeric field.
  • Find the minimum or maximum value of a numeric field etc.

#21 Optional description for each data source schema field

description

If a certain data source schema field is not self-explanatory (quite common in the case of calculated fields) then you can enter a small note next to it in the ‘Description’ column which can instantly remind you what the field is all about and what it is supposed to do.

#22 Search data source schema fields

search fields

Use this search box to search for a particular field (dimension, metric, parameter) in your data source schema. This search functionality comes really handy when you have dozens or even hundreds of fields in your schema.

#23 List of all the dimensions available

list of dimension

Note: Dimensions appear in green chips in the data source schema.

#24 List of all the metrics available

list of metric

Note: Metrics appear in blue chips in the data source schema.

#25 Refresh data source schema fields

refresh fields 1

If you make any changes to the underlying data source then click on the ‘Refresh fields’ button.

#26 Number of fields in the data source schema

no of fields

Dimensions, metrics and parameters are all counted as fields in the data source schema. So if there are 6 dimensions, 6 metrics, and 1 parameter then the total number of fields in the data source schema would be reported as 13 (6+6+1).

#27 List of all the parameters available

parameter list

Note: Parameters appear in purple chips in the data source schema.

Sorting the data source schema fields, data types and default aggregation in ascending or descending order:

sort

Other articles on Google Data Studio

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  2. Google Data Studio Parameters explained with examples
  3. Google Data Studio Number Formats / Data Types
  4. How to Change Language in Google Data Studio
  5. Google Data Studio Date Format and Time Explained
  6. Google Data Studio Tutorial with FREE PDF ebook
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  9. Google Data Studio Page Navigation Tutorial
  10. Understanding Report Editor in Google Data Studio
  11. Best practices for creating a report in Google Data Studio
  12. How to share reports in Google Data Studio
  13. Seven methods to create a new report in Google Data Studio
  14. Google Data Studio Report Tutorial
  15. How to invite people to view or edit a report in Google Data Studio
  16. How to share the link of your report in Google Data Studio
  17. Schedule email delivery of a report in Google Data Studio
  18. How to download Data Studio report as PDF
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  20. Guide to Data Types in Google Data Studio
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  26. Google Data Studio Calculated Fields Tutorial
  27. Working with the Text data type in Google Data Studio
  28. The Data Set Configuration Error in Google Data Studio
  29. Data Source Fields in Google Data Studio – Tutorial
  30. Refresh data source schema fields in Google Data Studio
  31. Google Data Studio Dimension vs Metric
  32. How to filter by email in Google Data Studio
  33. Google Data Studio – Sharing Data Sources (aka data source schema)
  34. Field editing in reports – Google Data Studio
  35. Data Source Version History in Google Data Studio
  36. Community Visualization Access in Google Data Studio
  37. Understanding Data Source Credentials in Google Data Studio
  38. Understanding Data Freshness in Google Data Studio
  39. How to create and configure a data source in Google Data Studio
  40. Google Data Studio Aggregation Explained
  41. How to Edit a Calculated Field in Google Data Studio
  42. Formula Rejection in Google Data Studio
  43. Doing Basic Maths on Numeric Fields via Calculated Fields

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