Welcome to my Google Data Studio Tutorial. I am very excited to teach you how to use Google Data Studio to visualize and analyze data.

What is Google Data Studio?

Google Data Studio (or GDS) is a tool used to visualize data. It is a cloud-based tool which means you can access it from any device/browser as long as you have access to a stable internet connection. Data Studio is a completely free visualization tool which allows you to build great dashboards and reports.

Note: Google Data Studio is built on Google Drive. That means you would need a Google Drive account before you can access it.

Why use Google Data Studio?

When you have got a lot of data to analyze (especially big data) you cannot spend days or weeks analyzing thousands or millions of rows of data in Excel spreadsheets …. to find hidden trends and insight.

You need a tool that allows you to quickly make sense of data and determine patterns and anomalies which are otherwise….. can be extremely hard to detect in a timely manner. This is where data visualization tools like Data Studio comes in handy. Through this tool, you can greatly speed up your data analysis.

Data visualization is the presentation of data in graphical format.

Data visualization helps in data interpretation and data retention. It helps to tell meaningful, emotional and engaging stories to key decision-makers.

If you wish to make your data reporting more meaningful and persuasive then you need to learn the art of storytelling by visualizing your data. Data Studio can make your data reporting much more meaningful and persuasive.

Get the ebook on Google Data Studio (50+ Pages)

What are the benefits of using Google Data Studio?

Google Data Studio is a great visualization tool since it is very versatile, easy to create, share and collaborate with zero cost.

Following are some of the main benefits of using Google Data Studio as a visualization tool.

Multiple data sources:

You can connect Google Data Studio to multiple data sources and collect and combine data in one single report. This way you can measure your marketing activities across platforms and channels and generate cross-platform and multi-channel insights.

Unlimited customization:

You can fully customize the Data Studio reports. You can use a blank canvas to design your own report from scratch or you can use a Google Data Studio template. This makes Google Data Studio a very convenient and hassle-free way to design reports and dashboards for various data platforms like Google Analytics, Google Ads, YouTube ads, etc.

Dynamic and real-time reporting:

Google Data Studio reports are very dynamic in nature. That means you can apply any sort filter on a data source and narrow down the data based on date range, time, users, device category, country, etc. Also, these reports can be made real-time by pulling the data in real-time as it is available in the corresponding data source.

Report sharing and collaboration:

Google Data Studio reports can be shared in multiple formats by scheduling email delivery, by creating a link for a report or downloading the report as PDF. You can also add your peers to the report for editing and reading purpose which makes collaboration painless across the team.

Zero cost:

One of the big advantages of using Google Data Studio is that it is completely free to use. Also, there is no limit to the number of users per data studio account which makes it more meaningful in a large organization.

How to access Google Data Studio

If you have never used Google Data Studio before then the best way to access it is by searching for the keyword ‘google data studio’ on google.com and then click on the first search engine listing:

Alternatively, you can access Google Data Studio by clicking on this link: https://datastudio.google.com/overview

Then click on ‘Use it for free’ button:

Now log in using your Google email address and password. If you do not have a Google account then click on the ‘create account’ link:

If you have never used Google Data Studio before then this is what the home page of Google Data Studio will look like:

Related Article: How to use Google Data Studio in another language

Why you should pull data into Data Studio via a spreadsheet

A rookie mistake that most Data Studio users make is that they pull data directly from a data platform into Data Studio and then try to manipulate it there. But Data Studio is not meant for data manipulation. It is not a spreadsheet.

When you manipulate data in Data Studio, it slows down your report. This is especially true for large data sets.

Manipulating data in a spreadsheet is a lot easier than manipulating data in Data Studio.

When you choose to manipulate data in Data Studio, you make it unnecessarily hard to use.

That is why we first pull the data from a data platform into a spreadsheet (like Google Sheets or Excel) and manipulate the data there, and only after that use that data in Data Studio.

How to visualize data in Google Sheets via Google Data Studio

Step-1: Prepare your Google Sheet Data for Data Studio.

Before you upload data from Google Sheets to Google data studio, you need to make sure two things:

1. You pulled data correctly into Google Sheets. 
2. The data you pulled into Google Sheets is in the correct format.

Because this is going to affect your data visualization and data analysis in Data Studio. 

If you feed garbage to data studio then you are going to get garbage. 

Garbage in, Garbage out.

Following is an example of incorrectly formatted data:

The data is not formatted correctly because it has got empty rows, empty columns, totals.

The column headers are missing. The data is not using correct data types.

So for example, the field ‘order date’ is not of type ‘date’. The ‘Revenue’, ‘Tax’ and ‘Shipping’ fields are not of type currency.

Following is an example of correctly formatted data:

By correct format, I mean:

• There are no empty rows or columns.
• Each column has headers and these headers are meaningful, unique and self-explanatory.
• There should not be subtotals or grand-totals in your data source.
• You also need to make sure that you are using the correct data types. So for example, dates are of type ‘date’, texts are of type ‘text’, numbers are of type ‘number’, the currency is of types ‘currency’.

 

Step-2: Navigate to https://datastudio.google.com/overview

Step-3: Click on the ‘Use it for free’ button:

Step-4: Sign in with your Google email and password. You should now see the home page of Data Studio:

Step-5: Click on the ‘Create’ button:

Step-6: Click on ‘Data Source’

Step-7: Scroll down, find the Google Sheet Connector and then click on it:

Step-8: Rename your data source by double-clicking on the ‘Untitled Data Source’ text:

Step-9: Find and click on your Google Sheets which contains the data you want to visualize:

Step-10: Click on the blue ‘Connect’ button on the top right-hand side:

You should now see a screen like the one below:

Step-11: Make sure each field is of the correct data type. 

For example, from the screenshot above we can see that the ‘order date’ field is of type text. It should be of type ‘date’:

Similarly, ‘Transaction ID’ field is of type ‘date’. It should be of type ‘number’:

All the green fields represent dimensions and all the blue fields represents metrics. 

At this point you can also change the order of various dimensions and metrics through drag and drop:

Step-12: Once everything looks all right then click on the ‘Create Report’ button on the top right-hand side of your screen:

You should now see a dialog box like the one below:

Step-13: Click on the ‘Add to Report’ button.

You should now see following similar screen with a table on the canvas:

Step-14: Name your report by double-clicking on the text ‘Untitled Report’:

That’s how you can create a report in Google Data Studio and visualize the data from a Google Sheets.

Step-15: In order to see this table in the ‘view mode’, click on the ‘view’ button on the top right-hand side:

That’s how your report will look like in the view mode:

Step-16: If you want to edit this table again then click on the ‘Edit’ button on the top right-hand side:

That’s how you can use Data Studio with Google Sheets.

Let’s now learn, how to use Google Data Studio with Google Analytics.

Related Articles:

1. How to format Google Sheets data for Google Data Studio
2. How to use Google Data Studio with Google Sheets
3. Working with timezones in Google Sheets and Google Data Studio

How to visualize Google Analytics data via Google Data Studio

Step-1: Navigate to the home page of your Google Data Studio account: https://datastudio.google.com/navigation/reporting

Step-2: Click on the ‘Create’ button:

Step-3: Click on ‘Data Source’:

Step-4: Scroll down and find the Google Analytics Connector, then click on it:

You should now see a screen like the one below:

 

Step-5: Double click on the text ‘Untitled Data Source’ and then rename it (say ‘Google Analytics Account’):

Step-6: Find and click on the GA property which contains the data you want to visualize:

Step-7: Click on the blue ‘Connect’ button on the top right-hand side:

Here we are using the Google demo account.

Once you clicked on the ‘connect’ button, you should now see a screen like the one below:

Here, all green fields are Google Analytics dimensions and blue fields are Google Analytics metrics.

Step-8: click on the ‘Create Report’ button on the top right-hand side of your screen:

You should now see a dialog box like the one below:

Step-9: Click on the ‘Add to Report’ button.

You should now see following similar screen with a table on the canvas:

Step-10: Name your report by double-clicking on the text ‘Untitled Report’.

That’s how you can you visualize Google Analytics data in Google Data Studio.

Related Articles

1. How to extract data from Google Analytics into Google Sheets
2. How to extract data from Google Ads into Google Sheets
3. How to extract data from Facebook Ads into Google Sheets
4. How to extract data from Google Search Console into Google Sheets
5. How to extract data from Excel or CSV file into Google Sheets 

The building blocks of Google Data Studio

Following are the building blocks of Google Data Studio:

1. Data platforms
2. Connectors
3. Data sources (aka Data Source Schemas)
4. Data sets
5. Data source fields
6. Dimensions
7. Metrics
8. Data types
9. Reports
10. Components (charts)

Introduction to data platforms

Before you can use Data Studio and create reports to visualize data, you need access to one or more data platforms.

Following are examples of data platforms:

• Google Sheets
• Google Analytics
• Excel Spreadsheet
• BigQuery
• Google Ads
• Google Search Console
• YouTube Analytics
• Facebook Ads
• Adobe Analytics, etc

In order to pull data from these data platforms into Data Studio, you would need to use a connector(s).

Introduction to connectors

A connector is a mechanism through which you can pull data from a specific data platform. Any data platform accessible via the internet can be connected with Data Studio.

There are two broad categories of connectors:

• Ready-made connectors
• Custom made connectors

#1 Ready-made connectors

These connectors are ready to use. They are either free to use or require monthly/annual paid subscription. Google connectors, partner connectors and open-source connectors are examples of ready-made connectors.

#2 Custom made connectors

These connectors are developed on demand and are used when ready-made connectors can’t be used to pull data from a specific data platform. You can create your own connector by using Google Apps Script. If you are not a developer, you can hire someone to create a custom made connector for you.

Google Data Studio Connector Gallery

The Google Data Studio Connector Gallery lists all the connectors supported by Google Data Studio. Here you can see a list of all the currently available connectors. If you build your own connector, you can choose to publish and promote it in the connector gallery.

Here is the link to the Google Data Studio Connector Gallery: https://datastudio.google.com/data

Introduction to Google connectors

Google connectors are the connectors built and maintained by Google.

At present Google provides 18 different types of connectors in Data Studio:

All of the Google connectors are free to use as long as you have access to the right Google product. For example, if you do not have access to GA 360 then the Display and Video 360 connector is of no use to you:

There are three categories of Google connectors:

#1 Google product connectors

#2 Google database platform connectors

#3 File upload connector

Google product connectors

Through Google product connectors you can pull data from Google products into Data Studio.

Following are examples of Google product connectors:

1. Campaign Manager – use this connector to connect your Data Studio account to your Campaign Manager network and advertiser data.

2. Display & Video 360 – use this connector to connect your Data Studio account to your Display & Video 360 data.

3. Google Ad Manager 360 – connect Data Studio to Google Ad Manager 360

4. Google Ads – connect Data Studio to Google Ads

5. Google Analytics – connect Data Studio to Google Analytics.

6. Google Cloud Storage – connect Data Studio to Google Cloud Storage.

7. Google Sheets – connect Data Studio to a Google Sheets worksheet or range.

8. Search Console – connect Data Studio to Google Search Console.

9. YouTube Analytics – connect Data Studio to YouTube Analytics.

10. Search Ads 360 connector – connect Data Studio to Search Ads 360.

11. Google Surveys – connect Data Studio to Google Surveys

Google database platform connectors

Through Google database platform connectors you can pull data from Google database platforms into Data Studio.

Following are examples of Google database platform connectors:

1. Google BigQuery – connect Data Studio to BigQuery tables.

2. Google Cloud Spanner – connect Data Studio to Cloud Spanner databases.

3. Google Cloud SQL for MySQL – connect Data Studio to Google Cloud SQL databases.

4. MySQL – connect Data Studio to MySQL databases.

5. PostgreSQL – connect Data Studio to PostgreSQL based databases.

File upload connector

Use the file uploader connector to upload data from any data source (via a CSV file) to Data Studio that is not supported by a specific connector. Use this connector if you want to connect your data studio account with Microsoft Excel spreadsheets. 

If you prefer using Excel with Data Studio then you will find yourself using this connector a lot. I prefer to use Google sheets because it natively integrates with Data Studio and other Google products like Google Analytics and Google Ads.

Extract data connector

Extract data connector is used to pull only a subset of data from an existing data source (i.e. data source which is already available in your data studio account).

The subset of data from an existing data source is called the ‘Extracted Data Source‘.

Thus by using the Extract data connector, you can create an extracted data source in Google Data Studio.

The advantage of using the Extract data connector is that when you extract only a subset of data (instead of all of the data) from a data source (to create reports and explorations), it can make your data studio reports and explorations load faster.

Not only that, but your reports and explorations also become more responsive when applying filters and date ranges.

Note(1): Extracted data sources can contain up to 100MB of data.

Note(2): By default, the extracted data sources contain static data. If you want the extracted data source to automatically update then you would need to turn on the ‘Auto Update’ feature while creating the data source:

Introduction to partner connectors

Partner connectors are connectors built and maintained by third parties like Supermetrics, Funnel, etc. At the time of writing, 257 different types of partner connectors are available in Data Studio: https://datastudio.google.com/datasources/create

Note: Partner connectors are usually not free to use and would require a monthly/annual paid subscription.

Why do you need partner connectors?

Google does not provide any connector for non-Google products.  If you want to pull data from a non-Google data platform (like Facebook Ads, Adobe Analytics, Bing Ads, etc) then you need to use/purchase a partner connector.

Partner connectors are required when you want to consolidate data from multiple data platforms and visualize them in Data Studio. Through partner connectors, you can unite data from multiple marketing platforms into Data Studio.

For example, you can report and compare Google Ads, Facebook, Instagram, Twitter, LinkedIn and Bing Ads campaigns in a single Data Studio report.

Partner connectors make cross-platform reporting possible in Data Studio.

Supermetrics partner connectors

Supermetrics is a great tool that you can use to get partner connectors. They provide connectors for the following data platforms:

• Facebook Ads
• Hubspot
• Microsoft Advertising
• Twitter Ads
• Instagram Insights
• LinkedIn Ads
• YouTube
• Adobe Analytics
• MailChimp, etc.

Supermetrics for Data Studio is a Google Sheet add-on that lets you use several connectors for pulling data from multiple non-Google data platforms.

I also use and recommend Supermetrics for Google Sheets add-on. I use this add-on to pull data from Google Analytics into Google Sheets. Its free version is also available and is good enough, as long as you are using only Google Analytics as a data source.

Related Articles:

1. How to use Supermetrics for Google Sheets Add-on
2. Guide to Supermetrics queries for Google Sheets

Difference between the Supermetrics for Google Sheets and Google Analytics Spreadsheet add-ons

Both are Google Sheet add-ons and both are free to use. Both are used to pull Google Analytics data into a Google Sheet. The main difference is in the ease of use. 

The Google Analytics Spreadsheet Add-on (developed by Google) is not as easy to use as the Supermetrics for Google Sheets add-on, so I recommend using the Supermetrics for Google Sheets add-on.

Related Article: How to use Google Analytics API without any coding

Open-source connectors (community connectors)

Open-source connectors are the connectors built by the Data Studio open-source community. They are also called community connectors: https://datastudio.google.com/datasources/create

You can create your own community connector by using the Apps Script. If you are not a developer then you can hire one to create a custom made connector for you. Any data platform accessible via the internet can be connected with Data Studio.

Introduction to data sources

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

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:

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 data source schema which defines how a connector should pull data from a specific data set and then send it to one or more reports.

A connector pulls these data source fields from the data set. Only the fields provided by the connector are the ones available to use in your reports.

Related Articles:

1. Guide to data sources in Google Data Studio
2. Guide to data source fields in Google Data Studio
3. How to create and configure a data source in Google Data Studio
4. How to share a data source with others in Google Data Studio
5. Data Source version history in Google Data Studio
6. Community visualization access in Google Data Studio
7. Understanding data freshness in Google Data Studio
8. Understanding data source credentials in Google Data Studio
9. Field editing in reports – Google Data Studio
10. The ‘data set configuration error’ in Google Data Studio
11. Formula Rejection in Google Data Studio
12. Understanding functions in Google Data Studio
13. Guide to calculated fields in Google Data Studio
14. Doing basic maths on numeric fields via calculated fields
15. How to edit a calculated field in Google Data Studio
16. Why you should avoid using functions and calculated fields in Data Studio

Introduction to dimensions in Google Data Studio

A dimension is the attribute of your website visitors. It is used to describe or categorize your data. Dimensions in your data source schema appear as green fields:

Introduction to metrics in Google Data Studio

A metric is a number that is used to measure one of the characteristics of a dimension. Metrics in your data source schema appear as blue fields:

Note: In Google Analytics, a dimension cannot be used as a metric and vice versa. Whereas, in Google Data Studio, a dimension can be used as a metric and vice versa.

Related Articles:

• Dimensions and metrics in Google Data Studio

Introduction to data types

The data type of a data source schema field determines the kind of data to expect (in the connected data set) 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:

The data type 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.

Google Data Studio supports the following data types:

1. Numeric
2. Text
3. Date and Time
4. Boolean
5. Geo
6. Currency
7. URL

Related Articles:

1. Guide to data types in Google Data Studio
2. Understanding aggregation in Google Data Studio
3. Google Data Studio number formats/data types
4. Guide to date and time data types in Google Data Studio
5. How to work with text data type in Google Data Studio
6. How to work with boolean data type in Google Data Studio

Introduction to Google Data Studio reports

Reports in data studio are used to tell stories with data. Every report you create should have some purpose. The purpose can be to provide actionable insight, give recommendations or persuasion.

Following are some best practices for creating a report in data studio:

1. Understand who your report is meant for
2. Keep it short and simple
3. Use a report template whenever you can to create a new report.
4. Avoid pulling data directly from a data platform into your reports.
5. Avoid charting data for the current day in your reports.
6. Avoid using functions and calculated fields in your reports.
7. Distribute related charts across multiple pages

You can create a new Data Studio report in the following ways:

1. From the home page
2. From the template found in the template gallery.
3. From the template found in the report gallery.
4. While editing a report
5. While editing a data source
6. By making a copy of an existing report

To learn more about reports in Google Data Studio, check out this article: Google Data Studio report tutorial

Introduction to chart components

A report in Google Data Studio is made up of one or more chart components like:

1. Table
2. Scorecard
3. Time Series
4. Bar Chart
5. Pie Chart
6. Google Maps
7. Geo Chart
8. Line Chart
9. Area Chart
10. Scatter Chart
11. Pivot Table
12. Bullet Chart
13. Treemap

You can access these chart components by clicking on ‘Add a Chart’ drop-down menu in the report editor:

Let’s build a chart to show website performance.

Click on the ‘Add a Chart’ drop-down menu and then click on ‘Score Card’:

On the right-hand side of your report editor, you should see the panel where you can select the metric for the scorecard.

Let’s select ‘Sessions’ metric:

Note: You can also add filters or segments to the selected metric.

Let’s repeat this step to add a few more metrics to our report.

Once you are done, our report may look like the one below:

Now let’s add a trend chart for ‘Visits in Last Week’.

Click on ‘Add to Chart’ drop-down menu and then select ‘Time Series’:

Under the ‘Data’ tab on the right-hand side panel, select ‘Date’ as a dimension and ‘Sessions’ as a metric:

Now our chart on the canvas may look like the one below:

Since Google Data Studio supports dynamic reporting, you can also add controls to your report, to give your report users more freedom to slice and dice data by selecting a date range, device type, segment etc.