Organizations rely on several Business Analytics and Data Visualization Tools to gain meaningful insights into data. One such Business Analytics tool is Google Data Studio, which enables businesses to create reports on organizational data and make data-driven decisions. Since Google Data Studio can access data from different applications of Google Suite like Google Analytics, Google Ads, and Google Sheets, data professionals popularly use it to create useful reports and dashboards.
However, Google Data Studio does not only connect with Google Suite’s products but also can integrate with External Data Sources or Database Management Applications like PostgreSQL, SQL, and MySQL. You can seamlessly fetch or access data from specific databases to perform, for example, Google Data Studio PostgreSQL integration, and analyze data with better visualizations.
In this article, you will learn the basics of Google Data Studio, its features, and steps to connect Google Data Studio with the PostgreSQL database using the Google Data Studio PostgreSQL connector.
Prerequisites for Google Data Studio PostgreSQL Integration
You would need basic knowledge of the Google Data Studio platform, PostgreSQL database, and SQL queries.
What is Google Data Studio?
Image credit: Data Studio
Google Data Studio is an open-source tool used to convert your data into interactive and easy-to-understand reports and dashboards. It helps organizations to create and share data visualizations with teams and make informed decisions. With Google Data Studio, you can interpret your data using charts, graphs, pie charts, geography maps, pivot tables, paginated tables, and more.
Reports in Google Data studio use clickable images to create product catalogs, video libraries, and other hyperlinked contents. Besides, users can invite their team to edit or view reports by sending email links. They can also embed their reports to other web pages like Google Sites, Blog Posts, Marketing Articles, or Social Media Platforms like Facebook or Twitter.
With Google Data Studio, you can create your dashboards to answer specific questions about your business. The Explorer function in Google Data Studio allows you to work with your data by adding dimensions, mathematical operations, and custom formulas to transform your data into meaningful business intelligence.
Using Google Data Studio, organizations can pull information from different data sources, which can help them understand their customers across their business operations.
For more information on Google Data Studio, we have a beginner’s guide here – What is Google Data Studio 360?. If you would like to explore new features added to Google Data Studio, we have a comprehensive guide here – Google Data Studio Update: Amazing New Features.
What Are the Benefits of Using Google Data Studio?
Several Widget Options
Unlike Google Analytics, where you can only have 12 graphs or charts in a report, you can have any number of widgets in Google Data Studio, thereby allowing users to modify these widgets with various metrics. Types of widgets include heat graphs (region, state, or country), pie charts, time-series graphs, and many more.
Collect Data From Multiple Sources
Google Data Studio allows users to collect and access data from multiple sources like Google Analytics, Google Ads, YouTube, Search Console, and many more. Users can consolidate their reports from all such data sources.
Share Reports Easily
Often you are required to get your reports reviewed by colleagues to receive feedback and improve the accuracy of reports. Google Data Studio enables you to provide access to your reports for your team or colleagues, just like Google Sheets and Google Docs. This feature allows real-time sharing, where the entire team can access reports and make changes to them simultaneously.
Customizable Reports
Google Data Studio can create custom reports using different styles, graphs, designs, and formatting. You can customize the page layout, text, graphs, metrics, and style elements.
Free Data Studio Templates
Google Data Studio provides users with preloaded templates for Google Analytics, YouTube, Google Ads, and more. It also provides templates for E-commerce, Data Analysis, Content Marketing, Rank Tracking, SEO Reports, and many more. This feature enables users to create quick and easy reports.
Embed Data Studio Reports
Google Data Studio enables users to embed their reports across Social Media Platforms like Facebook or Twitter. You have to include the report URL in your social media post, and then it will be published.
What is PostgreSQL?
PostgreSQL is an advanced and open-source Object-Relational Database Management System. It is the extension of SQL along with some advanced features.
Today, PostgreSQL functions as both relational and non-relational queries. It has helped developers build applications while protecting data integrity. Many websites as well as mobile applications leverage PostgreSQL for the flexibility and reliability of digital solutions.
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How to Connect Google Data Studio PostgreSQL Database?
Method 1: Connecting Google Data Studio PostgreSQL Using PostgreSQL Connector
Follow the steps below to connect your Google Data Studio with the PostgreSQL database.
Step 1: Register for the Google Data Studio if you don’t have an account yet. If you have one, log in to your account.
Image Credits: data36
Step 2: Add a new Data Source by clicking the “+Create” button in the top left corner.
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Step 3: Click on the Data Source option as shown in the image below.
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Step 4: Search and select for the Google Data Studio PostgreSQL connector. You can see it in the window below.
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Step 5: Set the credentials for the Data Server.
After selecting the PostgreSQL connector, the below Database Authentication window will pop up.
Image Credits: data36
It consists of the following attributes.
- Host Name/IP address: IP address of the Data Server.
- Port: Port of the PostgreSQL connector on the Data Server. It is 5432 by default.
- Database: The name of the database. In this case, it is a PostgreSQL database.
- Username: Username of the PostgreSQL database.
- Password: Password of the PostgreSQL database.
- SSL Connection: This is the SSL connection. You can enable the secure SSL connection by checking it.
After filling in all fields, your authentication window will look like the image below.
Image Credits: data36
Step 6: Select your data table.
You can choose any data table in Data Server. In this case, we have selected a zoo table, as shown in the image.
Image Credits: data36
Starting 2018, Google Data Drive introduced a new feature where you can use a query to transform your PostgreSQL data in a preferred format before connecting it to your Google Data Drive. Through this feature, you can import the aggregated data of your data table instead of the whole data table.
In the below example, we have used a query to count the number of animals in the zoo data table.
Image Credits: data36
Step 7: Format the data table.
You need to name the new data table. You can also rename the column names and set the data type and the aggregate function as shown below.
Image Credits: data36
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Step 8: Create reports.
After connecting the Google Data Studio PostgreSQL database, you can generate reports by creating charts for the zoo dataset.
Image Credits: data36
You can also show the number of animals for your zoo-data-counted dataset, as displayed in the image below.
Image Credits: data36
If there are any changes in the PostgreSQL table, they will be reflected in the Google Data Studio. You can see them by simply refreshing the above-created charts.
Method 2: Creating Google Data Studio PostgreSQL Data Reports Using CData Connect Cloud
You can use Google Data Studio PostgreSQL connection to create reports with visualizations for sharing with your clients. Alternatively, you can connect with CData Connect Cloud to get instant access to PostgreSQL data for visualizations.
Connecting to PostgreSQL Database Using CData
Follow these steps to create a virtual PostgreSQL database and build reports from it through Google Data Studio.
Step 1: Sign up for a free trial at CData Connect if you don’t have an account. If you have one, proceed to the next step.
Step 2: Log in to the CData Connect Cloud and click on Databases. It will show the available data sources in a new window.
Image Credits: CData
Step 3: Select the PostgreSQL database option.
Step 4: Enter the authentication properties for connecting with the PostgreSQL database like the name of the connection, username, password, and security token.
The default port number is 5432 to connect with the PostgreSQL database. Set the username and password to your server. Your database property is then connected to your default database, as shown below.
Image Credits: CData
Step 5: Click on the Test Database tab.
Step 6: Now, click on the Privileges tab and add the new user, or you can use the existing user with appropriate permissions.
Visualizing PostgreSQL Data in Google Data Studio
Here are the steps to visualize PostgreSQL data in your Google Data Studio.
Step 1: Log in to your Google Data Studio and click on Data Sources.
Step 2: Create a New Data Source and choose CData Connect Cloud Connector, as shown below.
Image Credits: CData
Step 3: You need to authorize the CData Connect Cloud connector to connect with the external service.
You can use your instance name as myinstance in myinstance.cdatacloud.net to connect with your Connect Cloud instance. You are also required to enter your username and password to connect to your Connect Cloud instance.
Step 4: Select the PostgreSQL database and click on Next.
Step 5: Select the table and click on Next.
Step 6: Click on the Connect button in the top right corner.
Image Credits: CData
Step 7: You can now modify the columns. Once done, select Create Report.
Image Credits: CData
Step 8: Add the data source to your report as shown below.
Choose the visualization type and add it to the report. You can select the dimensions and measures to customize the visualization, as shown below.
Image Credits: CData
This brings us to the end of the Google Data Studio PostgreSQL connection article. We discussed two methods to connect Google Data Studio PostgreSQL database – one using Google Data Studio PostgreSQL connector and the other using CData integration.
Conclusion
In this tutorial, you learned how to use Google Data Studio for data visualization with Google Data Studio PostgreSQL database connector. However, in Google Data Studio, you can also explore and visualize data from other sources like Google Analytics, Google Ads, Google Sheets, and more. Google Data Studio can perform visualizations on real-time data for database connectors, like MySQL, MS SQL Server, and just like Google Data Studio PostgreSQL connector.
To get the best analysis results and get a complete picture of your data, it is imperative to look at data from multiple sources together. In such cases, designing and using your ETL pipelines to merge data can become challenging especially when your number of data sources keeps growing day by day.
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Manjiri loves data science and produces insightful content on AI, ML, and data science. She applies her flair for writing for simplifying the complexities of data integration and analysis for solving problems faced by data professionals businesses in the data industry.