Google Data Studio Azure Connection: 2 Easy Steps

on Data Integration, Database, Database Management Systems, Google Data Studio, Microsoft Azure • March 24th, 2022 • Write for Hevo

Data Studio Azure - Featured Image

Gaining meaningful insights from millions of rows of data can be a crucial & challenging task for a business. Free Data Visualization Tools such as Google Data Studio allow you to easily import data from several sources and generate informative dashboards & reports. After gaining essential insights from your charts and reports, you may be required to export this data to your databases such as Azure.  

You can easily set up the Google Data Studio Azure SQL Database Connection using CSV files. You can export your data from the charts in a CSV format and import it to your Azure SQL Database.

In this article, you will learn how to effectively set up the Google Data Studio Azure SQL Database Connection in 2 easy steps.

Table of Contents

What is Google Data Studio?

Data Studio Azure - Google Data Studio Logo
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Google Data Studio (GDS) is a free Data Visualization Tool that allows you to build beautiful interactive dashboards and custom reports. Using this Business Intelligence platform, business teams can effortlessly transform raw data into informative visualizations that assist in making strategic decisions. As an integral part of the Google Ecosystem, you can easily get data from up to 12 different sources, including Google Analytics, and combine it into one customizable and interactive report.

Key Features of Google Data Studio

Since its initial release in 2016, Google Data Studio has become one of the popular Business Intelligence platforms due to the following features:

  • Report Sharing: To streamline the communication between various business teams, Google Data Studio allows you to access and share your reports via Link sharing, Email permissions & scheduled email deliveries.
  • Real-Time Data: Instead of manually exporting & importing data, you can automate your reports to display graphs & charts based on real-time data.
  • Easy Integrations: Seamlessly connect to Multiple data sources such as Google Ads, Google Analytics, Google Search Console, Sheets, etc all within a single dashboard.
  • Data Customization: Google Data Studio’s filter tools allow you to organize and refine your data by applying filters such as date range, account, campaign, location, etc. You can also apply these filters at the report level, page level, or chart level. Similar to an excel spreadsheet, you can create calculated fields based on formulas and conditions.

What is Microsoft Azure?

Data Studio Azure - Microsoft Azure Logo
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Microsoft Azure is a public Cloud Computing platform that allows you to access and manage Microsoft’s cloud services and resources. The cloud service includes best-in-class computation, Data Analytics, Storage, networking, IoT, migration, artificial intelligence, and other machine learning, integration, management tools, developer tools, security, databases, DevOps, media identity, and web services. For instance, Microsoft Azure SQL Database is completely managed PaaS(Platform as a Service) offering continuous upgrading, patching, backups, and monitoring of the database.

Key Features of Microsoft Azure

  • Improved Backup & Data Recovery: Azure allows you to back your data from any language or operating system & also lets you decide the frequency of the data backup cycle. As a preventive measure, Azure stores 3 copies of your in 3 different places as well as three separate copies in a remote Azure data center.  
  • Manageability: Features such as Automatic Patch Management for virtual machines allow you to focus on your core objectives. Azure scales automatically as your business scales, thereby providing a seamless experience.
  • Analytics Capabilities: Cortana Analytics, Stream Analytics, Machine Learning, and SQL services are some of the brilliant analytics tools provided by Azure to assist you in discovering new business opportunities, improving customer service, and making informed decisions.
  • Flexibility: Microsft Azure allows you to work with multiple programming languages, including Java, Node Js, and C#. After developing your applications, Azure also provides a platform to test and deploy them.

Why set up the Google Data Studio Azure connection?

Google Data Studio is powerful Data Visualization and Analytics tool for creating visually stunning dashboards and reports. The refined and transformed data in Google Data Studio is often required for better Operational Analytics. By setting up the Google Data studio Azure Connection, you can improve the user experience in real-time. You may also want to merge the data from Google Data Studio to your Azure SQL Database Tables for more a consolidated view.

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Steps to Establish Google Data Studio Azure Connection

Currently, there is no direct method to establish a connection between Google Data Studio Azure connection. However, you can export your Google Data Studio data in an Excel file and then import the Excel file into your Microsoft Azure SQL Database. You easily achieve this following the 2 simple Google Data Studio Azure Connection steps given below:

Google Data Studio Azure Connection Step 1: Export Data from Google Data Studio to CSV

To export data from your Google Data Studio chart for initiating the Google Data Studio Azure Connection, follow these easy steps:

  • Step 1: Go to your report and hover over the chart from which you want the data.
  • Step 2:  Now, either you can right-click on the chart or click on the ⠇option and then select the Export option.
  • Step 3: Type in the name for your export file and choose CSV as your Export As option. By selecting this format, Google Data Studio can now create a comma-separated text file. You can also select the Google Sheets option that directly sends your data to Google Sheets and from there you can download it as a CSV file. You can choose the CSV(Excel) file, however, you would need to later convert it to a CSV file as Azure SQL Database doesn’t accept imports via an Excel file.
Data Studio Azure - Export options
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  • Step 4: To ensure that the number and date formats applied in Data Studio are retained in the exported data, you can choose the Keep Value Formatting option. This concludes the CSV export step of the Google Data Studio Azure Connection. 

Note that instead of saving the image of the chart, Google Data Studio only exports the data in the format you have chosen. Available in the View mode, Data export is applicable on individual charts. When trying to export data from a chart, all the existing filters, date range controls, or Google Analytics segments will also be applied to the exported data. 

Google Data Studio Azure Connection Step 2: Import Data from CSV to Microsoft Azure SQL Database

Microsoft Azure SQL Database doesn’t allow you to directly import data from an excel file. Hence, if you have an existing Excel spreadsheet then first save its copy as a CSV file. There are several ways to import data from a CSV file to your Microsoft Azure SQL Database such as Transact-SQL OPENROWSET or OPENDATASOURCE functions, BULK INSERT command, BCP tools, etc. 

For a more user-friendly experience, you can use the Import Flat File Wizard doesn’t require you to have any programming language knowledge. To use that, ensure that you have the SQL Server Management Studio (SSMS) v17.3 or later installed on your system. To complete the Google Data Studio Azure connection, follow these easy steps:

  • Step 1: Go to SQL Server Management Studio & connect to an instance of the SQL Server Database Engine or localhost.
  • Step 2: On the left-hand side Object Explorer vertical menu, navigate to Databases and right-click on your desired database(Test is the sample database for this article). Now go to Tasks > Import Flat File.
Data Studio Azure - Import Flat File option
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  • Step 3: Now, the Import Flat File “Database Name” ( Import Flat File “Test” ) dialog box will pop up on your screen. Click on the Next button to move on from the introduction page.
Data Studio Azure - Import Flat File Intro Page
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  • Step 4: Click on the Browse button and select the CSV file you want to import. Specify the name of the new table. Note that the Import wizard won’t go to the next step if the name of the table is not unique. Once done, click on the Next button.
Data Studio Azure - Import Flat File Add File Location
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  • Step 5: Now, you see the preview of the table and verify if it is read correctly. Click on the Next button.  
Data Studio Azure - Import Flat File Preview Data
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  • Step 6: The import wizard checks your column names, data types, etc, and also allows you to modify your columns. For example, you can check “Allows Nulls” for the columns which you believe can be empty.  After verifying and making the necessary changes, click on the Next button. 
Data Studio Azure - Import Flat File Modify Columns
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  • Step 7: A summary of all the configuration settings will be displayed. Click on the Finish button to complete the Google Data Studio Azure connection.
Data Studio Azure - Import Flat File Summary Page
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After a successful Google Data Studio Azure connection, you will see the result as Success for the insert data operation,

Data Studio Azure - Import Flat File Result Page
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Conclusion

In this article, you have learned how to effectively set up the Google Data Studio Azure SQL Database connection in 2 easy steps. Since there is no direct method for the Google Data Studio Azure SQL Database connection, you have to first import the data from Google Data Studio in a CSV file and import it Azure. There are several ways to load data from CSV files to Azure SQL Database such as BULK INSERT command, BCP tools, etc. To simplify this process, you can use the Import Flat File Wizard which doesn’t require any technical knowledge.

As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for complete performance analysis of your business. However, it is a time-consuming and resource-intensive task to continuously monitor the Data Connectors. To achieve this efficiently, you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse, BI Tool, or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.   

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Tell us about your experience of setting up the Google Data Studio Azure SQL Database Connection! Share your thoughts with us in the comments section below.

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