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.
What is Google Data Studio?
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?
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.
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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:
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 1.1: Go to your report and hover over the chart from which you want the data.
- Step 1.2: Now, either you can right-click on the chart or click on the ⠇option and then select the Export option.
- Step 1.3: Type in the name for your export file and choose CSV as your Export As option. You can choose the CSV(Excel) file; however, you would need to convert it to a CSV file later as Azure SQL Database doesn’t accept imports via an Excel file.
- Step 1.4: 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.
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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 2.1: Go to SQL Server Management Studio & connect to an instance of the SQL Server Database Engine or localhost.
- Step 2.2: On the left-hand side of the 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.
- Step 2.3: 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.
- Step 2.4: 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.
- Step 2.5: Now, you see the preview of the table and verify if it is read correctly. Click on the Next button.
- Step 2.6: 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.
- Step 2.7: A summary of all the configuration settings will be displayed. Click on the Finish button to complete the Google Data Studio Azure connection.
After a successful Google Data Studio Azure connection, you will see the result as Success for the insert data operation,
Use cases for Data Studio Azure Integration
Connecting Google Data Studio Azure is a powerful data solution. Here are a few simple use cases for how they can combine into a service:
Data Visualization for Azure Databases
Data can be kept inside the Azure services, like Azure SQL Database and Azure Blob Storage. That data one can connect with Google Data Studio for creating interactive dashboards and reports. This is also useful in turning complex data into easy-to-understand visuals.
Tracking of Azure Analytics
Azure offers numerous data processing and machine learning tools, such as Azure Data Factory or Azure Machine Learning. Leverage Google Data Studio in order to visualize performance metrics and results, keeping you updated on your operations.
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Business Reporting
Organizations that utilize Azure for cloud storage and computing can design reports in Data Studio on all sorts of business metrics, such as sales performance, customer engagement, or tracking financials, by drawing data from Azure.
Infrastructure Monitoring with Azure
You can take logs or metrics from Azure Monitor, which tracks the health and performance of cloud resources, and feed them into Google Data Studio to build customized dashboards showing the health of your servers, app performance, or resource utilization.
Marketing Analytics with Azure Data
Companies that keep customer data or the performance data of ads in Azure can connect this to Google Data Studio to deliver dashboards that enhance data visualization regarding marketing performance. This helps in making better decisions.
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 to Azure. There are several ways to load data from CSV files to Azure SQL Database, such as the BULK INSERT command and BCP tools. To simplify this process, you can use the Import Flat File Wizard, which doesn’t require any technical knowledge.
Check out how to sync data from Google Sheets to Azure Synapse for robust data integration and analysis.
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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.
FAQs
1. How is Azure SQL different from SQL Server?
Azure SQL is a cloud-based service that automates infrastructure
management tasks such as upgrading or monitoring databases. You
have to do these tasks manually while using the SQL Server. However,
you can deploy SQL Server on a cloud platform like Azure Infrastructure
as a Service (IaaS).
2. What is the difference between Azure Databricks and Azure Data Studio?
Azure Databricks is a cloud-based platform for big data analytics, enabling large-scale data processing and machine learning, whereas Azure Data Studio is a tool for managing and querying databases, focused on SQL development and database management, particularly for SQL Server and Azure SQL databases.
2. Do I need Azure Data Studio for SQL Server?
No, you don’t need it, but it’s a helpful tool for querying and managing SQL Server databases, providing features like rich query editing and data visualization.
Sanchit Agarwal is an Engineer turned Data Analyst with a passion for data, software architecture and AI. He leverages his diverse technical background and 2+ years of experience to write content. He has penned over 200 articles on data integration and infrastructures, driven by a desire to empower data practitioners with practical solutions for their everyday challenges.
