Google Data Studio is an easy tool for the creation of visually appealing dashboards. If you have data that you need to analyze, you can choose Google Data Studio as your data analysis tool. It will allow you to visualize data using different tools and extract insights from it for sound decision making.
Initially, one of the greatest disadvantages of Google Data Studio was its inability to combine multiple data sources in a single visualization. However, it changed after Google Data Studio introduced the data blending feature.
In this article, you will learn how to combine multiple data sources in Google Data Studio in a single visualization using the data blending feature.
Prerequisites
This is what you need for this article:
- A Google Data Studio Account.
How to Use Google Data Studio?
Google Data Studio is a tool developed by Google for building dashboards and generating reports from data. The tool can be used to schedule and share reports with much ease. Data Studio can help you track KPIs (Key Performance Indicators) for clients, compare performance, and visualize trends over time. It can be seen as an advanced version of the Google Analytics dashboard, which comes with limited functionality.
Data Studio has hundreds of connectors that you can use to establish connections to different data sources. Data Studio gives you full control over your reports, with the ability to customize and add as many visuals as you wish. You also have the opportunity to choose the chart or visual that you want to use to present your data, including line charts, bar charts, and Google Maps.
Data Studio comes with both basic and advanced formulas for data analysis. You can use these formulas to transform your data the way you want and paint a great picture with your data. To use Data Studio, you should have a Data Studio account. If you already have a Google account that you use to access services like YouTube, Gmail, etc., then you are ready to go. You can log into your Data Studio account using that Google account.
Here are the steps to use Google Data Studio:
Step 1: To access Data Studio, use the link here. You will be prompted to log into your account. Log in using your Google account.
Step 2: You will be taken to the “Reports” page which is shown below:
The page shows sample reports that have been created using Data Studio. You can click on any of the reports to get an idea of how a Data Studio report looks like and the kind of data that you can add into your Data Studio reports.
Step 3: To create a new report, simply click the “+ Blank Report” button which is shown below:
Reports are created from the data.
Step 4: You will be prompted to add data to your report.
You will see the connectors that you can use to establish a connection to different data sources.
Step 5: If you have already loaded some data into Data Studio, and you need to use it to create the report, click the “My data sources” button.
You will see a list of data that you have loaded into your Data Studio account.
The above figure shows that the page has been organized into 3 columns. The first column shows the name of the data. The second column shows the owner of the data, and the third column shows the time, the data was created or last modified. The last two columns have filtering options provided in the form of a drop-down button. You can play around with these options and see how they work. You can also see the same when you click the “Data sources” button located next to the “Reports” button.
Step 6: When you click the “Explorers” button located next to the “Data sources” button, you will see the list of explorers available in your Data Studio account.
Step 7: To create a new explorer, simply click the “+ CREATE” button located at the top left corner of the window.
The left side of the window shows options in a navigation pane that you can use to filter the Reports, Data sources, and Explorers.
The “Shared with me” option shows the Reports, Data sources, or Explorers that have been shared with you. The “Owned by me” option shows the Reports, Data sources, or Explorers that you have created or the ones that you own. The “Trash” option shows the Reports, Data sources, or Explorers that have been deleted.
Let’s see why we need to integrate multiple data sources in Google Data Studio.
Why Integrate Multiple Data Sources in Google Data Studio?
Previously, to compare data from multiple data sources (like Google Analytics, Google Search Console, and Google AdWords), you had to create separate charts side by side. It has a limitation that the differences and similarities between the different data sources will not be depicted clearly. After the introduction of the data blending feature to integrate multiple data sources in Google Data Studio, it is now possible to combine these into one chart to have a clear view of the relationships between them.
There are different ways through which you can combine your data from multiple data sources in Google Data Studio.
Method 1: Combine Charts
It is the easiest way for you to combine multiple data sources in Google Data Studio. You can simply put the charts that you’ve created into one chart. It becomes a very useful approach when you’ve already created separate charts, and you want to bring them together.
To combine charts, follow the steps given below:
Step 1: Place the two charts that you want to blend side by side or just close to each other on the same report page.
Step 2: Select the two charts. You can hold down the “Ctrl” key when selecting them.
Step 3: Right click and choose “Blend data”.
A new chart will be created that contains data from all the widgets that you had selected.
You can then do a comparison between the charts on one chart.
Method 2: Combine Data from Resource Menu
You can combine multiple data sources in Google Data Studio using the “Resource” menu.
Follow the steps given below:
Step 1: Click the “Resource” menu from the menu bar, then choose “Manage blended data”.
Step 2: You will be taken to a new page. Click the “ADD A DATA VIEW” button.
Step 3: A new window will popup showing a video that takes you through the process of data blending. Click the “GET STARTED” button.
Step 4: Select either two or more data sources to be combined.
Step 5: Choose a join key. The join key should be common in all the selected data sources. Click the “SAVE” button.
Those are the two approaches that you can use to connect multiple data sources in Google Data Studio.
Limitations
The following are the limitations associated with integrating multiple data sources to Google Data Studio using data blending feature:
- You can only combine up to a maximum of 5 data sources in Data Studio. If you add a large number of graphs, data, and sources, then Data Studio will become very slow, especially after adding calculated metrics to your visuals.
- Data blending may also develop data accuracy issues. Information obtained from external sources may be imported or displayed incorrectly. That’s why it’s always good for you to first add the data into a table before you can turn your blended data into a visualization.
- Blended data sources only belong to the report in which they have been created. If you need to use the blended data source in another report, copy and paste the component with the blended data into your new report.
Conclusion
This is what you’ve done in this article:
- You’ve learned how to use Google Data Studio.
- You have learned how to connect multiple data sources in Google Data Studio by combining charts.
- You have learned how to connect multiple data sources in Google Data Studio from the “Resource” menu.
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Share your experience of connecting multiple data sources in Google Data Studio in the comment section below.
Nicholas Samuel is a technical writing specialist with a passion for data, having more than 14+ years of experience in the field. With his skills in data analysis, data visualization, and business intelligence, he has delivered over 200 blogs. In his early years as a systems software developer at Airtel Kenya, he developed applications, using Java, Android platform, and web applications with PHP. He also performed Oracle database backups, recovery operations, and performance tuning. Nicholas was also involved in projects that demanded in-depth knowledge of Unix system administration, specifically with HP-UX servers. Through his writing, he intends to share the hands-on experience he gained to make the lives of data practitioners better.