Using Data Studio
The course is part of these learning paths
Google Data Studio is a web-based application for creating reports and dashboards. It’s an easy-to-use tool for displaying your data visually. It was designed to help Google Analytics users create custom reports, but it can now read data from many sources, including BigQuery, Cloud SQL, and Cloud Storage.
In this course, you will learn how to connect a Data Studio report to a BigQuery dataset, visualize it with charts and graphs, and share it with your co-workers to make data-driven decisions.
- Create a report in Data Studio
- Connect a Data Studio report to a BigQuery dataset
- Share a Data Studio report with appropriate levels of access
- Explain the differences between Data Studio and Cloud Datalab
- Data professionals, especially those who work with big data
- People studying for the Google Professional Data Engineer exam
- “Introduction to Google BigQuery” course or experience with BigQuery
- Google Cloud Platform account (sign up for free trial at https://cloud.google.com/free if you don’t have an account)
This Course Includes
- 39 minutes of high-definition video
- Many hands-on demos
I hope you enjoyed learning about Google Data Studio. Let’s do a quick review of what you learned. A dimension is a data field that has a number of categories. A metric gives a measurement for each category in a dimension. You can reduce the amount of data displayed by using date ranges and filters.
Data Studio lets you connect to data in a variety of places, such as BigQuery and Google Analytics. When you create a connection to one of these places, that connection is called a data source. You have to add a data source to a report to use it.
Data Studio uses two levels of caching. It gets data from the query cache when you request the exact same query as a previous one. It gets data from the prefetch cache when it has correctly predicted what data you would request. You can disable the prefetch cache to save money, but you can’t disable the query cache. You can refresh both caches manually, though, by clicking the “Refresh data” button. You can only do this if you have editor access.
If you have more complex query requirements than Data Studio can handle on its own, then you can write a custom query. To see what queries Data Studio has run, you can look at the query history in the BigQuery console.
When you share a report, you can give people either view or edit access. Editors can change access for existing users and can even give access to other people. You can disable this for a particular report if you want. When you give out a shareable link, you can still restrict access to only people in your organization if you’d like.
If you set a data source to use owner’s credentials, then people who don’t have access to the underlying dataset can still see the data in your report, although they won’t have direct access to the dataset itself. If you want to restrict access to only those people who already have access to the underlying dataset, then you can set the data source to use viewer’s credentials.
You can use any shared report as a template by simply making a copy of it, although the person sharing the report can disable copying to prevent that.
Cloud Datalab is meant to be used for data science and machine learning. It lets you create Jupyter notebooks, which you can fill with documentation, code, and the results of executing the code. This can include data visualizations. But Datalab is much more difficult to use than Data Studio because you have to write code and because you have to spin up a VM to use it. Data Studio, on the other hand, is an easy-to-use, general-purpose reporting tool.
Now you know how to create a report in Data Studio, connect a Data Studio report to a BigQuery dataset, share a Data Studio report with appropriate levels of access, and explain the differences between Data Studio and Cloud Datalab.
To learn more about Data Studio, you can read Google’s documentation. Also watch for new big data courses on Cloud Academy, because we’re always publishing new courses.
If you have any questions or comments, please let me know in the Comments tab below this video or by emailing email@example.com. Thanks and keep on learning!
Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).