Running a Query
Getting Data In
Getting Data Out

The course is part of these learning paths

Google Associate Cloud Engineer Exam Preparation (PREVIEW)
course-steps 8 certification 1 lab-steps 6
Google BigQuery
course-steps 3 certification 1 lab-steps 1 quiz-steps 1
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BigQuery is Google’s managed data warehouse in the cloud. BigQuery is incredibly fast. It can scan billions of rows in seconds. It’s also surprisingly inexpensive and easy to use. Querying terabytes of data costs only pennies and you only pay for what you use since there are no up-front costs.

This is a hands-on course where you can follow along with the demos using your own Google Cloud account or a trial account. You do not need any prior knowledge of Google Cloud Platform and the only pre-requisite is having some experience with databases.

Learning Objectives

  • Load data into BigQuery using files or by streaming one record at a time
  • Run a query using standard SQL and save your results to a table
  • Export data from BigQuery using Google Cloud Storage



Welcome to the Introduction to BigQuery course. I'm Guy Hummel, and I'll be showing you how to analyze huge amounts of data incredibly quickly.

Data warehouses have been around decades. When databases first became popular, they were primarily used for transaction processing, and that's still the case today. But managers also needed to analyze data and create reports, which is difficult to do when the data resides in numerous databases across an organization. So data warehouses were created to collect data from a wide variety of sources, and they were designed specifically for reporting and data analysis.

If data warehouse technology has been around for so long, why did Google release BigQuery? And, why would you use it instead of a more established data warehouse solution? Well for two main reasons, ease of implementation and speed.

First, building your own data warehouse can be expensive, time consuming, and difficult to scale. With BigQuery, on the other hand, the only thing you have to do to get started is load your data into it, and you only pay for what you use, so you don't need to spend a lot of money building capacity to handle peak periods.

Second, even if you do build your own high-performance data warehouse, it will probably never be as fast as BigQuery, because BigQuery can process billions of rows in seconds. This speed is especially valuable if you need to perform real-time analysis of streaming data, such as from online gaming systems, or Internet of Thing sensors.

To get the most from this course, it's helpful to have some experience with databases. It's also helpful to have some familiarity with writing queries using SQL, but it's not a requirement.

This is a hands-on course with lots of demonstrations. The best way to learn is by doing, so I recommend that you try performing these tasks yourself on your own Google Cloud account. If you don't have one, then you can sign up for a free trial.

We'll start by running some basic queries and then save the results. After that, I'll show you how to load data into BigQuery from files and from other Google services. Then you'll see how to stream data into BigQuery one record at a time. Finally, we'll wrap up with how to export data from BigQuery.

If you're ready to learn how to crunch big data with ease, then let's get started.

About the Author

Learning paths31

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).