The course is part of these learning paths
BigQuery is Google's incredibly fast, secure, and surprisingly inexpensive data warehouse, but there are ways to make it even faster, cheaper, and more secure.
Here are some examples of what you will learn in this course:
- BigQuery can process billions of rows in seconds, but only if you break the rules of relational database design.
- If you are analyzing relatively small amounts of data, then your queries won’t cost very much, but if you regularly analyze huge datasets, then your costs can add up quickly. However, with a few adjustments to how you store your data in BigQuery, you can run queries for a fraction of the cost.
- To give you the flexibility to implement fine-grained security, BigQuery has several layers of access control capabilities, but they can be confusing, so I’ll show you which ones to use to meet your organization’s requirements.
This is a hands-on course where you can follow along with the demos using your own Google Cloud account or a trial account. If you don’t already have experience with BigQuery, then please take Introduction to Google BigQuery first.
- Reduce your BigQuery costs by reducing the amount of data processed by your queries
- Create, load, and query partitioned tables for daily time series data
- Speed up your queries by using denormalized data structures, with or without nested repeated fields
- Implement fine-grained access control using roles and authorized views
Welcome to the “Optimizing Google BigQuery” course. I’m Guy Hummel and I’ll be showing you how to get the most from this big data service.
BigQuery is an incredibly fast, secure, and surprisingly inexpensive data warehouse, but there are ways to make it even faster, cheaper, and more secure.
To get the most from this course, if you don’t already have experience with BigQuery, then please take my Introduction to BigQuery course first.
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 with how you can reduce the amount of data that’s processed by your queries, which will also lower your costs. Then we’ll go into more depth on partitioned tables, which is one method for reducing processing requirements.
Next, we’ll talk about ways to speed up your queries, including denormalizing your data structures and using nested and repeated fields.
Finally, we’ll wrap up with how to use roles and authorized views for access control.
If you’re ready to learn how to get the most out of BigQuery, then let’s get started.
About the Author
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).