Does your organization generate a huge amount of data every day? Does all of that data sit in a number of different databases, making it difficult to analyze? Even if you already have a data warehouse, can it keep up with your constantly growing volume of data? Google’s solution to these problems is Google BigQuery, a massive, lightning-fast data warehouse in the cloud.
This learning path will first show you the fundamentals of how to use BigQuery and then how to optimize BigQuery to reduce costs, speed up your queries, and apply proper access control.
- 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
- 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
So, if you’re interested in learning more about Google BigQuery, then click on the first course to get started!
- June 13, 2018 - Added Learning Path Exam
Learning Path Steps
Google BigQuery Quiz
Exam: Google BigQuery
- "Structure and Analyze Data with Google BigQuery" lab
- "Visualizing BigQuery Data with Google Data Studio" course
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).