Got big queries? We have big answers.
Forrester marveled that “BigQuery lets developers query petabytes in milliseconds” — which can be quite helpful, and affordable in the cloud when you’re renting resources only for a few minutes or hours at a time. Whether you’re an experienced data scientist interested in taking advantage of BigQuery’s compute power or a SQL novice, get hands-on training with the new BigQuery for Data Analysis quest.
Learn advanced topics like JSON, arrays, structs, and even machine learning within SQL in this twelve-step quest. If you’re less confident in Standard Querying Language than you’d like, you don’t have to miss out. There is an optional introduction lab (expanded upon below) to help you get on your feet re: query syntax.
Get your first look at some of our favorite labs:
Introduction to SQL for BigQuery and Cloud SQL — The journey to SQL fluency begins with a single step. In this introductory lab, you’ll learn how to write simple queries like SELECT, FROM, WHERE, which allows you to manipulate and edit data. You’ll also learn to export and store subsets of data into CSV files, and build a Cloud Storage bucket to keep them in.
Using the BigQuery Web UI — Do you hate storing and querying massive datasets without the right infrastructure and hardware? Of course you do! Luckily, BigQuery runs queries super fast thanks to Google’s processing power. This lab teaches you to load your data sets into BigQuery, and the time you’ll save frees you up to learn how to integrate third-party tools into BigQuery to visualize your data.
Troubleshooting Common SQL Errors with BigQuery — SQL isn’t perfect. When something doesn’t work quite right, you’ll troubleshoot the problem within the BigQuery database. This lab teaches you to use BigQuery’s code editor in order to troubleshoot common logical and syntactical errors.
People accumulate more data every day. It doesn’t matter if you need gigabytes, terabytes, or petabytes; BigQuery has no administrative charges or upfront payment. You don’t have manage the infrastructure or assign a database admin. You can just focus on what matters most, analyzing your data.
More fun with BigQuery: