Google BigQuery Analytics

Chapter 2BigQuery Fundamentals

This chapter introduces you to BigQuery, describing what it can do, when to use it, when not to use it, and even a bit about why it is so fast. Because you may be evaluating whether BigQuery is the right tool for you, this chapter spends a bit of time comparing it to other systems and other architectures. It discusses the performance and types of workloads best-suited to BigQuery, and also how BigQuery fits with other offerings in the Google Cloud Platform.

This chapter concludes with an introduction to an AppEngine and Android App that is used as the basis of many of the examples throughout the book. This sample app demonstrates several ways that BigQuery can be integrated into an application—from log collection and analyses to dashboard development and correlation of multiple data streams.

What Is BigQuery?

BigQuery, like many tools, started with a problem. Google engineers were having a hard time keeping up with the growth of their data. The number of Gmail users is in the hundreds of millions; by 2012, there were more than 100 billion Google searches done every month. Trying to make sense of all this data was a time-consuming and frustrating experience.

Google is hugely a data-driven company. Decisions ranging from café menus to interview strategies to marketing campaigns are made by analyzing data. If you have a great idea but you don't have data to back it up, you're going to have a hard time convincing anyone to implement your suggestion. ...