Book Image

Learning Google BigQuery

By : Thirukkumaran Haridass, Mikhail Berlyant, Eric Brown
Book Image

Learning Google BigQuery

By: Thirukkumaran Haridass, Mikhail Berlyant, Eric Brown

Overview of this book

Google BigQuery is a popular cloud data warehouse for large-scale data analytics. This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data. You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. Then, you will be introduced to the Google BigQuery API and how it fits within in the framework of GCP. The book covers useful techniques to migrate your existing data from your enterprise to Google BigQuery, as well as readying and optimizing it for analysis. You will perform basic as well as advanced data querying using BigQuery, and connect the results to various third party tools for reporting and visualization purposes such as R and Tableau. If you're looking to implement real-time reporting of your streaming data running in your enterprise, this book will also help you. This book also provides tips, best practices and mistakes to avoid while working with Google BigQuery and services that interact with it. By the time you're done with it, you will have set a solid foundation in working with BigQuery to solve even the trickiest of data problems.
Table of Contents (9 chapters)
Free Chapter
Google Cloud and Google BigQuery

What this book covers

Chapter 1, Google Cloud and Google BigQuery, is a hands-on demo of App Engine, Cloud SQL, BigQuery, Cloud datastore, compute engine, and Google Cloud Storage.

Chapter 2, Google Cloud SDK, covers how to install and configure the Google Cloud SDK and use various utilities provided in the SDK to interact with App Engine, Cloud SQL, BigQuery, and Google Cloud Storage.

Chapter 3, BigQuery Data Types, illustrates various data types supported in Google BigQuery and how to migrate your data to BigQuery.

Chapter 4, BigQuery SQL Basic, covers how to query the data using both legacy SQL and standard SQL, and how to merge data from various tables using queries.

Chapter 5, BigQuery SQL Advanced, shows how to use partition tables in your project and query an external data source on Google Cloud (such as Google Cloud Storage) from within BigQuery. We cover querying of wild card tables, user-defined functions, views, and using nested and repeated types in our tables to support importing JSON data.

Chapter 6, Google BigQuery API, teaches you how to use BigQuery API to create tables and datasets dynamically. You learn to load data into BigQuery and perform streaming insert of records for real-time analytics using Python and C#. Permissions, users, and roles are covered in this chapter.

Chapter 7, Visualizing BigQuery Data, shows you how to visualize your data by connecting it to various frontend tools, such as Tableau and Google Data Studio. We write custom programs in R. 

Chapter 8, Google Cloud Pub/Sub, covers the use of the Cloud Pub/Sub messaging system to log messages from various applications and its use to implement real-time reporting and analytics. This chapter also covers Cloud Dataprep, which helps prepare the data for loading into BigQuery.