Learning Google BigQuery: A beginner's guide to mining massive datasets through interactive analysis - Softcover

Haridass, Thirukkumaran; Brown, Eric

Softcover

ISBN 10: 1787288595 ISBN 13: 9781787288591

Publisher: Packt Publishing, 2017

Synopsis

Get a fundamental understanding of how Google BigQuery works by analyzing and querying large datasets

Key Features

• Get started with BigQuery API and write custom applications using it
• Learn how BigQuery API can be used for storing, managing, and querying massive datasets
• Learn everything you need to know about Google BigQuery

Book Description

Google BigQuery is a popular cloud data warehouse for large-scale data analytics. Learning Google BigQuery will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from on 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.

In the final chapters, you’ll explore tips, best practices, as well as 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.

What you will learn

• Get a hands-on introduction to Google Cloud Platform and its services
• Understand the different data types supported by Google BigQuery
• Migrate your enterprise data to BigQuery and query it using SQL techniques
• Use partition tables in your project and query external data sources and wild card tables
• Create tables and datasets dynamically using the BigQuery API
• Insert records for analytics using Python and C#
• Visualize your BigQuery data by connecting it to third-party tools such as Tableau and R
• Master the Google Cloud Pub/Sub to implement real-time reporting and analytics of your Big Data

Who This Book Is For

Learning Google BigQuery is for developers, data analysts, and data scientists looking to run complex queries over thousands of records in seconds. No prior experience of working with BigQuery is assumed.

Table of Contents

1. Google Cloud and Google BigQuery
2. Google Cloud SDK
3. Google BigQuery Data Types
4. BigQuery SQL Basic
5. BigQuery SQL Advanced
6. BigQuery API
7. Visualizing BigQuery Data
8. Google Cloud Pub Sub

About this title

About the Author

Thirukkumaran Haridass currently works as a lead software engineer at Builder Homesite Inc. in Austin, Texas, USA. He has over 15 years of experience in the IT industry. He has been working on the Google Cloud Platform for more than 3 years. Haridass is responsible for the big data initiatives in his organization that help the company and its customers realize the value of their data. He has played various roles in the IT industry and worked for Fortune 500 companies in various verticals, such as retail, e-commerce, banking, automotive, and presently, real estate online marketing.

Eric Brown currently works as an analytics manager for PMG advertising in Austin, Texas. Eric has over 11 years of experience in the data analytics field. He has been working on the Google Cloud Platform for over 3 years. He oversees client web analytics implementations and implements big data integrations in both Google BigQuery and Amazon Redshift. Eric has a passion for analytics, and especially for visualization and data manipulation through open source tools such as R. He has worked in various roles in various verticals, such as web analytics service providers, media companies, real-estate online marketing, and advertising.

Edition details

• Publisher: Packt Publishing
• Publication date: 2017
• ISBN 10: 1787288595
• ISBN 13: 9781787288591
• Binding: Paperback
• Language: English
• Number of pages: 264