Thirukkumaran Haridass - Learning Google BigQuery

BIRMINGHAM - MUMBAI

Copyright 2017 Packt Publishing

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First published: December 2017

Production reference: 1211217

ISBN 978-1-78728-859-1

www.packtpub.com

No one is more pleased than I am to see this book come to fruition. I first heard about this book during a water cooler conversation I was having with Thirukkumaran (Thiru) earlier this year. We were discussing ways to effectively store, process, and analyze millions of records of behavioral data captured daily over several years, then visualize that data in near real-time. Having seen the extensive, hands-on work Thiru and Eric have done with BigQuery, this book does not come to me as a surprise just a few months later.

Thiru started experimenting with BigQuery around the time it was first piloted by Google sometime in 2010. In subsequent years, as data, analysis, and reporting needs have grown, Thiru and Eric have instrumented world-class business intelligence and analytics platforms that have been robust, fast, scalable, and, most importantly, cost-effective for customers. We are taking and transforming large datasets with billions of records here.

Many of these big data transformations have been brownfield operations that involved modernizing clunky reporting systems that were once powered by cumbersome data management processes. This book seems to be the culmination of all this learning crystallized and put together in an easy-to-apply form.

This book should serve as a great resource for the novice developer or analyst that wants to get their feet wet, as well as the SME that is looking for a handbook for daily reference. Thiru and Eric go in-depth with some of the core concepts of BigQuery, such as schema design, query syntax, APIs, data preparation and loading, visualizations, and even billing! The book is also packed with valuable code samples and tips and tricks.

I highly recommend adding this book to your BigQuery development toolkit.

Praveen Guggarigoudar

Director, Risk Systems Development at Visa

Austin, TX

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.

MikhailBerlyant is a data warehousing veteran. He has been a data developer since the late '70s. Since 2000, he has led data systems, data mining, and data warehouse teams at Yahoo and Myspace.

Mikhail is currently a senior vice president, technology at Viant Inc. (a Time Inc. company), a people-based advertising technology company that enables marketers to plan, execute, and measure their digital media investments through a cloud-based platform. At Viant, Mikhail has led the migration of a petabytes-sized data warehouse to Google Cloud and currently is focusing on self-serve/productivity tools for BigQuery/Google Cloud Platform.

Mikhail is a data enthusiast and helps others as time allows. He is a Google developer expert (GCP, BigQuery). His Chrome extension for BigQuery (BigQuery Mate) was adopted in his company as well as across the world by BigQuery users with great feedback, including from Google and BigQuery in particular.