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Learning Google BigQuery

You're reading from Learning Google BigQuery A beginner's guide to mining massive datasets through interactive analysis

Product type Paperback

Published in Dec 2017

Publisher Packt

ISBN-13 9781787288591

Length 264 pages

Edition 1st Edition

Languages

Python

Tools

BigQuery

Concepts

Database Administration

Authors (3):

Eric Brown

Thirukkumaran Haridass

Mikhail Berlyant

View More author details

Table of Contents (9) Chapters

Preface

1. Google Cloud and Google BigQuery FREE CHAPTER

2. Google Cloud SDK

3. Google BigQuery Data Types

4. BigQuery SQL Basic

5. BigQuery SQL Advanced

6. Google BigQuery API

7. Visualizing BigQuery Data

8. Google Cloud Pub/Sub

BigQuery SQL Advanced

This chapter explores advanced options in BigQuery SQL. It explains partition tables in BigQuery and how to query data from partition tables. Sharding of tables is explained as an option to store data across multiple tables to save on billing. Built-in functions are explained for various categories such as datetime, strings, numbers, and so on.

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Authors (3)

Berlyant

Berlyant

See other products by Berlyant

Haridass

Haridass

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.

See other products by Haridass

Brown

Brown

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.

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