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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

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781787288591
Length 264 pages
Edition 1st Edition
Languages
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Authors (3):
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Eric Brown Eric Brown
Author Profile Icon Eric Brown
Eric Brown
Thirukkumaran Haridass Thirukkumaran Haridass
Author Profile Icon Thirukkumaran Haridass
Thirukkumaran Haridass
Mikhail Berlyant Mikhail Berlyant
Author Profile Icon Mikhail Berlyant
Mikhail Berlyant
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Toc

Table of Contents (9) Chapters Close

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

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.

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