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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
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Authors (3):
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Eric Brown Eric Brown
Author Profile Icon Eric Brown
Eric Brown
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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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Thirukkumaran Haridass Thirukkumaran Haridass
Author Profile Icon Thirukkumaran Haridass
Thirukkumaran 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.
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Mikhail Berlyant Mikhail Berlyant
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Mikhail Berlyant
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Table of Contents (9) Chapters Close

Preface 1. Google Cloud and Google BigQuery 2. Google Cloud SDK FREE CHAPTER 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

Google BigQuery API

This chapter will explore the Google BigQuery API. The API methods explored in this chapter will provide an idea of how to:

  • Create a new dataset in a project
  • Create new tables in the dataset
  • Load data to the table from files in the Google Cloud Storage location
  • Execute a query and get its results or save the results of the query to a new table

This chapter also introduces Google APIs Explorer, to help users understand the API methods used in this chapter deeply so that it can used in other programming languages. This chapter has code samples for accessing the BigQuery API via C# .NET and Python programming languages. 

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Authors (3)

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Profile icon 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.
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