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You're reading from  Learning Google BigQuery

Product typeBook
Published inDec 2017
Reading LevelBeginner
PublisherPackt
ISBN-139781787288591
Edition1st Edition
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Authors (3):
Thirukkumaran Haridass
Thirukkumaran Haridass
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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.
Read more about Thirukkumaran Haridass

Eric Brown
Eric Brown
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Eric 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.
Read more about Eric Brown

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Sanitizing data

Most data warehousing projects follow a standard process. This process involves the extraction of data from a data source, the transformation of this data to both the standards of the data warehouse and the requirements of the end user, and the loading of data into the resulting database table. This process is more commonly known as the Extract, Transform, Load Process, or ETL for short.

The transformation step is important for a few reasons:

  • Decoding of encoded values (that is, converting values of W and E to West and East)
  • Calculation of values (that is, calculating the average order value by dividing the revenue by the count of orders)
  • Splitting separated lists into individual columns
  • Aggregation
  • Data validation, either in the form of invalidating incorrect values or as reprocessing of incorrect data

If you are using files to load data into BigQuery then...

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Learning Google BigQuery
Published in: Dec 2017Publisher: PacktISBN-13: 9781787288591

Authors (3)

author image
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.
Read more about Thirukkumaran Haridass

author image
Eric 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.
Read more about Eric Brown