Learning Google BigQuery: A beginner's guide to mining massive datasets through interactive analysis

Learning Google BigQuery: A beginner’s guide to mining massive datasets through interactive analysis

Author: Thirukkumaran Haridass – Eric Brown
ISBN-10 书号: 1787288595
ISBN-13 书号: 9781787288591
Release Finelybook 出版日期: 2017-12-22
pages 页数: 264

$34.99


Book Description to Finelybook sorting

Google BigQuery is a popular cloud data warehouse for large-scale data analytics. This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data.
You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. Then, you will be introduced to the Google BigQuery API and how it fits within in the framework of GCP. The book covers useful techniques to migrate your existing data from your enterprise to Google BigQuery, as well as readying and optimizing it for analysis. You will perform basic as well as advanced data querying using BigQuery, and connect the results to various third party tools for reporting and visualization purposes such as R and Tableau. If you’re looking to implement real-time reporting of your streaming data running in your enterprise, this book will also help you.
This book also provides tips, best practices and mistakes to avoid while working with Google BigQuery and services that interact with it. By the time you’re done with it, you will have set a solid foundation in working with BigQuery to solve even the trickiest of data problems.
Contents
1: GOOGLE CLOUD AND GOOGLE BIGQUERY
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 You Will Learn
Get a hands-on introduction to Google Cloud Platform and its services
Understand the different data types supported by Google BigQuery
Migrate your enterprise data to BigQuery and query it using the legacy and standard SQL techniques
Use partition tables in your project and query external data sources and wild card tables
Create tables and data sets dynamically using the BigQuery API
Perform real-time inserting of records for analytics using Python and C#
Visualize your BigQuery data by connecting it to third party tools such as Tableau and R
Master the Google Cloud Pub/Sub for implementing real-time reporting and analytics of your Big Data
Authors
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.
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.

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Learning Google BigQuery
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