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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

Ethical considerations


Big data often involves the gathering of large volumes of data that may contain users' personal information. Companies such as Facebook and Google have flourished on analyzing individual information to target ads and perform other types of marketing. This evidently poses an ethical dilemma. To what extent should personal data be collected? And how much is too much? There are, of course, no correct answers to these questions. The rise of hacking in which information from hundreds of millions of user accounts has been compromised is so commonplace today that we have almost become complacent about the consequences.

In October 2017, Yahoo! disclosed that 3 billion accounts, in fact every single account on Yahoo!, had suffered a data breach. Equifax, one of the largest credit reporting companies in the US suffered a data breach that exposed the personal details of more than 140 million consumers. There were scores of other similar incidents, and in all of them, the common...

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