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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

Enterprise Data Science

We have thus far discussed various topics regarding both data mining and machine learning. Most of the examples shown were designed so that anyone with a standard computer would be able to run them and complete the exercises. In real-world situations, datasets would be much larger than those encountered in general home use.

Traditionally, we have relied on well-known database technologies such as SQL Server, Oracle, and others for organizational data warehouse and data management. The advent of NoSQL and Hadoop-based solutions made a significant change to this model of operation. Although companies were at first reluctant, the popular appeal of these tools became too large to ignore, and today, most, if not all, large organizations leverage one or more non-traditional contemporary solution for their enterprise data requirements.

Furthermore, the advent...

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