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Big Data Analytics with Hadoop 3

You're reading from   Big Data Analytics with Hadoop 3 Build highly effective analytics solutions to gain valuable insight into your big data

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788628846
Length 482 pages
Edition 1st Edition
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Author (1):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Hadoop FREE CHAPTER 2. Overview of Big Data Analytics 3. Big Data Processing with MapReduce 4. Scientific Computing and Big Data Analysis with Python and Hadoop 5. Statistical Big Data Computing with R and Hadoop 6. Batch Analytics with Apache Spark 7. Real-Time Analytics with Apache Spark 8. Batch Analytics with Apache Flink 9. Stream Processing with Apache Flink 10. Visualizing Big Data 11. Introduction to Cloud Computing 12. Using Amazon Web Services

Introduction to big data

Twitter, Facebook, Amazon, Verizon, Macy's, and Whole Foods are all companies that run their business using data analytics and base many of the decisions on the analytics. Think about what kind of data they are collecting, how much data they might be collecting, and then how they might be using the data.

Let's look at the grocery store example seen earlier; what if the store starts expanding its business to set up hundreds of stores? Naturally, the sales transactions will have to be collected and stored at a scale hundreds of times more than the single store. But then, no business works independently any more. There is a lot of information out there, starting from local news, tweets, Yelp reviews, customer complaints, survey activities, competition from other stores, the changing demographics or economy of the local area, and so on. All such...

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