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Analytics in the Cloud

  • Naresh Kumar Sehgal
  • Pramod Chandra P. Bhatt
  • John M. Acken
Chapter

Abstract

The sheer volume of information available on Cloud, and the rate at which new data is being generated, is overwhelming the capacity of enterprises to manage it and people to use it in a meaningful manner. We examine a typical day in the life of the Internet. Such a data deluge has surpassed the capacity of existing data centers to store and process it in a timely manner. This gave rise to a new class of algorithms, such as MapReduce, which we shall study in a later section.

In this chapter, we will introduce MapReduce and Hadoop and give examples of Amazon’s MapReduce (AMR). A class project of Twitter sentimental analysis using cloud is presented, which was able to predict the outcome of 2016 US Presidential Elections a full year in advance. Then we look at IoT-driven analytics in Cloud with a healthcare application, real-time decision-making support systems, and machine learning in a public cloud.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Naresh Kumar Sehgal
    • 1
  • Pramod Chandra P. Bhatt
    • 2
  • John M. Acken
    • 3
  1. 1.Data Center GroupIntel CorporationSanta ClaraUSA
  2. 2.Computer Science and Information Technology ConsultantRetd. Prof. IIT DelhiBangaloreIndia
  3. 3.Electrical and Computer EngineeringPortland State UniversityPortlandUSA

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