Analytics in the Cloud

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


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.


  1. 1.
  2. 2.
    Domo, marketing data company’s 5th annual “Data Never Sleeps” infographics, 2017.Google Scholar
  3. 3.
  4. 4.
  5. 5.
    Amazon Elastic Map-Reduce:
  6. 6.
    Kouloumpis, E., et al. (2011). Twitter sentiment analysis: The good, the bad and the OMG! Processings of the fifth international AAAI conference on Weblogs and Social Media, pp. 538–541.Google Scholar
  7. 7.
  8. 8.
  9. 9.
    McCue, T. J. (2015, April). $117 billion market for Internet of things in healthcare by 2020, forbes,
  10. 10.
    Schneider, S. (2015, January). How the industrial internet of things can save 50,000 lives a year. Industrial Internet Consortium,
  11. 11.
    Hossain, M. S., & Muhammad, G. (2016). Cloud-assisted Industrial Internet of Things (IIoT) – Enabled framework for health monitoring. Computer Networks, 101, 192.
  12. 12.
  13. 13.
    Benetia, I., et al. (2016, January). Implementing a cloud-based decision support system in a private cloud. International Journal of Decision Support System Technology, 8(1), 25–42. Scholar
  14. 14.
  15. 15.
  16. 16.
  17. 17.
  18. 18.

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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