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Hadoop and Risk Analytics

Pankesh Bamotra, Saira Banu J. Published in Distributed Processing

International Journal of Applied Information Systems
Year of Publication: 2013
© 2012 by IJAIS Journal
10.5120/ijais13-450942
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  1. Pankesh Bamotra and Saira Banu J.. Article: Hadoop and Risk Analytics. International Journal of Applied Information Systems 5(7):38-40, May 2013. BibTeX

    @article{key:article,
    	author = "Pankesh Bamotra and Saira Banu J.",
    	title = "Article: Hadoop and Risk Analytics",
    	journal = "International Journal of Applied Information Systems",
    	year = 2013,
    	volume = 5,
    	number = 7,
    	pages = "38-40",
    	month = "May",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

This paper brings out the specific use case of Hadoop in risk analytics which forms an important part of every organization. Risk analytics is necessary because from business perspective, business leaders in any organization run into one or other kind of risk. They need to add value proposition to any kind of risk they take on behalf of the organization. But how to assess that risk is a big challenge in today's world. This is because of volume, veracity, velocity and variety of data that need to be analyzed is growing on an ever-increasing scale. This ultimately leads to vulnerability. Every day several petabytes of information is being stored, logged and analyzed, thus putting a bottleneck in the use of traditional RDBMS for real-time analytics. Here is when Hadoop comes as a savior. The paper talks about what Hadoop is, its programming paradigm called MapReduce, how is Hadoop different from traditional RDBMS, the technologies built on top of Hadoop, when to choose and not to choose Hadoop, its limitations and future scope. The use case of Hadoop with respect to risk analytics and that too particular to e-payments industry is also discussed.

Reference

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Keywords

Big Data, Hadoop, Risk analysis, RDBMS