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Contribution to Book
Making sense out of big data - popular machine learning tools in business analytics
Big Data & Analytics for Business
  • Kuldeep Kumar, Bond University
  • Sukanto Bhattacharya, Deakin University
Date of this Version
1-1-2014
Document Type
Book Chapter
Publication Details

Citation only

Kumar, K., & Bhattacharya, S. (2014). Making sense out of big data - popular machine learning tools in business analytics. In V. Kumar & S. Mittal (Eds.), Big Data & Analytics for Business (pp. 81-85). Haryana, India: Society for Education & Research Development.

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© Copyright, Society for Education & Research Development, 2014

2014 HERDC submission.

ISBN
978-1-63415-497-0
Abstract

'Big data' is the new buzzword in academic as well as industry circles. Laney (2001) came up with the three Vs that characterize big data - volume, velocity and variety. When talking about big data one is usually referring to a huge volume, in terabytes rather than gigabytes, that is captured either across cross-section or across time or more likely across both i.e. as a panel. However it is the sheer size of the data set that puts big data in an entirely different category requiring a special set of analytical tools and approaches for extracting information and also data storage for future retrieval and analysis.

Citation Information
Kuldeep Kumar and Sukanto Bhattacharya. "Making sense out of big data - popular machine learning tools in business analytics" Haryana, IndiaBig Data & Analytics for Business (2014) p. 81 - 85
Available at: http://works.bepress.com/kuldeep_kumar/58/