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    Tools and technologies for the implementation of Big Data.

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    Authors
    Self, Richard
    Voorhis, Dave
    Affiliation
    University of Derby
    Issue Date
    2015-02-27
    
    Metadata
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    Abstract
    This chapter uses the five V’s of Big Data (volume, velocity, variety, veracity, and value) to form the basis for consideration of the current status and issues relating to the introduction of Big Data analysis into organizations. The first three are critical to understanding the implications and consequences of available choices for the techniques, tools, and order to provide an understanding of choices that need to be made based on understanding the nature of the data sources and the content. All five V’s are invoked to evaluate some of the most critical issues involved in the choices made during the early stages of implementing a Big Data analytics project. Big Data analytics is a comparatively new field; as such, it is important to recognize that elements are currently well along the Gartner hype cycle into productive use. The concept of the planning fallacy is used with information technology project success reference class data created by the Standish Group to improve the success rates of Big Data projects. International Organization for Standardization 27002 provides a basis considering critical issues raised by data protection regimes in relation to the sources and locations of data and processing of Big Data.
    Citation
    Self, R. and Voorhis, D. (2015) 'Tools and technologies for the implementation of Big Data.' in Babak, A. et al (eds.) Application of Big Data for National Security: A Practitioner's Guide to Emerging Technologies, London: Elsevier, pp. 140-154
    Publisher
    Elsevier
    URI
    http://hdl.handle.net/10545/622362
    DOI
    10.1016/B978-0-12-801967-2.00010-0
    Additional Links
    https://www.sciencedirect.com/science/article/pii/B9780128019672000100
    https://www.sciencedirect.com/science/book/9780128019672
    Type
    Book chapter
    Language
    en
    ISBN
    9780128019672
    ae974a485f413a2113503eed53cd6c53
    10.1016/B978-0-12-801967-2.00010-0
    Scopus Count
    Collections
    Department of Electronics, Computing & Maths

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