Tools and technologies for the implementation of Big Data.
| dc.contributor.author | Self, Richard | |
| dc.contributor.author | Voorhis, Dave | |
| dc.date.accessioned | 2018-03-16T13:56:20Z | |
| dc.date.available | 2018-03-16T13:56:20Z | |
| dc.date.issued | 2015-02-27 | |
| dc.identifier.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 | en |
| dc.identifier.isbn | 9780128019672 | |
| dc.identifier.doi | 10.1016/B978-0-12-801967-2.00010-0 | |
| dc.identifier.uri | http://hdl.handle.net/10545/622362 | |
| dc.description.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. | |
| dc.description.sponsorship | N/A | en |
| dc.language.iso | en | en |
| dc.publisher | Elsevier | en |
| dc.relation.url | https://www.sciencedirect.com/science/article/pii/B9780128019672000100 | en |
| dc.relation.url | https://www.sciencedirect.com/science/book/9780128019672 | en |
| dc.subject | Data protection | en |
| dc.subject | Governance | en |
| dc.subject | Big Data analytics | en |
| dc.title | Tools and technologies for the implementation of Big Data. | en |
| dc.type | Book chapter | en |
| dc.contributor.department | University of Derby | en |
| html.description.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. |
Files in this item
Name:
Publisher version