Tools and technologies for the implementation of Big Data.

Book chapter


Self, Richard and Voorhis, Dave 2015. Tools and technologies for the implementation of Big Data. in: Elsevier.
AuthorsSelf, Richard and Voorhis, Dave
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.

KeywordsData protection; Governance; Big Data analytics
Year2015
PublisherElsevier
ISBN9780128019672
Digital Object Identifier (DOI)https://doi.org/10.1016/B978-0-12-801967-2.00010-0
Web address (URL)http://hdl.handle.net/10545/622362
hdl:10545/622362
File
File Access Level
Open
Publication dates27 Feb 2015
Publication process dates
Deposited16 Mar 2018, 13:56
ContributorsUniversity of Derby
Permalink -

https://repository.derby.ac.uk/item/93y07/tools-and-technologies-for-the-implementation-of-big-data

Download files


File
license.txt
File access level: Open

  • 59
    total views
  • 0
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Rel: The 'true' relational model for desktop data processing.
Voorhis, Dave 2017. Rel: The 'true' relational model for desktop data processing. University of Derby.
Ensemble of ESA/AATSR aerosol optical depth products based on the likelihood estimate method with uncertainties
Xie, Yanqing, Xue, Yong, Che, Yahui, Guang, Jie, Mei, Linlu, Voorhis, Dave, Fan, Cheng, She, Lu and Xu, Hui 2017. Ensemble of ESA/AATSR aerosol optical depth products based on the likelihood estimate method with uncertainties. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2017.2757910
Smart device location services:- A reliable analytics resource?
Self, Richard 2015. Smart device location services:- A reliable analytics resource?
Students as research partners
Self, Richard 2015. Students as research partners.
Optimising student achievement in Collaborative Partnerships
Self, Richard 2015. Optimising student achievement in Collaborative Partnerships.
Location based services analytics: Students as co-producers and partners in research
Self, Richard 2015. Location based services analytics: Students as co-producers and partners in research.
The governance impact of Big Data and the Internet of Things on the practice of knowledge management in organisations
Self, Richard 2015. The governance impact of Big Data and the Internet of Things on the practice of knowledge management in organisations.
Students learning software programming: Innovative strategies for learning and assessment
Self, Richard 2016. Students learning software programming: Innovative strategies for learning and assessment. Higher Education Academy (HEA).
Inspiring undergraduates to high achievement in STEM (and other) subjects
Self, Richard 2016. Inspiring undergraduates to high achievement in STEM (and other) subjects.
Assessing undergraduate and postgraduate hard and soft skills in analytics and data science courses
Self, Richard 2016. Assessing undergraduate and postgraduate hard and soft skills in analytics and data science courses. SAS Inc..
Giving effective academic presentations
Self, Richard 2016. Giving effective academic presentations.
Learning to program using immersive approaches: A case study learning SAS®, IBM Bluemix and Watson Analytics
Self, Richard 2016. Learning to program using immersive approaches: A case study learning SAS®, IBM Bluemix and Watson Analytics. Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-472-3
Facilitating soft skill excellence in STEM subjects leads to outstanding achievements
Self, Richard 2016. Facilitating soft skill excellence in STEM subjects leads to outstanding achievements. University of Derby.
Governance strategies for the cloud, Big Data, and other technologies in education
Self, Richard 2014. Governance strategies for the cloud, Big Data, and other technologies in education. IEEE. https://doi.org/10.1109/UCC.2014.101
Policy development and implementation in the Bretton Woods institutions: A consideration of the legality, human right impact and effectiveness of their programmes
Self, Richard 2011. Policy development and implementation in the Bretton Woods institutions: A consideration of the legality, human right impact and effectiveness of their programmes. International Journal of Arts and Sciences.
Rel
Voorhis, Dave 2016. Rel.
From DOOM to duty: The evolution of design patterns in first person shooters
Voorhis, Dave and Thompson, Tommy 2016. From DOOM to duty: The evolution of design patterns in first person shooters. Digital Games Research Association.
Big Data applications: Making them deliver value
Self, Richard 2016. Big Data applications: Making them deliver value.
Big Data applications: Making them deliver value
Self, Richard 2016. Big Data applications: Making them deliver value. TEST Magazine.
Big data analytics: a threat or an opportunity for Knowledge Management?
Self, Richard and Crane, Lesley 2014. Big data analytics: a threat or an opportunity for Knowledge Management? in: Springer Verlag.
Outstanding student achievement: A journey of pedagogy informed and confirmed by analytics
Self, Richard 2016. Outstanding student achievement: A journey of pedagogy informed and confirmed by analytics. in: IGI.
Tools and technologies for the implementation of Big Data
Self, Richard and Voorhis, Dave 2015. Tools and technologies for the implementation of Big Data. in: Butterworth-Heinemann.
Rel
Voorhis, Dave 2004. Rel.
Planning in the Cloud: Massively Parallel Planning
Voorhis, Dave and Thompson, Tommy 2014. Planning in the Cloud: Massively Parallel Planning. IEEE Computer Society. https://doi.org/10.1109/UCC.2014.67
Designing Big Data Analytics Undergraduate and Postgraduate Programmes for Employability
Self, Richard and Voorhis, Dave 2014. Designing Big Data Analytics Undergraduate and Postgraduate Programmes for Employability.
Novel Approaches to Learning and Teaching SAS-based Analytics
Self, Richard and Voorhis, Dave 2013. Novel Approaches to Learning and Teaching SAS-based Analytics. BDA EdCon.
Feature Selection in the Corrected KDD-dataset
Zargari, Shahrzad A. and Voorhis, Dave 2012. Feature Selection in the Corrected KDD-dataset. IEEE Computer Society.