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Big data and privacy : a modernised framework

Mini Dissertation (MBA)--University of Pretoria, 2017.

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Other Authors: Beney, Robert
Format: Thesis
Language:English
Published: University of Pretoria 2017
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access_status_str Open Access
author2 Beney, Robert
author_browse Beney, Robert
author_facet Beney, Robert
collection Thesis
dc_rights_str_mv © 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria.
description Mini Dissertation (MBA)--University of Pretoria, 2017.
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institution University of Pretoria (South Africa)
language English
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license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2017
publishDateRange 2017
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publisher University of Pretoria
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spelling oai:repository.up.ac.za:2263/59805 Big data and privacy : a modernised framework Beney, Robert ichelp@gibs.co.za Ainslie, Mandi UCTD Mini Dissertation (MBA)--University of Pretoria, 2017. Like the revolutions that preceded it, the Fourth Industrial Revolution has the potential to raise global income levels and improve the quality of life for populations around the world. Responding to global challenges, generating efficiencies, prediction improvement, democratisation access to information and empowering individuals are a few examples of the economic and social value created by personal information. However, this technological innovation, efficiency and productivity comes at a price -?privacy. As a result, individuals are growingly concerned that companies and governments are not protecting data about them and that they are instead using it in ways not necessarily in their best interests. The objective of this research is to investigate the validity and feasibility of a Personal Data Store (PDS) against the developed a priori framework. Ten qualitative, semi-?structured interviews using the long interview method were conducted with individuals identified as a subject matter expert (SMEs) in the Big Data analytics and the data privacy field. The findings show that the guiding principles of transparency, control, trust and value, ensures the validity and feasibility of the PDS. Furthermore, user-?centricity provides greater control within the Big Data continuum. However, as personal data should not be trusted in the hands of third-?parties, identity management and security must be entrenched at a foundational level of the model. The remaining elements -? selective disclosure, purpose and duration, signalling and data portability - is in fact value adding qualities that allows for the commodification of personal data. In the age of the Internet of Things (IoT), organisations churn out increasing volumes of transactional data, capturing trillions of bytes of information about their customers, suppliers and operations. However, amplifying the rate of technological disruption with the failure to provide safe spaces where individuals can think free, divergent and creative thoughts will significantly diminish the progress organisations (and society) can enjoy. ms2017 Gordon Institute of Business Science (GIBS) MBA Unrestricted 2017-04-07T13:05:45Z 2017-04-07T13:05:45Z 2017-03-30 2017 Mini Dissertation Ainslie, M 2017, Big data and privacy : a modernised framework, MBA Mini Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/59805> http://hdl.handle.net/2263/59805 en © 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Big data and privacy : a modernised framework
title Big data and privacy : a modernised framework
title_full Big data and privacy : a modernised framework
title_fullStr Big data and privacy : a modernised framework
title_full_unstemmed Big data and privacy : a modernised framework
title_short Big data and privacy : a modernised framework
title_sort big data and privacy a modernised framework
topic UCTD
url http://hdl.handle.net/2263/59805