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Towards an Interdisciplinary Master’s Degree Programme in Big Data and Data Science: A South African Perspective

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ICT Education (SACLA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 642))

Abstract

Many businesses see Big Data and Data Science as a catalyst for innovation. The problem is that many of these businesses are hesitant to embrace these new technologies mainly because of a shortage in skilled manpower. On a global level, higher education institutions are in the process of developing curricula for graduate degree programs relating to Big Data and Data Science. Developing such curriculum has its own challenges. For example: What level of knowledge is required from disciplines such as Computing and Statistics? What underlying foundations in Mathematics are required? This paper presents a framework for the design of an interdisciplinary Big Data and Data Science curriculum on the Master’s level.

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Notes

  1. 1.

    ‘Data munging’ refers to mapping data from one form to another.

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Authors and Affiliations

  1. Department of Computer Science, University of Pretoria, Pretoria, South Africa

    Linda Marshall & Jan H. P. Eloff

Authors
  1. Linda Marshall
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  2. Jan H. P. Eloff
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Corresponding author

Correspondence to Linda Marshall .

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Editors and Affiliations

  1. Department of Computer Science, University of Pretoria, Pretoria, South Africa

    Stefan Gruner

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Marshall, L., Eloff, J.H.P. (2016). Towards an Interdisciplinary Master’s Degree Programme in Big Data and Data Science: A South African Perspective. In: Gruner, S. (eds) ICT Education. SACLA 2016. Communications in Computer and Information Science, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-47680-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-47680-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47679-7

  • Online ISBN: 978-3-319-47680-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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