The need for an enterprise risk management framework for big data science projects

Jeffrey Saltz, Sucheta Lahiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This position paper explores the need for, and benefits of, a Big Data Science Enterprise Risk Management Framework (RMF). The paper highlights the need for an RMF for Big Data Science projects, as well as the gaps and deficiencies of current risk management frameworks in addressing Big Data Science project risks. Furthermore, via a systematic literature review, the paper notes a dearth of research which looks at risk management frameworks for Big Data Science projects. The paper also reviews other emerging technology domains, and notes the creation of enhanced risk management frameworks to address the new risks introduced due to that emerging technology. Finally, this paper charts a possible path forward to define a risk management framework for Big Data Science projects.

Original languageEnglish (US)
Title of host publicationDATA 2020 - Proceedings of the 9th International Conference on Data Science, Technology and Applications
EditorsSlimane Hammoudi, Christoph Quix, Jorge Bernardino
PublisherSciTePress
Pages268-274
Number of pages7
ISBN (Electronic)9789897584404
StatePublished - 2020
Event9th International Conference on Data Science, Technology and Applications, DATA 2020 - Virtual, Online, France
Duration: Jul 7 2020Jul 9 2020

Publication series

NameDATA 2020 - Proceedings of the 9th International Conference on Data Science, Technology and Applications

Conference

Conference9th International Conference on Data Science, Technology and Applications, DATA 2020
Country/TerritoryFrance
CityVirtual, Online
Period7/7/207/9/20

Keywords

  • Big data
  • Data science
  • Enterprise risk management (ERM)
  • Risk management framework (RMF)

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems
  • Software
  • Computer Networks and Communications

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