Data Governance Principles Research & Development Project

  • CIPIT
  • |  
  • August 21, 2021
  • |
  • Reports

Summary


Digitalisation has resulted in increased data collection which forms an integral role in various industries and day-to-day activities thus the need to ensure that the data is managed in a manner that not only protects the integrity and security of that data but the rights and interests of the organisations processing the data and the people whose data may form part of the data sets being processed. Consequently, processes and standards have been developed to ensure the management or governance of that data. As a result of digitisation and the large volumes of data being processed in the digital era and the interdisciplinary nature in which processes and standards need to be applied, there has been an increase in these data governance processes. The interdisciplinary nature of data governance and the three interrelated concepts—Data (Information) Management, Enterprise Information Management and Data (Information) Architecture—resulted in different terms being used to refer to data governance. In this Report we use the term ‘data governance’.


The objective of this research is to provide a baseline understanding of what data governance is, the principles and frameworks applied in the governance of data and examine how these principles and frameworks translate in the African context. We found that data governance encompasses legal and human rights requirements, technological, security and economical considerations. These aspects inform, not only how data is managed within an organisation but determines the principles that are considered is that governance and the frameworks that are developed. In light of this data governance can essentially be defined as the use of authority combined with policy to ensure the proper management of data assets.


We record and provide a number of principles for data governance that can be used by research to focus on important data governance issues and practitioners to develop an effective data governance strategy and approach.1 We therefore incorporate data governance sources from practitioners.

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