Data Science Competency in Organisations: A Systematic Review and Unified Model

Abstract

The paper presents a systematic literature review of the literature on the competencies that are essential to develop a globally competitive workforce in the field of data science. The systematic review covers a wide range of literature but focuses primarily, but not exclusively, on the computing, information systems, management, and organisation science literature. The paper uses a broad research search strategy covering four separate electronic databases. The search strategy led the researchers to scan 139 titles, abstracts and keywords. Sixty potentially relevant articles were identified, of which 42 met the quality criteria and contributed to the analysis. A critical appraisal checklist assessed the validity of each empirical study. The researchers grouped the findings under six broad competency themes: organisational, technical, analytical, ethical and regulatory, cognitive and social. Thematic analysis was used to develop a unified model of data science competency based on the evidence of the findings. This model will be applied to case studies and survey research in future studies. A unified data science competency model, supported by empirical evidence, is crucial in closing the skills gap, thereby improving the quality and competitiveness of the South Africa's data science workforce. Researchers are encouraged to contribute to the further conceptual development of data science competency.