A systematic literature review of data governance and cloud data governance

Abstract

Data management solutions on their own are becoming very expensive and not able to cope with the reality of everlasting data complexity. Businesses have grown more sophisticated in their use of data, which drives new demands that require different ways to handle this data. Forward-thinking organizations believe that the only way to solve the data problem will be the implementation of an effective data governance. Attempts in governing data failed before, as they were driven by IT, and affected by rigid processes and fragmented activities carried out on system by system basis. Up to very recently governance is mostly informal with very ambiguous and generic regulations, in siloes around specific enterprise repositories, lacking structure and the wider support of the organization. Despite its highly recognized importance, the area of data governance is still under developed and under researched. Since data governance is still under researched, there is need to advance research in data governance in order to deepen practice. Currently, what exist are mostly descriptive literature reviews in the area of data governance. In this paper, a systematic literature review (SLR), which offers a structured, methodical, and rigorous approach to the understanding of the state-of-the-art of research in data governance. The objective of the study is to provide a credible intellectual guide for upcoming researchers in data governance to help them identify areas in data governance research where they can make the most impact. The systematic literature review covered published contributions from both academia and industry. The presented SLR searches and examines most relevant published work since year 2000 to-date for data governance for non-cloud, and for cloud computing since 2007. Only 52 studies met the inclusion criteria, which are critically reviewed.