Cloud governance is a new term in the IT field; however, it has not been given a clear definitionyet . Microsoft defines cloud governance as “defining policies around managing the factors: availability,security, privacy, location of cloud services and compliance and tracking for enforcing the policies at run timewhen the applications are running” . The core of cloud governance revolves around the relationshipsbetween provider and consumer, across different business models . The business model shoulddefine the way in which an offer is made and how it is consumed. To function at all cloud levels (IaaS,PaaS and SaaS), the business model should be devoid of the type of resources involved.The literature reported different views on what drives what within these governance domains; inour research, we argue that data governance should be the key driver for all other governance domains,sitting at the heart of everything. The most debated relationship among these governance domainshas been that of information governance and data governance, where numerous schools of thought,including the Data Governance Institute, have consistently used information and data governanceinterchangeably, connoting the understanding that the two terms mean the same thing.A veryrecent paper, published only in 2016, as part of the proceedings of the 28th Annual Conference of theSouthern African Institute of Management Scientists, presented a systematic analysis to prove that datagovernance is indeed a prerequisite for information governance, and hence the argument was extendedto state that data governance must become an ingrained part of both corporate governance and ITgovernance . Figure3provides an illustration of the advocated hierarchy of these governancedomains, showing also the difference between management and governance.
Sustainability2018,10, 958 of 26Figure 3.The hierarchy for the difference between management and governance.5. Data Governance TaxonomyTo construct a holistic taxonomy, we must determine the key dimensions of data governance.This adopted dimension-based approach allows for the categories in the taxonomy to be broken down intodiscrete areas. A dimension-based approach allows more flexibility in placing content into various nodes,represented by the dimension to which they belong. In the context of data governance, this approach willallow users to manage data governance content more efficiently. Successfully achieving this could bea potentially complex process, and consequently requires more investigative effort and the involvementof different stakeholders. Therefore, the taxonomy for data governance was developed followingexploratory and qualitative research, where the method employed was merrily based on a combinationof analysing the relevant knowledge in the public domain, resulting from the above describedsystematic literature review (Section3) and following the analytic theory .