Data Governance on Data Platforms : Designing Playbook for Data Platforms

Abstract

The amount and value of data are increasing. Data can be seen as one of the key enterprise assets. Organizations have started to build data platforms to have the data from all sources available for use in cross-organization and cross-industry business ecosystems. The constraints with data are no longer the amount of data or the technology. It is the structures and processes. Data needs governing like any other enterprise asset. Data professionals interviewed for this research had rarely experienced successful data governance. The academic literature on data governance frameworks is fragmented and lacks holistic guidance on how data governance on data platforms should be designed, implemented, and monitored. This master’s thesis contributes to the lack of holistic guidance on designing data governance on data platforms through design science research. The research supports the theoretical framework and advances it with data analysis of 13 semi-structured interviews with data professionals. This research produces a canvas tool, Playbook for Data Platforms, to help people working with data design successful data governance in the data platform context. The canvas tool aims to increase data value and minimize the data-related cost and risk in the platform context. The research also considers how cloud data affects the data governance framework. As a result, 12 areas and 31 guiding questions are proposed to be included in the data governance framework on data platforms.