A Data Governance framework and a roadmap for practical implementation

• Main Author: Freire, Carolina Djovana da Silveira
• Publication Date: 2024
• Format: Master thesis
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10400.26/53862
• topic: Data governance; Framework; Implementation roadmap; critical success factors; Design science research

Businesses have increasingly adapted to the fact that data serves as an asset that adds value to the trade. To deal with the growing complexity of data in the digital age, authors highlight the importance of Data Governance. Despite not having a single definitive description in the literature, Data Governance is broadly referred to as the exercise of authority and control over the management of data, encompassing planning, monitoring, and enforcement. Anova, an Industrial Internet of Things company, felt the need to develop a Data Governance solution to support the challenges related to the management of their data, especially regarding lack of undefined roles and responsibilities, lack of defined policies and processes, lack of stakeholder knowledge on Data Governance and low data quality. The objective of this dissertation was the development of a Data Governance framework and implementation roadmap for Anova, through a Design Science Research approach. This methodology is made up of six phases, which involve problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication of the artifact. Each of these phases has been successfully completed. The design and development followed literature directions that proved to be more suitable for Anova's case. Focusing on a firm-wide approach aiming to develop a data quality strategy, first the formal structure, governance bodies, and accountabilities were arranged, defining roles, responsibilities and the allocation of decision-making authority; followed by procedural mechanisms such as data strategy, policies, standards, processes and procedures; and lastly, the description of the tools that facilitate the cooperation between stakeholders. With the framework at hand, it was possible to elaborate an implementation roadmap tailored to Anova's specific context. During the demonstration and evaluation phases of the Design Science Research methodology, it was possible for Anova to assess the contribution of the artifact within the company. The artifact building process has already proven to be useful for the company, as it served as an evaluator of its current state and has had a positive impact on creating awareness of data-related issues within the company. Although the company does not plan on implementing the framework yet, this dissertation is intended to serve as a basis for future application.