Data governance & quality management—Innovation and breakthroughs across different fields
In today's rapidly evolving digital landscape, the substantial advance and rapid growth of data presents companies and their operations with a set of opportunities from different sources that can profoundly impact their competitiveness and success. The literature suggests that data can be considered a hidden weapon that fosters decision-making while determining a company's success in a rapidly changing market. Data are also used to support most organizational activities and decisions. As a result, information, effective data governance, and technology utilization will play a significant role in controlling and maximizing the value of enterprises. This article conducts an extensive methodological and systematic review of the data governance field, covering its key concepts, frameworks, and maturity assessment models. Our goal is to establish the current baseline of knowledge in this field while providing differentiated and unique insights, namely by exploring the relationship between data governance, data assurance, and digital forensics. By analyzing the existing literature, we seek to identify critical practices, challenges, and opportunities for improvement within the data governance discipline while providing organizations, practitioners, and scientists with the necessary knowledge and tools to guide them in the practical definition and application of data governance initiatives.
Authors
- Bruno Bernardo (ORCID: https://orcid.org/0000-0002-8581-5633)
- Vítor Santos (ORCID: https://orcid.org/0000-0002-4223-7079)
- Henrique São Mamede (ORCID: https://orcid.org/0000-0002-5383-9884)
- João Barroso (ORCID: https://orcid.org/0000-0003-4847-5104)
Institutions
- University of Trás-os-Montes and Alto Douro (PT)
- Universidade Aberta (PT)
- INESC TEC (PT)
- Universidade Nova de Lisboa (PT)
Publication Details
- Journal
- Journal of Innovation & Knowledge
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1016/j.jik.2024.100598
- Citations
- 47
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 23.05
Funders
- Fundação para a Ciência e a Tecnologia