Identifying the Components of Data Governance in the Organizational Context: Metasynthesis of Texts

Document Type : Original Article

Authors

1 PhD. Student, Department of Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Professor, Department of Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, Iran

3 Assistant Professor, Department of Industrial Engineering, Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran

4 Associate Professor, Department of Knowledge and Information Science, Science and Research Branch, Islamic Azad University, Tehran, Iran.

5 Assistant Professor, Department of Knowledge and Information Science, Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran.

Abstract

Purpose: Data governance describes the processes for defining data policies within an organization, the processes that specify how these policies will be implemented, and establishing an organizational structure that includes data governance councils and data stewards to monitor and ensure compliance between policies and data. Data governance is a multifaceted management program, with its primary objective being to treat data as a valuable organizational asset. This is accomplished by utilizing a comprehensive framework of policies, standards, processes, personnel, and technology that are essential for effective data management. Many organizations face challenges in establishing a successful and sustainable data governance program. The initial step in enhancing the organization’s performance is to ensure that the data governance program aligns with its goals and mission. What currently exists as data governance is an abstract concept, and this abstraction hinders its effective implementation. Therefore, it is essential to first establish a clear and effective definition based on existing literature to facilitate its implementation by identifying the various components of this concept.
Method: This study analyzed the content of texts in the field of data governance using the meta-synthesis method. The selection of information sources was conducted purposefully, based on their relevance to the research objectives. The studies were conducted between 2000 and 2021. A total of 68 articles and theses related to this field were selected by searching reputable databases, including Emerald, Scopus, Sage, ProQuest, Springer, Web of Science, and Google Scholar. Additionally, searches were conducted in the Persian section of the Iranian Scientific Information and Documents Center, the National Library and Documentation Center of Iran, the National Publications Information Database (Iran Mag), the Humanities Portal, the Noor Specialized Magazines Database (Noormags), the Academic Jihad Scientific Information Center, and the APEC libraries of various universities,
such as Tehran University, Allameh Tabatabaei University, Al-Zahra University, Tarbiat Modares University, and Kharazmi University. Ultimately, the articles were purposefully selected based on the Sandusky and Barroso model and were reviewed using qualitative content analysis.
Findings: The research findings identified five main components of data governance: “planning,” “organization and management,” “performance,” “execution,” and “evaluation.” Each of these main components has subcomponents, resulting in a total of 32 components for data governance identified through a meta-synthesis of texts. These components significantly contribute to the definition and implementation of data governance across various organizations. According to the findings of this research, data governance encompasses planning, organizing, managing, determining performance, implementing, monitoring, and evaluating data related to different organizations. Data governance should align with the organization's mission, strategy, norms, and culture to effectively manage data as a strategic asset. It should ensure quality control and safeguard access, management, monitoring, and maintenance, with the goal of enhancing the value of the company’s data and transforming it into a competitive advantage.
Conclusion: By using these components, each organization can design and implement a data governance program appropriate to its context. Organizations with different expertise and contexts can modify these components according to their context adapt them to their goals and strategies, and benefit from the benefits of data governance in their organization. Regarding the application of the main and secondary components derived from the current research, organizations need to pay attention to the importance of each of them. Organizations must consider the goals and strategies of the program to implement data governance and design principles to support the structure, culture, and goals.

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Sciences and Techniques of Information Management
Volume 10, Issue 3
November 2024
Pages 101-130

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