Data governance
Searched over 200M research papers for "data governance"
Summary
10 papers analyzed
These studies suggest that data governance enhances data value, ensures compliance, and addresses challenges in data management across various sectors, though it remains an underdeveloped field requiring further research and practical implementation strategies.
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Introduction
Data governance refers to the exercise of authority and control over the management of data within an organization. It aims to increase the value of data while minimizing data-related costs and risks. Despite its growing importance, data governance remains an underdeveloped and under-researched area, necessitating a structured approach to guide both practitioners and researchers.
Key Insights
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Importance and Challenges of Data Governance:
- Data governance is crucial for ensuring data quality, compliance with regulations, and leveraging data as an asset .
- Implementing data governance is challenging due to issues like fragmented activities, lack of structure, and insufficient organizational support .
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Frameworks and Models:
- Several frameworks and models exist to guide data governance, including the DAMA framework and others that differentiate between governance and management .
- Effective data governance frameworks identify decision domains, establish decision rights, and define accountability .
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Activities and Decision Domains:
- Data governance involves various activities such as defining data policies, implementing data quality measures, and monitoring compliance .
- These activities are categorized into decision domains, which include defining, implementing, and monitoring actions .
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Regulatory Compliance:
- Data governance is essential for compliance with regulations like Sarbanes-Oxley, Basel III, and HIPAA, which mandate the integrity and accuracy of data .
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Collective Action and Organizational Challenges:
- Governing data effectively requires collective action and collaboration across different organizational units.
- Challenges include aligning value, collaboration, capabilities, and practices within the organization.
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Data Governance as a Service:
- The concept of data governance as a service is emerging, providing standardized, repeatable processes to manage data assets and ensure compliance.
Conclusion
Data governance is a critical component of an organization's information management strategy, essential for ensuring data quality, regulatory compliance, and leveraging data as an asset. Effective data governance frameworks and models help in defining decision domains, establishing decision rights, and ensuring accountability. However, implementing data governance remains challenging due to fragmented activities and lack of organizational support. Addressing these challenges requires a collective action approach and the adoption of standardized processes, potentially through data governance as a service.
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