Frameworks for effective data governance: best practices, challenges, and implementation strategies across industries

Abstract

This paper explores frameworks for effective data governance, emphasizing the importance of robust policies, processes, roles, and metrics. It outlines best practices for ensuring high data quality, data privacy, and security while highlighting stakeholder engagement and the role of technology. The paper also discusses implementation challenges, including organizational, technical, regulatory, and cultural obstacles. It presents tailored strategies for various industries such as financial services, healthcare, retail, manufacturing, and the public sector. Future directions for research include the integration of AI and machine learning, evolving data privacy regulations, and the challenges posed by big data and IoT. Effective data governance is crucial for managing risks, ensuring compliance, and unlocking the full potential of data assets across industries. Keywords: Data Governance, Data Quality Management, Data Privacy, Regulatory Compliance.