Abstract

Data governance frameworks are essential for ensuring compliance, maintaining data quality, and managing risks in cloud-based big data systems where vast amounts of diverse data are processed and stored. This paper explores data governance frameworks tailored for cloud-based big data systems, focusing on strategies to address compliance requirements and maintain data quality throughout the data lifecycle. We examine key components of data governance, including data classification, access controls, data lineage, auditing, and metadata management, and their relevance to cloud environments. Additionally, we discuss emerging technologies such as blockchain and distributed ledgers for enhancing data governance and transparency in cloud-based big data systems. Through empirical analysis and case studies, we evaluate the effectiveness and scalability of different data governance frameworks in ensuring compliance with regulatory standards and maintaining data quality in real-world cloud-based big data environments. Furthermore, we discuss challenges, best practices, and future research directions in implementing and managing data governance frameworks for cloud-based big data systems. This study aims to provide guidance and insights for practitioners and researchers in designing and deploying robust data governance frameworks to ensure compliance and quality in cloud-based big data systems.

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