Architecting Reliable Data Governance Frameworks

Abstract

In the era of data-driven decision-making, establishing robust data governance frameworks is paramount for organizations to ensure the quality, integrity, and security of their data assets. This paper explores the architectural principles and strategies involved in creating reliable data governance frameworks. From defining data policies and standards to implementing effective data management processes, the paper provides insights into building a foundation that fosters trust, compliance, and efficient utilization of data resources. By examining real-world case studies and best practices, this work aims to guide organizations in architecting data governance frameworks that withstand the challenges of evolving data landscapes.