Enhancing Enterprise Data Governance Maturity Through Cloud Based Data Integration Frameworks in Modern Organizations

Abstract

As digital transformation takes center stage, data has become a critical resource for modern businesses to inform their decisions, drive innovation, and gain a competitive edge. But with many heterogeneous data sources and legacy system restrictions, effective data governance is challenging. Traditional data governance models are not always scalable, real-time, or flexible enough to integrate, making it difficult to achieve higher levels of data governance maturity. This research paper investigates the use of cloud-based data integration frameworks for improving the maturity of enterprise data governance in today’s business landscape.
The research topics include the history of data governance models, and the challenges of traditional integration architectures. It offers a vision of a scalable ingestion pipeline, a centralized metadata management system, automated policy enforcement and real-time analytics within a cloud-based data integration architecture. The framework adopts cloud computing principles like elasticity, distributed processing, and service-oriented architecture to enhance data quality, consistency, accessibility, and compliance.
It covers topics related to security, privacy issues, vendor dependency, and provides strategic recommendations for organizations looking to evolve to more advanced, cloud-based data governance ecosystems.