Intelligent Data Governance in Distributed Systems: Advancing Compliance through AI Integration
This comprehensive article examines the evolution and implementation of intelligent data governance frameworks in modern distributed systems, focusing on integrating artificial intelligence and metadata-driven approaches. The article explores how organizations address unprecedented challenges in managing sensitive data across complex infrastructures while maintaining regulatory compliance. The article investigates the transformation from traditional governance models to sophisticated, AI-enhanced systems that enable real-time monitoring, automated classification, and predictive analytics. The article provides insights into successful deployment strategies through a detailed examination of implementation considerations, including technical architecture requirements and organizational readiness factors. It demonstrates the significant improvements in operational efficiency, security controls, and compliance management achieved through intelligent governance frameworks.
Authors
- Amit Kumar (ORCID: https://orcid.org/0000-0002-8367-9981)
Institutions
- Michigan Institute for Neurological Disorders (US)
Publication Details
- Journal
- International Journal of Scientific Research in Computer Science Engineering and Information Technology
- Published
- 2025-03-09
- DOI
- https://doi.org/10.32628/cseit25112434
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00