Enterprise Data Quality Management: A Technical Deep Dive into Automated Governance

Author(s)	Suman Etikala
Country	United States
Abstract	This comprehensive article examines the implementation and impact of enterprise-wide data quality management and governance frameworks in modern organizations. The article investigates how automated data quality monitoring, combined with robust governance protocols, transforms organizational data integrity and decision-making capabilities. Through details of various case studies and research findings, this article demonstrates the effectiveness of systematic approaches to data quality management, highlighting improvements in operational efficiency, compliance adherence, and financial performance. The article particularly focuses on the integration of machine learning capabilities, microservices architecture, and advanced analytics in enhancing data quality management systems, while also addressing the challenges and opportunities presented by modern enterprise data environments.
Keywords	Enterprise Data Management, Automated Governance, Data Quality Framework, Machine Learning Integration, Compliance Management.
Field	Computer
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-02
Cite This	Enterprise Data Quality Management: A Technical Deep Dive into Automated Governance - Suman Etikala - IJSAT Volume 16, Issue 2, April-June 2025.

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