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

Suman Etikala

2025 · DOI: 10.71097/ijsat.v16.i2.3050
International Journal for Sciences and Technology · 0 Citations

TLDR

How automated data quality monitoring, combined with robust governance protocols, transforms organizational data integrity and decision-making capabilities is investigated, highlighting improvements in operational efficiency, compliance adherence, and financial performance.

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.