Transforming Enterprise Data Governance Via Metadata Intelligence and Automated Data Lineage Frameworks
DOI:
https://doi.org/10.15662/IJEETR.2026.0806003Keywords:
Enterprise Data Governance, Metadata Intelligence, Automated Data Lineage, Data Cataloging, Machine Learning, Data Quality Management, Knowledge Graphs, Regulatory Compliance, Data Transparency, Enterprise Data ArchitectureAbstract
The growing complexity of enterprise data ecosystems has increased the need for intelligent, scalable, and automated data governance mechanisms. Traditional governance approaches frequently depend on manual metadata documentation, fragmented data catalogs, and disconnected lineage tracking processes, creating challenges related to data quality, transparency, regulatory compliance, and operational efficiency. This research proposes an integrated enterprise data governance framework that combines metadata intelligence with automated data lineage capabilities to improve organizational data management. The proposed framework utilizes metadata harvesting, machine learning, automated lineage discovery, knowledge graph representations, and policy-driven governance mechanisms to establish comprehensive visibility across distributed enterprise data environments. It integrates structured and unstructured data sources, cloud platforms, data warehouses, application programming interfaces, and real-time data pipelines. Intelligent metadata classification supports automated identification of sensitive information, business terminology, and data ownership responsibilities, while lineage analysis provides traceability throughout data transformation and consumption processes. The framework also incorporates continuous monitoring, data quality assessment, and compliance validation to strengthen governance accountability. The proposed architecture aims to reduce manual governance activities, improve data discoverability, enhance audit readiness, and establish trusted enterprise information assets. This research presents a conceptual and methodological foundation for implementing intelligent, metadata-driven governance across modern enterprise data infrastructures.
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