A Governance-Driven Data Quality Engineering Framework For Enterprise Data Warehouses

Artificial intelligence (AI) and metadata-driven governance have emerged as transformative technologies for managing enterprise information systems in increasingly complex digital environments. Organizations generate massive volumes of structured, semi-structured, and unstructured data from diverse business applications, cloud platforms, Internet of Things (IoT) devices, and external data sources, making effective governance essential for ensuring data quality, consistency, security, and regulatory compliance. This paper presents an artificial intelligence-enabled metadata-driven data governance framework for enterprise information systems that integrates metadata management, automated data lineage, governance policy enforcement, data cataloging, master data management, and intelligent analytics into a unified governance architecture. The proposed framework leverages AI and machine learning techniques to automate metadata discovery, classify enterprise data assets, monitor data quality, detect anomalies, generate lineage relationships, and recommend governance actions with minimal human intervention. It also incorporates governance-driven lifecycle management, role-based access control, privacy protection, auditability, and compliance monitoring to strengthen organizational accountability and information integrity. Furthermore, the framework supports scalable cloud-native architectures, distributed data platforms, and real-time data processing environments, enabling seamless interoperability across heterogeneous enterprise systems. By combining artificial intelligence with metadata-driven governance principles, the proposed approach enhances enterprise data visibility, operational efficiency, regulatory compliance, and decision-making capabilities while reducing governance complexity and manual administrative effort. The framework provides a practical foundation for building intelligent, resilient, and scalable enterprise information systems capable of supporting digital transformation, advanced analytics, and sustainable business innovation.