The increasing reliance on data-driven decision-making in modern enterprises has elevated the importance of effective Master Data Management (MDM) as a foundation for trusted and intelligent business operations. This research reimagines enterprise MDM by proposing a comprehensive framework that integrates data governance, advanced analytics, and intelligent automation to enhance data quality, consistency, and reliability across organizational systems. The study addresses critical challenges such as data silos, inconsistency, and lack of trust in enterprise data by introducing a unified architecture that ensures standardized data definitions, real-time synchronization, and secure data access. The proposed model incorporates policy-driven governance, metadata management, and role-based access control to maintain data integrity and compliance with regulatory standards. Furthermore, the integration of intelligent techniques, including automation and data validation mechanisms, improves decision-making capabilities and operational efficiency. Experimental evaluation demonstrates that the reimagined MDM framework significantly enhances data accuracy, reduces redundancy, and supports scalable enterprise operations. The findings highlight the strategic role of advanced Master Data Management in enabling organizations to build trust in their data ecosystems while driving innovation and intelligent business transformation.
Collins et al. (2021) studied this question.