Intelligent Metadata and Context-Aware MDM for Dynamic Decision-Making

Master Data Management (MDM) is experiencing a transformative evolution through the integration of artificial intelligence and advanced analytics capabilities. This comprehensive article explores how AI-driven metadata management and context-aware systems are revolutionizing traditional MDM approaches, enabling organizations to make more informed and dynamic decisions. The article examines the implementation of intelligent MDM systems across various industries, highlighting improvements in data quality, operational efficiency, and strategic decision-making. The article demonstrates how predictive analytics and contextual intelligence enhance data governance, customer experience, and supply chain management. Furthermore, it analyzes the technical requirements and organizational readiness factors crucial for successful MDM implementation, providing insights into the future of enterprise data management practices.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-16
DOI
https://doi.org/10.32628/cseit25112460
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Intelligent Metadata and Context-Aware MDM for Dynamic Decision-Making

Viswakanth Ankireddi
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Semantic Web and Ontologies
article

Intelligent Metadata and Context-Aware MDM for Dynamic Decision-Making

Viswakanth Ankireddi
article en

Abstract

Master Data Management (MDM) is experiencing a transformative evolution through the integration of artificial intelligence and advanced analytics capabilities. This comprehensive article explores how AI-driven metadata management and context-aware systems are revolutionizing traditional MDM approaches, enabling organizations to make more informed and dynamic decisions. The article examines the implementation of intelligent MDM systems across various industries, highlighting improvements in data quality, operational efficiency, and strategic decision-making. The article demonstrates how predictive analytics and contextual intelligence enhance data governance, customer experience, and supply chain management. Furthermore, it analyzes the technical requirements and organizational readiness factors crucial for successful MDM implementation, providing insights into the future of enterprise data management practices.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Intel (United States) (US)
Openalex Percentile: Top 98%
Semantic Web and Ontologies
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