A review of master data management technologies and their applications across diverse industry domains

This review explores Master Data Management (MDM) technologies and their applications across multiple industries. Although MDM is vital for achieving unified and reliable data, existing studies lack an integrated cross-sectoral analysis connecting emerging technologies with key MDM components and implementation results. To bridge this gap, a structured literature review was conducted using Snyder’s (2019) methodology. Peer-reviewed articles from 2021–2025 were sourced mainly from Scopus, resulting in 43 relevant studies selected from 101 initial records. The analysis, guided by the DAMA-DMBOK framework, reveals growing adoption of AI, machine learning, blockchain, and semantic knowledge graphs in sectors such as healthcare, manufacturing, energy, government, retail, and transportation. Findings show that MDM enhances data quality, governance, and operational efficiency while facing challenges like integration complexity, scalability, and compliance. The review contributes a conceptual framework linking MDM components, enabling technologies, and strategic outcomes to support both research and real-world implementation.