Building Scalable Master Data Management (MDM) Systems for Enterprise Data Platforms

Abstract

To achieve the correct, consistent and efficient data across the disparate systems, organizations must build scalable Master Data Management (MDM) systems on enterprise data platforms. This paper introduces a model of building scalable MDM systems to suit large-scale enterprise data platforms. The framework outlines the following important principles: data integration, quality management, governance, and scalability, and organizations are able to manage increasing volumes of data without compromising the integrity of master data. The paper will address the kinds of architectural models, tools as well as technologies that are applied to design and implement MDM systems, and how they are focused on the overall data strategy of the organisation. Data modeling, metadata management as well as data stewardship best practices are also discussed to enhance data governance. This paper will include case studies, which demonstrate how the framework can be put into practice, challenges and successes that organisations experience when using MDMs. Moreover, scalability of the system is examined using performance optimization methods such that the MDM system can be scaled as the needs of the enterprise changes. The results suggest that the introduction of a properly organized MDM system can greatly enhance data consistency, minimize operational risks, and facilitate decision-making. The paper has added to the body of knowledge by offering a detailed road map to the development of scalable MDM systems, and by giving an understanding of the dynamic emerging world of enterprise data management.