Improving Data Quality and Data Governance Using Master Data Management: A Review

Abstract

Master data management (MDM) is a method of maintaining, integrating, and harmonizing master data to ensure consistent system information. The primary function of MDM is to control master data to keep it consistent, accurate, current, relevant, and contextual to meet different business needs across applications and divisions. MDM also affects data governance, which is related to establishing organizational actors’ roles, functions, and responsibilities in maintaining data quality. Poor management of master data can lead to inaccurate and incomplete data, leading to lousy stakeholder decision-making. This article is a literature review that aims to determine how MDM improves the data quality and data governance and assess the success of MDM implementation. The review results show that MDM can overcome data quality problems through the MDM process caused by data originating from various scattered sources. MDM encourages organizations to improve data management by adjusting the roles and responsibilities of business actors and information technology (IT) staff documented through data governance. Assessment of the success of MDM implementation can be carried out by organizations to improve data quality and data governance by following the existing framework.