Defining Attribute Composition in Master Data Management: An Indispensable Stage for Data Quality

This article by SOFROS explores the critical importance of defining attribute composition during the normalization of Master Data (MDM). The authors argue that selecting object characteristics is not merely a matter of convenience, but the foundation for future automation, analytics, and data integration. An erroneous or redundant set of attributes renders a system dysfunctional, whereas thoughtful design transforms a directory into a reliable 'single source of truth.' The material examines case studies demonstrating that even a complete list of characteristics does not guarantee data quality without a systematic approach to structuring. Proper attribute design is a prerequisite for a company's transition to data-driven management, eliminating the need for manual record processing. The article encourages viewing attribute composition not as a simple template, but as a strategic tool for managing information quality within enterprise systems.