Master Data Management (MDM) Reference Architecture (PowerPoint PPTX)

The Master Data Management MDM Reference Architecture is an industry- and product-agnostic reference architecture that supports implementing the multiple styles of implementation (Regirtry, Consolidation, Co-existence, Centralised) for MDM.

It enables the ability to design business solutions incorporating MDM capabilities. By industry-agnostic, it means that the reference architecture incorporates the knowledge, best practices, and patterns
discovered through review and analysis of how MDM was deployed in multiple Customer Data
Integration and Product Information Management Solutions spanning multiple industry sectors. The document consists of abstracted knowledge and patterns from those implementations to develop the Master Data Management RA as a way to describe MDM as a MDM Solution within the enterprise that
implements MDM capabilities

The PPT delves into the critical aspect of data quality management, emphasizing the importance of data profiling and deduplication. Profiling helps in assessing the quality of source data, ensuring it meets baseline standards. Deduplication and enrichment processes are outlined to eliminate redundancies and enhance data accuracy. These practices are essential for maintaining high-quality data that supports business intelligence and decision-making.

Metadata management is another key component covered in the document. Metadata, or 'data about data,' is crucial for developing consistency in data definitions across the enterprise. It facilitates better communication between end users and IT teams, enhancing efficiency and reducing data ambiguity. The document explains how metadata can increase the value of data in data warehouses and provides clear definitions of data availability and location.

The document also addresses the organizational structure necessary for effective data governance. It highlights the roles of governance leadership, data stewards, and the data management team. Data stewards are pivotal in managing information across the organization, ensuring data quality and usability. The governance structure is designed to provide visibility into critical data issues and streamline their resolution, making it an indispensable resource for enterprises aiming to optimize their data management strategies.