Description
In all organizations, in every industry and of every size, master and reference data is collected and used extensively. Master data management (MDM) refers to two related but distinct forms of data: reference data and master data. High-quality master and reference data are essential components of every organization’s performance capabilities.
Reference data are the data that every organization defines as the set of permissible values to be used by other data in the organization. Reference data gain value when they are widely re-used and widely referenced. Typically, their definitions and values do not change much apart from occasional additions. Think of state codes, currency codes, etc., as forms of reference data.
Master data are the data that every organization collects and uses across multiple areas, such as customer data (name, address, etc.), location data, vendor data (name, addresses, etc.), product information data, etc. Master data differs from transaction data, but the master data supports the transactional data.
Many organizations struggle with the ability to develop and sustain a master data management program, one built and maintained according to industry standards and best practices. Therefore, organizations expend much effort and resources to correct master and reference data and cannot integrate data from disparate sources due to incompatible master or reference data.
This introductory seminar will provide an overview of master and reference data, its purpose, and how an enterprise master data management program can be implemented consistently. The attendees will gain an understanding of the importance of master data management to the business success of every organization and will include an overview of the need to align a data quality program with the MDM initiative. The session will highlight the various types of master data management approaches/architectures, the functions of the MDM team, and will provide some proven approaches to the implementation of an MDM program.
