A simple way to introduce new topics is to analyze existing and, above all, recognized definitions. Let's use the definitions of Master Data Management (MDM) by Gartner and Forrester, two recognized and leading international research and advisory companies.
"Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts."
"Master data management (MDM) is a category of software infrastructure that operationalizes the acquisition, distribution, and management of core data entities, including customers, products, and suppliers. As enterprises grapple with service-oriented architecture (SOA) demands, they increasingly recognize the need to manage master data, such as customer, product, supplier, location, and employee data, outside of the core applications that use it. Doing so offers the promise of enabling existing applications to work off the same master data, reducing data quality and redundancy concerns and improving the support of instance consolidation, supplier collaboration, Lean Manufacturing, eCommerce, and business intelligence initiatives."
According to the two definitions, an overall goal of any Master Data Management initiative is to create a single source of reference of critical business data. More in detail, MDM is a collaboration discipline between business and IT, that continuously ensures that data from the various data domains (including product, customer, supplier, location and employee information) is consistently and accurately available in each system.
As a result, users can trust the information displayed in their respective applications, plus the data is managed centrally. An MDM program also ensures better data quality by connecting existing silo or island applications and providing accurate information and data across applications. For this it is necessary to fulfill different tasks of the MDM discipline. Among other things it is necessary to define responsibilities for data domains or processes.