Master Data Management

Master Data Management is a discipline focused on matching records (across systems), deduplicating, and applying survivorship rules to generate a canonical "golden record" for each core Master Data* record in your business. A "golden record" is a single authoritative trustworthy version of each Master data record. Master Data is among the most important data in your business, yet its core role means it is often duplicated across multiple systems, creating a management nightmare. Which version of a customer is the correct one, the record in sales, manufacturing, or finance? And which system holds the email address you should use to make contact? Because of this many organizations choose to implement Master Data Management.

Master data is the core non-transactional data entities like customers, employees, products, suppliers, accounts etc. that participate in the activities and events of your business processes. It is the key "people", "places", "things", or "nouns" (e.g. account, policy etc.) that are involved in a business process.

The two main functions of MDM are:

Entity/Identity Resolution. The practice of identifying multiple records from different systems as the same person, place or thing. It involves matching records across multiple attributes with matching rules and confidence scoring. In some cases, a partial match is forwarded to a human for adjudication.
Survivorship. If multiple records have conflicting values for an attribute (e.g. address, email address, phone number), which does the MDM system use in its golden record? This is where survivorship rules come into play. They determine which value "wins". Again, in some cases a conflict is forwarded to a human for adjudication.

When is MDM really critical? Some examples include post-merger identity or legal exposure if you pick the wrong surviving record (e.g. health or aged care). There can be real financial implications of not managing Master data correctly.

Learn more

Deep dive into Reference data management (RDM). Learn about the challenges facing businesses, the typical uses cases, capabilities and collaboration requirements of a good RDM system, Governance and implementation options, and the future of AI and automation for RDM. Read the white paper: Reference Data Management - The Missing Layer in Enterprise Data Architecture.