Reference data
Reference Data is the lists of valid values behind the attributes of key business entities in Operational Systems.
So what is Reference Data?
Two competing definitions of the term tend to confuse the subject. This section works through both to arrive at a clear, definitive definition of Reference Data Management.
The narrow definition comes from the Data Management Association’s DMBOK (Data Management Body of Knowledge, the profession’s standard reference text). In this case, Reference Data is the lists of valid values behind the attributes of Master Data entities. It’s discussed as a sub-topic of Master Data Management, which is the management of the core or “master” entities of your business (E.g., Customer, Product, Employee). It is the lists of valid country codes, currency codes, and status codes that sit behind the attributes of these master data entities. Operational systems will generally maintain their own lists of reference data.
The broader definition adds to the narrow definition and includes the mappings, hierarchies, categorizations, bandings, and augmentation of data that determine how data from different systems is translated, grouped, rolled up, and assigned for the purposes of data integration, migration, warehousing, reporting, and analysis.
The difference between the two is ownership. For the narrow definition, an operational system is the system of record. For the broader definition, in most organizations, there is no system of record. It survives only in a sprawl of poorly governed spreadsheets, CSV files, and hard-coded transformation logic.
Reference Data is also different to Reference Data Management. Reference Data Management (RDM) encompasses the maintenance of reference data lists, but it's more than that, and comes into its own in the spaces between operational systems (i.e. data integration, data migration and data warehouses). RDM is concerned with the mapping, categorization, hierarchies etc. that augment and map key business entities across systems.
Reference Data Management in many organizations is implemented piecemeal as 100s of spreadsheets, CSV files, and hard coded rules. A better option is a dedicated Reference Data Management system like TitanRDM.
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.