Reference data are data that define the set of permissible values to be used by other data fields. Reference data gain in value when they are widely re-used and widely referenced. Typically, they do not change overly much in terms of definition, apart from occasional revisions. Reference data are often defined by standards organizations, such as country codes as defined in ISO 3166-1.
Examples of reference data include:
- Units of measurement
- Country codes
- Corporate codes
- Fixed conversion rates e.g., weight, temperature, and length
- Calendar structure and constraints
Differences with master data
Reference data should be distinguished from master data, which represent key business entities such as customers and materials in all their necessary detail (e.g., for customers: number, name, address, and date of account creation). In contrast, reference data usually consist only of a list of permissible values and attached textual descriptions. A further difference between reference data and master data is that a change to the reference data values may require an associated change in business process to support the change; a change in master data will always be managed as part of existing business processes. For example, adding a new customer or sales product is part of the standard business process. However, adding a new product classification (e.g. restricted sales item) or a new customer type (e.g. gold level customer) will result in a modification to the business processes to manage those items.
- "IBM Redbooks | Reference Data Management". www.redbooks.ibm.com. 2013-05-16. Retrieved 2015-12-09.
- "Reference Data Management and Master Data: Are they Related ? (Oracle Master Data Management)". blogs.oracle.com. Retrieved 2015-12-09.
- Chisholm, Malcolm (2001). Managing Reference Data in Enterprise Databases. Morgan Kaufmann Publishers. ISBN 1558606971.
- Whei-Jen, Chen (2014). Master Data Management for SaaS Applications. IBM Redbooks. ISBN 978-0738440040.
- Berson, Alex (2011). Master Data Management and Data Governance. McGraw-Hill Osborne Media. ISBN 978-0071744584.
- Master Data
- Data modeling
- Master Data Management
- Enterprise bookmarking
- Data architecture
- Transaction data