12 January 2017

Data Management: Reference Data (Definitions)

"Reference data is focused on defining and distributing collections of common values to support accurate and efficient processing of operational and analytical activities." (Martin Oberhofer et al, "Enterprise Master Data Management", 2008)

"Sets of values or classification schemas referred to by systems, applications, data stores, processes, and reports, as well as by transactional and master records. Examples include lists of valid values, code lists, status codes, flags, product types, charts of accounts, product hierarchy." (Danette McGilvray, "Executing Data Quality Projects", 2008)

"Data that describe the infrastructure of an enterprise. These comprise the 'type' entity classes that provide lists of values for other attributes." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"Data characterized by shared read operations and infrequent changes. Examples of reference data include flight schedules and product catalogs. Windows Server AppFabric offers the local cache feature for storing this type of data." (Microsoft, "SQL Server 2012 Glossary", 2012)

"Corporate data that has been defined externally and is uniformly changed across company boundaries, such as country codes, currency codes and geo-data." (Boris Otto & Hubert Österle, "Corporate Data Quality", 2015)

"Reference data is commonly used to link and give additional details to the data. It is the data used to classify, organize, or categorize other data. Reference data can also contain value hierarchies, for example, the relationships between product and geographic hierarchies. It is escorted by the discipline Reference Data Management, which makes sure the reference data is consistent and that different versions are managed and distributed properly." (Piethein Strengholt, "Data Management at Scale", 2020)

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IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.