Data mapping
process of linking data objects in distinct models
In computing and data management, data mapping is the process of defining correspondences and transformation rules between data represented in a source model and data represented in a target model. A mapping can specify direct correspondences between data elements as well as transformations such as conversion, concatenation, lookup, or restructuring.
Data mapping is used in data integration, data migration, extract, transform, load (ETL), electronic data interchange (EDI), application integration, and other processes in which data must be exchanged or reconciled between different representations.
For example, a source system might contain fields named first_name and last_name, while a target system expects givenName, familyName, and fullName. A mapping could associate the first two fields directly with their corresponding target fields and define fullName as a concatenation of the two source values.
Concepts
A data mapping relates a source representation to a target representation. The source and target can be database schemas, files, messages, application data models, metadata schemas, or other structured representations.
Mappings range from simple one-to-one correspondences to transformations involving multiple fields. Common forms include direct mappings, conversions between units or formats, lookup rules, composition of several source values into a target value, decomposition of a source value into several targets, and structural transformations.
Mapping and schema matching
Data mapping overlaps with schema matching, and terminology varies in the literature.
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This entry incorporates text from “Data mapping” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.