The term mapping or mappings in ETL and data processing is a useful but generic term. However, It’s often not clear what is mapped to what.
Data mapping in ETL systems has been variously described as:
A map of the links between the source data and the target data.
Details of how each field in the source data corresponds to a field in the target data.
A tracing of tables/files and columns/fields from the data source (where data comes from) all the way through where it ends up in a data warehouse.
The process of mapping data accurately for ETL involves identifying the source and target data systems, examining the data in both systems for any discrepancies, creating a mapping document that details how each field in the source data corresponds to a field in the target data, and testing the mapping to ensure it is functioning as intended.
Mapping is a very generic but important concept. On it’s own however, “mapping” doesn’t tell you what is mapped to what. Sometimes “mapping” describes what a process does, sometimes the output of a process, sometimes metadata or a metadata store, sometimes documentation, and sometimes the UI that maintains the mapping metadata.