Transformation vs. Translation

Mapping data relies on two basic operations: data transformation and data translation.

Data transformation is the process of creating a correspondence between records and fields of a source schema to (often different) records and fields in a destination schema. An example of data transformation is to map shipping and billing address information from a purchase order to an invoice. This is the most basic type of mapping. Data transformation can also apply to operations such as:

  • Averaging data from a looping record and sending the output to a single field in the destination schema.
  • Converting character data to its ASCII format.
  • Adding or subtracting data from one or more records and putting the result in a single field in the destination schema.

Data translation is the process of changing the format of an instance message. Data translation is very helpful in solving enterprise application integration problems by translating a given type of message into alternative formats required by existing systems.

See Also

Types of Mapping Operations

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