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Transformations and Enrichment

  • Mark Lui
  • Mario Gray
  • Andy Chan
  • Josh Long

Abstract

One approaches integration so that two or more applications may share services and data. One of the key challenges of integration is that the underlying data models of any two given applications are likely different, or incompatible. The various properties of, say, a customer record, can vary for a simple field such as an address. Some applications define the complete address as a single property, and others break down the address into the street number, street, city, state, zip code, and so on. In addition, the exchange format of the record itself may be incompatible: system A might expect a serialized Java object, and system B might expect an XML-encoded record or some other serialization. An integration platform should be able to adapt messages as required by consumers. Care should be taken that data is of as high fidelity as possible when moving from system to system. To support an extensible framework for data transformation, integration platforms support transformation.

Keywords

Output Channel Input Channel Incoming Message Customer Information Public Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Dr. Mark Lui, Mario Gray, Andy Chan, and Josh Long 2011

Authors and Affiliations

  • Mark Lui
  • Mario Gray
  • Andy Chan
  • Josh Long

There are no affiliations available

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