Reverse Engineering is the process of inductively deriving data architectures and models from existing databases and business information systems.
While there is no magic bullet to this effort, the Whitemarsh approach reduces to the maximum degree possible redundant and conflicting activities and results. Because of the Whitemarsh engineered Data Architecture data generalization Levels when a lower level model component is discovered but despite having different names is determined to be the same as a higher level model component, the lower level component merely has to be mapped to the higher level component.
The data architecture levels that are constructed from the Operational Database level are the Implemented Database level, the Specified Data Model (models of concepts), and the Data Element model level.
The Whitemarsh approach enables the process of Reverse Engineering to be accomplished in a distributed fashion such that the lower levels can remain distinct while the upper levels are common and represent common semantics across functions and across the Enterprise's semantics.
Once complete, the work product set resulting from reverse engineered models provides two very significant work-assist benefits. First, the upper levels of a model enable common semantic and value domain mappings that are necessary for any data exchange processes between and among operational databases.
The second work assist provided by the created upper levels is the manufacturing of new lower level databases.