The

Methodology

Data rationalization, a.k.a. data mapping, is a comparative analysis of data architectures.  In practice, it involves the conversion of an existing “source” structure’s data to be re-represented in some existing “target” structure.  The process of data rationalization compares two existing structures with the intent of moving the data from one into the other.  The actual “rationalization” is the resulting set of rules on how to move the data.

What is domain rationalization?
Domain rationalization is an integral part of the data rationalization process.  Unlike data name rationalization, domain rationalization focuses less on a particular data element’s name and more on the values the element can assume.  It is, perhaps, the most critical value-added thought process that must be performed in order to determine how data element values from different data structures relate or compare to each other.

For instance, two sets of data elements from different systems may look and feel different but may, in fact, contain the same business information and serve the same business purpose.  Conversely, they may look and feel the same but behave quite differently.  The differences are due to how the systems and their respective data structures were architected.

Description of DATARAT Tool
Navigation Rule Screen
Transformation Rule Screen
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