One of the major processes concerning Master Data Repositories is the handling of data exceptions. These exceptions arise when data being provided is incompatible with the MDR being loaded.

Some examples of exceptions are:

1. Null data when expecting a value
2. Character data when expecting numeric
3. Data that does not pass a validation screen (e.g. Postal Code mask)

In a real time interface, the challenge is lessened, as an error code can be returned back and the update refused.

With batch processes, the situation can become far more complex.

Batch MDR Exception Handling Techniques

How these exceptions are handled have some very far reaching consequences. It is important that the business users understand the process that is implemented and, ideally, have the opportunity to provide input into the creation of the processes.

Some possible processes:

1. Allow the “bad data” to be input into the MDR, but flag it for possible follow up
2. Reject the exception data, place in a holding queue for:
   1. Automatic correction and/or Manual correction
   2. Send back to provider
   3. Obliteration (don’t care about this or not worth the trouble to fix)