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Why is Change So Hard in
Oracle Applications?
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The
complexity of Oracle Applications’ relational databases has
grown exponentially with each new version release, resulting in a
system that is extremely difficult to implement and maintain.
For example, Oracle Applications 11.5.10.2 contains over 2 million
columns, each of which could be related to any other, or could be part
of a check constraint, or part of a unique or primary key.

The
constraints (or rules about the data) determine the sequence of changes
made to the database. Most of these rules are not documented
at the database level, so if a change is to be made, the rules have to
be discovered and then validated with actual data.
Furthermore, because rules cascade in a relational database, it is
impossible to comprehend all of the possible combinations of
relationships, making manual mining of the rules a daunting task that
will almost certainly result in compromising the data
integrity. While consultants with expert knowledge of
relational databases can be an asset to an organization undergoing
changes to their data systems, the assistance of software is necessary
to ensure complete and correct data as well as an understanding of the
impact of change. Verification has been a manual process, as
analysts and consultants manually mine the database attempting to
maintain data integrity, checking as many of the possible existing
combinations as they can and keeping numerous spreadsheets as
workarounds to making changes in their Apps.
The changes and rules at the database level do not consider the impact
of business changes to related data. (If a product ID is
changed, what is the business impact to production and inventory
processes?) Managing the complexity of change both at the
database level and at the business process level often results in a
disconnect between the technical and functional players of database
management. The time-consuming task of manual mining is naive
concerning its effects on business processes, often proving very costly
for a company going through data and business changes.
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