The problem with legacy data-based
systems is that they are hard-coded and limited to
processing data and outputting information. It's still
up to the human being to analyze all the information to
make decisions and recommendations. The result is often
information-overload and costly mistakes. |
Rule-based systems process data
and output information, but they also process rules and
make decisions. They are good at processing lots of
simple business rules with broad logic. They are
commonly used for real-time
decisioning systems and
compliance systems.
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Knowledge-based systems also process data
and rules to output information and make decisions. In
addition, they also process expert knowledge to output
answers, recommendations, and expert advice. They are
good at processing deep logic and very complex business
rules. They are commonly
used for advising systems, expert
systems, and knowledge automation. |