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What is the difference between data-based, rule-based, and knowledge-based systems?

The chart below summarizes the key differences between data-based, rule-based, and knowledge-based systems:

  Data-Based system Rule-Based system Knowledge-Based system
Can process
Data
 
Data
Rules
Data
Rules
Knowledge
Can output Information
Information
Decisions
Real-Time Decisions
Information
Decisions
Answers
Expert Advice
Recommendations
Commonly used for Hard-coded rules Enterprise rules Departmental rules
Ideal for IT/System rules Simplistic business rules Complex business rules
Best for these types of applications* Traditional information systems
Decisioning
Compliance
Advising
Product Selection
Recommending
Troubleshooting
Domain scope - Broad logic Deep logic

Copyright 2006-2007 BIZRULES. All rights reserved.

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.

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.

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.


See What is the difference between data-based, rule-based, and knowledge-based systems? for original post and comments.
Database vs. Rulebase vs. Knowledgebase
Deciding between a Rule-Based or Knowledge-Based solution
* List of Applications where Rule-Based and and Knowledge-Based solutions are Most Effective  

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