Using Agents to extract data from existing sources of information is a key development area to unlock previously unknown relationships between heterogeneous data sources. It becomes an issue when large volumes of data, such as in the case of data from different sources like SQL, ORACLE,IBM-DB2,MySQL,FLAT FILES and others need to be analyzed. The main focus of this paper is on how data warehousing and mining techniques can be applied in knowledge discovery. We therefore proposed architecture for heterogeneous data integration based on Multi-Agent Driven Rule-based Decision Support System in data warehousing. With our predictive model, we achieved high accuracies of over 83% compared to (65%-72%) and (66%-72%) achieved by Clark, P & Niblett, T and Michalski, R.Set. al respectively on the Breast Cancer Wisconsin dataset.
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