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Over the past decade, data mining has gained an important role in analysis of large datasets and there by understanding the complex systems in almost all areas. Such datasets are often collected in a geographically distributed way, and cannot, in practice, be gathered in to single repository. Existing data mining methods for distributed data are of communication intensive. Many algorithms for data mining have been proposed for a data at a single location and some at multiple locations with improvement in terms of efficiency of algorithms as a part of quality but effectiveness of these algorithms in real time distributed environment are not addressed, as data on the web/network are distributed by very of its nature. As a consequence, both new architectures and new algorithms are needed. In this paper we introduce the software agent technology that supports building of distributed data mining architecture and explore the capabilities of mobile agents' paradigm and will show by experiment that, it is suited for distributed data Mining compared to traditional approaches like client server computing..

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