With the evolution of distributed computing, the databases were inherently distributed across the globe. The core need in the current industrial environment is to extract information from the huge, complex and dynamic data through data mining techniques. Existence of an inconsistency in the data will directly affect the data mining and thereby affect the business performance. Thus, agents which are a powerful technology for the analysis design and implementation of autonomous intelligent systems is used to handle the varied issues related to inconsistencies in the data. This paper provides the design and development of intelligent software that uses agents to handle the data preprocessing thereby improving and enhancing the quality of data to be mined.

1. Bobek, S. and Perko, I. , 2006. Intelligent Agent Based Business Intelligence. University of Maribor, Faculty of Economics and Business, Razlagova ulica14, SI-2000 Maribor, Slovenia.
2. Han, J. and Kamber, M. 2001. Data Mining: Concepts and Techniques. Simon Fraser University, Academic Press. Information Quality Issues. International Institute for Advanced Studies in Systems Research and Cybernetic, IIAS.
3. Langseth, J. and Vivarat, N. , 2005. Why Proactive Business Intelligence Is A Hallmark Of The Real-Time Enterprise: Outward Bound. Intelligent enterprise.
4. Lin, L. , Osan, R. and Tsien J. Z. 2006. Organizing Principles of Real-time Memory Encoding: Neural Clique Assemblies and Universal Neural Codes. Center for Systems Neurobiology, Departments of Pharmacology and Biomedical Engineering, Boston University, Boston, MA 02118, USA. Shanghai Institute of Brain Functional Genomics, and the Key Laboratory of Chinese Ministry of Education, East China Normal, University, Shanghai 200062, China.
5. Petteri Nurmi, W. S. 1999. Using Neural Networks for Data Mining. Computer Science Department, Carnegie Mellon University, University of Wisconsin-Madison.
6. Wook Baik, Mitra, S. Pal, S. K. and Mitra, P. 2002. Data Mining in Soft Computing Framework: A Survey. IEEE Trans. Neural Networks, 13(1):3–14.
7. Chunsheng Li and Yatian Gao, 2001. An Introduction to Multi agent systems. Department of Computer Science, University of Iiverpool, UK. ISBN 0-471-49691- X.
8. Nils, N. , 1998. Artificial Intelligence: A New Synthesis. Morgan Kaufmann Publishers. ISBN 978-1-55860-467-4.
9. Padghan, L. and Winikopff, M. , 2004. Developing Intelligent Agent Systems. Wiley.
10. Roya, A. , Norwati, M. , Nasir, S. (2009). Training Process Reduction Based On Potential Weights Linear Analysis to Accelerate Back Propagation Network, Accepted by International Journal of Computer Science and Information Security (IJCSIS), Vol. 3, No. 1, July
11. Roya, A. , Norwati, M. , Nasir, S. and Nematollah S. (2009). New Supervised Multi layer Feed Forward Neural Network model to accelerate classification with high accuracy, Accepted by European Journal of Scientific Research (EJSR), ISSN 1450-216X, Vol. 33 Issue 1, pp. 163-178.
12. Jiawei Han, Micheline Kamber, Jian Pei, Data Mining: Concepts and Techniques,Elsevier, 22-Jun-2011 - 744 pages
13. Stuart J. R. and Peter N. , 2003. Artificial Intelligence: A Modern Approach. Second edition, Upper Saddle River, NJ: Prentice Hall, ISBN 0-13-790395-2.
14. Sharon Christa, Lakshmi Madhuri, Suma. V, 2012 Data Preprocessing Using Intelligent Agents, International conference on Frontiers in Intelligent Computing Theory and Application, December, Orissa.
15. Sharon Christa, Suma. V, Lakshmi Madhuri, 2012 An Effective Data Preprocessing Technique for Improved Data Management in a Distributed Environment, Third International Conference on Advanced Computing and Communication Technologies for High Performance Applications- June, Cochin.
16. T. R. G. Nair, Sharon Christa, Lakshmi Madhuri, Suma. V "Data Preprocessing Model Using Intelligent Agents", International Conference on Information Systems Design and Intelligent Applications- January, 2012 Visakhapatnam.
17. Vijayan S. 2006. Application of agents and Intelligent Information Technologies. ISBN 1-59904-265-7. Published in USA by Idea group publishing.
18. Werbos, P. J. 1974. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences. PhD Thesis, Harvard University, Cambridge, MA.
19. Wooldridge, M. , 2002. An Introduction to Multi Agent Systems. West Sussex, Willey.
20. Yoav Sh. and Kevin L. , 2009. Multi Agent Systems: Algorithmic, Game- Theoretic, and Logical Foundation. First published. Printed in the USA. ISBN 978-0-521-89943-7.

Coordinator Agent Transformation Agent Discretization Agent