The goal common to all users will be to maximize the amount of useful information extracted while minimizing the loss of productivity resulting from wasted time and resources, prohibitive access or transmission charges, and retrieval of meaningless, incorrect, or corrupted data. To meet this goal, we must develop the capabilities to represent and store large information data sets efficiently, to extract and transmit material across a distributed multiuser network, and to analyze, interpret and display such information effectively and meaningfully. Ironically the information on Datamining itself is mind boggling. The field is still in its infancy still most of the research and related literature. The objective of the final paper is to consolidate the research and various projects in the area of Data Mining globally, study various techniques used, emphasizing the application of Neural Networks.
Data mining is the data-driven extraction of information from large databases.
It is the process of automated presentation of patterns, rules or functions to a knowledgeable user for review and examination. Data mining is a useful tool, a new approach which combines discovery with analysis. Data mining is not a newly discovered branch of mathematics embodied in software that will, when hooked-up to a large and problematical database, inexplicably and inevitably reveal the business insights contained in the millions of records stored therein. Yet still it is important. It is an area that will increasingly become mandatory for competitive businesses.