We are living in the information age. The importance of collecting data that reflects one business or of activities that achieve competitive advantage, are widely recognized now. Powerful systems for collecting data and managing it in large databases are available in most organizations. However, the major bottleneck of converting this data into effective information is the difficulty faced in extracting knowledge about the system from the col!.ected data. Modeling investigated system discovering relations that connect variables in a database are the subjects of data mining.
Data mining is the process of identifying valid, novel, potentially useful and uHimatelf comprehensible Information trom databases that is used to make crucial business decisions. Modern data mining systems self learn from the previous history of the investigated system, formulating and testing hypotheses about the rules, which the system obeys. When concise and valuable knowledge about the system of interest has been discovered, it can and should be incorporated into some decision support system which helps the manager make wise and informed business decisions.
The main reason for needing automated computer systems for intelligent data analysis is the enormous volume of existing and newly appearing data that require processing. The amount of data accumulated each day by Various businesses, scientific and governmental organizations around the world is daunting. Research organizations, academic institutions and commercial organizations create and stOie huge amounts of data each day. It becomes impossible for human analysts to cope with such overwhelming amounts of data.
The other problems that surface when human analysts process data are:
. The inadequacy of the human brain when searching for complex multifactorial dependencies in the data
. The lack of objectiveness in analyzing the data

A human expert is always a hostage of the previous experience of investigating other systems. Sometimes this helps, sometimes this hurts, but it is almost impossible to get rid of this fact.
One additional benefit of using automated data mining systems is that this process has a much lower cost than hiring an army of highly trained (and paid) professional statisticians. While data mining does not eliminate human participation in solving the task completely, it significantly simplifies the job and allows an analyst, who is not a professional in statistics and programming, to manage the process of extracting knowledge from data.