Over the last 20 years, $1 trillion has been invested in new computer system to gain competitive edge. The vast majority of these systems have automated business process, to make them faster, cheaper and more responsive to the customer. Companies are beginning to realize the vast potential o the information that they hold in their organization. The problem for most companies, though, is that their operational systems were never designed to support this kind of business activity, and probably never can be. Even the latest technology cannot be optimized to support both operational and multidimensional requirements cost-effectively. Operational systems also tend to be numerous, with overlapping and sometimes contrary definitions. To meet these needs there is a new breed of system, one that evolved and manufactured in recent years and is now known as data warehouse.
This is an introduction to a young and promising field called data mining and knowledge discovery from data. The material is represented from data perspective, where emphasis is placed on basic data mining concepts and techniques for uncovering interesting data patterns hidden in large data sets. The implementation methods discussed are particularly oriented towards the development of scalable and efficient data mining tools. It is also known that data mining is a part of the natural evolution of database technology, why is it important and how it is defined. General architecture, its scope and applications are also discussed.
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