Ans. The term KDD’ (Knowledge Discovery in Database) be employed to describe the whole process of extraction of knowledge from data. In this context, knowledge means relationships and patterns between data elements. It was further proposed that the term ‘data mining’ should be used exclusively for the discovery stage of the KDD process.
A less official definition of KDD is the nontrivial extraction of implicit, previously unknown, and potentially. useful knowledge from data, so the knowledge must be new, not obvious, and one must be able to use it. KDD is not a new technique. but rather a multidisciplinary way field of research, machine learning, statics, database technology, expert system, and data visualization all make a contribution.
American express and AT & T utilizing KDD to analyze their client flies. In most European countries, a number of large banks and insurance ‘companies are tentatively doing, initial experiments with KDD. At the same time, however, it is becoming increasingly clear that KDD involves more problems than was initially realized. As much as 80% of KDD is about preparing data, and the remaining 20% is about mining. Manipulating data using normal database routines in, order to clean or code it is a much more important part of the KDD process than the actual pattern recognition itself.
