ABSTRACT
The purpose of this chapter is to introduce data mining concepts, provide some examples of data mining applications, list the most commonly used data mining techniques, and briefly discuss the data mining applications available in the
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SAS software. For a thorough discussion of data mining concept, methods, and applications, see the following publications.4-6
1.2 Data Mining: Why it is Successful in the IT World In today’s world, we are overwhelmed with data and information from various sources. Advances in the field of IT make the collection of data easier than ever before. A business enterprise has various systems such as transaction processing system, HR management system, accounting system, and so on, and each of these systems collects huge piles of data everyday. Data mining is an important part of business intelligence that deals with how an organization uses, analyzes, manages, and stores data it collects from various sources to make better decisions. Businesses that have already invested in business intelligence solutions will be in a better position to undertake right measures to survive and continue its growth. Data mining solutions provide an analytical insight into the performance of an organization based on historical data, but the economic impact on an organization is linked to many issues and, in many cases, to external forces and unscrupulous activities. The failure to predict this does not undermine the role of data mining for organizations, but on the contrary, makes it more important, especially for regulatory bodies of governments, to predict and identify such practices in advance and take necessary measures to avoid such circumstances in future. The main components of data mining success are described in the following subsections.
