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Data Warehousing Fundamentals for IT Professionals by Paulraj Ponniah

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CHAPTER 17

DATA MINING BASICS

CHAPTER OBJECTIVES

  • Learn what exactly data mining is and examine its features
  • Compare data mining with OLAP and understand the similarities and differences
  • Notice the place for data mining in a data warehouse environment
  • Carefully go through major data mining techniques and understand how each works
  • Study a few data mining applications in different industries and perceive the application of the technology to your environment

In today's environment, almost everyone in IT has certainly heard about data mining. Most of you know that the technology has something to do with discovering knowledge. Some of you possibly know that data mining is used in applications such as marketing, sales, credit analysis, and fraud detection. All of you know vaguely that data mining is somehow connected to data warehousing. Data mining is used in just about every area of business from sales and marketing to new product development to inventory management and human resources.

There are perhaps as many variations in the definition of data mining as there are vendors and proponents. Some experts include a whole range of tools and techniques, from simple query mechanisms to statistical analysis in the definition. Others restrict the definition to knowledge discovery techniques. A workable data warehouse, although not a prerequisite, will give a practical boost to the data mining process.

Why is data mining being put to use in more and more businesses? Here are some basic reasons: ...

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