Introduction to Business Data Mining

Introduction to Business Data Mining was developed to introduce students, as opposed to professional practitioners or engineering students, to the fundamental concepts of data mining. Most importantly, this text shows readers how to gather and analyze large sets of data to gain useful business understanding. A four part organization introduces the material (Part I), describes and demonstrated basic data mining algorithms (Part II), focuses on the business applications of data mining (Part III), and presents an overview of the developing areas in this field, including web mining, text mining, and the ethical aspects of data mining. (Part IV). The author team has had extensive experience with the quantitative analysis of business as well as with data mining analysis. They have both taught this material and used their own graduate students to prepare the text's data mining reports. Using real-world vignettes and their extensive knowledge of this new subject, David Olson and Yong Shi have created a text that demonstrates data mining processes and techniques needed for business applications.Feature : Coverage of business applications: This text focuses on the value of data analyses to business decision making while also exploring concepts such as lift, customer relationship management, market segmentation, and more. Feature : Straightforward explanation of methods, demonstrated with examples: Short vignettes are used throughout showing how specific concepts have been applied in actual business situations. References to data mining software and websites are also featured.Feature : Major software addressed: The textĹźs appendices show how major software projects support various aspects of data mining. Also, the text reviews popular data mining software to help students become familiar with the software options available in data mining. Feature : Concepts of data mining introduced early: Concept overviews precede the discussion of data mining algorithms, allowing readers to understand the importance of techniques by seeing how they are applied before they actually learn them.