Data mining involves using statistical, machine learning, and artificial intelligence techniques to discover patterns in large data sets. It is a component of business intelligence that helps organizations understand their data, customers, and markets. The key steps in data mining include data preparation, model building, validation, and deployment of results. Data mining is used in applications like customer segmentation, risk management, and fraud detection across industries like banking, retail, and healthcare. It plays an important role in customer relationship management by helping companies better understand customer behavior.

1. DATA MINING: KNOWING THE UNKNOWN

6. Data mining as a component of BI FIGURE 12.2:

12. FIGURE 12.3: Data Warehouse and DM Technological Framework

16. FIGURE 12.4 Conventional Approach to Corporate Decision Making

17. FIGURE 12.5: DM in the Context of the New Corporate Business Model

19. The Virtuous DM Cycle

37. DM as a Required Component for Various Applications in Different Departments

39. Integrated Knowledge Management System for Marketing

41. Customer-Centric Data Warehousing Enables Next Generation E-Commerce

43. Data-Mining Challenges

48. Chapter 12 DATA MINING: KNOWING THE UNKNOWN