Knowledge Discovery

1. What is data mining? In your answer, address the following:

(a) Is it another hype?

(b) Is it a simple transformation of technology developed from databases, statistics, and machine learning?

(c) Explain how the evolution of database technology led to data mining.

(d) Describe the steps involved in data mining when viewed as a process of knowledge discovery.

1. a) Present an example where data mining is crucial to the success of a business. What data mining functions does this business need? Can they be performed alternatively by data query processing or simple statistical analysis?

b) Suppose your task as a software engineer at Big-University is to design a data mining system to examine their university course database, which contains the following information: the name, address, and status (e.g., undergraduate or graduate) of each student, the courses taken, and their cumulative grade point average (GPA). Describe the architecture you would choose. What is the purpose of each component of this architecture?

c) How is a data warehouse different from a database? How are they similar?

d) Briefly describe the following advanced database systems and applications: object-relational databases, spatial databases, text databases, multimedia databases, the World Wide Web.

e) Define each of the following data mining functionalities: characterization, discrimination, association and correlation analysis, classification, prediction, clustering, and evolution analysis. Give examples of each data mining functionality, using a real-life database that you are familiar with.

f) What is the difference between discrimination and classification? Between characterization and clustering? Between classification and prediction? For each of these pairs of tasks, how are they similar?