Q.1 Explain the fundamental concept of Data Warehousing. How does it differ significantly from an operational database system in terms of purpose, data characteristics and usage? [12 Marks]
Q.2 Describe and illustrate the various OLAP operations with examples. [12 Marks]
Q.3 Explain the various types of data that can be mined. [12 Marks]
Q.4 How can data mining provide business intelligence and create a competitive advantage for organizations? [12 Marks]
Q.5 Explain the difference between supervised and unsupervised learning with example. [12 Marks]
Q.6 What is frequent item set? How is it identified using the Apriori principle? [12 Marks]
Q.7 Write short notes on any TWO: (a) Data Mart (b) Data Transformation (c) Outlier Analysis [12 Marks — any 2]
Q.8 Provide an example of a scenario where association rule mining would be a useful technique. What kind of insights could it provide? [20 Marks]
Q.9 What is classification? Explain classification with Decision Tree induction. [20 Marks]
Q.10 What is clustering? Describe the steps involved in performing a clustering analysis. Explain any one application of it in detail. [20 Marks