Q1. Describe in details three main reasons why the data warehouse modeling needs modeling methods other than OLTP database modeling.
Q2. What do you mean by data mart? Distinguish between the dependent and independent data marts.
Q3. Each and every data structure in the data warehouse comprises the time element. Explain why?
Q4. Illustrate the difference between the three main kinds of data warehouse usage: information processing, analytical processing and the data mining?
Q5. Describe the motivation behind OLAP mining (OLAM). With the help of a clean diagram describe architecture of the OLAM.
Q6. In real-world data, the tuples with missing values for several attributes are a common occurrence. Explain any five methods for handling this dilemma.
Q7. What do you mean by Apriori property? Explain why it is used? Describe the Apriori algorithm for discovering the frequent item sets for mining the Boolean association rules.
Q8. Association rule mining frequently generates a large number of rules. Describe efficient methods which can be used to decrease the number of rules produced while still preserving most of the interesting rules.