MU Computer Engineering (Semester 8)
Data Warehouse & Mining
December 2014
Total marks: --
Total time: --
(1) Assume appropriate data and state your reasons
(2) Marks are given to the right of every question
(3) Draw neat diagrams wherever necessary

1 (a) What are the different characteristics of a Data Warehouse?
5 M
1 (b) For a Supermarket Chain consider the following dimensions, namely Product, store, time, promotion. The schema contains a central fact table, sales facts with three measures unit_sales, dollar_sales and dollar_cost. Design star schema for this application.
5 M
1 (c) Explain Web usage mining.
5 M
1 (d) Illustrate how the supermarket can use clustering methods methods to improve sales.
5 M

2 Define the following terms:
i) Dimension Tables
ii) Snowflake Schema
iii) Web Structure Mining
iv) Supervised learning.
20 M

3 (a) Explain Hierachical Clustering methods.
10 M
3 (b) Explain the Page Rank algorithm.
10 M

4 (a) Describe the following OIAP operations using an example:
i) Slice
ii) Dice
iii) Rollup
iv) Drill Down
v) Pivot
10 M
4 (b) Consider the following transaction database:
TID Items
01 A,B,C,D
02 A,B,C,D,E,G
03 A,C,G,H,K
04 B,C,D,E,K
05 D,E,F,H,L
06 A,B,C,D,L
07 B,I,E,K,L
08 A,B,D,E,K
09 A,E,F,H,L
10 B,C,D,F

Apply the Apriori algorithm with minimum support of 30% and minimum confidence of 70% and find all the association rule in the data set.
10 M

5 (a) Explain Classification Algorithms.
10 M
5 (b) Explain the ETL (Extract, Transform, Load) cycle.
10 M

6 (a) Define multidimensional and multilevel association mining.
10 M
6 (b) Explain the role of Meta data in a data warehouse.
10 M

Write detailed notes on
7 (a) Data Warehouse Architecture.
10 M
7 (b) K-Means Clustering.
10 M

More question papers from Data Warehouse & Mining