STUPIDSID
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.
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
i) Slice
ii) Dice
iii) Rollup
iv) Drill Down
v) Pivot
10 M
4 (b)
Consider the following transaction database:
Apply the Apriori algorithm with minimum support of 30% and minimum confidence of 70% and find all the association rule in the data set.
| 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
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