Data Warehousing and Data Mining 2072

                                       Group-A

                       Attempt any two questions.                               (10x2=20) 

1. Differentiate between Data-Warehouse and Data-mining. Explain the stages of knowledge discovery in database with example.

2. What do you mean by clustering? Explain the K-Mean and K-Mediod algorithm with example.

3. Explain the data warehouse architecture. Differentiate between distributed and virtual data warehouse.

                                                                 Group-B

                                                  Attempt any eight questions.                                   (8x5=40)   

4. Explain the multidimensional data model with example.

5. Differentiate between OLTP and OLAP.

6. Explain the tuning and testing of Data Warehouse.

7. Differentiate between KDD and Data Mining.

8. Explain the data mining query language with example.

9. What are the advantages and disadvantages of association rules?

10. What are the types of Regression? Explain.

11. Explain the Apriori Algorithm.

12. Explain the application of mining used in WWW.

13. Write short notes (Any Two)

    a) HOLAP

    b) Hierarchy specification

    c) Spatial Database