QUESTION BANK
1. Explain the concept of building a data warehouse.
2. Describe data cubes with suitable example.
3. Define data warehouse. What strategies should be taken care while designing a warehouse.
4. Explain client server computing model for data warehouse.
5. Explain the OLAP operations with example.
6. Differentiate between OLAP and OLTP.
7. Explain warehouse management and support processes.
8. Explain hardware and software used in data warehouse.
9. Explain all the steps for warehouse planning and implementation.
10. Discuss distributed databases with architecture.
11. Elaborate data integration and transformation in data mining
12. Explain data cleaning and phases of data cleaning.
13. Describe decision trees with the help of example.
14. llustrate data reduction. Write down the various strategies for data reduction
15. Discuss hierarchical clustering algorithm.
16. What is partitioning clustering. Explain K-means clustering with example.
17. Differentiate between
[1] Web Mining, Spatial Mining and Temporal Mining.
[2] OLAP Servers: ROLAP, MOLAP, HOLAP
[3] Grid Based Methods- STING, CLIQUE.
[4] Density Based Methods DBSCAN, OPTICS
18. Discuss Datawarehouse Security, Backup and Recovery
19. Describe data visualization reference to data mining
