DATA WAREHOUSING AND DATA MINING

1.Briefly discuss.
a) Virtual datawarehouse Vs Data mart.
b)Kneapsort Neighbor classifier.
c)Multi dimensional databases.
d)Bagging.
e)Pruning.
f)Synchronous generalization.
g)Segmentation by Natural Partitioning.
h)Strategies of data reduction.
1. Discuss about the efficient computation of data cubes.
2. explain architecture for on-line analytical mining.
3. Explain the methods of decentralization and hierarch generation for categorical data.
4. a) As a marketing manager of All Elecronics, characterize the buying habits of customers who purchases items priced at no less that $100, with respect to the customer’s age and type of item purchased, and the place in which the item was made.
b) Discuss about functional components of Data mining GUI.
6. a) How to implement attribute oriented induction technique?
b) Explain the Associate rule mining using market basket analysis.
7. a) What is classification and what is prediction and how to prepare data for classification and prediction?

8. Explain how back propagation is useful for classification of data.