Browse papers
A

Section A: Long Answer Questions

Attempt any TWO questions.

3 questions·10 marks each
1long10 marks

Explain the architecture of a data warehouse. Differentiate between MOLAP, ROLAP, and HOLAP.

data-warehouseolap
2long10 marks

Explain the FP-growth algorithm for frequent pattern mining with an example. How does it improve upon Apriori?

association-rulesfp-growth
3long10 marks

What is classification? Explain the ID3 decision tree algorithm and build a decision tree for a given training dataset.

classificationdecision-tree
B

Section B: Short Answer Questions

Attempt any EIGHT questions.

9 questions·5 marks each
4short5 marks

What is a data mart? How does it differ from a data warehouse?

data-mart
5short5 marks

Explain the snowflake schema with an example.

schema
6short5 marks

Define support and confidence in association rule mining.

association-rules
7short5 marks

What is data cleaning? Explain methods to handle missing values.

preprocessing
8short5 marks

Explain the working of the Naive Bayes classifier.

classificationnaive-bayes
9short5 marks

What is the difference between supervised and unsupervised learning?

machine-learning
10short5 marks

Explain hierarchical clustering briefly.

clustering
11short5 marks

What is a fact table and a dimension table?

schema
12short5 marks

Write short notes on metadata in data warehousing.

metadata