2010 Jawaharlal Nehru Technological University, Hyderabad M.C.A JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD MCA IV Semester Supplementary Examinations July 2010 DATAWARE HOUSING AND MINING Question paper
Code No: 45
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
MCA IV Semester Supplementary Examinations July 2010
DATAWARE HOUSING AND MINING
Time: 3hours Max.Marks:60
Answer any five questions
All questions carry equal marks
- - -
1. Draw the three tire decision support information diagram depicting the summary
and detailed information.
2.a) Write about the major factors of building a data warehouse.
b) How is OLAP different from OLTP?
3.a) Write about the primitives of data mining for designing a query language.
b) Explain about major issues in mining.
4.a) Describe the data generalization & summarization based characterization
b) What is need of performing attribute relevance analysis?
5. Explain Apriori algorithm with an example
6. Explain about basic decision tree induction algorithm with an example.
7.a) Write in detail categorization of major clustering methods
b) Discuss about Bayesian classification.
8. Write short notes on:
a) DBSCAN
b) Intelligent query answering
c) Meta data
KEYWORDS:DATAWARE HOUSING AND MINING,DATAWARE HOUSING AND MINING QUESTION PAPER,JNTU,JNTU QUESTION PAPER,JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD MCA IV SEMESTER SUPPLEMENTARY EXAMINATIONS JULY DATAWARE HOUSING AND MINING
Code No: 45
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
MCA IV Semester Supplementary Examinations July 2010
DATAWARE HOUSING AND MINING
Time: 3hours Max.Marks:60
Answer any five questions
All questions carry equal marks
- - -
1. Draw the three tire decision support information diagram depicting the summary
and detailed information.
2.a) Write about the major factors of building a data warehouse.
b) How is OLAP different from OLTP?
3.a) Write about the primitives of data mining for designing a query language.
b) Explain about major issues in mining.
4.a) Describe the data generalization & summarization based characterization
b) What is need of performing attribute relevance analysis?
5. Explain Apriori algorithm with an example
6. Explain about basic decision tree induction algorithm with an example.
7.a) Write in detail categorization of major clustering methods
b) Discuss about Bayesian classification.
8. Write short notes on:
a) DBSCAN
b) Intelligent query answering
c) Meta data
KEYWORDS:DATAWARE HOUSING AND MINING,DATAWARE HOUSING AND MINING QUESTION PAPER,JNTU,JNTU QUESTION PAPER,JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD MCA IV SEMESTER SUPPLEMENTARY EXAMINATIONS JULY DATAWARE HOUSING AND MINING