Exam Details
| Subject | Data Warehousing And Mining | |
| Paper | ||
| Exam / Course | B.Tech In Computer Science And Engineering (BTCSVI) | |
| Department | School of Engineering & Technology (SOET) | |
| Organization | indira gandhi national open university | |
| Position | ||
| Exam Date | June, 2016 | |
| City, State | new delhi, |
Question Paper
No. of Printed Pages: 3
IBICS.020 1
B.Tech. -VIEP -COMPUTER SCIENCE AND ENGINEERING (BTCSVI) Term-End Examination 007Bb June, 2016
BleS-020 DATA WAREHOUSING AND MINING
Time: 3 hours Maximum Marks: 70
Note: Attempt any sevenqueE;tions. Assume suitable missing data, if any. All questions carry equal marks.
1. What is data mining Describe the steps involved in data mining when viewed as a process of knowledge discovery. 5
Draw and explain the architecture of a typical data mining system. 5
2. List out various data mining techniques. Explain in detail about any two data mining techniques with one example each.
3. Explain data scrubbing tools and data auditing tools with examples. 5
List the types of data used in-cluster analysis. 5
4. Define 'Aggregation' and 'Approximation' with respect to spatial data. 5
Differentiate between OLTP and OLAP. 5
5. Explain in brief about ETL (Extraction/Transformation/Loading) process. 5
Write and explain the characteristics of metadata. 5
6. Explain in brief about 'data mart'. How is it different from a 'database' 5
Explain KDD process. 5
7. What do you mean by data reduction? What are the strategies of data reduction 10
8. What do you mean by subject-oriented, integrated, time-variant and non-volatile collection of data in data warehouse? 5
Differentiate between star schema and snowflake schema with examples. 5
9. Explain Market Basket Analysis. 5
Explain the concept of classification. 5
10. Write short notes on any two of the following: 2x5=10
Cluster Analysis
World Wide Web
Hypercubes
IBICS.020 1
B.Tech. -VIEP -COMPUTER SCIENCE AND ENGINEERING (BTCSVI) Term-End Examination 007Bb June, 2016
BleS-020 DATA WAREHOUSING AND MINING
Time: 3 hours Maximum Marks: 70
Note: Attempt any sevenqueE;tions. Assume suitable missing data, if any. All questions carry equal marks.
1. What is data mining Describe the steps involved in data mining when viewed as a process of knowledge discovery. 5
Draw and explain the architecture of a typical data mining system. 5
2. List out various data mining techniques. Explain in detail about any two data mining techniques with one example each.
3. Explain data scrubbing tools and data auditing tools with examples. 5
List the types of data used in-cluster analysis. 5
4. Define 'Aggregation' and 'Approximation' with respect to spatial data. 5
Differentiate between OLTP and OLAP. 5
5. Explain in brief about ETL (Extraction/Transformation/Loading) process. 5
Write and explain the characteristics of metadata. 5
6. Explain in brief about 'data mart'. How is it different from a 'database' 5
Explain KDD process. 5
7. What do you mean by data reduction? What are the strategies of data reduction 10
8. What do you mean by subject-oriented, integrated, time-variant and non-volatile collection of data in data warehouse? 5
Differentiate between star schema and snowflake schema with examples. 5
9. Explain Market Basket Analysis. 5
Explain the concept of classification. 5
10. Write short notes on any two of the following: 2x5=10
Cluster Analysis
World Wide Web
Hypercubes
Other Question Papers
Departments
- Centre for Corporate Education, Training & Consultancy (CCETC)
- Centre for Corporate Education, Training & Consultancy (CCETC)
- National Centre for Disability Studies (NCDS)
- School of Agriculture (SOA)
- School of Computer and Information Sciences (SOCIS)
- School of Continuing Education (SOCE)
- School of Education (SOE)
- School of Engineering & Technology (SOET)
- School of Extension and Development Studies (SOEDS)
- School of Foreign Languages (SOFL)
- School of Gender Development Studies(SOGDS)
- School of Health Science (SOHS)
- School of Humanities (SOH)
- School of Interdisciplinary and Trans-Disciplinary Studies (SOITDS)
- School of Journalism and New Media Studies (SOJNMS)
- School of Law (SOL)
- School of Management Studies (SOMS)
- School of Performing Arts and Visual Arts (SOPVA)
- School of Performing Arts and Visual Arts(SOPVA)
- School of Sciences (SOS)
- School of Social Sciences (SOSS)
- School of Social Work (SOSW)
- School of Tourism & Hospitality Service Sectoral SOMS (SOTHSM)
- School of Tourism &Hospitality Service Sectoral SOMS (SOTHSSM)
- School of Translation Studies and Training (SOTST)
- School of Vocational Education and Training (SOVET)
- Staff Training & Research in Distance Education (STRIDE)
Subjects
- Advanced Computer Architecture
- Artificial Intelligence
- Computer Architecture
- Computer Networks
- Computer Organisations
- Cryptography And Network Security
- Data Structure
- Data Warehousing And Mining
- Database Management System
- Design and Analysis of Algorithm
- Digital Image Processing
- Discrete Maths Structure
- E-Business
- Formal Language And Automata
- Logic Design
- Microprocessor
- Mobile Computing
- Object Oriented Programming
- Operating Systems
- Parallel Algorithms
- Pattern Recognition
- Principles of Programming Lang.
- Real Time Systems
- Software Engineering
- Software Quality Engineering
- Software Reusability
- System Programming And Compiler Design
- Theory Of Computation
- Unix Internals And Shell Programming
- Web Technology