nielit.gov.in : C Level Course Data Warehousing & Mining Paper 2017

Name of the Organisation : National Institute of Electronics & Information Technology
Examination : C Level Course
Document Type : Sample Question Paper
Year : 2017
Name of the Subject : Data Warehousing And Data Mining

Website : http://beta.nielit.gov.in/content/january-2017
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C Level Course Data Warehousing & Mining Paper

Time: 3 Hours
Total Marks: 100
Note :
1. Answer question 1 and any FOUR from questions 2 to 7.
2. Parts of the same question should be answered together and in the same sequence.

Related : C Level Course Multimedia Systems Question Paper 2017 : www.pdfquestion.in/13073.html

1. a) Differentiate between OLAP and OLTP.
b) Differentiate between Classification and clustering.
c) Define Composite Aggregates with an example.
d) What are decision trees?
e) Describe the types of situations that produce sparse or dense data cubes.
f) What is Concept Hierarchy? Describe why Concept Hierarchies are useful in data mining?
g) What is the use of Regression? (7×4)

2. a) What are the similarities and the differences between Star schema and snowflake schema? State their advantages and disadvantages.
b) What is Data generalization? Discuss basic principle of Attribute Oriented Indication.
c) Discuss distributive, algebraic and holistic measures. (8+7+3)

3. a) What is metadata? Explain.
b) What are data marts? How they are different from traditional data warehouses?
c) What is multidimensional data model? Explain. (6+6+6)

4. a) How multilevel association rules can be mined efficiently using concept hierarchy?
b) What is the purpose of Apriori Algorithm?
c) List out the OLAP operations in multidimensional data model. (6+6+6)

5. a) Compare the advantages and disadvantages of eager classification versus lazy classification.
b) Briefly describe the classification processes using genetic algorithms, rough sets and fuzzy sets. (9+9)

6. a) Briefly describe the clustering methods. Give examples in each case.
b) Briefly discuss the data smoothing techniques. (12+6)

7. a) Given then Bayesian network shown in below figure, compute the following probabilities:
i) P(B=good, F=empty, G=empty, S=yes)
iii) P(B=bad, F=empty, G=not empty, S=no)
iii) Given that the battery is bad, computer the probability that car will start
b) Write a short note on web usage mining.
c) What is time series database? (8+6+4)

BE6-R4- Data Warehousing And Data Mining :
1. a) Give one example each of numeric, ordinal, nominal and binary attribute from a health care database.
b) Differentiate between Classification and Regression with the help of an example.
c) What is k-fold cross-validation?
d) List and explain methods to handle missing data?
e) What are outliers? How are they useful in data analysis?
f) What is Principle component analysis? How it is used for dimension reduction?
g) What is the difference between the OLAP and OLTP? (7×4)

2. a) Explain snowflake schema with the help of an example.
b) Differentiate between ROLAP and MOLAP server architecture with help of neat diagram. (9+9)

3. a) What is data mart? How is it related to data warehouse?
b) Write an algorithm for K-Nearest neighbor classification?
c) What is the difference between gini index and entropy? (6+6+6)

4. Consider the following data set shown in table where bank officials need to build decision tree to classify bank loan applications by assigning applications to one of the three risk classes that is A, B, C Draw the decision tree for the above table using ID3 algorithm? (18)

5. a) Given the set F = {a(100), b(75), c(50), d(25), bc(50), bd(20), bcd(5)} of frequent item-sets with the support counts in bracket. List all association rules with one item of LHS that can be generated from F. Compute confidence of each rule.
b) What are the different methods to test the performance of a classifier? (10+8)

6. Write Short-notes on
a) Web Data Mining
b) Text Mining
c) Neural Networks (6+6+6)

BE7-R4: Software Testing And Quality Management :
1. Each question below gives a multiple choice of answers. Choose the most appropriate one and enter in the “OMR” answer sheet supplied with the question paper, following instructions therein. (1×10)
1.1 Which is the reputed testing standard?
A) M Bridge awards
B) QAI
C) ISO
D) Microsoft

1.2 You are performing a test to see that it complies with the user requirement that a certain field be populated by using a drop down box containing a list of values. What kind of testing are you doing?
A) White box testing
B) Black box testing
C) Load testing
D) Regression testing

1.3 Test Readiness review is conducted by the
A) Project Manager
B) Test Manager
C) Quality Assurance Personnel
D) User/Customer

1.4 If the measurement taken by the two people are same refers to the terms as
A) Reliability
B) Validity
C) Calibration
D) Ease of use and simplicity

1.5 Which testing is concerned with behavior of whole product as per specified requirements?
A) Acceptance testing
B) Component testing
C) System testing
D) Integration testing

1.6 Who is responsible for component testing?
A) Software tester
B) Designer
C) User
D) Developer

1.7 Which of the following is not other name for structural testing?
A) White box testing
B) Glass box testing
C) Behavioral testing
D) None of the option

1.8 What are the types of requirement in Quality Function Deployment (QFD)?
A) Known, Unknown, Undreamed
B) User, Developer
C) Functional, Non-Functional
D) Normal, Expected, Exciting

1.9 What kind of approach was introduced for elicitation and modelling to give a functional view of the system?
A) Object Oriented Design (by Booch)
B) Use Cases (by Jacobson)
C) Fusion (by Coleman)
D) Object Modeling Technique

1.10 FAST stands for
A) Functional Application Specification Technique
B) Fast Application Specification Technique
C) Facilitated Application Specification Technique
D) None of the mentioned