UNIVERSITY EXAMINATIONS: 2019/2020
EXAMINATION FOR THE DEGREE OF BSCIT, BSD, BBIT, BISF & BAC
BIT 3201A/ BBIT 300/ BAC 3201 – DATA MINING AND WAREHOUSING/
DATA MINING AND MANAGEMENT
FULL TIME/ PART TIME/DISTANCE LEARNING
DATE: MAY, 2020 TIME: 6 HOURS
INSTRUCTIONS: Answer ALL Questions
SECTION B: [20 MARKS]
a) Give an example situation where supporting a business decision with data mining promises
the following: [4 Marks]
i. Cost savings
ii. Better customer satisfaction.
b) Obtaining some new data may be costly. Discuss the consequences of this for data
strategy in an organization. [5 Marks]
c) Study the statement below and justify how true it is with regards to proper testing of
models. [5 Marks]
“Using a model to predict for inputs it has already seen is “not fair”. In the real world
applications, the model has to be proven by predicting on previously unseen inputs”.
d) Briefly describe TWO possible application of entropy and information gain in a data
oriented organization [2 Marks]
SECTION C: [20 MARKS]
(a) Briefly the meaning of the term “over fitting”, its symptoms and techniques that are used to
avoid it in decision trees learning [4 Marks]
(b) Discuss two clustering methods and explain using practical examples how each of them can
be applied in business enterprises [4 Marks]
(c) The data classification process includes TWO steps. Name and discuss the two steps of data
classification, giving examples where possible. [3 Marks]
(d) Rule-based classifier makes use of a set of IF-THEN rules for classification. Explain the
importance of this form of classification, and give an instance where this is applicable.
[1 Mark]
(e) Briefly explain how the following technologies can be applied by KCA University to support
teaching and learning or administration services such as enrollment. Use a practical example to
illustrate each application
(i) Data mining [2 Marks]
(iii) Data warehouse [2 Marks]
(iv) Data Mart [2 Marks]
(v) Classification [2 Marks]
