UNIVERSITY EXAMINATIONS: 2017/2018
EXAMINATION FOR THE DEGREES OF BACHELOR OF SCIENCE IN
INFORMATION TECHNOLOGY
BIT3201A BBIT300 DATA WAREHOUSING AND DATA MINING
FULLTIME/ PART TIME/ DISTANCE LEARNING
ORDINARY EXAMINATIONS
DATE: APRIL, 2018 TIME: 2 HOURS
INSTRUCTIONS: Answer Question One & ANY OTHER TWO questions.
QUESTION ONE: 30 MARKS (COMPULSORY)
a) Describe the following approaches to data mining. 4 Marks
i. Regression
ii. Summarization
b) Define the following terms 4 Marks
i. Pruning
ii. Data binning
c) Data mining tasks can be broadly classified into two categories: Predictive Vs Descriptive models.
Explain what predictive and descriptive mean and give examples of tasks under each category.
6 Marks
d) Discuss any six desired features of cluster analysis. 6 Marks
e) Outline three application areas in each of the following data mining tasks.
6 Marks
i. Cluster analysis
ii. Classification
f) Discuss five benefits of data mining 4 Marks
QUESTION TWO: 20 MARKS
a) Describe the following thresholds applied in the process of link analysis.
4 Marks
i. Support
ii. Confidence
b) Define the following terms commonly used in link analysis. 2 Marks
i. Frequent items
ii. Confident rules
c) Discuss the major stages of the data mining process. 4 Marks
d) With the help of diagrams illustrate six ways in which the data that has been mined can be visually
presented. 6 Marks
e) Discuss four challenges facing data mining. 4 Marks
QUESTION THREE: 20 MARKS
a) Define the following terms 4 Marks
i. Data warehousing
ii. Data mining
b) By use of appropriate examples discuss the following possible discoveries from a data mining
exercise. 4 Marks
i. Time Series Analysis
ii. Sequence Discovery
iii. Link Analysis
iv. Evolution And Deviation Analysis
c) Discuss four factors that lead to the growth and popularity of data mining.
4 Marks
d) Describe any four types of data that are gathered and be mined and state the type of organizations
that gather these types data 4 Marks
e) Describe the various classification of data mining systems 4 Marks
QUESTION FOUR: 20 MARKS
a) Define an OLAP system 2 Marks
b) Discuss five characteristics of OLAP 5 Marks
c) Discuss any three factors that influence the selection and acquisition of data mining software.
3 Marks
d) Consider a retail shop with the following set of transactions
Using the Apriori algorithm find the association rules with 30% and 60% confidence.
10 Marks
QUESTION FIVE: 20 MARKS
a) Describe four measures of distance in cluster analysis. 4 Marks
b) In cluster analysis the concept inter-class similarity and intra-class similarity is key. With the help
of a diagram, differentiate between them. 4 Marks
c) Before the activity of data warehousing, the data is normally cleaned since it is dirty. Required:
i. Give any three types of dirt/noise in data 3 Marks
ii. Give any four causes of noise in data 4 Marks
d) Discuss the activities that constitute data preprocessing in preparation of data warehousing.
5 Marks
