**UNIVERSITY EXAMINATIONS: 2016/2017**

**EXAMINATION FOR THE DEGREE OF MASTERS OF SCIENCE IN DATA**

**ANALYTICS**

**MDA5204 DATA ANALYTICS AND KNOWLEDGE ENGINEERING**

**ORDINARY EXAMINATIONS**

**DATE: AUGUST, 2017 TIME: 2 HOURS**

**INSTRUCTIONS: Answer Question One & ANY OTHER TWO questions.**

**QUESTION ONE [20 MARKS]**

(a) Briefly describe the meaning of the following terms:

(i) Data Analytics (1 Mark)

(ii) Big Data (1 Mark)

(ii) Knowledge engineering (1 Mark)

(b) List characteristics of Knowledge-based Systems in the context of Data analytics and knowledge engineering.

(2 Marks)

(c) State and explain four applications of factor analysis. (2 Marks)

(d) Consider the following data set:

Given the above data set, interpret the mean and standard deviation of “good value for the money” and “Product

Reliability” ratings. (4 Marks)

(e) Big data is increasingly important in modern organizations. Discuss any four uses of big data in modern

organizations (4 Marks)

(f) Briefly discuss the interplay between the terms ‘Big Data’, ‘Data analytics’ and ‘Knowledge engineering’

(3 Marks)

(g) State and explain two motivations of Data analytics (2 Marks)

**QUESTION TWO [15 MARKS]**

(a) State and explain four types of Data analytics and illustrate how they are related. Describe one application for

each (4 Marks)

(b) Briefly explain how ‘Measures of dispersion” are used in data analytics. Use one example to illustrate your

answer (2 Marks)

(c) Consider the following figure showing IQs of 13 students enrolled in class A.

Calculate variance of the above data set (3 Marks)

(ii) Calculate standard deviation of the above data and interpret the results (2 Marks)

(d) Briefly explain the difference between the following concepts as used in data analytics and knowledge

engineering

(i) Roll up and drill down (2 Marks)

(ii) Dashboard and performance score card (2 Marks)

**QUESTION THREE [15 MARKS]**

(a) Briefly explain the following terms in the context of data analytics and knowledge engineering. Give one

example for each case (3 Marks)

(i) Factor loading

(ii) Communality

(iii)Observed variables

(b) Describe the difference between confirmation factor analysis and exploration factor analysis (2 Marks)

(c) Consider the following data set.

Use the above to calculate correlation between Temperature and sales. Interpret the results (4 Marks)

(c) The following data shows factor loading for four observable variables

Calculate use the above data set to calculate the following values

(i) Eigen values for each factor (2 Marks)

(ii) Communality value for each variable (2 Marks)

(d) Briefly explain two types of factor rotation in the context of factor analysis (2 Marks)

**QUESTION FOUR [15 MARKS]**

(a) Discuss five knowledge engineering activities. Give one practical example to illustrate each activity

(5 Marks)

(b) State and explain four participants of developing knowledge base system (4 Marks)

(c) Describe any three components of a knowledge base system (3 Marks)

(d) Consider the following knowledge base

furniture(sink, kitchen,1).

furniture(chair,lounge,4).

furniture(bed,bedroom,1).

furniture(cooker,kitchen,1).

furniture(chair,kitchen,4).

furniture(sofa,lounge,1).

Use the above knowledge base to answer the following questions

i. What query would we use to find the number of chairs in each room? (1 Mark)

ii.What query would we use to get the room with four chairs and one cooker? . (1 Mark)

iii. List all the rooms without stating items or the numbers (1 Mark