CIS8008 Business Intelligence

CIS8008 Business Intelligence Semester 1 2020 Examination Period
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FACULTY OF BUSINESS, EDUCATION, LAW AND ARTS
Course code: CIS8008Course Name: Business Intelligence
Examination Period: Semester 1, 2020Examination Duration:
Total examination marks:
36 hours 0 minutes
One-hundred (100)
Examiner: MICHAEL LANEModerator: ANUP SHRESTHA

USQ has replaced end of semester paper-based examinations, in line with Government requirements
around COVID-19 social distancing, as notified on 18 March. Face-to-face Formal Paper-Based
Examinations have been replaced with an online examination or an alternative form of assessment.
In this course, the face-to-face examination will be replaced with exam alternative assessment
consisting of two separate Parts A and B:

Part A:
Online Exam
(Moodle Quiz)
• Type/conditions of the exam/assignment:
Open Book Exam
30 Multiple Choice Questions
• How it will be submitted?
Via a link in the Assessment Tab in section labelled End of
Semester Examination The link is labelled Examination Part A:
Online Exam (Moodle Quiz). Students should hit ‘Submit’ button to
finalise their response.
• How long it will be open for?
For 36 hours from the start date and time of exam 11th June 2:30
pm AEST until 13th June 2:30 am AEST
• Online Exam (Moodle Quiz) Duration:
60 minutes
• How many attempts are permitted?
1 attempt only
Part B:
Take Home Exam
• Type/conditions of the exam/assignment:
Open Book Exam
7 Short Answer Questions
• How it will be submitted?
Via a link in the Assessment Tab in section labelled End of
Semester Examination Part B: Take Home Exam. The link is
labelled “Submit Your Part B Take Home Exam Answers Here”
• How long it will be open for?
For 36 hours from the start date and time of exam 11th June 2:30
pm AEST until 13th June 2:30 am AEST

Any non-USQ copyright material used herein is reproduced under the provisions of Section 200 (1) (b) of the Copyright Amendment Act
1980.
CIS8008 Business Intelligence Semester 1 2020 Examination Period
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Exam Part A Moodle Quiz (Multiple Choice Questions) is worth a total of thirty (30) marks.
• You are required to answer thirty (30) multiple choice questions.
• Please attempt Part A of the Examination via the link on the CIS8008 Course Study Desk
Assessment Tab under End of Semester Examination section labelled: Exam Part A
Moodle Quiz (Multiple Choice Questions)
End of Part A of Examination
Part B of Examination starts on next page
CIS8008 Business Intelligence Semester 1 2020 Examination Period
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Part B Take Home Exam consists of seven (7) compulsory questions worth 10 marks each
and 70 marks in total
• Please write no more than about one (1) A4 page for your answer to each question
• Use each question as the heading for your answer to each question started on a new
page
• Drawing on relevant Modules 1 to 11 and related literature, your answers should be
written in Your Own Words as your Take Home Exam answers document when
submitted is also automatically submitted to Turnitin to check for plagiarism and
collusion. You will not have access to the Turnitin Originality Report.
• Your answers to Part B Take Home Exam must be in word document format .docx or
.doc or .rtf
• Submit your Part B Take Home Exam Answers document via CIS8008 Course Study Desk
Assessments Tab under End of Semester Examination section Link labelled: Submit Your
Part B Take Home Exam Answers Here
Question One (10 Marks)
Decision support systems have evolved into data analytics and now play a key role in
supporting data driven decision making in big data era and the Fourth Industrial Revolution.
Identify and discuss three key drivers of the Fourth Industrial Revolution underpinned by
data analytics and machine learning.
Question Two (10 Marks)
Identify and describe the four main steps in data pre-processing. For each of these four
main steps of data pre-processing identify and discuss one key method used.
Question Three (10 Marks)
The following confusion matrix was generated to evaluate performance of a classification
model using a Decision Tree for predicting whether a patient has Alzheimer’s disease or not.
YES being True a patient has Alzheimer’s disease; and NO being False a patient does not
have Alzheimer’s disease. Using this Confusion Matrix:

PredictedPredicted
YesNo
ActualYes17037
ActualNo36105

a) State the formula used, calculate and discuss what the Accuracy Rate tell us about the
above model for predicting if a patient has Alzheimer’s disease.
b) State the formula used, calculate and discuss what the Sensitivity Rate tells us about the
above model for predicting if a patient has Alzheimer’s disease.
c) State the formula used, calculate and discuss what the Specificity Rate tells us about the
above model for predicting if a patient has Alzheimer’s disease.
d) State the formula used, calculate and discuss what the F1 Score tells us about above
model for predicting if a patient has Alzheimer’s disease.
CIS8008 Business Intelligence Semester 1 2020 Examination Period
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Question Four (10 Marks)
Describe the term Social Media Analytics and discuss the impact of social media sites like
Facebook and Twitter can have on customer sentiment and how this can be measured using
social media analytics.
Question Five (10 Marks)
Describe what is meant by the term Stream Analytics and provide an example of how
stream analytics is being used in a real-world situation. Discuss two key benefits that are
being realised in your example.
Question Six (10 Marks)
Describe the four major aspects of Internet of Things (IoT) Technology Infrastructure and
explain how IoT technology could be used in a hospital ward to improve and complement
patient care with two specific examples
Question Seven (10 Marks)
Analytics and Artificial Intelligence (AI) rely on identifying patterns in large amounts of data
to accurately predict outcomes which are often used in automation of operational decision
making. However exceptional events like the recent bush fires in Australia and globally the
COVID-19 Pandemic can play havoc with the accuracy and reliability of algorithms
underpinning analytics and data driven decision making. Discuss how these analytics
algorithms should be evaluated and made more reliable and robust in dealing with
exceptional events, changing contexts and norms.
END OF EXAMINATION