BISM2201 Principles of Business Analytics Exam

BISM2201 Principles of Business Analytics Exam

Exam information
Course code and name BISM2201 Principles of Business Analytics
Semester Semester 1, 2021
Exam type Take-home (School-based Take-home Assessment)
Exam date and time
The assessment will be available from Monday the 7th of June from 9am.
The assessment is due at 3pm on Friday the 11th of June.
Please note: you will not be able to access the assessment task after this
time.
BISM2201 Principles of Business Analytics Exam window
You have a five-day window in which you must complete your exam. You can
access and submit your exam at any time within the five-day window.
Optional: Even though you have the entire five days to complete and submit
your exam, the expectation is that it will take most students between four to
six hours to complete it.
Weighting This assessment is worth 30 percent of your total mark for this course.
Permitted materials This is an open book exam – all materials permitted.
Required/recommended materials
To complete this exam successfully you will need a computer with the
following software: Microsoft Word.
Instructions:
The exam consists of ten short-answer style questions worth a total of 100
points. The questions have the same weights (10 questions × 10 points each
= 100 points). Please answer all the questions and clearly label each answer
with reference to the question it addresses. Submit your answers as a typed
Microsoft Word document.
Exam extension/deferral
Please begin your exam as soon as possible within the available window.
However, if you become unwell or experience exceptional circumstances
while completing this exam then submit an extension request before the
due date/time.
Who to contact:
Should you have any issues about the assessment task (including technical
difficulties or to request an extension), you should contact the course
coordinator – Len Coote (l.coote@business.uq.edu.au).
Important exam condition information:
The normal academic integrity rules apply to this assessment task.
• You are not to seek outside assistance with this assessment item (other
than from the course coordinator) or to give assistance to others – giving
and/or seeking outside assistance will be deemed cheating and will result
in disciplinary action.
• You are permitted to use your prior work in the course to help construct
your answers.
By undertaking this online assessment you will be deemed to have
acknowledged UQ’s academic integrity pledge to have made the following
declaration: “I certify that my submitted answers are entirely my own work and
that I have neither given nor received any unauthorised assistance on this
assessment item”.

Question 1
Why did I ask you to read the book and/or watch the film Moneyball, and in what ways is the book/film emblematic of the analytic revolution? Specifically, how and for what purpose do the decision makers (sports teams) use analytics in Moneyball? (What is the output variable of interest, what are the likely feature variables?)
Question 2
What are the precursors to business analytics; that is, what established fields have informed the practice of business analytics and/or its domain of content? What worldview has had the most influence on the emerging field of business analytics – the data science paradigm or the social science tradition (and why)? (What might these worldviews learn from one another?)
Question 3
What are the two main pathways to becoming an analytical competitor? What pathways have Amazon and Netflix followed to become analytical competitors, have they followed the same or different pathways and where do they currently sit on their analytical journeys? (What can companies on each pathway possibly learn from companies on the other pathway if anything?)
Question 4
What is an algorithmic trading system? What are the main components of algorithm trading systems? Can you offer an example of a firm that uses an algorithm trading system(s); if yes, what is the firm? What is one of the main challenges for firms implementing algorithmic trading systems? (How does the firm you mentioned in your answer address this challenge?)
Question 5
What is a recommendation system? What are the main components of recommendation systems? Can you offer an example of a firm that implements a recommendation system(s); if yes, what is the firm? What is one of the main challenges for firms in implementing recommendation systems? (How does the firm you mentioned in your answer address this challenge?)
Question 6
What is the business analytics process? What are the key steps in the business analytics process, and why are these steps the key steps? What specific activities can business analysts undertake to improve organisational and/or stakeholder “buy-in” to an analytics project? (How should the criteria for evaluating an analytics project be developed?)
Question 7
What warrants the creation of the role of Chief Analytics Officer (CAO)? What are the key responsibilities of the role, how does the role complement existing C-suite roles – especially the roles of Chief Operations Officer (COO), Chief Marketing Officer (CMO), and Chief Information Officer (CIO)? (What firms would most benefit from the creation of a CAO role?)
Question 8
Briefly outline the roles and responsibilities of business analysts and data scientists. Are these roles complements or substitutes? Offer a rationale for your answer. The role of business analyst is sometimes described as a “boundary spanning” role – why? (Why have universities developed courses, majors, and programs in business analytics and data science?)
Question 9
What are the “big five” methods of business analytics? Which of these methods is increasingly used in implementations of business AI? What are some of the popular software platforms for business analytics? (What considerations might a business analyst/data scientist have in the choice of proprietary versus open-source software environments for analytics?)
Institute for Teaching and Learning Innovation (ITaLI) | Last updated by UQBS: 5 May 2020 3
Question 10
What is the difference, if any, between artificial intelligence (AI) and artificial general intelligence (AGI)? What are the relationships between AI, machine learning, and deep learning? How is the machine learning approach to AI different to symbolic AI? (Give an example of the machine learning approach to AI that can improve the lives of consumers.)
End of exam

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