Course coordinator
Dr Thomas Magor
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Business School
This project-based course uses live case studies to deliver a signature learning experience in business analytics. Participating businesses offer for study an analytics problem or strategic decision. Further, the partner businesses will make relevant decision-makers and information available to the students. Each student focuses on one of the participating businesses, meeting with their key decision makers and addressing their project to the needs of the partner business. Working under academic supervision, students develop project plans, and write and present their project reports to an audience including representatives of their partner businesses. Finally, each student delivers its partner business with a decision support system embedding its analytics in a graphical user interface. A lecture series on the principles of agile analytics complements the project-based learning.
BSAN4204 is the capstone course of the Business Analytics major of both the Bachelor of Advanced Business and Bachelor of Commerce programs. It requires students to research the technical requirements needed to solve a business problem provided by an industry partner, develop a prototype and deliver a functioning business analytics application. Students will work under the direction of both academic advisors (the BSAN4204 teaching team) and the industry partner. The BSAN4204 teaching team will be available throughout the semester to facilitate and guide students through their projects. The industry partner will be available at specific times in the semester to offer feedback and business guidance on the feasibility of projects as they develop.
The course concludes with students conducting a research project on emerging technologies in business analytics. This project also serves to encourage students to reflect on their completed projects, as well as their progress through the business analytics major. Part of this research project will comprise considering what future personal professional skill development they may need to engage in beyond their graduation to solve the business problems of the future.
Course requirements
Prerequisites
You'll need to complete the following courses before enrolling in this one:
(BISM2201 + 2204) or (BSAN2201 + 2204)
Incompatible
You can't enrol in this course if you've already completed the following:
BISM4204
Course contact
Course staff
Lecturer
Dr Thomas Magor
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Please note: Teaching staff do not have access to the timetabling system to help with class allocation. Therefore, should you need help with your timetable and/or allocation of classes, please ensure you email business.mytimetable@uq.edu.au from your UQ student email account with the following details:
- Full name
- Student ID
- Course Code
Aims and outcomes
This capstone course aims to provide students with unique opportunities to approach and solve authentic business problems, working collaboratively with industry and academic stakeholders, using innovative business analytic skill sets.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Recognise and explain the application of business analytics to solving practical and strategic business problems.
LO2.
Understand how the principles and methods of business analytics can address business problems and improve business performance.
LO3.
To create a project proposal for the design and development of a business analytics project that addresses a problem faced by business, government or society.
LO4.
Apply a range of software tools for completing analytics projects and embedding analytics into decision support systems.
LO5.
Assess the value of analytics projects to business and the costs and benefits of investments in analytics projects and teams.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Poster, Product/ Design |
A1 Project Proposal/Prototype
|
20% |
19/03/2025 4:00 pm |
| Computer Code, Project |
A2 Analytics Project
|
40% |
7/05/2025 4:00 pm |
| Product/ Design, Reflection |
A3 Research Project and Reflection
|
40% |
28/05/2025 4:00 pm |
Assessment details
A1 Project Proposal/Prototype
- Mode
- Product/ Artefact/ Multimedia
- Category
- Poster, Product/ Design
- Weight
- 20%
- Due date
19/03/2025 4:00 pm
- Other conditions
- Student specific, Work integrated learning.
- Learning outcomes
- L01, L02, L03
Task description
This task requires students to conduct research on the technical requirements for an initial prototype for an online application as a proposed solution to solve a business problem provided by an industry partner, using either their own data or a dataset provided in class. The prototype should be delivered in the form of a 1-2 page description of the envisaged analytics solution in response to the industry partner briefing. Students are encouraged to use an "infographic" style of presentation that both depicts and explains the functional form of the online application as a proposed solution and how it addresses the business problem. The purpose of the prototype is for student to research a range of possible solutions so that feedback from project supervisors and teaching team can be received early in the development process.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
A2 Analytics Project
- Mode
- Product/ Artefact/ Multimedia
- Category
- Computer Code, Project
- Weight
- 40%
- Due date
7/05/2025 4:00 pm
- Other conditions
- Student specific, Work integrated learning.
- Learning outcomes
- L04, L05
Task description
This task requires students to deliver a fully functional form of their prototype that addresses the briefing provided by the industry partner using either their own data or a dataset provided in class. The application should be based on their initial prototype, implementing feedback provided by the industry partner and academic supervisors. The assessment submission will comprise a URL link to a functioning implementation and deployment of the application. The task is to produce data-driven insights that address the business problem in an effective, technically sound, and creative way. The application should include features which guide users on how to use the application with clear and concise language, navigational buttons, and structuring the application using a layout that ensures a good user experience as well as delivering robust analysis of the data. The application must include documentation (e.g., as a section/page/tab within the application) which provides a technical summary of how the application works.
The weekly workshop sessions cover how create an R Shiny dashboard hosted on rshinyapps.io, however students may decide use any combination of technologies and platforms which they independent research to create their application.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
A3 Research Project and Reflection
- Mode
- Written
- Category
- Product/ Design, Reflection
- Weight
- 40%
- Due date
28/05/2025 4:00 pm
- Other conditions
- Student specific.
- Learning outcomes
- L01, L02, L05
Task description
This task requires students to conduct research on currently emerging technologies of business analytics and to propose a future business analytics project which addresses a business problem (either the one provided by the industry partner addressed in the project, or a completely different business problem in another domain of business analytics). This requires students to reflect on their completion of the first two assessments and to identify what were some of the technological limitations or barriers they encountered which could be overcome by using currently emerging technologies. A secondary objective of this task is to encourage students to reflect upon and research what personal professional skill development they may need to engage in beyond their graduation to solve the business problems of the future, and to outline these as part of the necessary steps towards delivering the project proposal.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submission link on Blackboard
Deferral or extension
You may be able to apply for an extension.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0 - 29 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30 - 46 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 84 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
Grades will be allocated according to University-wide standards of criterion-based assessment.
Supplementary assessment
Supplementary assessment is available for this course.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 1 |
Seminar |
Kick off, Student Team Formation Team formation exercise, industry partner business problem briefing Learning outcomes: L01 |
Week 2 |
Seminar |
Setting up Shinyapps.io, R Shiny walk-through Setting up Shinyapps.io, R Shiny walk-through. Students to finalise their team formations and begin working on project prototype Learning outcomes: L01, L02 |
Week 3 |
Seminar |
R Shiny App design workshop R Shiny App design workshop. Students in their teams to continue working on their project prototype. Learning outcomes: L01, L02, L04, L05 |
Week 4 |
Seminar |
Drop-In session Drop-In session to receive advice on project prototype before submission. Project prototype due this week. Learning outcomes: L01, L02, L04, L05 |
Week 5 |
Seminar |
R Shiny App design workshop Learning outcomes: L01, L02, L04, L05 |
Week 6 |
Seminar |
R Shiny App design workshop Learning outcomes: L02, L04 |
Week 7 |
Seminar |
R Shiny App design workshop Learning outcomes: L01, L02, L04, L05 |
Week 8 |
Seminar |
R Shiny App design workshop Learning outcomes: L01, L02, L04, L05 |
Mid-sem break |
No student involvement (Breaks, information) |
In-Semester Break No class this week |
Week 9 |
Seminar |
R Shiny App design workshop Learning outcomes: L01, L02, L04, L05 |
Week 10 |
Seminar |
Drop-in Session Drop-In session to receive advice on project before submission. Project due this week. Learning outcomes: L01, L02, L04, L05 |
Week 11 |
Seminar |
Drop-in Session Drop-in Session to discuss work on reflection essay. Learning outcomes: L01, L02, L03, L04, L05 |
Week 12 |
Seminar |
Drop-in Session Drop-in Session to discuss work on reflection essay. Learning outcomes: L01, L02, L03, L04, L05 |
Week 13 |
Seminar |
Course Review and Reflection Final seminar to close out semester. In this session we will discuss contemporary issues in business analytics, focusing on topics, trends and technologies which have emerged during the course. Learning outcomes: L01, L02, L03, L04, L05 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.