Course coordinator
Dr Len Coote
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Business School
Data science is transforming business and the ways in which the applied business disciplines are practiced. The field of business analytics has emerged as a result of application of the application of data science to business problems. This course introduces students to the fundamental principles of business analytics. The course aims to firstly, provide students with an appreciation of how business analytics are changing business practices and second, to offer a specific overview of key topics in business analytics including predictive modelling.
The success of businesses such as Google, Netflix, and WeChat tell us the world of business is changing and becoming increasingly data-driven. The emergence of specialist consulting firms like Quantium and the development of practice areas in business analytics by the "big four" consulting firms are also emblematic of this shift in business thinking and practice -- reflecting the growing importance of analytics to many businesses. A purpose of the business analytics major is to equip students with the data and statistical literacy increasingly needed to be successful in business. BSAN2201 Principles of Business Analytics provides an introduction to and overview of the many challenges businesses confront in building an analytics capability. Emphasis is placed on developing an appreciation of the domains and methods of business analytics, with a particular emphasis on the domains and successful pathways through to the organisational implementation and achievement of an analytics advantage.
Course requirements
Prerequisites
You'll need to complete the following courses before enrolling in this one:
8 units of study in any discipline
Recommended companion or co-requisite courses
We recommend completing the following courses at the same time:
BSAN2204
Incompatible
You can't enrol in this course if you've already completed the following:
BISM2201
Course contact
Course staff
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, and
- the Course Code
Aims and outcomes
The broad aim of the course is to provide students with an overview of the domains of business analytics and how the application of analytics to those domains can improve organisational performance. The domains include accounting/financial, people/talent, operations, marketing, social media, and supply chain analytics. Methods of business analytics are previewed -- but they are the focus of the companion course: BSAN2204 Methods of Business Analytics.ﾠ The Principles course has the aim of building understanding of business analytics and its potential applications to business, and understanding the change management processes that might be required to support its successful adoption by organisations.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Recognise and explain the importance of business analytics to managerial decision making
LO2.
Explain the basic concepts used in business analytics and their applications to managerial decision making
LO3.
Identify and apply the appropriate methods of business analytics for solving a range of business problems
LO4.
Compare and critically evaluate the various approaches to business analytics, and
LO5.
Evaluate the value of business analytics for improving managerial and strategic decision making.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Essay/ Critique | Article Review | 30% |
2/09/2024 - 6/09/2024 |
| Paper/ Report/ Annotation, Presentation | Case Study and Presentation | 60% |
21/10/2024 - 25/10/2024 |
| Reflection | Reflection | 10% |
4/11/2024 - 15/11/2024 |
Assessment details
Article Review
- Mode
- Written
- Category
- Essay/ Critique
- Weight
- 30%
- Due date
2/09/2024 - 6/09/2024
- Learning outcomes
- L01, L02
Task description
A review of articles on business analytics. More details about the format, style, etc. will be discussed in class and provided on Blackboard.
Artificial Intelligence (AI) provides emerging tools that may support students in completing this assessment task. Students may appropriately use AI in completing this assessment task; however, students must clearly reference any use of AI in each instance. A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Via 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.
Case Study and Presentation
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Presentation
- Weight
- 60%
- Due date
21/10/2024 - 25/10/2024
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
Development of a written industry case study on an application of business analytics. More details about the format, style, etc. will be discussed in class and provided on Blackboard.
Artificial Intelligence (AI) provides emerging tools that may support students in completing this assessment task. Students may appropriately use AI in completing this assessment task; however, students must clearly reference any use of AI in each instance. A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Via 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.
Reflection
- Mode
- Oral
- Category
- Reflection
- Weight
- 10%
- Due date
4/11/2024 - 15/11/2024
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A reflective assessment where students are are asked to record a video of themselves briefly presenting on their key learnings from the course and on how these learnings differ from their previous perspectives and experiences. Note the reflective assessment is scheduled to be submitted during the examination period.
More details regarding the reflective assessment will be discussed later in the semester and provided on Blackboard.
Artificial Intelligence (AI) provides emerging tools that may support students in completing this assessment task. Students may appropriately use AI in completing this assessment task; however, students must clearly reference any use of AI in each instance. A failure to reference generative AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Via 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) | 85 - 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 |
Lecture |
Introduction and A1 Overview Learning outcomes: L01 |
Week 2 |
Lecture |
What is Business Analytics? Learning outcomes: L01, L02 |
Tutorial |
What is Business Analytics and A1 Check-In Learning outcomes: L01, L02 |
|
Week 3 |
Lecture |
The Analytics Advantage Learning outcomes: L01, L02 |
Tutorial |
The Analytics Advantage and A1 Check-In Learning outcomes: L01, L02 |
|
Week 4 |
No student involvement (Breaks, information) |
Royal Queensland Show Holiday Royal Queensland Show Public Holiday - Wednesday 14 Aug 2024 - Check Blackboard for announcements about affected classes. |
Week 5 |
Lecture |
Competing on Analytics: Internal Applications Learning outcomes: L03, L04 |
Tutorial |
Competing on Analytics (Internal Applications) and A1 Check-In Learning outcomes: L03, L04 |
|
Week 6 |
Lecture |
Competing on Analytics: External Applications Learning outcomes: L03, L04 |
Tutorial |
Competing on Analytics (External Applications) and A1 Check-In Learning outcomes: L03, L04 |
|
Week 7 |
Lecture |
Developing Analytics Capability Learning outcomes: L03, L04, L05 |
Tutorial |
Developing Analytics Capability and A1 Check-In Learning outcomes: L03, L04, L05 |
|
Week 8 |
Lecture |
The Business Analytics Process and A2 Overview Learning outcomes: L03, L04, L05 |
Tutorial |
The Business Analytics Process and A2 Check-In Learning outcomes: L03, L04, L05 |
|
Week 9 |
Lecture |
Methods and Technologies of Business Analytics Learning outcomes: L03, L04, L05 |
Tutorial |
Methods and Technologies of Business Analytics and A2 Check-In Learning outcomes: L03, L04, L05 |
|
Mid Sem break |
No student involvement (Breaks, information) |
In-Semester Break |
Week 10 |
Lecture |
Data for Business Analytics Learning outcomes: L01, L02, L03 |
Tutorial |
Data for Business Analytics and A2 Check-In Learning outcomes: L01, L02, L03 |
|
Week 11 |
Lecture |
Artificial Intelligence and Machine Learning Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Artificial Intelligence and Machine Learning and A2 Check-In King's Birthday Public Holiday - Monday 7 Oct 2024 - Check Blackboard for announcements about affected classes. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 12 |
Lecture |
Deep Learning and Beyond Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Deep Learning and Beyond and A2 Check-In Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 13 |
Lecture |
Revision and A3 Preparation Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Revision and A3 Check-In 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 - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.