Dr Ali Darvishi
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Postgraduate Coursework
- Location
- External
- Attendance mode
- Online
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Business School
A business analytics project, like any ICT project, requires careful planning, analysis and management to ensure successful completion. This course introduces students to project management principles, in the context of large multi-disciplinary big data initiatives. It provides students with knowledge and skills in estimating risks, identifying stakeholders, understanding human and organisational factors, project leadership, and project controlling/management.
Managing Analytics Projects is offered as a part of the UQ’s Master of Business Analytics program. The course focuses on teaching the knowledge and skills required to manage a business analytics project. The topics cover the development of a typical system from the initial concept to the closing of the project and handover of the system as a business as usual system.
The course is organised into four different modules:
- BA project management Introduction: an introduction to approaches suitable for a business analytics project, including setting the scene for the kickstart;
- Business Analytics Project Ignition: kickstarting a business analytics project;
- Controlled burns and fire containment: daily management of business analytics projects during delivery and organisational change;
- Extinguishing the fire but not the flame: realising the benefits from a BA Project
The course is built in a learning platform rich with an engaging learning experience. Each module is a blend of self-directed learning materials, professionally aligned assessments, case examples, social discussions, and interactive live sessions.ﾠAll the live sessions will be recorded and provided to students to enable flexible learning.
Course requirements
Recommended companion or co-requisite courses
We recommend completing the following courses at the same time:
BSAN7205 OR DATA7001
Restrictions
MBusAn, MDataSc
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
- Course Code
Aims and outcomes
This course aims to provide you with the opportunity to acquire the ﾠknowledge and skills that areﾠ needed toﾠ be a successful project manager, a contributing team member or an engaged stakeholder for a business analyticsﾠ project.
The course builds on related concepts from ﾠBusiness Analytics Foundations such as design thinking, business case development. These concepts are extended and additional concepts and skills introduced and applied, such as a specific approach to business analytics projects, in ﾠreadiness for the capstone project. The course also provides a further opportunity to grow team skills and uses this experience to reflect on team management demands.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Effectively appraise, judge and defend analytic projects and champion organisational change for a range of stakeholders.
LO2.
Design analytic projects aimed at high velocity industries and environments through practical approaches such as the business case, project plan, and test strategy.
LO3.
Manage project group dynamics to achieve agreed ethical, financial, temporal, and organisational objectives and expectations.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Paper/ Report/ Annotation, Presentation |
Business Case with Pitch
|
40% |
3/09/2024 3:00 pm
The above due date and time is when the report and video of the pitch is due. Team pitches will be presented utilising the team’s video during the live session either this week or next. |
| Project |
Individual Report
|
40% |
1st iteration 30/09/2024 3:00 pm 21/10/2024 3:00 pm |
| Reflection | Reflective Report | 20% |
4/11/2024 3:00 pm |
Assessment details
Business Case with Pitch
- Team or group-based
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Presentation
- Weight
- 40%
- Due date
3/09/2024 3:00 pm
The above due date and time is when the report and video of the pitch is due.
Team pitches will be presented utilising the team’s video during the live session either this week or next.
- Other conditions
- Peer assessed.
- Learning outcomes
- L01, L02, L03
Task description
This is a group assessment with multiple components. The assessment requires teams to:
- Write a project management focused business case (20%),
- Conduct a pitch (10%),
- Respond to Q&A (5%) and
- Complete peer assessment (5%) after the assessment has been submitted. All peer assessments will be due one week after the submission due date.
Groups will be formed over Weeks 1 and 2. The group size will depend on the number of enrolments for the semester. This will be announced by the course coordinator in Week 1.
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.
More details can be found on the task sheet in the Assessment Folder on Blackboard, including arrangements for groups that cannot attend the live lecture to present.
Submission guidelines
The Business Case, Video and Peer Assessment will be submitted via the course's Learn.UQ site.
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.
Individual Report
- Mode
- Written
- Category
- Project
- Weight
- 40%
- Due date
1st iteration 30/09/2024 3:00 pm
21/10/2024 3:00 pm
- Other conditions
- Longitudinal.
- Learning outcomes
- L01, L02
Task description
The business case from Assessment 1 forms the base of the now individual project plan that is at the centre of this assessment submission.
An iteration of the report must be submitted by the end of Week 10.
After submission of the iteration, you will receive details of a disruptor. The disruptor is to see how you propose to address the issue and to test your project plan in areas such as adaptability, resiliency, risk management and contingency planning. It will also test you as a project manager as parts of the disruptor may mean that you need to approach management and disagree with them with evidence to support such a position.
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.
Further details can be found in the task sheet on Blackboard.
Submission guidelines
This assessment will be submitted via the course's Learn.UQ site.
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.
Reflective Report
- Mode
- Written
- Category
- Reflection
- Weight
- 20%
- Due date
4/11/2024 3:00 pm
- Learning outcomes
- L01
Task description
Reflection is an important skill in agile approaches. While in agile approaches it is undertaken with others, here this assessment is an individual activity. The task is to write a reflective report that is to cover the areas stated on the task sheet available 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. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submissions independent of AI tools.
Submission guidelines
This assessment will be submitted via the course's Learn.UQ site.
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 |
|---|---|---|
Multiple weeks From Week 1 To Week 2 |
Not Timetabled |
Topic 1.1: The BA project management journey Self-Directed Learning: This is a two week module where you will take the first steps in navigating the journey of a business analytics project. We will consider: the differences between a business analytics project and business as usual, the required skills needed for your business analytics project, and evaluate the options available to kickstart a business analytics project. Learning outcomes: L01 |
Week 1 |
Workshop |
Welcome session and course introduction This week we will have a short introduction to the course and introduce the course content by running a simulation. Learning outcomes: L01 |
Week 2 |
Workshop |
Simulation and project discussion This week we will run the simulation again, finalise groups for the project and discuss the project. Learning outcomes: L01 |
Week 3 |
Not Timetabled |
Topic 1.2:Setting the scene for a kickstart Self-Directed Learning: This topic will continue to discuss recommendations for the management of a business analytics project. This week will mainly concentrate on the kickstart of the project when using CRISP-DM embedded in Scrum. Learning outcomes: L01, L03 |
Team Based Learning |
Project Squad The main focus will be on kickstarting your project. Together will undertake an exercise using a generic project and then we will consider the group projects. Learning outcomes: L03 |
|
Week 4 |
Not Timetabled |
Topic 2.1 Business understanding Self-Directed Learning: This topic considers a number of ways that business understanding can be gained. It will consider the application of CRISP-DM and facilitating workshops involving key stakeholders, utilising a range of techniques. Learning outcomes: L01, L02 |
Workshop |
Live Session This is the first part a simulation of a workshop to assist with Assessment 1. Groups will simulate a workshop that would be run for their projects by role playing the stakeholders and applying the recommended techniques. Learning outcomes: L02, L03 |
|
Week 5 |
Not Timetabled |
Topic 2.2: Data understanding Self-Directed Learning: This topic examines questions related to the data that will be needed for the project from a business case/project management perspective and delivery road maps. Learning outcomes: L02, L03 |
Workshop |
Live Session This is the second part of a simulated workshop to assist with Assessment 1. Groups will simulate a workshop that would be run for their projects by role playing the stakeholders and applying the recommended techniques. Learning outcomes: L02, L03 |
|
Week 6 |
Not Timetabled |
Topic 2.3: Ethics and project management practices Self-Directed Learning: This topic is to allow some time to consider holistically how to avoid or mitigate common ethical dilemmas or issues that arise in business analytics project management. Learning outcomes: L01, L03 |
Workshop |
Live Session Ethics Debate Learning outcomes: L01, L03 |
|
Week 7 |
Not Timetabled |
Module 2 Conclusion Self-Directed Learning: This week's self directed study is to focus on concluding this module's work. Learning outcomes: L01, L02, L03 |
Team Based Learning |
Project Pitches Note: this session may be more than one hour. Therefore, there may be no live session in Week 8, or Week 8 will be used to complete pitches if required. Learning outcomes: L01, L02, L03 |
|
Week 8 |
Not Timetabled |
Topic 3.1 Daily Project Life and Challenges Self-Directed Learning: This topic considers the management of a business analytics project's daily life during delivery and addressing risks, issues and changes. Learning outcomes: L01, L03 |
Team Based Learning |
Live Session May not be needed. An announcement will be made. Learning outcomes: L01, L02, L03 |
|
Week 9 |
Not Timetabled |
Topic 3.2: Organisational Change Self-Directed Learning: This topic critically examines how a project manager can influence organisational change to lessen the risk of project failure, in particular, if the organisational culture may be creating barriers. Learning outcomes: L01, L03 |
General contact hours |
Live Session This will be a discussion about the topics for this module and an assessment Q&A session. Learning outcomes: L01, L02, L03 |
|
Mid Sem break |
No student involvement (Breaks, information) |
In-Semester Break |
Week 10 |
Not Timetabled |
Module 3 Conclusion Self-Directed Learning: This week is a good time to reflect and explore the extra resources provided in this module. You may wish to reconsider Module 3.1 again in the light of the organisational change issues raised in Module 3.2. Please spend some time discussing the module topics on the discussion board. Learning outcomes: L01, L03 |
Workshop |
Live Session This session will be used to explore available propriety applications that assist/automate project management tools. Learning outcomes: L02 |
|
Week 11 |
Not Timetabled |
Topic 4.1: Final Delivery and implementation Self-Directed Learning: This topic considers the final delivery planning requirements including final testing and implementation needs. Learning outcomes: L01, L02 |
General contact hours |
Live Session This session will be used for discussion on finalising a project and for assessment Q&A. Learning outcomes: L01, L02 |
|
Week 12 |
Not Timetabled |
Topic 4.2: The rocky last mile Self-Directed Learning: This topic examines the closing a project to ensure a good handover into business as usual mode for the system and safeguarding the lessons learnt from this project so they are utilised by future projects. Learning outcomes: L01 |
Workshop |
Live Session This session will be used to prepare for the retrospective and for assessment Q&A. Learning outcomes: L02, L03 |
|
Week 13 |
Not Timetabled |
Topic 4.3 Course Summary Self-Directed Learning: This week is looking back over the course and reflecting on the journey. It is an opportunity to undertake a retrospective. It is also about the completion of the final assessment piece. Learning outcomes: L01, L02, L03 |
Workshop |
Live Session Run a retrospective for the course and discuss and reflect on its outcomes. Q&A Assessment 3. Learning outcomes: L01, L02, L03 |
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.