QBUS6600 Data Analytics for Business Capstone

Data Analytics for Business Capstone

Semester 1, 2025

Assignment 3 (Individual Assignment)

1. Key Instructions

Required submission:

 Written report (in pdf, due date: Friday, May 30, 11:59 PM).

Weight: 30% of your final grade.

Length: Your written report should have a maximum of 6 pages (single spaced, 11pt). Cover

page, references, and appendix (if any) will not count towards the page limit. Please keep in

mind that making good use of your audience’s time is an essential business skill: every sentence,

table or figure should serve a purpose.

2. Background

You have worked on a real-world industry project both individually and collaboratively with

your peers. Now you have an opportunity to reflect on what you have done and what you have

learned from this semester代写QBUS6600 Data Analytics for Business Capstone-long project. Using the materials from the peer review as your

starting point, you will document your experiences, reflect on the difficulties you have

encountered, and discuss what you could have done differently. You will summarise and reflect

on your experiences during the work on the group project, think critically about the analysis

and the findings, and offer constructive recommendations/suggestions.

For a general background on reflection skills in business, please have a look at the following

resource. Please refer to your experiences explicitly and provide specific details. Generic

reflective text without referring to specific details could result in a low mark for this

assessment. Section 6 below gives examples of generic and explicit writing styles.

Guidance on the use of generative AI

The use of generative AI agents such as ChatGPT is permissible only to refine your text and to

help you organise your thoughts. If you use these tools, you must include a short footnote

explaining what you used the tool for and provide the prompts that you used. Your assessment

submission must not be taken directly from the output of these tools or be a translation of the

output.

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3. Outline of the written Report and marking scheme
4. Individual versus group investigation 15%
5. Contribution to the group

a. Technical contribution

b. Non-technical contribution

35%

3. Major difficulties 20%
4. What could be done differently 20%
5. Ethical considerations 10%

Total 100%

Please use the above outline for your written report (you are welcome to break down the longer

sections into smaller subsections). Please note that for this particular assignment the above

outline is required rather than suggested.

4. Rubric (basic requirements) and further details

Individual versus group investigation. Start with a brief introductory paragraph providing

the context and background for the semester long project. Discuss how you applied the results

and findings of your first individual assignment in your group project work. Explain why your

findings were helpful to the group. If your results or findings were not adopted in the group

project, reflect critically on why this happened and explain how the group achieved consensus.

Contribution to the group work. Discuss your contribution (both technical and non-technical)

to the group project. Critically reflect upon your role within the group. Discuss the tasks (both

technical and non-technical) that you were responsible for and highlight the work that you have

done. Explain how your contributions benefited the group. If your technical contribution was

minimal, you should also reflect on why this was the case and discuss what technical skills you

would like to improve.

Major difficulties. Discuss and reflect on the main difficulties or complications that you and

your group faced in your work on the project. Explain how you overcame the difficulties and

highlight your own contribution. The complications can be technical, non-technical, or both.

Ethical considerations. Discuss potential ethical problems with the data that has been

collected for your project or the analysis that you conducted. If you see no problems, discuss

potential ethical problems that may come up in the future if more data is collected and analysed.

Offer recommendations to UNICEF Australia on how to avoid or overcome these problems.

What could be done differently. Discuss what you would have done differently if you had the

opportunity to re-consider this project as a data scientist at UNICEF Australia. Explain why the

changes would be beneficial. Discuss what you would like to investigate further and how this

investigation would benefit your organisation.

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General requirements that apply to all sections. Your writing should be clear, precise, and

free of grammatical and spelling errors. Your paragraphs and sentences should follow a clear

logic and be well-connected. Your report should be well-organised and professionally

presented. There should be clear divisions between sections and paragraphs. If you use any

tables or figures, they should be appropriately formatted and clearly presented. They should

not contain irrelevant information and should be placed near the relevant discussion in your

report. You should follow the University of Sydney referencing rules and guidelines. Your

reflection should be critical, sound, and logical. You should explain things clearly with specific

examples, drawing clear conclusions based on analysis and well-grounded arguments.

5. Late submission of the report

Late submissions are subject to a deduction of 5% of the maximum mark for each calendar day

after the due date. After ten calendar days late, a mark of zero will be awarded.

6. Past examples of generic and explicit reflection

Generic: ‘The incorporation of my findings from the individual assignment into the group

project was challenging’ (without further detail).

Explicit: ‘I had initially decided to incorporate certain features (e.g., sales amount) into the

model because of their high correlation with the target variable. However, a discussion with my

teammates made me realise that these features may not be available at the time of prediction.

For example, we would not be able to know what the sales amount is for a particular day until

that day has passed. Consequently, we ended up excluding these features from the model.’

Generic: ‘My role encompassed the preparation of the report, which entailed developing the

model, converting our findings into actionable conclusions and recommendations, and

presenting an executive briefing’ (without further detail).

Explicit: ‘I was responsible for the final edit of the model building section of the written report,

as detailed in action item 4 of our meeting notes from September 23. This task was challenging

due to the dissimilar writing styles of my teammates who contributed to the section. It was also

challenging to make all the figures, which came from several different applications, look

uniform and professional. For these reasons, the task took much longer than I originally

anticipated.’