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QBUS6600 Data Analytics for Business Capstone Semester 1, 2024 Assignment 3

发布时间:2024-05-13

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QBUS6600

Data Analytics for Business Capstone

Semester 1, 2024

Assignment 3 (individual assignment)

1.  Key information

Required submissions: Written report (due: Friday, May 24).

Weight: 30% of your final grade.

Length:  Your written report should have a maximum of 6 pages (single spaced, 11pt). Cover page, references, table of contents and appendix (if any) will not count towards the page limit.

2.  Background

You have worked on an 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 learnt from this semester-long project.  Using the materials from the two rounds of peer review as your starting point, you will document your experiences, reflect on the difficulties you faced, and discuss what you could have done differently.  You will summarise your experience with 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.

You will  refer to your  experiences explicitly,  giving details of each experience.   Generic reflective text could result in you failing this assessment. Section 8 below provides further examples of the difference between generic and explicit styles.

Guidance for 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.  For example, you may want to prompt the tool to suggest corrections to your grammar or to provide feedback on your reflection.  If you use these tools, you must include a short footnote explaining what you used the tool for and the prompts that you used.  Such a footnote is not included in the word count.  Your assessment submission must not be taken directly from the output of these tools, including translations from other languages generated by these tools.

3.  Outline of the written report and the marking scheme

1.   Individual versus group investigation

15%

2.   Contribution to the group

a.   Technical contribution

b.   Non-technical contribution

 

35%

3.   Major difficulties

20%

4.   Ethical considerations

15%

5.   What could be done differently

15%

Total

100%

Please use the above outline for your 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 Big W or Mad Paws on how to avoid or overcome these problems.

What could be done differently.  Discuss what you would do differently if you had the opportunity to re-consider this project as a data scientist at Big W or Mad Paws. Explain why the changes would be beneficial. Discuss what you would like to investigate further and how this investigation would benefit your organization.

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.

7.  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 (and partial deductions for partial days). After ten calendar days late, a mark of zero will be awarded.

8.  Examples of generic and explicit reflection

Generic: ‘the incorporation of my findings from the initial assignment into the group project was challenging’. (without further detail)

Explicit:  ‘I had initially decided to employ some features because of high correlation, e.g., sales amount, etc. However, the discussion with my group made me realize that these features may not be available at the time of prediction. For example, we won’t be able to know what the sales amount is for a particular day until that day has passed. Consequently, we ended up excluding those features’ .

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 analysis section of the report, as detailed in Action item 4 from our meeting notes of April 19th (Appendix). This was challenging due to the different uses of language by my teammates, and making the graphics look professional. It took more time than I had expected, as I don’t have strong English skills myself and the graphics contributed by my teammates all came from different applications’ .