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QBUS6600 Data Analytics for Business Capstone
创建日期：2024-08-20 14:36:57
标签： QBUS6600
Data Analytics for Business Capstone

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QBUS6600


Data Analytics for Business Capstone

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’ .

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CIVL2010 ECMT2150 CS 333 CP1406 KIT308 Economics 701 ECON3740 ECE 5759 BFC3340 FINC2012 COMP4500 MATH3871 FIT3080 18-819C Economic ECO202Y5Y PHY100 FINC-780 Econ 100B EC602 IE582 EE450 COMP9517 WRDS 150B ECON 570 LECTURE 2 ECA5101 ECE 4420 ADAD9311 FIT3031 CS 544 MF 703 CS 6140 KIT501 ENGSCI 344 CSC171 IE 332 FINM8007 21S2 COSC 1114 FE545 E471 SIT102 CSC108 MAT301 IAE 101 COP3503 STAT2004 EC 303 CS1026 STAT1203 MATH3171 ISOM5160 IFN657 FIT2014 ACCT2102 DSCI550 STATS 330 ELEC421 COMP3670 QBUS6840 MEES:698B MAST30027 MIET1077 Economics IFT 6758 FIT5122 BUSN5101 CptS 111 HRMT5502 Math2018 PP 312 INFS3200 CZ3005 CSSE1001 SENG 2011 MKTG 553Q BUFN 640 COMP507 ETF5952 DATA 311 ECE4043 BANK3011 finance M3H623544 HW1 INFS 7410 AI6103 STAT3888 INFS3208 ACCT7103 ECOS3013 PSYCH 20B F79MA STAT3006 ENGG952 2X MGSC 7000 ECE4132 MSF 526 MATH 3033 CDS 511 EEEE4120 EEET2465 ECA5103 MATH2070 ELEC3104 BU51019 EEE8147 ENGR20003 COSC 1107 ETF3200 FNCE 435 MSFI 435 ISyE6420 GENG4405 HW ETC5523 IE 7315 MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A 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ACCOUNTING BUSS1040 CHEM 181 MAT136H1 GY 6183 COMP3170 AGRI90089 PHYSICS 1002 ECON10003 IEOR E4004 ACS61012 MATH 40550 MKTG2113 TELE4653 ENSC1004 ECE 232E MK726 MTRX2700 SHEET 3 CSCA08 COMP30027 Math 2XX3 statistic MMAN3200 BISM7213 ECMM109 ECON 2022 FNCE 20005 GR5067 CSCB09 ME 3017 CS 5100 PHYS 2903 COMS 4771 COMP222 COMP 1046 CSC148H1 ISYS2038 FINS2615 OT5206 COMP2048 A6 MECH5770M MA826/20 CMPT 726 STA457 INFS6071 INFS588 integral ECON 216 IRDR 0017 MA323 PA 15213 PSYC2001 ENV222 Statistics ACCT5930 ACCT12 LAND2121 ME 5405 COMM1180 TELE3113 A7 ECE 568 ACCT2019 INFS1200 ENGG1340 CS 1400 ASST3 FINM7409 SWEN30006 INFO2222 FIN20150 SOSS1000 CSSE7231 FINS5513 COMS3200 CECN 702 ECON4060H MN3515 HW2 PSYA02H3 ECON 2112 COMP90051 CS 1652 MA30059 AF1605 MKTG7501 ECO-6003B COM4521 CTM ECON3350 COMP 3804 ELEC9762 BISM 7255 ST22 MATH20014 MNE3122 COMP343 MATH5165 ELE7029 ENGR30002 SEEM3500 ECON7350 RISK5002 FINM7405 COMP90059 MOS 3320B STAT 431 BISM7221 MATH3014 MTH783P EBA 35302 ACS133 BUS2206 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