| Assessment Type | Group Project | |
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Assessment Number |
3 | |
| Assessment Weighting | Groups 40% | |
| Alignment with Unit and Course | Unit Learning Outcomes | Graduate Attributes Assessed |
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ULO02:Analyze and reflect on the application of different Business Analytics techniques in business scenarios. ULO03: Use Business Analytics approaches to find trends and patterns in data from which to form a sustainable competitive advantage. ULO04: Examine the features of various Business Analytics software and draw insights from their application in business situations. |
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| Due Date/Time |
Week4 ReportdueWeek12(Friday)viaMoodleTurnitin5:00pm(AEST)Part A Written Report (20%) and Part B Group Presentation (15%). |
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| Assessment Description |
Studentswillworkinteamsof3or4memberstosubmitaprojectreport. The group report should be at least 2,500 words. Students should apply advanced business analytics on a chosen dataset. They are expected to apply a combination of business analytic techniques to tell the story behind the dataset and to provide meaningful insights derived from the dataset. Moreover, this could also contribute to more informed discussions making and an increase in the organization’s business value.
The groups should answer the following questions:
Each group should obtain permission from the unit coordinator as to which dataset they should use and they should also discuss the type of business analytic technique that they would like to apply for this assessment.No two group should use the same dataset and the |
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dataset should have at least3000records.There are many publicly available datasets that students can evaluate and analyze for this assessment such as Yahoo Webscope and SQLBELLE. Students can also use search engines such as Google dataset search.
The group report should be a business report something that can be presented to management of an organization. Students should apply a combination of business analytic techniques for this assessment, and it should not be limited to the following approaches:
- Descriptive statistics
- Multiple Linear Regression and time series forecasting
- Predictive analytics and cluster analysis
- Natural language processing,social media analytics and sentimental analysis
You are encouraged to attend the workshop on Referencing and Research Practice organized with the Academic Success Team(AST). You may also schedule a one-on-one work shop with the AST by emailing academicsuccess@aih.nsw.edu.au.
Thestructureoftheprojectisa2500-wordreport,the contents of which are detailed below. It is the report that requires submitting as the finished piece of work and this will be marked based on the rubric provided on page 5. Ad hoc work in whatever form will not be marked if submitted.
The word count is 2500 words. This is subject to plus or minus 10%. The word count does not include the title page, the table of contents, executive summary, the list of references or any appendices.However,please note that appendices should be used for supplementary information only: they will NOT be considered for marking.
The report content will comprise of the following sections:
Title page:this must contain the title of the report and your names,unit name,unit number and date of submission.
Table of contents(TOC):ideally,but not necessarily, constructed using the hyperlink functions in Word. Lists of figures and tables are not required.
Executive summary: an executive summary provides an overview of the ENTIRE report.It is NOT an introduction section. It is NOT a background section. The purpose of an executive summary is to provide an understanding of the document without having to read the complete report. Ideally, half to one page in length(but no longer),the executive summary will contain a summary sentence or two on each section of the report. Do not use headings or titles in the executive summary; it should be written in essay narrative format and read seamlessly.
Introduction:the introduction informs the reader of the aims and methods applied in the project.It also defines the scope of the project (what is included and what is not).
Background: a background informs that reader of the context to the project. It is easy to ‘go overboard’ with this section and consume much word count;one page is all that’s needed to set the scene for the project.
Methodology: This section highlights the methodologies applied to your given case. You need to clearly state a reason as to why they used that technique and provide supporting references especially if the technique is relevant for that industry.
Results: In this section, students will provide the results of their analyses. The results need to be provided in a logical sequence to ensure that the document is coherent and well synthesized.The results need to clearly show the application of the techniques covered in this unit and that the relevant assumptions in terms of the data have been given due considerations.
Key Findings:The findings of the analyses will be explained in this section.You are expected to be elaborate and to provide an in-depth explanation of the results and why they
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support or don’t support the results of the analyses.You need to provide the necessary reference to support any claims to ensure that the findings are supported by others in that field. Recommendations: The recommendation highlights any key findings from the analyses that is informed by the findings. Recommendation sections are usually concise and provide practical advice on areas that needs to be addressed. Conclusions:Through logical reasoning, this section should summarize how the project objectives have been achieved using appropriate business analytics tools and techniques. List of references: this should be formatted in Harvard style.
It is also vital that your work is guided by the marking rubric.
Research expectation:
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| Detailed Submission Requirements |
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| Individual Work | |
| Misconduct |
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| Late Submission |
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| Special consideration |
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