Assessment Description To synthesise your learnings from the Business Analytics course into a report, you need to undertake an analytics project and prepare an industry research report. Objective:

Kaplan Business School Assessment Outline

Assessment 3 Information

Field	Details
Subject Code	DATA6000
Subject Name	Capstone: Industry Case Studies
Assessment Title	Project Report
Assessment Type	Individual Report and Pitch
Assessment Length	2000 Words (+/-10%)
Weighting	35% Report / 15% Pitch
Total Marks	50
Submission	Turnitin and in class
Due Date	In class and Friday Week 12

Your Task

1. Develop and execute an analytics project that must include predictive analytics and/or forecasting.
2. Describe your project work addressing all feedback received in a report.
3. Pitch your work convincingly in 3 minutes.

Assessment Description

To synthesise your learnings from the Business Analytics course into a report, you need to undertake an analytics project and prepare an industry research report.

Objective: Your objective is to develop a solution that must:

• Outline an industry business problem with a question that can be addressed through data analytics.
• Apply descriptive and predictive analytics techniques to the business problem.
• Provide recommendations addressing the business problem using data visualisations and outputs.
• Communicate these recommendations to a diverse audience of analytics and business professionals.

This assessment aims to achieve the following subject learning outcomes:

• LO2: Employ the techniques covered throughout this course as they relate to contemporary client data and technology.
• LO3: Analyse the financial, ethical and environmental considerations related to data analytics and technology.
• LO4: Integrate advanced and innovative data-driven technologies for an industry project.

Tasks

• You are required to develop an analytics model and upload this model to the file dropbox.
• You are required to produce a report and upload it to Turnitin.

In your report, please follow the below structure. The words per section are only a suggestion.

1. Executive Summary (100 words)

• Summary of the business problem and data-driven recommendations.

2. Industry Problem (300 words)

• Provide industry background.
• Outline a contemporary business problem in this industry.
• Justify why solving this problem is important to the industry.
• Formulate a question based on the problem that is solved in this project.
• Justify how data can be used to provide actionable insights and solutions.
• Reflect on how the availability of data affected the business problem you eventually chose to address.

3. Data Processing and Management (400 words)

• Describe the data source and its relevance.
• Outline the applicability of descriptive and predictive analytics techniques to this data in the context of the business problem.
• Briefly describe how the data was cleansed, prepared, and mined (provide one supporting file to demonstrate this process).

4. Data Analytics Methodology (400 words)

• Describe the data analytics methodology and your rationale for choosing it.
• Provide an Appendix with additional detail on the methodology.

5. Visualisation and Evaluation of Results (300 words)

• Visualise descriptive and predictive analytics insights.
• Evaluate the significance of the visuals for addressing the business problem.
• Reflect on the efficacy of the techniques/software used.

6. Recommendations (400 words)

• Provide recommendations to address the business problem with reference to data visualisations and outputs.
• Effectively communicate the data insights to a diverse audience.
• Reflect on the limitations of the data and analytics technique.
• Evaluate the role of data analytics in addressing this business problem.
• Suggest further data analytics techniques, technologies and plans that may address the future business problem.

7. Data Ethics and Security (100 words)

• Outline the privacy, legal, security and ethical considerations relevant to the data analysis.
• Reflect on the accuracy and transparency of your visualisations.
• Recommend how data ethics needs to be considered if using further analytics technologies and data to address this business problem.

8. Elevator Pitch (3 Minutes)

• Prepare a 3-minute presentation pitching your project.
• Approach this task as if you are seeking funding and have just met an investor in the elevator.

Assessment Instructions

1. Your report should be submitted in Word Document or PDF format and be approximately 2,000 words in length, excluding references and appendices.
2. Report Format: Your submission should be a well-structured report that includes:
   • An executive summary.
   • A detailed solution and interpretation.
   • Analysis of the problem-solving approach.
   • Ethical considerations.
3. Visual Aids: Integrate diagrams and flowcharts to illustrate your solution and the data flow within the network.
4. References: Support your analysis with at least ten academic references.
5. Process Documentation: Document your thought process and decision-making journey from the initial design to the final recommendations.
6. Please refer to the assessment marking guide to help you complete all the assessment criteria.
7. Submit your written report via Turnitin as a .docx file.

Important Study Information

Academic Integrity and Conduct Policy https://www.kbs.edu.au/admissions/forms-and-policies

KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.

Please read the policy to learn the answers to these questions:

• What is academic integrity and misconduct?
• What are the penalties for academic misconduct?
• How can I appeal my grade?

Late Submission of Assignments

Number of Days Late	Penalty
1* – 9 days	5% per day for each calendar day late deducted from the total marks available.
10 – 14 days	50% deducted from the total marks available.
After 14 days	Assignments submitted more than 14 calendar days after the due date will not be accepted and the student will receive a mark of zero for the assignment(s) unless special consideration, reasonable adjustment or an alternative factor related to compassionate circumstances is approved and applied.

Assignments submitted at any stage within the first 24 hours after the deadline will be considered to be one day late and therefore subject to the associated penalty.

Length Limits for Assessments Penalties may be applied for assessment submissions that exceed prescribed limits.

Study Assistance Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Further details can be accessed at https://elearning.kbs.edu.au/course/view.php?id=1481

Generative AI Traffic Lights

Traffic Light	Amount of Generative AI Usage	Evidence Required	This Assessment
Level 1 – Prohibited	No GenerativeAI allowed. This assessment showcases your individual knowledge, skills and/or personal experiences in the absence of Generative AI support.	The use of generative AI is prohibited for this assessment and may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment.
Level 2 – Optional	You may use GenerativeAI for research and content generation that is appropriately referenced. This assessment allows you to engage with Generative AI as a means of expanding your understanding, creativity, and idea generation in the research phase of your assessment and to produce content that enhances your assessment.	The use of GenAI is optional. Your collaboration with GenerativeAI must be clearly referenced. You must include an appendix that documents your GenerativeAI collaboration including all prompts and responses.	✓
Level 3 – Compulsory	You must use GenerativeAI to complete your assessment. This assessment fully integrates Generative AI, allowing you to harness the technology’s full potential in collaboration with your own expertise.	You will be taught how to use generative AI and assessed on its use. Your collaboration must be clearly referenced and an appendix documenting all prompts and responses must be included.

Assessment Marking Guide

Standards for this Task	Points	Feedback
Problem Statement — Clear executive summary; clear description of the industry problem; clear description of data processing and management; well-researched project with accurate and relevant referencing.	/10
Results, Analysis & Recommendations — Extensive coverage of analytics methodology including an appendix. Multiple data sources used effectively. Clear forward-looking outcomes. Extensive discussion of project recommendations. Clear outline of privacy, legal, security and ethical considerations. Analytics model file uploaded to file dropbox (if missing, marks for this section = zero). For a higher grade: original and challenging business problem; multiple, technically sophisticated analytics methods.	/20
Report — Appropriate structure; ten or more relevant references; in-text references related to paragraphs; use of GenerativeAI in accordance with Traffic Lights; report uploaded to Turnitin and analytics model to file Dropbox.	/5
Elevator Pitch — Appropriate arguments to convince audience; understanding of competitive benefit; ability to answer questions; project pitched must match Assessment 2 and Assessment 3 report.	/15
Total	/50

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