Reference no: EM133164408

DATA6000 Capstone: Industry Case Studies - Kaplan Business School

Research Project

Assessment Instructions

In your report please follow the below structure.

1. Executive Summary (100 words)
• Dot point summary of business problem and data-driven recommendations

2. Industry Problem (500 words)
• Provide industry background
• Outline a contemporary business problem in this industry
• Argue why solving this problem is important to the industry
• 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 (300 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 of the methodology

5. Visualisation and Evaluation of Results (300 words including visuals)
• 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** (800 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 which may address the business problem in the future

7. Data Ethics and Security (400 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. Self Reflection(100 words)
• In your view, how has this project contributed to you satisfying the course learning outcomes for the KBS analytics program?