代做DATA6000 Capstone: Industry Case Studies Assessment 3代做Prolog

日期：2024-09-12 05:39

Assessment 3 Information

Subject Code:	DATA6000
Subject Name:	Capstone: Industry Case Studies
Assessment Title:	Project Report
Assessment Type:	Individual Report and
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 what your learnings from Business Analytics course you need to undertake an analytics project and prepare an industry research report. This project needs to:

1.   Outline an industry business problem with a question that can be addressed through data analytics.

2.   Apply descriptive and predictive analytics techniques to the business problem.

3.   Provide recommendations addressing the business problem using data visualisations and outputs.

4.   Communicate these recommendations to a diverse audience of analytics and business professionals.

Assessment Instructions

•    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)

•    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 which may address the business problem in the future.

7.   Data Ethics and Security (100 words)

1.   Outline the privacy, legal, security and ethical considerations relevant to the data analysis.

2.   Reflect on the accuracy and transparency of your visualisations.

3.   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)

4.    Prepare a 3-minute presentation pitching your project.

5.  Approach this task as if you are seeking funding and have just met an investor in the elevator.