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Subject Code – DATA6000
Subject Name – Capstone: Industry Case Studies
University Name – Kaplan Business School, Australia

Data analytics entails examining databases to find trends and insights that are later used to make informed organizational decisions.
Business analytics is concerned with evaluating various forms of data in order to create realistic, data-driven business choices and then putting those conclusions into action. Data analysis is frequently used in business analytics to identify problems and develop solutions.

Data Analysis Methods

Descriptive Analysis
Exploratory Analysis
Diagnostic Analysis
Predictive Analysis
Prescriptive Analysis

Data Visualization is the process of representing data and information through the use of graphics such as charts, infographics, plots, treemaps, and animations. Data visualization helps to understand complex data easily.
Data Visualization Tools: these are the software tools that make it easier to understand and work with huge massive data. Tableau, Qlikview, Microsoft Power BI, Excel, Sisense are some examples of data visualization.
Kaplan Business School, Australia
Kaplan Business School is one of the leading educational universities in Australia. The university has its campuses in various cities across Australia like Adelaide, Brisbane, Melbourne, Perth, and Sydney. The university is successfully offering graduation certificates, graduate diplomas, master’s, and MBA degree courses to students.

Assessment Details

Assessment: Individual Literature Review
Generate a unique business question that can be explored using available data sources and
analytics methodologies mastered in the business analytics degrees.


The first part of any good research project is a literature review. In approximately 1000 words
(excluding referencing) address the following sections which will assist you to outline a business industry problem that can be addressed through data analytics.

Industry Background:

Chose an Industry, e.g. healthcare, retail, education, finance, recreation, government, etc., and discuss three key business problems currently facing this industry.
Existing Analysis and Methodologies:
Research and evaluate existing analysis on the three business problems you have chosen
and reflect on the data and analytics methodologies that may have been employed this this
Explain and demonstrate the type(s) of internal company data you would ideally need
access to in order to achieve your objectives.

Data Sources:

Evaluate the types of data sources available to analysts in this industry. Explore the available
data sources you can access to address the three business problems you identified in this
industry and evaluate what type of descriptive and predictive analytics techniques could potentially be applied to it.
Provide at least three visualizations that demonstrate the applicability and relevance of your dataset to your research objective(s).
Selecting Business Problem: Generate a unique business question for this industry based
on one of the business problems. This is the business problem you will address in Assessment 4 (Industry research report). For the business problem you select summarise briefly:
1. the data source you will use
2. the methodologies you will explore (brief)
3. the originality of your contribution (WHY is your analysis unique given existing analysis)

Provide at least ten relevant, credible references to support your ideas and explanations.

Assessment: Methodology Summary Video

This assessment is to be done individually. Students have to present a 5-8 minute video summary of the below sections of the final research report:
o Data sources and data processing
o Data Analytics Methodology
o Visualisation of Results


Prepare a 5-8 minute video on the following three areas of the project:
1. Data Analytics Methodology (8 slides)
• Describe to a general audience the data analytics methodology you chose and why.
• Use a flow chart to illustrate the framework.
• Address the following
o What was the statistical/analytics method called?
o How much data was used in the model?
o What type(s) of internal company data would have enhanced the model?
o How did you input the data?
o What was the output?

2. Visualisation and Evaluation of Results (2 + 1 + 2 = 5 slides)
• Visualise your (A) descriptive analytics and (B) predictive analytics insights.
• Evaluate the model & significance of the analytics in addressing the business problem.
• Reflect on the efficacy of the techniques/software used and what other data and
techniques could enhance the analysis.

3. Brief Summary of your results (2 slides)
• Outline your broad results
• Provide your insights with reference to the business problem you selected.
• Reflect briefly on the role & limitations of the data and analytics technique that you have
used in addressing this business problem.


Industry Research Report
In order to synthesize what you have learned throughout your Analytics degree, you need to submit an industry research report. This report needs to:
1. Outline a business industry problem 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 with reference to data
visualizations and outputs.
4. Communicate these recommendations to a diverse audience made up of both analytics
and business professionals within the report.


In your report, follow the following structure:
Executive Summary (100 words)

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.

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)

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.

Visualization and Evaluation of Results (300 words not 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.

Recommendations** (800 words)
• Provide recommendations to address the business problem with reference to data
visualizations 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.

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 visualizations.
• Recommend how data ethics needs to be considered if using further analytics technologies and data to address this business problem.

Self-Reflection (100 words)
• Evaluate whether this project has contributed to you satisfying the course learning
outcomes for the KBS analytics program.

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