I uploaded the files which contains the Exercise and the other files to solve it.
Please adhere to the following:
1- Do not use artificial intelligence, as the university detects its use and has Turnitin.
2- Do not duplicate assignments from other students.
3- Submit within the specified timeframe,I have chosen four days.
Format: 1500-2000 words (Excluding graphs and charts) based on the guidelines below.
I. Assignment Brief
This assignment requires you to produce an academically grounded business analytics report.
You are required to select one dataset from the pool of datasets provided on the assignment
Loop submission link. All datasets have been sourced from open-access repositories and are
approved for use for educational purposes only.
Choose a dataset that aligns with an industry sector of interest to you (e.g. Healthcare
Management, Human Resources, Marketing, Inventory Management, Transport, Education,
etc.). Your role is to identify a business problem or opportunity that can be addressed
analytically using the variables available in the selected dataset.
Your task is to conduct the appropriate analytics processes to address the identified problem or
opportunity and to present your findings in a business analytics report.
In brief, a business analytics report is a structured document that presents data-driven insights to
inform business decision-making. Using your chosen dataset, you are required to conduct descriptive,
predictive, and prescriptive analytics.
1. 2. II. Analytics Report Framework
1. Organisational Context and Decision Challenge (20%)
This section must demonstrate that the analytics work is grounded in a business need. You should
include:
Industry Context: Introduce the sector and explain the relevance of the dataset to a real
industry setting.
Decision Problem or Strategic Opportunity: Clearly define the business problem or
opportunity. Business Value and Strategic Importance: Explain why this issue matters and what
organisational value is sought (e.g., efficiency, growth, risk mitigation, optimisation).
Analytics Objectives and Key Questions: Frame clear, data-answerable business questions
aligned with the decision challenge.
2. Working with Data and Analytical Design (20%)
This section must demonstrate the use of the dataset to answer the business questions, not just
technical execution. You should include:
Dataset Overview and Variable Classification: Identify key predictors (independent variables)
and targets (dependent variables).
Data Exploration and Assumptions: Discuss patterns, outliers, and potential limitations.
Data Preparation and Transformation: Explain cleaning steps and justification.
Analytical Approach and Justification: Describe why specific descriptive, predictive, and
prescriptive techniques were selected (you can limit the techniques to those taught in class).
3. Analytical Execution and Evidence (30%)
This section presents the analytic process and techniques in a structured analytical output.
Descriptive steps and insights
Predictive modelling results
Prescriptive analysis and decision scenarios
Analytics Dashboard: All key charts, tables, and visualisations must be presented together.
Each visual must include a short managerial insight statement.
4. Critical Evaluation and Managerial Insight (20%)
This section discusses your evaluation of the results.
Interpretation of results
Discussion of reliability, assumptions, risks, and limitations.
Managerial implications
Demonstrate how analytical outputs are combined with your industry understanding to inform
decisions.
5. Recommendations and Decision Communication (5%)
This section translates your analysis into action.
Actionable recommendations
Expected organisational impact
Implementation considerations
6. Housekeeping (5%)
Harvard or APA referencing (include DOIs where available)
Logical structure and coherent argumentation
Table of contents
Professional presentation of dashboard and appendices
II. Minimum Requirements for Technical Analytics
1. Descriptive Analytics
a) Select four (4) variables from the dataset and formulate four (4) descriptive analytics
questions that are relevant to your stated business problem.
b) Produce data visualisations to support your descriptive analysis and summary statistics.c) Each visualisation must include a brief insight statement explaining what the visual shows
and what decision or action it may inform.
All descriptive analytics visualisations should be compiled and presented together in an
analytics dashboard.
2. Predictive Analytics
Formulate and analyse at least one (1) predictive analytics question. Explain how the results of the
analysis could influence or support the business decision or action.
3. Prescriptive Analytics
Formulate and analyse at least one (1) prescriptive analytics question. Clearly explain how the
resulting recommendation would change or improve the business decision or action.
Notes:
1. 2. 3. Academic work at MSc level is expected to demonstrate independent research and critical
judgement, supported by academic evidence and reputable third-party sources. Please use the
Harvard or APA referencing style throughout your work.
A wide range of relevant peer-reviewed journal articles covering all areas of analytics is
available and should be consulted where appropriate.
Plagiarism will not be tolerated. All sources must be properly acknowledged in accordance
with the chosen referencing style