Reference no: EM133996747
Foundation Skills in Data Analysis
Learning Outcome 1 Apply the fundamentals of quantitative reasoning to solve real-world problems.
Learning Outcome 2: Manipulate and summarise data that ethically and accurately represents real-world problems.
Learning Outcome 3: Interpret and present analytical outputs to ensure transparency and integrity of data.
Task - Designing an Interactive Dashboard for Data Interpretation
Purpose
This assignment requires you to apply the ideas and concepts introduced in Module 1 on presenting and describing data. The task aligns with the learning outcomes GLO1, GLO4 & ULO1, ULO2, ULO3. In this assessment, you will work with a provided dataset to prepare and analyse data and design an interactive dashboard that visualises key insights. You will manipulate, summarise, and organise the dataset in preparation for analysis and then develop a dashboard that clearly communicates patterns, relationships, and trends in the data.
In completing this assessment, you will develop practical skills in structuring datasets, summarising key metrics, and creating interactive visualisations so that they support effective decision-making. Your dashboard should allow users to explore the data through features such as filters, charts, and key performance indicators (KPIs). No AI shortcuts — Only authentic assignment help from real expert tutors.
An important objective of this task is to ensure that your dashboard represents the underlying data accurately and ethically. You must design your visualisations so that they avoid misleading representations and present your analytical outputs in a clear, transparent, and interpretable manner.
Context/Scenario: The Global Sustainable Prosperity Initiative (GSPI)
You have been hired as a Data Analyst for the Global Sustainable Prosperity Initiative (GSPI), an international non-profit organisation. Your task is to develop a high-impact dashboard for global policy advisors and humanitarian strategists who need to make rapid, data-driven decisions on where to allocate their development resources.
The purpose of this dashboard is to identify the "Efficiency of Well-being", by identifying countries that achieve high citizen happiness and human development without having excessive economic wealth or causing environmental degradation. You must create a "single source of truth" (dashboard) that balances economic indicators with social and environmental health across 140 countries.
GSPI has compiled a dataset encompassing approximately 140 countries. Dataset - Global Development Indicators (Cross-Sectional Data, 2020)
This dataset contains socio-economic, environmental, and development indicators for countries. Variables include:
Country
Region
Population (Millions)
Happiness Index (0-10)
GDP per Capita (USD)
Corruption Perceptions Index (0-100)
Developing (Yes/No)
Exchange Rate to USD
Inflation Rate (%)
Unemployment Rate (%)
Pollution Level (PM2.5)
Renewable Energy Adoption (%)
Human Development Index (0-1)
Education Index (0-1)
Life Expectancy (Years) § Urbanisation (%)
Specific Requirements
This assignment includes two parts:
Task A: Interactive Dashboard Development
GSPI requires an interactive analytics dashboard to support evidence-based policy decisions and to identify patterns in wellbeing, economic development, and sustainability indicators across countries. Your role is to prepare, validate, analyse, and visualise the data while maintaining data integrity and using information ethically.
Using the provided data, you will:
Perform data validation, data transformation, and data organisation to ensure the data is ready for analysis.
Create an interactive dashboard that includes appropriate charts, filters (e.g., slicers), and key performance indicators (KPIs).
Apply prompt engineering techniques when using AI tools to assist with tasks such as generating formulas, suggesting dashboard layouts, or improving visualisation design.
Task B: Analytical Report
You will submit a short report that:
Interprets the key insights identified in the dashboard.
Explains how the chosen visualisations support interpretation of the data and contribute to identifying meaningful insights.
Discusses ethical considerations in data analysis and visualisation, including bias, potential data limitations, transparency in dashboard design, and responsible data communication.
Reflects on the use of AI tools and prompt engineering in the dashboard development process. Critically evaluate any AI-generated outputs used and explain how you ensured the final dashboard accurately, transparently, and ethically represents the underlying data, including any adjustments made to correct errors, clarify insights, or avoid misleading representations. Present this reflection for Task A: Interactive Dashboard Development as a whole, not for each individual task or sub-task, and include specific details based on your own experience.
There is no need to have a Table of Contents; an Executive Summary; or a Conclusion. You must, however, include a cover page that includes your name and student details, and an appendix that documents how you applied prompt engineering techniques when using AI tools to assist with your tasks. This appendix should clearly show:
The task or problem addressed, e.g., generating formulas, suggesting dashboard layouts, improving visualisation design.
The prompts used: include the exact prompts or instructions provided to the AI tool.
The AI outputs received: briefly describe or show the results generated by the AI.
Refinements or iterations: note any changes made to the prompts to improve accuracy, relevance, or clarity of the output.
Reflection on impact: explain how using prompt engineering helped you to complete the task, improve your efficiency, or enhance the final design.
Guidelines
Guideline One - Interactive filters
Dashboard should include at least 7 visualisations and allow filtering by Region, Country, and Developing vs Developed.
Guideline Two - Visualisation Choices
Visualisations you use should be purposefully selected to support interpretation of the data and communicate meaningful insights. Your Dashboard should emphasise clarity, relevance, and analytical value rather than the number of visualisations included.
Guideline Three - Interpretation of Results
Students should provide analytical insights and highlight at least five meaningful insights supported by visual evidence.
Guideline Four - AI platform
Guideline Five - Prompt Engineering Documentation
A short example appendix entry that students could model their own:
Task: Generate a formula to calculate the monthly growth rate of sales in Excel.
Initial Prompt:
"Create an Excel formula to calculate monthly growth rate using sales data in columns A (Month) and B (Sales)."
AI Output:
=(B2-B1)/B1 - Basic formula, works for row 2 only.
Refined Prompt:
"Create an Excel formula to calculate the monthly growth rate for all rows in column B, starting from row 2, and make it adaptable when copied down the column."
AI Output:
=(B2-B1)/B1 (then copied down automatically when applied in Excel) - Now fully applicable across all rows.
Reflection:
Using prompt engineering allowed me to iteratively refine the instructions until the formula was correct and adaptable for the entire dataset. This saved time compared to manually writing formulas for each row and ensured accuracy.
Guideline Six - use of AI Platforms
You are responsible for critically evaluating all AI-generated outputs before incorporating them into your work. You must document this evaluation as part of the required tasks, as outlined in the Specific Requirements section of the assignment, showing how you assessed accuracy, relevance, and ethical considerations in your final deliverables.Guideline Seven - Reference list
In this assignment, you must reference all sources used in your assignment, including words and ideas, facts, images, videos, audio, websites, statistics, diagrams and data. Although there are many different types and styles of referencing, we recommend that you use the APA7 method.