BILLIONAIRS DATASET REPORT
BILLIONAIRS DATASET REPORT
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I analysed a global billionaires dataset containing detailed information on wealth, industries, demographics, and country-level economic indicators. My goal was to clean, structure, and visualise the data in a dashboard that highlights wealth distribution, industry dominance, geographic patterns, and demographic trends among the world’s richest individuals.
I analysed a global billionaires dataset containing detailed information on wealth, industries, demographics, and country-level economic indicators. My goal was to clean, structure, and visualise the data in a dashboard that highlights wealth distribution, industry dominance, geographic patterns, and demographic trends among the world’s richest individuals.
I prepared the dataset so it could support accurate analysis and interactive dashboard exploration.
I built pivot tables to analyse wealth by person, industry, and region.
I grouped industries and categories to make comparisons clearer.
I structured the data model so the dashboard could filter by country, industry, gender, and region.
This preparation allowed me to build a dashboard that is both informative and easy to navigate.
I reviewed the raw data and ensured fields such as age, net worth, industry, and country were consistent and usable.
I created summary metrics, including the total count of billionaires, average net worth, and the average age.
I designed the dashboard to highlight the most important insights at a glance while allowing deeper exploration.
I placed key metrics at the top, including the total number of billionaires (475), average net worth, and average age.
I used bar charts to show the richest individuals and the industries with the highest total wealth.
I included slicers for region, industry, gender, and self‑made status to make the dashboard interactive.
I used colour‑coding to differentiate industries and regions clearly.
I added tables and charts that show both individual-level and industry-level wealth distribution.
The dashboard provides a clear, structured view of global billionaire wealth and the factors that influence it.
What the Dashboard Shows
Key Insights
Wealth by Individual
• Bernard Arnault leads with $211B, followed by Elon Musk at $180B.
• The top group includes Jeff Bezos, Larry Ellison, Warren Buffett, and Bill Gates.
• Wealth is heavily concentrated among a small number of individuals.
Wealth by Industry
• Technology is the richest sector with $1.299T in total wealth.
• Fashion & Retail follows with $1.160T.
• Finance, Food & Beverage, and Manufacturing also contribute significantly.
This shows how tech and retail dominate modern wealth creation.
Regional Patterns
• North America has the highest number of billionaires, especially in tech and finance.
• Europe is strong in luxury goods, retail, and manufacturing.
• APAC shows major growth in technology, automotive, and mining.
Demographics
• The average billionaire is 67 years old.
• Most billionaires are male, though several women appear in retail, fashion, and diversified industries.
• Many billionaires are self‑made, especially in tech and finance
Summary
This Excel project shows my ability to clean data, build pivot‑based analysis, and design a dashboard that highlights global wealth patterns. The final dashboard gives a clear view of the richest individuals, the industries generating the most wealth, and the regions where billionaires are most concentrated. It provides a strong, visual summary of how global wealth is distributed and what drives it.
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