PostgreSQL-Analysis-of-the-World-s-Oldest-Businesses

This project utilizes PostgreSQL to analyze a curated dataset, revealing the timeless footprints of the world's oldest businesses."

INTRODUCTION

In the dynamic landscape of global commerce, the longevity of a business stands as a testament to its resilience, adaptability, and strategic foresight. Some enterprises have not only weathered the storms of changing market conditions but have thrived for centuries. BusinessFinancing.co.uk, in a meticulous endeavor, has delved into the archives of economic history, researching and identifying the oldest companies still operational in almost every country. The findings of this comprehensive investigation have been distilled into a dataset that now invites exploration.

Problem Statement

Our primary aim is to dissect the patterns and characteristics that have enabled certain businesses to endure for centuries. The specific objectives of this analysis include: Investigating the commonalities among the world's oldest businesses. Analyzing the founding years and distribution of these businesses across categories and countries. Uncovering any discernible trends or anomalies that may provide insights into the factors contributing to long-term success.

Questions

1. What are the unique business categories in the dataset? 
2. How many businesses are there in each category? 
3. Which category has the highest number of businesses? 
4. How many unique countries are covered in the dataset? 
5. Which continent has the highest number of businesses? 
6. What is the distribution of businesses across continents? 
7. What is the range of founding years for businesses in the dataset?
8. How many businesses were founded in each decade?
9. What is the average founding year of businesses?
10. What are the 10 oldest businesses in the dataset, and what are their categories and countries?
11. Which categories have the highest percentage of businesses that have survived for over 200 years?
12. How has the average age of businesses in each category changed over the past 100 years?
13. What are the most common business categories within each country?
14. Which countries have the most diverse representation of business categories?
15. Identify any countries where a single category dominates the oldest businesses.
16. Have any business categories consistently produced long-lasting businesses across multiple countries?
17. Which categories have the most significant variation in business longevity across different countries? 
18. Which countries have the most businesses represented in the dataset? 
19. What are the top 5 countries with the most diverse range of business categories?
20. Identify any categories that have seen a significant increase or decrease in representation over time. 
21. Analyze the distribution of businesses within each category by continent.
22. Explore the relationship between business age and category size.
23. Identify any trends in the founding dates of businesses within each country. 
24. Investigate the evolution of dominant business categories across different country groupings. 
25. Use window functions to calculate the "rolling age" of each business category within each country.