🧨 Layoffs Analysis – MySQL

📌 Project Overview

Analyzed layoff events across industries and companies using SQL to discover job market trends. Focused on identifying which sectors were most affected and when layoffs spiked.

🛠 Tools Used

• MySQL
• SQL Aggregations, Joins, Date Functions

🧾 Dataset Features

• Company, Industry, Location
• Date of Layoff
• Total Laid Off
• Workforce Size

🔍 Key Business Questions

1. Which industries had the most layoffs?
2. When did layoffs peak?
3. Which countries and company sizes were most affected?

🔬 What I Did

• Cleaned and imported raw layoff data
• Parsed layoff dates into months/quarters
• Grouped layoffs by industry, company size, country
• Calculated layoffs as % of total workforce

💡 Key Insights

• Tech sector = 60% of layoffs in 2023
• February and October had highest events
• Startups (<500 employees) had highest layoff % by headcount
• U.S. dominated total layoff volume

📈 Business Impact

• Guides recruiters and career advisors on market volatility
• Helps companies model layoffs as a function of macro events
• Enables HR teams to benchmark risk by industry

📬 Contact

Made by Deven Mbuyane
📧 devenmbuyane@gmail.com | 🌐 Portfolio