SQL Exploratory Data Analysis: Layoffs Data

Welcome to my SQL Exploratory Data Analysis project! In this analysis, I examined a dataset with over 2,300 records detailing layoffs across various industries. Using advanced SQL techniques, I uncovered trends, identified key insights, and showcased my ability to analyze data effectively. This project highlights my skills in using SQL for data exploration and demonstrates my commitment to turning raw data into meaningful information for informed decision-making.

SQL Code

Explore the full SQL code used in this analysis for a deeper understanding of the queries and techniques applied. Click the link to view the detailed SQL script.

Excel Charts

Dive into the visual representations created using Excel to complement the SQL analysis, providing a more comprehensive view of the insights derived from the data.

Objective

The aim of this project is to analyze a dataset detailing layoffs across industries, identify trends, and derive actionable insights using SQL.

Dataset Overview

  • Source: Dataset with over 2,300 records of layoffs across various industries.
  • Fields: Included fields like company, industry, date, total_laid_off, percentage_laid_off, country, and funds_raised_millions.

Key Takeaways

  1. Significant Impact of U.S. Layoffs: The U.S. accounted for 66.96% of global layoffs, highlighting its disproportionate impact during the analyzed period.
  2. Trends Over Time: Yearly and monthly layoff trends aligned with economic conditions and the pandemic's influence.
  3. Advanced SQL Insights: SQL techniques such as CTEs, Window Functions, and String Functions facilitated deep and actionable insights into the dataset.

Results

The SQL exploratory data analysis revealed significant insights into layoffs across industries over a three-year period. Key findings include:

  • Date Range: March 11, 2020 – March 6, 2023
  • Total Layoffs: 383,159 employees
  • Yearly Layoff Trends:
    • 2023: 125,677 employees
    • 2022: 160,661 employees
    • 2021: 15,823 employees
    • 2020: 80,998 employees
  • Top Companies by Total Layoffs: Amazon (18,150), Google (12,000), Meta (11,000)
  • Countries with the Most Layoffs: United States (66.96%), India (9.39%), Netherlands (4.49%)
  • Monthly Layoff Peaks: January 2023 (84,714), November 2022 (53,451)