This repository explores global layoffs trends across industries, countries, and regions, alongside demographic patterns in parks and recreation. The project includes data cleaning and exploratory analysis using MySQL.
A complete SQL-based project analyzing global company layoffs between 2020 and 2023. Includes data cleaning, duplication handling, date standardization, and exploratory analysis to uncover key trends by country, sector, and year — all done using MySQL.
This project presents a comprehensive analysis of global layoffs using Power BI, transforming raw data into actionable insights through interactive dashboards. The dashboard is designed across three key pages, focusing on trends, patterns, and insights in layoffs across different industries, companies, and regions
Analyze global company layoffs using SQL: data cleaning, deduplication, and exploratory analysis to uncover trends across industries, countries, companies, and time.
A practical SQL data cleaning project that standardizes and prepares the Global Layoffs dataset for analysis using SQL techniques like window functions, staging tables, and data quality checks.
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