Layoff Data Cleansing

Project Overview:

This SQL-based data cleaning project focused on preparing a global layoff dataset for analytical use. I performed comprehensive data standardisation, removed inconsistencies, handled missing values, and created summary tables that could be used in downstream dashboards and analytics tools.

Technologies Used:

• MySQL (DDL, DML, CTEs, Window Functions)
• CSV Dataset (layoffs.csv)

Key Features:

• Created staging tables and applied data pipeline logic
• Removed duplicate rows using ROW_NUMBER() and CTE strategy
• Replaced invalid entries (e.g. 'NULL', 0) with true SQL NULLs
• Standardised industry names and country values using TRIM and LIKE operations
• Transformed date fields from string to DATE type
• Enriched missing industry fields via table joins
• Built aggregated summary table grouped by industry

🔗 View Source Code on GitHub

🔍 Blog Post