Sales Data Cleaning and Transformation — 85,000 Records

Cleaned and transformed a messy raw sales dataset of over 85,000 records for a retail company. Tasks included removing 23% duplicate entries, filling missing values, standardizing inconsistent date formats, handling outliers, and restructuring columns for analysis. Used Python (Pandas), Excel, and SQL. Final output was a fully clean, analysis-ready Excel file that saved the client 40+ hours of manual work and achieved 100% data accuracy for Q4 reporting.