Took a raw e-commerce dataset of 51,290 rows and cleaned it using Python (pandas) — fixed null values, removed outliers, standardised inconsistent categories and added derived metrics like profit margin and revenue after discount. Built a 4-chart Excel dashboard with live KPI summaries showing total revenue ($5.4M), total profit ($3.6M), average profit margin (42.53%) and key business insights across product categories, order priority, monthly trends and payment methods.