This project analyzes Zepto sales and inventory data using SQL and Power BI to uncover customer purchasing patterns, product performance trends, and revenue-driving categories. The goal was to transform raw quick-commerce data into actionable business insights through data cleaning, analysis, and interactive dashboarding.
The analysis focuses on identifying:
- High-performing product categories
- Customer purchasing behavior
- Discount impact on sales
- Inventory and stock availability trends
- Revenue-driving products and categories
- SQL
- Power BI
- Excel / CSV
- Identified strong sales concentration among top-performing product categories
- Found high-demand products contributing significantly to overall sales
- Analyzed the relationship between discounts and purchasing behavior
- Tracked category-level sales and inventory trends
- KPI Tracking
- Category Performance Analysis
- Product-Level Insights
- Discount Impact Analysis
- Inventory Monitoring
- Interactive Filters & Visualizations
- Raw Dataset
- Cleaned Dataset
- SQL Analysis Queries
- Power BI Dashboard (.pbix)
- Dashboard Screenshots
Refer to the detailed project documentation for complete analysis, methodology, business insights, and dashboard explanation.