A full-stack data exploration and visualization project based on a fictional Zepto-style inventory dataset. This project leverages SQL for data cleaning and analysis, and Tableau for crafting an interactive business intelligence dashboard with insights like product value, revenue potential, restocking recommendations, and discount patterns.

💾 SQL-based analysis: Schema design, data cleaning, exploration, and deep-dive queries.

📊 Tableau Dashboard: Interactive visualizations showing inventory weight, pricing efficiency, category performance, and more.

📖 Story Points: A narrative walkthrough of business insights using Tableau’s storytelling interface.

Tool Usage MySQL - Schema creation, data cleaning, analysis Tableau - Interactive dashboards and storytelling Excel/CSV - Sample data transformation (optional) Git - Version control + portfolio publishing

Insight Area Description Inventory Weight Total inventory grams per category (weightInGms * quantity) Revenue Potential Estimated earnings using discountedSellingPrice * quantity Discount Strategy Top 5 categories by average discount percentage Best Value Products Lowest price per gram items for max cost-efficiency Stock Gaps & Restock Flags Out-of-stock items with high MRP, low available quantity Anomaly Detection High-MRP, low-discount products that may need repricing Product Segmentation Binning by weight: Low, Medium, Bulk

The story component in Tableau guides viewers through curated insight chapters like:

🏷️ Overview: Product availability and category distribution

⚖️ Category Weight vs. Revenue Potential

🎯 Discount Leaders & Best Value Products

🚨 Restock Suggestions

🔚 Key Recommendations

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