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Zepto-Inventory-Analysis-Visualization

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.

📌 Project Highlights

  • 💾 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.

Tools & Technologies

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

🔍 Core Analyses (SQL + Visualized in Tableau)

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

Tableau Story Walkthrough

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

  1. 🏷️ Overview: Product availability and category distribution
  2. ⚖️ Category Weight vs. Revenue Potential
  3. 🎯 Discount Leaders & Best Value Products
  4. 🚨 Restock Suggestions
  5. 🔚 Key Recommendations

🚀 How to Use

  1. Clone the repository:
    git clone https://github.com/Abhii58/zepto-inventory-analysis.git
    
    

About

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.

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