🛒 Zepto E-commerce SQL Data Analysis Project

A complete PostgreSQL-based SQL project using a real-world e-commerce inventory dataset from Zepto, one of India’s fastest-growing quick-commerce startups. This project demonstrates end-to-end data analytics skills — from data exploration to business-focused insights — using real analyst techniques like CASE, JOINS, CTEs, and Subqueries.

---

📌 Project Highlights

• ✅ Realistic SQL project with retail use-case
• 🧹 Data cleaning & transformation (e.g. paise → rupees)
• 📊 Business insights: revenue, stock status, product value
• 🧠 Uses advanced SQL techniques: CASE, JOIN, CTEs, Subqueries
• 💼 Perfect for interview prep, portfolio building, or SQL learning

---

📁 Dataset Summary

• Source: Kaggle (scraped from Zepto’s mobile app)
• Real-world e-commerce catalog structure
• Duplicate product names with different packaging/weights
• Each row = unique SKU (Stock Keeping Unit)

🔧 Columns

Column	Description
sku_id	Unique product ID
name	Product name
category	Product category (e.g. Fruits, Snacks)
mrp	Max Retail Price (₹)
discountPercent	% discount on MRP
discountedSellingPrice	Final discounted price
availableQuantity	Inventory units available
weightInGms	Product weight (grams)
outOfStock	Boolean - Is the product out of stock?
quantity	No. of units per SKU

---

🚀 SQL Features Demonstrated

🧹 Data Cleaning

• Removed products with MRP or price = 0
• Converted mrp & discountedSellingPrice from paise to rupees
• Handled null values and inconsistent entries

🔍 Data Exploration

• Counted total rows
• Identified distinct categories
• Compared stock vs out-of-stock
• Detected repeated product names (same product, different SKU)

📊 Business Queries

• Top discounted products
• High MRP but out-of-stock products
• Revenue by category
• Expensive products with low discount
• Avg. discount by category
• Price-per-gram value ranking

---

✅ 1. Top 10 products with highest discount %

SELECT DISTINCT name, mrp, discountPercent
FROM zepto
ORDER BY discountPercent DESC
LIMIT 10;

📸 Output Screenshots

---

✅ 2. High-MRP products that are out of stock

SELECT DISTINCT name, mrp 
FROM zepto
WHERE outOfStock = TRUE AND mrp > 300
ORDER BY mrp DESC;

📸 Output Screenshots

---

✅ 3. Estimated revenue per category

SELECT category,
SUM(discountedSellingPrice * availableQuantity) AS total_revenue
FROM zepto
GROUP BY category
ORDER BY total_revenue DESC;

📸 Output Screenshots

---

✅ 4. Expensive products (MRP > ₹500) with low discount (< 10%)

SELECT DISTINCT name, mrp, discountPercent
FROM zepto
WHERE mrp > 500 AND discountPercent < 10
ORDER BY mrp DESC, discountPercent DESC;

📸 Output Screenshots

---

✅ 5. Top 5 categories with highest average discount %

SELECT category,
ROUND(AVG(discountPercent), 2) AS avg_discount
FROM zepto
GROUP BY category 
ORDER BY avg_discount DESC
LIMIT 5;

📸 Output Screenshots

---

✅ 6. Price per gram (value for money)

SELECT DISTINCT name, weightInGms, discountedSellingPrice,
ROUND(discountedSellingPrice / weightInGms, 2) AS price_per_gram
FROM zepto
WHERE weightInGms >= 100
ORDER BY price_per_gram;

📸 Output Screenshots

---

✅ 7. Classify product by weight (CASE statement)

SELECT DISTINCT name, weightInGms,
  CASE 
    WHEN weightInGms < 1000 THEN 'Low'
    WHEN weightInGms > 5000 THEN 'Medium'
    ELSE 'Bulk'
  END AS weight_category
FROM zepto;

📸 Output Screenshots

---

✅ 8. Total inventory weight per category

SELECT category,
SUM(weightInGms * availableQuantity) AS total_weight
FROM zepto
GROUP BY category
ORDER BY total_weight DESC;

📸 Output Screenshots