This project focuses on analyzing inventory and product data from Zepto, one of India’s leading quick-commerce platforms. The objective of the project is to understand product attributes, stock availability, pricing, discounts, and category patterns using SQL.
The dataset contains product-level inventory information. Key fields include:
| Column | Description |
|---|---|
| category | Product category (e.g., Dairy, Snacks, Beverages) |
| name | Product name |
| mrp | Maximum Retail Price |
| discountPercent | Discount applied on the product |
| discountedSellingPrice | Final selling price after discount |
| availableQuantity | Number of units available |
| weightInGms | Weight of the product |
| outOfStock | Indicates if the item is currently unavailable |
| quantity | Units per package |
The table used for analysis:
CREATE TABLE zepto (
unit_id SERIAL PRIMARY KEY,
category VARCHAR(120),
name VARCHAR(150) NOT NULL,
mrp NUMERIC(8,2),
discountPercent NUMERIC(5,2),
availableQuantity INTEGER,
discountedSellingPrice NUMERIC(8,2),
weightInGms INTEGER,
outOfStock BOOLEAN,
quantity INTEGER
);This structure ensures proper data types for financial values, product attributes, and inventory flags.
The SQL analysis focuses on understanding:
- Product pricing and discount patterns
- Stock availability and out-of-stock trends
- Category-wise product distribution
- High-value and low-value items
- Variations between MRP and final selling price
- Weight and quantity insights
Each query is designed to answer a specific business-oriented question.