Zepto Data Analysis with SQL

📌 Project Overview

This project involves performing data analysis on a dataset from Zepto, a quick-commerce delivery platform. The goal is to derive business insights related to product pricing, discounts, inventory availability, and category performance.

The analysis is performed using SQL and covers advanced concepts such as:

• Aggregations (SUM, AVG, COUNT)
• Window Functions (RANK, OVER, PARTITION BY)
• Common Table Expressions (CTEs)
• Conditional Aggregation (CASE WHEN)
• Statistical Functions (PERCENTILE_CONT)

🛠️ Database Schema

The analysis is based on the zepto table, which stores product-level details.

DROP TABLE IF EXISTS zepto;

CREATE TABLE zepto (
    sku_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
);

🚀 How to Use
1. Set up your database: Execute the schema creation script in your SQL environment (e.g., PostgreSQL).
2. Import Data: Load your dataset into the zepto table.
3.Run Queries: Execute the provided SQL scripts to replicate the analysis.