PostgreSQL analysis of retail inventory data to evaluate product pricing, discounts, stock availability, estimated revenue, and inventory distribution.
This project analyzes the Zepto retail inventory dataset using PostgreSQL and pgAdmin.
The analysis covers data exploration, data cleaning, and business-focused SQL queries to identify useful patterns in pricing, discounts, product availability, and inventory.
- What are the top products based on discount percentage?
- Which high-priced products are out of stock?
- What is the estimated revenue for each category?
- Which products have an MRP above ₹500 but a discount below 10%?
- Which categories offer the highest average discounts?
- Which products provide the best price per gram?
- How can products be grouped by weight?
- What is the total inventory weight by category?
- SELECT, WHERE & DISTINCT
- GROUP BY & HAVING
- Aggregate Functions
- ORDER BY & LIMIT
- CASE WHEN
- Data Cleaning
- UPDATE & DELETE
- Calculated fields
- Business-oriented SQL analysis
- PostgreSQL
- pgAdmin
- SQL
💡 Key Takeaway
The project demonstrates how SQL can be used to transform raw retail inventory data into business insights around pricing, discounts, product value, stock availability, and inventory distribution.
👨💻 Author
Shreyas Samrutwar Data Analyst | SQL | Power BI | Python