Back to Projects
SQL EDA

Blinkit SQL Data Exploration Project

This project analyzes Blinkit's database by exploring various tables in MySQL and performing ad-hoc queries to analyze inventory wastages, delivery optimization, and customer retention rates.

May 2025
View on GitHub
Blinkit SQL Data Exploration Project

About This Project

Explored Blinkit’s operational data using SQL to uncover insights around inventory wastage, delivery performance, and customer retention.

Built a structured MySQL database from multiple CSV sources and performed ad-hoc SQL analysis to answer core business questions such as reasons for stock damage, delivery delays, and patterns in repeat purchases.

The project involved preprocessing data with Python and SQL, constructing a normalized MySQL schema, executing complex queries (joins, CTEs, aggregates), and interpreting results to support operational decision-making.

Key outcomes included

•Designed and populated a MySQL database using 11 dataset files, ensuring data quality and consistency.
•Analyzed inventory wastage and stock outages, identifying high damage rates in specific product categories and shelf-life concerns for perishable goods.
•Evaluated delivery performance, revealing common causes for delays (such as traffic) and quantifying average delay times.
•Measured customer retention patterns, uncovering a high repeat customer rate (around 94%), indicating strong loyalty.
•Proposed actionable recommendations, including improved vendor packaging for damage-prone items, shelf-life-based stock optimization, micro-hubs for faster delivery, and enhanced customer support to boost loyalty.

Technologies Used

PythonMySQL WorkbenchMySQLSQLAlchemy

Project Files

Source Code Repository

Gallery