This project is focused on analyzing Walmart’s retail transaction data using SQL. The goal is to explore patterns, uncover insights, and understand business trends through structured queries and data analysis.
Data Cleaning & Preparation: Organized raw transaction data for analysis
Advanced SQL Queries: Used GROUP BY, HAVING, subqueries, CTEs, and window functions to extract meaningful insights
Performance Insights: Identified top-performing branches, peak hours, popular products, and revenue trends
Actionable Business Insights: Helped simulate how real-world retail businesses can optimize strategies using data
SQL (PostgreSQL / MySQL)
CSV/Excel Dataset
(Optional) Visualization tools like Tableau or Power BI for dashboards
This project strengthened my SQL skills and provided hands-on experience in retail analytics. It demonstrates how structured queries can be applied to answer real-world business questions and generate actionable insights.