This project analyzes historical transaction data from Walmart stores using advanced SQL queries to uncover insights related to sales performance, customer behavior, and operational efficiency. By leveraging SQL techniques, the project covers various aspects such as branch performance, product profitability, customer segmentation, and sales trends.
- Branch Performance: Identifying the top-performing Walmart branch by calculating monthly sales growth.
- Profitability Analysis: Analyzing the most profitable product lines for each branch based on gross income and cost of goods sold.
- Customer Segmentation: Classifying customers into High, Medium, and Low spenders based on their average spending.
- Anomaly Detection: Identifying abnormal sales transactions based on average sales for the product line.
- Sales Trends: Analyzing sales by day of the week, customer type, and payment method preferences.
- Task 1: Identified the top-performing branch based on sales growth.
- Task 2: Determined the most profitable product line for each branch.
- Task 3: Segment customers by spending behavior.
- Task 4: Detected anomalies in sales transactions.
- Task 5: Analyzed the most popular payment methods by city.
- Task 6: Analyzed monthly sales distribution by gender.
- Task 7: Identified the best product line by customer type.
- Task 8: Identified repeat customers within a specific time frame.
- Task 9: Found top 5 customers by sales volume.
- Task 10: Analyzed sales trends by day of the week.
- MySQL
- Advanced SQL queries (e.g., JOINs, GROUP BY, window functions, subqueries)
Feel free to connect:
- LinkedIn: https://www.linkedin.com/in/mandeep-sharma04/
- Email: Mandeep04sharma@gmale.com