Welcome to my end-to-end Pizza Sales Analysis project, built entirely using MySQL. This project demonstrates how raw sales data can be transformed into actionable business insights through structured querying, advanced SQL techniques, and thoughtful problem-solving.
- Domain: Food & Beverage / Retail Analytics
- Tools Used: MySQL
- Data Source: CSV files imported into a relational database
- Techniques Applied: CTEs, Window Functions, Aggregations, Joins, Grouping, Filtering, Ranking
This project aims to answer key business questions for SHODWE Pizza Resto, such as:
- Which pizza types contribute most to total revenue?
- What is the cumulative revenue trend over time?
- Which pizzas are top performers in each category?
- What are the busiest hours for orders?
- Which pizza sizes are most popular?
- What are the top 5 most ordered pizza types?
- Common Table Expressions (CTEs) for layered logic
- Window Functions (
DENSE_RANK,SUM OVER) for ranking and cumulative analysis - Joins across multiple tables (
orders,orders_details,pizzas,pizza_types) - Group By & Aggregations for summarizing data
- Date & Time Functions (
HOUR(),ORDER BY) for temporal analysis
| Insight | Description |
|---|---|
| 💰 Revenue Contribution | Calculated % contribution of each pizza category to total revenue |
| 📈 Cumulative Revenue | Tracked revenue growth over time using window functions |
| 🏆 Top Performers | Identified top 3 pizzas per category based on revenue |
| ⏰ Peak Hours | Analyzed order distribution by hour of day |
| 🍕 Popular Types | Listed top 5 most ordered pizza types |
| 📐 Size Preference | Determined most commonly ordered pizza size |
- Import the CSV data into MySQL tables (
orders,orders_details,pizzas,pizza_types) - Run the queries from
pizza_sales_analysis.sqlsequentially - Review insights and validate results using sample outputs or visualizations
I'm Vishal, a Data Analyst Bootcamp student passionate about SQL, Python, and turning raw data into meaningful stories. This project reflects my growing expertise in SQL optimization, query structuring, and business-focused analytics.
Feel free to connect or reach out for collaboration, feedback, or portfolio reviews:
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