🍕 Pizza Sales Analysis Dashboard

This project analyzes pizza sales data using MySQL for querying and Microsoft Excel for data manipulation and dashboard creation.It analyzes a dataset of approximately 50,000 pizza sales records with 12 columns. The analysis involves querying the data using MySQL, performing data manipulations in Excel, and creating pivot tables, pivot charts, and a dashboard to visualize key insights.

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📁 Project Structure

pizza-sales-analysis/
├── data/
│   └── pizza_sales.csv               # Raw dataset (~50k rows, 12 columns)
├── mysql/
│   └── queries.sql                   # SQL queries for KPIs and trend analysis
├── excel/
│   └── Pizza_Sales_Dashboard.xlsx    # Final Excel dashboard with PivotTables & charts
├── screenshots/
│   └── dashboard_overview.png        # Dashboard preview image
├── README.md                         # Project documentation (this file)
└── .gitignore                        # Excludes temp files and backups

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🧠 Key Business Questions

1. What is the total revenue generated from pizza sales?
2. What is the average order value?
3. How many total pizzas were sold?
4. How many total orders were placed?
5. Which are the best- and worst-selling pizzas?
6. What are the daily and hourly order trends?

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📊 KPIs Tracked

• ✅ Total Revenue
• ✅ Average Order Value
• ✅ Total Pizzas Sold
• ✅ Total Orders
• ✅ Average Pizzas Per Order

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📈 Charts and Dashboards

Visualization Type	Purpose
📅 Daily Trend (Mon–Sun)	Shows order trends over the week
⏰ Hourly Order Trend	Identifies peak hours
🍕 Sales by Pizza Category	Highlights category performance (Pie Chart)
📏 Sales by Pizza Size	Customer preference breakdown
🏆 Top 5 Best Sellers	Most popular pizzas by quantity
💔 Bottom 5 Worst Sellers	Least popular pizzas
📉 Sales Funnel by Category	Visual comparison by category

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⚙️ Tools Used

• MySQL: Data extraction and transformation
• Excel: PivotTables, PivotCharts, Slicers, and Dashboard creation
• GitHub: Version control and project hosting

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🚀 Getting Started

1. MySQL Analysis:

   • Open mysql/queries.sql in MySQL Workbench
   • Load your pizza_sales.csv data
   • Run and customize the queries for your insights

2. Excel Dashboard:

   • Open excel/Pizza_Sales_Dashboard.xlsx
   • Explore PivotTables and visual dashboards

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🖼️ Preview

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📌 Notes

• The dataset contains ~50,000 rows and 12 columns
• Data types include text, int, double, and datetime fields
• Time and Date columns were parsed and formatted in Excel for visualization

For any help, feel free to reach out to me 🙂

• Email: Drop a Mail
• LinkedIn: Connect with me
• Instagram: Follow me

📄 License

This project is open source and available under the MIT License.