This project analyzes pizza sales data using SQL queries to generate insights into customer preferences, popular pizzas, and sales trends. The analysis leverages order details, pizza categories, and pricing data.
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Total Orders & Revenue
Analyze overall sales volume and the total revenue generated. -
Highest-Priced Pizza & Common Pizza Size
Identify the most expensive pizza and the most commonly ordered size. -
Top 5 Most Ordered Pizzas
Rank pizzas by order volume to find the most popular options. -
Orders by Pizza Category
Breakdown orders by pizza categories (e.g., Veg, Non-Veg). -
Orders Distribution by Hour
Understand customer order patterns throughout the day. -
Average Pizzas Ordered Per Day
Calculate the daily average number of pizzas sold. -
Top 3 Pizzas by Revenue
Identify which pizzas contribute the most to overall revenue. -
Revenue Contribution by Pizza Type
Analyze how much revenue each pizza category (type) contributes. -
Cumulative Revenue Over Time
Visualize how revenue accumulates over a specific time period. -
Top 3 Pizzas by Category
Identify the top 3 pizzas in each category based on sales.
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SQL Clauses:
ORDER BY, GROUP BY, JOINS (INNER, LEFT, RIGHT, OUTER) -
Functions:
- Aggregate: COUNT, SUM, AVG
- DateTime: DATE, HOUR
- Subqueries
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Window Functions:
ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE()
- Order_Details
- Pizza_Types
- Orders
- Pizzas