SQL & EXCEL CASE STUDY

Pizza Sales Analysis

Dataset: Kaggle Pizza Sales Dataset Tools: SQL Server, Excel Role: Data Analyst

Project Overview

A SQL and Excel analysis of a pizza store's transaction data, built to answer four core business questions: how much revenue the store generates, when the busiest ordering hours and days are, which pizza categories and sizes drive the most revenue, and which items are the best and worst performers. All KPIs were calculated directly in SQL, then visualized in an interactive Excel dashboard.

Total Revenue

$817,860

Total Orders

21,350

Pizzas Sold

49,574

Avg Order Value

$38.31

Avg Pizza / Order

2.32

Note on Defensibility: Every KPI here comes directly from a SQL aggregate query against the raw transaction data, not from Excel formulas layered on top of a summary. The queries are documented in full in the repo, so each number traces back to exactly how it was calculated.

Key Performance Indicators

Five core KPIs, each calculated with a single aggregate query. Total revenue, for example:

SELECT SUM(total_price) AS Total_Revenue
        FROM pizza_sales;

The same pattern — aggregate function, single table was used for average order value, total pizzas sold, total orders, and average pizzas per order.

Trend Analysis

Daily trend: Orders peak on Friday and Saturday evenings.
Hourly trend: Two clear peaks — 12 PM to 1 PM, and 5 PM to 7 PM.

Hourly trend query:

SELECT DATEPART(HOUR, order_time) AS order_hours,
        COUNT(DISTINCT order_id) AS total_orders
        FROM pizza_sales
        GROUP BY DATEPART(HOUR, order_time)
        ORDER BY DATEPART(HOUR, order_time);

Sales Distribution

By category — Classic leads, but the margin over the rest of the field is narrow:

Category	Share of Revenue
Classic	26.91%
Supreme	25.46%
Chicken	23.96%
Veggie	23.68%

By size — Large pizzas dominate revenue, while the largest sizes barely register:

Size	Share of Revenue
Large	38.05%
Medium	31.65%
Small	29.06%
X-Large	1.17%
XX-Large	0.07%

Product Performance

The Classic Deluxe Pizza is the best selling item by units sold; the Brie Carre Pizza sells the least. Both were identified with the same query pattern, ranked in opposite directions:

SELECT TOP 5 pizza_name,
        SUM(quantity) AS Total_Pizza_Sold
        FROM pizza_sales
        GROUP BY pizza_name
        ORDER BY Total_Pizza_Sold DESC;

Pizza Sales Analysis Excel dashboard — KPI cards, order trends, and category breakdown

Interactive Excel dashboard built from the SQL analysis above.

Key Insights

Revenue is fairly evenly split across the four pizza categories. No single category dominates the way order patterns might suggest.
Size drives revenue more than category does: Large alone accounts for over a third of total revenue, while X-Large and XX-Large combined make up barely more than 1%.
Demand is concentrated around lunch and dinner hours, and weekends — a pattern that would directly inform staffing and inventory decisions in a real operating context.