This project analyzes Pizza Hut sales data to uncover business insights using SQL and Power BI. The analysis identifies key performance indicators (KPIs) such as total orders, revenue, most popular pizzas, and category-wise performance. Interactive Power BI dashboards visually represent trends, sales by category, and performance comparisons.
Retrieve and analyze pizza sales data using SQL.
Build KPIs to monitor overall business performance.
Visualize data using Power BI for better decision-making.
Identify the most profitable and popular pizza types.
Compare monthly and daily sales performance.
Total Revenue: ₹817.86K
Total Orders: 48.62K
Top Performing Pizzas: Barbecue Chicken, California Chicken, Classic Deluxe.
Most Popular Category: Chicken pizzas contributed the highest share of total revenue.
Peak Sales Month: July showed the highest total sales.
Order Trend: Most orders are placed on Fridays, with sales dropping toward Sundays.
SQL Server — for data extraction and KPI creation
Power BI — for data visualization and dashboard building
Excel — for initial data cleaning and exploration
Total number of orders placed
Total revenue generated from sales
Highest & second highest priced pizzas
Most common pizza size ordered
Top 5 most ordered pizzas
Total quantity of each pizza category
Distribution of orders by time of day
Category-wise pizza count and contribution to revenue
Cumulative revenue over time
Top 3 pizzas by revenue in each category
See the Pizza_Analysis.pdf file for the full SQL code and queries.
- Dashboard 1 — Overall Sales Overview
KPIs for Quantity, Revenue, and Orders
Total Sales by Month
Sales by Category & Pizza Type
Month-over-Month Sales Comparison
- Dashboard 2 — Detailed Pizza Performance
Top & Least Pizzas by Revenue
Orders Per Day
Total Pizza Ordered by Type
Category & Size Filters
Integrate real-time data using APIs.
Add predictive sales forecasting.
Include customer segmentation and loyalty analysis.
Prashant Kashyap
📧 www.linkedin.com/in/prashant-kashyap-116ab224b
📅 Project Year: 2025