SQL & Power BI | Business Intelligence Project
An interactive end-to-end sales analytics dashboard designed to analyze pizza sales performance, customer ordering behavior, and product trends.
This project demonstrates how raw transactional data can be transformed into actionable business insights using SQL for analysis and Power BI for visualization — enabling data-driven decision-making for sales growth and operational efficiency.
This analytics solution provides a complete performance view of a pizza business by tracking:
- Revenue growth patterns
- Customer ordering trends
- Product-level performance
- Category and size contribution
- Peak demand periods
The dashboard helps business owners, sales managers, and analysts quickly identify what’s working, what’s not, and where to focus.
- Identify best and worst selling pizzas
- Analyze daily & monthly sales trends
- Understand revenue contribution by category and size
- Improve inventory, pricing, and promotional strategies
- Support data-driven decision-making
Source: Pizza sales transaction dataset
Dataset includes:
- Order ID & date
- Pizza category & size
- Quantity sold
- Total price per order
📁 Dataset File:
🔗 Pizza Sales Dataset
| Tool | Purpose |
|---|---|
| SQL | Data analysis & KPI calculations |
| Power BI | Dashboard design & visualization |
| Excel | Initial data inspection |
- Total revenue & total orders
- Average order value (AOV)
- Pizzas per order
- Daily & monthly order trends
- Top & bottom pizzas by:
- Revenue
- Quantity sold
- Number of orders
- Sales distribution by category & size
📄 SQL Scripts:
🔗 Pizza Sales Analysis Queries
The Power BI dashboard is designed with business storytelling in mind.
It includes:
- KPI cards for revenue, orders, and AOV
- Best & worst seller analysis
- Daily & monthly trend analysis
- Category-wise & size-wise sales contribution
- Interactive slicers for date and category
📥 Power BI Report (.pbix):
🔗 Power BI Dashboard
A high-level snapshot showing:
- Total revenue
- Total orders
- Average order value
- Overall sales performance
Highlights:
- Top-performing pizzas driving revenue
- Underperforming pizzas impacting profitability
Identifies:
- Peak ordering days
- Seasonal and monthly demand patterns
Shows:
- Revenue contribution by pizza category
- Performance comparison across pizza sizes
- Classic pizzas generate the highest revenue and total orders
- Large-sized pizzas contribute the most to total sales
- Orders peak on Fridays and Saturdays
- January and July show the highest demand
- Certain pizzas consistently underperform across all metrics
- Promote high-performing pizza categories and sizes
- Improve or discontinue consistently low-performing pizzas
- Plan inventory and staffing for peak demand days
- Introduce targeted promotions during low-demand periods
- SQL Data Analysis & Aggregations
- KPI Identification & Tracking
- Data Cleaning & Preparation
- Power BI Dashboard Design
- Data Storytelling & Visualization
- Business Intelligence Reporting
This project shows how analytics can:
- Improve sales strategy
- Optimize product offerings
- Enhance operational efficiency
- Enable data-driven decision-making
Riddhi K
🔗 LinkedIn: http://www.linkedin.com/in/kriddhi
Aspiring Data Analyst | SQL | Power BI | Excel
📌 This project is part of my data analytics portfolio and demonstrates real-world business problem-solving using data.