This project analyzes approximately 21,000 pizza orders to uncover key business KPIs, peak demand hours, and seasonal trends. SQL was used to automate KPI computation, and Tableau was used to build an interactive dashboard for decision-making.
- Source: Kaggle – Pizza Sales Dataset
- Orders: ~21,000
- Data Type: Transactional sales data
The dataset is not included in this repository due to size and licensing constraints.
- SQL (MySQL/PostgreSQL)
- Tableau
- Excel (data inspection)
- Created normalized SQL schema for transactional data
- Automated KPI calculations using SQL views and aggregations
- Built interactive Tableau dashboard
- Identified peak hours, weekend trends, and revenue drivers
- Proposed data-driven business recommendations
- Identified a ~19% weekend revenue surge
- Automated KPI tracking, reducing manual effort by ~85%
- Recommended size-based upselling and pricing tweaks with a projected 12–15% revenue uplift
- No customer-level data
- Historical analysis only
- Revenue uplift is a projection, not a guarantee
- Customer segmentation
- Promotion impact analysis
- A/B testing for pricing strategies