Overview
This project analyzes U.S. airline performance data using SQL generated datasets covering delays, cancellations, airports, airlines, and temporal patterns. This analysis was conducted by Gentry Lamb for the course DSAN-6300 Database Systems and SQL.
The goals of the project are to:
- Understand patterns in flight volume and delays across airlines and airports
- Identify worst-performing airports for each airline
- Explore temporal trends such as busiest days and moving averages
- Build clear visual explanations combining multiple datasets
All analysis is performed in Python, documented through a Quarto website, with a narrative story to demonstrate findings and insights.