SQL-Powered Booking Insights from 36,000+ Hyatt Records

This project analyzes over 36,000 Hyatt hotel bookings using ANSI-compliant SQL to surface eight high-value business insights. Conducted entirely within PostgreSQL, the project answers questions related to demand geography, booking behavior, channel profitability, and cancellation impact. Key findings include: the U.S. and China lead globally in guest volume (18% and 12% respectively); 52% of bookings occur within 15 days of check-in; and GDS channels generate $4.2M in revenue—$900K more than OTA. The most profitable segment, Corporate × Direct, averages $412 per booking, while UK-based cancellations account for $152 lost per booking, 23% above the global average. UAE guests book early (62 days out) and spend the most, averaging $510 per stay. All monetary values were stored as formatted strings and cast to numeric on-the-fly, demonstrating efficient SQL-based data cleaning. This project bridges business questions with technical clarity and highlights SQL’s power as both an analytical and storytelling tool.

Explore the project in full: https://github.com/dangquii/Hyatt-Hotel-Booking-Analytics_Data-Exploration.sql