Hotel Revenue Glossary · Technology

Data Warehouse

A centralized repository that stores historical and current hotel data from multiple operational systems in a structured format optimized for reporting and analysis. The data warehouse preserves historical snapshots that operational systems typically overwrite.

Why it matters: Without a data warehouse, historical performance data is lost as the PMS overwrites records. Year-over-year pace comparisons, trend analysis, and forecast models all depend on having clean historical data preserved in a data warehouse.

Worked example: On 15 March your PMS shows 1,240 room nights on the books for April. On 30 April it shows 3,180 sold. Ask it in May what April looked like on 15 March and it cannot tell you — that record was overwritten as bookings changed. A warehouse that snapshotted that day lets you say April picked up 1,940 nights inside the month, against 1,610 the same way last year: 330 nights of extra in-month pace, not a vague feeling that it was busier.

Common mistake: Snapshotting only the totals. A daily room-night count tells you pace moved but never why — you cannot go back and see that the 330 nights came from one association block, because the segment detail was never stored. Capture at the grain you will want to question later, which is always finer than the grain you think you need.

All glossary terms Business Intelligence Platform (BI) Snapshot PMS (Property Management System)