A data warehouse is a centralized system that combines large amounts of historical data from multiple sources for analysis and decision-making. A regular operational database mainly stores current data and supports routine transactions such as purchases, bookings, or account updates.
How a data warehouse works
Data is collected from sources such as sales databases, customer relationship management systems, websites, and external datasets. An ETL process extracts the data, transforms it into a consistent structure, and loads it into the warehouse.
The resulting data is usually subject-oriented, meaning it is organized around areas such as customers or sales; integrated, because formats and values are standardized; time-variant, because historical records are retained; and non-volatile, because stored data is normally read rather than frequently changed.
Data warehouses support online analytical processing (OLAP). Users can identify trends, compare periods, create reports, and perform complex aggregate queries across large datasets.
| Feature | Data warehouse | Regular operational database |
|---|---|---|
| Main purpose | Analysis and strategic decision-making | Processing day-to-day transactions |
| Typical data | Integrated historical data | Current, detailed operational data |
| Workload | Complex queries and aggregations | Frequent inserts, updates, and short queries |
| Sources | Multiple databases and external systems | Usually one application or business process |
| Design priority | Fast analytical querying, sometimes using denormalized schemas | Data integrity and efficient transactions, often using normalized tables |
| Typical example | Comparing five years of regional sales | Recording a customer's latest purchase |
A common misconception is that a data warehouse is simply a very large regular database. Size alone does not define it: its distinguishing features are the integration of historical data and its analytical purpose.
Exam technique
For IB Computer Science HL topic A3.4 Alternative databases and data warehouses, a “distinguish” question requires paired differences, not two isolated definitions. State the purpose, type of data, workload, and source of each system, then apply them to a relevant example.
