Support large numbers of concurrent users actively adding and modifying data.

Represent the constantly changing state of an organization

Contain large amounts of data, including extensive history data.

Heavy indexing. DSS systems have low update requirements but large volumes of data. Use many indexes to improve query performance.

Use of a hierarchical schema to organize the data within the database.

Data is organized to facilitate analytical queries rather than transaction processing.

Differences among data structures across multiple heterogeneous databases can be resolved.

Data transformation rules can be applied to validate and consolidate data when data is moved from the OLTP database into the data warehouse.

An intuitive multidimensional data model that makes it easy to select, navigate, and explore the data.

Technology to manage security, client/server query management and data caching, and facilities to optimize system performance based upon user needs.

Can combine data from heterogeneous data sources into a single data warehouse.

Organize data in simplified structures for efficiency of analytical queries rather than for transaction processing.