The main technology behind decision support systems, a.k.a. business intelligence systems, is data warehousing. A data warehouse is a specialized database that stores summary information from other databases such as order, inventory or customer relationship. When data is collected into a data warehouse, they are organized into data cubes. Each data cube has multiple dimensions such as time, geography or product line. Each cell in the cube contains measurements that help the managers and executives monitor the operations of the business, e.g. sales amount, product count, etc.

To provide access to the business user, reporting tools are able to query against data warehouse, and present the result in an easy to read format. Very often, these reports can contain tables, pie charts, bar charts, etc.  Some of the reports are interactive, allowing users to drill down from the top to a particular problem area, or navigate up from a smaller area to the larger containing area to get a better overview. For example, users can organize inventory amount by month by region or inventory amount by quarter by city.

Implementing decision support systems requires good understanding of both business requirements and the existing database applications. From the human resource perspective, a data warehouse project typically involves:

• Data warehousing specialist from in-house IT teams or consulting companies
• Application specialists from in-house IT teams or consulting companies
• Database administrators, typically from in-house IT teams
• Business users, typically from in-house business divisions

Further, a decision support system requires software that provides data warehousing and end-user reporting solutions. Here is the list of some of the mature software solutions:

• Microsoft Analysis Services
• Informatica
• Oracle Warehouse Builder and Oracle Reports
• SAS Business Intelligence Software
• MicroStrategy