When a dimension or summary is loaded into the decision cube, it takes up memory. Adding a new summary increases memory consumption linearly: that is, a decision cube with two summaries uses twice as much memory as the same cube with only one summary, a decision cube with three summaries uses three times as much memory as the same cube with one summary, and so on. Memory consumption for dimensions increases more quickly. Adding a dimension with 10 values increases memory consumption by a factor of 10. Adding a dimension with 100 values increases memory consumption 100 times. Thus adding dimensions to a decision cube can have a dramatic effect on memory use, and can quickly lead to performance problems. This effect is especially pronounced when adding dimensions that have many values. 

Memory consumption can be limited by the following techniques:

• Setting maximum Dimensions
• Setting Dimension State
• Using Paged Dimensions

The decision support components have a number of settings to help you control how and when memory is used. For more information on the properties and techniques mentioned here, see TDecisionCube.