Aggregations

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Historically, aggregating data was summing detail data to provide subtotals and totals. However, using OLAP DML aggmap objects you can specify more complex aggregation calculation:

• The summary data dimensioned by hierarchical dimension can be calculated using many different types of methods (for example, first, last, average, or weighted average). For an example of this type of aggregation, see Example: Aggregating Up a Hierarchy.

• The summary data dimensioned by a nonhierarchical dimension can be calculated using a model. This functionality is useful to calculate values for dimensions, such as line items, that do not have a hierarchical structure. Instead, you create a model to calculate the values of individual line items from one or more other line items or workspace objects. For an example of this type of aggregation, see Example: Solving a Model in an Aggregation.

• The detail data used to calculate the summary data can be in the variable that contains the summary data or in one or more other variables. The variable that contains the summary data does not have to have exactly the same dimensions as the variables that contain the detail data. For an examples of this type of aggregation, see Example: Aggregating into a Different Variable and Example: Capstone Aggregation.

• The data can be aggregated as a database maintenance procedure, in response to user requests for summarized data, or you can combine these approaches. See "Executing the Aggregation" for more information.

• Data that is aggregated in response to user requests can be calculated each time it is requested or stored or cached in the analytic workspace for future queries.

• The specification for the aggregation can be permanent or temporary as described in "Creating Custom Aggregates".