Data aggregation is the process of combining individual data values into summarized data values. To measure the revenue in dollars generated by the order management process, a Total Order Revenue KPI might sum the dollar amounts of orders received during a ten-minute data collection interval. To measure the order cycle time in minutes, an Order Cycle Time KPI might average the time required to process orders over a one-hour data collection interval. To measure available memory, a Total Memory for Integration Server KPI might store the last value in kilobytes of the Integration Server's available memory at the end of each one-minute interval.

Optimize aggregates data for KPIs that calculate sums differently from KPIs that calculate differences, averages, last values, and states. For example, a chart of KPI performance shows four consecutive data points: 5, 8, 7, and 4. You increase the time range until Optimize must aggregate the four data points into one data point. For KPIs that calculate differences, averages, and last values, the aggregated data point is the average of the four individual data points: 6. For KPIs that calculate sums, the aggregated data point is the sum of the four individual data points: 24. (For KPIs that calculate states, the aggregated data point is also the average of the four individual data points, but the values of those individual data points would be 0 or 1.

In addition to aggregating all the data collected during the data collection interval, Optimize must eventually aggregate data from multiple data collection intervals as the time range for data displayed on the KPI Summary page or KPI Instance Detail page increases.

Depending on the data display interval, the time range for the displayed data, a displayed data value may represent one data collection interval or multiple data collection intervals. For more information, see KPI Data Display.