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Aggregation Behavior of Non-Cumulative Key FiguresLocate this document in the navigation structure

Use

Aggregation behavior determines whether and how key figure values are aggregated in reports using various characteristics or characteristic values. Aggregational behavior can depend on whether time characteristics or other characteristics are used for aggregation.

You can see how aggregation affects the query result under Interpreting Query Results.

If you add up all the cumulative values such as Sales Revenue using all characteristics (that is, time characteristics as well), the non-cumulative key figure relating to the time characteristic, the first value (FIRST aggregation), the last value (LAST aggregation) or the average is often taken.

For more information about aggregate types, see Tab Page: Aggregation.

Example

In the following example, the difference between the FIRST aggregation and the LAST aggregation is made clear. If one considers, for example, the aggregated values for 02.02.02, then the non-cumulative is considered 90 with the FIRST aggregation, which is the non-cumulative without receipts. The non-cumulative with the LAST aggregation is considered 110, which is the non-cumulative from 90 plus the receipts of 20.

There are two possible kinds of aggregational behavior for non-cumulative key figures:

  • The standard aggregation specifies how a key figure is compressed using all characteristics (but not time characteristics).

  • The exception aggregation specifies how a key figure is compressed using all time characteristics.

Exception aggregations in terms of time

Every key figure has a standard aggregation and an exception aggregation. Non-cumulative key figures always have summation as standard aggregation, whereas time characteristics have an exception aggregation of not equal to summation.

Example

The non-cumulative key figure Warehouse Stock is aggregated using Summation for characteristics that are not time-related such as Articles or Stock. For time characteristics such as Calendar Month, however, the non-cumulative key figure Warehouse Stock has the exception aggregation Last Value.

Meaningful aggregations for non-cumulative key figures are primarily Average Weighted According to Calendar Days (AV1) and Last Value (LAS). Additional, possible exception aggregations for non-cumulative key figures are listed in the following table.

Technical name

Description

AV1

Average (weighted with the number of calendar days)

AV2

Average (weighted with the number of working days according to the factory calendar with the ID 01)

AVS

Total of all non-cumulative values

FIR

First value

LAS

Last value

MAX

Maximum

MIN

Minimum

Example

The time at which non-cumulatives were posted for different materials is displayed in the following graphic. The evaluation results for the non-cumulative for Material 1, for exception aggregation Average, and the exception aggregation Last Value, are listed in the following tables, where they are displayed once by calendar month and once by calendar day.

Average (calendar day)

Last Value

January

100

110

February

140

160

March

150

140

Drilldown on the non-cumulative value for material 1 by calendar day

Note that non-cumulatives that are evaluated by calendar day, both for the average and for the last value, always produce the same result. The reason for this is that Calendar Day is the smallest unit of time to which the data is transferred. This always occurs when you drill down to the most detailed time characteristic.

Average (calendar day)

Last Value

01.01.2000

90

90

02.01.2000

90

90

03.01.2000

90

90

04.01.2000

90

90

...

...

...

09.01.2000

90

90

10.01.2000

90

90

11.01.2000

99

99

...

...

...