Best Practices for SAP BI using DB2 9 for z/OS - IBM Redbooks

6.4.3 Cumulative data versus non-cumulative key figures
6.4.4 Areas of impact
Important: Packages cannot be deleted from the E- fact table using a
package ID. Ensure that packages in the F- fact table have been reviewed
prior to compression, since deletion from the F- fact table is much simpler.
There are two types of key figures in a fact table: cumulative key figures and
non-cumulative key figures. If a cube has at least one non-cumulative key figure,
it is called a non-cumulative cube. In the E- fact table, the data for
non-cumulative key figures is stored in separate records, which are called
reference points and have their own package DIMID to distinguish them from
common records.
The E- fact table contains consolidated data from the F- fact table. For
cumulative data, the key figure values are summed. For non-cumulative data, a
function is applied to the key figures before the record is inserted in the E- fact
table. Common functions include minimum value, maximum value, last value,
and so on.
► Non-cumulative key values get assigned a package ID different from 0 in the
E- fact table when the record is moved from the F- fact table to the E- fact
table. For non-cumulative key figures, an additional row (the reference point)
is inserted or updated in the E- fact table that has the same combination of
dimension IDs, except for the time and package dimension. Rather than
requiring summing all delta values from the F- fact table, the E- fact table
reference point can be accessed directly, thus improving query performance.
► Cumulative key values get assigned a PID of 0 in the E- fact table. When a
record in the F- fact table has the same key as a record already in the E- fact
table a new record is not added to the E- fact table. Instead the cumulative
key values for the record in the E- fact table are incremented by the value in
the same record from the F- fact table.
We recommend that SAP compression be implemented and updated on a
regular basis (even if the ratio of compression appears to be insignificant) for the
following reasons:
► Storage impact
– SAP compression may result in reduced data storage requirements.
– Occasionally, no change will occur.
98 Best Practices for SAP BI using DB2 9 for z/OS