Set A Regular Rollup Function For Measures - IBM Cognos User Manual

For example, level of inventory is recorded for a specific product, at the same
warehouse, in the same year, on different dates. If you select Average and the
Degree of detail set for the column is Day, the identical records are summed
and then divided by the number of day categories in the month. However, if
you select Last period, the inventory value for the last day of the month is
shown.
Duplicates rollup is automatically used whenever the PowerCube Consolidate
v
feature is turned on.
If you select both Regular rollup and Time state rollup, regular rollup is
performed first, followed by the time state rollup.
If the measure is used as a weighted value, as occurs during measure allocation,
you can use only the Sum rollup type.
When a model has more than one time dimension, you cannot use time state
rollup.

Set a Regular Rollup Function for Measures

By default, the values for a measure are automatically totalled using the Sum
function. Depending on the context, you may change this default rollup to
Minimum, Maximum, Average, Count, Count All, Any, or External.
For example, suppose your sales analysis model contains a measure named QTY.
You want your OLAP reports to show the average monthly quantity sold for each
store. You use Regular rollup (the Average function) to obtain the correct result.
Your source data is as follows.
Date
20070101
20070131
20070101
20070131
After applying the Average rollup function, the following results appear in your
report.
Date
2007
Date
Calculated measures can be computed after rollup or before rollup. When the
measures are calculated before rollup, the values are those calculated in the data
source.
For the time dimension, when you select Average as your regular rollup type, the
records are first summed and the result is then divided by the number of records
in the rollup time period.
The formula for a first-quarter average involving 78 records can be represented as
follows:
Store Product
STORE1 TR139SQ
STORE1 TR139SQ
STORE2 TR139SQ
STORE2 TR139SQ
STORE1 STORE2
350 500
350 500
Chapter 5. Modeling Your Key Performance Measures
QTY
500
200
400
600
STORE
425
425
101