Databases Reference
In-Depth Information
Figure 6-21
In your source data, if you had partitioned your fact data into multiple
fact tables across a specific dimension, that needs to be handled differ-
ently while designing the cube. For example, if you have Fact Internet
Sales data stored in separate fact tables for each quarter (fact data has
been partitioned into multiple fact tables across the Time dimension),
then with respect to the cube all these are considered a single fact table
because they have the same schema. You have partitioned your rela-
tional fact data into multiple fact tables due to design or scalability con-
siderations, but when you want to analyze the data you will be look-
ing forward to aggregating the data appropriately across various dimen-
sions, especially the Time dimension. You can either merge the data
from all the fact tables within the DSV with a named query or you can
utilize the partitioning feature in Analysis Services so that Analysis Ser-
vices aggregates the data correctly during browsing. You learn more
about partitions in
Chapters 12
and
13
.
You can see several properties of the cube in
Figure 6-21
. The most im-
portant property is DefaultMeasure. As the name indicates, this property
is used to define the measure used by default whenever queries are sent
to the cube. The reason why the default measure is important is that
whenever your MDX query does not contain the explicit measures spe-
cified, the default measure is returned. In addition to that, the default
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