A measure group is a collection of one or more measures, and by default each fact
table has its own measure group. One exception is for measures that are distinct
counts; for example, a store might have 10,000 shoppers during a week, but some
people come in multiple times, so the number of unique shoppers might only be
7500. Distinct counts are put in a separate measure group by default for performance
reasons.
After selecting the measures the cube wizard next tries to detect hierarchies in the
dimensions. As previously mentioned, this is an area in which the wizard often has
problems. The good news is that the warehouse developer can modify the hierarchy
design at this stage or after the wizard has completed.
The wizard not only tries to determine hierarchies, but determines attributes as
well. Attributes are those items that help describe a dimension item. For example,
a hierarchy for a customer might be Country, State/Province, City, and finally
Customer. However, a significant amount of additional information might be stored
for a customer, such as age, height, weight, income level, education level, and more.
A hierarchy that goes from Country to State/Province to Height probably doesn??™t
make sense, and neither would going from Education Level to Weight. Therefore,
many of these attributes are not part of a hierarchy but are still valid for analysis.
The good news is that with these attributes, end users have the flexibility to
analyze by nearly anything by simply selecting the attribute when constructing a
query.
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