Measures and Measure Groups - Expert Cube Development with SSAS Multidimensional Models - page 109

That said, there are situations where referenced relationships are useful because
it's simply not feasible to add all of the attributes you need to a dimension. You
might have a Customer dimension, for instance, that has a number of attributes
representing dates—the date of a customer's first purchase, the date of a customer's
tenth purchase, and the date of a customer's last purchase. If you had created these
attributes with keys that matched the surrogate keys of your Time dimension,
you could create multiple, referenced (but not materialized) role-playing Time
dimensions joined to each of these attributes that would give you the ability to
analyze each of these dates. You certainly wouldn't want to duplicate all of the
attributes from your Time dimension for each of these dates in your Customer
dimension. Another good use for referenced relationships is when you want
to create multiple parent/child hierarchies from the same dimension table, as
discussed in Chapter 3 , Designing More Complex Dimensions .
Data mining relationships
The data mining functionality of Analysis Services is outside the scope of this topic,
so we won't spend much time on the data mining relationship type. Suffice it to say
that when you create an Analysis Services mining structure from data sourced from
a cube, you have the option of using that mining structure as the source for a special
type of dimension called a data mining dimension. The wizard will also create a
new cube containing linked copies of all of the dimensions and measure groups in
the source cube, plus the new data mining dimension, which then has a data mining
relationship with the measure groups.
Summary
In this chapter, we've looked more closely at the problems we're likely to face when
designing real-world cubes. We saw how to configure measures to aggregate in the
way we wanted, how to create new measure groups and handle the problems of
different dimensionality and granularity, and we've started to look at the different
types of relationships that are possible between dimensions and measure groups.
In the next chapter, we'll continue with that theme and explore drill through
(which is related to the topic of fact relationships) and many-to-many relationships.