Named queries act like a view in a relational database; they
allow for the building a query that will act as a table. The underlying schema here is
Figure 3-7 The Data Source View Wizard steps developers through the process of
creating a DSV, a logical view of the underlying physical database schema.
C h a p t e r 3 : D a t a W a r e h o u s i n g a n d B u s i n e s s I n t e l l i g e n c e 53
a snowflake schema wherein the product dimension is made up of three tables. It is
a simple matter to write a query that combines those tables into a single view or, in
DSV terms, a named query. In other words, writing a standard relational query, and
then naming it, makes it appear on the DSV just like any other table.
Figure 3-9 shows the same DSV as before, but the three product tables have been
replaced with a single named query called DimProductStar. DimProductStar contains
the columns from DimProduct, DimProductSubcategory, and DimProductCategory
in a single virtual table. Creating a named query changes absolutely nothing in the
underlying database; it is merely a logical construct in the DSV. Named queries are
easy to identify because the symbol next to the name looks like two small tables as
opposed to a single large table icon used for physical tables.
Named calculations are similar to named queries in that they are logical constructs
that exist only in the DSV. However, named calculations appear as a column in an
existing table. As the name suggests, these new columns may be used to perform
Figure 3-8 A Data Source View representing two fact tables and several dimension
tables
54 B u s i n e s s I n t e l l i g e n c e w i t h M i c r o s o f t O f f i c e P e r f o r m a n c e P o i n t S e r v e r 2 0 0 7
mathematical calculations, or they may be used to concatenate strings.
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