The bad news is that users can be quickly overwhelmed when presented with
a list of dozens of attributes from which to choose. This gets back to the discussion
in Chapter 1; know the users. Most users would want to see just the hierarchies,
because they provide a nice guided path through the data. Analysts would likely
want to see everything and have complete flexibility to create their own queries,
even if those queries involved many single attributes not included in any hierarchy.
After completing the wizard, the cube is shown in a manner similar to that in
Figure 3-10. Notice that the measures are shown along the left-hand side, broken
into measure groups that match the fact tables. Also note that main window with the
cube diagram is labeled Data Source View at the top. This is unfortunate and leads to
much confusion among those new to Analysis Services. This is not the same as the
data source view itself, but is just a representation of the tables from the DSV.
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 57
Cube Deployment and Processing
Once the cube has been designed, the files defining the cube exist only on the
developer??™s machine. The next step is to deploy the project to a server. Whether this
is a test or production server is immaterial for this discussion. The important point
is that the files are transferred to a server on which Analysis Services is running.
Deployment actually creates the cubes, dimensions, mining models, roles, and other
objects that make up an Analysis Services project when the data is copied to the
server.
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