Analyzing Cubes using Office Client Components - Professional SQL Server Analysis Services 2005 with MDX - page 783

archy and level are not the same. For example, an attribute hierarchy Cus-
tomer will have the name of the hierarchy shown as Customer with the same
level name, as shown in Figure 15-10 . If there is a multilevel hierarchy cre-
ated with a level called Customer, the name of the hierarchy itself could not
therefore be called Customer.
One of the drawbacks of analyzing Analysis Services 2005 cube data using
Excel 2003 is the inability to distinguish hierarchies in dimensions that have
the same name. For example, if you have the dimensions employee and cus-
tomer, each of these dimensions can have hierarchies with the name Name
or Geography. If you are designing a cube for users analyzing data using Ex-
cel 2003, we recommend you take this into consideration and create names
that have full qualification so that your users are not confused as to which
hierarchy to select from the Pivot Table Field List.
Analyzing Data using Pivot Tables
Having created a pivot table against Analysis Services cube data, the next lo-
gical question is how is the pivot table helpful in analyzing this data? Assume
you are interested in looking at the Sales of products to customers in various
countries over time. The first step for analysis is to drag and drop the hier-
archies and measures of interest to the appropriate rows, columns, pages,
and data areas. To start, drag and drop the measure Internet Sales Amount to
the field containing the instructions "Drop Data Items Here," which you'll see if
you look back at Figure 15-9 . The value that you'll see in cell C4, as shown in
Figure 15-11 , is the total Internet Sales Amount across all dimensions. The
pivot table allows you to analyze data on a two-dimensional view based on
rows and columns. When there are no hierarchy members specified in the
row and column field's area, the default is to show the total value.
Figure 15-11