Browse the Newly Discretized Attribute
with the Dimension Browser
1.
Click the Browser
tab in the Dimension Designer.
2.
Ensure that Vacation
Hours remains selected in the Hierarchy selector atop the Browser tab.
3.
Click the Reconnect
button atop the tab, as shown in Illustration 13.
Illustration 13: Partial Browser View - before Reconnecting
The browser details update, and (assuming the All
Employees level remains expanded in the browser), we see ten groups appear, as
depicted in Illustration 14.
Illustration 14: The Discretized Attribute Member’s Groups
We see
the groups appear, as expected. Ten groups have been created, based upon the algorithm
selected by the Automatic discretization method.
Browse the Newly Discretized Attribute
with the Cube Browser
Let’s go
one step further and examine the results of our selection of the Automatic discretization method
from another practical perspective, that of the cube browser. This will give
us an appreciation for the improvements seen by the information consumers in
querying / analyzing from the affected data.
1.
Within the Solution
Explorer, once again, right-click the Basic cube (expand the Cubes
folder as necessary).
2.
Click Open on
the context menu that appears, as shown in Illustration 15.
Illustration 15: Opening the Dimension via the Dimension Designer ...
The
tabs of the Cube Designer open, and we arrive, by default, at the Cube
Structure tab.
3.
Click the Browser
tab.
4.
Click the Reconnect
button atop the tab.
5.
In the Metadata
pane, expand the Employee dimension by clicking the “+” sign to its immediate
left.
6.
Expand the
newly exposed Organization folder.
7.
Right-click
the Vacation Hours attribute within the expanded Organization folder.
8.
Select Add to
Row Area from the context menu that appears, as depicted in Illustration 16.
Illustration 16: Adding the Vacation Hours Attribute to the Browser Row Area ...
We see
all ten Vacation Hours buckets appear in the rows of the browser pane.
9.
Click and drag
the Employee Name attribute to the immediate right of the physical column
containing the newly placed Vacation Hours buckets (a line will form at the
drop point), juxtaposing the Employee Names on rows to the immediate right of
the Vacation Hours, as shown in Illustration 17.
Illustration 16: Juxtaposing the Employee Name alongside the Vacation Hours in Rows ...
All ten Vacation
Hours buckets continue to appear in the rows of the browser pane – with “+”
sign “expand” buttons appearing to the immediate left of the bucket labels.
10.
Expand the 70-79
and the 90-99 Vacation Hours buckets by clicking the “+” sign to its immediate
left of each label.
The two Vacation Hours buckets expand, revealing lists of
the employee members whose total Vacation Hours place them within the
respective buckets in which they appear, as partially depicted in Illustration 18.
Illustration 18: Select Vacation Hours Buckets, Expanded to Show Membership
In what is but one example of how we can use the Vacation
Hours buckets, we can see lists of employees that have Vacation Hours on the
books for each of the ten buckets we have created via Automatic discretization.
We tell our client colleagues that they might use this arrangement to do far
more than present lists of the members of the various strata. They might also
flesh out the browser with other dimension members (such as Calendar Years,
etc.), drop in various measures (such as Reseller Sales and the like), and
perform analysis (as another simple example) upon employee balances of “unused
vacation” when viewed within the perspective of the sales figures attributed to
those employees.
Having demonstrated the potential effects that we can
achieve using Automatic discretization, we turn the development environment
over to the client representatives with which we have worked. Our colleagues
express satisfaction with our efforts, and state that they grasp the concepts
adequately to apply Automatic discretization to other contiguous attributes
within their cube.
11.
Experiment
further within the browser, as desired.
12.
Select File -> Exit to leave the design environment, when ready,
and to close the Business
Intelligence Development Studio.
Conclusion
In this article, we continued our exploration of attributes
in Analysis Services, this time with the objective of introducing, and gaining
some hands-on exposure to setting up, one of the multiple pre-defined discretization
methods supported within the Analysis Services UDM. We first discussed the
options that are available, and then chose to work with
Automatic discretization in the sample cube, to meet the business requirements
of a hypothetical client. (We noted that, in individual articles designed
specifically for the purpose, we will examine the setup of other discretization
options, in a manner similar to the one we took here, gaining hands-on exposure
to the use of those options in individual practice scenarios.)
Our examination included a brief,
general review of attribute discretization in Analysis Services, potential
benefits that accrue from discretization in our UDMs, and how the process can
help us to meet the primary objectives of business intelligence. We performed an overview of the multiple pre-defined discretization
processes supported within the Analysis Services UDM. We then began our
practice session with an inspection, via the browser in the Dimension Designer,
of the contiguous members of a select attribute hierarchy, noting the absence
of grouping and discussing shortcomings of this default arrangement.
Next, we enabled the Automatic discretization method
within the dimension attribute Properties pane. We then reprocessed the sample
cube with which we were working to enact the new Automatic discretization of
the select attribute members. Finally, we performed further inspections, via
the Dimension Designer and Cube Designer browsers, of the members of the attribute
hierarchy involved in the request for assistance by our hypothetical client,
noting the new, more intuitive grouping established by the newly enacted Automatic
discretization method.
About the MSSQL Server Analysis Services Series
This article
is a member of the series
Introduction to MSSQL
Server Analysis Services.
The series is designed to provide hands-on application of the fundamentals of MS
SQL Server Analysis Services (“Analysis Services”), with each installment
progressively presenting features and techniques designed to meet specific
real-world needs. For more information on the series, please see my initial
article, Creating Our First Cube. For the software components, samples and tools
needed to complete the hands-on portions of this article, see Usage-Based Optimization in Analysis Services 2005, another article within this
series.
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