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Posted Jul 17, 2009

Attribute Discretization: Customize Grouping Names - Page 5

By William Pearson

Browse the Newly Named Attribute Groups with the Cube Browser

Let’s go one step further and examine the results of use of the attributes group naming template from another practical perspective, that of the cube browser. As we noted in the similar browse of the earlier section, this will give us an appreciation for the improvements seen by the information consumers in querying / analyzing from the affected data.

1.  Click the Browser tab within the Cube Designer, once again.

2.  Click the Reconnect button atop the tab, as before.

3.  In the Metadata pane, expand the Employee dimension by clicking the “+” sign to its immediate left.

4.  Expand the newly exposed Organization folder.

5.  Right-click the Vacation Hours attribute within the expanded Organization folder.

6.  Select Add to Row Area from the context menu that appears, as we did in the earlier section.

We see all ten Vacation Hours buckets, with new custom labeling, appear in the rows of the browser pane.

7.  Click and drag the Employee Name attribute to the immediate right of the physical column containing the newly placed Vacation Hours buckets, as we did earlier, juxtaposing the Employee Names on rows to the immediate right of the Vacation Hours, once again.

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.

8.  Expand the Between 70 & 79 (incl) and the 90 & Over Vacation Hours buckets by clicking the “+” sign to its immediate left of each custom 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 shown in Illustration 23.

Select Vacation Hours Buckets, Expanded to Show Membership
Illustration 23: Select Vacation Hours Buckets, Expanded to Show Membership

We again emphasize to our client colleagues that they might use this arrangement to do far more than present lists of the members of the various strata. We also note that the naming template can be modified to meet similar, or even somewhat different, custom naming needs for the attribute groups they create via discretization, and encourage them to experiment further with the procedures we have examined together.

Having demonstrated the potential effects that we can achieve using the naming template, in conjunction with Automatic discretization (but certainly available to the other discretization methods, as well), 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 leverage the naming template anytime they apply any of the discretization methods offered within Analysis Services to other attributes within their cubes.

9.  Experiment further within the cube browser, as desired.

10.  Select File -> Exit to leave the design environment, when ready, and to close the Business Intelligence Development Studio.


In this article, we continued our exploration of discretization in Analysis Services, this time with the objective of introducing, and gaining some hands-on exposure to employing, custom naming for the attribute groups created within the various discretization methods. Our focus was to go beyond the First Group Member – Last Group Member default that Analysis Services uses in creating group labels during discretization, and enacting the generation of custom labels for our groups.

We first discussed the discretization options that are available (referring to individual articles covering each within this Database Journal subseries), before choosing to work with Automatic discretization in the sample cube, to serve as a basis for meeting the custom naming requirements of a hypothetical client. 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 (and the default naming of the attribute groups) established by the most recent use of the Automatic discretization method.

Once we had a discretized the attribute members and examined the default naming of the resulting groups, we discussed the naming template supplied with Analysis Services, describing its parts and their uses. We next modified the template to meet the naming requirements requested by our hypothetical client, and placed the syntax within the Format property of the affected attribute. We then reprocessed the cube to enact the new naming template we had supplied, within the context of Automatic discretization of the selected attribute members. Finally, we performed a final examination, via the browsers in both the Dimension Designer and the Cube Designer, of the members of a select attribute hierarchy, noting the new, more intuitive grouping, together with more user-friendly labels, 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.

» See All Articles by Columnist William E. Pearson, III

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