The context menu, with our selection circled, appears in Illustration 30.
Illustration 30: Select Data Point Attributes
The Data Point Attributes selection dialog appears.
29. Click the Warehouse tab to bring it to the front, as necessary.
30. Double-click All Warehouses on the tab.
31. Double-click USA, which appears along with the two other countries under the expanded All Warehouses.
The three states in which we have warehouses now appear.
32. Click-highlight CA.
33. Select any shade of Red in the Color selector.
34. Select "* Star" in the Shape selector.
35. Click Add.
CA appears in the Rules list, with a red star to its left.
36. Click-highlight OR.
37. Select any shade of Blue in the Color selector.
38. Select "* Star" in the Shape selector.
39. Click Add.
OR appears in the Rules list, with a blue star to its left.
40. Click-highlight WA.
41. Select any shade of Green in the Color selector.
42. Select "* Star" in the Shape selector.
43. Click Add
WA appears in the Rules list, with a green star to its left.
The completed Data Point Attributes selection dialog appears as depicted in Illustration 31.
Illustration 31: Data Point Attributes
The view appears, as presented in Illustration 32, showing that, although Warehouse Profit and Cost amounts varied among the states for the three product families, profit margins / ratios, at least at this level of rollup, were not dramatically different (note that the points plotted approach a straight line).
Consistent with the behavior of the application in other areas, we can see the amounts that underlie each coordinate by simply hovering the pointer over it. The values that make it up appear, as shown for one example in Illustration 32.
Illustration 32: Perspective - Final Data View
The uniformity we see in our results is largely due to the fact that this is a sample database; we might also attempt the same exercise at lower levels in the Product dimension hierarchy to isolate differences that are more meaningful. Were there significant outliers, we might investigate the details further through other analytical approaches. Whatever the case, the ProClarity Perspective view is an excellent tool for uncovering patterns for our various business purposes.
45. Select Book --> Add to Briefing Book from the main menu.
The Add to Briefing Book dialog appears.
46. Name the page something meaningful. (I called mine ANSYS19-03.)
47. Click OK to save.
48. Select File --> Save Book.
49. Select File --> Exit when ready to close ProClarity.
We have examined only a handful of the options available to analysts in ProClarity. Much of the available body of functionality, including the numerous ways to save, publish and otherwise deploy the results of analysis and other report components, can be reviewed within the online documentation. This would be an obvious next step for anyone interested in evaluating or learning the application further.
ProClarity is a rising star in the business intelligence market, particularly because MSAS is gaining acceptance as a low-cost source of robust OLAP data sources. ProClarity and other solutions that capitalize on the MSAS cube will benefit significantly from the fact that, as the RDBMS-level MSAS cube rapidly gains market share, organizations will seek to choose more pragmatic solutions that let MSAS handle cube builds, while focusing solely on OLAP analysis and reporting.
The days of acceptance of the tiresome overhead and financial punishment of a proprietary cube machine, among the other peripheral structures that the previously dominant business intelligence solution providers peddle in their enterprise business intelligence solutions, can no longer be gladly suffered by those organizations "in the know." For the OLAP reporting portion of a larger, custom-fit enterprise analysis and reporting solution, ProClarity is an excellent example of a robust, easy-to-use application that should be evaluated early in the selection process.
In this, the second half of a two-part article, we explored ProClarity Professional in a return to an earlier subseries, Reporting Options for Analysis Services Cubes. Our focus in those articles, as well as this, was to respond to a recurring request from readers to explore options for analyzing and reporting data in MSAS cubes.
After a brief introduction to ProClarity, together with an overview of establishing connectivity between ProClarity and an MSAS cube, we examined some of the options offered by the application for analyzing our OLAP data. We performed practice examples of browsing and analysis from within the application, continually examining the layout and navigation of the ProClarity interface as we practiced its use.
In this two-article set, we provided a hands-on introduction to numerous useful features that are available within ProClarity to provide for analyzing, and creating enterprise reporting components from, data in MSAS cubes. We worked through practice examples of ProClarity's functionality, discussing several key advantages that the tool offers. Finally, throughout our exploration of the application, we exposed various use and navigation tips for the ProClarity interface in analyzing, and reporting from, MSAS cubes.
» See All Articles by Columnist William E. Pearson, III
Discuss this article in the MSSQL Server 2000 Analysis Services and MDX Topics Forum.