Reports Defined

Like scorecards, Reports in PerformancePoint will ultimately be displayed as a web part on a SharePoint page. Reports can be of several different varieties, each of which requires you to have a corresponding data source of the same type:

• Analytic Chart— Interactive charts, based on OLAP cube data, such as SQL Server Analysis Services, can be in bar, line, and pie chart format.

• Analytic Grid— Also based on data from OLAP cubes, Analytic grids display rows and columns of processed data.

• Excel Services— Allows for views of any components from Excel Services.

• KPI Details— View detailed information about any KPI line item.

• ProClarity Analytics Server Page— Create a reference to an existing ProClarity Analytics server page.

• Reporting Services— Reference an existing report from SQL Server Reporting Services.

• Strategy Map— Create a strategy map report that is connected to a scorecard by using Microsoft Office Visio 2007 or 2010.

• Web Page— Create a reference to an existing web page

Of all the report types, the Analytic Chart is one of the most interesting and most often used by organizations. When connecting to a well-defined Analysis Services OLAP data source, you can drag any combination of relevant measures and dimensions to the series and Axis sections to quickly spin up various charts.

Even more interesting, however, is the ability to click any data point within the chart and drill down to see how the chart changes based on the selected factor. Imagine the power of an executive viewing corporate sales data to re-create the chart, on-the-fly, based on any of the following:

• Salesperson

• Region

• Product line

• Year, month, quarter, week, or day

• Customer

Figure 30.9 shows a simple report showing the progression of sales on a quarterly basis. Notice that the user, when viewing the chart, has several options. He can drill down to view the chart based on one of the other dimensions. Additionally, he can sort, filter, pivot, and perform a number of other additional actions.

Figure 30.9. Drilling into information data using key data dimensions.