A dashboard report provides a concise view of key metrics. Those metrics might include costs, sales, customer satisfaction, or other measures critical for monitoring goals and trends. A dashboard report has the look and functionality of a dashboard in a car or plane, displaying data as a set of graphic representations. Figure 25‑2 shows an example of a dashboard report.

An effective dashboard report distills extensive detail data onto a single page, and highlights trends or potential problems. A typical dashboard report presents a series of charts to display data from different perspectives, for example, sales data by product, by customer, by sales manager, and by region, as shown in Figure 25‑2.

A chart relies on data derived from typically hundreds, even hundreds of thousands, of data rows. If the data is stored in a database, you can write a query that groups, aggregates, and filters the data to return a small subset of the rows that can be used as summary data for a chart. If a dashboard report displays multiple charts, creating multiple data sets, each running a different query, can be resource-intensive.

To build a dashboard report, it is sometimes more efficient to create charts that reference, or reuse, data in another report element, typically a table or a cross tab. A data set you create for a table or a cross tab frequently returns a large number of data rows, which the table or cross tab then groups and aggregates to display the data in an organized, readable format. By using table or cross tab data, it is possible to create a single data set that multiple charts access through the table or cross tab.

A key point to remember when creating a chart that uses data from another report element is that the sorting, groups, aggregations, and filters defined in the report element also apply to the chart. You cannot sort, group, aggregate, or filter data differently in the chart. Rather than being a limitation, this behavior helps synchronize the data in various report elements.

For example, the report in Figure 25‑3 shows a series of charts that use data from a cross tab. The cross tab defines a filter that enables the report user to specify at run time the quarters for which to get sales data. Each time the report runs with a different value, the cross tab and all the charts display sales data for the selected quarters. This report illustrates the primary advantage of using another report element’s data—dynamic and consistent data updates.

A table is the most common element for displaying data. A table can display pages of detail data or just summary data. You can group data to show hierarchical views of the data, display aggregate information at any group level, and filter data at the table and group levels. Because you can manipulate data in a table in ways not possible at the data set level, the table is most often used as the source of data for charts, when presenting the same data in a table and a chart.

The report in Figure 25‑4 shows four charts and four tables that display summary sales data in various categories. Each chart uses data from the table below it, for example, the Top Products chart displays the top products listed in the Top 5 Products table. When data in any of the tables is updated, the data in the corresponding chart is updated, too. Figure 25‑5 shows the same report updated to display the top four performers in each category.

The previous report showed how you can base a chart on a table that displays summary data. You can also base a chart on a table that displays detail data. The report in Figure 25‑6 shows two charts and two tables. The table on the left displays detailed sales data grouped and aggregated by order number and country, and filtered to display only sales in the top three countries. The Top Countries chart uses data from this table to display the sales totals for the top three countries. The table on the right displays similar sales data, except by sales representative instead of country. The Top Sales Representatives chart uses data from this table to display sales totals for the top three sales representatives.

This procedure assumes you have already created the table that contains the data to share with the chart.

A cross tab is the ideal element for displaying aggregate data, or measures, by multiple categories. Many types of charts are also suitable for displaying aggregate data by different categories, although not by as many categories as a cross tab. To show aggregate data by x and by y, use a chart to present the data graphically and a cross tab to present the data in a compact row‑and‑column matrix.

To present the same data in both elements, it makes sense for a chart to leverage the data in the cross tab. After you define the initial measures in the cube and insert them in a cross tab, the cross tab calculates all the subtotals and grand totals and creates all the necessary column bindings. The report in Figure 25‑3 shows three charts—order totals by product line, totals by quarter, and totals by product line and by quarter—based on a single cross tab. Figure 25‑11 shows the column bindings that BIRT creates for each measure and dimension in that cross tab.

When specifying data for a chart that uses cross tab data, all you do is select a measure to use as the value series. You do not select a dimension for the category series because a measure already defines the category or categories by which the aggregate data is grouped. For example, the measure defined by the column binding ORDER_PRICE_Group/PRODUCTLINE returns the sum of order prices by product line groups. ORDER_PRICE_Group/PRODUCTLINE_Group2/quarter returns the sum of order prices by product line and by quarter.

Based on the measure you select, the chart builder assigns the appropriate dimension to the category series and, if applicable, to the optional Y series grouping as well. Figure 25‑12 shows the measure ORDER_PRICE_Group/PRODUCTLINE_Group2/quarter selected for the value series. The chart builder assigns data["PRODUCTLINE"] to the category series and data["quarter"] to the optional Y series grouping. As the Chart Preview shows, the chart displays order price totals by product line and by quarter.

This procedure assumes you have already created the cross tab that contains the data to use in the chart.

To display identical data in a series of charts, create one chart as the primary element, then create the other charts to use data from the first chart. Figure 25‑16 shows an example of a bar chart, a pie chart, and a line chart displaying identical data, sales by product line.

In the example shown in Figure 25‑16, the bar chart is the primary chart. The bar chart defines the data to use in the value and category series, and controls how the data is sorted, grouped, aggregated, and filtered. The other charts reuse this data; you cannot make any modifications to the data in the pie chart or line chart. To change the data that appears in all three charts, edit the bar chart.

Figure 25‑17 shows the data definition for the bar chart. This chart uses data from a data set, Sales By Product Line. Value (Y) Series displays data from the TotalSales column, and Category (Y) Series displays data from the PRODUCTLINE column.

Figure 25‑18 shows the data definition for the pie chart, which uses data from the bar chart. Notice that the data specified in Slice Size Definition and Category Definition is the same data specified in the bar chart and is read‑only.

This procedure assumes you have already created the primary chart.