Lesson One: Advanced Functions in Ad Hoc Views
Ad Hoc View Overview
The Ad Hoc View Editor
Creating an Ad Hoc View
Calculated Fields
Calculated Measures
Ad Hoc View Tips
Lesson Two: Ad Hoc View Types
Working with Tables
Working with Crosstabs
Working with Charts
Formatting Charts
Highcharts: Advanced Chart Formatting
Lesson Three: Creating a Dashboard
Dashboard Overview
The Dashboard Designer
Creating a Dashboard
Dashboard Properties
Dashlet Properties
Previewing a Dashboard
Editing a Dashboard
Lesson Four: Advanced Dashboard Topics
Overview: Dashboard Filters
Adding Filters
Mapping Filters
Editing Filters
Overview: Dashboard Hyperlinks
Hyperlinks: Drilling Down
Hyperlinks: Drilling Through
Dashboard Tips
Appendix A: Advanced Chart Formatting Examples
Appendix B: Segmenting Data by Fields
Appendix C: Additional Resources
This class will provide an in-depth look at advanced functionality with Ad Hoc Views and Dashboards.
With successful completion of this course, students will be able to:
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An Ad Hoc View can be used to explore data, and provides analysis options (such as slice, pivot, and filter) to help you recognize trends and outliers in your data. You can drill into specific details, or analyze your data at a very high level.
The Ad Hoc View Editor is the interactive tool for exploring your data and designing views. Figure 1 and Table 2 explain the components of the Editor and their functionality.
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Calculated fields are user-generated fields that allow for manipulation of data in the Ad Hoc Editor. The most common type of calculated field is a concatenation; for example, combining the ID and Name of an entity into a single calculated field.
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Calculated measures allow you to manipulate numeric data. They can be mathematical, like computing the inverse of a number, or logical, including IF statements.
For a list of mathematical and logical operators that can be used for calculated fields and measures, read the Jaspersoft Community Documentation on Operators Ad Hoc Views. |
The computational demands of reporting can be taxing for a database, causing views to take a long time to render. The recommendations below can help you reduce the complexity of your views and increase performance.
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The Ad Hoc Editor allows you to select from three view types:
Tables: Used to view values in the database and to summarize the values in columns.
Crosstabs: Used to aggregate data across multiple dimensions. Crosstabs are more compact representations than tables; they show only computed values, rather than individual database values.
Charts: Used to summarize data graphically. Charts compare one or more measures across multiple sets of related fields. Time series and scatter charts use time intervals to group data. Other chart types compare summarized values for a group; for example, a bar chart that compares the sum of Payments Received for each of the products in each of the cities.
Crosstabs aggregate data across multiple dimensions. They are more compact representations than tables: they show only computed values, rather than individual database values. Crosstabs have different data, layout, and format options than tables or charts. Fields, Row Groups and Column Groups in Crosstabs Fields can be added to crosstabs as row groups or column groups. Measures can be added to crosstab rows or columns as well, but all measures must be included in a crosstab as either a row or a column -- that is, you can add one or more measures to the crosstab as columns, or add one or more measures to the crosstab as rows, but you cannot have one measure as a column and another as a row in the same crosstab. When creating a crosstab-type view, keep in mind that row and column groups are arranged in hierarchies. The group headings can be dragged to rearrange the hierarchy. The right-click option also allows you to select a heading and then move the headings. Rearranging the groups may change the preview data in the editor. To add a field or measure to a crosstab group:
Crosstab Measures Measure labels are displayed in the crosstab based on their status as a row or column:
Measures are arranged in cells. You can add any number of measures. All the measures appear together in every cell. Measures can be re-arranged by dragging them in the measure label area. A right-click menu also provides the following options:
Pivoting Pivoting switches all row and column fields in a crosstab to visualize your data where your rows or columns now iterate as their opposite. This provides the ability to analyze data in a different and possibly more intuitive way.
The slice feature lets you keep or exclude group members in a crosstab. You can select multiple row groups or multiple column groups; you cannot slice by both row groups and column groups at once.
Summarizing Group Data This feature allows you configure group summaries. By default, all row and column groups are summarized automatically. NOTES: For the Summary options:
To configure summarization:
By default, the rows and columns of crosstabs are sorted in alphabetical order of the group names. When the crosstab includes more than one row group or more than one column group, the inner groups are also sorted according to your selection. Only one measure can be used for sorting at any one time; changing the sort order for another measure resets all others to the default.
Resizing and Layout Many of the layout and formatting options that are set manually in tables are set automatically in crosstabs. Row and column sizes are fixed and no spacer is available.
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Ad Hoc charts are a flexible, interactive way to explore your data graphically. You can choose different levels of aggregation for rows and columns, change a field from a column to a row, pivot the entire chart, hide chart values, and zoom in to see chart details. Using Fields and Measures in Charts You must add at least one measure to view a chart. The initial display only reflects the measures you add; it does not change when you add fields or dimensions. For example, for each measure you add to a bar chart, you see a bar with the total value of the measure, regardless of how many fields you add. This means you can add, remove, and arrange measures and fields without waiting for the display to update. Once you have the fields and measures you want, you can use the sliders on the right to select the level of detail you want.
When creating a chart, keep in mind that row and column groups are arranged in hierarchies, with the highest member of the hierarchy on the left. For an Ad Hoc view based on an OLAP data source, you can change the order of distinct dimensions by dragging, but you cannot change the order of levels within a dimension. For an Ad Hoc view based on a non-OLAP data source, you can drag the field headings to rearrange the hierarchy; the highest level in a group should appear to the left; the lowest level in a group should appear to the right. For example, it doesn't make sense to group first by postal code then by country, because each postal code belongs to only one country.
Selecting a Chart Type
When you add a field or dimension to a column or row, a multi-level slider located at the top of the Filters pane allows you to set the level of aggregation to use for viewing the data. The number of fields or dimensions in the row or column determines the number of levels on the slider; measures are not reflected in the slider. ![]() The sliders help you explore your data visually in several ways:
Changing Date Grouping If your chart includes data based on a date field, you can change the level of aggregation for the time data. (Time Series charts can only use day, or smaller, intervals.)
You can get a new view of your data by changing the summary function of a measure, for example, from sum to average.
Like pivoting a crosstab, pivoting a chart switches row and column data to flip how the chart iterates to possibly visualize data in better way. Pivoting removes any custom sorting applied to headings in your crosstab. It does not affect column or row sorts. ![]() To pivot the entire crosstab: To switch the row and column places, click the Pivot icon (
Use the chart legend to hide or show members of the data groups in a chart, as shown in Figure 6. NOTE: Hidden members cannot be saved as part of an Ad Hoc view. When you save a view, or create a report from a view, the chart is automatically reset to show all members. ![]() To hide data on a chart:
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Reduce the Number of Labels By default, every field included in your chart has a label displayed along either axis. Measures show up as numeric values, often along the Y axis, and fields being measured show up as text along the X axis. On some charts - especially those with many fields - these labels may overlap, crowd together, or become difficult to read. You can alleviate this problem by "stepping," or reducing, the number of labels displayed on your chart.
By default, labels on your chart are displayed horizontally. When you have many labels, or very long ones, this can also make chart labels difficult to read. You can change the direction of these labels, on both the X and Y axes, to improve chart readability.
By default, in charts that include only a single measure, that measure's name is not displayed. For instance, if your measure displays the number of employees each store in the region has, that measure's label (which shows the number of employees) appears along the Y- (or value) axis, but the name of the measure ("Number of Employees" or similar) does not. You can, however, choose to display that measure name to clarify the information on your chart.
To change legend settings:
To display data points:
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P2 Reporting HTML5 Javascript Charts are defined with default formatting. While the Ad Hoc Designer provides some basic formatting control via properties that are selected from the Chart Formatting window, in some cases you may require more control over a chart's appearance. The Advanced tab is designed to let you enter formatting commands. With advanced formatting you can apply almost any customization to your chart via Highcharts, an SVG-based charting library that allows usage of JavaScript functions as property values.
Notes
To apply a Highcharts property:
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Dashboard Overview
A Dashboard displays Ad Hoc Views, Reports, and other BI objects in a single, interactive space. By combining types of related content, you can create appealing, data-rich dashboards that quickly convey trends. A Dashboard can also include input controls that allow users to filter the data displayed in the Dashboard.
The Dashboard Designer is a web-based UI for building dashboards. You can compile dashboards that include pre-existing elements, such as reports and views, and create new charts, tables, and crosstabs from your data sources directly from the designer. Figure 9 and describe the components of the Dashboard Designer.
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Building a Dashboard involves creating, adding and formatting Dashboard content. More complex aspects of a Dashboard, such as filtering and hyperlinking, are described in Lesson Four: Advanced Dashboard Topics.
When adding existing content:
To move a dashlet:
To resize a dashlet:
To delete a dashlet:
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You can view and edit the appearance of and basic information for each dashlet on your dashboard, and determine the refresh settings, through the Dashlet properties. The properties vary based on the type of dashlet you are working with. To view and edit the Dashlet properties:
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You can select Input Control values to verify that your filters are working in the preview state.
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Dashboards can be modified to meet your unique needs.
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The true power of dashboards is harnessed by mastering their interactive functionality, such as filtering and hyperlinking.
As with Ad Hoc Views and Reports, you can add input controls to filter the data displayed in a Dashboard. The Filters panel on the left of the Dashboard Designer displays the filters (input controls) that exist within the content that you have added to the Dashboard. When you add an Ad Hoc View or Report that has input controls to a dashboard, the controls do not appear on the dashboard until you explicitly add them, one-by-one. |
You can add filters to define what data is displayed in a dashboard. The input controls of each dashlet appear under the dashlet names in the Filters panel.
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To filter more than one dashlet with the same filter, the Parameter Mapping window is available to help refine your filter mapping. With the Parameter Mapping window, you can specify which dashlets and which parameters are affected by a filter.
To refine filter mapping:
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You can change the labels, or display names, of individual input controls and filters within a dashlet.
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IFS Reporting Dashboards can implement hyperlinks, which allow you to drill down into your data. In other words, you can click data in the Dashboard to open more detailed reports about that data series or point. Hyperlinks can also help you drill through your data. This means you can click in the dashboard to update data in the other dashlets on the Dashboard. Drilling through your data can reveal more detailed information about the data series or point. Wiki Markup \[Hyperlink already constructed via the browse functionality\]?companyId_1=$P\{companyId_1\}
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Using the Dashboard Designer, you can specify other reports within IFS Reporting to drill down to from Ad Hoc View dashlets. After you have setup a hyperlink, with or without passed parameters, you can click your dashlet or values within your dashlet to generate a report.
In Figure 15, the action is set to Open new page, so clicking the dashlet will cause a report to open in a new browser window.
To create a chart hyperlink:
Adding Parameters to Hyperlinks Wiki Markup \[Hyperlink already constructed via the browse functionality\]?companyId_1=$P\{companyId_1\}
Wiki Markup \[Hyperlink already constructed via the browsefunctionality\]?companyId_1=$P\{companyId_1\}
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Drill through functionality allows you to explore your data from multiple perspectives within the Dashboard itself. Adding drill through hyperlinks is like adding filters to a dashboard, because you are filtering dashlets by selecting input control values in another dashlet.
To add drill through hyperlinks:
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This appendix contains example syntax for formatting Highcharts in an Ad Hoc View.
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Learning to design views and reports that utilize your existing data fields to segment the data can significantly impact simplicity and performance. This appendix demonstrates how to generate the same chart using fields to segment data instead of using IF statements.
This method of data segmentation can be applied to tables and crosstabs, with the same performance benefits.
Figure 18. Segmenting Data
Example 1: Using IF Statements To segment a measure by a field:
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