In past releases of Oracle Utilities Application Framework, Query Zones have been a flexible way of display lists of information with flexible filters and dynamic interaction including creating and saving views of the lists for reuse. In Oracle Utilities Application Framework V4.3.0.6.0 and above, we introduced the Cube Viewer, which extends the query model to support pivot style analytical analysis and visualization of operational data. The capability extends the ConfigTools (aka Task Optimization) capability to allow implementations to define cubes and provide interactivity for end users on operational data.
The Cube Viewer brings together a number of ConfigTools objects to build an interactive visualization with the following capabilities:
- Toolbar. An interactive toolbar to decide the view of the cube to be shown by the user. This includes saving a view including the criteria for reuse.
- Settings. The view and criteria/filters to use on the data set to help optimize the analysis. For example you might want to see the raw data, a pivot grid, a line chart or bar chart. You can modify the dimensions shown and even add rules for how certain values are highlighted using formats.
- Filters. You can decide the filters and values shown in the grid within the selection criteria.
- View. The above configuration results in a number of views of the data.
An example of the Cube Viewer is shown below:
The Cube Viewer has many features that allow configuration to optimize and highlight critical data whilst allowing users to interact with the information presented. In summary the key features are:
- Flexible View Configuration. It is possible to use the configuration at runtime to determine the subset the data to analyze and display format as a saved view. As with query portals, views can be saved and reused. These views can be Private, Shared (within an Access Group) or Public.
- Formatting Support. To emphasize particular data values, it is possible at runtime to alter their display using simple rules. For example:
- Visual and Analytical Views. The data to be shown can be expressed in a number of view formats including a variety of graph styles, in grid format and/or raw format. This allows users to interpret the data according to their preferences.
- Configurable using ConfigTools. The Cube View uses and extends existing ConfigTools objects to allow greater flexibility and configuration control. This allows existing resources who have skills in ConfigTools.
- Comparison Feature. Allows different selection criteria sets to be used for comparison purposes. This allows for difference comparison between two sets of data.
- Save View as "Snapshot". It is possible to isolate data using the interactive elements of the Cube Viewer to find the data you want to analyze. Once found, you can save the configuration and filters etc for recall later, very similar to the concept of a "Snapshot". For example, if you find some data that needs attention, you can save the view and then reuse it to show others later if necessary.
- Function Support. In the details additional functions such as Average Value, Count, Maximum Value, Median Value, Minimum Value, Standard Deviation and Sum are supported at the row and column levels. For example:
Cube Views may be available with each product (refer to documentation shipped with the product) and Cubes Views can be configured by implementers and reused across users as necessary. Over the next few weeks a step by step guide will be published here and other locations to show the basic process and some best practices of building a Cube Viewer.