Dashboard Components are the building blocks for creating a Dashboard Layout. It allows you to condense and aggregate data and transform it into meaningful, visual representations. Each component is built on a database stored procedure for its data source, created within the customers SQL database environment. Only stored procedures in the Report schema are available to be used. They must begin with spCHT.
Defining a dashboard component.
Most of the configuration settings for dashboard components are optional. In order to provide the greatest out-of-the-box user experience, administrators should take the time to define these settings before the user adds it to a layout. Settings can be further tailored by the user in the layout as well.
Tailoring does not impact the default dashboard component configuration; it only enhances the instantiated configuration further. Additionally, changing the defaults afterwards does not affect instantiated components on layouts.
Insight provides a set of predefined dashboard components that can be used as inspiration for creating your own dashboard components. Insight is delivered with a collection of predefined dashboard components, which can be used as it or inspiring the creation of additional ones.
Stacking.
Stacking aggregates multiple series on the argument axis, allowing you to visualize the total on the value axis. This technique is ideal when the overall sum is more important than individual series values.
For example, viewing different classes of products assembled across a certain timeframe, where the quantity of products assembled in total is the important data, and the breakdown of the individual class segments are interesting but not the principal factor.
Marks/Hints.
Marks are visual elements in a chart that display a series' value without needing to check the value axis. Hints appear when a user hovers over a series, serving a similar purpose to Marks. The styling and visibility of both can enhance data clarity and minimize clutter based on the chart's content.
Axis.
Axis customization is an aspect of data visualization that lets users tailor the appearance and behavior to enhance readability and clarity. By adjusting axis elements such as increments, ranges, and labels, users can highlight specific data trends or ensure accurate representation of information.
Legend.
A Legend serves as a descriptive guide for the series. The purpose of a Legend is to act as a reference guide to what is being shown on a chart, adding clarity when multiple series are being represented. In single value mode charts, it's advantageous to turn the legend off to save real estate due to the simplicity of the data.
Reference Values/Strips
Reference Values can be added to a chart in order to provide context in relation to a standard, goal, or range. Used as comparison elements, they can be added to emphasize underperformance or overachievement using colors and text can be used as indicators.
Parameters.
A parameter is a predefined, user-selected boundary that controls the scope of data sets. Rather than allowing free-form text entry, parameters must be selected from established lists, ensuring accuracy in reporting and data analysis.
Parameters are managed within lookup tables under the Parameters section. Users have the flexibility to add custom parameters as needed, enabling more tailored reporting options. A key aspect of parameters is their integration with dashboard components, especially date range parameters. These can be reserved for words like Today, This Month, or Last Quarter, which act as references rather than hard-coded dates.
This allows dashboard elements to remain current without requiring manual updates. However, if a hard-coded date range is applied, it will not update automatically unless the parameters are edited.