UF Dashbuilder - Real time dashboards

   Dashboard solutions face different scenarios when it comes to data retrieval. While some dashboards do not require frequent updates as the data doesn't change very often or even rarely, other dashboards may require constant updates, because its data changes at a very fast pace. Therefore, we can classify our dashboards into two main groups:

• Analitics: usually focused on the analysis of information about the past (historical/statistics), or about information that is known in advance (forecasts). The main trait of these dashboards is that data does not change very often and the time frame is usually long. Some examples: A company's sales evolution and forecast, sport statistics in general, etc.

• Real time: their main trait is that data changes at a very fast pace. Therefore, this requires to update the indicators & reflect the changes in the UI frequently. Usually, the data is bound to a very short time frame, such as the last 10 seconds. Real time dashboards are typically used to monitor critical resources or systems, for example: Health display sensors, IT resources, air traffic control, etc. 

   Here is a comparison table which summarizes the main features of both:

	Analytics	Real-time
Data changes very often	No	Yes
Time frame	Any	Short
Amount of information	Any	Little
Dashboard updates	Rarely	Frequent

  Dashbuilder is a general purpose dashboard solution. One of its design goals is to support both approaches. The following video shows an example of a real time dashboard built using the Dashbuilder GWT Client API (do not forget to select HD). The dashboard contains some metrics about an emulated cluster (the values shown are not real).

Real time dashboard example

   The dashboard is part of the Dashbuilder examples gallery and it's basically a GWT UI binder widget (source code here).

   Not only we allow for creating programmatic dashboards but also for custom ones created by end users. The next video (select HD) is a demo of how to create a real-time dashboard from scratch using the tooling. Here again, we're using the emulated cluster metrics data set, so the values shown are not real.

Creating a real-time dashboard

    As you can see, Dashbuilder covers a wide range of scenarios. As we introduced in this blog entry, data can be extracted from different systems. Once you have the data you can easily create your own visualizations. Both the analytics and real-time approaches are supported out of the box.