Data Analysis Features
Just having data displayed into a gauge does not allow for easy interpretation. One of the features that separates Dundas Gauge from the competition is its extensive data analysis feature set.
Dundas Gauge does not just show incoming data, but we are also performing data analysis to give end users a value that is more meaningful. Just having data coming in can be chaotic, so making use of moving averages, min max values, as well as data dampening and the use of intervals, helps to understand the incoming data.
Events
Events also allow the gauge to respond to "important" data. For example, if a gauge was set up to monitor CPU load, and data reaches a critical level, an email can be sent to the CTO or other party, notifying of the problem. If sales data or inventory data reach a certain level, an event can be fired to call attention to the situation. Dundas Gauge is also built so that it can base events on calculations allowing for the firing of events in more appropriate situations (for example, if average CPU load for a 24 hour period reaches a certain point, etc).
History
Making use of the History functionality within Dundas Gauge is also important because we can now plot data from the Gauge into a chart or other format, allowing for more in-depth analysis (which is why Dundas Chart for .NET is a great complimentary product to Dundas Gauge.)
You can also pre-load history into a gauge, allowing for more accurate use of statistical analysis (i.e. average values, etc.) This is important after recovering from a system failure, or for preloading an application for example.