One of the most attractive features of many computer based visualisations is the ability to animate visual representations and see how they change over time.
Watch the following presentation by Hans Rosling:
Who ever thought a statistics talk could double up as a live performance? But did you notice what sorts of techniques Hans Rosling used to explain the story that the animated data was telling?
Read Six Simple Techniques for Presenting Data: Hans Rosling (TED, 2006), which analyses Rosling's presentation, and in particular how he works with the visualisation, to narrate the stories the data tells, and then watch the video again. Even if you never have to give a 'live' presentation about data, you may still be able to invoke some of the techniques if you ever have to provide a written explanation about a data set.
The Trendalyzer application works best with multidimensional sets of continuous numerical data collected over a long period of time (that is, longitudinal data sets). Such data is often found in the social sciences - as Rosling's talk suggests.
How does the Trendalyser animation help you spot correlations - or anomalies - in the data presented? How does the visualisation manage to communicate changes in several variables at once (and how many variables can it describe at the same time)?
If you would like to 'play' with the Trendalyzer visualisation tool that Rosling demonstrated, and the UN data he visualised with it, you can find it here: Gapminder World. You might notice that the application actually provides different 'views' over the data - either as a chart against (user selected) numerical axes, or overlaid on a map.
You can create your own Trendalyser animated displays by using a Google "Motion Chart" gadget.