Lots of people wouldn’t really consider tools like ‘ggplot’ true visualization tools, but in some disciplines it’s exactly what’s called for: Simple visualization with no fuss. A talk given by Hadley Wickman, and available online, discusses its use along with the popular statistics package R.
Data analysis, the process of converting data into knowledge, insight and understanding, is a critical part of statistics, but there’s surprisingly little research on it. In this talk I’ll introduce some of my recent work, including a model of data analysis. I’m a passionate advocate of programming that data analysis should be carried out using a programming language, and I’ll justify this by discussing some of the requirement of good data analysis (reproducibility, automation and communication). With these in mind, I’ll introduce you to a powerful set of tools for better understanding data: the statistical programming language R, and the ggplot2 domain specific language (DSL) for visualisation.
The challenge that utilities are facing is how to attract and retain younger workers in what is becoming an increasingly competitive market place. What I am seeing is that 3D technology can help. The net generation is conversant with communications, media, and digital technologies and in particular have been brought up with gaming technology, PSPs, XBoxes, and Wiis. Many modern 3D design applications, which use the same 3D visualization tools that were developed for the gaming industry, provide an environment that is much more familiar and stimulating for the millennial generation, who may perceive traditional 2D design as something left over from the dark ages. In the last few months I have come across several utilities who are finding that for this reason 3D engineering design technology can contribute to attracting and retaining younger workers.
AEC Infrastructure management guru at Autodesk and author of 
VizWorld.com 
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