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 :: Hello :: 


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 :: Hello :: 


I teach people to work with data. I believe that everyone – everyone – can use data to help them do the things that are important to them and to do those things better. And so I teach people the principles and the practices that will help them get useful insights and concrete suggestions from their data. I teach online via my own company, datalab.cc, through Lynda.com/LinkedIn, and on YouTube. I teach in person as a professor at Utah Valley University and in workshops that I organize for datalab.cc or with my partners. And, finally, I teach through the books that I have written.

 
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 :: Tech :: 


 :: Tech :: 


You need tools to work with data. Basic tools include programming languages, specialized statistical and visualization applications, and everyday tools like Microsoft Office, Google Drive, and Apple’s iWork suite. I have taught people to use these tools through online channels, in-person settings, and in print media. The goal is never to master all of the tools or every aspect of a tool but, rather, to be sufficiently familiar with an adequate range of tools that you can easily and efficiently accomplish the tasks before you. 

 
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 :: Art :: 


 :: Art :: 


I love art. I believe that practicing art makes for a better data science practice. But mostly I love it because it’s art: it’s beautiful, rewarding, expressive, and fun. I have deep connections to art: I studied design for most of my undergraduate career; I’ve been involved with modern dance for years; I love poetry; I’m a regular patron of the opera; I play the saxophone – of which Gioachino Rossini exclaimed “This is the most beautiful sound I have ever heard!” – and I’m working on methods for computer-assisted composition and live looping in the indie classical genre.

But it was only a few years ago, when I was on a sabbatical to learn more about data visualization, that I (re)discovered the connection between my data work and my aesthetic interests. I learned about “creative coding” and how to use visualization tools – Processing, in particular – to create art. I also learned how to use Max/MSP/Jitter to create music and, at the same time, capture, analyze, and transform video. These developments led to a surprising turn for a data person: showings in two galleries, a commission for a modern dance performance – in partnership with choreographer Jacque Bell (and my wife) – and two years at Utah Valley University working with a Presidential Fellowship to devise methods for live video looping in modern dance. And, through it all, I have maintained an abiding interest in using the lessons learned to enrich my data practice and teaching.