By: Gigaom
Can Visual.ly spawn the data scientists of the future?
We live in a big data world full of complex algorithms calculating trends and patterns among any type of data one can imagine, but gaining the skills to do big data requires a lot work. The first step might be realizing that data can be fun.

We live in a big data world full of complex algorithms calculating trends and patterns among any type of data one can imagine, but gaining the skills to do big data requires a lot work. The first step might be realizing that data can be fun.

My web database comparison using Visual.ly.

On Monday, infographic hub Visual.ly began its quest to bring this idea to the masses, releasing a new feature that lets users instantly create infographics based on statistics from competing Twitter accounts or from their own Facebook accounts. While the tool’s current utility is questionable, Visual.ly Create could have some profound effects on the future of visualization as it opens its doors to different data sets.

Experimenting with the new Visual.ly Create feature as it currently works, it’s easy to spot the limitations. Showdown-style infographics comparing Twitter followers aren’t particularly useful for anyone not somehow connected to the social media field, and visualizing data from one’s own Facebook page isn’t exactly an ideal vehicle for spreading meaningful information. They’re fun, yes (so fun, in fact, that the system was hammered all day and resulted in some serious processing delays), but fun only goes so far.

However, Co-Founder and Chief Content Officer Lee Sherman told me, the company is planning some serious customization options that I think could help introduce a generation of children and teenagers to working with data and visualization. We’re not talking about visualizations as unique or advanced as what you see certain data journalists doing, the type of stuff that pops up on Flowing Data every day. Just a tool that makes it easy, fun and rewarding to spend a little time thinking about data.

The problem is that we need more people with math skills to meet growing employer demand for data scientists and data analysts. But how do you get started caring about data in the first place when the barriers are so high? Really working with data requires a deep understanding of both math and statistics, and Excel isn’t exactly a barrel of monkeys (nor are the charts it creates). Applications like Tableau make it a little easier and the results more visually stunning, but they’re still business intelligence products aimed at professionals. At our Structure: Data event next week in New York, we’ll talk about all sorts of new tools for making big data easier, but none are apps in the sense that today’s teens are used them.

This wasn't made with Visual.ly. (http://blog.thejit.org/2012/02/27/wind-motion-patterns/)

Think about every lame report you ever wrote or every essay you turned in based on little more than your own opinions. If it were relatively simple to produce a visually captivating graphic that used data to illustrate the point you were trying to make, or to pose a point of comparison for consideration, wouldn’t you have used it? Quantified-self apps are hot right now in part because people get addicted to data once it’s made easy to digest. But, as with visualizing your Facebook profile, that type of data isn’t very useful beyond your own body.

That’s where Visual.ly — whose founders came from personal-finance startup Mint.com — come in. Sherman said they’re trying to marry the ease of use that exemplifies Mint with the greater data world. And while right now that means just making some instant graphics using Twitter and Facebook data, that will soon mean access to various APIs and publicly available data sets, as well as letting users upload their own data and even mashup data sources. Ultimately, Sherman said, users will be able to move away from prepackaged infographics and actually edit the fields themselves.

Whether it’s Visual.ly or something similar that ends up making infographics and other visualizations mainstream, it has to happen. The data revolution is too important to remain the haunt of only the best and the brightest, but it will take something to convince everyone else to give data a chance. The ability to create a worthwhile visualization via an app could be that something.

Wind-motion patterns image courtesy of Nicolas Garcia Belmonte.

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