Data visualization is perhaps the most promising of formats with the proliferation of Big Data.  Stimulating multiple areas of the brain, visual feedback is one of the best paths to knowledge comprehension.  And as data becomes increasingly democratized in the workplace and beyond, determining the best interfaces for consuming that data will fundamentally change its actionability.

Now that the Big Data trend is settling into a well-worn path, its many subsets are branching out into their own applications.  We’re seeing increased demand for accessible data, leading to more businesses addressing the need.  New software solutions are emerging for enhanced data consumption, adding to the SaaS model that’s aiding the cloud movement today.  One such business is Tableau, a leader in data visualization that’s evolved from a Stanford project to a commercial offering, debuting a successful entry onto the NYSE under the clever ticker: DATA.

Just before Tableau’s IPO we caught up with the company’s Software Director of Visual Analysis, Jock Mackinlay, who provides some great insight on the skills required for data visualization today, the junction of data visualization and the real-time web, and a couple of things he’d like to see from the industry at large.

What cloud collaboration trends are you seeing with data visualization?

We’re definitely seeing more and more people putting their data in the cloud and working together.

We also have Tableau Public – very interesting for this question.  It’s been out since 2009 and it’s free for journalists, students and bloggers.  There’s a huge amount of story-telling going on here.  Tableau Public has been growing.  We just sent an academic paper on its growth and the rates indicate there’s a huge potential here, and definite interest.

Top 3 most necessary skills in data visualization?

One thing that’s been in the press a lot is Big Data and Data Scientists. To do so, you have to be a broad range of skills – programming, stats, information architectures.  That’s at the high end.

At the democratization end where i’m interested in – anyone can get started.  Basic analytics skills in wanting to get answers from your data.  Slowly over time you can acquire an understanding of how data analysis goes.  You may have to clean it a bit  (sorting) to answer the right question.  The nice thing is you don’t have to become a specialist – those are valuable skills but not the ones you need to start with.  You don’t have to go to your organization’s statistician to get answers.  Today you can DIY.”

Ideal junction for data visualization and real-time web?

There’s certainly applications where real-time is absolutely important. A classic example is, traders watching the stock market. Tableau is not privileged with those types of applications, though it could be someday.  The good thing is, with Tableau, since you’re directed to the database every time you refresh, you get the latest data.

Live data vs. real time – I think a lot of people can use live data.  It’s the static, old data they don’t want.  For real-time, you’ll often use custom visualization tools.  Not the focus of Tableau.

2 things you’d like to see from the data visualization industry?

1.  I spent years being very active in the academic community in data visualization, and what I’d like to see here is more understanding in databases and actual practices in computation.  They’ve turned this way – not just classic (SQL) DBs, but Hadoop, MapReduce – that’s really interesting.  It’s a good space for researchers, and takes advantage of the technologies.

2.  Understand that it’s not just about building use cases for visual data, but it needs to be embedded in the user experience.  Human-computer interaction is as important as the visual aspect.  Let a person think with data along the flow of thought.  Slow and clunky tech affects your focus and ability to understand and leverage data.