UPDATED 13:07 EDT / JANUARY 25 2012

NEWS

A Perfect Match: When Big Data Met Node.js

Battery Ventures’ Todd Papaioannou announced live on theCUBE yesterday that he is transitioning out of the venture capital firm to form a new Big Data start-up called Continuity.

Papaioannou, speaking live from the Node Summit in San Francisco, was short on details other than to say that Continuity is “in the Hadoop ecosystem” and that the start-up will announce more funding details later this week.

However, during the interview with SiliconANGLE founder John Furrier, Papaioannou shared his views on what’s needed from the Big Data industry going forward that may shed light on his plans for Continuity.

Real-Time Big Data Applications Needed

Echoing Wikibon’s 2012 Big Data predictions, Papaioannou said the next evolution for the Big Data industry must be the development of interactive Big Data applications that incorporate real-time data. Said Papaioannou:

Once you’ve got the [Big Data] infrastructure and plumbing deployed, then what? You need to build applications. Well, building applications on distributed systems and real-time distributed systems is super-hard. So there’s a whole focus on developers that’s going to come, that’s the natural next wave for Big Data.

Node.js, the red-hot programming language, will play an important role, he said.

I think the most interesting things that are going on in the next decade are Big Data applications. Big Data applications and fabrics are the next generation middleware. And then when you actually get out to where the consumer is, that’s where node comes in.

Where node has really taken off is it really allows you to focus on the application, focus on way more [data] connections so you can actually be pumping real-time data backwards and forwards. So I think that node and Big Data and the real-time web and continuous business s intelligence is going to be one of the key trends we see in this environment going forward.

I think Papaioannou is right on the mark here. As I’ve said before, packaged applications built on modern languages like Node.js that allow traditional enterprises to operationalize insights gleaned from Big Data and related analytics are the key to realizing impactful business value from Big Data. This is particularly true for “traditional” enterprises that don’t have the staff or expertise to build Big Data applications themselves but are instead looking for ready-to-go applications from the vendor community that turn the theoretical benefits of Big Data into concrete business results.

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Big Data Analytics Without Coding

Another area Papaioannou highlighted was the need for analytic platforms that allow not just Data Scientists but less technical business analysts to manipulate and derive insights from Big Data without needing to be versed in complex coding.

“Our job as an industry is to be able to allow the people that are used to sitting in Excel or sitting in Microstrategy to be able to do data science with really useful tools,” Papaioannou said. “You shouldn’t have to write code to get value out of the data.”


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Again I think Papaioannou is on to something. It’s well known that the ranks of qualified, experienced Data Scientists are thin. Really thin. According to McKinsey, “by 2018 the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills.”

There are two ways to deal with the data science skills gap. One is to train existing business analysts in the ways of data science, as well as to develop more data science educational opportunities for college students. The other is to develop intuitive tools that reduce the level of analytic sophistication needed to perform data science.

Realistically its very unlikely that training and education alone will produce the needed number of Data Scientists in the near term, say the next five to ten years. Of course training and education are critical in the long term, but the analytic platforms and tools Data Scientists use to do their work must become easier to use, as Papaioannou described, if Big Data analytics is to become attainable to the average enterprise in the here-and-now.

So while Papaioannou wouldn’t divulge just what his new start-up Continuity is focused on, my bet is that is something in the application and analytics layer of the Big Data stack rather than the infrastructure/plumbing layer. That’s where the real action is.

Papaioannou had a lot of other great insights, including his take on the Big Data vendor landscape, so definitely check out the full interview (below) if you didn’t catch it live. Also, check out our new pub DevOpsANGLE.


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