Big Data in NYC is all business, and that's a good thing

At the NYC Data Business Meetup, constituencies congregate to foster Big Data, beyond its mere technology.
Written by Andrew Brust, Contributor

The panel at last week's NYC Data Business Meetup

I've now attended two meetings of the NYC Data Business Meetup, a group that serves as a scale model for the wider Big Data phenomenon.  The group is run by Matt Turck and Shivon Zilis of Bloomberg Ventures, and that's a good start right there.  Turck and Zilis are involved in the funding side financial technology and seem to have both the connections and good taste to pull in executives from some of the hottest Big Data startups.  And they do good venues too, having so far booked very nice rooms in the Midtown Manhattan headquarters of parent company Bloomberg L.P., which is arguably the oldest Big Data company out there. All-star cast At the most recent meeting, the panel consisted of leaders from "NewSQL" database player VoltDB, Cassandra in-the-cloud provider DataStax, hosted Business Intelligence (BI) and dashboard vendor RJ Metrics and customer analytics specialist Custora.

It's not all about the speakers though; the audience is pretty impressive too. The most recent meeting, which took place on May 21st, had about 150 people in the audience, and that was on a day that saw almost incessant torrential downpours in NYC. At the prior month's meeting, which took place on a much nicer day, there seemed to be more like 200 people attending and the rather large meeting space was standing-room only.

What's on the program? Turk and Shivon keep things moving nicely.  At the two meetings I've attended, each panel member was given about 10 minutes to make a quick presentation about his company's products, mission and work.  Afterwards, attendees ask questions that have so far been well-above-average in quality compared to other meetups and startup gatherings I've been to.  Turck has the panel share the questions and encourages just enough banter to keep things entertaining without getting contrived.  Analysts, IT customers, entrepreneurs and budding Big Data practitioners come to the meetings. 
This mix is reflective of the hot and growing tech startup environment in NYC and its traditional mix of other core industries like financial services and media.  These meetings have been truly exciting to attend and the super-high enthusiasm and morale at these gatherings is contagious.
The San Francisco Bay area and Silicon Valley may still be bigger for tech, but New York's combination of companies offering Big Data services and products, along with the those companies' customers and critics, is what gives these meetings the edge and energy that I find so remarkable.
End game There was some symbolism at the last meeting that was not lost on me though.  The meeting took place on the second day that Facebook traded publicly, and the Bloomberg news zippers around the building were emblazoned with headlines about the shares closing below the offer price.  Someone in the room mumbled that this tech bubble had burst.
During the Q&A session I asked the panelists a somewhat loaded question: how did they see consolidation in the Big Data space playing out?  Would Big Data companies merely go through a shake-out, with the strongest surviving?  Would they merge with each other?  Or would the "megavendors" like IBM, Oracle, Microsoft and SAP each do a round of acquisitions, and simply add Big Data to their enterprise stacks, as they had done with so many former BI startups and pure-plays?

Exceptional, or maybe just different? One or two panelists seemed a bit thrown off by my question.  Others earnestly felt the Big Data world was unique and didn't fit the enterprise software stack template, citing Splunk as an example.  I'm skeptical, to be honest. 

But I'm also genuinely optimistic.  Bubble or not, I've always believed that companies focused on data have huge value that transcends their hype cycle. Plus, startups and their funders have done such a good job at making Big Data a household term that I think the residual post-bubble activity will be a larger phenomenon than the BI and relational database bonanzas that preceded it.  Big Data is here to stay, and real events with real people are -- for me at least -- proving that out.

Photos courtesy of Matt Turck

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