It would be trite to say that when Matt Turck talks about big-data, people listen. But it's true, so I'll say it anyway.
Turck is a managing director at Bloomberg Ventures, the incubation and investment arm of Bloomberg LP, and founder of the NYC Data Business Meetup, the main monthly big-data event in Manhattan.
In addition to organizing meetups and pursuing investment and partnership opportunities for Bloomberg, he helps operate Bloomberg Ventures-incubated businesses. Most recently, he spearheaded the launch of the Bloomberg Institute, which wants to become the world's leading online education and recruitment business for finance professionals.
Before joining Bloomberg Ventures as a principal in 2008, he was a senior director at Oracle. He joined Oracle in 2005, when the company acquired TripleHop Technologies, a venture-backed enterprise software company that Turck co-founded and where he served as president and COO.
Did I mention he started his career as a securities lawyer?
But none of that may be as impressive to big-data pros as the fact that Turck and a colleague recently attempted the near impossible by mapping the rapidly evolving big-data ecosystem. They made a first attempt in June. After more interviews, research, and feedback from people who have a stake in big-data, they released a second version of the map in Ocotber.
"It's still a work in progress and will presumably always be. That's the nature of the beast," he told me. The second version "is even more crowded than the first time around, which reflects the incredible vitality of the big-data space."
I was so impressed with the chart that I decided to ask Turck for even deeper insights -- a state of the union on big-data, if you will. Here are the top five things he thinks you should know.
We're a bit ahead of ourselves in the cycle. As of now, there's a bit of a gap between all the excitement (in the press, conferences, startups, and venture capital circles) and the reality of what most large companies are doing with big-data technologies (still often just starting to dip their toe in the water, in the form of pilots or lab experiments.)
Large companies are often right to be careful with adopting big-data technologies. A number of products are still very new and fairly immature, and a variety of early-stage companies are still largely "science projects," so it's important to evaluate those technologies carefully and thoroughly.
Things are evolving rapidly, however. Big-data (together with cloud computing) is a long-term trend that will play out over a number of years. The needs are real, the technologies to address the needs are maturing quickly, and the excitement draws a lot of smart minds to solving big-data problems, making it a self-fulfilling prophecy that big-data will have a profound impact -- in some ways, a revolutionary impact -- on business and society.
What's truly exciting is that we have barely started scratching the surface. A lot of progress has been made at the infrastructure and analytics level, but the world of big-data applications (whether enterprise or consumer-facing ones) is just starting. Take a look at the chart above for examples of companies doing great things in those categories.
Even though the spotlight is on the startups that build new big-data technologies, ultimately the real beneficiaries of big-data will be large companies that will fully leverage those new technologies, along with the customers they serve.
What do you think of his list? Can you amplify any of his points?
A problem of big-data projects is that they are of complex nature and require reasonable technical and human resources and oversight if they are to be executed effectively. Also the problem is that most companies lack experience in big data projects therefore there are many unforeseen setbacks. The solutions are to plan well or hire consultants who are experts in the field. I am commenting very vaguely and generally. Ofcourse there are many things to look at and also, some companies might think that big-data projects are easily manageable and of simple nature.
Reading between the lines is a good point - IT and anyone with tech in their responsiblity scope are sometimes approached with a light-switch mentality. In other words, decisions and information are shared as if the team can be started or stopped instantaneously. That can be a costly decision-making process if management does not apply good time management techniques. Managing technical resources is critical to project success and ensuring that poorly performing projects have a minimal cost to resources.
" IT professionals have seen it time and time again. It may be a while before any signs of burn out are revealed"
It may even be difficult for people like us to get aware of the burn-outs as many corporates wont disclose their failure to us i.e. if they realize that their big-data projects are a failure. What the executives will reveal to the press is that big data concept is new to the information industry and there is lot to be learnt. You just have to read between the lines and figure that it is an announcement of failure or criticism on the people responsible in their organizations.
It is true that big data, if taken as an industry to evaluate, has not gone beyond the immature or experimental phase. In case of many companies, it is just now that they are beginning to even think that they need data analysts in their HR pool for the task as specialists and the all-rounder financial analysts are too less-knowledgeable for handling the big quantum data in an effective manner.
To be honest I didn't see anything in the list that I was not aware of but I guess I understand big data issues a little better than the "average person", that aside as with any new area of study it will take time for theory to become reality but it is IMO a certainty because we as a society are moving towards ever more data not less.
So whether businesses want to or not - big data is an issue they must confront eventually.
Over-hyped doesn't mean Big Data won't change how we work and live. Most everything that makes a difference goes through stages of over-optimism, followed by over-pessimism before settling into reality.
For Big Data, the expected timeline is shorter than most of the other technologies that are at the same stage of the hype cycle - Big Data is projected to be mainstream in just 2 to 5 years:
Alexis, it's a strong possibility that the big data may be hyped passed the actionability busineses can take. IT professionals have seen it time and time again. It may be a while before any signs of burn out are revealed. I think a determining factor is the amount of actionable results that are announced related to big data. To me it is in the same boat at Facebook commerce - it will come but not without some trial and error before a strategy an be widely used.
The gap between excitement and reality will change as more companies discover economic value from their big data effort. Until then, the hype will outstrip the reality, though I don't think anything will be solely flights of fancy.
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