Big Data: Get ahead or get behind

Big Data. It is an industry that has been around for more than seven decades, or, since the dawn of the in-home computer. More recently, it has become a mega-booming, $100B market that is expected to grow 10 percent larger each year.

That boom has led to a cocktail of industry growing pains. According to the McKinsey Global Institute, nearly two million job vacancies for data analysis and information management will be announced next year. Meanwhile, black box marketing tactics have c-suite and engineering executives at war over the notion of and the vocabulary around what it means to get on the cloud and leverage big data or large amounts of data in real time — or near-real time — or, what others describe as, up-to-real-time.

In our first-ever podcast, Trench Media, met up with three of the leaders who are on-the-ground delivering data solutions to learn why big data has suddenly become a $100B market and what challenges are ahead.

This podcast and all future podcasts at Trench serve to navigate the grey areas in technology. As listeners, you are welcome and encouraged to share your thoughts, opinions, and feedback with featured domain experts at


JENNA BUEHLER, TRENCH MEDIA: Meet Eric Little who says he operates outside traditional norms or titles when it comes to data science. In fact, he said his daughter is really the best at describing to people what it is that he does for a living.

ERIC LITTLE, CEO of OSTHUS: She described me as a doctor who if you talk to me I won’t make you feel better, I’ll probably make you feel worse, because I’ll like to argue with you and tell you why you’re wrong.

JB: Eric says he never took a single computer science class and adds that companies don’t care about yesterday’s degrees. They’re too concerned with whatever it is that has the market advantage and getting ahead in big data while they still can.

EL: In the past, I’ve worked with companies in insurance like Blue Cross Blue Shield. I’ve worked with companies like BP. I spent a lot of time in the defense industry,

Normally, across all these industries, what I see is that people have a lot of legacy data. That people a lot of legacy data systems and they’ve been very reliable up until now.

But they’ve invested so much money in those systems, you can’t expect huge companies to throw away hundreds of millions to billions of dollars in investment and start all over. No one is going to do that.

JB: The key here, according to Eric, is for companies to recognize that now is the time to start fostering a culture of innovation in everything that they do.

EL: Because you’re talking companies that are very old, OK. I mean people who have invented Aspirin and Ibuprofen people who have invented Q-tips or diapers or talcum powder. Anytime you have to change a corporate culture especially in a very large, very old company — that’s not an easy task.

JB: The result, according to Eric, is a paradigm shift.

EL: It’s not just about our product and selling our things. We have to get a handle around what it is that we’re doing internally and that can be a bitter pill to swallow for some people …

But I can tell you that, of the companies who are willing to augment their culture, they see big benefits out of it but it’s a struggle.

JB: Other big data advisors like Karen Gregory, start with culture and expectations as a first step to implementing data solutions. As an aside, Karen serves as a member of congressman Bill Posey’s veteran advisory council and wears many hats when it comes to navigating politics and solutions.

KAREN GREGORY, CEO of HRSS: Humans really are mini-computers. We are dynamic computers in it of themselves.

JB: Karen says she works with c-suite and engineering teams to look critically at what strategies will most effectively get them to a desired goal.

KG: There’s nothing worse than going into an organization and they say I think and I feel. How do we drive decision-making in a kind of proven and scientific manner? As a scientist, that’s important to us and as an organization that’s how we’re approaching our organizational development services.

Big data is here to stay. To me, it should be driving decision-making the challenges ahead are just collecting too much and not knowing what to do with it. At least, that’s what we’ve seen.

JB: While Karen works with companies to get proactive about what data-driven decisions and implement cultural strategies may amplify their findings, other data scientists are hired to react to immediate-now needs. CEO of DFHeinz, Daryl Heinz, says a majority of his time is spent wading through the muck of misinformation.

DARYL HEINZ, CEO of DFHeinz: Literally we spent 5 days removing misconceptions of their c-level people that trickled down to the people who actually worked with data.

They told me ‘oh no, Hadoop’s a silver bullet it’s fast and we’re going to replace everything…

Oh, they have so much pain ahead of them. But that’s OK.

JB: Heinz consults with Fortune 500 leaders in social media, tech, automotive, and medicine to build out custom-designed data architecture. He says for 20 years, corporate leaders have been cutting licensing and storage costs out of their margins by hiring teams like his to support in building open source date architecture using component design.

Daryl has even tasked himself with the charge to train as many people for free as he possibly can…he calls this initiative “Data Scientists Without a Degree”.

DH: If they would just learn about the tools and learn how to listen to assemble these tools to make a solution, their careers are golden for the next 10 years — easily.

JB: Daryl will announce trainings in Orlando and Miami in 2018 in an effort to build an army of people who can help him to further evangelize and demystify common misconceptions — like this one that I had about the level of risk companies are up against when they use open source solutions…..

DH: When I walk into organizations, that’s their first concern.

[Scenario] On a Sunday you’ve got a bug that brings production down. Who are you going to call? So, what is happening in the industry is that there is something called professional open source.

JB: More than debunking the security of open source, Daryl’s team is also helping people to better understand why it is data that is so valuable.

DH: As they accrue this data for years and years and years they also want to know whether you are who they believe you are. So, for example, an insurance company will know whether you’re a risk. A credit card company will know whether you’re a fraud.

So, the uses of big data are very far reaching. As a matter of fact a lot of my friends refer to big data as big brother and, in a sense, it really is — if it’s used incorrectly.

JB: Our Trench data analysts conclude that industry leaders across all verticals must take steps toward fostering a culture of innovation when it comes to data analysis right or risk getting left behind in the dust. In the next Trench Podcast we’ll explore what works and doesn’t work when companies start the process of introducing that culture to their employees. Until next time, I’m Jenna Buehler. For more stories direct from the tech industry trenches visit

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