Expert Interview (Pt 1): John Myers on Big Data and Machine Learning for the C-Suite
At this year’s Strata Data Conference in New York City, Syncsort’s Paige Roberts sat down with John Myers (@johnlmyers44) of Enterprise Management Associates (EMA) to discuss what he sees in the evolving Big Data landscape. In this first part, Myers points out a shift away from technology and toward business value, even at the Big Data technology shows like Strata, and some of the advantages of moving to in-memory processing for machine learning.
Paige Roberts: So, tell me, what are you looking forward to seeing at the show?
John Myers: You know, it’s very interesting to me to see how Big Data is evolving. I think a lot of the organizations are getting away from kind of the technical descriptions of Big Data or Hadoop, etcetera. And we’re now talking about what do you do with the data?
It’s no longer about the technical environment. It’s about what are the business outcomes. And I think that it’s always great to see that next step of how people are embracing the changes in what’s going on. Because I think that strictly as a technology, it goes down below the CXO Suite. Like, they go, “Okay, great. You guys have a Big Data environment?”
Knock yourself out. Yeah.
Exactly. But when you talk about, this is how we can improve customer experience. This is how we can manage our business better. That really brings things up a notch and that gets you into the CXO Suite. It gets the attention of whether it’s… your newly minted Chief Data Officer, your COO, your CEO – you’re now impacting topline revenues, bottom line costs, and the margin, increasing the margin. So, I think that’s an important part of how that all works.
It does seem like the messaging is up-leveling. But it also seems like the attendees are different now. It used to be a lot more hoodies. And now there’s more suits.
Right. I was just about to say. I usually call this the suit to hoodie ratio. I think here in New York, naturally, we’re going to have more suits versus hoodies.
I think Strata in Northern California, you get more hoodies than suits. But we’re starting to see some changes in that.
The overall proportion is shifting over time.
Exactly! So, I agree with the messaging. We’re seeing great improvements in the technology, the ability to use Spark to be able to do things faster, to do things in a speed of business context, as well as from those origins. I think we’re really getting some good advances.
So as far as the tech goes, what are you seeing that’s exciting? What’s the most thrilling tech change that you’ve seen?
I like the concept of Spark and in general in-memory processing. Not necessarily for the “I can do it now” but for the concept that if I have a latency that I can use, I can now cycle through not just one iteration but multiple iterations. And I can present to you not an answer, but the best of three to five answers.
And why they’re different.
Exactly. In-memory gives you those opportunities to be responsive, and if you have the time, to go through and say we ran this against five different models. This gave us the greatest uplift. Would you like to use this one?
Duh! [Laughter] No, let me use the terrible one. [Laughter]
But I think a lot of times when people think of in-memory or real-time processing, they think of automated trading. They think about telecommunications or financial services fraud. They don’t necessarily think about how can we inform our customer care guys while the call is being connected, or while we’re talking to them on the phone. We’re giving them the best possible scenario not just a scenario, if that makes sense.
As John Myers points out above, Big Data is shifting from IT to the business, read our eBook The New Rules for Your Data Landscape to discover how this new data supply chain impacts how data is moved, manipulated, and cleansed.
Tomorrow, in part 2, John talks about “Playing Money Ball with Machine Learning in Business,” with tips on how to deal with cultural pushback against machine learning applications, and how to get machines and people working together to take advantage of the strengths of each.