Thought Leaders in Big Data: Interview with Steve Shine, CEO of Actian (Part 3)

Sramana Mitra: So your core differentiation is to be able to handle very large volume data at very low latencies and power the business analytics layer on top?

Steve Shine: We enable the business analytics like the BI tools, the analytic frameworks, or analytics applications. We do this all the way, connecting from the original data sources all the way through to offering it up and enabling those analytics capabilities.

SM: What are industry segments where you are winning? What kinds of use cases are taking particular advantage of your capabilities?

SS: Sometimes people think that big data is only for the Fortune 1000. That is absolutely not the case. I can’t share customer names, but let me walk you through the business to know. I mentioned one of them to you just now. There are several really large investment banks on Wall Street that use our ParAccel MPP technology to run their risk platforms. That is a really good example. Financial services is a data-rich world and very low latency.

Let me give you another low latency example. There is an enormous e-commerce web-based company that has a huge real estate of web pages that you and I frequent on a very regular basis. Therefore, a very large amount of their income is associated with advertising. In that scenario, the latency of what you want to do is incredibly important, but the scale now is pushing the boundaries of technology.

So, what happens? Most people think it is just about serving the relevant ad to people when they are on the web page. It is far more sophisticated than that today. As you or I click around a particular web page, especially if we are browsing from a purchasing perspective, there are rich analytical algorithms out there that can effectively recognize signatures, patterns, and the way you are clicking and searching changes as you get close to the point where you make a purchase. This is an incredibly important thing to recognize. Rather than just “Steve Shine is on this web page, let’s serve up ads,” they are saying, “Steve is on this web page, we have his cookie history for the last three months and we know that his pattern of clicks on our web page is changing and it is starting to match the pattern that we recognize as somebody who is getting close to making a purchase.”

At that point they turn to their advertising customers. They want to be able to say, “We recognize this. We are going to tell you that now is the time if you want to put a specialized offer to him, because he is close to buying mode.” This organization has a 80 terabyte in-memory version of our MPP technology. So they are essentially tracking everybody’s cookie history and also matching that up against real-time clicks. If they miss that window, if they don’t catch the change in click patterns, the moment that moment has passed, and it is worthless – the data is out of date. That is where people are getting very sophisticated, and you need to look at a lot of data to be able to see and analyze that trend and build a model that says, “His or her pattern on the web is changing, now is the time to offer your best promotional items.”

Let me go to the gaming industry. It is truly fascinating. Most of the really fast-growing gaming companies are not even in the Fortune 5000. They are relatively small and are in what you and I would call small or medium business. But their growth rate is phenomenal. Those companies are so data rich. Understanding that data is fundamentally the difference between success and failure. That may sound a little bit nonsensical for the gaming company. It is all about the quality of the game. Essentially that is true, but getting the best quality in that game is not just about the artistic design, it is also about being able to say, “When everybody is online, and I have hundreds of thousands of people online and I am able to track every click and move they make on their consoles and can trace that, why are so many people stopping at this point in the game? Why are we not getting to that next stage?” That amount of analysis enables them to be able to recognize that there are design issues in the game.

That thinking is the first sign of these changes. To me, this is fascinating. That is really using big data to scientifically help you with the design of your core, which you and I would think of as purely artistic.

This segment is part 3 in the series : Thought Leaders in Big Data: Interview with Steve Shine, CEO of Actian
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