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Top Three Emerging Big Data Trends: A Q&A with Hannah Smalltree of Treasure Data

Originally published December 19, 2013

This BeyeNETWORK article features Ron Powell’s interview with Hannah Smalltree, director of marketing for Treasure Data. Hannah and Ron talk about time to value, the ability to take action on what your big data analytics reveal, and the cloud.
Hannah, can you tell us a little bit about yourself?

Hannah Smalltree: I’ve been working in the technology space for quite a while. When I was editorial director of SearchDataManagement, I remember when the big data term was introduced and how much confusion there was around it. Over the past few years, we’ve really seen that evolve as customers try things. Sometimes they fail. Sometimes they succeed. I’ve heard a lot of stories in my role as an editor interviewing companies about their implementations and how they’re going. Now as marketing director for Treasure Data, we talk with our customers a lot about how they’re doing with their implementations. We come to them at various stages in the game. I think I can offer a perspective that sort of spans the last couple of years as we’ve sorted through this big data trend.

Great. How do you evaluate the market right now?

Hannah Smalltree: Well, it’s from talking with customers and people who use this technology. We talk with analysts like yourself and other experts in the market, and I think that’s important because the good ones are also getting perspective from their customers or subscribers. I think it’s all about what we’re hearing from the market directly—where the successes are and where the failures are. So it’s more about listening very carefully to what’s going on and what’s succeeding and what’s not. Sometimes it can be a little more difficult to figure out what’s not succeeding because people don’t like to talk about it. Today I hope to share more about what I’ve learned, especially as I’ve interviewed the customers of Treasure Data.

Customers really drive the market because they give you what needs are important.

Hannah Smalltree: Yes, it’s really all about the customer, and it’s really all about getting value from your projects. I’m really interested in helping people succeed regardless of what technology they choose.

What kinds of trends you are seeing as the big data journey continues?

Hannah Smalltree: I’ll summarize three trends, and then maybe we can talk a little more about them. The first one that we’re hearing, especially as big data evolves, is that time to value is critical. We’ll talk a little bit more about that, but there were some early big data projects that took a really long time to get off the ground. And, some of them really didn’t show a big impact. That’s a problem, both internally and externally.

The second trend is that the value of big data really seems to be more about its immediate use—not necessarily instantaneous, but being able to take action on what you’re finding from your big data analytics is extremely important.

The third trend we’re seeing is that the cloud is becoming more and more involved in these big data implementations, sometimes successfully and sometimes not successfully. More and more often, we’re finding that the cloud and big data, as I like to say, are two great tastes that go together, especially when you’re talking about big data.

Let’s zero in and start with the first trend—time to value. What does that mean in this context?

Hannah Smalltree: Time to value is a big one. When big data first became all the rage and everyone was talking about it, the immediate technology that came to mind was Hadoop. A lot of people were really interested in using Hadoop to solve big data problems. That makes sense because Hadoop is really well-suited for dealing with some of these new kinds of data—the multi-structured data forms that we’re dealing with. But here’s the issue. Hadoop is a newer technology for a lot of people. It’s a collection of open source technologies. It’s not just one piece of software that you can hit “install” and use from there. So it can take a while to hire Hadoop people. Once you have a Hadoop expert on board, it can take months to even get your Hadoop implementation up and running. So now you might be six months in and you have shown no value, which in enterprise technology projects can really be the kiss of death. Organizations need to be able to deliver quick wins and deliver immediate value.

At Treasure Data—and you can go to our Treasure-Data.com website and learn more—we have several customers that did build their own Hadoop clusters. Some of them took months to build it as I have described. Some of them actually used it for almost a year. And then decided it really took a long time to maintain it, and they weren’t able to get the value from it that they had hoped. In one case, they wanted to do more real-time updates; and Hadoop is a much more batch-oriented system. So the bottom line here is that the time to value with projects is critical. Most companies can’t afford to take months and months to implement Hadoop. If you’re going to show value with big data, you need to do it quickly and often, which is always the mantra—this quick wins idea. Every three months are you showing value to your organization and continuing that trend as you learn more about the data and the value it can bring to your organization?

You stated that big data’s value is in its immediate use. Do you mean real time?

Hannah Smalltree: In some cases I mean real time. In other cases, I just mean being able to take action on it. This is not necessarily specific to big data. This is about all analytics. If you’re analytics or BI team can put together a great tool and come up with these great insights, is your organization actually equipped to take action on the results—to make adjustments to your product or service as a result of what they’re seeing in the analytics? I think that’s an important thing to consider up front in your project. As you’re looking at different pilot projects and different things that you could do, what part of your organization is best equipped to take action on it? You don’t want to spin off a project that is really insightful and provides a lot of data for a department that is notoriously bad at changing their processes and taking action on the results of analytics. Instead you need an internal group that’s really good at taking new insights and turning those around and making changes based on what they’re finding. It's important to develop this ability to take action on it, to be able to use data relatively quickly—sometimes it is in real time even within minutes of it being created.

A recent study from Enterprise Management Associates found that about 70% of big data projects were focusing on operational analytics or operational processing and that speed of use is becoming increasingly important in these big data processes and projects. I think that this idea of being able to use things quickly, take action on it—whether it’s in real time or whether it’s within minutes, hours or days. It can’t take months to get some insight and then turn it around. The wave will have passed you by. You have to be able to act on it quickly.

The third trend—the cloud—is also evolving. How does that factor into big data projects?

Hannah Smalltree: The cloud makes sense for big data because of your ability to scale. Big data is, by definition, big. The other big thing with big data is the velocity. That can be really difficult to deal with in enterprise systems. I’ve heard a lot of people say that incoming speed of clickstream data, sensor data or machine data can be very difficult for enterprise systems to handle. Especially because that data often lives in the cloud already, it makes sense to keep it in the cloud and land it in a cloud environment. The cloud also offers the ability to scale very quickly and has some other benefits of being able to handle different types of data and be very flexible.

Now, that said, certain cloud platforms are difficult to use and require some specific skills—some cloud IT skills. Not all organizations have those. So in that case, you want the benefits of the cloud, but then you realize that there’s often a skills gap to actually implement on the cloud. And that’s where managed services like Treasure Data can be really helpful. We basically have a team of people for whom data management is their business. It is our core competency to manage data in the cloud. It might not be a retailer’s core competency. So they’re coming to us and saying, “Can you help us get up and running quickly?” And we’re saying, “Yes.” Often within 14 days or less, we can have our customers up and running in the cloud so they can focus on analysis, on getting insights that they can turn around and use—not on how they are going to manage the incoming flow of data and the storage. When you need to worry about that, it definitely adds a layer of complexity to your big data projects. Overall, I’d say the cloud often helps these big data projects. You really want to evaluate your internal skills and the type of cloud service that you are pursuing for these big data projects.

It would seem to me the managed service aspect takes all of the technology concerns and infrastructure needs away from the business so that a businessperson can just focus on the analytics and what they’re trying to solve.

Hannah Smalltree: Yes, and I call it the “fun” part. We actually have a great article on our website in the resources section of Treasure-Data.com. We call it “Get to the Fun Part Faster.” So instead of spending 80% of your time managing and figuring out how to deal with the data and 20% analyzing it, you can flip that on its head and spend 80% of the time analyzing it. You can really focus on getting value from data. With Treasure Data, within a few minutes of data being created, it’s ready for analysis without you having to do all those DBA tasks or write indexes or do all of those other things that you used to have to do in traditional on-premises environments. I really love it because it gives you the ability to start doing the interesting work and the analytics on the data. That’s exciting and it’s inspirational. It can give you more ideas, and you can keep that cycle going.

Getting to the fun part! That’s great. Thank you for sharing these major trends in big data today.

Hannah Smalltree: Thank you so much for talking with me, and I hope that we get to talk again. I would encourage people to continue the conversation with us at Treasure-Data.com or look me up on LinkedIn.

  • Ron PowellRon Powell
    Ron is an independent analyst, consultant and editorial expert with extensive knowledge and experience in business intelligence, big data, analytics and data warehousing. Currently president of Powell Interactive Media, which specializes in consulting and podcast services, he is also Executive Producer of The World Transformed Fast Forward series. In 2004, Ron founded the BeyeNETWORK, which was acquired by Tech Target in 2010.  Prior to the founding of the BeyeNETWORK, Ron was cofounder, publisher and editorial director of DM Review (now Information Management). He maintains an expert channel and blog on the BeyeNETWORK and may be contacted by email at rpowell@powellinteractivemedia.com. 

    More articles and Ron's blog can be found in his BeyeNETWORK expert channel.

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