 And from San Jose in the heart of Silicon Valley, it's theCUBE covering Big Data SV 2016. Hey, welcome back everybody. Jeff Frick here with theCUBE. We are live in San Jose, California for Big Data Week, which is Big Data SV here at the Fairmont at the Gold Room as well as Strata Hadoop across the street at the convention center. And we're excited to be here. It's our third year of Big Data SV. And again, we got to this events. We get the smartest people we can find. We bring them on theCUBE and we ask them questions that you would like to ask and really get the insight. So we're really excited to be joining this next segment. It's live. Let me turn my computer sound off by Marcy Campbell, SVP of Sales and Business Development for CUBO. Welcome. Thank you. Thank you for having me. So first off, CUBO, CUBALL. Yeah. Is there a story behind the name? It's a... I think it was a domain that was available. But it was, it's CUBALL, but nobody can say her name. All right. But we're getting better at that. So for the people that aren't familiar with the company, give them kind of the quick overview. Sure. We're Big Data as a Service. So we're a SaaS platform that allows enterprises and other customers that have massive amounts of data to process it, process structured and unstructured data on the cloud. And we offer an orchestration layer that sits on top of Amazon, Microsoft and Google. And we don't resell those services. Our customers have those services in place. And then does your service sit inside those public clouds as well or just connects to those clouds? It connects to those clouds. So the customers own their own S3 or EC2 or Google or Microsoft components. And they're already running those. And so we have an orchestration layer that allows you to build a layer on top of it that allows you to get access to that data. Excellent. And you've been at it for how long has the company been around? We're about five years old. Five years old. About 100 people. And you got terrific customer references on the website so you guys are up and running. We do. Yeah. We're really excited about the customers that we have. So I gather you guys grew something like 600% last year? Yeah, we had an amazing year last year. It was Marcy's run and sale. Obviously. Yeah, no, I think what was interesting for us was I've been with a company almost two years. And when I first joined in June of 2014, our customer base that we had was really those customers that were born in the cloud. So companies like Pinterest and Quora, and we just acquired Datalogics as a customer, which is now Oracle. And those companies really were building their products on data and using data as a differentiation in the market. So they were a natural fit for us. What we've seen since then, and especially in the last half of last year, is that we're seeing larger enterprise brand names that you know about like Autodesk. Those kinds of companies that are actually building their own data platforms have decided that they should move over to the cloud. And they've been looking at our products seriously. So Marcy, what changed in the last year in terms of two years from born in the cloud to traditional enterprises that they became more mainstream customers of yours? Yeah, I think there's been a couple of shifts in the market. The first one was, well, when I first joined the company, we were out talking about the value of big data and the value of the cloud. And it became really apparent to me that we didn't really need to talk about either those were trends that were going to happen and that people were going to move to the cloud and they were going to move big data to the cloud. And I think that Amazon, Microsoft, and Google have done a really good job of making the public cloud safe. And enterprises are starting to feel comfortable about putting their data in the cloud. And so as that shift has happened, people are looking at what's the value of being able to process structured and unstructured data and to get that data into their customers' hands. So a company like MediaMath, who is a born in the cloud company, is taking our product and building our product into a product that they're developing for their customers to allow their customers access to their own data. We're seeing other companies start to transform their environments by allowing and sharing data throughout the organization. Were you guys on-prem before you operated with all the cloud system? No, we were actually born in the cloud. Born in the cloud. What's interesting is the founders of the company, Joy Deeps and Sarma and Ashish Tussou, they came from Facebook. And they built the Facebook platform. And one of the premises of building that platform was they had about 300 users that were getting access to this data at the time. And what they were able to do is build a platform that gave people access to massive amounts of data. By the time that they left, they had about 4,000 people using that product. And that is the precepts for what we're doing. It's like we want to give data to the end users so that they can make better business decisions. And the cloud allows you to do that because it separates storage and compute. And so it would be massively expensive if you actually just took a distribution and put it on top of a cloud because it would have to run 24 by 7. But because we have a pay-as-you-go model, people can then just roll up compute when they need it and roll up storage when they need it. So let's say you're going to no longer just a born-in-the-cloud company, your prospect, say an Autodesk or some other, say, a Telco or something like that. And they know that they don't necessarily have all the skills to build a huge infrastructure on their own. But they're also being pitched by, say, an Amazon or an Azure about doing a data platform in the cloud. How do you explain to them the differences in your approach? Yeah, I think the main difference is we're a service. So when you look at Amazon and their products, they're actually a series of tools that you stitch together and allows you the Amazon EMR product. It'll take you two or three weeks to get that up and running. That's the main difference for us. And also the administrative cost. So the difference for us is we can support 21 users with one administrator because of our user interface, whereas with the other products that are out there, they're one-on-one. So we just have an economies of scale. What we do see, however, is we have two types of customers. I have a customer who has tried to do something on-prem and is not happy with it for whatever reason. So it's either not scaling or they don't have Hadoop resources or Spark resources. It's too expensive. So that's one area. I also have other customers. These new applications are getting built. So we're seeing large enterprise builds, really interesting IoT applications and machine learning applications and devices. So Under Armour is one of our customers using the fitness device. And those are pretty interesting because they transform those companies. And I think the big difference with us and some of the other providers that are on the cloud already is the fact that we are really a self-service model. So what we can do is provide an interface for a data scientist or a data analyst where they can do an ad hoc query without having to have an IT organization build out that infrastructure. So let me take you back to the two types of customers you were talking about. One is the IoT. I'm going to use data as a product. And then the first one was I'm trying to build a data infrastructure, but it's proving more difficult than I expected. Are you seeing companies who've put two years into a POC and pilot? And they don't really want to admit failure because that's not good when they're reporting to the CIO or CFO. Are they looking more to the cloud now and saying, well, that's our future pass and we're just going to keep some stable workloads on prem? Yeah, I think we are in an experimental mode in some cases. It just depends on the type of industry. There get some industries that are all in. And some industries that have been calling us that I wouldn't expect like finance, right? That would be the last place that I would send my sales folks to go, but we're having those conversations. But what we do see is that people are experimenting on anywhere the cloud is being adopted, right? I don't have to sell the cloud. The cloud's being adopted in marketing. It's being adopted in retail and customer information and customer tracking. And those are the kinds of applications that we're seeing people start to implement with our solution, even if they have some on-prem data. When you talk about this, it sounds like you're looking at sort of a departmental focus. Do you go into an organization where they have sort of pilots that have different departments have done on the cloud? Or have they attempted to do a central sort of Hadoop as a service, and that's not working? Yeah, I think it's a ladder. I think what's interesting for us is, you know, when I look at our sales model, I really do talk to the VP of engineering, right? Is the VP of product marketing or product management or the VP of data engineering? Those are the people that actually have the money and make those decisions. They're building these big data platforms. We had an interesting POC. Our POCs are two weeks long, right? Which is a big differentiator. So our sales cycle. Two weeks long. Yeah, so we can get someone up and running. We have one customer, it was a large casino customer in Las Vegas that basically had a query that ran four days and they tested with us and it was 23 minutes, right? So all of the value of the cloud of being able to, you know, the ability to scale, but also being able to process at that speed is a big differentiator for us. So do I also talk to the VP of data analytics and the VP of data science? Absolutely, right? Those are guys that, they look at our product and they say, I want that. But the real value, I think, of what we're doing is twofold. It's in the data or in the data engineering group because it saves them resources. And if you look at what those guys are trying to do, the VP of engineering is really trying to deliver products out there, right? And services to his customer. And we help do that. Is it that they're building data products or is it just that he needs this infrastructure to build whatever products? Right, so do I want to track manufacturing, right? Am I going to track customer responses to certain products that we're putting out there? Is it, do I have to look at inventory and supplies? And we're starting to see pharma look at this and say, how do we build better products for pharmaceuticals and track inventory across their networks. And are these data analytic functions as part of, are they part of IT or are they part of these line of business functions? I talk to line of business about the value of what we're offering, but usually we start with IT. Yeah, because most of, you know, what I've seen in the last year is most everybody is trying to build a data platform, right? As a differentiator for their company. They're looking at how do I extend the reach of the data that's actually in my organization and then how do I connect to other organizations to create more value? But the data platform piece is such a big, you know, ocean to boil potentially, right? So I would assume a lot of them in your sales people on a two week POC are looking for the low hanging fruit. They're looking for, get them started on the journey. Look for workloads. So we look for workloads, right? But the conversation has started to shift because we're starting to work with some big SIs who are shifting that conversation into, you know, liberating data, right? What's the value of data associated with, you know, as a successful asset for a company? And so yeah, you know, do we sell to IT and we sell features and functionality? Absolutely. And I believe that if we, I can engage with a customer who is already on the cloud that I have the best product out there to win in that environment. Would an SI be looking at, in terms of their value at starting at the infrastructure layer or do they really wanna sell, you know, the value of data and analytics and you help get them there faster? We do both. We have smaller SIs that we work with that are looking at like, okay, I have a project that I've got to build and get out to market. You know, we're working with a large media company that's looking at putting programmatic assets onto set top boxes, right? And that's with an SI. On the other side, we're just starting to have conversations with the bigger SIs because we're a small little company and we need to show our value, you know, in the marketplace. Right, right. So what is kind of the land and expand then for your component when you're at one of these companies? They do a two week POC, you know, kind of what's the result? What are the KPIs? What are they looking to measure and then what is the next steps? Because, you know, a lot of people are curious about the journey. How do I get started? And it's a big thing. I know I got to be there. Right. You know, where do I start? How do I make sure I don't get locked in so that I can't expand? You know, what are some best practices you can share or, you know, kind of your insights from the field? Yeah, I think what we're looking for is, you know, we're looking for people who have their data in the cloud, right, or have access to that data in the cloud to test, right? And so what we wanna do is put together a proof of concept that allows them to test us against performance that they may see on-prem and also look at, you know, how quickly can they process? So we have, we had one proof of concept where we took an on-prem environment that had 500 nodes, right, and we pointed it, we used our QBIL platform to test on that and we were able to run that up in minutes, right? So, I mean, what we do is we look at performance, we look at the amount of data. One of the reasons Pinterest is a great customer of ours is because of the scale, right? And so, you know, as a company, we're running 300 petabytes or 327 petabytes this month, right? So it's a massive amount of data and I think the secret sauce is in, you know, what we've built in that platform and the ability for us to build a MetaCache that scales. I was gonna say, it's funny that you, statement that you're working with somebody in Vegas and, you know, we had Ryan Peterson on earlier talking about the Caesar's bankruptcy, but then after it was over, they figured out their data was worth a billion dollars. Had they known that their data was worth a billion dollars, maybe they wouldn't have filed for bankruptcy, but really this concept of, it's a tremendous asset. It used to be kind of a nuisance, right? If you had too much of it, now it's this tremendous asset, but how do you pull the value out? How do you extract the value? How do you make it actionable? Exactly, and then how do you allow people who normally don't have access to that data to get access to that data and do ad hoc queries that would normally take you weeks to get structured with an IT organization, right? So, I mean, that's one of the things that we provide to the market. One last question from me. When you talked about the companies that are sort of IoT related, where you've got data originating sort of at the edge or in the cloud, what does an engagement with them look like and how can you sort of accelerate the path to value from where data is a compliment to whatever they're trying to sell? See if I can answer that correctly. So, what we see is we usually, and this goes back to the proof of concepts, what we usually do is we test a number of workloads that are easy accessible, and then what we do is we look at taking those workloads or those pipelines over into the cloud. So, I'm not sure I may answer your question. Would it be that they started by doing it, by collecting all their data on-prem themselves, and then it's now so much faster and easier? So, we work with a number of companies that'll bring that data into, let's say, an S3 bucket, right, some sort of object store, right? So, our platform works on a private cloud, public cloud, excuse me. We have public private clouds, but we also look for companies, or work with companies, that have data in an object store, right? So, it's a cheap source of data. It allows you to separate storage from compute, right? And so, getting that data over into that area is something that we either work with an SI or we work with a company to get that into an object store. Just, I'd love your perspective on how cloud, combined with big data, has really opened up these opportunities, and that's before we talk about edge computing, and IOT, and pushing stuff out, but it's really this confluence of things that have enabled this, where before we used to kind of put big data in one bucket and cloud was kind of in another bucket, but the two together seem to be the things that are really driving the adoption, and the fun, and experimentation, and... Yeah, I think analytics and big data is the killer app for the cloud, right? I think that when I looked at coming to this company, I had spent five years in the cloud, right? Had worked with Amazon previously. I knew how big they were, right? I knew their adoption rates. I had worked with Microsoft, worked a little bit with Google, and I was a true believer in the public cloud, and the big data space was new to me, but when I looked at it from an application standpoint, it made a lot of sense because it drives large workloads into the cloud, and when I got there, because we were such a small company, what I didn't want to do was go sell cloud, and I also didn't want to sell big data because there were other big companies that raised a lot of money who were doing that, but what we did was we went right in the middle and said, okay, this is the convergence of those two things, and I think it resonates with our customers, with our partners, and with enterprises now. I believe that that, personally, I believe that the cloud's going to take over everything. I'm a little bit of an iconoclast there because I think that all data belongs on the cloud. What's interesting to you, because that discussion's already finished by the time, it's an opportunity for you, and clearly, you're part of three very big cloud companies. Obviously, Amazon is way out front and it's done phenomenal things, and Google just had their cloud event last week, or it's the last week, two weeks, I can't keep track of it, and then Microsoft already has a huge installed base, right? And Satya's clearly done a great job of turning the corner. So, kind of running low on time, as you look forward, what are you excited about for the next six months, nine months? What do you see some kind of new opportunities or exciting customers or some crazy transformative things that you've seen in the marketplace? You know, I think that we're, our largest, fastest growing part of our business is Spark, right? So, what we're seeing is more and more adoption of Spark, and people like the fact that we have a Spark, a Hive, a Presto, and a Pig Engine right from the same interface. And so, we've been winning a lot of customers there, so that's pretty exciting for us. All right, well, maybe we'll see you at Spark Summit West. Next time, okay. Nice lead-in for the plug. The queue will be at Spark Summit West. We were at Spark Summit East a couple of months ago already. Time flies in New York City, so we look forward to returning back to Spark. I'm Jeff Frick, Marcy Claver, thanks for stopping by. Thank you. Absolutely, you're watching theCUBE with George Gilbert. We're live in San Jose, California at Big Data SV, concurrent with Big Data Week and Strata Hadoop. This is the center of the Big Data Universe, and it involves a lot of cloud too, so we'll be back with our next segment after this short break. Thanks for watching.