>> Announcer: theCUBE presents On The Ground. (light techno music) >> Hello, everyone. Welcome to a special, exclusive On the Ground CUBE coverage at Oracle Headquarters. I'm John Furrier, the cohost of theCUBE, and we're here with Joey Echeverria, Platform Technical Lead at Rocana here, talking about big data, cloud. Welcome to this On The Ground. >> Thanks for having me. >> So you guys are a digital native company. What's it like to be a digital native company these days, and what does that mean? >> Yeah, basically if you look across the industry, regardless of if you're in retail or manufacturing, your biggest competitors are the companies that have native digital advantages. What we mean by that is these are companies that you think of as tech companies, right? Amazon's competitive advantage in the retail space is that their entire business is instrumented, everything they do is collected. They collect logs and metrics for everything. They don't view IT as a separate organization, they view it as core to their business. And really what we do at Rocana is build tools to help companies that aren't digital native compete in that landscape, get a leg up, get the same kind of operational insight into their data and their customers, that they don't otherwise have. >> So that's an interesting comment about how IT is fundamental in their business model. In the traditional enterprise, the non-digital if you will, IT's a department. >> Joey: Exactly. >> So big data brings a connection to IT that gives them essentially a new lift, if you will, a new persona inside the company. Talk about that dynamic. >> Yeah, big data really gives you the technical foundation to build the tools and apps on top of those platforms that can compete with these digitally native companies. No longer do you need to go out and hire PhDs from Stanford or Berkeley. You can work with the same technology that they've built, that the open source community has built, and build on top of that, leverage the scalability, leverage the flexibility, and bring all of your data together so that you can start to answer the questions that you need to in order to drive the business forward. >> So do you think IT is more important with big data and some of the cloud technologies or less important? >> I think it starts to dissolve as a stand-alone department but it becomes ingrained in everything that a company does. Your IT department shouldn't just be fixing fax machines or printers, they should really be driving the way that you do your business and think about your business, what data you collect, how you interact with customers. Capturing all of those signals and turning that signal into noise-- Or sorry, filtering out the noise, turning the signal into action so that you can reach your customers and drive the business going forward. >> So IT becomes part of the fabric of the business model, so it's IT everywhere? >> Joey: Exactly, exactly. >> So what are you seeing out there that's disruptive right now, from your standpoint? You guys have a lot of customers that are on the front end of this big wave of data, cloud, and emerging technology. We're seeing certainly great innovations, machine learning, AI, cognitive, Ya know, soon Ford's going to have cars in five years, Uber's going to have self-driving cars in Pittsburgh by this year. I mean, this is a pretty interesting time. What are some of the cool things that you see happening around this dynamic of big-data-meets-IT? >> Yeah, I think one of the biggest things that we see in general is that folks want turnkey solutions. They don't want to have to think about all of the plumbing, they don't want to go out and buy a bunch of servers, rack them themselves, and figure out what's the right bill of materials. They want turnkey, whether that's cloud or physical appliances. And so that's one of the reasons why we work so well with Oracle on their Big Data Appliance. We can turn our application, which helps customers transform their business into being digital native, into a turnkey solution. They don't have to deal with all of the plumbing. They just know that they get a reliable platform that scales the way that they need to, and they're able to deploy these technologies much more rapidly. And we do the same thing with our cloud partners. >> So I got to the tough question. You guys are a start-up, certainly growing really fast, you got a lot of great technical people, but why not just do it yourself? Why partner with Oracle? >> Oh, that's a great question. I mean, Oracle has great reach in the marketplace, they're trusted. We don't want to solve every problem. We really want to partner with other companies, leverage their strengths, they can leverage our strengths and at the end of the day, what we end up building together is a much stronger solution than we could build ourselves. One of the main reasons why we in particular are not, say, a SAS company where we're just hosting everything in the cloud, is we need to go to where the data is and for a lot of these non-digital native companies, that data is still on-prem in their data centers. That being said, we're ready for the transition to the cloud. We have customers running our software in the cloud. We run everything in the cloud internally because, obviously as a small start-up, we don't want to go out and spend a lot of money on physical hardware. So we're really ready for both of those. >> Is this a big trend that you're seeing? 'Cause this is consistent with, some people say, the API economy. People can actually sling APIs together, build connectors, build a core product, but using API as a comprehensive solution is a mix between core and then outsourced, or partnering. Is that a trend that's beyond Rocana? >> Oh, definitely. One of the reasons why we build on top of open source software and open source standards is for that network effect. One of our core tenets is that we don't own the data. You own the data. So we store everything in file formats like Apache Parquet because it has the widest reach, the widest variety of tools that can access it. If there's a use case that you want to perform on our data that our application doesn't solve for you, fire up your Tableau, point it at the exact same data sets and go to town. The data is there for the customer, it's not there for us. >> What's the coolest thing that you're seeing right now in the marketplace, relative to disruption? You've got upcoming start-ups like you guys, Rocana, you got the big companies like Oracle, which are innovating now with opening up and not just being the proprietary database, using an open source. So what are some of the big things you're seeing right now between the dynamics of the big guys and the up-starts? >> Yeah, I think right now the biggest thing is turning data into the central cornerstone of everything that you're doing. No longer can you say, "I'm going to launch this project," without explaining what data are you going to collect, what are the metrics going to look like, how do we know if it's working, how do we know if it's not working. That sort of infusion of data everywhere, and even as you look across broader industry trends, things like IoT. IoT is really just the recognition that every device, every thing needs to have a connection to the network and a connection to the Internet and generate data. And then it's what you do with that data and tools that allow you to make sense of that data that are really going to drive you forward. >> IoT is a great example of your point about IT becoming the fabric because most IoT sensor stuff is not even connected to databases or IT. So now you're seeing this whole renaissance of IT getting into the edge of the network with all this IoT data. I mean, they have to be more diverse in their dealing with the data. >> Exactly, and that's why you need more native analytics. So one of the core parts of our platform is anomaly detection. Across all of your different devices in your data center, you're generating tons of data, tons of data. That data needs to be put into context. What may be a major shift is a problem with one data set isn't a problem with another. And so you have to have that historical context. That's one of the reasons why we also build on these big data platforms, is for things like security use cases. It takes, on average, nine months for you to actually detect that you've been breached. If you don't have the logs from nine months ago, you're not going to be able to find out how they got in, when they got in, so you really need that historical context to put the new data into the proper context and to be able to have the automated analytics that drive you and your analysis forward, rather than forcing you to sort of dumpster dive with just search and guess what's working. >> Dumpster diving into the data swamp, new buzzwords. Yeah, but this is really the big thing. The focus on real time seems to be the hot button, but you need data from a while back to mix in with the real time to get the right insight. Is that kind of the big trend? >> Oh yeah, absolutely. Whenever you talk about machine learning, you want the real time insights from it, but it's only as powerful as the historical data that you have to build those models. And so a big thing that we focus on how to make it easy to build those models, how to do it automatically, how to get away from having 500 different tuna bowls that the customer has to set, and really put it on autopilot. >> Well, making it easy, but also fast. It's got to get in low latency, that's another one. >> Oh absolutely. I mean, we leverage Kafka for just that reason. We're able to bring in millions of events per second into moderate size environments without breaking a sweat. >> Rocana, great stuff. Joey, great to chat with you again, here On The Ground at the Oracle Headquarters. I'm John Furrier, you're watching a special CUBE On The Ground here at Oracle Headquarters. Thanks for watching. (light techno music)