 Line from Orlando, Florida, extracting a signal from the noise. It's theCUBE covering Pentaho World 2015. Now your host, Dave Vellante and George Gilbert. We're back in Orlando, Florida. This is day two of Pentaho World, the second Pentaho World, and this is theCUBE, SiliconANGLE Wikibon's flagship program. We go out to the events. We extract the signal from the noise. Quentin Gallivan is here as the CEO of Pentaho. Quentin, great keynote yesterday. You must be excited. High energy. Thanks for coming on theCUBE. I am. It's outstanding. Thank you for having us. You guys do a great job here. Thank you. I love the fact that you're in the middle of it. You're in the buzz. We love being in the buzz. Yeah. Feel the energy. You know, it was so interesting here in the keynotes yesterday. You guys have a lot of substance. You've been around for 11 years. About the same amount of time as Hadoop has been around. Right. So you weren't too early, and you weren't, you know, too new. So you've had time to harden your platform, and I think it really showed in the keynotes yesterday. I wonder if you could talk about some of the shifts that you see in the marketplace, some of the things you talked about yesterday in your keynotes, and how Pentaho has really capitalized on that. Right, right. What's really interesting is our second user's conference, customer conference. And very much the focus has been on around big data analytics, the Hadoop ecosystem, and really what's happening. And last year, you know, we focused a lot on the technology. And what's the technology around the Hadoop ecosystem? What do the pieces fit? What do the reference architectures look like? And then this year, because we had such a strong adoption, we really focused on the business use cases around Hadoop. And we're really starting to see companies take advantage of the technology where there's a return on investment initiative that's going to drive a revenue advantage, a cost advantage, or an operating advantage for customers. So the shift we've seen, really the kind of macro view is the maturation of the Hadoop market. So that's the theme of Pentaho World is putting big data to work. So as you saw in the keynotes, you know, a lot of discussions around internet of things, how are companies deploying it? How are they making money at it? 360 view of the customer, you know, big data analytics, how are companies getting intelligence about their customer in order to get closer to the customer to drive higher conversion rates on target offers and revenues. So what I like about the theme is really the maturation. It's really all about the business advantages, which is very different than a year ago. Well, the business value is critical. I mean, we've been studying this for years now, and a lot of companies, you know, some companies on the edge, obviously the Googles and the LinkedIn's and the big web guys that get in value from big data, but there's the fat middle that's struggling. What I heard yesterday from the customers that we interviewed is they're getting massive value, and the reason is you've actually put together an end-to-end pipeline. They're not having to spend 70, 80% of their time figuring out how to make all this stuff work. That's a critical competitive advantage for you, and it's unique in the industry. I wonder if you could talk about that. Yeah, I think one of the big, sort of unlocking the value of big data is that companies, there was a focus before around primarily just what data can we put in Hadoop, unstructured data in Hadoop, and that's an important component is being able to analyze this unstructured data. But what we've seen from the line of business trying to drive these 360 view of the customer initiatives or Internet of Things or fraud control and compliance is the need to blend that unstructured data with structured data or relational data data you already have in your systems about your customer, about the transactions, about all the ERP kind of activities. The key in unlocking is blending the unstructured data, which is really what are the behavior patterns, what are people doing on Clickstream, what are they doing around IoT devices, but blending that with the relational data, that's unlocking the insight. And so what Pentalo does that end-to-end platform, it automates the process, it takes friction out of the process, and essentially allows companies to unlock the value of big data. George, and I know you want to jump in, I want it to follow up on the whole IoT piece as it relates to strategy. I know Richard had a go, so I'll ask you the strategy question. Chris said yesterday, strategy should not waiver, should be consistent. Now that's not always the case, sometimes companies have to do massive pivots and change strategy. When you started the company, Pentalo started, there was no IoT, people were talking about IoT, and now it's like this huge tailwind for you, the Hitachi acquisition, and we'll talk about that, but so the strategy wasn't IoT. The strategy was around data, so I wonder if you could sort of summarize that strategy, because it's positioned you very well for some of the changes in the marketplace. Right, it's a great insight. When we started out really, we had two themes in the company, and we have been around for 11 years, that we've tried to be consistent to those themes. One theme is that we truly believe commercial open source is a way to innovate faster. So that was one theme we had from the very beginning. The other theme we had is that for companies to get real insights, you have to marry the ability to integrate data from all different sources, blend that data, and then easily put that into an analytical tool. So that's been our theme for 11 years. What's changed is big data. So big data has made those themes more profound. It's made those themes more relevant in the sense that the traditional data sources are still important, but now this unstructured data becomes very, very critical. And so for us it was easier to point the company with our themes at the bigger opportunity. Now as it relates to big data, so what we've been doing is really putting together an analytical platform that takes unstructured data, structured data, puts it into an analytical model, individualized it, that end-to-end pipeline. And so with big data we've been trying to find is what are the business use cases? And so IoT has just become another business use case that's getting a lot of attention, it's getting a lot of traction, and it's getting all this attention because you've got traditional, old-line, industrial companies that weren't really associated with technology innovation. They were associated with manufacturing innovation, supply chain management innovation, but now they're on the forefront of taking advantage of IoT as a way to transform these industrial businesses. For us it just happened to be right place, right time that we've been focusing on business use cases and IoT now becomes a very popular business use case. Lucky timing sounds easy, but a lot of execution behind it. Go ahead George. So I'm listening to two things that are related. One, it sounds like when you can unlock value across data silos and make it easy, you can capture a lot of the value that customers are unlocking and the rise of big data in a separate repository was a key part of that. Other than internet of things data coming from many different sources, how are you positioned to take advantage of that? I mean it comes in from so many more sources, it's continuously coming in. How do you work with that? Yeah, so there's a couple of key trends emerging around IoT, because IoT is a whole different game in terms of instead of a, you know, usual business communications is even about a person communicating to a person or a person communicating to a business. Now you've got people and things and people and systems connecting. Or things and things. And things and things connecting. And so from our perspective we're seeing a couple of key technology trends happening. One is the emergence of the cloud as a deployment model for big data, particularly around IoT. And you ask yourself, why is the cloud emerging as a deployment model? Or the reason you mentioned is that when you're doing internet of things you're basically capturing machine data from devices, from sensors. It could be 10,000 sensors, it could be millions of sensors on a global basis, sitting in a customer premise, sitting in a home, sitting in a retail shop. By the very nature, because of the distributed environment where the things are generating data, it makes sense to put that infrastructure in a cloud, a cloud environment. And so the cloud thing is an important piece. And the other important piece around the internet of things is the ability to capture data coming in very, very fast, coming in short bursts from devices and quickly move that into an analytical platform so that the analysis can basically capture the data and then review the health of that device. That's the main event around IoT is what's the health of that device and things like predictive maintenance are use cases where companies want to get ahead of the device failing in a customer's environment or on a factory floor is they want to see based on the health of that device with the machine data is telling them do something about it, do be preemptive, take that device out, remediate that device. That predictive maintenance piece is one of the key use cases we see around IoT. So my understanding then listening to you is you actually now have sort of pivoted like from the iPod to the iPhone into yet another super sweet spot that's actually bigger in the sense that as you say the internet of things sort of machine data is coming in continuously and very fast and so you need an end to end pipeline that doesn't get stuck handing off to different tools. That's one thing. And then you're also to some extent hiding the information processing layer in the form right now of a Hadoop ecosystem that does all these handoffs whereas you can sort of manage it at a higher layer. So in other words shorter pipeline, faster pipeline is that sort of a core of your advantage with the internet of things? Yes, because you are seeing what's happening with the internet of things is that it's moving away from a batch process of moving data to more real time, to more streaming of information continuously coming in. And so with Pentaho, we do have an advantage around the scalability of our infrastructure, the innovations that we're working on today and working on tomorrow to really go from that batch data movement to a more streaming data environment because that's going to be very critical and then also to your point is really take the complexity out of the process and that's the value that we bring is we try to abstract the complexity from the eyes of the customer and handle that end to end process in an automated fashion. So I want to bring in the Hitachi piece. We're talking about internet of things, obviously there's a clear Hitachi synergy there. One day we saw Dell announce an acquisition the largest acquisition in our industry's history of EMC, a company that HDS has been competing with for years. Interesting to note HDS, Hitachi going into finding ways to leverage internet of things acquiring a software company like Pentaho and you're seeing sort of these hardware companies consolidate. I wonder if you can talk about two things. One is what do you make of that? And two talk about the synergy with Hitachi and the IOT play I want to dig into that a little bit. One of the things that was compelling for me as the CEO of Pentaho to be acquired by Hitachi, what was my strategic rationale and really the strategic rationale for us was we saw a very big opportunity in just doing what we were doing. It was a 40 billion dollar opportunity, big data analytics and we started to see IOT this emerging use case and we have many IOT customers that aren't Hitachi customers. We'll continue to build more. But we're kind of on the outside looking in of the IOT tent. And what we saw the opportunity with Hitachi is really to expand our ambition expand the aperture and be inside the tent in terms where IOT is going. And what we liked about Hitachi's point of view is that if you think about Hitachi, you know it's an 80 billion dollar plus company and a lot of industrial businesses but it's also a very large I.T. company. And so we thought that being part of one of very large I.T. companies is also a very large industrial company. You're going to have domain expertise bringing IOT together and we wanted to be in the middle of all that. So that was part of the strategic rationale from my perspective. So that makes sense I want to talk about the go to market. So when you're a small company you struggle, you try to build up a distribution channel, you hire salespeople, I mean it's hard you know. And you might have a slight advantage against the competition. And then you get bought by a big company and distribution changes. So can you talk about the go to market and how Hitachi will bring the Pentaho innovations to its marketplace. Right, right, right. So that was another strategic rationale for me is that if you look at the market opportunity Pentaho was targeting it's a big market opportunity and a lot of that market opportunity is large enterprises deploying big data solutions and buying the technology. For a small company like Pentaho we had to really work scratch and claw to get into those large enterprises. The synergy value of Hitachi data systems is they have a very large sales organization, they have a large customer base, existing contracts, really strong relationships. For me it was really a way to catapult into getting our solutions and getting part of these projects leveraging the large Pentaho go to market capabilities. So that's sort of synergy value one. So synergy value two is that Hitachi has a lot of software IP around technology around data management. One of the things that were very intriguing to us is that predictive analytics is becoming a very important part of all these big data analytics use cases, not just IOT. At Pentaho we have a predictive analytics capability and we have some data scientists. Hitachi's R&D has 500 data scientists and they're looking for problems to solve. So I looked at those 500 data scientists and all the Hitachi IP and said that's something that can be super helpful for us going forward. So tell us, Dave asked about sort of go to market. Let me ask about sort of go to market V2. Which is when you start leveraging some of their internal IP the data scientists and data scientists sort of this generation's professional services. How does some, how do some of Hitachi's businesses change and how does Hitachi sell to other industrial companies when they're sort of offering analytic data capabilities along with an industrial product. Right. So a couple ways that Hitachi's approaching the opportunity and I'll talk about where we fit into that opportunity. So even if you look around here at the convention center in the expo booth, Hitachi data systems has built big data analytical applications. Pentaho is more of an infrastructure end to end company but someone needs to build applications on top of that, our technology. So if you go around the expo here Hitachi data systems have built big data analytics for the telco industry in terms of network traffic analysis. They've built big data analytics capabilities for IT in terms of machine analytics. They've built big data analytics capabilities for smart cities. And so the Hitachi data systems already built a handful of really powerful big data analytics applications on Pentaho on top of Pentaho. So we're going to continue to be a partner there but we also work with a lot of other companies that are building big data analytical applications. 40% of our business comes from partners, many of those in the rooms many of those that you saw in the keynotes that build applications big data analytical applications on top of the Pentaho platform. Just to be clear 40% is it 40% of your partners build apps or 40% of your revenue comes from apps built by partners? Ladder. Wow. The ladder. That means you're one serious platform. So then a follow on to that is how do you think about capabilities that might belong in the platform but that application developers put in now that you know you have to trade do you step on them or do you broaden the platform? It's a great question so it gets back to the earlier one you had about so who are we? What are our themes? So our basic theme at Pentaho is commercial open source end to end analytical platform and be very extensible and be very about plugins. So our heritage has always been about having other companies, partners, customers build on top of the platform and because of our commercial open source roots they're very much an extensible API oriented platform. You can build plugins and that's been our community, the open source community that's been where they've really spent a lot of time is building applications, building visualizations building front ends, building back ends on the Pentaho platform. We're going to keep that heritage and that DNA so we allow companies like Hitachi to build applications on our platform and then you know the rest of the marketplace. So we've talked a lot about some of the exciting things IoT and let's close on sort of summarizing some of those things that excite you. You talked about telematics in your keynote you talked about O-Power talked about 5 billion devices 5 billion people, 50 billion things connected. We talked about cloud. Summarize Quentin some of the things that are exciting you you're head of a technology company what are some of the technology enablers that you see that are really exciting you guys? Right, so a couple things one is and again it's only been a year since we're seeing these dramatic changes and these shifts. It's amazing. But a couple things around big data that we think are really interesting both technology and then shifts. So one is we do think use cases like IoT are here, they're real, it's very transformative. We do think big data is getting cloudy right and not just around IoT but now you had FINRA on here and so look what they're doing in terms of that's very serious credible big data stuff I mean they're basically monitoring the capital markets in the United States looking for fraud as a regulator looking for insider trading 75 billion events or trades every day they have to capture and quickly analyze and looking for bad behavior that's serious stuff and they're doing that in the cloud they're doing that big data in the cloud so we think IoT, big data in the cloud and then there's all the cool stuff or the innovation that's going on in the big data space all these commercial all these open source activities like spark in terms of new trends that's a pretty exciting Apache project and you've got very fast processing in memory large data sets that could be part of a platform things like Kafka which is real time streaming message cues so there's all these components that make sense in terms of taking big data to the next stage what we're trying to do is that we want to be the heat shield for our customers around these components I mean we take these new technologies in we embed it in the platform then we harden it the exciting thing about these new technologies in open source is the innovation is dizzying the challenge is that it's fairly immature and fairly command line kind of technology so our job is to take those components in make our products faster more real time more scalable more performant and harden those and I think that allows a company like Pentaho whether pre Hitachi or post Hitachi to innovate dramatically fast because we are an open source company we take advantage of those technologies well you've made the open source angle work it's very hard it's obviously red hat huge success but a lot of companies struggling to do it why do you think Pentaho was able to be so successful with an open source strategy well we've been at it for 11 years so I think like anything else in business time and experience it allows you to it allows us to really shift our focus from yes we want to be an open source company but also where's the business value for the customers and so we've been very focused on keeping pace with innovation but where do we add value from a business and that's why we've really focused on these use cases that I talked about around big data I think the more that we can not only bring the technology but bring skills and expertise or cookbooks or blueprints around if a company wants to do IOT we've got a reference architecture for you if you want to do of your customer we have a reference architecture do you want to manage fraud from a big data standpoint we have a reference architecture for you so I think it's just a combination of technology plus business process skills and expertise well it's been an amazing journey so far sounds like a lot of exciting things ahead the timing has just been amazing to watch and you know I've seen a lot of exits in this business you guys aren't a lightweight tool or lightweight tool an acquirer has to then harden you guys have done a lot of hard work in doing that road map we're going to have some other guest on later today to talk about that and drill into that so Quentin congratulations on all the success and we'll be watching going forward thank you for all your support thank you for coming here and you sort of capture the energy of the moment here it's really been our pleasure so thank you keep right there everybody we'll be back live from Pentaho World in Orlando we'll be right back