 Live from Orlando, Florida. It's theCUBE, covering Pentaho World 2017. Brought to you by Hitachi Ventara. Welcome back to theCUBE's live coverage of Pentaho World, brought to you by Hitachi Ventara. We are wrapping up day one. I'm your host, Rebecca Knight, along with my co-host today, James Kobielus and Dave Vellante. Guys, day one is done. What have we learned? What's been the most exciting thing that you've seen at this conference? What's most exciting is that, clearly Hitachi Ventara, which of course Pentaho is a centerpiece of, is very much building on their strong background and legacy and open analytics and pushing towards open analytics and the internet of things, their portfolio, the whole edge to outcome theme with Brian Householder doing a sensational keynote this morning, laying out their strategic directions. Now Dave had a great conversation with him on theCUBE earlier, but I was very impressed with the fact that they've got a dynamic leader, a dynamic strategy, and just as important, Hitachi, the parent company, has clearly put together three product units that make sense. You've got strong data integration, you've got a strong industrial IoT focus, and you've got a really strong predictive and machine learning capability with Pentaho for the driving the entire pipeline towards the edge. Now that to me shows that they've got all the basic strategic components necessary to seize the future, further possibilities. Now they brought a lot of really good customers on, including our latest one from IMS, Hillel, to discuss exactly what they're doing in that area. So I was impressed with the amount of just solid substance of them seizing the opportunity. Well so, I go back two years ago when theCUBE first did Pentaho World 2015, and the story then was pretty strong. You had a company in Big Data, they seemingly were successful, they had a lot of good customer references, they achieved escape velocity and had a nice exit, under Quentin Gallivan who was the CEO at the time and the team, and they had a really, really good story, I thought, but I was like, okay, now what? We heard about conceptually we're going to bring the industrial internet and analytics together, and then it kind of got quiet for two years, and now you're starting to see the strategy take shape in typical Hitachi form. They tend not to just rush in to big changes and transformations like this, they've been around for a long time, very thoughtful company. I kind of look at Hitachi Limited in a way as an IBM-like company of Japan, even though they do industrial equipment, and IBM's obviously in a somewhat different business, but they're very thoughtful. And so I like the story, the problem I see is not enough people know about the story. Brian was very transparent this morning, how many people do business with Hitachi? Very few, and so I want to see the ecosystem grow. The ecosystem here is, it's Hitachi, a couple of big data players, I don't see any reason why they can't explode this event and the ecosystem around Hitachi Ventara to fulfill its vision, I think that's a key aspect of what they have to do. I want to see it. It's all to be the tipping point, just to get, as you said, I mean it's the brand awareness and every customer who we had on the show really said, when he said that, my eyes lit up and I thought, oh wow, we could actually be doing more stuff with Hitachi, there's more here. I want to see a developer focus, a stronger developer focus going forward. That focuses on AI and deep learning at the edge. I'm not hearing a lot of that here at Pentaho World of that right now, so that to me is a strategic gap right now in what they're offering. When everybody across the IT and data and so forth is going real deep on things like frameworks like TensorFlow and so forth for building ever more sophisticated data-driven algorithms with the full training pipeline and deployment and all that. I'm not hearing a lot of that from the Pentaho product group or from the Hitachi, the whole Hitachi Vantara group here at this event, so next year at this event I would like to hear more of what they're doing in that area. For them to really succeed, they're going to have to have a solid strategy to migrate up their open stack to include, like I said, a bit of TensorFlow or MXNet or some of the other deep learning toolkits that are becoming essentially de facto standards for the developers. Yeah, so I mean, I think the vision's right. Many of the pieces are in place and the pieces that aren't there, I'm actually not that worried about because Hitachi has the resources to go get them, either build them organically, which it's proven that can do over time or bring in acquisitions. Hitachi is a decent acquirer of companies. It's content platform came in on an acquisition. I've seen them do some other hardware acquisitions. Some have worked, some haven't, but there's a lot of interesting software plays out there. And I think there's some values, frankly. The big data, tons of money poured in to this open source world, hard to make money in open source, which means I think that companies like Hitachi could pick off to do some M&A and find some value. Personally, I think if the number's right, it was a half a billion dollars, I personally think that was pretty good value for Hitachi. You've seen all these multi-billion dollar acquisitions going left and right. And so the other thing is the fact that Hitachi under the leadership of Brian Householder and others was able to shift its model from 80% hardware, now it's 50-50 software and services. I'd like to dig into that a little bit. They're a public company, but you can't really peel the onion on the Hitachi Ventara side. So it kind of is what they say it is. I would imagine that's a lot of infrastructure software, kind of like EMC is a software company. But nonetheless, they're moving toward a subscription model. They're kind of committed to that. And I think that the other thing is a lot of customers, we come to a lot of shows and they struggle to get customers on with substantive stories. So we've heard virtually every customer we talk to today is like, here's how I'm using Pentaho. Here's how it's affecting. Not like super sexy stories yet, right? I mean, that's what the IoT and the Edge piece come in. But fundamental plumbing around big data, Pentaho seems like a pretty important piece of it. Fundamental plumbing that's really saving them a lot of money too and having a big ROI. They're fairly blue chip as a solution provider of a full core data portfolio. I think of them in many ways as sort of like SAP, not a flashy vendor, but very much a solid blue chip in their core markets. I'm just naming another vendor that I don't see with a strong AI focus yet. What I'm saying is Pentaho, nothing to sneeze at when you have one customer after another like we've had here, rolling out some significant work they've been doing with Pentaho for quite a while, not to sneeze at their delivering value, but they have to rise to the next level of value before long to avoid being left in the dust. I mean, you know, you got this data. Obviously they're going to be capturing more and more data with the devices and the relationship with Atachi proper, the elevator makers is still a little fuzzy to me. I'm trying to understand how that all shakes up. But my question for you Jim is, okay, so let's assume for a second they're going to have this infrastructure in place because they are industrial internet. And they've got the analytics platform. Maybe there's some holes that they can fill in. One being AI and some of the deep learning stuff. Can't they get that somewhere? I mean, there's so much action going on in the AI world. Can't they bring that in and learn how to apply it over time? Of course they can. First of all, they can acquire the, and tap their own internal expertise. I mean, they've got like Mark Hall, for example, on the panel. They've obviously got a deep bench of data scientists like him who can take it to that next level. That's important. I think another thing that Atachi of Intara needs to do to take it to the next level is they need a strong robotics portfolio. He's really talking about industrial internet, you know, internet of things. It's robotics with AI inside. I'd like to, I think they, they're definitely a company that could go there fairly quickly, a wide range of partners they can bring in or acquire. You get fairly significant in terms of, not just robotics in general, robotics for a broad range of use cases where the AI is not so much the supervised learning and stuff that involves training, but things like reinforcement learning. And there's a fair amount of like, smarts and academe on reinforcement learning for embodied cognition for robots that's out there in terms of, that's like the untapped space of the other of the broad AI portfolio, reinforcement learning. If somebody's going to innovate and differentiate themselves in terms of the enterprise, in terms of leveraging robotics in a variety of applications, it's going to be somebody with a really strong grounding in reinforcement learning and productizing that and baking that into an actual solution portfolio. I don't see yet the Googles and the IBMs and the Microsofts going there. And so if these guys want to stand out, that's one area they might explore. And I think, to pick up on that, I think this notion of robotics process automation, that market's going to explode. We were at a conference this week in Boston, you know, the data roti of Boston, the chief data officer conference at the Park Plaza. 20 to 25% of the audience, the CDOs in the audience had some kind of RPA, robotic process automation initiative going on, which I thought was astoundingly high. And so it would seem to me that Hitachi's going to be in a good position to capture all that data. The other thing that Brian stressed, which a lot of companies without a cloud will stress is that it's your data, you own the data. We're not trying to resell that data, monetize that data, repackage that data. I pushed him a little bit on, well, what about that data training models? And I, where do those models go? And he says, look, we are not in the business of taking models as a big consultancy and bringing it over to other, you know, competitors. Now, Hitachi does have consultancy, but it's sort of, you know, focused. So, you know, as Brian said in his keynote, you have to listen to what people say and then watch them to see how they act. How they respond. You know, and so that's, you have to make your own decision. But I do think that's going to be a very interesting field to watch because Hitachi's going to have so much data in their devices. Of course they're going to want to mine that data for things like predictive analytics. Those devices are going to be in factories, they're going to be in ecosystems, and there's going to be a battle for who owns the data. And it's going to be really interesting to see how that shakes out. So I want to ask you both, as you both have said, we had a lot of great customer stories here on theCUBE today. We had a woman who does autonomous vehicles. We had a gamer from Finland. We had a benefit science out of Massachusetts. Who are your favorite customer stories and what excited you most about their stories? I know you like the car, the car woman. Well, yeah, the car woman. Ella, Ella, hello, the PHD, yeah. That was really, I found many things fascinating. I was on a panel with Ella as well as she was on theCUBE. What I found interesting, I was expecting her to go to town on all things autonomous driving, self-driving vehicles and so forth. What she actually talked about was the augmentation of the driver passenger experience through analytics, dashboards in the sense that dashboards to help, not only drivers, but insurance companies and fleet managers to sort of do behavioral modification to help them modify their behavior to get the most out of their vehicular experience, like reducing wear and tear on tires and by taking better rows or advising and everything. I thought that's kind of interesting. Build more of the recommendation engine capability into the overall driving experience. That depends on infrastructure of predictive analytics and big data, but also metered data coming from the vehicle and so forth. I found that really interesting because they're doing work clearly in that area. That's an area that you don't need levels one through five of self-driving vehicles. To get that, you can get that at any level of that whole model. Just by bringing those analytics somehow into an organic way, hopefully safely, into your current driving experience, maybe through a heads-up display that's integrated into your GPS or whatever it might be, I found that interesting because that's something you could roll out universally and it could actually make a huge difference in, A, safety, B, people's sort of pleasure with the driving experience, far for a new one, that's the most big one. And then also, C, help people make the best use of their own vehicular assets in an area where people mostly own their own car. Well, for me, if there's gambling involved, I'm going to take it. You're there. It was the gaming, not only because of the gambling, and we didn't find out how to beat the house, Leonard, maybe next time, but it was confirmation of the three-tier data model from edge to gateway to cloud and that the cloud has two vectors, the on-prem and the off-prem cloud. And the fact that as a gaming company who designs their own slot machines, it's an edge device and they're basically instrumenting that edge device for real-time interactions. He said that most of the data will go back. I'm not sure. Maybe in that situation, it might. Maybe all the data will go back, like weather data. It all comes back. But generally speaking, I think there's going to be a lot of analog data at the edge that's going to be digitized maybe you don't have to save and persist. But anyway, confirmation of that three-tier data model, I think is important because I think that is how Brian talked about it. We all know the pendulum is swinging, swung away from mainframe to decentralize back to the centralized data center. Now it's swinging again to a much more distributed data architecture. So it was good to hear confirmation of that. And I think it's again, it's really early innings in terms of how that all shakes out. Great, and we'll know more tomorrow at day two, Pentaho day two. And I look forward to being up here again with both of you tomorrow. Great, likewise. Great. This has been theCUBE's live coverage of Pentaho World brought to you by Hitachi Ventera. I'm Rebecca Knight for Jim Kobielus and Dave Vellante. We'll see you back here tomorrow.