(upbeat music) >> Announcer: Live from Orlando, Florida, it's the Cube. Covering Pentaho World 2017 brought to you by Hitachi Vantara. >> Welcome back to the Cube's live coverage of Pentaho World brought to you of course by Hitachi Vantara. I am your host Rebecca Knight along with my co-host, Dave Vellante. We're joined by Anthony Deshazor. He is the Chief Solution's Architect and SVP of Customer Success at Pentaho. Thanks so much for coming on the Cube. >> Thank you for having me. Wonderful to be here. >> So before the cameras were rolling, we were talking a little bit about your career. You've been at this company for 12 years. >> Anthony: 12 years. >> And in different iterations of the company. >> Anthony: Right. >> Tell our viewers a little bit about how the company has evolved and also your role has evolved. >> One of the things that I really have watched Pentaho go through is the evolution to be more customer-centric. We began as a technology company. A bunch of geeks getting together. Had some neat tech, we could write some code and it was fun. We enjoyed it, but now as we start getting more customers we realized the technology had to serve the customer versus the customer serving the technology. That's wonderful transformation to go through to figure out how do you take that technology, bend it to the will of the customer and have that customer at the center of all your conversations. That was something that took us about six years to go through. Where we had all the geeks, kind of out of the room and put them in the back. I was one of the geeks so I got excused for some of those strategy conversations. But we got some good sales guys involved, some good marketing people who really brought that customer focus. Along the way we built better solutions 'cause we were listening more to our customers. It's interesting when you hear what people want to do you have a better chance of actually achieving it versus, let me build it and they will come. Other way, what do they need now let me build that. >> And really you said you were a geek, but you also really straddled the non-geek side too-- >> Anthony: Right. >> Because you can speak the other side. How do you do that, what is sort of the secret sauce to? >> I actually attribute that to some of my non-Pentaho, non-technical training. I'm actually a pastor of a church in Orlando, Florida. So I've done a lot of theological studies, a lot of homiletics that teach you how to stand on a stage and how to relate to people, even at a distance. And that actually comes through when you talk one on one with people. They feel like you're actually listening to them. And I actually attribute that all to that training. >> But the underline architecture still has to be malleable in order to accommodate-- >> Absolutely. >> That vision that you just put forth. It's kind of like that platforms versus products. >> Anthony: Yes. >> You built a platform not a product. And if you don't start with a vision of a platform you get a bunch of products. It don't necessarily tie together. Take us back to the early days. Was that part of the design thinking? >> Actually it was. Our five founders at Pentaho had that in their DNA. We had done three startups. I've been luckily enough or maybe stupid enough to do three of their startups. They had done three, I have done all three. But at the very core it was we needed to build something that was embeddable. That can work in process. Something that can be molded to the client's problem. We understood that whatever we built will never be enough. It would never be able to solve all of the problems. So if we put gates around it, it would reduce what we can do. So we wanted to build something that was extendable. Something that was a platform that if we didn't have the functionality you could easily build it. That's one of the reasons why went open source originally. Where all the code was open source. Anyone could extend it, anyone could bend it. Just because we understood there's no way for us, sitting in an ivory tower, to really figure out what's needed. >> And these decisions were made in the early to mid 2000's. >> Anthony: Yes. >> So they way predated Hadoop. >> Anthony: Yes. >> Then you had Hadoop saying okay, we're just going to bring compute to the data. And totally different data paradigm and platform approach. >> Anthony: Yes, yes. >> Was it that sort of philosophy that allowed you to adapt or did you have to do a heavy lift to adapt? >> Actually it wasn't a heavy lift. The legend has it, I wasn't in the conversation but our founding CEO had a conversation with one of our architects. I think they were having drinks or something at one of the local bars or pubs around Orlando, around the Orlando office. They begin to talk about Hadoop, pulled out a white napkin and just drew some things on the back of the napkin. A week later we had our first integration with Haddook. That's built upon that extendable, pluggable architecture that was there at the core. So that's really allowed up to adapt to new technologies to really catch the waves early and maybe sometimes anticipate the waves. >> So in this latest iteration of the company, Hitachi Vantara what can customers expect? >> The one way I can describe it is that it's maturity. You get the size of Hitachi Vantara behind you, you can do things that you could not do with a small company. As great as Pentaho was as a standalone company I believe we'll be that much bigger when you have the whole weight of Hitachi Anatara standing behind you. We had our strategic advisory board yesterday and one of the things I shared with those customers is that now you will see us attack things that we could not even fathom before. We have more developers so we can move features further, faster. We have more people in different regions so now we can do more services, help customers better in far regions like an Apac region for example. Where we struggled in the past as a standalone company. When you have a support center. A whole geography dedicated to Hitachi Vantara already there, it's now how do we instead of build the infrastructure just add that analytic DNA to the infrastructure that already exists. So that's what I think customers will experience very quickly. We can do more faster. We can do more in different locations. And we can even do more at a higher level of efficiency and quality if you would, because we have that backing of Hitachi Vantara. >> You were sharing this off camera. You do a lot of traveling, you talk to a lot of customers. >> Yes. >> You spend a lot of time in the aluminum tube. When you talk to customers and you compare it to now versus in the early days. The technology when you guys started was sort of mysterious and today the technology, there's plenty of it, it's abundant and it's pretty well understood. Sometimes it's hard to make work. But when you guys talk about digital transformation. >> Anthony: Sure. >> And disruption, be the disruptor, not the disruptee. A big thing that's changing is the processes within organizations. Those are largely unknown. It used to be very well known processes. Accounting or HR or whatever it was. Now the processes they're changing everyday. >> Yes. >> Do you have those conversations with customers and how are you as a company adapting and supporting that premise. >> One of the things I've noticed is that we have new roles introduced everyday. (laughter) All of a sudden, we had a data engineer. They used to be called DBA's, now they're data engineers. Now we have data scientists. Some companies I know they have data janitors and we have data prep. All these people now new roles in the organization all related to data. What we've been looking at is how do we make sure that every person, no matter their role understands how to use the data. My interest and my focus here at Pentaho is not just around architecture but also customer success. And we learned very quickly in the last two years as we've been on this customer success journey, you can install the best technology. It can be absolutely pristine from an architectural standpoint. You can get awards on architecture. But if you can't get the people to adapt, to adopt and use the software, use the solution you've basically just wasted your time. So what we've been focused on, how do we identify those new roles? How do we identify what skills do they need? How do we do training on the solution that was built so that no matter what their role is they understand how the solution can add value. How does the solution improve your job? Improve your life experience, maybe get things done faster. Maybe do more than you used to be able to do. But we've gotten out of the old tradition that there's a training department, accounting department. There used to be a time, I'm old enough to say this, where there was business analytics team but now every team has business analytics in it. It's part of someone's job to analyze the data. Even if that's not their primary function. So it's that, how do you make sure that no matter the role they have the skills and they access the data. >> How are you fostering collaboration between those roles? You always hear the stories of data scientists spend 80% of their trying to-- >> Anthony: Clean your data. >> Mess with the data, right. But you're right you've got the data engineer, the quality engineer, the application developer now-- >> Anthony: Yes. >> Data's now the new development kit. >> Anthony: It is. >> So how are you approaching the collaboration across those roles? >> So one of the things we've challenged our customers with is do you have a center of excellence? Doesn't have to be a dedicated center of excellence. It can be a concept or virtual team. But do you have a forum where people can collaborate? If you're doing analytics in a silo, if you're doing data integration in a silo and people are not talking to each other you're missing opportunities for efficiency, for innovation, even for understanding, wait if I do this that allows you to do this better. So how do you create that center of excellence? We have services now, professional services team are working with our customers to start that concept. Let's train one or two people. Make them the go to people for everyone else. >> Rebecca: Evangelists. >> Exactly, they become the evangelist. That helps us in two ways. One it helps us when it comes to getting people to use the technology in the right way. When you have a platform that means people have to use it correctly. You can build some amazing things with Pentaho, but you can also build some pretty, let's just say non-efficient things with the same platform. And then of course, me being the customer guy, they're going to blame the technology and I have to have that very delicate conversation, like not real good technology. It's the builder, it's what you built that's the problem. So we have some experts there that we can train and have them be the guardians, if you would. The custodians of the quality of the solutions. To make sure there's consistency and best practices. But the other side, we're also a renewable based company where we want to get the subscriptions, we want to get the renewals. So if I have evangelist there that can help the company use the solutions, adopt the solutions, that makes the renewal conversations that much easier. >> So I want to talk to you about measuring success. >> Anthony: Sure. >> Because one of the things that came out in the keynote today was Pentaho's underlying principles of social innovation and not just saving companies money or making them more money but also doing good in the world and bettering society. So how do you pitch that to customers? How do customers respond? How do you approach that idea? >> It's a hard one at times, because most companies are focused, I need to solve my problem. I don't care what we're doing about the rest of the world. I have this major pain point. This is what I need you to focus on. >> And fair enough. >> Absolutely, that's what they're paying the money for. That's where we start. We start there, can we get into start solving some problems together. And as the partnership develops, now what else can we do? So it's not just let me go sell this one solution. Let's partner for your good but for the good of the whole society. Are there things we can do that actually make not only your job easier, bring you money, but actually make things better. So some of the customers I love you heard IMS, you heard Dr. Alaina there Ella, excuse me today. I met with some of the other ones that are working with IMS, Dr. Ben. That story's actually close to my heart, 'cause who doesn't want to save money on their insurance but who also doesn't want better and safer cars? That's a social innovation story. Absolutely we're driving down the costs, we're helping companies manage their risks, understand their risks around insurance. But then we're also helping them get feedback on what makes cars better. What makes them safer? How can we avoid accidents? That is social innovation, that's what we're looking for. That's what Brian talked about with that double bottom line. How can we help you achieve your business goals but go beyond that to better society. >> We've heard a lot about transformations. Hitachi's own transformation, Pentaho, pre Hadoop, the Hadoop big data mime. You guys caught that wave. Now you're sort of entering, I don't know if it's your third wave or not. (laughter) Could be your fifth, tenth, I don't know. But there's another big wave coming. >> Anthony: Absolutely. >> Which is industrial IOT, Brian talked about IT and OT coming together. >> Anthony: Coming together. >> And it's early days but what are you seeing in the customer base. It was interesting, Brian very transparent, said how many Hitachi customers are out there? A few hands went up. >> Great, great. >> But not a ton. So as I say it is early days, but on paper the potential is enormous. >> Anthony: Great. >> It's a trillion dollar market, makes a lot of since, you see a lot of big industrial giants going after this and you've got some real assets you can bring to bear. >> Anthony: Right. >> What are the conversations like with customers and where do you see that all going? >> The way we approached customers and what I hear from customers, they don't really mention the word IOT. >> Dave: Okay. >> Most of them don't understand that they have an IOT problem. All they know is, I have this problem. So we're using IOT is to say, you have that outcome. You desire that outcome and to get that outcome you need to get data from all your devices. We have an IOT platform that can help you do that. So where the word even IOT comes up for us, is only in the solution not in the problem. Where I think some companies are missing the mark 'cause they're selling the technology. We have an IOT platform, please come buy our platform. Well, we've been a platform play forever with Pentaho and we understand that if you go there with a blank slate and say here, here's my platform come buy it, people don't understand it. They don't see the value. But if you can come and say, what's the problem you have? What's the outcome you're looking for? Let's focus on the outcome and back our way into the technology. And that's how we're approaching customers. That seems to be working so far. We have some IOT customers today that did not realize that they were doing IOT. >> The big product announcement today with Pentaho 8. What can we expect? >> Scale, that's the one word I would use for Pentaho 8. This is one of the best releases I think we've had. We have a new functionality called Work Nodes. We have customers who have been implementing something similar to this in the field for years. We've now productized it, it allows customers to scale out. We've heard from Brian and from others that to do this right you have to do it at scale. You have to provide this data, this analytics at scale. What our Worker Nodes allows customers to do is spin ups, spin down, distribute the workload on prim in the cloud. We don't really care, it's just we have a workload. You've given us a set of nodes we can work on we're just distribute the workload throughout that and when we're done we can spin them down. That elasticity, that flexibility as absolutely needed for today's data solutions. >> Great, Anthony thank you, you were a great guest. Thanks for coming on the Cube. >> Thank you for having me, thank you. >> I'm Rebecca Knight for Dave Vellante. We will have more from Pentaho World just after this. (upbeat music)

>> Announcer: Live, from Orlando, Florida, it's The Cube. Covering PentahoWorld 2017. Brought to you by, Hitachi Vantara. >> Welcome back to Orlando, everybody. This is PentahoWorld, #pworld17 and this is The Cube, The leader in live tech coverage. My name is Dave Vellante and I'm here with my co-host, Jim Kobielus Donna Prlich is here, she's the Chief Product Officer of Pentaho and a many-time Cube guest. Great to see you again. >> Thanks for coming on. >> No problem, happy to be here. >> So, I'm thrilled that you guys decided to re-initiate this event. You took a year off, but we were here in 2015 and learned a lot about Pentaho and especially about your customers and how they're applying this, sort of, end-to-end data pipeline platform that you guys have developed over a decade plus, but it was right after the acquisition by Hitachi. Let's start there, how has that gone? So they brought you in, kind of left you alone for awhile, but what's going on, bring us up to date. >> Yeah, so it's funny because it was 2015, it was PentahoWorld, second one, and we were like, wow, we're part of this new company, which is great, so for the first year we were really just driving against our core. Big-Data Integration, analytics business, and capturing a lot of that early big-data market. Then, probably in the last six months, with the initiation of Hitachi Ventara which really is less about Pentaho being merged into a company, and I think Brian covered it in a keynote, we're going to become a brand new entity, which Hitachi Vantara is now a new company, focused around software. So, obviously, they acquired us for all that big-data orchestration and analytics capability and so now, as part of that bigger organization, we're really at the center of that in terms of moving from edge to outcome, as Brian talked about, and how we focus on data, digital transformation and then achieving the outcome. So that's where we're at right now, which is exciting. So now we're part of this bigger portfolio of products that we have access to in some ways. >> Jim: And I should point out that Dave called you The CPO of Pentaho, but in fact you're the CPO of Hitachi Vantara, is that correct? >> No, so I am not. I am the CPO for the Pentaho product line, so it's a good point, though, because Pentaho brand, the product brand, stays the same. Because obviously we have 1,800 customers and a whole bunch of them are all around here. So I cover that product line for Hitachi Vantara. >> David: And there's a diverse set of products in the portfolios >> Yes. >> So I'm actually not sure if it makes sense to have a Chief Products officer for Hitachi Vantara, right? Maybe for different divisions it makes sense, right? But I've got to ask you, before the acquisition, how much were you guys thinking about IOT and Industrial IOT? It must have been on your mind, at about 2015 it certainly was a discussion point and GE was pushing all this stuff out there with the ads and things like that, but, how much was Pentaho thinking about it and how has that accelerated since the acquisition? >> At that time in my role, I had product marketing I think I had just taken Product Management and what we were seeing was all of these customers that were starting to leverage machine-generated data and were were thinking, well, this is IOT. And I remember going to a couple of our friendly analyst folks and they were like, yeah, that's IOT, so it was interesting, it was right before we were acquired. So, we'd always focus on these blueprints of we've got to find the repeatable patterns, whether it's Customer 360 in big data and we said, well they're is some kind of emerging pattern here of people leveraging sensor data to get a 360 of something. Whether it's a customer or a ship at sea. So, we started looking at that and going, we should start going after this opportunity and, in fact, some of the customers we've had for a long time, like IMS, who spoke today all around the connected cars. They were one of the early ones and then in the last year we've probably seen more than 100% growth in customers, purely from a Pentaho perspective, leveraging Machine-generated data with some other type of data for context to see the outcome. So, we were seeing it then, and then when we were acquired it was kind of like, oh this is cool now we're part of this bigger company that's going after IOT. So, absolutely, we were looking at it and starting to see those early use cases. >> Jim: A decade or more ago, Pentaho, at that time, became very much a pioneer in open-source analytics, you incorporated WECA, the open-source code base for machine-learning, data mining of sorts. Into the core of you're platform, today, here, at the conference you've announced Pentaho 8.0, which from what I can see is an interesting release because it brings stronger integration with the way the open-source analytic stack has evolved, there's some Spark Streaming integration, there's some Kafaka, some Hadoop and so forth. Can you give us a sense of what are the main points of 8.0, the differentiators for that release, and how it relates to where Pentaho has been and where you're going as a product group within Hiatachi Vantara. >> So, starting with where we've been and where we're going, as you said, Anthony DeShazor, Head of Customer Success, said today, 13 years, on Friday, that Pentaho started with a bunch of guys who were like, hey, we can figure out this BI thing and solve all the data problems and deliver the analytics in an open-source environment. So that's absolutely where we came form. Obviously over the years with big data emerging, we focused heavily on the big data integration and delivering the analytics. So, with 8.0, it's a perfect spot for us to be in because we look at IOT and the amount of data that's being generated and then need to address streaming data, data that's moving faster. This is a great way for us to pull in a lot of the capabilities needed to go after those types of opportunities and solve those types of challenges. The first one is really all about how can we connect better to streaming data. And as you mentioned, it's Spark Streaming, it's connecting to Kafka streams, it's connecting to the Knox gateway, all things that are about streaming data and then in the scale-up, scale-out kind of, how do we better maximize the processing resources, we announced in 7.1, I think we talked to you guys about it, the Adaptive Execution Layers, the idea that you could choose execution engine you want based on the processing you need. So you can choose the PDI engine, you can choose Spark. Hopefully over time we're going to see other engines emerge. So we made that easier, we added Horton Work Support to that and then this concept of, so that's to scale up, but then when you think about the scale-out, sometimes you want to be able to distribute the processing across your nodes and maybe you run out of capacity in a Pentaho server, you can add nodes now and then you can kind-of get rid of that capacity. So this concept of worker-nodes, and to your point earlier about the Hitachi Portfolio, we use some of the services in the foundry layer that Hitachi's been building as a platform. >> David: As a low balancer, right? >> As part of that, yes. So we could leverage what they had done which if you think about Hitachi, they're really good at storage, and a lot of things Pentaho doesn't have experience in, and infrastructure. So we said, well why are we trying to do this, why don't we see what these guys are doing and we leverage that as part of the Pentaho platform. So that's the first time we brought some of their technology into the mix with the Pentaho platform and I think we're going to see more of that and then, lastly, around the visual data prep, so how can we keep building on that experience to make data prep faster and easier. >> So can I ask you a really Columbo question on that sort-of load-balancing capabilities that you just described. >> That's a nice looking trench coat you're wearing. >> (laughter) gimme a little cigar. So, is that the equivalent of a resource negotiator? Do I think of that as sort of your own yarn? >> Donna: I knew you were going to ask me about that (laughter) >> Is that unfair to position it that way? >> It's a little bit different, conceptually, right, it's going to help you to better manage resources, but, if you think about Mesos and some of the capabilities that are out there that folks are using to do that, that's what we're leveraging, so it's really more about sometimes I just need more capacity for the Pentaho server, but I don't need it all the time. Not every customer is going to get to the scale that they need that so it's a really easy way to just keep bringing in as much capacity as you need and have it available. >> David: I see, so really efficient, sort of low-level kind of stuff. >> Yes. >> So, when you talk about distributed load execution, you're pushing more and more of the processing to the edge and, of course, Brian gave a great talk about edge to outcome. You and I were on a panel with Mark Hall and Ella Hilal about the, so called, "power of three" and you did a really good blog post on that the power of the IOT, and big data, and the third is either predictive analytics or machine learning, can you give us a quick sense for our viewers about what you mean by the power of three and how it relates to pushing more workloads to the edge and where Hitachi Vantara is going in terms of your roadmap in that direction for customers. >> Well, its interesting because one of the things we, maybe we have a recording of it, but kind of shrink down that conversation because it was a great conversation but we covered a lot of ground. Essentially that power of three is. We started with big data, so as we could capture more data we could store it, that gave us the ability to train and tune models much easier than we could before because it was always a challenge of, how do I have that much data to get my model more accurate. Then, over time everybody's become a data scientist with the emergence of R and it's kind of becoming a little bit easier for people to take advantage of those kinds of tools, so we saw more of that, and then you think about IOT, IOT is now generating even more data, so, as you said, you're not going to be able to process all of that, bring all that in and store it, it's not really efficient. So that's kind of creating this, we might need the machine learning there, at the edge. We definitely need it in that data store to keep it training and tuning those models, and so what it does is, though, is if you think about IMS, is they've captured all that data, they can use the predictive algorithms to do some of the associations between customer information and the censor data about driving habits, bring that together and so it's sort of this perfect storm of the amount of data that's coming in from IOT, the availability of the machine learning, and the data is really what's driving all of that, and I think that Mark Hall, on our panel, who's a really well-known data-mining expert was like, yeah, it all started because we had enough data to be able to do it. >> So I want to ask you, again, a product and maybe philosophy question. We've talked on the Cube a lot about the cornucopia of tooling that's out there and people who try to roll their own and. The big internet companies and the big banks, they get the resources to do it but they need companies like you. When we talk to your customers, they love the fact that there's an integrated data pipeline and you've made their lives simple. I think in 8.0 I saw spark, you're probably replacing MapReduce and making life simpler so you've curated a lot of these tools, but at the same time, you don't own you're own cloud, you're own database, et cetera. So, what's the philosophy of how you future-proof your platform when you know that there are new projects in Apache and new tooling coming out there. What's the secret sauce behind that? >> Well the first one is the open-source core because that just gave us the ability to have APIs, to extend, to build plugins, all of that in a community that does quite a bit of that, in fact, Kafka started with a customer that built a step, initially, we've now brought that into a product and created it as part of the platform but those are the things that in early market, a customer can do at first. We can see what emerges around that and then go. We will offer it to our customers as a step but we can also say, okay, now we're ready to productize this. So that's the first thing, and then I think the second one is really around when you see something like Spark emerge and we were all so focused on MapReduce and how are we going to make it easier and let's create tools to do that and we did that but then it was like MapReduce is going to go away, well there's still a lot of MapReduce out there, we know that. So we can see then, that MapReduce is going to be here and, I think the numbers are around 50/50, you probably know better than I do where Spark is versus MapReduce. I might be off but. >> Jim: If we had George Gilbert, he'd know. >> (laughs) Maybe ask George, yeah it's about 50/50. So you can't just abandon that, 'cause there's MapReduce out there, so it was, what are we going to do? Well, what we did in the Hadoop Distro days is we created a adaptive, big data layer that said, let's abstract a layer so that when we have to support a new distribution of Hadoop, we don't have to go back to the drawing board. So, it was the same thing with the execution engines. Okay, let's build this adaptive execution layer so that we're prepared to deal with other types of engines. I can build the transformation once, execute it anywhere, so that kind of philosophy of stepping back if you have that open platform, you can do those kinds of things, You can create those layers to remove all of that complexity because if you try to one-off and take on each one of those technologies, whether it's Spark or Flink or whatever's coming, as a product, and a product management organization, and a company, that's really difficult. So the community helps a ton on that, too. >> Donna, when you talk to customers about. You gave a great talk on the roadmap today to give a glimpse of where you guys are headed, your basic philosophy, your architecture, what are they pushing you for? Where are they trying to take you or where are you trying to take them? (laughs) >> (laughs) Hopefully, a little bit of both, right? I think it's being able to take advantage of the kinds of technologies, like you mentioned, that are emerging when they need them, but they also want us to make sure that all of that is really enterprise-ready, you're making it solid. Because we know from history and big data, a lot of those technologies are early, somebody has to get their knees skinned and all that with the first one. So they're really counting on us to really make it solid and quality and take care of all of those intricacies of delivering it in a non-open-source way where you're making it a real commercial product, so I think that's one thing. Then the second piece that we're seeing a lot more of as part of Hitachi we've moved up into the enterprise we also need to think a lot more about monitoring, administration, security, all of the things that go at the base of a pipeline. So, that scenario where they want us to focus. The great thing is, as part of Hitachi Vantara now, those aren't areas that we always had a lot of expertise in but Hitachi does 'cause those are kind of infrastructure-type technologies, so I think the push to do that is really strong and now we'll actually be able to do more of it because we've got that access to the portfolio. >> I don't know if this is a fair question for you, but I'm going to ask it anyway, because you just talked about some of the things Hitachi brings and that you can leverage and it's obvious that a lot of the things that Pentaho brings to Hitachi, the family but one of the things that's not talked about a lot is go-to-market, Hitachi data systems, traditionally don't have a lot of expertise at going to market with developers as the first step, where in your world you start. Has Pentaho been able to bring that cultural aspect to the new entity. >> For us, even though we have the open-source world, that's less of the developer and more of an architect or a CIO or somebody who's looking at that. >> David: Early adopter or. >> More and more it's the Chief Data Officer and that type of a persona. I think that, now that we are a entity, a brand new entity, that's a software-oriented company, we're absolutely going to play a way bigger role in that, because we brought software to market for 13 years. I think we've had early wins, we've had places where we're able to help. In an account, for instance, if you're in the data center, if that's where Hitachi is, if you start to get that partnership and we can start to draw the lines from, okay, who are the people that are now looking at, what's the big data strategy, what's the IOT strategy, where's the CDO. That's where we've had a much better opportunity to get to bigger sales in the enterprise in those global accounts, so I think we'll see more of that. Also there's the whole transformation of Hitachi as well, so I think there'll be a need to have much more of that software experience and also, Hitachi's hired two new executives, one on the sales side from SAP, and one who's now my boss, Brad Surak from GE Digital, so I think there's a lot of good, strong leadership around the software side and, obviously, all of the expertise that the folks at Pentaho have. >> That's interesting, that Chief Data Officer role is emerging as a target for you, we were at an event on Tuesday in Boston, there were about 200 Chief Data Officers there and I think about 25% had a Robotic Process Automation Initiative going on, they didn't ask about IOT just this little piece of IOT and then, Jim, Data Scientists and that whole world is now your world, okay great. Donna Prlich, thanks very much for coming to the Cube. Always a pleasure to see you. >> Donna: Yeah, thank you. >> Okay, Dave Velonte for Jim Kobielus. Keep it right there everybody, this is the Cube. We're live from PentahoWorld 2017 hashtag P-World 17. Brought to you by Hitachi Vantara, we'll be right back. (upbeat techno)