(techno music) >> (Narrator) Live from Washington, DC. It's Cube conversations with John Furrier. (techno music) >> Hello and welcome to the special exclusive Cube Conversations here in Washington, DC. I'm John Furrier host of the Cube. Here at Amazon Web Services Headquarter World Headquarters for Public Sector Summit in Arlington, Virginia. Our special guest is Tricia Davis-Muffett, who is the Director of Marketing for Worldwide Amazon Web Services. Thanks for joining me. >> Yep. >> So we see each other and reinvent Public Sector Summit, but you're always running around. You got so many things going on. >> I am. >> Big responsibility here. (Tricia laughs) >> You guys are running hard and you have great culture, Teresa's team. Competitive, like to have fun. Don't like to lose. (Tricia laughs) >> What's it like being a marketer for the fastest growing hottest product in Washington, DC and around the world? >> Yeah. I mean it's really been amazing. When I came here, I kind of took a leap of faith on the company because it's four and a half years ago that I came. I literally accepted the job before we had even gotten our first fed ramp approval. So it wasn't entirely sure that this was going be the place to go to for technology for the government, but I really loved the way that we were helping the government innovate and save money of course. I think most of us who are in Public Sector have a passion for citizens, and for making government better and so that's really what I saw in Teresa and her team that they had such a passion to do that and that the technology was going to help the government really improve the lives of citizens. It's been great. One of the things that's been amazing is the passion that our customers have for our technology. I think they get a little taste of it and they go "Wow, I can't believe what I can do "that I thought was impossible before." And so I love seeing what our customers do with the technology. >> It's something people would think might be easy to be a marketer for Amazon, but if you think about it, you have so much speed in your business. You have a cult of personality in the Cloud addiction, or Cloud value. In addition to the outcomes that are happening. >> Uh huh. >> We're a customer and one kind of knows that's pretty biased on it. We've seen the success ourselves, but you guys have a community. Everywhere you go, you're seeing Amazon as they take more territory down. Public Cloud originally, and now Enterprise, and Public Cloud, Public Sector Enterprise, Public Cloud. Each kind of wave of territory that Amazon goes in to Amazon Web Services, is a huge community. >> Yeah. >> And so that's another element. I mean Public Sector Summit last year it felt like Reinvent. So this years going to be bigger. >> Yeah. We had 65 hundred plus people attend last year, just in the Washington DC area and we've also expanded that program now and we are taking our Public Sector Summit specifically for government education non-profit around the world. So this year we will be in Brussels, and Camber, Australia. We have great adoption in Australia as well with the government there. In Singapore, Ottawa. So we're really expanding quite a bit and helping governments around the world to adopt. >> So if that's a challenge, how are you going to handle that because you guys have always been kind of with Summits. Do you coattail Summits? Do you go separate? >> No. We go separate. We actually have the Public Sector Summits we take the experience of our technology to government towns that wouldn't typically get a Summit. So for instance here in the United States of course, San Francisco and New York there's a lot of commercial businesses. We have our big Summits there, but there's not as much commercial business here in Washington DC, so really Public Sector takes the lead here. And then we focus on some of the things that really are most important to our Public Sector customers. Things like, procurement and acquisition. Things like the security and compliance that's so critical in the government sector. And then also, we do a really careful job of curating our customers, because we know that our government customers want to hear from each other. They want to hear from people who are blazing a trail within the Public Sector. They don't necessarily want to hear about what we want to say. They want to hear what their peers are doing with the technology. So last year, we had over a hundred of our Public Sector customers speaking to each other about what they were doing with the Cloud. >> And I find that's impressive. I actually commented on the Cube that week that it's interesting you let the customers do the talking. I mean, that's the best ultimate sign of success and traction. >> Yeah. And the great thing is, you know I've worked in other places in the Public Sector and government customers can be kind of shy about talking about what they're doing. You know, there are very motivated to just keep things going calmly, quietly, you know get their jobs done. But I think... >> Well, it doesn't hurt when you have the top guy at the CIA say, "Best decision we've ever made." "It's the most innovative thing we've ever done." I mean talk about being shy. >> Yeah. >> That's the CIA, by the way. That's the CIA. And we've also had, people like NASA JPL who've been very outspoken. Tom Soderstrom said that it was conservatively 1/100th of the cost of what it would have been if he had built out the infrastructure himself to build the infrastructure for his Mars landing. I mean that kind of... >> It just keeps giving. You lower prices. Okay I got to change gears, because a couple things that I've observed to every Reinvent, as being a customer and I think I've used Amazon I first came out as an entrepreneur. (inaudible) had no URL support, but that's showing my age. (Tricia laughs) But, here's the thing, you guys have enabled customers to solve problems that they couldn't solve in the past. >> (Tricia) Right. >> You mentioned NASA and then a variety of other (inaudible). But you guys are also in Public Sectors specifically are doing new things. New problems that no ones ever seen before. And society, entrepreneurship, diversity inclusion, education, non-profits. You don't think of Gov Cloud and Public Sector; you think non-profits, education. So it's kind of these sectors that are coming together. This is a new phenomenon. Can you talk and explain the dynamic behind that and the opportunity? >> Sure. I love to hear the stories of what our customers are doing when they really are tackling a problem that no one had thought of before. So for instance, at Reinvent this year, one of our Public Sector customers who spoke was Thorne. And they are using AI to crawl the dark web and help find people who are trafficking children in human trafficking, and that's a great use of AI and that's the kind of thing. It also helps our public servants because it helps to make police officers' jobs more effective. So of course we know that police officers, there are never enough police officers to go around. There's never enough detectives to look into everything that they need to and this makes them so much more effective to make the world a safer, better place. I also love some of the things about educational outcomes. Ivy Tech Community College is one of our great community college customers. And their using big data analysis to put together all of the different data sets that they have about their students and identify who might be at risk of failing a class 10 days into the semester so that they can help intervene with those students. >> Where was that class when I needed it? >> I know. >> Popup and say, "Hey homework time." >> I mean it really is looking at what kind of issues that they're having very early on with attendance, with different behavioral things. >> A great example at Reinvent with the California Community College system. That was a very interesting way. He was up there bragging like it was nobody's business. >> Yeah, and I think the community colleges that really goes into this idea of we're trying to expand opportunity for a wide-range of people. You might think of computer scientists as that's going to be all the Carnegie Mellon and Stanford and MIT people. And of course those are great contributors to computer science, but the fact is that computer science is so critical in so many aspects of life and in so many different kinds of careers. We know that one of the limiters to our own growth is going to be the talent that we have available to take advantage of the technology. We've been really working hard to expand opportunity for a wide-range of people, so that any smart person with an idea, can be using our technology, that's part of what's behind building the AWS Educate Program, which is a program to offer free computer science training to any university student or college student anywhere in the world. >> So it's a program you guys are doing? >> (Tricia) This is a program we are doing, >> What's it called again? >> AWS Educate. And it's a program that offers free credits to use AWS to any student who is enrolled in any kind of university or college anywhere around the world. >> That's a gateway drug to Cloud computing. >> Absolutely. >> Free resources. >> Yeah, and we're giving them a training path so that they can... >> So they want to write some code, or whatever they want to do. >> Yeah, and they can take different paths and learn. Okay, I want to learn a data science pathway, so I'm going to go that way. I want to learn a websites pathway. And they can go through things and build a portfolio of projects that they've actually built. >> So can they tap into some of the AWS AI tools too? >> They can tap into a wide range of tools and they have different levels of tiers of credits that they get, so it's a really great program to really open up Cloud computing. >> Now is there any limitations on that? What grade levels, is it college and above? >> Actually at Reinvent we just opened it up to students 14 and above. >> (John) Beautiful. That's awesome. >> And we also have a program called... >> How do they prove they're a student? >> Having a school, an EDU email address, or their school being registered through the program. >> (John) Okay, that's awesome. >> And then we also have another program called We Power Tech, and that really is a program to help open up the talent pool again to women to underserved communities, to people of different ethnic backgrounds who might not see themselves in technology because they don't see themselves as computer programmers on TV or whatever. >> Or they don't see their peer group in there, or some sort of might be an inclusion issue. >> Right and we're looking at if you take educate and We Power Tech, we're looking at that full pipeline of talent all the way from kids who are deciding should I pursue computer science or not, all the way through to professionals and getting them to try to stay in technology. >> So you guys are legit on this. You're not going to just check the box and focus on narrow things. A lot of companies do that, where they go oh we're targeting young girls or women. You guys are looking at the spectrum broader. >> Yep. And we're really looking at different communities and helping people to find their community in technology so that they can find supportive networks and also find people to mentor them or find people to mentor who are elsewhere. >> How big of a problem is it right now in today's culture and in the online culture to find peers and friends to do work like this? Because it just doesn't seem to me like there's been any innovation in online message groups. Seems like so 30 years ago. (Tricia laughs) >> Yeah. I think it is tough and I think there are somethings that we're trying to break through. For instance, a lot of the role models out there are the same people over and over again. We're trying to find new role models. And we find that through our customers. We find customers who are doing interesting work and we're trying to cultivate their voice and help put them on stage. >> New voices because it's new things. Machine learning, these are new disciplines. Data science across the board. >> Yeah, and one of the things that I love about the technology is it really is has democratizing affect. If you have an idea, you can make that idea happen for very little money, with just your ingenuity and your ability to stick to it. >> I got to ask you the hard question. Shouldn't be hard for you, but Amazon is gritty. It's been called gritty by me, hustling, but they're very good with their money. They don't really waste a lot in marketing. >> Yeah we're frugal. >> Very frugal, but you're very efficient, so I got to ask your favorite gorilla marketing technique. Cause you guys do more with less. >> (Tricia) We do. >> Once been criticized in Wired magazine. I remember reading years ago about they were comparing the Schwag bag to Reinvent. (Tricia laughs) Google almost gave out phones. It's kind of like typical reporter, but my point is you guys spend your money on education to engineers. You don't skip on that, but you might not put the flair onto an event, but now you guys are doing it. >> I think there are two things. So one of them is the aesthetic of our events. We typically do have a very stripped down aesthetic and we've made frugal look cool. I think that's one of the things I learned when I came here was go ahead and have the concrete floor and put quotes from customers there instead of paying to carpet it. So don't waste money on things that don't add value that's one of the core tenants of what we do in marketing. >> Get a better band instead of the rug. You guys have always had great music. >> We do always have great music. >> Tricia, tell me about your favorite program or project you've done a lot over the years. Pick your favorite child. What's your favorite? You have a lot of great stuff going on. Do you have a favorite? >> I think that my favorite is probably the City on a Cloud Innovation Challenge which is something we've done every year for the last four years. And we really went and asked cities, "Tell us what you're doing with our technology." Because we weren't sure what they were doing cause it's not very expensive for cities to run on us. We found that they were doing incredible things. They were doing water monitoring in their cities to help improve the quality of life of their citizens. They were delivering education more effectively. They were helping their transportation run in a more effective way. New York City Department of Transportation was doing really cool citizen facing apps to help them manage their transportation challenges and also cities all around the world. We've had people put in things about garbage management in Jerusalem and about lighting management in a Japanese city. We've had all kinds of really interesting stories come out and I just love hearing what the customers are doing and this year we added a Dream Big category where we said, "If you had the money, what would "you do with technology in your city?" and we've been really thrilled to be able to offer grants and fund some of those things to help cities get started. >> That's awesome. Not only is it engaging for them to engage with you through the program, it's inspirational. The use cases are everything from IOT to every computer. >> Yeah and we've also had partners submit as well, and we've learned about things like parking applications that cities are putting in place to help their citizens find better parking or all kinds of really interesting. How to keep track of the tree and do a tree census in their cities. Things like that. >> Maybe I'll borrow that and give you credit for it as a Cube question. What would you do if you had unlimited money? >> Exactly. (John laughs) Well the great part is that most of the cities find out that they can do what they want to do with very little money. They think it's going to be millions of dollars and then they realize, "Oh my gosh, it's going to be hard "for me to spend this 50 thousand dollar grant "because it doesn't cost that much." >> That's awesome and you got a big event coming up in June. Public Sector Summit again. Any preview on that? Any thing you can share? I'm sure it's a lot of things up in the air. >> A lot of really cool things. We are very excited to have some of our great customers on stage again. We're also this year going to have a pre day where we're going to feature Air and Space workloads on AWS. So that's going to be really interesting. I think we're going to have Blue Origin there and we're going to talk about what it's going to take to get to the next planet. >> And certainly that's beautiful for Cloud and also a huge robotics trend. People love to geek out on space related stuff. >> Yep. >> Awesome. Well the Cube will be there. Any numbers? Is it going to be the same location? >> It's going to be the same location at the Convention Center June 20th and 21st. We're going to have boot camps and certification labs and all that kind of stuff. I expect we'll grow again, so definitely more than seven thousand people. >> How big was the first one? >> Oh my gosh, the first one was in a little hotel conference room. I think there were a hundred and 50 people there. (Tricia laughs) >> Sounds like Reinvent happening all over again. We've seen this movie before. >> (Tricia) Yep. >> Tricia, thanks so much for coming on the Cube here. In the headquarters of Amazon Web Services Public Sector Summit in Washington DC. We're in Arlington, Virginia, right next to the nation's capital. I'm John Furrier. Thanks for watching. (techno music)

>> Announcer: 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 I'm your host Rebecca Knight along with my co-host Dave Vellante, we're joined by Brendan Aldrich he is the chief data officer at Ivy Tech which is Indiana's community college system Thanks so much for joining us. >> Thank you very much I appreciate it. >> And congratulations because I know that you've just won the Pentaho Excellence Award for the Social Impact category. At Ivy Tech you are you using the power of data to combat one of the toughest problems in education higher education drop out rate so tell us a little bit about what you're doing and how you're using data. >> Certainly, well Ivy Tech has been really one of the more innovative players in the higher education space when it comes to how we're utilizing data. Both from the work that data engineering and our chief technology officer has done to the work we're doing now from my area to make that data very useful and very usable for the organization. And we're tackling it on multiple fronts. We're using data in order to help more quickly identify students that have already completed the requirements to graduate. Or if they are close to or have already potentially completed the requirements to graduate on another major other than their declared major and starting those conversations with the students. >> And what about the drop out too so you are obviously also looking at students that are at risk. >> We've been engaged in a project called Project Early Success where we work in the first two weeks of a 16 week term to identify which students we believe are at risk for failure. And then we spend the next two weeks, weeks 3 and 4 of the term coordinating hundreds of faculty staff and administrators to reach out and try to talk to those students and see if we can move them back on track. The first term that we did that we saw a great success with, we, by mid-term were showing a 3.3 percentage point drop in our number of D's and F's being reported. For an organization our size, that meant over 3000 students, more student, who were passing their courses at mid-term as compared to failing them, compared to the year before. >> Scope of the organization? Student size? >> Ivy Tech, we are Indiana state wide community college system so we have 19 campuses, almost 9000 employees and we educate around 160 000 students per year. >> Wow. So just getting back to that college drop out, so professors are putting in the data about who's going to class, who's not going to class >> Brendan: That's right. >> The grades that their getting. And then that's all being fed in and you're finding out who the at risk people are, and it's really just reaching out to them and it's saying "Hey, what's going on?" >> Absolutely. And in fact a lot of the work was done with our engineering team to actually identify data that related to the behaviors of the students. So it's not just their attendance it's not just previous performance in similar classes. But it's really finding those data elements that relate to behaviors of the students that we believe are going to put them on a less successful track. >> Brendan I wonder if we can talk about the role of the Chief Data Officer. When we talk to CDO's in for profit organizations they always say we start with an understanding of how data can help with our monetization strategies. Now let's translate that for a community college. Is that a reasonable starting point if I frame it as how data adds value to the organization is that where you started and take us through sort of the journey of your role. >> Absolutely. Well first of all Chief Data Officers in higher education are still fairly rare. At the time Ivy Tech hired me in December of 2015 I was only the 9th Chief Data Officer working at any college or university in the country. And the first that had been appointed at a two year college. So whereas a public institution like ours is not necessarily as driven by profitability students success is something that's very high on our priority list and being sure that we were able to make data very available to everyone in the organization that was working with our students so that they could use that data to more directly target the areas that they could help the student best. Now there can be profitability components as a public institution we do receive funds from the state, performance funding for students who successfully graduate. In some ways we've been able to use data to help our registrars identify those students more quickly. Which certainly gives us a lot of opportunity not only to help the students on their own educational goals and careers but to be able to increase the amount of performance funding that Ivy Tech receives from the state as well. >> So that you brought to the other point CDO's tell us is data access, making that data accessible. And then there's a trust component too. It's got to be reliable and it's hard with all this data and all this data growth is how are you addressing kind of those challenges? >> One of the things that's really unique about how we're approaching data at Ivy Tech is this idea of a data democracy. It's more than self-service business intelligence or self-service analytics. Because instead of just providing access we wanted to make sure that once our employees had access, that the data was intuitive. That it was relevant to their responsibilities. That it was interactive. So that as their needs and challenges and questions evolved they could continue to use data to answer those questions without having to go back to a central IT team or a central research team. So the data democracy is a really unique aspect of ours that was important to us and I think at the moment we have about 4000 of our employees trained and running on our platform today. >> So everybody wants to be data driven these days your job is to actually affect that data driven initiative. Culturally, people say they're data driven but they don't necessarily act that way. They still act on gut feel and this is the way we've always done it. How have you been able to affect the cultural transformation? >> Well it's important to remember that if you can make the right data available to the people who are ready to use it, that's a transformational opportunity. For us, before we began on this project less than 2% of our employee base actually had the ability to create a report. Everyone else had to make requests wait for data to be made available it could take time and maybe that data wasn't available by the time they actually needed it. So if you think about that, moving from a place where less than 2% of our employees had access to data to a point where we're approaching 50% of our employees now having really good access to data we didn't want just a few silver bullets we feel that every one of our employees has the potential, if they have the right data available to test their ideas with data and come up with brand new, innovative ideas. So we could have thousands of silver bullets coming to rise throughout our organization. >> So give us some examples, I mean we've talked a little bit about how the data is transforming the student experience and student success rate but how, what are some of your grand ideas about how faculty and how employees can use data to test ideas and make their lives easier and make Ivy Tech more successful. >> Oh absolutely. And even if you think about Project Early Success and the idea that we were helping to identify students that we believe may be struggling behaviorally in being successful in their courses. Now if you can take that as an attribute and you can surface it through our system to the employees that are using it which includes our faculty. Our faculty members now have the ability to see very quickly which of their students may be struggling and have the chance to intervene with those students as well on a regular basis. So it's not just one phone call at the beginning of the term. It's not just Project Early Success but now what we're talking about as Project Student Success how do we continue to use that kind of information to engage the student over the entire course of the term to ensure that we're not just changing their trajectory a little bit in the beginning but that we're following that journey with them over the course of their educational goal. >> Can you talk about the regime in your organization? The reporting structure, to whom do you report is there a CIO- >> Brendan: There is. >> What's the relationship there? >> There is a CIO who I report to the Chief Technology Officer and I both report to the CIO and we had a recent change in our leadership within the organization as well. Back a year ago this last July we have a new president of the state wide organization Dr. Sue Ellspermann who was formerly our lieutenant governor for the state of Indiana. >> So that's interesting that you report to the CIO. Most Chief Data Officers, we find, I wonder if you can comment don't report to the CIO there's sort of a parallel organization for a variety of reasons. People generally believe that well, it maybe one day was the CIO's job it's sort of the CIO's job morphed into kind of keeping the lights on and the infrastructure going, but what do you see amongst your colleagues with that regard? >> You know what's important for me and I think that if you look at every organization across the country there is this data knowledge gap. This idea that you've got your IT and engineering staff that knows everything there is about how to build, support, augment and de-commission these systems but generally have not been as involved in what the data means inside those systems or what decisions are being made off that data. On the other half of that gap you've got all of the rest of your organization the people that are using data who know what it means and who are making decisions from it but generally don't know enough about how to think about structuring that data so that they could get the engineering teams to build them new tools. This is really the place where a Chief Data Officer in my mind comes to sit. Because my goal is to build those bridges between the organization so that we can help engineering learn more about what we're doing as an organization with data and then use that information to build tools that will drive the rest of the organization closer to those goals through data. >> Now you're not a bank so you've got, I'm imagining a pretty small team. >> Brendan: We do. >> So maybe you can talk about that and how you manage with such a small team. >> You know it's interesting most organizations when you think about a build versus buy scenario you think about well I don't have a lot of people I don't have a lot of bandwiths, maybe we need to buy. Now Ivy Tech went through that process and every one of the RP's that came back were too expensive We couldn't afford to do it. So as a team we had to sit down and think about how do we really rethink the way that we approach this in order to still accomplish what we need out of data and out of our data warehouse and analytic systems. Part of what I'll be speaking at the conference today is some of those entrenched data practices that we had to overcome or rethink and rewrite in order to get to where we are today. >> Well Brendan it's been so much fun having you on theCUBE, thanks so much. >> Well thank you, I appreciate it. >> I'm Rebecca Knight for Dave Vellante you are watching theCUBE, we will have more from Pentaho World in just a little bit. (electronic music)

>> Announcer: Live from San Jose, California, it's theCUBE. Covering Big Data Silicon Valley 2017. >> Okay, welcome back everyone. Here live in Silicon Valley this is theCUBE. I'm John Furrier, covering our Big Data SV event, #BigDataSV. Our companion event to Big Data NYC, all in conjunction Strata Hadoop, the Big Data World comes together, and great to have guests come by. Donna Prlich, who's the senior VP of products and solutions at Pentaho, a Hitachi company who we've been following before Hitachi had acquired you guys. But you guys are unique in the sense that you're a company within Hitachi left alone after the acquisition. You're now running all the products. Congratulations, welcome back, great to see you. >> Yeah, thank you, good to be back. It's been a little while, but I think you've had some of our other friends on here, as well. >> Yep, and we'll be at Pentaho World, you have Orlando, I think is October. >> Yeah, October, so I'm excited about that, too, so. >> I'm sure the agenda is not yet baked for that because it's early in the year. But what's going on with Hitachi? Give us the update, because you're now, your purview into the product roadmap. The Big Data World, you guys have been very, very successful taking this approach to big data. It's been different and unique to others. >> [Donna} Yep. What's the update? >> Yeah, so, very exciting, actually. So, we've seen, especially at the show that the Big Data World, we all know that it's here. It's monetizable, it's where we, actually, where we shifted five years ago, and it's been a lot of what Pentaho's success has been based on. We're excited because the Hitachi acquisition, as you mentioned, sets us up for the next bit thing, which is IOT. And I've been hearing non-stop about machine learning, but that's the other component of it that's exciting for us. So, yeah, Hitachi, we're-- >> You guys doing a lot of machine learning, a lot of machine learning? >> So we, announced our own kind of own orchestration capabilities that really target how do you, it's less about building models, and how do you enable the data scientists and data preparers to leverage the actual kind of intellectual properties that companies have in those models they've built to transform their business. So we have our own, and then the other exciting piece on the Hitachi side is, on the products, we're now at the point where we're running as Pentaho, but we have access to these amazing labs, which there's about 25 to 50 depending on where you are, whether you're here or in Japan. And those data scientists are working on really interesting things on the R & D side, when you apply those to the kind of use cases we're solving for, that's just like a kid in a candy store with technology, so that's a great-- >> Yeah, you had a built-in customer there. But before I get into Pentaho focusing on what's unique, really happening within you guys with the product, especially with machine learning and AI, as it starts to really get some great momentum. But I want to get your take on what you see happening in the marketplace. Because you've seen the early days and as it's now, hitting a whole another step function as we approach machine learning and AI. Autonomous vehicles, sensors, everything's coming. How are enterprises in these new businesses, whether they're people supporting smart cities or a smart home or automotive, autonomous vehicles. What's the trends you are seeing that are really hitting the pavement here. >> Yeah, I think what we're seeing is, and it's been kind of Pentaho's focus for a long time now, which is it's always about the data. You know, what's the data challenge? Some of the amounts of data which everybody talks about from IOT, and then what's interesting is, it's not about kind of the concepts around AI that have been around forever, but when you start to apply some of those AI concepts to a data pipeline, for instance. We always talk about that 6data pipeline. The reason it's important is because you're really bringing together the data and the analytics. You can't separate those two things, and that's been kind of not only a Pentaho-specific, sort of bent that I've had for years, but a personal one, as well. That, hey, when you start separating it, it makes it really hard to get to any kind of value. So I think what we're doing, and what we're going to be seeing going forward, is applying AI to some of the things that, in a way, will close the gaps between the process and the people, and the data and the analytics that have been around for years. And we see those gaps closing with some of the tools that are emerging around preparing data. But really, when you start to bring some of that machine learning into that picture, and you start applying math to preparing data, that's where it gets really interesting. And I think we'll see some of that automation start to happen. >> So I got to ask you, what is unique about Pentaho? Take a minute to share with the audience some of the unique things that you guys are doing that's different in this sea of people trying to figure out big data. You guys are doing well, an6d you wrote a blog post that I referenced earlier yesterday, around these gaps. How, what's unique about Pentaho and what are you guys doing with examples that you could share? >> Yeah, so I think the big thing about Pentaho that's unique is that it's solving that analytics workflow from the data side. Always from the data. We've always believed that those two things go together. When you build a platform that's really flexible, it's based on open source technology, and you go into a world where a customer says, "I not only want to manage and have a data lake available," for instance, "I want to be able to have that thing extend over the years to support different groups of users. I don't want to deliver it to a tool, I want to deliver it to an application, I want to embed analytics." That's where having a complete end-to-end platform that can orchestrate the data and the analytics across the board is really unique. And what's happened is, it's like, the time has come. Where all we're hearing is, hey, I used to think it was throw some data over and, "here you go, here's the tools." The tools are really easy, so that's great. Now we have all kinds of people that can do analytics, but who's minding the data? With that end-to-end platform, we've always been able to solve for that. And when you move in the open source piece, that just makes it much easier when things like Spark emerge, right. Spark's amazing, right? But we know there's other things on the horizon. Flink, Beam, how are you going to deal with that without being kind of open source, so this is-- >> You guys made a good bet there, and your blog post got my attention because of the title. It wasn't click bait either, it was actually a great article, and I just shared it on Twitter. The Holy Grail of analytics is the value between data and insight. And this is interesting, it's about the data, it's in bold, data, data, data. Data's the hardest part. I get that. But I got to ask you, with cloud computing, you can see the trends of commoditization. You're renting stuff, and you got tools like Kinesis, Redshift on Amazon, and Azure's got tools, so you don't really own that, but the data, you own, right? >> Yeah, that's your intellectual property, right? >> But that's the heart of your piece here, isn't it, the Holy Grail. >> Yes, it is. >> What is that Holy Grail? >> Yeah, that Holy Grail is when you can bring those two things together. The analytics and the data, and you've got some governance, you've got the control. But you're allowing the access that lets the business derive value. For instance, we just had a customer, I think Eric might have mentioned it, but they're a really interesting customer. They're one of the largest community colleges in the country, Ivy Tech, and they won an award, actually, for their data excellence. But what's interesting about them is, they said we're going to create a data democracy. We want data to be available because we know that we see students dropping out, we can't be efficient, people can't get the data that they need, we have old school reporting. So they took Pentaho, and they really transformed the way they think about running their organization and their community colleges. Now they're adding predictive to that. So they've got this data democracy, but now they're looking at things like, "Okay we an see where certain classes are over capacity, but what if we could predict, next year, not only which classes are over capacity, what's the tendency of a particular student to drop out?" "What could we do to intervene?" That's where the kind of cool machine learning starts to apply. Well, Pentaho is what enables that data democracy across the board. I think that's where, when I look at it from a customer perspective, it's really kind of, it's only going to get more interesting. >> And with RFID and smart phones, you could have attendance tracking, too. You know, who's not showing up. >> Yeah absolutely. And you bring Hitachi into the picture, and you think about, for instance, from an IOT perspective, you might be capturing data from devices, and you've got a digital twin, right? And then you bring that data in with data that might be in a data lake, and you can set a threshold, and say, "Okay, not only do we want to be able to know where that student is," or whatever, "we want to trigger something back to that device," and say, "hey, here's a workshop for you to login to right away, so that you don't end up not passing a class." Or whatever it is, it's a simplistic model, but you can imagine where that starts to really become transformative. >> So I asked Eric a question yest6erday. It was from Dave Valante, who's in Boston, stuck in the snowstorm, but he was watching, and I'll ask you and see how it matches. He wrote it differently on Crouch, it was public, but this is in my chat, "HDS is known for main frames, historically, and storage, but Hitachi is an industrial giant. How is Pentaho leveraging the Hitachi monster?" >> Yes, that's a great way to put it. >> Or Godzilla, because it's Japan. >> We were just comparing notes. We were like, "Well, is it an $88 billion company or $90 billion. According to the yen today, it's 88. We usually say 90, but close enough, right? But yeah, it's a huge company. They're in every industry. Make all kinds of things. Pretty much, they've got the OT of the world under their belt. How we're leveraging it is number one, what that brings to the table, in terms of the transformations from a software perspective and data that we can bring to the table and the expertise. The other piece is, we've got a huge opportunity, via the Hitachi channel, which is what's seeing for us the growth that we've had over the last couple of years. It's been really significant since we were acquired. And then the next piece is how do we become part of that bigger Hitachi IOT strategy. And what's been starting to happen there is, as I mentioned before, you can kind of probably put the math together without giving anything away. But you think about capturing, being able to capture device data, being able to bring it into the digital twin, all of that. And then you think about, "Okay, and what if I added Pentaho to the mix?" That's pretty exciting. You bring those things together, and then you add a whole bunch of expertise and machine learning and you're like, okay. You could start to do, you could start to see where the IOT piece of it is where we're really going to-- >> IOT is a forcing function, would you agree? >> Yes, absolutely. >> It's really forcing IT to go, "Whoa, this is coming down fast." And AI and machine learning, and cloud, is just forcing everyone. >> Yeah, exactly. And when we came into the big data market, whatever it was, five years ago, in the early market it's always hard to kind of get in there. But one of the things that we were able to do, when it was sort of, people were still just talking about BI would say, "Have you heard about this stuff called big data, it's going to be hard." You are going to have to take advantage of this. And the same thing is happening with IOT. So the fact that we can be in these environments where customers are starting to see the value of the machine generated data, that's going to be-- >> And it's transformative for the business, like the community college example. >> Totally transformative, yeah. The other one was, I think Eric might have mentioned, the IMS, where all the sudden you're transforming the insurance industry. There's always looking at charts of, "I'm a 17-year-old kid," "Okay, you're rate should be this because you're a 17-year-old boy." And now they're starting to track the driving, and say, "Well, actually, maybe not, maybe you get a discount." >> Time for the self-driving car. >> Transforming, yeah. >> Well, Donna, I appreciate it. Give us a quick tease here, on Pentaho World coming in October. I know it's super early, but you have a roadmap on the product side, so you can see a little bit around the corner. >> Donna: Yeah. >> What is coming down the pike for Pentaho? What are the things that you guys are beavering away at inside the product group? >> Yeah, I think you're going to see some really cool innovations we're doing. I won't, on the Spark side, but with execution engines, in general, we're going to have some really interesting kind of innovative stuff coming. More on the machine learning coming out, and if you think about, if data is, you know what, is the hard part, just think about applying machine learning to the data, and I think you can think of some really cool things, we're going to come up with. >> We're going to need algorithms for the algorithms, machine learning for the machine learning, and, of course, humans to be smarter. Donna, thanks so much for sharing here inside theCUBE, appreciate it. >> Thank you. >> Pentaho, check them out. Going to be at Pentaho World in October, as well, in theCUBE, and hopefully we can get some more deep dives on, with their analyst group, for what's going on with the engines of innovation there. More CUBE coverage live from Silicon Valley for Big Data SV, in conjunction with Strata Hadoop, I'm John Furrier. Be right back with more after this short break. (techno music)