>>Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host. Lisa Martin. We've got two female rock stars here with me next. Stephanie Curry joins us the worldwide head of sales and go to market strategy for AWS at NetApp and Danielle GShock is back one of our QM ISV PSA director at AWS. Looking forward to a great conversation, ladies, about a great topic, Stephanie, let's go ahead and start with you. Give us an overview of your story, how you got into tech and what inspired you. >>Thanks so much, Lisa and Danielle. It's great to be on this show with you. Thank you for that. My name's Stephanie curs. Lisa mentioned I'm the worldwide head of sales for AWS at NetApp and run a global team of sales people that sell all things AWS going back 25 years now, when I first started my career in tech, it was kind of by accident. I'd come from a different background. I have a business background and a technical background from school, but had been in a different career. And I had an opportunity to try something new. I had an ally really that reached out to me and said, Hey, you'd be great for this role. And I thought, I'd take a chance. I was curious. And it, it turned out to be a 25 year career that I'm really, really excited about and, and really thankful for that person for introducing me to the, to the industry >>25 years in counting. I'm sure Danielle, we've talked about your background before. So what I wanna focus on with you is the importance of diversity for high performance. I know what a machine AWS is, and Stephanie, I'll come back to you with the same question, but talk about that, Danielle, from your perspective, that importance for diversity to drive the performance. >>Yeah. I truly believe that, you know, in order to have high performing teams, that you have to have people from all different types of backgrounds and experiences. And we do find that oftentimes being, you know, field facing, if we're not reflecting our customers and connecting with them deeply on, on the levels that they're at, we, we end up missing them. And so for us, it's very important to bring people of lots of different technical backgrounds experiences. And of course, both men, women, and underrepresented minorities, and put that forth to our customers in order to make that connection and to end up with better outcomes. So >>Definitely it's all about outcomes, Stephanie, your perspective and NetApp's perspective on diversity for creating highly performing teams and organizations. >>I really aligned with Danielle on the comment she made. And in addition to that, you know, just from building teams in my career note, we've had three times as many women on my team since we started a year ago and our results are really showing in that as well. We find the teams are stronger, they're more collaborative and to Danielle's point really not only our partners, but our customers themselves. So this really creates connections, which are really, really important to scale our businesses and, and really meet the customer where they're at as well. So huge proponent of that ourselves, and really finding that we have to be intentional in our hiring and intentional in how we attract diversity to our teams. >>So Stephanie let's stay with you. So a three X increase in women on the team in a year, especially the kind of last year that we've had is really incredible. I, I like your, I, your thoughts on there needs to be a, there needs to be focus and, and thought in how teams are hired. Let's talk about attracting and retaining those women now, especially in sales roles, we all know the number, the percentages of women in technical roles, but what are some of the things that, that you do Stephanie, that NetApp does to attract and retain women in those sales roles? >>The, the attracting part's really interesting. And we find that, you know, you, you read the stats and I'd say in my experience, they're also true in the fact that a lot of women would look at a job description and say, I can't do a hundred percent of that. So I'm not even going to apply with the women that we've attracted to our team. We've actually intentionally reached out and targeted those people in a good way to say, Hey, we think you've got what it takes. Some of the feedback I've got from those women are, gosh, I didn't think I could ever get this role. I didn't think I had the skills to do that. And they've been hired and they are doing a phenomenal job. In addition to that, I think a lot of the feedback I've got from these hires are, Hey, it's an aggressive sales is aggressive. Sales is competitive. It's not an environment that I think I can be successful in. And what we show them is bring those softer skills around collaboration, around connection, around building teams. And they do, they do bring a lot of that to the team. Then they see others like them there and they know they can be successful cuz they see others like them on the team. >>The whole concept of we can't be what we can't see, but we can be what we can see is so important. You said a couple things, Stephanie, that really stuck with me. And one of 'em was an, an interview on the cube I was doing, I think a couple weeks ago about women in tech. And the stat that we talked about was that women will apply will not apply for a job unless they meet 100% of the skills and the requirements that it's listed, but men will, if they only meet 60. And I, that just shocked me that I thought, you know, I, I can understand that imposter syndrome is real. It's a huge challenge, but the softer skills, as you mentioned, especially in the last two years, plus the ability to communicate, the ability to collaborate are incredibly important to, to drive that performance of, of any team of any business. >>Absolutely. >>Danielle, talk to me about your perspective in AWS as well for attracting and retaining talent and, and, and particularly in some of those challenging roles like sales that as Stephanie said, can be known as aggressive. >>Yeah, for sure. I mean, my team is focused on the technical aspect of the field and we definitely have an uphill battle for sure. Two things we are focused on first and foremost is looking at early career women and that how we, how can we bring them into this role, whether in they're in support functions, cl like answering the phone for support calls, et cetera, and how, how can we bring them into this organization, which is a bit more strategic, more proactive. And then the other thing that as far as retention goes, you know, sometimes there will be women who they're on a team and there are no other women on that team. And, and for me, it's about building community inside of AWS and being part of, you know, we have women at solution architecture organizations. We have, you know, I just personally connect people as well and feel like, oh, you should meet this person. Oh, you should talk to that person. Because again, sometimes they can't see someone on their team like them and they just need to feel anchored, especially as we've all been, you know, kind of stuck at home during the pandemic, just being able to make those connections with women like them has been super important and just being a long tenure Amazonian, that's definitely one thing I'm able to, to bring to the table as well. >>That's so important and impactful and spreads across organizations in a good way. Daniel let's stick with you. Let's talk about some of the allies that you've had sponsors, mentors that have really made a difference. And I said that in past tense, but I also mean in present tense, who are some of those folks now that really inspire you? >>Yeah. I mean, I definitely would say that one of my mentors and someone who ha has been a sponsor of my career has Matt ion, who is one of our control tower GMs. He has really sponsored my career and definitely been a supporter of mine and pushed me in positive ways, which has been super helpful. And then other of my business partners, you know, Sabina Joseph who's cube alum as well. She definitely has been, was a fabulous partner to work with. And, you know, between the two of us for a period of time, we definitely felt like we could, you know, conquer the world. It's very great to go in with a, with another strong woman, you know, and, and get things done inside of an organization like AWS. >>Absolutely. And know S I've had, I've been agreed here several times. So Stephanie, same question for you. You talked a little bit about your kind of, one of your original early allies in the tech industry, but talk to me about allies sponsors, mentors who have, and continue to make a difference in your life. >>Yeah. And, you know, I think it's a great differentiation as well, right? Because I think that mentors teach us sponsors show us the way and allies make room for us at the table. And that is really key difference. I thinks also as women leaders, we need to make room for others at the table too, and not forget those softer skills that we bring to the table. Some of the things that Danielle mentioned as well about making those connections for others, right. And making room for them at the table. Some of my allies, a lot of them are men. Brian ABI was my first mentor. He actually is in the distribution, was in distribution with advent tech data no longer there, Cory Hutchinson, who's now at Hashi Corp. He's also another ally of mine and remains an ally of mine, even though we're not at the same company any longer. So a lot of these people transcend careers and transcend different positions that I've held as well and make room for us. And I think that's just really critical when we're looking for allies. And when allies are looking for us, >>I love how you described allies, mentors and sponsors Stephanie. And the difference, I didn't understand the difference between a mentor and a sponsor until a couple of years ago. Do you talk with some of those younger females on your team so that when they come into the organization and maybe they're fresh outta college, or maybe they've transitioned into tech so that they can also learn from you and understand the importance and the difference between the allies and the sponsors and the mentors? >>Absolutely. And I think that's really interesting because I do take an extra approach and extra time to really reach out to the women that have joined the team. One, I wanna make sure they stay right. I don't want them feeling, Hey, I'm alone here and I need to, I need to go do something else. And they are located around the world, on my team. They're also different age groups. So early in career, as well as more senior people and really reaching out, making sure they know that I'm there. But also as Danielle had mentioned, connecting them to other people in the community that they can reach out to for those same opportunities and making room for them >>Make room at the table. It's so important. And it can, you never know what a massive difference and impact you can make on someone's life. And I, and I bet there's probably a lot of mentors and sponsors and allies of mine that would be surprised to know the massive influence they've had Danielle back. Let's talk about some of the techniques that you employ that AWS employs to make the work environment, a great place for women to really thrive and, and be retained as Stephanie was saying. Of course that's so important. >>Yeah. I mean, definitely I think that the community building, as well as we have a bit more programmatic mentorship, we're trying to get to the point of having a more programmatic sponsorship as well. But I think just making sure that, you know, both E everything from recruit to onboard to ever boarding that they they're the women who come into the organization, whether it's they're coming in on the software engineering side or the field side or the sales side that they feel as though they have someone working with them to help them drive their career. Those are the key things that were, I think from an organizational perspective are happening across the board. For me personally, when I run my organization, I'm really trying to make sure that people feel that they can to me at any time open door policy, make sure that they're surfacing any times in which they are feeling excluded or anything like that, any challenges, whether it be with a customer, a partner, or with a colleague. And then also of course, just making sure that I'm being a good sponsor to, to people on my team. That is key. You can talk about it, but you have to start with yourself as well. >>That's a great point. You you've got to, to start with yourself and really reflect on that and, and look, am I, am I embodying what it is that I need? And not that I know they need that focused, thoughtful intention on that is so importants, let's talk about some of the techniques that you use that NetApp uses to make the work environment, a great place for those women are marginalized communities to really thrive. >>Yeah. And I appreciate it. And it much like Danielle and much like AWS, we have some of those more structured programs, right around sponsorship and around mentorship, probably some growth there, opportunities for allies, because I think that's more of a newer concept in really an informal structure around the allies, but something that we're growing into at NetApp on my team personally, I think leading by example is really key. And unfortunately, a lot of the life stuff still lands on the women, whether we like it or not, I have a very active husband in our household, but I still carry when it push comes to shove it's on me. And I wanna make sure that my team knows it's okay to take some time and do the things you need to do with your family. I'm I show up as myself authentically and I encourage them to do the same. >>So it's okay to say, Hey, I need to take a personal day. I need to focus on some stuff that's happening in my personal life this week. Now obviously make sure your job' covered, but just allowing some of that softer vulnerability to come into the team as well, so that others, men and women can feel they can do the same thing. And that it's okay to say, I need to balance my life and I need to do some other things alongside. So it's the formal programs, making sure people have awareness on them. I think it's also softly calling people out on biases and saying, Hey, I'm not sure if you know, this landed that way, but I just wanted to make you aware. And usually the feedback is, oh my gosh, I didn't know. And could you coach me on something that I could do better next time? So all of this is driven through our NetApp formal programs, but then it's also how you manifest it on the teams that we're leading. >>Absolutely. And sometimes having that mirror to reflect into can be really eye-opening and, and allow you to, to see things in a completely different light, which is great. You both talked about kind of being what you can see. And, and I know both companies are obsess customer obsessed in a good way. Talk to me a little bit, Danielle, go back over to you about the AWS NetApp partnership. Some of the maybe alignment on, on performance on obviously you guys are very well aligned in terms of that, but also it sounds like you're quite aligned on diversity and inclusion. >>Well, we definitely do. We have the best partnerships with companies in which we have these value alignments. So I think that is a positive thing, of course, but just from a, from a partnership perspective, you know, from my five now plus years of being a part of the APN, this is, you know, one of the most significant years with our launch of FSX for NetApp, with that key key service, which we're making available natively on AWS. I, I can't think of a better Testament to the, to the partnership than that. And that's doing incredibly well and it really resonates with our customers. And of course it started with customers and their need for NetApp. So, you know, that is a reflection, I think, of the success that we're having together. >>And Stephanie talk to about the partnership from your perspective, NetApp, AWS, what you guys are doing together, cultural alignment, but also your alignment on really bringing diversity into drive performance. >>Yeah, I think it's a, a great question. And I have to say it's just been a phenomenal year. Our relationship has started before our first party service with FSX N but definitely just the trajectory between the two companies since the announcement about nine months ago has just taken off to a, a new level. We feel like an extended part of the family. We worked together seamlessly. A lot of the people on my team often say we feel like Amazonians, and we're really part of this transformation at NetApp from being that storage hardware company, into being an ISV and a cloud company. And we could not do this without the partnership with AWS and without the first party service of Fs XM that we've recently released. I think that those joint values that Danielle referred to are critical to our success, starting with customer obsession and always making sure that we are doing the right thing for the customer. >>We coach our team teams all the time on if you are doing the right thing for the customers, you cannot do anything wrong. Just always put the customer at the dis in the center of your decisions. And I think that there is a lot of best practice sharing and collaboration as we go through this change. And I think a lot of it is led by the diverse backgrounds that are on the team, female, male race, and so forth, and just to really have different perspectives and different experiences about how we approach this change. So we definitely feel like we're part of the family. We are absolutely loving working with the AWS team and our team knows that we are the right place, the right time with the right people. >>I love that last question for each of you. And I wanna stick with you Stephanie advice to your younger self, think back 25 years. What advice would you seen what you've accomplished and maybe the, the turns and, and serendipitous route that you've taken along the way, what would you advise your younger Stephanie self? >>I would say keep being curious, right? Keep being curious, keep asking questions. And sometimes when you get a no, it's not a bad thing, it just means not right now and find out why and, and try to get feedback as to why maybe that wasn't the right opportunity for you, but, you know, just go for what you want. Continue to be curious, continue to ask questions and find a support network of people around you that wanna help you because they are there and they are, they wanna see you be successful too. So never be shy about that stuff. >>Absolutely. And I always say failure does not have to be a bad F word. A no can be the beginning of something. Amazing. Danielle, same question for you. Thinking back to when you first started in your career, what advice would you give your younger self? >>Yeah, I think the advice I'd give my younger self would be, don't be afraid to put yourself out there. It's certainly, you know, coming from an engineering background, maybe you wanna stay behind the scenes, not, not do a presentation, not do a public speaking event, those types of things, but back to what the community really needs. This thing, you know, I genuinely now took me a while to realize it, but I realized I needed to put myself out there in order to, you know, allow younger women to see what they could be. So that would be the advice I would give. Don't be afraid to put yourself out there. >>Absolutely. That advice that you both gave are, is so fantastic, so important and so applicable to everybody. Don't be afraid to put yourself out there, ask questions. Don't be afraid of a, no, that it's all gonna happen at some point or many points along the way. That can also be good. So thank you ladies. You inspired me. I appreciate you sharing what AWS and NetApp are doing together to strengthen diversity, to strengthen performance and the advice that you both shared for your younger was brilliant. Thank you. >>Thank you. >>Thank you >>For my guests. I'm Lisa Martin. You're watching the AWS partner showcase. See you next time.

>> Live from San Francisco, it's theCUBE, covering Micron Insight 2018. Brought to you by Micron. >> Welcome back to the Embarcadero everybody here in the heart of San Francisco. Actually at the bay of San Francisco. Golden Gate Bridge is that way, financial district over there, Nob Hill right up the street. You're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante, this is David Floyer, and we're covering the Micron Insight 2018 event. People are starting to filter in. Any minute now we're going to start the keynotes from the executives. A lot of buzz going on, Derek Dicker is here. He's the corporate vice-president and general manager of the storage business unit emerging activity within Micron, great to see you again. >> Thank you very much for having me. It's a pleasure to be here. >> You're very welcome, yeah, so Micron used to be just a straight memory company. We're hearing, we heard at the investor day in May how you guys are diversifying, finding new use cases, new applications, you run the storage business, and of course David Floyer was one of the first, the first, in my opinion, to predict the demise of the hard disk, spinning disk, and it's a tailwind for you guys, but Derek, take us through your business unit, your role, and let's get into it. >> Sure, that sounds great. I appreciate the opportunity again to be here. The storage business unit within Micron is actually comprised across a couple of product areas. Primarily NAND and NAND components, and then also SSDs, solid state drives. As we like to say, and we've talked a bit more about it since Sanjay's arrival, we have a pretty material focus on accelerating what we call high value solutions. It's a big focus of ours, so not only are we developing the core technology in memory and storage, but we're attempting to build more and more products that add value to our customers in the S-System space. But that's generally the storage business focus. Within the company, we have three other business units that focus on compute and networking memory as well as the embedded business unit and then the mobile business unit. >> Talk about some of the big trends that you see, I mean, we've talked about for years, the all-flash data center. We clearly see that in the customers that we work with. Some of the spinning disk guys don't necessarily fully buy into that, but even they have been investing in flash technologies. What are you seeing? >> I tell you, there is no better time, in my opinion, than to be in the memory and storage industry. When you look at what the trends are that are coming out in time. If you go and you stare at how memory and storage has evolved just going back into the 80s or the PC era, a $35 billion average size of the total market. You get into the mobile space, when mobile era started with smart phones, we were looking at a $62 billion-ish, and then in '17 we cleared $120 billion in size of the market, and we actually see a lot of secular trends that are going to continue to take us forward. A couple of things that are particularly noteworthy for us. The first one is the emergence of artificial intelligence, and machine learning, and deep learning. We're going to hear quite a bit about it here at the event. But in terms of a value driver for the consumption of both memory, DRAM, as well as storage, we see it going phenomenally up in content in every server that's purchased out in time. That's one, I think with the evolution of 5G out in time, we're also going to see that smart phone devices are going to end up having more memory to add features like facial recognition we see today, becoming mainstream, multiple cameras, that drives more DRAM content, but then also on top of that, storage is increasing. We're seeing, even today, a terabyte being put into some of the high-end phones, and we know that that's going to waterfall out in time. So I think if you look at this combination of what's happening both in the devices, you look at what's happening in the infrastructure, then you couple that with the processing that needs to happen, it's just an awesome time to be affiliated with memory and storage. >> Yeah, well, I've been following this LAN marketplace for the last, almost 10 years isn't it? More than that. And it's just broken through completely in the last two or three years. What are your thoughts about pushing compute closer and closer to that memory, adding to, for example, the SSDs, the capability of doing smart work? It's very very close to where the data is originally going to be placed? >> It's a great area of quite a bit of R&D work that's going on right now, and I actually think I view this as kind of two stages. One is there's the proliferation of solid state, as you suggested, it's been coming over time. I actually see it increasing dramatically as we look forward, and one of the key technologies that I think is going to enable that is QLC. The fact that we're now at a point where we're putting four bits per cell into devices, SSDs are starting to show up, I think that just creates even more opportunity. And I'll talk a little bit about that in just a minute, but I want to answer your direct question as to how that's changing with AnIML. But I think the ability, once solid state is prolific, to be able to architect systems where you can actually have processing take place closer to the media is a very interesting area. It's right with a ton of research going on right now. People are just starting to implement it. I think there's quite a bit of potential sitting behind it. You know, our focus, of course, is we're deploying, and as quickly as we can, on two vectors. One is, how do we proliferate more solid state into the market as an industry, and the second is how do we add value when we build those solid state drives, so I think it's definitely very viable. >> Let's talk about the significance of QLC. David, your forecasts early on were very aggressive in terms of pricing declines for flash. We kind of, maybe got caught off, a little bit surprised by the-- >> I think we were caught off by the demand. >> Well the demand, but also the supply constraints kept prices up. >> Yeah. >> Okay so, it didn't actually happen as fast. How does QLC change that, Derek, and what's the significance of it? >> Well, the thing that I think is most exciting for us as Micron is we actually ended up delivering the world's first QLC device. It put a terabit of data on a single die, which was unprecedented, but then in addition to that, what we did was we actually built a solid state drive called the 5210 ION. This is a standard drive. It's the worlds first SSD built on the technology, and by being able to develop a solution early on, it allowed us to go engage with customers and find where the right workloads were where we could add the most value. QLC technology actually is perfectly aligned for super read intensive, very read intensive environments, and if you look at what's happening in the data center, we're actually seeing more and more workloads move into more read intensive workloads, and a good chunk of that is just because there's analytics going on. The data's being collected. It's being housed in on place, but as we've talked about quite a bit here at the event, we want to be able to deliver insight out of that data, which means we're going to be reading it quite a bit, and massaging it, and performing analytics on it. And what we're now seeing is what, in the days of the past, was a four to one read to write ratio, we're seeing as high as 5,000 to one and in some cases a million to one. So we get these heavily read intensive workloads coupled with the technology that's optimized for it. It's more power efficient than what rotating media solutions offer in certain workloads, we're starting to see these tremendous values coming out of these early engagements that we're having with customers. >> And does that have implications for longevity, or do you just make an assumption that the read/write ratio is still going to be more write intensive in terms of wear leveling and things like that? How does it change the reliability, if you will, of the technology? >> Actually the beauty is, we're able to deliver an enterprise class SSD with these read/write capabilities that are affiliated with these read intensive solutions, and we can fit within the workloads and the needs that people are talking about. So the drive writes per day that are required in a machine learning infrastructure, we believe we can address with QLC. Same thing with Hadoop style clusters and Ceph clusters. We've actually, as we've gone out and engaged each of our earlier customers, we're able to crank out reference architecture documents that we're now posting to our websites, and we're describing how we can actually leverage this technology to allow us to, in some cases, we'll better optimize where an SSD was used before. But in many, many cases we're actually in the process of displacing hard disk drives. >> So what are the limits of this QLC? How many more bits can we add? How many more layers can we add? >> So, it's actually a great question, David. In terms of what does a roadmap look like. I've been asked in the recent several hours, what the longevity for NAND looks like. And what I'll tell you is this, QLC NAND is just getting its start. What comes after that in terms of bits per cell, I don't think anybody's made any broad claims on. But from a layer stacking perspective, which is kind of the dimension upon which the industry is growing, for the foreseeable future, we see nothing that encumbers us from going substantially higher and higher layer count. Which I think is going to be great for our industry because it's going to allow us to deliver more bits in a given device, and hopefully, that'll allow us to get into markets that, historically, we haven't been able to approach. If you think about the demand elasticity dynamic that occur when we start to bring more and more costs down, the number of applications open up, not unlike the machine learning workloads I just mentioned or Hadoop workloads. We're starting to see more and more thirst and interest for replacing with solid state, just because it's more power efficient, allows for a cost structure that's better, and gives better performance too. >> I'm fond of saying that data's plentiful, insights aren't. You guys are a $30 billion company now. You're making some interesting announcements today that we're going to hear about a little later on that I won't divulge right now, but you're putting your hands in a lot of different places. When you're that size of a company, you can't help but, as you mentioned before, adding more value, becoming more of a systems focus. How do you help the industry go from just raw data to insights? What's your role in that? >> Oh, it's a phenomenal question and this is a major focus of the company. Not just in our business unit, but across all of the different business units in the company. We have a huge focus on sitting down with our customers and getting closer and closer to understanding what their workload needs are, where their paying points are, and then working with them to find solutions, and the beautiful part about it is, as Micron, we're the only company in the world that can combine together a 3D XPoint set of technologies, a NAND set of technologies, a DRAM set of technologies. We go sit down and talk about these challenges with those in mind, plus the emerging memories that we're developing to go develop better and better solutions. But after we're able to come to a solution, we put together a reference architecture, and we deploy it broadly. >> We've been trying to squint through 3D Xpoint and understand the right fit. It seems to us that one of the big advantages of flash was it had the, had this behind it. (laughs) It had the consumer volumes, thank you Steve Jobs. It's unclear whether or not 3D Xpoint will have that, maybe have the same, sort of, cost advantages, but the same time, it sounds like there's new and emerging applications. Like I said, we're trying to figure out. Have you guys figured out yet? You're obviously betting big on the technology. Help us understand where the fit is. >> Sure, I think, you know, if I look back in time, just at the storage hierarchy alone, I don't think the memory hierarchy's any different. You have these portions of the market where you build out hard disk drives, and we had DRAM before, and SSDs came along, and people started asking, not unlike several years back when we talked about the early parts. Hey, how big is this going to get? Cost structures may be prohibitive. But as innovation unfurled, the more time and investment got placed into it, we found new workloads, new use cases we were able to drive costs out, and we ended up slotting in solid state drives squarely. I think this is another tier of memory and storage. That's the beauty of the 3D XP technology. There's both memory semantics and storage semantics that are available for use. I think we're still scratching the surface on the early days, but I love what we're seeing from the customer base that we're engaging and targeting in this space. >> And people will pay up for that performance capability relative to flash. They'll pay down relative to DRAM. Is it, are you seeing a gradience for like the hyperscalers, for example, or is it, maybe the industrial internet? Where are you seeing the. >> It's fair, actually I think, you know, it's probably reasonable to say that, you know, the challenges of inserting a new memory tier into a system requires new programming algorithms, new APIs and interface. There's a lot of ecosystem that needs to be there, as well as, not to mention, you've got to have an ecosystem to go put memory products into a server, for instance, or any other platform. I think we're still early days of enabling all of this. And I also believe we're going to learn more and more where the value of this sits as we put it out there in a cost effective fashion. So I would say that people who control software environments are very, very well suited for this because they can take advantage of some of those challenges without having to have a whole ecosystem in place. I think there's going to be a continued ramp in acceleration as an industry we go build out that ecosystem. >> Well it's been amazing to watch Micron the last several years, I mean, the last several decades. When you were just a pure memory manufacturer which was diversified, you know, gorilla in this space. (laughs) You guys are really an extremely well run company. I mean, your financials have born that out. You're really transparent to the street providing great guidance and congratulations on all of the success. I'm looking forward to watching in the future. >> Oh thank you so much. It's a privilege to be part of the company, and I really appreciate your time today. >> Our pleasure, thanks for coming on theCUBE. All right, keep it right there everybody. We'll be back with our next guest right after this short break. You're watching theCUBE from Micron Insight 2018. (upbeat techno music)

>> Live from Bahrain, it's theCUBE. Covering AWS Summit Bahrain. Brought to you by Amazon Web Services. >> Hello everyone, welcome back to theCUBE's exclusive coverage live here in Bahrain. This is our exclusive coverage of Amazon's new region we're covering. Part of AWS Summit, first time here in the Middle East for theCUBE. We're excited to be here. Next guest is Tala Fakhro, Executive Director of Market and Strategy Intelligence of Bahrain's Economic Development Board, also known as the EDB. >> That's right! >> Great to see you. Thanks for coming on. >> Thanks for having me. >> I've learned so much and it was great to meet you last night and have a conversation around some of the things you are working on. The Economic Development Board is a big part of this digital first, cloud first strategy. >> That's right. >> And Amazon's at the center of it. They're going to drop a region in here. This is really big news and it's certainly got our attention. And I've learned so much about what's happening in the startup community. >> Yes, we are very-- >> You've got a lot going on. What's the impact of the AWS region mean for Bahrain, the region, and the economic development opportunity? >> We took a look at Bahrain, and we decided we are going to have to transform this economy from an oil dependent one into a digital one. It just, it seemed like the right thing to do. And having Amazon here, attracting Amazon, allows us to plant that flag to say we are serious, we want to do this. And we will do what we need to do. We, we work together as a government. You know Bahrain is unique because we can do we can do things really fast when we want to. We built the Formula One Racetrack in 14 months, which is unheard of. And we did the same for Amazon. We engaged with them at every level. It wasn't just let's talk about this plot of land here, or this fiber optic cable there. We had the government engaged in legislation, and regulation and education. Every part of the government was actively pushing for this transaction. >> And I think that's an important point. I want to just amplify and double down on that and talk about it, because I think culturally, Bahrain, what I learned was this is a culture of fast moving, open, friendly but pragmatic people. >> Absolutely. >> And that's Amazon's ethos. >> Absolutely. >> Scale, move fast, and innovate. >> Absolutely. We, we've been a trading nation all our lives since time immemorial, you know. We're a tiny little country in the middle of the map. We were cross-border trading before we knew what that was called. So this is something not unique to us. It is part of our DNA, and we found a good match with Amazon. They wanted all the same things we wanted and they are genuinely interested in making the ecosystem of the countries in which they install their regions better. And we found that to be very attractive for us. >> So I've got to ask you, as Amazon comes in they're expected to have that, this region up and running in the beginning of 2019. >> That's right. >> Which is just right around the corner, so they're running fast, so congratulations. >> Thank you. >> It's the new Formula One Racetrack for cloud computing. What is driving the demand for cloud computing? Because obviously we've seen the history of what's happened in North America with startups. >> That's right. >> And as Amazon goes around the world, there's a growth engine underneath Amazon. What's driving the demand for cloud computing in the region? >> Well, 96% by some measures of our entire economy are startups or SMEs. So you could imagine that the cost savings that Amazon offers is extremely attractive. In addition, the volatility of oil prices has put a big crunch on the government budget and so they are also attracted to the idea of saving some money on the cloud. And the government is a big employer and a big consumer. So they really drive the economy. >> Yeah. >> So in both, it was a win-win for everybody. We are really interested in making sure that our Startup scene is vibrant and is scalable. And cloud is the way to do that. It allows you to use as much as you need and pay for only what you would consume, so it's great. >> And so, Khalid Al Rumaihi, the CEO of the EDB. >> Yes. >> Who's a very good visionary. He has private sector background, super smart. Really enjoyed that conversation. But one of the things that we talked about was we always say in theCUBE and sometimes debate this, but data is the new oil. >> Absolutely. >> Couldn't be more indicative of an oil region, and you mentioned that in moving off the dependence of oil, or getting into a new market like data, data needs refineries as an economic opportunity. So he mentions, Vintech as a big driver for what could be possible in Bahrain as a core competency. When you do your research and your insight and intelligent analysis of the data of what's going on the macro level, is that consistent of what you are seeing that there's a need for this digital refinery, being a center point of innovation? And if so, what does that mean? What is, how should people understand that Bahrain is a small country in a big region? >> It is a small-- >> How do you differentiate? How do you take a leadership opportunity? >> Well, Bahrain is a small country but it is a small country that's rich in one thing. If it's not rich in oil, it's rich in its people. We are bilingual. Many of us are trilingual. We've always been open and outgoing and we've been willing to make partnerships and friends with other nations and other places. So we think that our human capital is coming together with the hard infrastructure that a region will bring. It makes it a, you know, a real good proposition. And it allows for our students, who are, by the way, already starting to be cloud trained. Over 2500 Bahrainis have signed up for cloud training since the program started six months ago. >> Yeah. >> That's a huge proportion given our population. That's a much faster rate than India or China for example. >> Yeah. >> So this shows you how much, how willing we are. You know coding is the new English. We learned English in the 70's so that we could compete globally. Now we are learning coding to do the same thing. >> And that's super important. Let's talk about the human capital side of it, 'cause I think this is a good point that a lot of people overlook. Everyone's now connected with mobile devices, so connectedness is now common. So coding is the new language. Digital is the new culture. How are you guys looking at transforming some of the day-to-day citizen roles? Because now you have opportunities to serve citizens from a government standpoint and to get enable them to be successful. And one of the things that I noticed at the Startup Bahrain sessions I was attending yesterday was the vibrant entrepreneurs. They're opinionated, which I love. 'Cause that's what entrepreneurs are. They're like, come on, let's move faster. Where's the cash? Where's the capital? So the human capital seems to be a big equation here. What are you guys doing to facilitate that? Where are you guys on the progress bar in your mind? Are people coding at a young age? Has it started? Is it, what's, what's the progress? Can you take us through the plan? >> Well we, as I mentioned, for a cloud computing, specifically we already have programs in place. We also have many other initiatives coming up through Udacity, through Carcera, through others. We are bringing them to Bahrain to have the technical skills added to the human capital skill set that we already have. But I think most importantly, we are making it important. We are making it a forefront of the government agenda. You know, we are making it something that is a requirement. And I think that as we set our national economic strategy for the next four years, human capital is a crucial driver for that and it is going to have it's very own chapter with all the recommendations and all the initiatives that we think need to be done in order to increase, not just our stem cell but also our creativity, our entrepreneurship, >> Yeah. >> And all the things that had made us great in the past. >> You know as I was observing also, talking to your CEO about, I've seen people trying to replicate Silicon Valley trying to manufacture innovation in a way or trying to get a momentum. It's really hard. But what you guys I think have done or have here that's hard to do or hard to replicate or manufacture out of thin air is you guys have actually built a community of people. I see the entrepreneurs. I see the support around them through the EDB. You have money? >> We do. >> And you have growth coming. The other stuff's mechanics. How do you get funded? How to do this? How are you looking at that? When you look at the research and you dig into, and sometimes the best move is just let it develop. Get out of the way and let the entrepreneurs develop. How are you guys letting this develop because I won't say that Bahrain has an identity crisis. I think they have an opportunity to set a new identity. >> Absolutely. >> How do you look at that? And how do you guys see that opportunity? How do you talk about it? >> Well, you can't buy innovation. I think we've proven that enough times, that government is no good at making people innovate. But what we can do is make life easier for those who want to innovate. So what we want to do is pave the way. Allow for the opportunities to be there. And then, you know, then it's every man for himself and the free market will compete. We're a very free market oriented entity and government and so all we're going to do is we're going to get out of the way. But we're going to make sure that the path is as clear as we can make it. We are going to make sure that whatever we can do to help, we will. Whether that's bringing somebody like an Amazon here, to have the people here or the Al Waha Fund which is a venture capital fund to fund, which was just launched and which is already invested in. And three or four independently managed >> Yeah. >> Venture capital funds. We feel like these kinds of things, where we're not directly funding but we are encouraging, motivating, helping, that's the role of the government. >> And I also want to just to say to the folks watching, you guys and give you guys some props, you don't just talk it, you walk it. And I think what I noticed in the sessions yesterday and meeting some of the top policy makers and the entrepreneurs was you guys are actually doing the work. >> Oh, we're trying. >> And Teresa Carlson's success in Washington D.C. with Amazon web services really is a testament that if you do the work, the results will pay off. And when Teresa came to Washington DC, Amazon Cloud Computing was like, whoa it'll never work. It is not secure. You know, now they are winning. They are doing extremely well. I've seen the model. Everyone's emulating and moving towards. You guys are doing the work. I see the check boxes. But there's still some work to do. EKYC, other things. >> Yup. >> So congratulations. >> Thank you very much. >> So the question is, what do you got done and what is to do? And what does that mean for people who want to come either work here or collaborate with Bahrain? 'Cause if you check the boxes you're going to be set up. What's the status? >> Well, the first thing we wanted to do was to make sure that the soft infrastructure was there, so we, as a government passed what we call the digital ecosystem package. So that's data protection. That's electronic transactions laws. There's a new law that's in the process that will allow people who are storing data on Amazon's region in Bahrain to bring their own laws with them. So that there are no issues with conflict of laws. >> On the compliance side? >> Exactly. >> Yeah. >> So you know, it's as if they are storing in Saudi or Kuwait. >> Yeah. >> But they are storing here. So these kinds of things, this was the first step. And we've passed a bunch of those laws and we think that they are very important. In addition, as I mentioned, we have the funding situation. We begin to look at that. We hope that with this-- >> That's a hundred million fund of funds. >> That's a hundred million dollars fund to fund. >> Fund to fund, which means that you are going to enable private sector-- >> Correct. >> And professionals to come in. >> Absolutely. People who know what they're doing, who have done it before, in the region and outside of the region, whether it's Silicon Valley or Dubai. They're going to come here and they're going to look at the Bahraini startups, and that gives us the chance to compete on the world stage and shine. And it also gives us the chance to up our game. Once you see the competition, then you can >> Yeah. >> Fix and adjust and do what you need to do. And that's what we want. We want them. We're not going to help spoonfeed them. >> Yeah. >> We're not going to give them charity. This is, you are going to compete because what we dream is that Bahrain will eventually become a global player, and we think we can do that. That's our vision. That's what we want to do, and that's where we are headed. >> So you guys are competitive? >> We have to be. (John laughing) We're a tie, we are the underdog. >> Yeah. >> But sometimes underdogs win. >> You know as I was saying also observing that, we're our first time here with theCUBE in the region. So I was noticing that, you know, we see a lot of events in Dubai. And Dubai is very blown, built, blown up now and is developed. Bahrain feels like Silicon Valley because New York is different than say, the San Francisco Bay area, Silicon Valley. But they don't have to be each other. New York is New York. Hustle, bustle. Silicon Valley is where innovation is. It feels like you guys have that same kind of-- >> We do. >> Vibe here. >> We do, and a rising tide lifts all ships. Where there's good for the Emirates and Saudi, there's also good for Bahrain. It's a region at the end of the day. We're too small to be a player on our own. But one thing I wanted to touch on, you mentioned, that, you know, with the Silicon Valley. The difference between New York and Silicon Valley is everybody knows everybody in Silicon Valley. So if you are an entrepreneur and you have a good idea, you can easily access the people that you need to access. >> Yeah. >> We think Bahrain has that advantage too. And this is-- >> Yeah. >> Clearly demonstrated in the Amazon transaction because you know at the time when we could, we had everyone from His Royal Highness, the Crown Prince on down. If we needed them, they were a phone call away. >> And people are accessible here. They're open. >> They're open. >> They're very friendly. But it's kind of, I won't say no, it's kind of no nonsense in the sense of people just want, get to the point. Right? But it's not in your face like a East Coast New York kind of thing. >> Well, we're not there yet. (John laughing) Give us time. >> All right, so back to the access to capital concept because I think first of all, we're going to open up our doors >> Yes. >> With theCUBE in Silicon Valley for you guys. So very impressive. Consider that an open invitation. But now you're talking about networks. As you built community outside of Bahrain, what are some of the things that you guys are trying to do? What does the research say to do? Is it, is there regions that you see that you need to connect through? Obviously, you want to build some communications with other groups. What's the data show for you guys? What's the sequence of execution? >> So I think what we need to do is we really need to focus on the partners that we have and enhance that relationship. But also we need to look a little bit deeper. So I think India and China are areas of interest for us as well because they are interested in this part of the world, and we need to improve our relationship with Silicon Valley. Not just giving them money. >> Yeah. >> Because everyone wants to give Silicon valley money. But we want to really learn-- >> Yeah. >> And understand what they have done, why it's worked there, why it doesn't work elsewhere, and apply some of those lessons here. >> And bring some collaborations, certainly. >> Absolutely. >> Well, people are leaving Silicon Valley and I know that most startups and growing companies have engineering teams all over the world so it's a global economy. >> Absolutely. >> Final question for you as we wrap up. What is going to attract, folks you are, or, let me rephrase that. What should companies know about Bahrain if they want to engage with you guys here and work with you, or domicile here and create a group here? >> Well first of all, they should know that they don't need to involve anyone else because they can come in and set up on their own. 100% foreign ownership is something that we have here. Where it's a very liberal economy. It's a great place to live. and that sounds facetious but it's actually really important because talent is the crucial component of every success for these companies. And people like to live here. People enjoy it. I think you'll find a welcoming environment. You'll find an environment where if you have an issue, you can raise it to the highest level very easily. >> Got it. >> And EDB is here to help with that. >> Well Tala, thank you coming on. >> Thank you. >> Tala Fakhro, Executive Director of the Bahrain Economic Development Board, the EDB. They have a website. You can engage them obviously doing great things. This is the calm before the storm. As Amazon Web Services Region gets up and running, we expect to see a lot of growth and unexpected things. >> Yeah. >> Unexpected, unintended consequences. Be careful what you wish for, Right? >> Well. >> I mean, it's coming. >> It's coming and we're waiting. >> Thanks for joining us. >> Thank you so much. >> I'm John Furrier with theCUBE. You can reach me at @furrier on Twitter. Bringing you all the action here in Bahrain for our exclusive coverage of the Amazon's new region in the area here in Bahrain and through the Middle East. Thanks for watching. Stay with us for more live coverage here at the Ritz Carlton for AWS summit in Bahrain 2018. We'll be right back. (bright music)

>> Live from Washington, D.C., it's theCUBE! Covering Inforum D.C. 2018. Brought to you by Infor. >> Good afternoon, and welcome back to the Walter Washington Convention Center, we're at Inforum 2018, here live on theCUBE, John Walls with Dave Vellante, and it's a pleasure now to welcome the CEO of Infor, Charles Phillips with us. Charles, good to see ya! >> Good to see you guys again, another year. It's great, it's great. >> Yeah, I tell ya, you are a man of demand aren't you? I mean, tell me about the week so far for you, how it's gone, and just your overall thoughts about the show? >> Yeah, it's been a fun Inforum for 2018 here. Great attendance, and a lot of energy level, and the common feedback we get is you guys just keep innovating and bringing new things, this is great, and that's why they come, they want to see what we're working on and kind of dream the art of the possible. We know what you, what we think you get a couple years ago, but if we don't have someone pushing us and painting a picture of what we could be doing, and we just think we might be missing it, so we want to hear it first hand. So that's what the conference is about, and hopefully they got that. >> Well, certainly thematically, human potential, you talk about that, you see that on the keynote stage, that's been a very consistent theme with our guests here, we've heard that a lot, you hear it down on the show floor. Talk about the theme if you would, a little bit, in terms of it's development, where that came from, and in how you think that's being expressed here this week. >> Well, we're one of the few companies that build mission critical operational systems, be it manufacturing or hospital operations, but we're also in HCM in a big way. And so we were talking to kind of both sides of the house, for some applications you're talking to the line of business manager, but for HCM you're talking to the CHRO, and rarely were those two people talking, and we saw obvious synergies. Don't you want to know how your people are doing, how to allocate people, and how they're performing, how they're changing the outcomes on a manufacturing floor or in a hospital, and a lot of HR directors weren't thinking like that because they think of HR, and they have their own world, they go to HR conferences and that's it. And the manufacturing guys are the same thing, and so we're trying to bring these two worlds together and say "Actually, you're in the same business, it's the same goals, and you actually could help each other a lot." And so by focusing on putting the employee at the center of all these applications and mapping all these operational processes to HR data, it's a different way of thinking about the role of HR. They can actually help drive the business, not just be an administrative function, and so it's resonating with a lot of the CHROs we met with, 'cause they want a seat at the table, they want to be more strategic, and this is a way for them to do that and at the same time the operational people want to know how their people are doing, want to develop talent, and want to know what are the tools out there I could be doing differently, and how am I doing, and which employees are working the best So, I think we can bring both sides together. >> So I first met Infor through AWS, at re:Invent, Pam Murphy came on, and we were like Infor? Back then it was like 2012, 2013 was kind of Infor who? And then we were invited to New Orleans, and then started to learn more about your micro-vertical strategy and a little bit about the platform, it was somewhat opaque to me. And now, fast forward last year and this year it's really starting to come in to view. The OS, the platform vision, the Birst acquisition, and of course Coleman, and I'm a sucker for platform plays especially when there's real R&D behind it that's actually having a business impact. So I wonder if you could talk about that piece of the strategy, I love the stack, was that sort of always your vision and now you're getting aggressive in it, did it sort of come together serendipitously, how'd we get here? >> Having our own stack and a platform was always the vision, but it's a lot harder to do than it sounds like, and it takes time. And so, when we arrived almost eight years ago, there were different applications, all had their own separate stacks and would say "This is not going to work." So, we need, just to be able to scale, to be able to serve multiple industries with different products, we can't have every development organization building their stack as well. So we set about taking that away from the development groups we're going to do this as a shared service, but it takes time, and as we build it you will adopt components of it. So what's changed is we've built out the entire stack, so, starting with ION, with integration, then we added document management, workflow, analytics, now AI and a lot of other services, Mongoose, platform as a service, on and on and on, in collaboration, those things took time, they're all on a single platform, federated security, single siloed across it all, and now it makes the developers job who's developing apps so much simpler. So they have Infor OS for the immediate platform, for cloud services they have AWS, I don't have to worry about any of those things anymore, just go and develop industry functionality. So, it's come together nicely, but the fact that we had the time to do it and the money to do it, and we weren't public, and we told our investors "This is the only way this is going to scale, this is the future, and it'll pay out later, you just got to trust us." And now that we've gotten there, they're seeing the synergy and go "Okay, now we see why you did that." >> So, Michael Dell's been on theCUBE many times, he used to talk about the 90 day shot clock, we obviously see what he's done in terms of transforming; but I want to talk about your business a little bit, because you've had that patient capital, I mean you're a quasi-public company in the sense that you do report so we can see the numbers on the income statement, but the income statement doesn't really tell the whole story It's about three billion in revenue, several hundred billion dollars on the balance sheet, but if you look at the SaaS component of it it looks rather small, maybe about 25% of the business, but from a booking standpoint I'm sure it's much, much larger than that. So how should we interpret the income statement in terms of the momentum in your business, where is all the action? >> So as a percentage of our sales, it's the highest of any of our competitors, so, about 70% of our new sales are on SaaS, we have about a $700 million SaaS business, so it's growing. There's nothing we can do about the maintenance piece of it, if it's related to perpetual, so if you take that out, it's a big percentage of our business. And over time the maintenance will turn into SaaS, so that's one of our big opportunities to look at that maintenance space and say "Move those over to cloud customers." and that's usually a financially lucrative thing for us to do, because we do even more for them, because they usually add on four or five other products when they move, they replace these third party products and so we get a bigger suite of products if they decide to move to the cloud. So that's part of the strategy, that's what UpgradeX is, let's move you from on-premise, so that maintenance revenue will turn into SaaS revenue, but bigger SaaS revenue over time. >> So let me make sure I understand, so it's not the classic case where you see a lot of software companies that are going from a perpetual model to a ratable model, you're goin' from a maintenance model which is ratable to a ratable model which is SaaS, but there's cohorts sales which increase the top line, is that correct? >> Exactly. So usually, because of what we do, we're doing something mission critical. So if you're going to take that, then you should do ACM financials, all the other things around it. So why would I move to core and leave the edge on-premise? So, almost by definition we have to do the whole suite. So when we do that it expands the deal, 'cause on-premise we may have been one vendor with 30 other ones existing, but the whole reason they want to get out of all of that is to move to the cloud and simplify. So we can't take all that with us, so we have to have the full suites, we've built that now. So now we can move them, but, it expands the size of the deal because we're replacing all these other products. >> Okay, and then some of the stats, just correct me if I don't get this right. Your SaaS business grown 50% faster than Oracle's, growing at a rate, I'd say 2X SAP's and a rate comparable to Workday, are those correct figures? >> Those are correct, and profitable. >> Oh, and profitable. >> Throw that in. (all laugh) >> Right, so okay. And then last year Koch Industries invested, so you kind of recap the company, you've made a big deal about that. One of the things that we've noted is you're seeing a tailwind there in terms of guys like Accenture and Capgemini, we've asked them "Do you guys service Koch Industries?" they said "Yep!" they helped us see the opportunity, and they said "Look, look for something substantive, we're not going to try to force you to do something, but we want you to take a look." So that's been helpful. Talk about that and maybe other things Koch has brought to the table? >> It's a, the relationship with the integrators is evolving, it probably was not a plus for us in the first four, five years. More recent years we've won enough deals where they had to say "Okay, we can't keep losin' these deals." And where they wanted to get engaged. Koch helped, because they had relationships and they wanted to run that business, that's why they're implementing our products globally, and so, they're a large customer for all of these guys, and one of the largest for Deloitte for instance, but what's really more-- that helped, but it was more the, what was happening in the market, the fact that we're in a Liberty Steel and replace SAP, or that we're in a Travis Perkins interview with SAP and Microsoft, so, if you're on the wrong side of those deals enough times your manager starts to ask you what's goin' on, and you got all these people on the bench here, okay, we train them for Infor if they're winning in that region, or in that industry. So, we just had to earn our way into it, our initial strategy was not one that, at least on the surface, looked like it was integrator-friendly because we were trying to take all those mods they like to do and put 'em in the product, and that's the whole thesis, let's the take the vertical industry features and let's put it in there once, I don't want everybody customizing my apps, we do that. And so now they've had to move up, okay we can do other things, configuration, changed management, there's AI, there's other things you can do, but you're not going to do that. So now that they've accepted that, there's a basis for us to work together, and, it just had to take time to get there. >> What can you tell us about where you want to go with this? I mean you've presided over public companies before, you know that business well, you were a rockstar analyst, is there an advantage to being a public company, is that something that you eventually want to do? >> I would say there are pluses and minuses, our board is evaluating that, that's going to be their call. The upside is, it would solve probably our biggest challenge which is brand recognition, almost instantly, because would be a top 10 tech IPO. It makes it a little easier to hire people because they can see public currency, they can value more quickly, and it gives you some acquisition currency; so those are the positives. But then you're on the 90 day cycle, and we're kind of on that anyway, 'cause we report publicly and we have publicly traded bonds. So for us it's, in some sense we have the worst of all worlds, right? We have the discipline of being a public company, and the scrutiny, without the capital, (laughs) and the branding, so. I think that's what everybody's evaluating. Every bank on Wall Street's visiting us telling us to go now, the window's great, you have the numbers. >> Oh, of course. (Dave and John laugh) >> And so, so we could do it, I just don't know what their decision's going to be. The advantages to being private as well, you have a little more flexibility obviously, and, we don't need the capital, we have plenty of capital coming from Koch and others who want to invest. >> Well, the flip side of that too, is you get to write your own narrative, right? >> Yeah. >> I mean, we're talkin' about the nuances of the income statement, the Street is obviously right now hooked on growth heroin, and if you got the transition in the base it doesn't become a tailwind, so, no rush from that standpoint. I want to pivot to the theme of this event, which is the human potential. My understanding is you sort of were instrumental in coming up with that. HCM this year got a big play on stage, where's that come from? >> Yeah, just as I talk to CEOs who are struggling to find talent, like I mentioned on stage 6.7 million jobs that are unfulfilled. It's not like we don't have people here, we have people here with their own skills, so, you're not going to fill those jobs any other way, we're not doing immigration to any degree and scaling more, that's been shut down. We have an aging population with the baby boomers, so the most logical thing that you would do is train people who are already here who want to work. And, let's take people who have jobs that they probably aren't thrilled about, and give them different skills so they can fill these 6.7 million jobs. So to do that, you have to make these applications easier to use, and I felt like we're probably in the best position to do it because we actually know what they do for a living, 'cause we wrote all those last features in those industries, we understand what they do. And if you're just doin' HR replication or financials, you actually have no idea what they do. So, we had to learn those jobs to automate those jobs, so we can find ways to use our HCM applications to better train people, professional development, coaching, take all these HR skills, and put them as part of the applications in the context of while you're working. >> We had Anne Benedict on just a little bit ago talking about really a test case that you can be for yourself. So how are you putting these things to practice yourself, and how are you working out maybe some kinks before you take them out to somebody else? And so, you can leverage your own success for your own success, and also learn from mistakes too I would think. >> We do. So we have this program called Infor at Infor, where everything we do, we want it to be on an Infor product, which was not the case when we arrived. Like a lot of companies, a mish mash of different things, and so we've implemented not only HR Financials of course, Birst, but the big innovation has really been talent science, that every employee we hire has to take that test, and all the executives have taken it as well. And what we've discovered is, is that, when people hire and go against the talent science recommendation, 68% of the time they end up being wrong. So it's better at judging people than people are sometimes, and you can't use it exclusively, but it'll tell you these are the things you should look into, some questions you might want to ask, here's how they rate on certain skillsets, they're very well meshed for this job, they look like they'd see their best performance in this area, but ask these questions. And so people don't know how to interview and how to think about this, and so, having a guide to go into an interview is actually pretty helpful. We hire much better people now by using that. >> So it's like StrengthsFinder in a way? >> No, it's different from that, this is AI, it's kind of Moneyball for business people. >> Well you're talking about that today, almost there. >> Yeah so it's 39 personality attributes, behavioral attributes we call them, so, empathy, resistance to authority, do you have the ambition or not, and depending on the job, you think all those things are good, depends on the job, so. For some jobs, it's actually better to have low ambition because, a lot of our customers who have low wage, fast food service jobs, people who have ambition are going to leave in four months, right? They're not going to stay, so, okay we're not going to be here long, at least know that going in, and know who wants to get promoted, and other people are fine with it. And so it depends on the mix of skills, just like I said, 39 attributes, and for that job role, you tune it to the people who like that job, they look like this. And, we've also found that it's 60% more diverse when you hire using science, because you don't know that when you're looking at the data, what they look like. >> It must've been super interesting getting those reports. You took it, obviously right? >> Yeah I took it. >> How'd you do? (laughs) >> Uhhh, nobody really likes their profile. (all laugh) >> I was going to say, I imagine I would be really defensive about this, oh I don't know. >> This can't be right! >> That is not me! I am not like that! (all laughing) >> Every person on our executive team said the same thing so. That's what it's for is to, you have certain perceptions even about yourself, and it calls it out, right? And there's no gaming the system because the questions have no right or wrong answer, it just puts you in scenarios that you answer what would you do, how do you feel about this? You're not clear what they're trying to get at, and you only have 27 minutes or 22 minutes to do the test. >> So you can't game it? >> You can't game it. >> Data doesn't lie! >> And we built the science, we know when someones trying to game it, they're taking to long on multiples, and changing their answers too much, so it's-- And we've now, I think we've tested some 200 million people over time, over years, so we have 20 years of data about people. >> That's, I mean, sounds unique, certainly unique of being infused into enterprise software, I've not seen anything like this from another enterprise software company. Can you confirm that, or? >> Yeah, so, we're the only ones that do this at scale, there's a few startups trying to do it, but they're trying to do it all facial recognition which is, we think pretty ridiculous, we're trying to get away from physical attributes not use that. So there's a company out there doing that, depending on your facial movements, but this is, we're eliciting responses about your personality in response to situations that we give you, and have a bunch of scientists that crunch the data and they basically shape it to the job role. And they test your best performance, and you get a DNA profile for your best performance for that job role, and then, that's what you're matching, and it's highly accurate. So we had a company on the Las Vegas Strip use it, because they have to hire in volume a lot, and essentially what they wanted to do was get better blackjack dealers. You need somebody that's good at math, good under pressure, not too emotive, don't give away anything; and so we did that, fine tuned the test, they call us back nine months later and said "We need you to change the test." We said "We did exactly what you wanted, what happened?" He said well, the winnings went up 30%, but everybody's leaving the hotel in 24 hours 'cause they lost all their money, so we don't need them to be that good. (all laugh) >> Dial it down a little bit. >> Which we did. And so that's part of the service is we fine tune it, you tell us what your goals are, and we'll tune to that. >> That's a great story. The other surprise for me this week has been the emphasis on robotic process automation, it's a space that we've kina looked at. And a lot of people are scared about software robots replacing humans, but if you talk to people who are using RPA, they love it. It's taking away these mundane tasks, I didn't realize that you guys had such capabilities there? >> Yeah, so we built that as part of a Coleman RPA platform, and not only can we automate and use RPA for ourselves, but we've built a whole development environment for our customers to build their own, 'cause we can't think of every process that they might want to automate, and we gave that platform to our partners as well, so. We don't want them doing database schema work anymore, and they used to get paid for that, there's other things you can do up the stack in AI, here's what we want you to focus on. So we had that meeting on Monday with the partners, and they all agreed that's what we're going to do. But there's tons of mundane things that people shouldn't be spending time on, and they can be much more productive, it makes them more loyal to the company, they're enjoying their job more, and they're thinking and innovating more. So I don't see it as replacing people, as making people better. And giving that engagement that I talked about during the keynote, they're engaged now, because they can do things that are more value adding now. >> So, back to New Orleans next year? That's the first Inforum that theCUBE was ever at was in N'Orleans, and, jazz, you like jazz, obviously, right? >> I like jazz, I met with the mayor when I was down there, Mitch Landrieu at the time, and he became a customer after that meeting, so the city of New Orleans runs on Infor software, it's another reason to go there; so thank you. >> You've get--nice. >> Yeah, thank you Mitch, so that worked well. And so as a thank you we're going back down there, they're a big customer now, and it's always fun, you know what I mean, you know. >> That's great. >> Just, before you go, you mention, I watched in the keynote this morning, Brooks Koepka. >> Yes. So you're working with him. I do a little bit of work on the golf side as well, so I was just intrigued because, he's not the, well he's not Tiger, right? >> Yeah. >> U.S. Open Champion, twice over. What was the attraction to him, and then can you play in the golf world a little bit, and with those brands, and is that an entry into that world? >> Well, we always like to bet on the scrappy guy, the next up and coming generation guy, and that's kind of our brand that's what we are, the Brooklyn Nets, someone who's not quite there yet, but they're moving up, that's kind of our scrappiness, that's why we like the whole Brooklyn image as well. And we started talkin' to him, like I said, before he won the U.S. Open, because he was ranking pretty high, moving up, but wasn't well known. A quite guy, very personable when you meet him, we thought he'd be good in front of clients, let's bet on his career, and we're going to work with him; and literally three weeks later he wins the U.S. Open, we go "Okay." (all laugh) >> Good grab! >> We'll take it! (laughs) So, we didn't even think it'd happen that quickly, and now he's a rockstar so. We were planning on hosting a CX event with him, and, we're not sure how many people are going to come, but when that happened, now, everybody RSVP'd right away of course. So now it's doing exactly what we wanted. >> Do you play golf? >> I don't play golf, I just started playing, 'cause we were doing these golf tournaments with customers over the last year, but I haven't had enough time to get out there yet. >> I'll bet Brooks would give you a lesson or two. (laughs) >> Yeah, he, a lot of people want to lesson from him. >> Charles thank you >> Alright, thank you guys, >> for the time, great show. >> Good to see ya again. See ya in New Orleans. >> Thank you, yeah. >> Congratulations. >> Alright guys, see ya. >> Wonderful week here in Washington, D.C. Back with more live on theCUBE here from D.C. right after this. (bubbly music)

>> Live from Washington DC, it's theCUBE, covering Inforum DC 2018, brought to you by Infor. >> Well, good morning. Welcome back here on theCUBE. We are live in Washington DC, at Inforum 2018. You can tell, Infor's just over the shoulder here. We're on top of the show floor, looking down, and a lot of buzz, a lot of activity out there. Good to be a part of that excitement here in DC. I'm John Walls, along with Dave Vellante, and we're joined by, he said, "Just call me Soma." Soma Somasundaram, who's the CTO at Infor. Soma, good job on the keynote stage this morning. Thanks for joining, appreciate that. >> Yeah, and yesterday. >> Yup, yup, thanks. >> So, talk about a couple of new products, one launched, one in beta. Why don't you go ahead and tell our audience a little bit about that, about what you're bringing to the marketplace now? >> Yeah, so, you know, we have, you know, as I mentioned in today's keynote, we're all about product innovation, and we're engineers. Charles is an engineer, I'm an engineer, and we're constantly driving new innovation. So, some of the innovation, there's fundamentally, we want to build what I would call a shared services platform that all of our cloud suites can utilize. There's no need for each of the applications to go reinvent the wheel to build a middleware, or a data lake, or an API layer, so we built a shared services platform, which is what we called Infor OS. As part of Infor OS, we continued to release new things. You heard today, we released something called Infor Go. As the name might suggest, the idea is that you as an employee in one of the customer organizations, you want to have, easily go to the app store, download something called Infor Go, it automatically is configured for your role. It gives you, if let's say you're a salesperson, it gives you access to CRM data, to curate your pipeline, it gives you access to employee data, because you're an employee of the organization, gives you ability to file expense reports, because you're a traveler. You get the idea. So, in a role, you don't want to be dealing with 20 different apps. It's just one thing. You just go in, one sign on, you get access to everything you need. That's one announcement we made. That's on the technology side. And on the functional side, you know, we launched a new CRM this morning, and the idea there again is that, we're in the CRM business not to build a horizontal CRM. Our idea is, you build, anything you do must be industry-specific, right? When you are selling and servicing an excavator, and you are a dealer of moving equipment, you want to know what kind of configuration installed, what kind of accessories I can sell to this farmer, what kind of terrain they're operating on. That is industry-specific. So to us, that is important. That's what we're doing with CRM. We built it on obviously our own platform, technology platform, multi-tenant, running in the cloud, but the main differentiation is industry, right? So that's something we announced. We've been on building a next generation HCM suite, which we talked about a lot yesterday. The final piece of that is payroll, which is important. So that payroll, which just went beta this morning. It's all built on the exact same platform, with Infor OS, multi-tenant, and it's highly extensible, so that completes our HCM suite on a unified platform. Those were the announcements we made today. >> So I wanted to talk a little bit about the platform. So last year, after Inforum 17, I wrote a blog post, and I put up the strategy and technology stack, and I kind of missed the OS underneath. So we'll come back and maybe course-correct that. But one of the problems with enterprise software, especially suites, is there are a lot of cul-de-sacs. You go down a road, and then you hit a dead end, and then you have to come all the way back, and if you want some other function, you have to go down and come all the way back, and it's a very frustrating user experience. So, I'm inferring that what you guys have done is try to address that and other problems with a platform approach. So a platform, in my view, beats products. So maybe talk about platform and what that means to you guys, and then I would love to get into the sort of conceptual and actual stack. >> Yeah, so, it is what should be common sense, in my opinion, that if you buy a HCM suite from a provider of software, you buy ERP from that same provider, you buy travel and expense application from the same provider. You would think that they all have the same user experience, and are integrated out of the box, they all seamlessly work together, with single sign-on. That would be a normal expectation as a customer, I would think, but unfortunately, the market's not going that way, right? Everybody's got their own, even within one company, you have multiple products, they don't work together well. Our idea is that if you buy an industry cloud suite, you must feel like it came from Infor, it all should have one single user experience, it all should work together as an integrated suite, it should all be sharing data for analytics, and so on and so forth. So that is the whole idea behind building this Infor OS. So, Infor OS has got several services underneath, starting with, you know, user experience, which is developing a hook and loop. So we have all of the controls, whether it's a dropdown box, or a grid control, or date picker, they all behave exactly the same way. Whether you're in CRM, or HCM, or inside a purchasing application, they all work the same, right? So, starting with that, then you go-- >> So if I can interrupt, so the Infor OS has the core services that you need, that the software needs to access for any function that you're building, correct? >> Exactly, yeah, yeah. >> Okay, please. >> So it's user experience, then you have integration. We have one integration layer called ION, and ION supports both an API layer, if you want to build a mobile app, you need APIs into the software, so built a lot of APIs into our applications. Those are exposed through a single gateway. There's one way to get into Infor applications through this API layer. We built that as part of Infor OS. We also built Coleman, which we announced last year. Coleman depends on two things. One, a lot of access to data, so I can crunch and do machine learning, and a lot of access to APIs. So what if you could create an acquisition, tucked into a device, versus having to open up a form, right? To do that, you need APIs. If you can order Domino's pizza from home, using Alexa, why can't you do that at work? So we built this framework for those kind of things. So it's got APIs, it's got Coleman, it's got data lake. So all of this data is in one place, so you can build analytics. We have Birst, which sits on top of the data lake, and I can go on. So that's really what we're doing with Infor OS. It's really, that's very, very important. It's not like your Intel Inside kind of thing. Without Infor OS, Infor apps don't work. >> So, if I can, if you bear with me, just to conceptualize the stack, the OS is at the bottom layer, and then you've got your micro-vertical functions as sort of the next layer, and then the cloud, which is really AWS, is the cloud infrastructure, then you've got the GT Nexus, essentially, the network commerce platform, so all those data and supply chain connection points that you have access to, Birst, the analytics, which was in acquisition last year, and then the Coleman AI completes the stack. My question is, as it relates to, for instance, Birst, that was an acquisition. So, you have to bring that in and do some engineering work to make it fit into the stack, is that right, or is it just kind of bolted on? >> No, you know, so, everything has to be done with the conscious way of design, right, so it just doesn't happen by itself. So, Birst is a fantastic world-class analytics platform, right? They as a company built a world-class platform that allows for department analytics, so if you're working in sales or working in marketing, you can go bring your own data, you can do analytics. It's great at that. At the same time, it's great at enterprise analytics, where you have all of this data in one place, you harmonize the data and do that. As a platform, it's a fantastic platform, but we're about delivering content on top of that platform, so we need to bring the network data, like you said, we need to bring the industry data, we need to bring the employee data from HCM. Bringing it all together and exposing that using Birst as the visualization layer is how we are exposing it. So to that extent, Birst was connected into the data lake, and it sits on top of the data lake, leverages that data. We built a semantic layer, which reflects the model of data that we have in the data lake, so yeah, it does, and we have the single sign-on, so it actually surfaces within Ming.le, within the homepage of a purchasing manager or whoever, and that's work, that's what we did. >> So you essentially re-platformed it. So of course, part of the due diligence is how challenging it's going to be to do that, how fast you can get that to market, but this is complicated. It requires a significant engineering resource on Infor's part. We talked about this a little bit at the analyst meeting last year, the industry analyst session. Couple things, one is the integration and exploitation of AWS cloud, and all the services there, the data pipelines, and the services there, but also modern software development. You know, microservices, and containers, and all of that good stuff. Can you talk about those sort of two dimension and any other points that you'd like to emphasize in terms of the things that Infor developers are doing to create this modern platform? >> Yeah, so, first of all, you know, we are all about applications, right, so we're not building databases, we're not building our own data centers, we're not building our own operating systems. We're a business software application company. Our belief is that if you try to verticalize and try to innovate on every single layer of what you do, it stifles innovation. Why not embrace industry's innovation, right? Can we out-spend AWS, in terms of building a cloud infrastructure? I don't think so. >> No way. >> No one can. And so, it's important to focus on what you do best, and leverage innovation that's coming in outside the four walls of Infor, to embrace that to deliver what the customer requires. So, what we really did is we took the AWS services, and we encapsulated them into our application, so when the application does disaster recovery, it's actually AWS services, right? When we call Elasticsearch, we're using AWS services there. We use DynamoDB for graphing the data in the data lake. Much like Facebook works on Open Graph, of trying to find people who are connected to each other, data inside the data lake is connected, right? Sales order is connected to a sales person. It's connected to a customer. Customer is connected to returns, and so on and so forth, so, we've done those kind of things. So, we've built a layer above the web services of AWS to actually create hooks into the application that leverages that, and we built our application itself in a sort of a microservices architecture. Granular APIs is a better way to describe how we did it, so that those granular APIs can be used in a digital project to create your own mobile app. It's the same APIs that are used in Coleman, for our digital assistant, or chat bots. All of those things require clear thought in terms of design, how you expose the functionality, and how you expose data, and that's what we did. >> Yeah, so, as a developer, in an engineering organization, having access to those primitives, those granular APIs, gives you what, greater flexibility, if the market turns, you can turn more quickly. I mean, it's more complicated, right, but it gives you finer grain control. Is that fair? >> Absolutely the case, yeah, and by the way, we know that the world is heterogeneous, right? I would love for a customer organization to just use Infor for everything, nothing else, right? But that's probably not realistic. So we built this to be able to work in a heterogeneous environment. So creating APIs and having this loosely-coupled architecture allows for that to happen. Ultimately, the customer has a choice. We obviously have to work to earn their business, but if they have other things outside of Infor that they're running in their ecosystem, you need to be able to embrace that. So this architecture actually allows for that. >> So it's the architecture, but if you're saying, if I'm a customer, and I want to run in the Google cloud, or Azure, technically, at least in theory, you can support that, but do you actually do that today, or is that sort of roadmap stuff? >> Technically, you could do that, right, but we obviously leveraged a lot of AWS services in our stack. What I meant to say in heterogeneity is that if you run a non-Infor application, right, so like, Salesforce for CRM, right? I would love for the customer to use Infor CRM, 'cause we think we are very competitive, but if they are running Salesforce, and they don't want to replace that, we need to be able to work in that environment, where it's running in a different cloud, it's running in a different architecture. So, we built Infor OS and the layer to be able to deal with that kind of hybrid deployments. >> Technically, what's the enabler there? Is it just sort of an API-based framework, or... >> It is API-based framework. It's also got federated security built into it. It's got the middleware understands, ION understands that data could come from a non-Infor system. As long as you're talking, you know, you go to United Nations, if everybody there has a headset, to really translate what anyone is saying, versus if everyone speaks English, well, world would be wonderful. >> But they spoke English yesterday. (John laughs) >> I got one more, I got one more geeky question. Anytime I get the head of engineering, you know, the CTO-- >> You love this. >> We love to get into it. The audience eats the stuff up. >> Yes. >> And we love the business talk too. But, I've heard a lot about multi-tenant architecture. My friends at servers now make a big deal about multi-instance, saying, oh, and I don't know if it's, if it can't fix a feature kind of thing, or if there's really, you know, additional value there, but the claim is it's more secure. Multi-tenant, I think conceptually, is certainly more cost-effective. What's your take on sort of multi-tenant? Why is it important? Maybe discuss the security levels that you guys engineer in, your comments. >> Yeah, yeah, if you have something that you can call it a feature, you can, like you said, but our belief is that multi-tenant architecture allows for faster innovation, easier update to the customer, to keep them current, and you know, you think about having thousands of individual instances that you have to update, on a weekly basis, because we will get to a weekly update. We are currently doing monthly update, and we get to a weekly update. That requires a natural act to create automation to be able to update all of them. I mean, there's, you know, you could argue which is really more pure, but multi-tenant architecture for us is one single application server farm that is able to work for different tenants, understanding their configuration, their business process, and operate the way they want it to be operated, but it is running in one single farm, that we can update as frequently as we need, without obviously causing disruption, so that is, I think is a good design scenario. Having said that, we actually isolate the data of a tenant, right, because you could have a scenario where all tenants' data is in one database. We don't do that. We actually insulate tenants so that data is not permeable. You can't go across tenants. So, we think that this is an elegant way to architect and keep it agile, and we can bring innovation faster to the customer. >> So when you go from monthly to weekly, to daily, to hourly, to minutely. Every customer comes with you, whereas in the multi-instance world, you actually have to plan for it. You've got to plan the migration. You're maybe N minus one, or maybe even N minus two, if that's supported, and it's more disruptive. >> That's correct. >> Okay, and then, you've got to engineer, you know, the security, and other factors. Thank you for that explanation. >> So, I always like to get back to, at the end of the day, you know, what are folks doing with what you're providing them, right? So, in kind of like your new services world, your new product world, what are some of the more, I guess, unique ways in which your customers are putting these great tools that you have to work for them, that you would like to use as kind of the poster child of success, and say, you know, we're providing this new value and these new enhancements, and give you the chance to take it to others, and use them as examples? >> Yeah, so, fundamentally, I'll be remiss if I don't start with the industry, right? So, it may not be very sexy, but ultimately, if I'm in a food and beverage industry, I really need to have a piece of software that understands that, right? Like for example, if you're an ice cream plant, you pay by part of a carton, you don't pay for the gallons of milk you get, right, so, does the software understand that? Right, if it don't, then you have to work around it, right? So, it may not sound sexy, but that's important to us, right? So, customers deploy without customization is very, very important for us. That's why we call it last man functionality. But if you flip to the technology side of things, I think that we're just scratching the surface in terms of what users want to do with Coleman. Coleman digital assistant, for example, like I earlier said about placing an acquisition target into a device. I think our idea is that every single employee of our customer organization should be using technology. Typical ERP, as it was deployed 20 years ago, only power users used it, right? Other people wrote on a piece of paper and sent it around. >> Same thing with decision support. There was like, three guys, two guys in the company who knew it. You had to go ask them to build a cube for you. >> Exactly. That doesn't scale, exactly. And we're living in a very diverse, global sort of set up. It doesn't work if you have three people who understand how to do BI, you know, two people who can create work flows, and I always like to use this example of this website called ifttt.com. I don't know if you've tried this or not. It literally stands for if this, then that. If I can go and describe something, and if this happens, then do that. Why can't we do that in enterprise software, right? Why is it that you have to go to knock on the door of IT to do it? So our idea is to bring that level of innovation, so we can innovate, our partners can innovate, customers can innovate, we don't step on each other. >> I got to ask you about a topic that we've heard a lot about this week, is robotic process automation, and you guys have essentially intimated, or at least, I've inferred that you've got quite a bit of capabilities in that regard. We're talking about software robots here, essentially, to replace sort of humans doing mundane tasks, or maybe augment humans. What is the capability that you have with RPA? Is it something that you're shipping today, and I have some follow up questions, if I may. >> Yeah, so, we built ION when we started building this years ago. We built it with the notion of build it on a data-rich architecture, right? What I mean by that is when something happens, an event happens in an application, a sales order is taken, or it's updated, give me a full copy of that document, that anyone can understand, right? That is a foundation of what you need to be able to externalize things like RPA. So we have access to the document as things happen. That's point number one. Point number two is that we built the Coleman AI platform, which we talked about earlier today. That actually leverages that workflow, as points in the workflow, to be able to go and do AI-based services that are hooks that are there in the workflow. So, where human beings need to intervene, I give an easy example. How often, like, there are people reporting to you, I do, and we get expense reports that people submit. First of all, I don't even look at them, Michelle looks at them, and do you think she opens and actually looks at how much somebody spent for dinner? No, you just push the button and approve. Why are we doing that, right? Why can't a robot figure out is there something that looks not quite right, then flag it, versus having to do this mundane work? So why can't Coleman do that? That's the way we've done it, and it's because we have a workflow engine, we have the API architecture, we have an AI platform, it's easy to wire these things together and having data externalized allows us to do that. >> So, in looking at the RPA market, there's several companies out there, and a lot of software companies, many of which are very, very complicated. You can't get your hands on the software. There is some, or maybe one in particular, it's easy, you download it, and it's low code or even no code, so I would imagine, I'm envisioning some kind of studio for a user like myself, who can, you know, is not technical, who can use it, and then maybe some kind of orchestrator, to be able to actually effect what I want done to get done. Is that something that you're shipping today, or how do I do it, as a user, and is it low code or no code? >> As an end user, if you are trying to figure out, yeah, I'll go to them to deploy, then obviously, you need a data scientist, okay? So, that part of it, we have a platform that is available for the data scientist, to be able to go look at the data, curate the data set, allow them to deploy different algorithms to figure out which one work, is the right for certain, then deploy that, and when you say deploy, it automatically creates an API, and allows for use anywhere. From an end user standpoint, like I said, this ifttt.com, you should be able to go in and say, set up your own alerts, that if I see, if you see, you know, X, Y, Z happen, let me know, or if I see X, Y, Z happen, you know, do this. So that part of capability exists in the platform, right? So, you can't completely replace data science and everything with the real end user doing it, but if you package the services in such a way that an end user can actually pick and choose and deploy, that can be done today. >> Your expense report, or approval example, and there are many, many others, so, are great, thank you for great. >> Soma, thank you, for the time too. We appreciate that. Thanks for dropping in, and again, great job on the keynote stage, and wish you success down the road here. >> Thanks a lot, appreciate it. >> I don't think you need it, though, I think you've got your, your act together really well. >> And your hands full. >> Yes, you do. A lot going on. All right, back with more here. We're live in Washington DC. You're watching theCUBE.

>> 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)

>> Announcer: Live from the Javits Center in New York City, it's theCUBE. Covering Inforum 2017. Brought to you buy Infor. >> Welcome back to Inforum 2017 everybody. This is theCUBE, the leader in live tech coverage. Duncan Angove is here, the President of Infor and a Cube alum. Good to see you again Duncan. >> Hey, afternoon guys. >> So it's all coming together right? When we first met you guys down in New Orleans, we were sort of unpacking, trying to squint through what the strategy is. Now we call it the layer cake, we were talking about off camera, really starting to be cohesive. But set up sort of what's been going on at Infor. How are you feeling? What the vibe is like? >> Yeah it's been an amazing journey over the last six years. And, um, you know, all the investments we put in products, as you know, we said to you guys way back then, we've always put products at the center. Our belief is that if you put innovation and dramatic amounts of investment in the core product, everything else ends up taking care of itself. And we put our money where our mouth was. You know, we're a private company, so we can be fairly aggressive on the level of investment we put into R&D and it's increased double digit every single year. And I think the results you've seen over the last two years, in terms of our financials is that, you know the market's voting in a way that we're growing double digits dramatically faster than our peers. So that feels pretty good. >> So Jim is, I know, dying to get into the AI piece, but lets work our way up that sort of strategy layer cake with an individual had a lot to do with that. So you know, you guys started with the decision of Micro-verticals and you know the interesting thing to us is you're starting to see some of the big SI's join in. And I always joke, that they love to eat at the trough. But you took a lot of the food away by doing that last mile. >> Yeah. >> But now you're seeing them come in, why is that? >> You know I think the whole industry is evolving. And the roles that different and the valor that different companies in that ecosystem play, whether it's an enterprise software vendor or it's a systems integrator. Everything's changing. I mean, The Cloud was a big part of that. That took away tasks that you would sometimes see a systems integrator doing. As larger companies started to build more completely integrated suites, that took away the notion that you need a systems integrator to plug all those pieces together. And then the last piece for us was all of the modifications that were done to those suites of software to cover off gaps in industry functionality or gaps in localizations for a country, should be done inside the software. And you can only do that if you have a deep focus, by industry on going super, super deep at a rapid rate on covering out what we call these last malfeatures. So that means that the role of the systems integrators shifted. I mean they've obviously pivoted more recently into a digital realm. They've all acquired digital agencies. And having to adapt to this world where you have these suites of software that run in The Cloud that don't need as much integration or as much customization. So we were there you know five, six years ago. They weren't quite there. It was still part of this symbiotic relationship with other large vendors. And I think now, you know, the reason for the first time we've got guys like Accenture, and Deloitte, and Capgemini, and Grant Thornton here, is that they see that. And their business model's evolved. And you know those guys obviously like to be where they can win business and like to build practices around companies they see winning business. So the results we've seen and the growth we've seen over the last two to three years, obviously that's something they want a piece of. So I think it's going to work out. >> Alright so Jim, you're going to have to bear with me a second 'cause I want to keep going up the stack. So the second big milestone decision was AWS. >> Duncan: Yeah. >> And we all understand the benefits of AWS. But there's two sides to that cone and one is, when you show your architectural diagram, there's a lot of AWS in there. There's S3, there's DynamoDB, I think I saw Kinesis in there. I'm sure there's some Ec2 and other things. And it just allows you to focus on what you do best. At the same time, you're getting an increasingly complex data pipeline and ensuring end-to-end performance has to be technically, a real challenge for you. So, I wanted to ask you about that and see if you could comment and how you're managing that. >> Yeah so, I mean obviously, we were one of the first guys to actually go all in on Amazon as a Cloud delivery platform. And obviously others now have followed. But we're still one of their top five ISV's on there. The only company that Amazon reps actually get compensated on. And it's a two way relationship right? We're not just using them as a Cloud delivery partner. We're also using some of their components. You know you talked about some of their data storage components. We're also leverage them for AI which we'll get into in a second. But it's a two way relationship. You know, they run our asset management facility for all of their data centers globally. We do all the design and manufacturing of their drones and robots. We're partnered with them on the logistic side. So it's a deep two way relationship. But to get to your question on just sort of the volume and the integration. We work in integrations with staggering volumes right? I mean, retail, you're dealing with billions and billions of data points. And we'll probably get into that in a second you know. The whole asset management space, is one of the fastest growing applications we have. Driven by cycle dynamics of IoT and explosion in device data and all of that. So we've had for a very, very long time, had to figure out an efficient way to move large amounts of data that can be highly chatty. And do it in an efficient way. And sometimes it's less about the pipes in moving it around, it's how you ingest that data into the right technology from a data storage perspective. Ingest it and then turn it into insights that can power analytics or feed back into our applications to drive execution. Whether it's us predicting maintenance failure on a pump and then feeding that back into asset management to create a work order and schedule an engineer on it. Right? >> That's not a trivial calculus. Okay, now we're starting to get into Jim's wheelhouse, which is, you call it, I think you call it the "Age of Network Intelligence". And that's the GT Nexus acquisition. >> Yeah. >> To us it's all about the data. I think you said 18 years of transaction history there. So, talk about that layer and then we'll really get into the data the burst piece and then of course the AI. >> Yeah, so there were two parts to why we called it "The Age of Network Intelligence". And it's not often that technology or an idea comes along in human history that actually bends the curve of progress right? And I think that we said it on stage, the steam engine was one of those and it lead to the combustion engine, it lead to electricity and it lead to the internet and the mobile phone and it all kind of went. Of course it was invented by a British man, an Englishman you know? That doesn't happen very often right? Where it does that. And our belief is that the rise of networks, coupled with the rise of artificial intelligence, those two things together will have the same impact on society and mankind. And it's bigger than Infor and bigger than enterprise software, it's going to change everything. And it's not going to do it in a linear way. It's going to be exponential. So the network part of that for us, from an Infor perspective was, yes it was about the commerce network, which was GT Nexus, and the belief that almost every process you have inside an enterprise at some point has to leave the enterprise. You have to work with someone else, a supplier or a customer. But ERP's in general, were designed to automate everything inside the four walls. So our belief was that you should extend that and encompass an entire network. And that's obviously what the GT Nexus guys spent 18 years building was this idea of this logistics network and this network where you can actually conduct trade and commerce. They do over 500 billion dollars a year on that network. And we believe, and we've announced this as network CloudSuites, that those two worlds will blur. Right? That ultimately, CloudSuites will run completely nakedly on the network. And that gives you some very, very interesting information models and the parallel we always give is like a Linkedin or a Facebook. On Linkedin, there's one version of the application. Right? There's one information model where everyone's contact information is. Everyone's details about who they are is stored. It's not stored in all these disparate systems that need to be synchronized constantly. Right? It's all in one. And that's the power of GT Nexus and the commerce network, is that we have this one information model for the entire supply chain. And now, when you move the CloudSuite on top of that, it's like this one plus one is five. It's a very, very powerful idea. >> Alright Jim, chime in here, because you and I both excited about the burst when we dug into that a little bit. >> Yes. >> Quite impressed actually. Not lightweight vis, you know? It's not all sort of BI. >> Well the next generation of analytics, decision support analytics that infuse and inform and optimize transactions. In a distributed value chain. And so for the burst is a fairly strong team, you've got Brad Peters who was on the keynote yesterday, and of course did the pre-briefing for the analyst community the day before. I think it's really exciting, the Coleman strategy is really an ongoing initiative of course. First of all, on the competitive front, all of your top competitors in this very, I call it a war of attrition in ERP. SAP, Oracle and Microsoft have all made major investments on going in AI across their portfolios. With a specific focus on informing and infusing their respective ERP offerings. But what I conceived from what Infor's announced with the Coleman strategy, is that yours is far more comprehensive in terms of taking it across your entire portfolio, in a fairly accelerated fashion. I mean, you've already begun to incorporate, Coleman's already embedded in several of your vertical applications. First question I have for you Duncan, as I was looking through all the discussions around Coleman, when will this process be complete in terms of, "Colemanizing", is my term? "Colemanizing" the entire CloudSuite and of course network CloudSuite portfolio. That's a huge portfolio. And it's like you got fresh funding, a lot of it, from Koch industries. To what extent can, at what point in the next year or two, can most Infor customers have the confidence that their cloud applications are "Colemanized"? And then when will, if ever, Coleman AI technology be made available to those customers who are using your premises based software packages? >> So yeah, we could spend a long time talking about this. The thing about Coleman and RAI and machine learning capabilities is that we've been at work on it for a while. And you know we created the dynamic science labs. Our team of 65 Ph.D.'s based up in M.I.T. got over three and a half four years ago. And our differentiation versus all the other guys you mentioned is that, two things, one, we bring a very application-centric view of it. We're not trying to build a horizontal, generic, machine learning platform. In the same way that we- >> Yeah you're not IBM with Watson, all that stuff. >> Yeah, no, no. Or even Auricle. >> Jim: Understood. >> Or Microsoft. >> Jim: Nobody expects you to be. >> No, you know, and we've always been the guys that have worked for the Open Source community. Even when you look at like, we're the first guys to provide a completely open source stack underneath our technology with postscripts. We don't have a dog in the hunt like most of the other guys do. Right? So we tap in to the innovation that happens in the Open Source community. And when you look at all the real innovation that's happening in machine learning, it's happening in the Open Source Community. >> Jim: Yes. >> It's not happening with the old legacy, you know, ERP guys. >> Jim: Pencer, Flow and Spark and all that stuff. >> Yeah, Google, Apple, the GAFA. >> Yeah. >> Right? Google, Apple, Facebook, those are the guys that are doing it. And the academic community is light years ahead on top of that of what these other guys will do. So that's what we tap into right? >> Are you tapping into partners like AWS? 'Cause they've obviously, >> Duncan: Absolutely >> got a huge portfolio of AI. >> Yeah, so we. >> Give us a sense whether you're going to be licensing or co-developing Coleman technologies with them going forward. >> Yeah so we obviously we have NDA's with them, we're deeply inside their development organization in terms of working on things. You know, our science is obviously presented to them around ideas we think they need to go. I mean, we're a customer of their AI frameup to machine learning and we're testing it at scale with specific use cases in industries, right? So we can give them a lot of insights around where it needs to go and problems we're trying to solve. But we do that across a number of different organizations and we've got lots and lots of academic collaborations that happen on around all of the best universities that are pushing on this. We've even received funding from DAPA in certain cases around things that we're trying to solve for. You know quietly we've made some machine-learning acquisitions over the last five, six years. That have obviously brought this capability into it. But the point is we're going to leverage the innovation that happens around these frameworks. And then our job is understanding the industries we're in and that we're an applications company, is to bring it to life in these applications in a seamless way, that solves a very specific problem in an industry, in a powerful and unique way. You know on stage I talked about this idea of bringing this AI first mindset to how we go about doing it. >> So it's important, if I can interject. This is very important. This is Infor IP, the serious R&D that's gone into this. It's innovation. 'Cause you know what your competitors are going to say. They're going to deposition and say, oh, it's Alexa on steroids. But it's not. It's substantial IP and really leveraging a lot of the open source technologies that are out there. >> Yeah. So you know, I talked about there were four components to Coleman, right? And the first part of it was, we can leverage machine-learning services to make the CloudSuites conversational. So they can chat, and talk, and see, and hear, and all of that. And yeah, some of those are going to use the technology that sits behind Alexa. And it's available in AWS's Alexa as you guys know. But that's only really a small part of what we're doing. There are some places where we are looking at using computer vision. For example, automated inspection of car rental returns, is one area. We're using it for quality management pilot at a company that normally has humans inspect something on a production line. That kind of computer-vision, that's not Alexa, right? It's you know, I gave the example of image recognition. Some of it can leverage AWS's framework there. But again, we're always going to look for the best platform and framework out there to solve the specific problem that we're trying to solve. But we don't do it just for the sake of it. We do it with a focus to begin with, with an industry. Like, where's a really big problem we can solve? Or where is there a process that happens inside an application today that if you brought an AI first mindset to it, it's revolutionary. And we use this phrase, "the AI is the UI". And we've got some pretty good analogies there that can help bring it to life. >> And I like your approach for presenting your AI strategy, in terms of the value it delivers your customers, to business. You know, there's this specter out there in the culture that AI's going to automate everybody out of a job. Automation's very much a big part of your strategy but you expressed it well. Automating out those repetitive functions so that human beings, you can augment the productivity of human beings, free them up for more value-added activities and then augment those capabilities through conversational chat box. And so forth, and so on. Provide you know, in-application, in process, in context, decision support with recommendations and all that. I think that's the exact right way to pitch it. One of the things that we focus on and work on in terms of application development, disciplines that are totally fundamental to this new paradigm. Recommendation engines, recommender systems, in line to all application. It's happening, I mean, Coleman, that really in many ways, Coleman will be the silent, well not so silent, but it'll be the recommendation engine embedded inside all of your offerings at some point. At least in terms of the strategy you laid out. >> Yeah, no, absolutely right I mean. It's not just about, we all get hung up on machine-learning and deep learning 'cause it's the sexy part of AI, right? But there's a lot more. I mean, AI, all the way back, you can go all the way back to Socrates and the father of logic right? I mean, some of the things you can do is just based on very complex rules and logic. And what used to be called process automation right? And then it extends all the way to deep learning and neural networks and so on. So one of the things that Coleman also does, is it unifies a lot of this technology. Things that you would normally do for prediction or optimization, and optimization normally is the province of operations research guys right? Which again it's a completely different field. So it unifies all of that into one consistent platform that has all of that capability into it. And then it exposes it in a consistent way through our API architecture. So same thing with bots. People always think chat bots are separate. Well that too is unified inside Coleman. So it's a cohesive platform but again, industry focused. >> What's your point of view on developers? And how do you approach the development community and what's your strategy there? >> Yeah, I mean, it's critical right? So we've always, I mean, hired an incredible number of application engineers every year. I think the first 12 months we were here, we hired 1800 right? 'Cause you know, that's kind of what we do. So we believe hugely in smarts. And it sounds kind of obvious, but experience can be learned, smarts is portable. And we have a lot of programs in place with universities. We call it the Education Alliance Program. And I think we have up to 32 different universities around the world where we're actually influencing curriculum, and actually bringing students right out of there. Using internships during the year and then actually bringing them into our development organization. So we've got a whole pipeline there. I mean that's critical that we have access to those. >> And what about outside your four walls, or virtual walls have been four? Is there a strategy to specifically pursue external developers and open up a PAZ layer? >> Yeah we do. >> Or provide an STK for Coleman for example, for developers. >> Yeah so we did, as part of our Infor Operating Service update. Which is, you know, the name for our unified technology platform. We did announce Mongoose platform was a service. Our Mongoose pass. >> Host: Oh Mongoose, sure. >> So that now is being delivered as a platform with a service for application development. And it's used in two ways. It's used for us to build new applications. It's a very mobile-first type development framework too. And obviously Hook and Loop had a huge influence in how that ships. The neat thing about it, is that it ships with plumbing into ION API, plumbing into our security layer. So customers will use it because it leverages our security model. It's easy to access everything else. But it's also used by our Hook and Loop digital team. So those guys are going off and they're building completely differentiated curated apps for customers. And again, they're using Mongoose. So I think between ION API's and between all the things you get in the Infor Operating Service, and Mongoose, we've got a pretty good story around extensibility and application development. As it relates to an STK for Coleman, we're just working through that now. Again, our number one focus is to build those things into the applications. It's a feature. The way most companies have approached optimization and machine learning historically, is it's a discrete app that you have to license. And it's off to the side and you integrate it in. We don't think that's the right way of doing it. Machine-learning and artificial intelligence, is a platform. It's an enabler. And it fuses and changes every part of the CloudSuite. And we've got a great example on how you can rethink demand forecasting, demand planning. Every, regardless of the industry we serve, everyone has to predict demand right? It's the basis for almost every other decision that happens in the enterprise. And, how much to make, how many nurses to put on staff, all of that, every industry, that prediction of demand. And the thinking there really hasn't changed in 20, 30 years. It really hasn't. And some of that's just because of the constraints with technology. Storage, compute, all of that. Well with the access we have to the elastic super-computing now and the advancements in sort of machine-learning and AI, you can radically rethink all of that, and take what we call and "AI First" approach, which is what we've done with building our brand new demand prediction platform. So the example we gave is, you think about when early music players came along on the internet right? The focus was all around building a gorgeous experience for how to build a playlist. It was drag and drop, I could do it on a phone, I could share it with people and it showed pictures of the album art. But it was all around the usability of making that playlist better. Then guys like Spotify and Pandora came around and it took an AI First approach to it. And the machine builds your playlist. There is no UI. AI is the UI. And it can recommend music I never knew I would've liked. And the way it does that, comes back to the data. Which is why I'm going to circle back to Infor here in a second. Is that, it breaks a song down into hundreds if not thousands of attributes about that song. Sometimes it's done by a human, sometimes it's even done by machine listening algorithms. Then you have something that crawls the web, finds music reviews online, and further augments it with more and more attributes. Then you layer on top of that, user listening activity, thumbs up, thumbs down, play, pause, skip, share, purchase. And you find, at that attribute level, the very lowest level, the true demand drivers of a song. And that's what's powering it right? Just like you see with Netflix for movies and so on. Imagine bringing that same thought process into how you predict demand for items, that you've never promoted before. Never changed the price before. Never put in this store before. Never seen before. >> The cold start problem in billing recommendation areas. >> Exactly right, so, that's what we mean by AI First. It's not about just taking traditional demand planning approaches and making it look sexier and putting it on an iPad right? Rethink it. >> Well it's been awesome to watch. We are out of time. >> Yeah, we're out of time. >> Been awesome to watch the evolution, >> We could go on and on with this yeah. >> of Infor as it's really becoming a data company. And we love having executives like you on. >> Yeah >> You know, super articulate. You got technical chops. Congratulations on the last six years. >> Thanks. >> The sort of quasi-exit you guys had. >> Great show, amazing turnout. >> And look forward to watching the next six to 10. So thanks very much for coming out. >> Brilliant, thank you guys. Alright thank you. >> Alright keep it right there everybody, we'll be back with our next guest, this is Inforum 2017 and this is theCUBE. We'll be right back. (digital music)

>> [Announcer] Live from Boston Massachusetts. This is theCUBE. Covering Sparks Summit East 2017. Brought to you by Databricks. Now here are your hosts, Dave Vellante and George Gilbert. >> [Dave] Welcome back to Boston everybody, this is Spark Summit East #SparkSummit And this is theCUBE. Ion Stoica is here. He's Executive Chairman of Databricks and Professor of Computer Science at UCal Berkeley. The smarts is rubbing off on me. I always feel smart when I co-host with George. And now having you on is just a pleasure, so thanks very much for taking the time. >> [Ion] Thank you for having me. >> So loved the talk this morning, we learned about RISELabs, we're going to talk about that. Which is the son of AMP. You may be the father of those two, so. Again welcome. Give us the update, great keynote this morning. How's the vibe, how are you feeling? >> [Ion] I think it's great, you know, thank you and thank everyone for attending the summit. It's a lot of energy, a lot of interesting discussions, and a lot of ideas around. So I'm very happy about how things are going. >> [Dave] So let's start with RISELabs. Maybe take us back, to those who don't understand, so the birth of AMP and what you were trying to achieve there and what's next. >> Yeah, so the AMP was a six-year Project at Berkeley, and it involved around eight faculties and over the duration of the lab around 60 students and postdocs, And the mission of the AMPLab was to make sense of big data. AMPLab started in 2009, at the end of 2009, and the premise is that in order to make sense of this big data, we need a holistic approach, which involves algorithms, in particular machine-learning algorithms, machines, means systems, large-scale systems, and people, crowd sourcing. And more precisely the goal was to build a stack, a data analytic stack for interactive analytics, to be used across industry and academia. And, of course, being at Berkeley, it has to be open source. (laugh) So that's basically what was AMPLab and it was a birthplace for Apache Spark that's why you are all here today. And a few other open-source systems like Mesos, Apache Mesos, and Alluxio which was previously called Tachyon. And so AMPLab ended in December last year and in January, this January, we started a new lab which is called RISE. RISE stands for Real-time Intelligent Secure Execution. And the premise of the new lab is that actually the real value in the data is the decision you can make on the data. And you can see this more and more at almost every organization. They want to use their data to make some decision to improve their business processes, applications, services, or come up with new applications and services. But then if you think about that, what does it mean that the emphasis is on the decision? Then it means that you want the decision to be fast, because fast decisions are better than slower decisions. You want decisions to be on fresh data, on live data, because decisions on the data I have right now are original but those are decisions on the data from yesterday, or last week. And then you also want to make targeted, personalized decisions. Because the decisions on personal information are better than aggregate information. So that's the fundamental premise. So therefore you want to be on platforms, tools and algorithms to enable intelligent real-time decisions on live data with strong security. And the security is a big emphasis of the lab because it means to provide privacy, confidentiality and integrity, and as you hear about data breaches or things like that every day. So for an organization, it is extremely important to provide privacy and confidentiality to their users and it's not only because the users want that, but it also indirectly can help them to improve their service. Because if I guarantee your data is confidential with me, you are probably much more willing to share some of your data with me. And if you share some of the data with me, I can build and provide better services. So that's basically in a nutshell what the lab is and what the focus is. >> [Dave] Okay, so you said three things: fast, live and targeted. So fast means you can affect the outcome. >> Yes. Live data means it's better quality. And then targeted means it's relevant. >> Yes. >> Okay, and then my question on security, I felt like when cloud and Big Data came to fore, security became a do-over. (laughter) Is that a fair assessment? Are you doing it over? >> [George] Or as Bill Clinton would call it, a Mulligan. >> Yeah, if you get a Mulligan on security. >> I think security is, it's always a difficult topic because it means so many things for so many people. >> Hmm-mmm. >> So there are instances and actually cloud is quite secure. It's actually cloud can be more secure than some on-prem deployments. In fact, if you hear about these data leaks or security breaches, you don't hear them happening in the cloud. And there is some reason for that, right? It is because they have trained people, you know, they are paranoid about this, they do a specification maybe much more often and things like that. But still, you know, the state of security is not that great. Right? For instance, if I compromise your operating system, whether it's in cloud or in not in the cloud, I can't do anything. Right? Or your VM, right? On all this cloud you run on a VM. And now you are going to allow on some containers. Right? So it's a lot of attacks, or there are attacks, sophisticated attacks, which means your data is encrypted, but if I can look at the access patterns, how much data you transferred, or how much data you access from memory, then I can infer something about what you are doing about your queries, right? If it's more data, maybe it's a query on New York. If it's less data it's probably maybe something smaller, like maybe something at Berkeley. So you can infer from multiple queries just looking at the access. So it's a difficult problem. But fortunately again, there are some new technologies which are developed and some new algorithms which gives us some hope. One of the most interesting technologies which is happening today is hardware enclaves. So with hardware enclaves you can execute the code within this enclave which is hardware protected. And even if your operating system or VM is compromised, you cannot access your code which runs into this enclave. And Intel has Intell SGX and we are working and collaborating with them actively. ARM has TrustZone and AMB also announced they are going to have a similar technology in their chips. So that's kind of a very interesting and very promising development. I think the other aspect, it's a focus of the lab, is that even if you have the enclaves, it doesn't automatically solve the problem. Because the code itself has a vulnerability. Yes, I can run the code in hardware enclave, but the code can send out >> Right. >> data outside. >> Right, the enclave is a more granular perimeter. Right? >> Yeah. So yeah, so you are looking and the security expert is in your lab looking at this, maybe how to split the application so you run only a small part in the enclave, which is a critical part, and you can make sure that also the code is secure, and the rest of the code you run outside. But the rest of the code, it's only going to work on data which is encrypted. Right? So there is a lot of interesting research but that's good. >> And does Blockchain fit in there as well? >> Yeah, I think Blockchain it's a very interesting technology. And again it's real-time and the area is also very interesting directions. >> Yeah, right. >> Absolutely. >> So you guys, I want George, you've shared with me sort of what you were calling a new workload. So you had batch and you have interactive and now you've got continuous- >> Continuous, yes. >> And I know that's a topic that you want to discuss and I'd love to hear more about that. But George, tee it up. >> Well, okay. So we were talking earlier and the objective of RISE is fast and continuous-type decisions. And this is different from the traditional, you either do it batch or you do it interactive. So maybe tell us about some applications where that is one workload among the other traditional workloads. And then let's unpack that a little more. >> Yeah, so I'll give you a few applications. So it's more than continuously interacting with the environment continuously, but you also learn continuously. I'll give you some examples. So for instance in one example, think about you want to detect a network security attack, and respond and diagnose and defend in the real time. So what this means is that you need to continuously get logs from the network and from the more endpoints you can get the better. Right? Because more data will help you to detect things faster. But then you need to detect the new pattern and you need to learn the new patterns. Because new security attacks, which are the ones that are effective, are slightly different from the past one because you hope that you already have the defense in place for the past ones. So now you are going to learn that and then you are going to react. You may push patches in real time. You may push filters, installing new filters to firewalls. So that's kind of one application that's going in real time. Another application can be about self driving. Now self driving has made tremendous strides. And a lot of algorithms you know, very smart algorithms now they are implemented on the cars. Right? All the system is on the cars. But imagine now that you want to continuously get the information from this car, aggregate and learn and then send back the information you learned to the cars. Like for instance if it's an accident or a roadblock an object which is dropped on the highway, so you can learn from the other cars what they've done in that situation. It may mean in some cases the driver took an evasive action, right? Maybe you can monitor also the cars which are not self-driving, but driven by the humans. And then you learn that in real time and then the other cars which follow through the same, confronted with the same situation, they now know what to do. Right? So this is again, I want to emphasize this. Not only continuous sensing environment, and making the decisions, but a very important components about learning. >> Let me take you back to the security example as I sort of process the auto one. >> Yeah, yeah. >> So in the security example, it doesn't sound like, I mean if you have a vast network, you know, end points, software, infrastructure, you're not going to have one God model looking out at everything. >> Yes. >> So I assume that means there are models distributed everywhere and they don't know what a new, necessarily but an entirely new attack pattern looks like. So in other words, for that isolated model, it doesn't know what it doesn't know. I don't know if that's what Rumsfeld called it. >> Yes (laughs). >> How does it know what to pass back for retraining? >> Yes. Yes. Yes. So there are many aspects and there are many things you can look at. And it's again, it's a research problem, so I cannot give you the solution now, I can hypothesize and I give you some examples. But for instance, you can look about, and you correlate by observing the affect. Some of the affects of the attack are visible. In some cases, denial of service attack. That's pretty clear. Even the And so forth, they maybe cause computers to crash, right? So once you see some of this kind of anomaly, right, anomalies on the end devices, end host and things like that. Maybe reported by humans, right? Then you can try to correlate with what kind of traffic you've got. Right? And from there, from that correlation, probably you can, and hopefully, you can develop some models to identify what kind of traffic. Where it comes from. What is the content, and so forth, which causes behavior, anomalous behavior. >> And where is that correlation happening? >> I think it will happen everywhere, right? Because- >> At the edge and at the center. >> Absolutely. >> And then I assume that it sounds like the models both at the edge and at the center are ensemble models. >> Yes. >> Because you're tracking different behavior. >> Yes. You are going to track different behavior and you are going to, I think that's a good hypothesis. And then you are going to assemble them, assemble to come up with the best decision. >> Okay, so now let's wind forward to the car example. >> Yeah. >> So it sound like there's a mesh network, at least, Peter Levine's sort of talk was there's near-local compute resources and you can use bitcoin to pay for it or Blockchain or however it works. But that sort of topology, we haven't really encountered before in computing, have we? And how imminent is that sort of ... >> I think that some of the stuff you can do today in the cloud. I think if you're on super-low latency probably you need to have more computation towards the edges, but if I'm thinking that I want kind of reactions on tens, hundreds of milliseconds, in theory you can do it today with the cloud infrastructure we have. And if you think about in many cases, if you can't do it within a few hundredths of milliseconds, it's still super useful. Right? To avoid this object which has dropped on the highway. You know, if I have a few hundred milliseconds, many cars will effectively avoid that having that information. >> Let's have that conversation about the edge a little further. The one we were having off camera. So there's a debate in our community about how much data will stay at the edge, how much will go into the cloud, David Flores said 90% of it will stay at the edge. Your comment was, it depends on the value. What do you mean by that? >> I think that that depends who am I and how I perceive the value of the data. And, you know, what can be the value of the data? This is what I was saying. I think that value of the data is fundamentally what kind of decisions, what kind of actions it will enable me to take. Right? So here I'm not just talking about you know, credit card information or things like that, even exactly there is an action somebody's going to take on that. So if I do believe that the data can provide me with ability to take better actions or make better decisions I think that I want to keep it. And it's not, because why I want to keep it, because also it's not only the decision it enables me now, but everyone is going to continuously improve their algorithms. Develop new algorithms. And when you do that, how do you test them? You test on the old data. Right? So I think that for all these reasons, a lot of data, valuable data in this sense, is going to go to the cloud. Now, is there a lot of data that should remain on the edges? And I think that's fair. But it's, again, if a cloud provider, or someone who provides a service in the cloud, believes that the data is valuable. I do believe that eventually it is going to get to the cloud. >> So if it's valuable, it will be persisted and will eventually get to the cloud? And we talked about latency, but latency, the example of evasive action. You can't send the back to the cloud and make the decision, you have to make it real time. But eventually that data, if it's important, will go back to the cloud. The other question of all this data that we are now processing on a continuous basis, how much actually will get persisted, most of it, much of it probably does not get persisted. Right? Is that a fair assumption? >> Yeah, I think so. And probably all the data is not equal. All right? It's like you want to maybe, even if you take a continuous video, all right? On the cars, they continuously have videos from multiple cameras and radar and lidar, all of this stuff. This continuous. And if you think about this one, I would assume that you don't want to send all the data to the cloud. But the data around the interesting events, you may want to do, right? So before and after the car has a near-accident, or took an evasive action, or the human had to intervene. So in all these cases, probably I want to send the data to the cloud. But for the most cases, probably not. >> That's good. We have to leave it there, but I'll give you the last word on things that are exciting you, things you're working on, interesting projects. >> Yeah, so I think this is what really excites me is about how we are going to have this continuous application, you are going to continuously interact with the environment. You are going to continuously learn and improve. And here there are many challenges. And I just want to say a few more there, and which we haven't discussed. One, in general it's about explainability. Right? If these systems augment the human decision process, if these systems are going to make decisions which impact you as a human, you want to know why. Right? Like I gave this example, assuming you have machine-learning algorithms, you're making a diagnosis on your MRI, or x-ray. You want to know why. What is in this x-ray causes that decision? If you go to the doctor, they are going to point and show you. Okay, this is why you have this condition. So I think this is very important. Because as a human you want to understand. And you want to understand not only why the decision happens, but you want also to understand what you have to do, you want to understand what you need to do to do better in the future, right? Like if your mortgage application is turned down, I want to know why is that? Because next time when I apply to the mortgage, I want to have a higher chance to get it through. So I think that's a very important aspect. And the last thing I will say is that this is super important and information is about having algorithms which can say I don't know. Right? It's like, okay I never have seen this situation in the past. So I don't know what to do. This is much better than giving you just the wrong decision. Right? >> Right, or a low probability that you don't know what to do with. (laughs) >> Yeah. >> Excellent. Ion, thanks again for coming in theCUBE. It was really a pleasure having you. >> Thanks for having me. >> You're welcome. All right, keep it right there everybody. George and I will be back to do our wrap right after this short break. This is theCUBE. We're live from Spark Summit East. Right back. (techno music)

live from Las Vegas Nevada it's the cute covering knowledge 15 brought to you by service now okay welcome back everyone we are live in Las Vegas this is SiliconANGLE Mookie bonds to cube our footage and event coverage would go out to the event started sitteth on the noise i'm john furrier likos day volante our next guest is Jen Stroud senior director and general manager of the HR applications within service now a former customer now general manager welcome to the cube thank you great I get the service now shirt on the jersey of the number everything right I'm official how does it feel so give us a quick you know Darkseid is always a dark side but I won't say which one it is is they always say with the VCS you join the dark side when entrepreneurs join the VC ranks but in this case service now pumping on all cylinders just like a well-oiled machine with the fast side yeah fasten what's it like give us the perspective it's been tremendous that I've been to two knowledge events before but as a customer very different perspective on this side and it's been it's been fabulous very fast you move fast here you have to keep up but it's been wonderful for me to engage with the partners and the customers here to see all the great things that customers are doing with the platform and with our product and also understanding where they want to see us take the the product going forward as a culture like its service now as a company you're in there ask you there for profit yeah kid jittery revenue from customers and I have a product they bring to the customers to get paid for that what's it like internally was the culture like what's the people like it's it's been incredible to be a part of this culture and a little I wasn't what I expected I knew it was going to be very fast-paced but coming in and being able to rely on everyone to make sure you're successful everybody is interested in everybody being successful and I think that starts from Frank on down he's created that culture and so that's what it's about everyone is staring in the same direction and we're I've always said in Silicon Valley you know people you know high fliers come goes a lot of love you come in and out but building a sustainable business is really haha yeah so you gotta give props to Frank's loop and talk about what you've learned Massey HR managers are out struggling this is in the press now small medium-sized businesses you see all kinds of certainly in Silicon Valley where I live you know eight lawsuits coming from just not keeping your eye on the ball little things like yeah Oh someone's offended in a meeting boom lawsuit I've been discriminating against so there's all kinds of stuff happening just by having shot eh our practices so talk about what that means why that's happening is it just because they're lazy or the games change the technologies change what's going on with in the HR application space I think some other people have said it in my colleague Eric hammer who's a solution consultant now leads the enterprise practice said it HR is kind of a 10 to 15 well five to ten years behind IT they're finally understanding that you can't manage with spreadsheets and email anymore and we're seeing it I don't care the the size of the organization or what their annual revenues are there are many organizations struggling with the same thing how do they provide a better experience for their employees and how do they do it in a consistent way and so that's we're seeing it out there the opportunities large and small with with customers it's very consistent Frank Frank mitch is a real time piece what's your perspective on that I mean being real time means service and complaints and managing that I'm sorry Dave I know oh absolutely i mean that's you want to be able to support your employees in a way that they're used to being supported in interacting outside of work right and yet especially the younger generation they come in and they want to work with a company that understands how to how to do that not you know managing through emails and so they want to come in with a hit company that you know gets it so service now is able to provide that type of experience so the state of Technology in HR is changing quite dramatically we were talking I was talking earlier guys from KPMG you know peoplesoft gets acquired by oracle it sets off this chain reaction taleo success factors work day comes into the market space and so the tech base is changing and then all of a sudden service now starts to play and people are confused people asked you yesterday yeah alist me who are you competing with with work day and of course no although you know but we've been asked eight or nine times already I'm just two days you'll continue to be asked you know and then you said something just recently to John that people they can't you know manage effectively with spreadsheets and the like so there's a lot of confusion because there's a lot of ton of technology that's begin going into a human humble management for decades there's some new cool cloud texts coming out technologies work days just you know one example successfactors many others and then and then service now with service management tied to the HRP so what's happening on the technology substrate how would you describe the changes that are going on it's it's amazing I mean they're the companies are understanding very quickly and you look at companies that have done results from their 2014 surveys of large leading HR organizations they understand that they have to to change and to leverage SAS technology in order to be able to to keep up so you like you were indicating we don't have any plan to compete with the workdays or the essay peas or PeopleSoft out there are our whole philosophy is let's figure out how we complement what they do and give like Frank said yesterday and I love what he said let's give let's give our customers choices let's give them good choices that they can they can have a good choice what they want to do ok so you're an HR pro so that's the many people in our audience have the same question that you've been asked nine times today yep you're not competing with the the transaction component that is work day you don't go to service now to to change my you know data about my self but we could if you want to though okay so we could be that front end so I mean again that's Ultima you start there you say yes sir then that make sense yeah go through service now so every request but we're not going to store that we're not we're not the system of Ragnar the system of record there that's the difference mm-hmm right okay but now love flip it so you're not going to go compete with with work day no but if I'm work day and I'm saying wow this company's service now is doing really well they grow in a 50 plus percent a year they got this great market cap maybe I should start doing some of that stuff now they could yeah but they're not going to do the other things it's hell's force like Frank said the other day well hey I talked to penny off all the time you know we're birds of a feather in a lot of ways we're developing apps they're developing absolutely a company like service now with a market tam of 40-plus billion you're playing in a lot of places especially when I have a platform that can do anything that's right now where do you see that all going well I mean in my view when I look at what I want to provide HR leaders I want to provide them out of the box a product that meets the majority of their needs and delivering services to their employees I and I want it to continue to and will expand on this and future releases look and feel the great user interface because it's all about the employee experience with HR IT doesn't care about the employee experience HR cares about the employee experience so really really working on that user interface and that experience and and the workflows for me the the possibilities are limitless what is it you and the work days of comprehensive system but optimizing workflows is interesting because there's so many different workflows in HR so there's that kind that stands like the strategy just picking it's almost like I Tina sends pick a few critical workflows could be trendy hey we got this new law comes out or longboarding of course is the big one that everybody's talking yeah so what is those use cases what are the key ones you guys are well I mean you have leave of absence as a big use case every HR organization and and it's it's one that can be very sticky it can also bleed into legal and other areas of the business so leave leave of absence managing those leave of absence requests some basic ones that are easy to ition reimbursement employment verification really standard that we that we will be offering out of the box too to our customers a pto request managing time off those are all yes you're lying fruit to use automation automation the other ones are just more yeah it's rewire or something or you know could be exposure that's right yep what percent of companies in your experience do performance reviews I just want to ask you as an HR pro ah too many too many too many do you think it's a I reproductive I think the so this is another probably great reason why I joined this organization is in Frank's and Shelley's philosophy on performance reviews and it's not formal the way we consider it formal or HR many HR organizations do with you know the whole performance review and setting goals he really believes that that that whole responsibility lives with the manager and HR is there to support the manager and I love that philosophy but we have to as a as we're developing our product understand that unfortunately this organization don't share Frank's philosophy ok so you're saying that many organizations have the HR oh they do the performance I feel like a neophyte I didn't know that what that's insane absolutely would you have the HR department it is performing well and i and i don't necessarily i don't i don't agree with it but it absolutely i would majority of organizations HR still manages the whole performance whether the sense that they sent a syntax they had the structure and process yeah which controls the behaviors of Manokotak attendance it's a whole they don't do the review submitted yourself they don't do their reviews but they they set the schedule and you must have your reviews done by this time and you must miss assurance icon the dentist makes your teeth pulled yeah basically and then they're constantly pounding on managers when they don't get it done to get it done get it done get it done i mean that's that's the way it was in my previous company no no offense but it just does it's not it doesn't work well what does frank with what what what Frank's philosophy and Shelley's philosophy is here and that is managers are responsible for the performance of their team and you reward people for their performance and then comes in the last place already no prize for you yeah so I want to ask question about systems of engagement versus a record this comes up a lot and that I look at it a little bit differently as I don't look it from the HR perspective mother from the day big data side what's your view of it from an HR perspective what is the definitions of those systems of engagement systems of record I can also imagine so I look at it and this from this is the my philosophy when I was on the customer side I wanted to create that one stop shop where my employees could come where they knew exactly i took all the guesswork out for them here's where you come to do everything now ultimately they may be the they may be interacting and engaging with a form and service now and that was going to feed being an integration to our hrs is system which was oracle that's fine but they don't need to know that for them I wanted to create that standard look and feel standard system of engagement that was predictable for them easy to use and that's really what you want to provide employees you want to make it easy that's an employee that's the app that's user interface user experience that's right flows and clicks yep click stream where all the information is ultimately stored is a whole different matter and not necessarily important to me other than I want to be able to integrate with those systems so bad you I bed ux taking that to the next level means you don't get the data you need for the systems records so the engagement date is pretty critical engagement is is absolutely critical if you want your your employees to use it if it if it is a bad you I if it isn't a good experience they're going to go I'm not going to use this and they're going to they're going to the employees make themselves heard very loudly so they'll let you know if it's a bad experience so that creating that great system of engagement where it's easy to use and they know how to use it that's important about mobile as it relates specifically an HR context that's the conversation we're having are you happy with where you are with mobile is there a lot more work to do there very happy with where we are but as with everything I think we can continue to enhance what we offer it's absolutely a necessity in HR as you think about where many of the employees make their benefit decisions it's not at the office on their lunch break it's at home with their with their families and so they may be you know looking for information and the knowledge base or making a benefit selection on their mobile device at home not at the office so being able to provide that capability on a mobile or you know iPad device is very critical she has talked a lot about you know the affinity with work day of course I know an eel and Frank you know birds of a feather and friendly but there's a lot of other HR platforms out there oracle SI p many others what about those we also so right now we're focusing just because the market there's a lot of shift to an interest in work days Oh cloud its cloud yeah and but other the other ones are also coming up with they have cloud as well as record yeah yeah so so with the Geneva will have a two-way integration with worth work day to make that easier for customers but then we'll be focusing on additional out-of-the-box integrations with those other hris systems as well so does it have to be cloud-based I mean everybody's cloud now everybody is just like it better because you're why it's this is part of the mantra it's easier it's easier for you it's easier for the customers it doesn't action okay yeah this is a big so what's your goal now you're in there get your running shoes on three feet in a cloud of dust making things happen to get some teammates to support you servicenow yeah what's next what's what are you gonna work on what's your plan well we just don't we're still not known enough in the HR industry as a trusted platform in HR so we've got our work cut out for us there and so you know it is about what we're building in the product that's going to help us but it's also going to help us getting out at HR tech that's coming here mandalay bay and octo we'll be here other events working with analysts as well to help them understand what we're doing and really it's going to be about creating more success and a great customer base so that you know this time next year I hope to you know be able to say you know we really are one of those vendors that HR looks to first and not you know us trying to get in there to have the because I think once they do and once they look at what we have to offer it's it's it's very intriguing for them but we really want to be you know on top of their mind it sounds like your strategy then is to say hey you know what you big pickle the big decisions we're going to come in create some value pretty nimble pretty agile land and expand and if that grows it grows and not really mutually exclusive to some other platform no and in we absolutely are concentrating right now on where we are very successful so we have a lot of great customers already on the IT side so they all have HR departments so we're absolutely focused there in 2015 but beyond we really want to expand and be first okay Jamie keep a track and we'll be following you if you need any help let us know we go stroll at the cube to HR tech con and in October it's the cube we are live here at Las Vegas extracting the scene from the noise shared that with you I'm genre Dave vellante we'll be right back after this short break of the next guest stay tuned off