>> From around the globe, it's theCUBE, covering Data Citizens'21. Brought to you by Collibra. >> We're back talking all things data at Data Citizens '21. My name is Dave Vellante and you're watching theCUBE's continuous coverage, virtual coverage #DataCitizens21. I'm here with Jim Cushman who is Collibra's Chief Product Officer who shared the company's product vision at the event. Jim, welcome, good to see you. >> Thanks Dave, glad to be here. >> Now one of the themes of your session was all around self-service and access to data. This is a big big point of discussion amongst organizations that we talk to. I wonder if you could speak a little more toward what that means for Collibra and your customers and maybe some of the challenges of getting there. >> So Dave our ultimate goal at Collibra has always been to enable service access for all customers. Now, one of the challenges is they're limited to how they can access information, these knowledge workers. So our goal is to totally liberate them and so, why is this important? Well, in and of itself, self-service liberates, tens of millions of data lyric knowledge workers. This will drive more rapid, insightful decision-making, it'll drive productivity and competitiveness. And to make this level of adoption possible, the user experience has to be as intuitive as say, retail shopping, like I mentioned in my previous bit, like you're buying shoes online. But this is a little bit of foreshadowing and there's even a more profound future than just enabling a self-service, that we believe that a new class of shopper is coming online and she may not be as data-literate as our knowledge worker of today. Think of her as an algorithm developer, she builds machine learning or AI. The engagement model for this user will be, to kind of build automation, personalized experiences for people to engage with data. But in order to build that automation, she too needs data. Because she's not data literate, she needs the equivalent of a personal shopper. Someone that can guide her through the experience without actually having her know all the answers to the questions that would be asked. So this level of self-service goes one step further and becomes an automated service. One to really help find the best unbiased in a labeled training data to help train an algorithm in the future. >> That's, okay please continue. >> No please, and so all of this self and automated service, needs to be complemented with kind of a peace of mind that you're letting the right people gain access to it. So when you automate it, it's like, well, geez are the right people getting access to this. So it has to be governed and secured. This can't become like the Wild Wild West or like a data, what we call a data flea market or you know, data's everywhere. So, you know, history does quickly forget the companies that do not adjust to remain relevant. And I think we're in the midst of an exponential differentiation in Collibra data intelligence cloud is really kind of established to be the key catalyst for companies that will be on the winning side. >> Well, that's big because I mean, I'm a big believer in putting data in the hands of those folks in the line of business. And of course the big question that always comes up is, well, what about governance? What about security? So to the extent that you can federate that, that's huge. Because data is distributed by its very nature, it's going to stay that way. It's complex. You have to make the technology work in that complex environment, which brings me to this idea of low code or no code. It's gaining a lot of momentum in the industry. Everybody's talking about it, but there are a lot of questions, you know, what can you actually expect from no code and low code who were the right, you know potential users of that? Is there a difference between low and no? And so from your standpoint, why is this getting so much attention and why now, Jim? >> You don't want me to go back even 25 years ago we were talking about four and five generational languages that people were building. And it really didn't re reach the total value that folks were looking for because it always fell short. And you'd say, listen, if you didn't do all the work it took to get to a certain point how are you possibly going to finish it? And that's where the four GLs and five GLs fell short as capability. With our stuff where if you really get a great self-service how are you going to be self-service if it still requires somebody right though? Well, I guess you could do it if the only self-service people are people who write code, well, that's not bad factor. So if you truly want the ability to have something show up at your front door, without you having to call somebody or make any efforts to get it, then it needs to generate itself. The beauty of doing a catalog, new governance, understanding all the data that is available for choice, giving someone the selection that is using objective criteria, like this is the best objective cause if it's quality for what you want or it's labeled or it's unbiased and it has that level of deterministic value to it versus guessing or civic activity or what my neighbor used or what I used on my last job. Now that we've given people the power with confidence to say, this is the one that I want, the next step is okay, can you deliver it to them without them having to write any code? So imagine being able to generate those instructions from everything that we have in our metadata repository to say this is exactly the data I need you to go get and perform what we call a distributed query against those data sets and bringing it back to them. No code written. And here's the real beauty Dave, pipeline development, data pipeline development is a relatively expensive thing today and that's why people spend a lot of money maintaining these pipelines but imagine if there was zero cost to building your pipeline would you spend any money to maintain it? Probably not. So if we can build it for no cost, then why maintain it? Just build it every time you need it. And it then again, done on a self-service basis. >> I really liked the way you're thinking about this cause you're right. A lot of times when you hear self self-service it's about making the hardcore developers, you know be able to do self service. But the reality is, and you talk about that data pipeline it's complex a business person sitting there waiting for data or wants to put in new data and it turns out that the smallest unit is actually that entire team. And so you sit back and wait. And so to the extent that you can actually enable self-serve for the business by simplification that is it's been the holy grail for a while, isn't it? >> I agree. >> Let's look a little bit dig into where you're placing your bets. I mean, your head of products, you got to make bets, you know, certainly many many months if not years in advance. What are your big focus areas of investment right now? >> Yeah, certainly. So one of the things we've done very successfully since our origin over a decade ago, was building a business user-friendly software and it was predominantly kind of a plumbing or infrastructure area. So, business users love working with our software. They can find what they're looking for and they don't need to have some cryptic key of how to work with it. They can think about things in their terms and use our business glossary and they can navigate through what we call our data intelligence graph and find just what they're looking for. And we don't require a business to change everything just to make it happen. We give them kind of a universal translator to talk to the data. But with all that wonderful usability the common compromise that you make as well, its only good up to a certain amount of information, kind of like Excel. You know, you can do almost anything with Excel, right? But when you get to into large volumes, it becomes problematic and now you need that, you know go with a hardcore database and application on top. So what the industry is pulling us towards is far greater amounts of data not that just millions or even tens of millions but into the hundreds of millions and billions of things that we need to manage. So we have a huge focus on scale and performance on a global basis and that's a mouthful, right? Not only are you dealing with large amounts at performance but you have to do it in a global fashion and make it possible for somebody who might be operating in a Southeast Asia to have the same experience with the environment as they would be in Los Angeles. And the data needs to therefore go to the user as opposed to having the user come to the data as much as possible. So it really does put a lot of emphasis on some of what you call the non-functional requirements also known as the ilities and so our ability to bring the data and handle those large enterprise grade capabilities at scale and performance globally is what's really driving a good number of our investments today. >> I want to talk about data quality. This is a hard topic, but it's one that's so important. And I think it's been really challenging and somewhat misunderstood when you think about the chief data officer role itself, it kind of emerged from these highly regulated industries. And it came out of the data quality, kind of a back office role that's kind of gone front and center and now is, you know pretty strategic. Having said that, the you know, the prevailing philosophy is okay, we got to have this centralized data quality approach and that it's going to be imposed throughout. And it really is a hard problem and I think about, you know these hyper specialized roles, like, you know the quality engineer and so forth. And again, the prevailing wisdom is, if I could centralize that it can be lower cost and I can service these lines of business when in reality, the real value is, you know speed. And so how are you thinking about data quality? You hear so much about it. Why is it such a big deal and why is it so hard in a priority in the marketplace? You're thoughts. >> Thanks for that. So we of course acquired a data quality company, not burying delete, earlier this year LGQ and the big question is, okay, so why, why them and why now, not before? Well, at least a decade ago you started hearing people talk about big data. It was probably around 2009, it was becoming the big talk and what we don't really talk about when we talk about this ever expanding data, the byproduct is, this velocity of data, is increasing dramatically. So the speed of which new data is being presented the way in which data is changing is dramatic. And why is that important to data quality? Cause data quality historically for the last 30 years or so has been a rules-based business where you analyze the data at a certain point in time and you write a rule for it. Now there's already a room for error there cause humans are involved in writing those rules, but now with the increased velocity, the likelihood that it's going to atrophy and become no longer a valid or useful rule to you increases exponentially. So we were looking for a technology that was doing it in a new way similar to the way that we do auto classification when we're cataloging attributes is how do we look at millions of pieces of information around metadata and decide what it is to put it into context? The ability to automatically generate these rules and then continuously adapt as data changes to adjust these rules, is really a game changer for the industry itself. So we chose OwlDQ for that very reason. It's not only where they had this really kind of modern architecture to automatically generate rules but then to continuously monitor the data and adjust those rules, cutting out the huge amounts of costs, clearly having rules that aren't helping you save and frankly, you know how this works is, you know no one really complains about it until there's the squeaky wheel, you know, you get a fine or exposes and that's what is causing a lot of issues with data quality. And then why now? Well, I think and this is my speculation, but there's so much movement of data moving to the cloud right now. And so anyone who's made big investments in data quality historically for their on-premise data warehouses, Netezzas, Teradatas, Oracles, et cetera or even their data lakes are now moving to the cloud. And they're saying, hmm, what investments are we going to carry forward that we had on premise? And which ones are we going to start a new from and data quality seems to be ripe for something new and so these new investments in data in the cloud are now looking up. Let's look at new next generation method of doing data quality. And that's where we're really fitting in nicely. And of course, finally, you can't really do data governance and cataloging without data quality and data quality without data governance and cataloging is kind of a hollow a long-term story. So the three working together is very a powerful story. >> I got to ask you some Colombo questions about this cause you know, you're right. It's rules-based and so my, you know, immediate like, okay what are the rules around COVID or hybrid work, right? If there's static rules, there's so much unknown and so what you're saying is you've got a dynamic process to do that. So and one of the my gripes about the whole big data thing and you know, you referenced that 2009, 2010, I loved it, because there was a lot of profound things about Hadoop and a lot of failings. And one of the challenges is really that there's no context in the big data system. You know, the data, the folks in the data pipeline, they don't have the business context. So my question is, as you it's and it sounds like you've got this awesome magic to automate, who would adjudicates the dynamic rules? How does, do humans play a role? What role do they play there? >> Absolutely. There's the notion of sampling. So you can only trust a machine for certain point before you want to have some type of a steward or a assisted or supervised learning that goes on. So, you know, suspect maybe one out of 10, one out of 20 rules that are generated, you might want to have somebody look at it. Like there's ways to do the equivalent of supervised learning without actually paying the cost of the supervisor. Let's suppose that you've written a thousand rules for your system that are five years old. And we come in with our ability and we analyze the same data and we generate rules ourselves. We compare the two themselves and there's absolutely going to be some exact matching some overlap that validates one another. And that gives you confidence that the machine learning did exactly what you did and what's likelihood that you guessed wrong and machine learning guessed wrong exactly the right way that seems pretty, pretty small concern. So now you're really saying, well, why are they different? And now you start to study the samples. And what we learned, is that our ability to generate between 60 and 70% of these rules anytime we were different, we were right. Almost every single time, like almost every, like only one out of a hundred where was it proven that the handwritten rule was a more profound outcome. And of course, it's machine learning. So it learned, and it caught up the next time. So that's the true power of this innovation is it learns from the data as well as the stewards and it gives you confidence that you're not missing things and you start to trust it, but you should never completely walk away. You should constantly do your periodic sampling. >> And the secret sauce is math. I mean, I remember back in the mid two thousands it was like 2006 timeframe. You mentioned, you know, auto classification. That was a big problem with the federal rules of civil procedure trying to figure out, okay, you know, had humans classifying humans don't scale, until you had, you know, all kinds of support, vector machines and probabilistic, latent semantic indexing, but you didn't have the compute power or the data corpus to really do it well. So it sounds like a combination of you know, cheaper compute, a lot more data and machine intelligence have really changed the game there. Is that a fair assumption? >> That's absolutely fair. I think the other aspect that to keep in mind is that it's an innovative technology that actually brings all that compute as close into the data as possible. One of the greatest expenses of doing data quality was of course, the profiling concept bringing up the statistics of what the data represents. And in most traditional senses that data is completely pulled out of the database itself, into a separate area and now you start talking about terabytes or petabytes of data that takes a long time to extract that much information from a database and then to process through it all. Imagine bringing that profiling closer into the database, what's happening in the NAPE the same space as the data, that cuts out like 90% of the unnecessary processing speed. It also gives you the ability to do it incrementally. So you're not doing a full analysis each time, you have kind of an expensive play when you're first looking at a full database and then maybe over the course of a day, an hour, 15 minutes you've only seen a small segment of change. So now it feels more like a transactional analysis process. >> Yeah and that's, you know, again, we talked about the old days of big data, you know the Hadoop days and the boat was profound was it was all about bringing five megabytes of code to a petabyte of data, but that didn't happen. We shoved it all into a central data lake. I'm really excited for Collibra. It sounds like you guys are really on the cutting edge and doing some really interesting things. I'll give you the last word, Jim, please bring us on. >> Yeah thanks Dave. So one of the really exciting things about our solution is, it trying to be a combination of best of breed capabilities but also integrated. So to actually create a full and complete story that customers are looking for, you don't want to have them worry about a complex integration in trying to manage multiple vendors and the times of their releases, et cetera. If you can find one customer that you don't have to say well, that's good enough, but every single component is in fact best of breed that you can find in it's integrated and they'll manage it as a service. You truly unlock the power of your data, literate individuals in your organization. And again, that goes back to our overall goal. How do we empower the hundreds of millions of people around the world who are just looking for insightful decision? Did they feel completely locked it's as if they're looking for information before the internet and they're kind of limited to whatever their local library has and if we can truly become somewhat like the internet of data, we make it possible for anyone to access it without controls but we still govern it and secure it for privacy laws, I think we do have a chance to to change the world for better. >> Great. Thank you so much, Jim. Great conversation really appreciate your time and your insights. >> Yeah, thank you, Dave. Appreciate it. >> All right and thank you for watching theCUBE's continuous coverage of Data Citizens'21. My name is Dave Vellante. Keep it right there for more great content. (upbeat music)

>>Hey guys, and gals. Welcome back to Las Vegas. Lisa Martin here at Coupa inspire 2022 with about 2,500 folks. Very excited to be back in person. I can assure you that is the vibe that is here to be. You joins me next to the managing director at KPMG Toby. It's great to have you on the program. >>Thanks. It's great to be here. >>Isn't it great to be back? I know it feels so normal. We were talking before we went live, that it feels normal. >>It does. It does. And it feels great. And after a great kickoff with, uh, with Rob >>Fantastic, Rob Bernstein has, and Barbara Corcoran, Rob has probably the highest energy of a CEO that I've ever gotten to work with. So you always know you're in for a good high energy conversation. Then Barbara Corcoran coming in, Jon Taffer with bar rescue is it's a, been a great morning so far. So you let's talk about you, you specialize in digital transformation within the procurement and the contract management spaces. Talk to me a little bit about that. >>Yeah, absolutely. You know, I, uh, I love helping folks to re-imagine their, uh, operating models to solve today's challenges. And there are so many challenges coming out in this post COVID world, um, that many of our clients are dealing with. And, and I'm never short on phone calls and, you know, uh, from, from my clients reaching out for help, um, to really figure out how to retool, um, and, and, and really help themselves to transform, to be able to address the, the, the changes to come. >>I heard a really smart description of the last two years today, compressed transformation. We've been talking about digital transformation for years, and then we've also been talking about it's acceleration during the COVID era, but the compressed transformation, I thought that's probably something that's here to stay. Nobody's going to want access to older, less data slower. >>Yep. >>They're just not >>A hundred percent. What >>Are some of the trends that you've observed in your role in the last couple of years? >>Yeah, I, I absolutely believe that folks that took advantage of that digital transformation pre pandemic have actually been able to fare much better than those that have held off on those investments. Um, for whatever reasons, you know, there are always different priorities, but those that have actually gotten that journey started, um, pre pandemic have definitely fared, uh, for, well, I think the trends that I'm seeing today, the CPO's challenge, um, and there are many challenges, um, but you know, the, you know, coming out of the, uh, post COVID era, you are now recovering and ramping up production as a result, your buying activities increasing, right. Um, and, and other ways other than increasing, um, activity. There's also the changing of requirements. So, you know, the folks in the front office are looking at new technologies to innovate new products and services, and that's going to change what the, the mix of the skills and resources that you need in the back office. >>Um, in addition to that, um, there are other requirements like ESG. And so as you're thinking about retooling and being able to, um, buy more sustainably or drive diversity, um, with the spend that you have, that's also changing the skill mix that you have. And I think on top of speak, uh, on top of that, um, the skills and the talent, we are dealing with the, a unfortunate situation that many companies are with the, uh, you know, the great resignation where the talent is, has as quickly exited the workforce. Um, and, uh, and, and with the demand increasing and changing, that puts everyone in a tough spot. And so those are really the big challenges that I've seen with the clients. Most recently, as we're coming out of COVID >>Of your customer conversations, escalated up the C-suite you talk, you mentioned the chief procurement officer. If we think of every company, these days has to be a data company to be successful. If they're not, they're probably not going to be around. Are you noticing that from a supply chain perspective within procurement and contract management, is that escalating the C-suite to be much more of a C-suite or board level initiative? >>Absolutely. Absolutely. I think what folks have realized in many of their, even the earlier digital transformation efforts, it was very geared around automating and streamlining transactions and processes, not so much putting data at the core. Yes, you would get intelligence out of that, but we hadn't architected your entire organization around data and good quality data and what is needed, um, to be able to actually translate that data to meaningful insights, to make the decisions or drive, um, visibility within to your, into your supply chain. Um, so when you think about things that are, um, such as ESG, where you really need to know, um, your tier one, tier two tier three suppliers, and all the impacts that that has, um, in order to drive to those, um, ESG objectives that you're telling your investors, you're telling your customers, and you're telling your, um, your employees about it's very important. You have to be centered around data and be able to be able to see their entire supply chain. And if you weren't, if you weren't architected to do so, doing it as an afterthought is very costly because you've already made those investments >>Very costly. And also, I mean, from a business perspective, I think, you know, we, we talk so often Toby and you probably do as well about it, business alignment. It's one of those, it's like digital transformation. It's almost a buzzword if you will, but it's critical because I'm seeing a lot of data and research from, from folks like Gardner that are showing that massive percentages of businesses believe that the technology is really the driver and the fuel of the business going forward. So no longer can it and lines of business be separated. >>Yeah, I, I totally agree. I actually think that when I mentioned about new skills, if you think about the next generation and the new operating models, um, uh, you know, the, the, the new folks coming out of college have to have that skill set because process and technology are, are, are completely linked. Um, and I think that the organizations, the future and the sick, the most successful ones will know how to actually be more human centric and be able to harness the data through the technologies. So I'll actually allow you and I to do what we do best, right, which is collaborate and negotiate deals work on our relationship versus focused on the technology or entering data into forms and all the administrative components that, uh, many of my clients are plagued with today, >>Collaboration, I think has maybe become even more important in the last two years that we've been so limited about how to collaborate. Thankfully, we have a lot of technologies to do that, but when I think of Coupa collaboration, community are two words that jump out. Talk to me a little bit about from an, a partnership perspective alignment there with the collaborative spirit at KPMG. >>Yeah, absolutely. Um, you know, for, for us, uh, I recently just presented on a very similar topic that nothing great in business is done by a single person. And it takes partners to be able to drive the innovation needed to solve the new challenges of tomorrow. And, and I see our relationship with that. You know, they offer a platform, they offer a method to get access to the data and simplify it in a way for our clients so that they can focus on the relationships and driving the collaboration with their suppliers. And, and I think that that's, that's the thought leadership, uh, in partnership with, uh, with them that we'd like to bring to the table. >>Speaking of alignment between KPMG and Qubit. Talk to me a little bit about ESG as, as sort of a new initiative within KPMG. Talk to me a little bit about that. And what's some of the high level objectives are >>Absolutely. Um, I wouldn't say that it's, it's, it's new. I think it's always been there and there's always been a focus, but I think the recent events and with the regulatory environment changing as well, and as with consumers, consumer behavior, driving and investor community driving towards, um, uh, ESG, I think that is quickly changing how companies are prioritizing that within the Mo amongst everything else that they have. And as a result, I think the CPO's role in that equation is ever so important when it comes to delivering and operationalizing ESG. >>I imagine it, the CPS role must be a lot more strategic these >>Days >>Because they really have to be kind of a transformation change agent. >>Yeah. And actually in most cases, the CPO is perfect for that because that's been their role, um, in, uh, in, in, uh, in many cases before. Um, and I think, yeah, this is just yet another dimension that they didn't have to attack and, and incorporate into the, uh, into the process of selecting the right partner or the right supplier within their, um, within the, uh, with, with who they want to onboard for, for the company. >>Got it. Okay. Let's talk about advice now for companies that are either in the early stages of the supply chain transformation really digitizing, how do they get started? Is it too late for some? >>No, I don't think it's ever too late. I don't think, I, I think, um, I don't think it's too late, you know, and especially with the very big focus on digital and tech these days, sometimes being the late, being late to the game allows folks to actually work out the kinks for, you know, the bleeding edge technologies. And so that makes it even less risky for them to adopt in, in many cases. Um, that's, that's, uh, that, that's what we've seen, but, you know, I think the advice is get educated, uh, really just understand as much as you can around what other people are doing. Are there other, um, uh, peer group, uh, companies like yours, you know, like themselves that are actually going through the transformation or have gone before and just kind of understand what were the drivers of that strategy and what were the outcomes that you can learn from them, get help from externals. >>Um, and whether they be technology partners, consultants, and actually hiring new skills and bringing in new perspectives to help you to own and drive that strategy important. This is super important and you can't outsource these things, right. This needs to come from within, especially when you think about things as purposeful and impactful as ESG. Um, those, those cannot be outsourced. Um, and I think those would be the, uh, the kind of the two key things. Um, but I always also say, um, take an outward in approach, as you're thinking about your new strategy, focus on what your employees are saying about, you know, your supply chain and how easy it is to actually understand and, and work within your supply chain. Talk to your suppliers, talk to your internal business partners, to really reflect and understand how do you make this process as easy as possible for them to comply with. >>I think one of the things I was reading, uh, in preparation for coming here is that some, some survey, a survey that that Cooper did of about 800 decision makers. And one of the things that was overwhelming as a theme is that a lot of organizations don't feel that they have the right data visibility to drive an ESG strategic initiative. So what Coupa does providing that visibility and the ability to collaborate and share across the community is, seems to be something that's going to be a business critical must have going forward. >>Yeah, a hundred percent, you know, many, uh, many of our clients operate under, you know, uh, not under like mandates or compliance, driven, um, kind of policies in the commercial world, many cases you have to influence the buying behavior. And so you can't do that without data. I'd like to think in this day and age presented with the right supplier options with them at the right point in time, you're able to influence and drive the spend to diverse candidates, sustainable options, you know, and there's, you know, not just savings, not just the lowest cost option, but there's so many other things to consider in this day and age. And I think that's where it's so important to be able to have a platform like Hoopa, to be able to gather that data acquire external sources of data, such as ESG related data and make that to, um, to, to all parties, um, and be that source of truth so that you can drive the >>Here's some truth. And also even something that was talked about this morning during the keynote is accountability. And have you heard Jon Taffer from bar rescue talking this morning, but he was talking about an 120 bar rescues. He goes, I've never met one person that has admitted from day one of the four days. They shoot that I'm responsible for the reason that my business is not successful. He goes, everybody has an excuse. There's no accountability until you really force someone to take probably that hard look in the mirror that they don't want to take, but that accountability within organizations within an overall business is critical. >>Yeah, I think, uh, I absolutely believe that went away to solve that is providing the data and making it available. And, um, and really once again, I think it goes back to driving that behavior that you want. And I think it starts with, uh, with, with leadership and I think the accountability, accountability of leadership, and to be able to drive that type of culture within your organization. Um, but absolutely you need data to be able to do that and, and be able to monitor that as well, you know, as a leader to make sure that that accountability is appropriately distributed. >>Right. But one of the things, I mean, I think patients has been in short supply the last two years have been, we've learned that. I think also that another thing we've learned is that access to real-time data is no longer, oh, then that would be great. It's you've got to have that for your business to be differentiated because the, you know, if we think about the consumer side, the consumers are so vocal on things like social media, if the experience isn't tailored, personalized and instantaneous, We have a very short Rob talked about the very short attention span that his kids have. I'm like three minutes. We don't even have that in business or on the consumer side. I don't think. >>Yeah, I, yeah, I see that in my kids and what he said today was, was spot on. Um, so, you know, when I think about my career and where I'm at, and he said the same thing, I mean, our kids are coming into the, there'll be in procurement organizations very soon, sooner than, you know, then, then I like to admit. Um, and as a result, I think that, um, we talked a bit about talent shortage and the challenge with keeping talent. And I think that what you had just expressed is very important is that that experience for the employee, but you come into a workforce and they expect you to have these quick turnarounds, but you've, you offered them tools that require spreadsheets and old archaic systems to be able to solve today's challenges. I think that you're not going to be able to retain your talent right along. Right. >>That's a great point. That's an absolutely fantastic point. Last question for you before we wrap here is so the changes that organizations need to make with respect to being prepared for ESG reporting requirements that are coming down the pike, obviously being, having a data strategy has got to be one of us. >>Yeah, absolutely. I think, um, I think we, many procurement organizations were really geared around savings and a very compliance, driven manner. And when you think about ESG, I think you gotta be very data-driven. Um, and so that should be a priority focus of how do you retool yourself to be able to acquire mass amounts of data, figuring out where you need to go, um, to get that data, whether they be third parties, whether they be directly from the supplier, um, and be able to aggregate it and provide the insight into those reporting standards that are required. Um, and then to be able to actually measure progress along those sustainability or diversity goals that it might be established at, at, at the leadership level. So I think it's coming down the pike. It's a matter of time. I think it's, I think it's, uh, you know, it's something that I've been waiting for to see. Um, and it's interesting to see how, uh, how quickly that it's, it's come down. Um, but I think with the regulatory compliance coming down, um, this is going to be moving very quick and people need to get ready. >>That's good. They need to be ready. Excellent to be thank you for joining me on the program today, talking about what you were doing at KPMG, what it's doing with Kupa and how organizations really should be thinking about and approaching supply chain, digital transformation. We appreciate your insights. >>Yeah, absolutely. Thank you so much. All >>Right. For Toby, you I'm Lisa Martin. You're watching the cube in Las Vegas at Cooper inspire 2022 stick around. My next guest will join me shortly.

(upbeat music) >> The Cloud essentially turned the data center into an API and ushered in the era of programmable infrastructure, no longer do we think about deploying infrastructure in rigid silos with a hardened, outer shell, rather infrastructure has to facilitate digital business strategies. And what this means is putting data at the core of your organization, irrespective of its physical location. It also means infrastructure generally and storage specifically must be accessed as sets of services that can be discovered, deployed, managed, secured, and governed in a DevOps model or OpsDev, if you prefer. Now, this has specific implications as to how vendor product strategies will evolve and how they'll meet modern data requirements. Welcome to this Cube conversation, everybody. This is Dave Vellante. And with me to discuss these sea changes is Ajay Singh, the Chief Product Officer of Pure Storage, Ajay welcome. >> Thank you, David, gald to be on. >> Yeah, great to have you, so let's talk about your role at Pure. I think you're the first CPO, what's the vision there? >> That's right, I just joined up Pure about eight months ago from VMware as the chief product officer and you're right, I'm the first our chief product officer at Pure. And at VMware I ran the Cloud management business unit, which was a lot about automation and infrastructure as code. And it's just great to join Pure, which has a phenomenal all flash product set. I kind of call it the iPhone or flash story super easy to use. And how do we take that same ease of use, which is a heart of a Cloud operating principle, and how do we actually take it up to really deliver a modern data experience, which includes infrastructure and storage as code, but then even more beyond that and how do you do modern operations and then modern data services. So super excited to be at Pure. And the vision, if you may, at the end of the day, is to provide, leveraging this moderate experience, a connected and effortless experience data experience, which allows customers to ultimately focus on what matters for them, their business, and by really leveraging and managing and winning with their data, because ultimately data is the new oil, if you may, and if you can mine it, get insights from it and really drive a competitive edge in the digital transformation in your head, and that's what be intended to help our customers to. >> So you joined earlier this year kind of, I guess, middle of the pandemic really I'm interested in kind of your first 100 days, what that was like, what key milestones you set and now you're into your second a 100 plus days. How's that all going? What can you share with us in and that's interesting timing because the effects of the pandemic you came in in a kind of post that, so you had experience from VMware and then you had to apply that to the product organization. So tell us about that sort of first a 100 days and the sort of mission now. >> Absolutely, so as we talked about the vision, around the modern data experience, kind of have three components to it, modernizing the infrastructure and really it's kudos to the team out of the work we've been doing, a ton of work in modernizing the infrastructure, I'll briefly talk to that, then modernizing the data, much more than modernizing the operations. I'll talk to that as well. And then of course, down the pike, modernizing data services. So if you think about it from modernizing the infrastructure, if you think about Pure for a minute, Pure is the first company that took flash to mainstream, essentially bringing what we call consumer simplicity to enterprise storage. The manual for the products with the front and back of a business card, that's it, you plug it in, boom, it's up and running, and then you get proactive AI driven support, right? So that was kind of the heart of Pure. Now you think about Pure again, what's unique about Pure has been a lot of our competition, has dealt with flash at the SSD level, hey, because guess what? All this software was built for hard drive. And so if I can treat NAND as a solid state drive SSD, then my software would easily work on it. But with Pure, because we started with flash, we released went straight to the NAND level, and as opposed to kind of the SSD layer, and what that does is it gives you greater efficiency, greater reliability and create a performance compared to an SSD, because you can optimize at the chip level as opposed to at the SSD module level. That's one big advantage that Pure has going for itself. And if you look at the physics, in the industry for a minute, there's recent data put out by Wikibon early this year, effectively showing that by the year 2026, flash on a dollar per terabyte basis, just the economics of the semiconductor versus the hard disk is going to be cheaper than hard disk. So this big inflection point is slowly but surely coming that's going to disrupt the hardest industry, already the high end has been taken over by flash, but hybrid is next and then even the long tail is coming up over there. And so to end to that extent our lead, if you may, the introduction of QLC NAND, QLC NAND powerful competition is barely introducing, we've been at it for a while. We just recently this year in my first a 100 days, we introduced the flasher AC, C40 and C60 drives, which really start to open up our ability to go after the hybrid story market in a big way. It opens up a big new market for us. So great work there by the team,. Also at the heart of it. If you think about it in the NAND side, we have our flash array, which is a scale-up latency centric architecture and FlashBlade which is a scale-out throughput architecture, all operating with NAND. And what that does is it allows us to cover both structured data, unstructured data, tier one apps and tier two apps. So pretty broad data coverage in that journey to the all flash data center, slowly but surely we're heading over there to the all flash data center based on demand economics that we just talked about, and we've done a bunch of releases. And then the team has done a bunch of things around introducing and NVME or fabric, the kind of thing that you expect them to do. A lot of recognition in the industry for the team or from the likes of TrustRadius, Gartner, named FlashRay, the Carton Peer Insights, the customer choice award and primary storage in the MQ. We were the leader. So a lot of kudos and recognition coming to the team as a result, Flash Blade just hit a billion dollars in cumulative revenue, kind of a leader by far in kind of the unstructured data, fast file an object marketplace. And then of course, all the work we're doing around what we say, ESG, environmental, social and governance, around reducing carbon footprint, reducing waste, our whole notion of evergreen and non-disruptive upgrades. We also kind of did a lot of work in that where we actually announced that over 2,700 customers have actually done non-disruptive upgrades over the technology. >> Yeah a lot to unpack there. And a lot of this sometimes you people say, oh, it's the plumbing, but the plumbing is actually very important too. 'Cause we're in a major inflection point, when we went from spinning disk to NAND. And it's all about volumes, you're seeing this all over the industry now, you see your old boss, Pat Gelsinger, is dealing with this at Intel. And it's all about consumer volumes in my view anyway, because thanks to Steve Jobs, NAND volumes are enormous and what two hard disk drive makers left in the planet. I don't know, maybe there's two and a half, but so those volumes drive costs down. And so you're on that curve and you can debate as to when it's going to happen, but it's not an if it's a when. Let me, shift gears a little bit. Because Cloud, as I was saying, it's ushered in this API economy, this as a service model, a lot of infrastructure companies have responded. How are you thinking at Pure about the as a service model for your customers? What's the strategy? How is it evolving and how does it differentiate from the competition? >> Absolutely, a great question. It's kind of segues into the second part of the moderate experience, which is how do you modernize the operations? And that's where automation as a service, because ultimately, the Cloud has validated and the address of this model, right? People are looking for outcomes. They care less about how you get there. They just want the outcome. And the as a service model actually delivers these outcomes. And this whole notion of infrastructure as code is kind of the start of it. Imagine if my infrastructure for a developer is just a line of code, in a Git repository in a program that goes through a CICD process and automatically kind of is configured and set up, fits in with the Terraform, the Ansibles, all that different automation frameworks. And so what we've done is we've gone down the path of really building out what I think is modern operations with this ability to have storage as code, disability, in addition modern operations is not just storage scored, but also we've got recently introduced some comprehensive ransomware protection, that's part of modern operations. There's all the threat you hear in the news or ransomware. We introduced what we call safe mode snapshots that allow you to recover in literally seconds. When you have a ransomware attack, we also have in the modern operations Pure one, which is maybe the leader in AI driven support to prevent downtime. We actually call you 80% of the time and fix the problems without you knowing about it. That's what modern operations is all about. And then also Martin operations says, okay, you've got flash on your on-prem side, but even maybe using flash in the public Cloud, how can I have seamless multi-Cloud experience in our Cloud block store we've introduced around Amazon, AWS and Azure allows one to do that. And then finally, for modern applications, if you think about it, this whole notion of infrastructure's code, as a service, software driven storage, the Kubernetes infrastructure enables one to really deliver a great automation framework that enables to reduce the labor required to manage the storage infrastructure and deliver it as code. And we have, kudos to Charlie and the Pure storage team before my time with the acquisition of Portworx, Portworx today is truly delivers true storage as code orchestrated entirely through Kubernetes and in a multi-Cloud hybrid situation. So it can run on EKS, GKE, OpenShift rancher, Tansu, recently announced as the leader by giggle home for enterprise Kubernetes storage. We were really proud about that asset. And then finally, the last piece are Pure as a service. That's also all outcome oriented, SLS. What matters is you sign up for SLS, and then you get those SLS, very different from our competition, right? Our competition tends to be a lot more around financial engineering, hey, you can buy it OPEX versus CapEx. And, but you get the same thing with a lot of professional services, we've really got, I'd say a couple of years and lead on, actually delivering and managing with SRE engineers for the SLA. So a lot of great work there. We recently also introduced Cisco FlashStack, again, flash stack as a service, again, as a service, a validation of that. And then finally, we also recently did a announcement with Aquaponics, with their bare metal as a service where we are a key part of their bare metal as a service offering, again, pushing the kind of the added service strategy. So yes, big for us, that's where the buck is skating, half the enterprises, even on prem, wanting to consume things in the Cloud operating model. And so that's where we're putting it lot. >> I see, so your contention is, it's not just this CapEx to OPEX, that's kind of the, during the economic downturn of 2007, 2008, the economic crisis, that was the big thing for CFOs. So that's kind of yesterday's news. What you're saying is you're creating a Cloud, like operating model, as I was saying upfront, irrespective of physical location. And I see that as your challenge, the industry's challenge, be, if I'm going to effect the digital transformation, I don't want to deal with the Cloud primitives. I want you to hide the underlying complexity of that Cloud. I want to deal with higher level problems, but so that brings me to digital transformation, which is kind of the now initiative, or I even sometimes call it the mandate. There's not a one size fits all for digital transformation, but I'm interested in your thoughts on the must take steps, universal steps that everybody needs to think about in a digital transformation journey. >> Yeah, so ultimately the digital transformation is all about how companies are gain a competitive edge in this new digital world or that the company are, and the competition are changing the game on, right? So you want to make sure that you can rapidly try new things, fail fast, innovate and invest, but speed is of the essence, agility and the Cloud operating model enables that agility. And so what we're also doing is not only are we driving agility in a multicloud kind of data, infrastructure, data operation fashion, but we also taking it a step further. We were also on the journey to deliver modern data services. Imagine on a Pure on-prem infrastructure, along with your different public Clouds that you're working on with the Kubernetes infrastructures, you could, with a few clicks run Kakfa as a service, TensorFlow as a service, Mongo as a service. So me as a technology team can truly become a service provider and not just an on-prem service provider, but a multi-Cloud service provider. Such that these services can be used to analyze the data that you have, not only your data, your partner data, third party public data, and how you can marry those different data sets, analyze it to deliver new insights that ultimately give you a competitive edge in the digital transformation. So you can see data plays a big role there. The data is what generates those insights. Your ability to match that data with partner data, public data, your data, the analysis on it services ready to go, as you get the digital, as you can do the insights. You can really start to separate yourself from your competition and get on the leaderboard a decade from now when this digital transformation settles down. >> All right, so bring us home, Ajay, summarize what does a modern data strategy look like and how does it fit into a digital business or a digital organization? >> So look, at the end of the day, data and analysis, both of them play a big role in the digital transformation. And it really comes down to how do I leverage this data, my data, partner data, public data, to really get that edge. And that links back to a vision. How do we provide that connected and effortless, modern data experience that allows our customers to focus on their business? How do I get the edge in the digital transformation? But easily leveraging, managing and winning with their data. And that's the heart of where Pure is headed. >> Ajay Singh, thanks so much for coming inside theCube and sharing your vision. >> Thank you, Dave, it was a real pleasure. >> And thank you for watching this Cube conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

>>long from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Welcome back to the Cube. Lisa Martin live on the show floor of AWS. A re in that 19 was stupid. And then this is the almost the end of our second day of coverage. And as we were just saying, There's more people in here now than there were probably a couple of hours ago. 65,000 or so folks that AWS is expecting here and I think they're all in the Expo Hall now. Sue and I are pleased to welcome from Amazon business. David Stout, the head of global alliances and partnerships. Stephen, welcome to the Cube. >>Thanks so much for having me excited because this afternoon, >>so everybody on the planet knows amazon dot com. It has transformed our lives. I also think that it's transformed us as consumers and put pressure on any business, be able to deliver to us what we want whenever way wanted >>everybody. This week's getting alerts on their phones of package deliveries. >>Yes, that's why you one of the best parts of your day is when that Amazon package shows up and it's so fast. I always forget what's really order. Hope is for me. But I'd love for you to share with our audience what Amazon businesses. >>So obviously, you just said we all know about Amazon. We'll know about eight of us, right? 65,000 people here this week. Amazon businesses, a group that's been around since 2015 and we're focusing specifically on the needs to procure it needs of business and institutional customers. >>So the big theme that we heard from Andy Jassy was talking about transformation. We can't incrementally change the environment, so tell us a little bit what happens in your space and how that ties in tow, those transformations a couple things. So so one we like. I >>said, we start in 2015 focusing on both private and public sector customers, and what we're really trying to focus on is that experience you talked about For consumers taking that same ease of use and experience to the business world, corporate chairman is really hard and cumbersome. There's a lot of tools that need to be in used, and so we're trying to drive that same ease of use into the corporate and public sector world as well. So one of things that we've done way launched 2015. As I said, way don't share a lot of details. But we did about a year ago announced that we're on about a $10 billion annualized run rate. We're in nine countries around the world so outside the United States were also live in Germany, United Kingdom, France, Italy, Germany, Spain, India, France, Sorry, India, Japan and just announced last month in Canada. So it's, ah, fast growing business and we continue to try to find ways our customers are great to give us feedback on how we can continue to innovate to serve their needs. >>Yeah, you know, it's funny. I have some history, my career, working with procurement organizations, and change is not something I hear from them. When I think of public sector, it's like, Well, it's on the G s, a contract negotiated from the years when you go to companies and you say, Hey, we've got the new product. Oh, well, I got to go through the procurement cycle to get that through these environments. So how do we make sure that companies can take the innovation, you know, be agile and, you know, take advantage of these things now from a human standpoint, yes. So there's >>a couple things. So one this week you're here in a town about digital transformation, right? Something that isn't an event. It's an ongoing evolution, one of things you know, We've been coming to to reinvent for four years now, and what we're seeing and continually saying, is that there's a convergence between the I T strategies and the procurement strategies. A lot of that is happening through technology and enabling a new technology. But it za super interesting observation for us sitting on the sidelines and helping drive some of that innovation for customers. >>The rule of the chief procurement officer has changed a lot in recent years alone. Where this rose. You're saying there's this now convergence with I T. But the CPO has a much bigger opportunity now to become much more of a strategic driver of business, whether it's evaluating supply chain management and looking for ways to streamline operations. Big shift from the financial perspective, Dr Spell some of the things that Amazon business is seeing in your customers and how it is enabling those two sides the I t folks on the procurement folks to come together so that what they're enabling is that digital business transfer. >>Yeah, absolutely so historically procurement teams up CPS and their teams were responsible for very traditional things. Sourcing contract management, risk management, supplier on boarding and off, boarding compliance with you to your point earlier still on regulations and is it on a schedule or not? Those >>are all >>still really important attributes and will continue to be a huge focus areas for those organizations. But I think with the advent of technology, what you're starting to see is a lot more focus on how to use artificial intelligence. How do we use our P? A. How do we use use machine learning to find new opportunities to Dr Efficiencies within those operations? And so I think because of that, what you're starting to see is a lot more harmonization between what see peos are thinking about. The strategy is employing and the c i ose and we're releasing a convergence between those two organizations. Republished. Amazon Business published an article with Procure Con a couple months ago. One of the findings that came out of that study was that there is a convergence happening. Over 55% of the respondents said that their goals are either fully aligned or mostly align with the goals of of the C. I. A. Organization. So we're works pretty excited about that happening. We think that we're gonna be helping customers continue to drive that collaboration and for forward thinking organizations that are trying to drive more technology way believe it's gonna be a requirement in essential. >>That's awesome. It aligns with some of the broader trends we've been seeing in cloud adoption overall, it can't be. I t in the business separately, doing their things. Help us understand how this movement forward translates into innovation for for customers. Yeah, >>so a couple things come to mind, um, eight of us things number things happening here. Eight abyss yesterday, oftentimes is sorry. Oftentimes eight of us is considered as a starter for when you think about digital transformation and cloud transformation. Um, pace of that evolution is amazing, right? Yesterday there were 14 press releases issued on new technologies and capabilities that AWS is delivering directly or through partners and I think those types of things we're helping drive that pace of evolution we talked about earlier. One of the things that I found really interesting is eight of us as a partner network. It's very mature. There's tens of thousands of partners. They launched it in 2013 and it's a huge portion of their business and growth. Amazon business is much younger in our in our maturity on we're just starting to Launch a partner network. One of things were really interested in is how do we work with third party organizations, and my team's responsible for really extending the range and reach of our traditional sales, marketing and service's channels by working with third parties. Those take the forms of primarily software companies. So you see Air P organizations, a procurement platforms and accounting expense management platforms is examples there and in the infrastructure providers that leverage that. So Octa eyes an identity management provider, their sponsor of reinvent this year they're our partner of Amazon business, and we've built a pre configured integration that will allow Octa customers that you're using a single sign of product to access the Amazon business, uh, store easily and within the controls that they've established >>it. Actually, we just had Dave McCann from the eight of us Marketplace on the program earlier, and we've watched the evolution in maturation of marketplace. How does that tie underworld allowing? Really? You know, I I've been going for years. It is close, is what we have to the enterprise app store there. So how does this play into your s? So, you know, I think there's gonna continue to be >>convergence between Amazon business in AWS overtime in the marketplace, we offer kind of a goods marketplace. They offer a software marketplace in a service marketplace. And so I think we're still working on how do we harmonize that experience better. And we've got a lot of work to do there. We have a saying in Amazon that it's always Day one, and that's a great example where we still have a lot of work to do. One >>of the >>things that is another one of our partners, Cooper, which is procure to pay platform and a long time Amazon business partner we've done some pretty creative things to improve the user experience and make it easier for customers is both Cooper and Amazon business and concert Together announced couple months ago. They've built an integration to the eight of US marketplace. And so that's a pretty exciting opportunity where people who are provisioning service is via a theatre. Best marketplace gonna have transaction, flows seamlessly into their, procured up a solution and let you know the user whose provisioning that focus on what they want to do, which is developing new solutions to serve customers. >>Yeah, Cooper is one of our cube clients. I was just covering their event Cooper London just a few weeks ago. One of the things that's interesting about them, and I'd love to get your feedback on the is their community is really massively influential in their technology, and I presume in terms of the partnerships that they forge and as really catalysts for that procurement role being so strategic to the business. Talk to us about some of the customers that you are working with, and there's third party folks as well. How are the influencing the road map of Amazon business? >>Yeah, so our customers are never shy to tell >>us that's a >>pretty right, and that's one of the things that we've been able to grow so quickly, right? So we have. We've segmented our business into four verticals who focus on health care, education, government and then commercial, which is our largest segment. We have custom invites your boards from each one of those segments and those air very intimate working sessions with everyone from micro customers up to Fortune 100 customers that are never shy, as I said to provide feedback on what we need to do better. I was with a client last week who and one of our partners who It was great to hear them say way. They just have been a at a customer advisory board. And we love the fact that those features we suggested to you 12 months ago are now in production. And so it's a huge part of what we do. It's a huge part of what drives our road map. Wey have probably the most sophisticated voice of customer feedback monitoring systems that I've seen, and that includes everything from, you know, our sales professionals talk to customers and log that feedback on future requests to monitoring social feeds to understanding what our customers want. So it's ah, it's a big part of what we do and how we do it. And I think it's one of the things that makes Amazon a really differentiated company business overall. >>All right. So, David, I think most people not only did the no Amazon, but many of them, including disclaimer myself, our Amazon prime customers. You'll have something called Business Prime. Maybe explain a little bit what that is. S >>O. So most of us are prime members as consumers, and there's a number of features to come with that. There's a shipping program, which is where it started, and then we've had a different solutions. Whether it's music or video, there are storage. Amazon business has the same philosophy. And so right now there are. We have a business prime shipping program, which was launched two years ago. We also have a other business prime offerings, including advanced analytics. So within Amazon business, them's on business portal. You can actually look at spend categorization, and we've got some pretty powerful data visualization capabilities, its prime benefit, and we have a pretty extensive road map for other features that are going to continue to come. We have financing vehicles that are tied to it already, and there's there's a lot on the road mouth. >>Well, if you need two more business videos for your business, prime customers, give us a call. We have a large library with Amazon for >>that year for seeing that, you know, >>let's talk about security. It is a fundamental component of any organization because there is so much data and we're only generating more and more and more businesses need to ensure that how they're transacting with any organization and that their data is managed in a secure way. What are some of the fundamental elements of Amazon business that you guys have built into the technology to delay liver that security for your business customers? >>First of all, we're built fully on AWS, as you'd expect, and so there's There's a >>happy about that, by the way. >>So there's there's that's that's just a safety feature that I think it gives most of his comfort. I think back to this kind of notion of convergence of I t and procurement. This is something I find really interesting. And so, um, this prick your con article I mentioned a few minutes ago one of the findings and that was that 70% of organ of respondents said that their security strategy is shared jointly between their i t and the procurement teams. And so obviously security here it reinvent you walked the expo floor. There is an entire row of things that are focused on security and how to continue to drive that within the cloud in an efficient way. This whole concept of I t and procurement coming together share objectives. I think that's a great example where it's already happening, and we continue to expect that it will happen in more detail. >>What are some of the things that surprised you most about the last day and 1/2 with all the announcements that folks understanding more about Amazon business, some of the feedback that you've gotten on the show floor or in customer meetings that the kind of highlight? Yeah, we're doing the right thing. Here >>S o. I think >>for it's always humbling when people don't know about us, right, Asai said. We've built a pretty big business, but it's still really, really early on dso It's to me that's a great opportunity that we can continue to be more to educate customers about the opportunity and how Amazon can help transform their procurement practices. It's still super release, so we're always wanting to hear that feedback. And what else could we d'oh For customers that are aware of us? What's been really also humbling is how much they're finding us to be a bigger and bigger portion of their strategic vision in the future. And so we're really excited about that on both fronts, right? The opportunity to Maur, but also that customers who are adopting us or seeing great opportunities to consolidate their suppliers Dr Greater Efficiencies and, most importantly, provide a better end user experience that they're used to from their home. Purchasing >>of this last question for you Looking at the vertical focus that you guys are taking, you mentioned the verticals, any of them in particular that are really kind of leading the way here. For that I t procurement strategic collaboration. You mentioned healthcare, commercial, anything that you really see as early adopters leading edge. >>So we actually see there's probably some some nuances between each vertical, but we've seen some great adoption across all for those vertical. So we have 55 of the Fortune 100 as customers. We have 80% of the largest educational institutions in the U. S. Is customers. We have a greater than 50% of the largest health systems in the U. S. Is customers already and greater than 40% of the largest municipalities in United States. So so we've seen some really great adoption across all four segments. Again, I think the needs of a small dentist's office are gonna be different than the needs of industrial manufacturing organization. And so we continue to find solution sets with little dress, the needs of each one of those customers. We have strategic teams that are focused specifically on the segments and how to solve them. And as I said before, customers will always tell us what we could do better at >>that. Really, >>What drives our innovation >>and where can folks go? Business owners small enlarged to learn more about Amazon business >>amazon dot com slash business >>Easy, David. Thank you for joining student on a program and sharing with us What Amazon business as we appreciate it. >>Very welcome. Thanks for having me. >>Alright. First the Minutemen. I'm Lisa Martin and you're watching the Cube from Day two of our coverage of aws reinvent 19 from Vegas signing off. Thanks for watching

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired 2019. Brought to You by Cooper. >> Welcome to the Q. But Lisa Martin on the ground in Las Vegas for Cooper Inspire. 19 Hot Vegas. Fresh Insight. I'm pleased to welcome Max Ground, the managing director from Deloitte to the program. Hey, Max. >> Good morning. Good afternoon. >> Good afternoon. Whatever time it is, Vegas Right here is this. It's a time warp. They don't like you see outside It's >> only place the world. The 25th hour. >> Right? So here we are. It inspired 19 kick Everything kicked off this morning with the general session. I was teasing Rob Bernstein a couple hours ago and I had him on that. I learned three things in the general session. He likes pizza, he likes kittens. And Cuba's platform now has 1.2 trillion dollars of spending data going through it. And I thought, man procurement is not what I thought. It wa ce and you have a really >> interesting story about procurement. I'd love for you to share with our audience >> because you said in your session earlier today you said people in this standing your morning session. How many of you wanted to be on procurement? Anybody that raises their hands of line tell me about the procurement of yesterday, the >> opportunities that it's given you and what it is now. >> So I think >> in the past, >> security has been something that had to happen. It was a must have not a place that people saw value. But was the rule enforcers right? So trying to do that and really adding value by discipline, where today, if you think about it, the value that they can add by driving savings authorization drops right to the bomb line. So all the savings that are out there, all >> the negotiations that are doing, it's really unique skill set >> and something that people really should move into finance folks when they're looking for a new opportunity. It's a great skill set to have. Lately I've come across a former attorneys are practicing law but now doing strategic sourcing, doing procurement, work, people from finance because the talent that you have to have is field work with people within their companies, understand their needs, negotiate with suppliers, do hard core analytics and, oh, by the way, we're talking about Cooper has helped in change and implemented technology like that. It's really fascinating. >> It's so much more than >> being a buyer or being somebody that's controlling a particular business unit's ability to buy and spend. >> One of the interesting things about Cooper is this platform that allows what started, I >> think, initially as more procurement corner invoicing is now expanded to also include payments and expenses and travel management and contingent workhorse management. So what the CPO now has the opportunity to do is get this visibility right across an entire business of all of the spending, to your point, make massive impacts to the bottom line. >> Yeah, I >> mean, data is so important, right? In the past, the vendors had all the information. Why? Because the sales people how to get commissions. They knew exactly what was being bought of that company. Today, you can reverse engineer saying, selling cells. I say it's reverse sales. I can't go in there and I tell them now I have the full picture. So if it's divided up that category by three or four different vendors, they're making assumptions about how much market share they have. I know it all. I can create a model, a pricing model on the reverse. Engineer it. It's really for sales. I'm telling them now why they should give me a great discount for the organization and >> I >> have the ability to actually enforce that and drive the savings that we have for the organization. It also helped them drive their numbers on sales. So it's a mutually beneficial relationship. They have more market share. I drive better value for the organization. It really works well, >> Well, one of the destructor is that you're kind of alluded to Is this consumer ization? You know, when you go to buy >> a car these days, you just walk in there. You have as a as a buyer of the consumer oven automobile. You have access to every piece of information possible, the whole transaction process. The sales process is different. So as consumers in our regular lives, we have so much expectation that weaken, find anything good Amazon, find anything that we want, get it delivered tomorrow and have all these information on what? Where's the best place I could get it? Who's selling it for what? How is this person that you know, more trustworthy supplier So this consumer ization element and how it's changing the role of the CPO in the CFO is >> really revolutionary. >> It really isn't so you think about it. Most of us go out to Amazon by something, and really the only control there for me, for example, is my wife has to approve it, right, so that's the only veto authority. So that's really the only difference between the two platforms. If you think about it is, there's controls in place, so you're doing the right thing. But from an end user perspective, if I go out there and find the right item and again in Amazon, I don't to go find the supplier. I don't know if that be on contract. Why don't you do that work? We shouldn't have to. I should just go out there and say, I need this And in the background, Cooper is working all those things, presenting the right products on the right contracts, driving right value and almost is important, minimizing the risk. So across all those different lenses, you see why the value of Cooper is for the end user. They're getting what they need for the organization, for the company we're reducing risk and we're increasing value, and then you have rich reporting on the back end. So it's just it's a great way of doing business. It really is taking what you used to do or what you do. It's Sunday afternoon like Rob, you say Monday at work, and I think that's really powerful thing of perspective. >> It is. And it can be so impactful if applied in the right way with an organization, whether it's a manufacturer or hospital or retailer that has a culture that is willing to embrace change, right? I mean, there's that right, Especially >> get him to get your >> perspective on when you're implementing Cooper at a large organization. Maybe have been around for many, many years versus maybe a more modern that we think might be more nimble organization. Culturally, Do you see massive differences in how they're leading procurement, and are you able to sort of level the playing field and show them doesn't matter what your culture is? Here's how your business, your body. >> So from a change perspective, I think there's a different perception. The newer, nimbler organization believes that they changed easy, but it still may have people the older organisation again still made people most people don't like to change. What I have learned is if you help them understand the value of it, how they're doing it, how their jobs are going to change and give them the tools to do it. Some people are gonna be early adopters. But finding that one person, the organization, no matter what level they are in that business unit or in that department that has that informal voice that people look to naturally, that the Nazi leader who's in a leadership position with leader from a personality perspective get them on board. And sometimes that's the hardest thing to do. They might be the most changed resistant, but was that person flips, They become your greatest greatest advocate out there. So it's a personal thing. This is hard work. That's why I talk about in our sessions, is going through. This requires a lot of work, but it's worth it. You can measure the value on the end that you got help. People understand why you're going on this journey and have have resource is there for help. >> So what were some of that? You said you did good Q and a session during your break out this afternoon. >> Tell me some of >> the things that that some of the audience said that you thought was really like they're getting it, >> Yes. So the whole point of our session was going live is not really the goal, right? That's just >> a guess, the exact right. >> And so most people focus on going live, and the answer is congratulations. You purchased the product, Kuba, and now it's working. So what? You don't have any real data? What do you do in the future? Some questions were as they're going through Supplier Neighborhood. The shift between procurement now taking a larger role in the relationships with the vendors. Well, that's great. It should be a balanced relationship. You know, there's a procurement role in that. And then there's the end. Users are the people in the organization from the business. You have to relate with those suppliers, so work together. If you were together in the past now it's a great time to do that. There's some other questions about if something is not working correctly. Post go live how quick It's not broken, but it could be optimized or you're getting complaints about. How quick should you change it? The answer is, I don't know, measuring yourself. I mean, obviously it's broken. Fix it. But it might be something around change. And maybe you have to help people understand why they're doing this new process. If people are giving feedback positive, negative, mostly native, was positive. We just go off our way. Welcome to Yelp. But if it's negative feedback, listen, don't get offended, understand that perspective and then measure it. Say, Is this something that we did is saying the platform, or is it just changed and work with it? What I tell our clients to is in Cooper, Just cause you can doesn't mean you should. I mean, that's really easy to build a field custom field, really easy to build, custom approval chance, really hard to maintain that stuff. So try to do it out of the not out of the box, but configured without as much customization as possible, and they can always improve it, understand it better. >> I think the key to adoption is the more customization that you have. I imagine the adoption funnel gets narrower and narrower. It's got >> interesting, so you customize because you think that's the way the process should go, because that's how we do it today. So if your goal is to take how you do your process today and put into Cooper, also tell clients congratulations. If you had a bad process now you're bad process that works faster. So take the time to say, Let's step back. Companies evolve, right? And so as they're evolving, if you haven't taken a really a view purposeful of you backwards and measure organization, where you're out from a charity model assessment, then you probably don't know where your gaps are. Take the opportunity when you're implying Cooper to use kind of leading practice that Cooper has start with that and said, Going back to what you're doing today, you know what a great example. That's improvers, right? So people like to have 10 approve er's because they think it reduces risk. So if I go back and look and I asked the audience, say, how many purchase order requests rejected? Very few. And how long do people actually have it open when they re prove it? So that's three seconds when they open it up and looked at it, do they really assess it from a risk perspective? Probably not. But if four people ahead of them approved it, that person's just gotta prove it, because I think it's okay because they're assuming someone else is looking at it, as opposed to in Cooper. Now I have the rich data to understand it. I could minimize risk that way instead of trying to do it. And what is a false sense of security? >> So getting people on board with bringing in automation and leveraging like I was saying in the beginning, the 1.2 trillion of spend that's going through the Cooper platform toe leverage that intelligence to not only have Cooper create the prescriptions for companies to be able to go. Okay, we don't we shouldn't your point. We shouldn't take a process that was clunky before and just do it faster. Still clunky, being able to have the automation thing. Analytics. Really, Those core enabling technologies can also be quite revolutionary. >> Absolutely. Yeah, absolutely. So the coop insights now, and you're seeing that measured against others and its mass, but you see how you're doing it, So this is really powerful sitting your goals out there and seeing how you're doing. Adjusting those really question yourself is, if we're not getting is approved in the speed that we thought, How do we do it differently? Right, So and that's nice about Cuba. It is really sounds right, and they really do come out with three releases a year, which is powerful. And so it's always changing, which means you have to be nimble. Understand your organization, adopting the new technologies to come out. They're also looking at their acquisitions and seeing that fits into what you're doing. >> Exactly. Last question for you is the announcement of the expansion of their in the AWS marketplace today and thinking, Wow, the I t person is probably gonna finally all these Shadow I T units that are popping up in finance and marketing and engineering and whatnot. They now have the ability to see and manage the entire software from search to deployment and management through AWS. What advantage is that going to give Deloitte when you're working with Cooper customers on implementation? >> That's probably too soon to say on that one. All the expansions they're having really help us with another tool. Tell clients I would say that there's always measuring the benefit for that client in the risk. So even if you take Amazon, for example, just opened by for Cooper is managing that So Amazon. When they first came out with Amazon for business open by, you couldn't control the categories that were exposed to the client. Now you can, but you can't control the items. So having a process in place, having a category strategy and then maximizing it if Amazon works that client fantastic, AWS is gonna get them or visibility across their platforms to manage those better. Fantastic. I think it just gives another opportunity to bring clients back into Cooper. Have a look at the value for Cooper from an end and solution, and all these wraparound acquisitions are making our expansions with their clients, people pay and all those other pieces out there. It's just another thing for them to have a goal and understand make a decision from their business, whether they're going to use it or not. But there's there's value across the board. Every every client is different, >> Absolutely. But it's also that that consumer ization approach that if you can take a process that somebody does on their own time, whether they're buying soccer balls or pool and bring that to their business life, that consumer ization following them. You think with potential there to transform every industry, every function, every line of business. It's just infinite. So >> truly dot, >> dot dot to me. Continue. Absolutely Wish we had more time. But Max, thank you so much for joining me on the Cube today and talk doing talking to me about what's going on at Deloitte and congrats on having us standing. You're only sessions. That's good, right? Take for Max Ground like I'm Lisa Martin. You're watching the Cube from Cooper Inspire 19. Thanks for watching.

>> Live, from Las Vegas, it's theCUBE, covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Welcome back to Las Vegas, as we continue our coverage here on theCUBE of AWS re:Invent, day two of our three days of coverage, happy Wednesday to you, wherever you might be watching. We're joined by Yaron Haviv, who is the founder and CPO of iguazio, and Yaron, thanks for joining us here on theCUBE, once again. >> Thank you, hi. >> For folks at home who might be watching or at their office and not familiar with iguazio, tell us a little bit about the history of the company, what you saw as the need, as the founder, and what your primary focus is. >> So our key focus is delivering advanced services, the same one that you see in the Cloud, high-performance for real time analytics, essentially what we've seen as a gap, you have all the Cloud services in the Cloud, but when you're fanning into an Edge or an on-prem environment, you're usually consuming, like IT, VAMs, et cetera. So what we are doing, we're matching the same level of services, we provide serverless functions, AI as a service, and manage databases that can run, either in the Cloud or on-prem, or in federated Edge environment. So one consistent application development environment brought where we are. >> So, on the AI side, you mentioned that, as you're looking at your client base, your customers, and you're introducing this concept now, right? For those who aren't there yet. What do you sell them on, if you will? Or what do they want to know, what don't they understand, you think, generally speaking? >> Yeah, so in AI and ML, there are a lot of companies solving that problem, okay? Where we master is the notion of real-time AI, okay? What people are looking, is into embedding AI into business applications. Okay? The traditional notion is, you have a data lake, you throw all the data, and then your data sign, just go learn stuff, create nice, you know, desk-origin tableau. Great. So what? You know? What people really want is to build recommendation engines. You know, someone is logging into a website, he gets recommendations, so that requires very short latency of response, okay? You are doing front-detection and financial applications, so you're freighting a lot of data. You need to make decisions now, okay? You're doing cyber security analysis, so you're feeding data from routers and firewalls and switches, and you need react immediately to whatever is happening. You think about retail stores, things like Amazon Go. Cameras examining your behavior et cetera, you need to respond very very quickly. And now this is a much harder problem to deliver AI in real time, than it is in a sort-of a data-science workbench or just a batching notion. And traditionally, the way people address that problem is by profiling, creating sort-of a, every time, I'm going to see something very similar to that, I'm going to go to a database, pull, compare, and contrast, but the problem is that you need more and more multi-environment analysis on objects that keep on updating. You know, my location keeps on changing. If I'm going to stand in front of this store, I need to get this advertisement, or if I've just done some purchase with my card, and the bank knows my GPS location, it can cross-correlate that, and know if it's a fraud or not, okay? So there are more inputs going into the decision. This is where we master is, the ability to ingest lots of data in real time, cross-correlate that, in real time, to generate what's called feature vector. It's all those things that make up a decision. Run the decision, based on the traditional AI and deep learning algorithms, and they act on it. Whether it's response to customer requests or, you know, block some firewall, or whatever. And our focus is time to action. And the way we are implementing it, is using two major components. One is, real time serverless functions, which is an open-source we're promoting, called nuclio. A second is a real-time database, extremely high performance, it attaches to those functions and allow and help stitching the data and calculating and getting the results. So that's the general thing we're doing. >> So that idea of the serverless functions with nuclio, that's really about bringing, what you're used to in the Cloud, and bringing that out into the Edge. Which, I think, we were talking before, and that's I think a focus for a lot of developers who, I want to use all of the things I'm used to in the Cloud, where it's, I can just consume them as services, and it's quite easy to deal with. But then I come back into the on-site or on onto the Edge in this kind-of hybrid Cloud model, I don't actually have access to all of those things anymore. And I want to. >> Right, and it's even beyond that, because, you the Lambda came from more of like, WebHooks, Seoscases, et cetera. Extremely not concurrent, extremely low performance. You're talking about hundreds of milliseconds of latencies, you know, you're talking about, like, thousand invocations per second, you know? That's sort-of the concurrency, single-threaded applications. We're talking about real-time applications, you know. Hundreds of thousands of events per second. We're talking about latency in the range of milliseconds response time, that you have to respond. So we had to build a different serverless. Something that's real-time, something that has real-time access to data, et cetera. So that's originally where nuclio came in. And then, we started seeing pull from customers, saying, yes, but you're also a multi-Cloud serverless. And I can run your serverless on a laptop for debugging. I can run it on a mini Edge appliance, because this is my enforcement point. I can run it on-prem, because, you know, I'm stuck with some old gear in my on-prem application, and this is what started making nuclio very popular in lots of getup starts et cetera. And the fact that we're provided as a fully managed platform you know, it's open-source, consume it, whatever, but when you're using our managed platform, you get security, integration with active directory, integration with data, logging, monitoring. So, it really provides an alternative to Lambda, where you need high concurrency and everywhere. You know, Edge, Cloud, on-prem, but also high performance, high concurrency for those new workloads of real-time analytics. >> Yeah, so what are some of things that customers are using the platform to develop on? Like, could you give us an example of someone who's using some of these serverless functions for real-time application? Yeah, so, one of the applications is a, we do a lot of work with the network operators. You know, Verizon is one of our investors, but also working with different, other tel-cos. So we're doing real-time network monitoring, across all their firewalls and network equipment et cetera, to predict the network behavior. So, if there's going to be a failure, is it a cyber-security attack right now, things like that. The next level that they went into doing is actually a remediation. It's essentially re-routing the networks to bypass faults automatically, based on the predicted behaviors. Or, you know, stopping some attacks as they occur. So that's one use case. Another use case, in financial services and many other places, is predictive network operations. It's monitoring, again, behavior of services et cetera, like in trading platforms. And knowing that there is going to be a latency spike that's going to impact the trading, and essentially going and fixing that, in order to not lose millions of dollars of trades. Or real time tick analytics, you know? Until now, all the financial applications were very sort-of event driven, and complex event driven, not incorporating deep learning, things like that. Now, I think that there are many variants. You know, the, your president, you know, is going to tweet something about some company, and then it's going to impact the buyover or with stock. So, the current high-frequency trading algorithms are not designed for that, okay? Now, if you build all those serverless functions that listens on Twitter and Muse and all those things, and they can start cross-correlating that information to a much smarter decision. They fit in the real-time decision of buying and selling stocks into a lot more intelligent decision, you can make more money, okay? Another application, retailers, okay? We're working with locations where they have a thousand cameras in a single supermarket, because they just inspect the shelves to look into inventory levels, and eventually they're going to like, an Amazon Go model, where they actually want to know, to track what you're buying et cetera. So a thousand cameras in a store, you cannot shape all that bandwidth to the Cloud. And this is where it comes to a federated application model. Where, as a developer, the guys that are Cloud-born, or Cloud-first, they know containers, they know APIs, they know that stuff. They don't know how to build a box that sits in a store, okay? This is the other world of VMs and Venix, they don't care about that, they want APIs. They want Lambda functions, Dynamo, et cetera. So what we're providing is a mechanism where they can develop in the Cloud, test, simulate, run CICD pipelines, push our defects to the store, to actually go and do the work. And there we have strong partnerships with at least a couple of the major Cloud providers. We have co-ceiling agreements with Azure, we're working with Google, and, I assume, Amazon will be next, but those two, we have a strong relations with already. >> Alright, before we cut you loose, just gimme your idea about the show in general here, from what you've seen, and kind of how you feel about the conversations that you're a part of. >> Yeah, I was very busy talking to customers all day, so I haven't had a lot of time. I think interesting announcements, you know, they've made announcements with VMware, I'm still trying to figure out, what have they announced. You know, again, we spoke about the fact that the whole idea of Cloud is about service obstructions. Not virtual machines, not Kubernetes containers. It's about using APIs, using serverless functions, using AI workbenches that you can develop this new logic. If I'm going to use this VMware on-prem with Amazon, am I going to get all the SageMaker, Lambda, all that on-prem, or just more of a tactical thing, like Azure Stack, like, we're bringing UVMs, we're calling it Cloud, you know, just for marketing's sake. Is that a real Cloud services platform, okay? I think it aligns with what we're seeing now with the Kubernetes, I think we had some discussion about it. You know, IBM buys Reddit, you know, Cisco collaborates with Amazon, VMware buys Apptio. Kubernetes is containers, it's infrastructure. We speak to customers, we show them what we do serverless, you know AI workbenches, databases, service. That's the interesting part. That eliminates IT. If you're putting Kubernetes, it perpetuates IT. Now they need to take Kubernetes, tie it to their security system, build Spark on top of a container et cetera. Now that is a lot of IT and dev ops work involved. But many customers need agility. The reason they're going to Cloud, is not to use VMs, you know? It's to be able to take some Lambda function, some pre-bagged services, glue them together, and really come fast to market with an application. >> So what we really want to do is just to Cloud all the things. I think? (group chuckles) Cloud all the things. >> Mission accomplished. Yaron, thanks for being with us. We appreciate the time you're on theCUBE. Good to see you, sir. >> Thank you. >> Alright, back with more, here at AWS re:Invent. You're watching it live, and we're on theCUBE. (techno music)

>> Coming back when we were a DOS spreadsheet company. I did a short stint at Microsoft and then joined Frank Quattrone when he spun out of Morgan Stanley to create what would become the number three tech investment (upbeat music) >> Host: Live from mid-town Manhattan, it's theCUBE covering the BigData New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. (upbeat electronic music) >> Welcome back, everyone. We're here, live, on day two of our three days of coverage of BigData NYC. This is our event that we put on every year. It's our fifth year doing BigData NYC in conjunction with Hadoop World which evolved into Strata Conference, which evolved into Strata Hadoop, now called Strata Data. Probably next year will be called Strata AI, but we're still theCUBE, we'll always be theCUBE and this our BigData NYC, our eighth year covering the BigData world since Hadoop World. And then as Hortonworks came on we started covering Hortonworks' data summit. >> Arun: DataWorks Summit. >> DataWorks Summit. Arun Murthy, my next guest, Co-Founder and Chief Product Officer of Hortonworks. Great to see you, looking good. >> Likewise, thank you. Thanks for having me. >> Boy, what a journey. Hadoop, years ago, >> 12 years now. >> I still remember, you guys came out of Yahoo, you guys put Hortonworks together and then since, gone public, first to go public, then Cloudera just went public. So, the Hadoop World is pretty much out there, everyone knows where it's at, it's got to nice use case, but the whole world's moved around it. You guys have been, really the first of the Hadoop players, before ever Cloudera, on this notion of data in flight, or, I call, real-time data but I think, you guys call it data-in-motion. Batch, we all know what Batch does, a lot of things to do with Batch, you can optimize it, it's not going anywhere, it's going to grow. Real-time data-in-motion's a huge deal. Give us the update. >> Absolutely, you know, we've obviously been in this space, personally, I've been in this for about 12 years now. So, we've had a lot of time to think about it. >> Host: Since you were 12? >> Yeah. (laughs) Almost. Probably look like it. So, back in 2014 and '15 when we, sort of, went public and we're started looking around, the thesis always was, yes, Hadoop is important, we're going to love you to manage lots and lots of data, but a lot of the stuff we've done since the beginning, starting with YARN and so on, was really enable the use cases beyond the whole traditional transactions and analytics. And Drop, our CO calls it, his vision's always been we've got to get into a pre-transactional world, if you will, rather than the post-transactional analytics and BIN and so on. So that's where it started. And increasingly, the obvious next step was to say, look enterprises want to be able to get insights from data, but they also want, increasingly, they want to get insights and they want to deal with it in real-time. You know while you're in you shopping cart. They want to make sure you don't abandon your shopping cart. If you were sitting at at retailer and you're on an island and you're about to walk away from a dress, you want to be able to do something about it. So, this notion of real-time is really important because it helps the enterprise connect with the customer at the point of action, if you will, and provide value right away rather than having to try to do this post-transaction. So, it's been a really important journey. We went and bought this company called Onyara, which is a bunch of geeks like us who started off with the government, built this batching NiFi thing, huge community. Its just, like, taking off at this point. It's been a fantastic thing to join hands and join the team and keep pushing in the whole streaming data style. >> There's a real, I don't mean to tangent but I do since you brought up community I wanted to bring this up. It's been the theme here this week. It's more and more obvious that the community role is becoming central, beyond open-source. We all know open-source, standing on the shoulders before us, you know. And Linux Foundation showing code numbers hitting up from $64 million to billions in the next five, ten years, exponential growth of new code coming in. So open-source certainly blew me. But now community is translating to things you start to see blockchain, very community based. That's a whole new currency market that's changing the financial landscape, ICOs and what-not, that's just one data point. Businesses, marketing communities, you're starting to see data as a fundamental thing around communities. And certainly it's going to change the vendor landscape. So you guys compare to, Cloudera and others have always been community driven. >> Yeah our philosophy has been simple. You know, more eyes and more hands are better than fewer. And it's been one of the cornerstones of our founding thesis, if you will. And you saw how that's gone on over course of six years we've been around. Super-excited to have someone like IBM join hands, it happened at DataWorks Summit in San Jose. That announcement, again, is a reflection of the fact that we've been very, very community driven and very, very ecosystem driven. >> Communities are fundamentally built on trust and partnering. >> Arun: Exactly >> Coding is pretty obvious, you code with your friends. You code with people who are good, they become your friends. There's an honor system among you. You're starting to see that in the corporate deals. So explain the dynamic there and some of the successes that you guys have had on the product side where one plus one equals more than two. One plus one equals five or three. >> You know IBM has been a great example. They've decided to focus on their strengths which is around Watson and machine learning and for us to focus on our strengths around data management, infrastructure, cloud and so on. So this combination of DSX, which is their data science work experience, along with Hortonworks is really powerful. We are seeing that over and over again. Just yesterday we announced the whole Dataplane thing, we were super excited about it. And now to get IBM to say, we'll get in our technologies and our IP, big data, whether it's big Quality or big Insights or big SEQUEL, and the word has been phenomenal. >> Well the Dataplane announcement, finally people who know me know that I hate the term data lake. I always said it's always been a data ocean. So I get redemption because now the data lakes, now it's admitting it's a horrible name but just saying stitching together the data lakes, Which is essentially a data ocean. Data lakes are out there and you can form these data lakes, or data sets, batch, whatever, but connecting them and integrating them is a huge issue, especially with security. >> And a lot of it is, it's also just pragmatism. We start off with this notion of data lake and say, hey, you got too many silos inside the enterprise in one data center, you want to put them together. But then increasingly, as Hadoop has become more and more mainstream, I can't remember the last time I had to explain what Hadoop is to somebody. As it has become mainstream, couple things have happened. One is, we talked about streaming data. We see all the time, especially with HTF. We have customers streaming data from autonomous cars. You have customers streaming from security cameras. You can put a small minify agent in a security camera or smart phone and can stream it all the way back. Then you get into physics. You're up against the laws of physics. If you have a security camera in Japan, why would you want to move it all the way to California and process it. You'd rather do it right there, right? So with this notion of a regional data center becomes really important. >> And that talks to the Edge as well. >> Exactly, right. So you want to have something in Japan that collects all of the security cameras in Tokyo, and you do analysis and push what you want back here, right. So that's physics. The other thing we are increasingly seeing is with data sovereignty rules especially things like GDPR, there's now regulation reasons where data has to naturally stay in different regions. Customer data from Germany cannot move to France or visa versa, right. >> Data governance is a huge issue and this is the problem I have with data governance. I am really looking for a solution so if you can illuminate this it would be great. So there is going to be an Equifax out there again. >> Arun: Oh, for sure. >> And the problem is, is that going to force some regulation change? So what we see is, certainly on the mugi bond side, I see it personally is that, you can almost see that something else will happen that'll force some policy regulation or governance. You don't want to screw up your data. You also don't want to rewrite your applications or rewrite you machine learning algorithms. So there's a lot of waste potential by not structuring the data properly. Can you comment on what's the preferred path? >> Absolutely, and that's why we've been working on things like Dataplane for almost a couple of years now. We is to say, you have to have data and policies which make sense, given a context. And the context is going to change by application, by usage, by compliance, by law. So, now to manage 20, 30, 50 a 100 data lakes, would it be better, not saying lakes, data ponds, >> [Host} Any Data. >> Any data >> Any data pool, stream, river, ocean, whatever. (laughs) >> Jacuzzis. Data jacuzzis, right. So what you want to do is want a holistic fabric, I like the term, you know Forrester uses, they call it the fabric. >> Host: Data fabric. >> Data fabric, right? You want a fabric over these so you can actually control and maintain governance and security centrally, but apply it with context. Last not least, is you want to do this whether it's on frame or on the cloud, or multi-cloud. So we've been working with a bank. They were probably based in Germany but for GDPR they had to stand up something in France now. They had French customers, but for a bunch of new reasons, regulation reasons, they had to sign up something in France. So they bring their own data center, then they had only the cloud provider, right, who I won't name. And they were great, things are working well. Now they want to expand the similar offering to customers in Asia. It turns out their favorite cloud vendor was not available in Asia or they were not available in time frame which made sense for the offering. So they had to go with cloud vendor two. So now although each of the vendors will do their job in terms of giving you all the security and governance and so on, the fact that you are to manage it three ways, one for OnFrame, one for cloud vendor A and B, was really hard, too hard for them. So this notion of a fabric across these things, which is Dataplane. And that, by the way, is based by all the open source technologies we love like Atlas and Ranger. By the way, that is also what IBM is betting on and what the entire ecosystem, but it seems like a no-brainer at this point. That was the kind of reason why we foresaw the need for something like a Dataplane and obviously couldn't be more excited to have something like that in the market today as a net new service that people can use. >> You get the catalogs, security controls, data integration. >> Arun: Exactly. >> Then you get the cloud, whatever, pick your cloud scenario, you can do that. Killer architecture, I liked it a lot. I guess the question I have for you personally is what's driving the product decisions at Hortonworks? And the second part of that question is, how does that change your ecosystem engagement? Because you guys have been very friendly in a partnering sense and also very good with the ecosystem. How are you guys deciding the product strategies? Does it bubble up from the community? Is there an ivory tower, let's go take that hill? >> It's both, because what typically happens is obviously we've been in the community now for a long time. Working publicly now with well over 1,000 customers not only puts a lot of responsibility on our shoulders but it's also very nice because it gives us a vantage point which is unique. That's number one. The second one we see is being in the community, also we see the fact that people are starting to solve the problems. So it's another elementary for us. So you have one as the enterprise side, we see what the enterprises are facing which is kind of where Dataplane came in, but we also saw in the community where people are starting to ask us about hey, can you do multi-cluster Atlas? Or multi-cluster Ranger? Put two and two together and say there is a real need. >> So you get some consensus. >> You get some consensus, and you also see that on the enterprise side. Last not least is when went to friends like IBM and say hey we're doing this. This is where we can position this, right. So we can actually bring in IGSC, you can bring big Quality and bring all these type, >> [Host} So things had clicked with IBM? >> Exactly. >> Rob Thomas was thinking the same thing. Bring in the power system and the horsepower. >> Exactly, yep. We announced something, for example, we have been working with the power guys and NVIDIA, for deep learning, right. That sort of stuff is what clicks if you're in the community long enough, if you have the vantage point of the enterprise long enough, it feels like the two of them click. And that's frankly, my job. >> Great, and you've got obviously the landscape. The waves are coming in. So I've got to ask you, the big waves are coming in and you're seeing people starting to get hip with the couple of key things that they got to get their hands on. They need to have the big surfboards, metaphorically speaking. They got to have some good products, big emphasis on real value. Don't give me any hype, don't give me a head fake. You know, I buy, okay, AI Wash, and people can see right through that. Alright, that's clear. But AI's great. We all cheer for AI but the reality is, everyone knows that's pretty much b.s. except for core machine learning is on the front edge of innovation. So that's cool, but value. [Laughs] Hey I've got the integrate and operationalize my data so that's the big wave that's coming. Comment on the community piece because enterprises now are realizing as open source becomes the dominant source of value for them, they are now really going to the next level. It used to be like the emerging enterprises that knew open source. The guys will volunteer and they may not go deeper in the community. But now more people in the enterprises are in open source communities, they are recruiting from open source communities, and that's impacting their business. What's your advice for someone who's been in the community of open source? Lessons you've learned, what is the best practice, from your standpoint on philosophy, how to build into the community, how to build a community model. >> Yeah, I mean, the end of the day, my best advice is to say look, the community is defined by the people who contribute. So, you get advice if you contribute. Which means, if that's the fundamental truth. Which means you have to get your legal policies and so on to a point that you can actually start to let your employees contribute. That kicks off a flywheel, where you can actually go then recruit the best talent, because the best talent wants to stand out. Github is a resume now. It is not a word doc. If you don't allow them to build that resume they're not going to come by and it's just a fundamental truth. >> It's self governing, it's reality. >> It's reality, exactly. Right and we see that over and over again. It's taken time but it as with things, the flywheel has changed enough. >> A whole new generation's coming online. If you look at the young kids coming in now, it is an amazing environment. You've got TensorFlow, all this cool stuff happening. It's just amazing. >> You, know 20 years ago that wouldn't happen because the Googles of the world won't open source it. Now increasingly, >> The secret's out, open source works. >> Yeah, (laughs) shh. >> Tell everybody. You know they know already but, This is changing some of the how H.R. works and how people collaborate, >> And the policies around it. The legal policies around contribution so, >> Arun, great to see you. Congratulations. It's been fun to watch the Hortonworks journey. I want to appreciate you and Rob Bearden for supporting theCUBE here in BigData NYC. If is wasn't for Hortonworks and Rob Bearden and your support, theCUBE would not be part of the Strata Data, which we are not allowed to broadcast into, for the record. O'Reilly Media does not allow TheCube or our analysts inside their venue. They've excluded us and that's a bummer for them. They're a closed organization. But I want to thank Hortonworks and you guys for supporting us. >> Arun: Likewise. >> We really appreciate it. >> Arun: Thanks for having me back. >> Thanks and shout out to Rob Bearden. Good luck and CPO, it's a fun job, you know, not the pressure. I got a lot of pressure. A whole lot. >> Arun: Alright, thanks. >> More Cube coverage after this short break. (upbeat electronic music)