(upbeat music) >> Hey everyone. Welcome back to the show floor in Las Vegas Snowflake Summit 22 with 7,000 plus folks here, Lisa Martin with Dave Vellante. Great to be back in person. We're excited to welcome a couple of guests that join us next. Persona Christian is here. The director of product for collaboration and Snowflake marketplace. Katie Laughlin joins us as well. The Global Head Offerings, Human Data Science Cloud at Customer IQVIA. Ladies, welcome to the program. >> Thank you. >> Thank you for having us. >> Dave: All right. Thanks for coming on. >> Katie, let's go ahead and start with you. Give the audience an overview of IQVIA. What you guys do, your mission, what you deliver? >> Yeah, sure. So, IQVIA is a healthcare focused data analytics and clinical research organization. We have 82,000 employees. We operate in a hundred countries and we have tens of thousands of data deliverables that we curate for our customers and deliver to them on a monthly basis. So, we're 100% healthcare focused, whether it's clinical research, helping our customers support their clinical trials, real world evidence, how are medicines operating in the market or commercial aspects. You know, how is your company performing overall in the market? >> How long have you been a customer of Snowflake's? >> A few years. Yeah. >> A few years, okay. Persona, tremendous growth going on right now. There's a rocket ship. You could even feel kind of like the whiplash from the keynote and all the announcements going on, but looking at the first quarter 23, fiscal 23 results, product revenue, 384 million, 85% growth tremendous momentum going on, big growth in customers. Talk to us about IQVIA, its partnership with Snowflake and the data driver award program. They, they just won. >> Yeah, absolutely. I'll start with a little bit about the Snowflake collaboration capabilities, which enable these thousands of customers to really collaborate on the data cloud to be able to break down silos between data and drive business decisions based on data and applications that live outside your own four walls as well. And this is where IQVIA, as a leader in healthcare data, bringing together data to enable healthcare organizations to be more data driven and to really drive insights. One, the data for good award, which we are really excited with for the partnership and really excited to have IQVIA be the winner of the award. >> And what does that mean? The data for good. We always love talking about that, Katie. >> Katie: Sure. What does that mean? How is that embodied at IQVIA? >> Can you say the last part? >> Yeah. How is that embodied at IQVIA? >> That's a great question. I think everyone that works at IQVIA believes in the mission, which is really to drive healthcare forward. We're really proud of a lot of the things that we do. So, with the advent of COVID, for example, we really had to pivot and help our customers. How do we keep executing on clinical trials? We supported a lot of the COVID trials that came forward and helped our customers understand how is this affecting patients in the real world? And how is it affecting your commercial operations? So, being in Vegas with tens of thousands of people around and almost nobody wearing masks, I think to myself, I'm part of the organization an organization that helped make that possible. >> So Frank Slootman today, Katie talked about compress. He talked about one pharmaceutical compressing from nine years to seven years, you guys have done a lot of obviously contract research over the years. So, what has that Snowflake journey been like? What's been the business impact of of working with that and the collaboration? >> Yeah. So my focus is really around our data as a service offering, which is where we're enabling our customers to ingest their data in modern ways. So if you imagine, you know, we've done everything from paper to big tapes of data for over 60 years of of our company being in business, now to VPN, SFTP, making multiple hops of data from one end to the other. I was just learning about one of our use cases where we're able to cut down processing time for our customers for two weeks. They data share some data with us. We do some additional processing on that. We serve it back to them and we're saving them two weeks of time to gain time to insights. >> Right. And Prasanna, collaboration transcends data sharing, right? It's almost like it's, that's, that's sort of the the first, the core of the concentric circle, right? >> Prasanna: Yeah. >> Talk about what else is embodied in collaboration. >> Yeah, that's a great question. So the first problem that we solved was getting access to data through our core sharing technology. And as you were talking about Katie, replacing FTPs and having to build APIs, which were cumbersome, and instead being able to access data on the data cloud without having to copy or move anything. That was the core sharing technology. But that solves the first problem, which is the access problem. The second problem is how do I discover what what's out there? How do I better understand it? How do I evaluate it? How do I try it and buy it? And those are all the problems that we're solving with the marketplace, which is now home to both data and applications that you can discover, try, and buy. >> Katie, talk to us about what IQVIA was doing before Snowflake? What was that life like before? How were you enabling customers to leverage data to make data driven decisions? >> Yeah, so we, as I said, we're a data and analytics company. So we provide some native analytics capabilities to our customers, but most customers, most of the large customers I would say, they're building their own data lakes. They have their own ecosystems. Some of them are adopting Snowflake and we really needed to partner with them on being able to get the data to them as quickly as possible. So like, I, I was just describing a minute ago we would have multiple hops where we deliver to a location, customer ingests it, customer does their QC. Then they process it and then it appears in their data warehouse. And now we're able to adopt their QC protocols within our own platform and deliver the data to them much more quickly. >> And what does that enable to your business from an outcomes perspective? If you look at overall Snowflake as an engine what is it enabling and empowering IQVIA to accomplish? >> So it helps us partner with our customers in modern ways. So I'm saying we've been in the data business for 60 years. So it's sometimes it's a legacy behemoth that you need to bring along to modern times. And I think for us, the shift has been night and day in terms of Snowflake's capabilities. >> So you will build data based apps in the Snowflake data cloud? Is that, is that where you're headed? >> Yes. So we have several applications that we built natively on Snowflake that we offer to our customers. >> And what will that bring you that you kind of couldn't do before? >> That we couldn't do before? I think the the ability to, we talk a lot about how you spend 80% of your time cooking the data, right? Getting it ready for insights and only 20% of your time being able to to bring those insights forward and Snowflake, it really helps us flip that ratio so that we don't have to worry so much about the scaling and the infrastructure and the data sourcing. We can focus more on driving those insights and innovations. >> So Prasanna, we talk a lot about, you have this application stack over here and it sends a database over here and then you have an analytics stack. It seems like you're enabling those worlds to come together. Is that, is that by design? Is that more organic? Can you talk about that? >> Yeah. I mean, that is essential to our our mission and our value prop is to bring it together. It's one product, it's seamless and lets you do more with your data. Benoit talked today in the opening keynote about running multiple workloads on your data and the way you do that is by having one product that allows you to to run your data, data queries but also build applications that can run against that data. >> Katie, can you share a little bit about the partnership? We'll say collaboration that IQVIA has with Snowflake in terms of your ability to influence the roadmap in the direction. We heard a lot of customer stories in the keynote and they talked a lot about Frank Slootman did, Benoit, Christian. We are listening to our customers. Do you feel that as a, a customer for the last few years? >> Yeah, absolutely. So we have a really broad partnership with Snowflake. We're a customer. We have OEM licensing where we're building applications on top of Snowflake. We're an SI partner where we're marrying our data healthcare expertise along with Snowflake technology expertise and helping customers build and utilize the data internally and as well as just, if nothing else, the Snowflake data share in order to deliver the data into their environment. >> Prasanna, what do you look for in a data driver winner? Like what stood out about IQVIA and others that aspire to that, what should they be focused on? >> Yeah, I mean, you know, we ultimately think that in every business you have business needs that you're trying to solve and business is inherently collaborative. You never solve problems with just what you have within your own four walls. And IQVIA is an example of someone that's really enabling outcomes for healthcare companies to be much faster through live access to data. Which is what we want to accomplish for the data cloud, help our company, help our customers solve business needs. >> Every company has to be a data company these days, right? There's no, you have no choice. We talked about, you know, software eating the world a few years. Now we're talking about data eating the world. For organizations, it's in any any vertical healthcare, life sciences, retail, finance. It's essential to not just have data, live data access to it, to be able to extract insights from it that you can act on. Talk about what you are doing at Snowflake as a differentiator? Is that goal of becoming the defacto standard data platform and what that enables partners like IQVIA to accomplish? >> Yeah. It starts with our fundamental architecture, which allows you to collaborate and access data without creating copies of it or sending around copies and built on top of that now, the ability to build applications and to monetize them really enables our customers to do more with their data and to monetize it and to be able to distribute it without having to deal with all the plumbing. >> That's nice. That saves you a lot of time. What do you think when you, Katie, if you talk to people that are your peers in either healthcare or other industries, what are like the top couple of recommendations that you would have for them? We have a data problem. It's all a data problem. How do we actually leverage value from this fast so we can be competitive? >> Yeah. So I think if I were to advise someone who is thinking about commercializing their data set, when if they haven't before, you know, you have to think about good data governance protocols, good data cataloging. Make sure you're, you know, conforming to all of the privacy rules that you need to and overseeing the management of that data, any changes in the data, you know, delivering that both to internal and external customers. But I think, just a quick plug for Snowflake, what I would say on a personal level is that their partner first mentality really is a pleasure, makes it a pleasure to work with them and makes it really easy for us to enable our services through, through Snowflake. >> Frank Slootman talked about mission alignment this morning, kind of a mission I thought of, of aligning on with the missions of their customers and partners. It sounds like that's what Katie's talking about from a cultural perspective. You've got that alignment here? >> Yes, absolutely. You know, we work with our partners to enable our customers to drive business value and solve the needs of their industry. >> What are some of the things that you are excited about? Fourth Annual Summit. We, I, I said 7,000 plus people we'll get numbers kind of later on. What are you excited about finally being back in person? >> Yes, of course. >> Being able to access this hugely growing population of customers and partners, what excites you about this Summit 22? >> What excites me most is the fact that we are now enabling our customers to do more, to build applications which has been a big theme at Summit, but also to be able to distribute and monetize this. So as Frank talked about this morning, helping customers drive value and more value from, from their data. >> Critical. Katie, last question for you. If we look at all the,it was a very technical keynote this morning. You talked about the great partnership, the synergies the alignment that IQVIA has with Snowflake. What are you excited about in terms of hearing and seeing and feeling and touching this week at Summit? >> Well, yesterday we won an award for Data Marketplace. Marketplace Partner of the year for healthcare and life sciences. That was really exciting for us. It was great recognition for us in terms of how we've been able to modernize on the cloud. But I'm really excited to see how much the Snowflake business has grown as well. Our General Manager for information management was telling me, he said, when I come to this conference a couple of years ago it was only a few thousand people and now it's really, it's really grown and really taken off. And it's really exciting to see how many of the different partnerships are interacting and and that we're able to take advantage of as well. >> Yeah, I think we heard earlier this morning that the first summit four years ago was a couple thousand people. Now here we are eight, eight to ten. We've also seen, Persona, I mentioned some of the product revenue numbers for fiscal 23 Q1. I also noticed that in the last four years, the number percentage of customers with a million plus ARR is grown over 1200%. Number of customers is growing, the high value customers are growing. It seems like you're on a rocket ship here with Snowflake. Would you agree? >> Yeah. We're excited with all the value that we're bringing to our customers and the growth we're seeing. >> Dave: Yeah. Way to amp it up. >> Yeah, absolutely. >> Excellent. Ladies, thank you so much for joining us talking about the partnership with IQVIA and Snowflake. Congratulations again. >> Katie: Thank you. >> Katie, on IQVIA winning the data driver award, Data for good >> Great to hear what you're doing together and how you're enabling organizations in the healthcare industry to maximize the value of data. We appreciate your insights. >> Thank you. >> Dave: Thank you guys. >> Thanks. >> For our guests, Dave Vellante, I'm Lisa Martin. You're watching the Cube's live coverage from Las Vegas of Snowflake Summit 22. Stick around, Dave and I will be right back with our next guest.

(upbeat music) >> Welcome back to the Javits in the big apple, New York City. This is theCUBE's coverage of MongoDB World 2022. We're here for a full day of coverage. We're talking to customers, partners, executives and analysts as well. Peder Ulander is here. He's the Chief Marketing Officer of MongoDB and he's joined by Radhika Krishnan, who's the Chief Product Officer at Hitachi Ventara. Folks, welcome back to theCUBE. Great to see you both again. >> Good to see you. >> Thank you David, it's good to be back again. >> Peder, first time since 2019, we've been doing a lot of these conferences and many of them, it's the first time people have been out in a physical event in three years. Amazing. >> I mean, after three years to come back here in our hometown of New York and get together with a few thousand of our favorite customers, partners, analysts, and such, to have real good discussions around where we're taking the world with regards to our developer data platform. It's been great. >> I think a big part of that story of course, is ecosystem and partnerships and Radhika, I remember I was at an event when Hitachi announced its strategy and it's name change, and really tried to understand why and the what's behind that. And of course, Hitachi's a company that looks out over the long term, and of course it has to perform tactically, but it thinks about the future. So give us the update on what's new at Hitachi Ventara, especially as it relates to data. >> Sure thing, Dave. As many, many folks might be aware, there's a very strong heritage that Hitachi has had in the data space, right. By virtue of our products and our presence in the data storage market, which dates back to many decades, right? And then on the industrial side, the parent company Hitachi has been heavily focused on the OT sector. And as you know, there is a pretty significant digital transformation underway in the OT arena, which is all being led by data. So if you look at our mission statement, for instance, it's actually engineering the data driven because we do believe that data is the fundamental platform that's going to drive that digital transformation, irrespective of what industry you're in. >> So one of the themes that you guys both talk about is modernization. I mean, you can take a cloud, I remember Alan Nance, who was at the time, he was a CIO at Philips, he said, look, you could take a cloud workload, or on-prem workload, stick it into the cloud and lift it and shift it. And in your case, you could just put it on, run it on an RDBMS, but you're not going to affect the operational models. >> Peder Ulander: It's just your mess for less, man. >> If you do that. >> It's your mess, for less. >> And so, he goes, you'll get a few, you know, you'll get a couple of zeros out of that. But if you want to have, in his case, billion dollar impact to the business, you have to modernize. So what does modernize mean to each of you? >> Maybe Peder, you can start. >> Yeah, no, I'm happy to start. I think it comes down to what's going on in the industry. I mean, we are truly moving from a world of data centers to centers of data, and these centers of data are happening further and further out along the network, all the way down to the edges. And if you look at the transformation of infrastructure or software that has enabled us to get there, we've seen apps go from monoliths to microservices. We've seen compute go from physical to serverless. We've seen networking go from old wireline copper to high powered 5G networks. They've all transformed. What's the one layer that hasn't completely transformed yet, data, right? So if we do see this world where things are getting further and further out, you've got to rethink your data architecture and how you basically support this move to modernization. And we feel that MongoDB with our partners, especially with Hitachi, we're best suited to really kind of help with this transition for our customers as they move from data centers to centers of data. >> So architecture. And at the failure, I will say this and you tell me if you agree or not. A lot of the failures of sort of the big data architectures of today are there's, everything's in this monolithic database, you've got to go through a series of hyper-specialized professionals to get to the data. If you're a business individual, you're so frustrated because the market's changing faster than you can get answers. So you guys, I know, use this concept of data fabric, people talk about data mesh. So how do you think, Radhika, about modernization in the future of data, which by its very nature is distributed? >> Yeah. So Dave, everybody talks about the hybrid cloud, right? And so the reality is, every one of our customers is having to deal with data that's straddled across on-prem as well as the public cloud and many other places as well. And so it becomes incredibly important that you have a fairly seamless framework, that's relatively low friction, that allows you to go from the capture of the data, which could be happening at the edge, could be happening at the core, any number of places, all the way to publish, right. Which is ultimately what you want to do with data because data exists to deliver insights, right? And therefore you dramatically want to minimize the friction in the process. And that is exactly what we're attempting to do with our data fabric construct, right. We're essentially saying, customers don't have to worry about, like you mentioned, they may have federated data structures, architectures, data lakes, fitting in multiple locations. How do you ensure that you're not having to double up custom code in order to drive the pipelines, in order to drive the data movement from one location to the other and so forth. And so essentially what we're providing is a mechanism whereby they can be confident about the quality of the data at the end of the day. And this is so paramount. Every customer that I talk to is most worried about ensuring that they have data that is trustworthy. >> So this is a really important point because I've always felt like, from a data quality standpoint, you know you get the data engineers who might not have any business context, trying to figure out the quality problem. If you can put the data responsibility in the hands of the business owner, who, he or she, has context, that maybe starts to solve this problem. There's some buts though. So infrastructure becomes an operational detail. Let's hide that. Don't worry about it. Figure it out, okay, so the business can run, but you need self-service infrastructure and you have to figure out how to have federated governance so that the right people can have access. So how do you guys think about that problem in the future? 'Cause it's almost like this vision creates those two challenges. Oh, by the way, you got to get your organization behind it. Right, 'cause there's an organizational construct as well. But those are, to me, wonderful opportunities but they create technology challenges. So how are you guys thinking about that and how are you working on it? >> Yeah, no, that's exactly right, Dave. As we talk to data practitioners, the recurring theme that we keep hearing is, there is just a lot of use cases that require you to have deep understanding of data and require you to have that background in data sciences and so on, such as data governance and vary for their use cases. But ultimately, the reason that data exists is to be able to drive those insights for the end customer, for the domain expert, for the end user. And therefore it becomes incredibly important that we be able to bridge that chasm that exists today between the data universe and the end customer. And that is what we essentially are focused on by virtue of leaning into capabilities like publishing, right? Like self, ad hoc reporting and things that allow citizen data scientists to be able to take advantage of the plethora of data that exists. >> Peder, I'm interested in this notion of IT and OT. Of course, Hitachi is a partner, established in both. Talk about Mongo's position in thinking. 'Cause you've got on-prem customers, you're running now across all clouds. I call it super cloud connecting all these things. But part of that is the edge. Is Mongo running there? Can Mongo run there, sort of a lightweight version? How do you see that evolve? Give us some details there. >> So I think first and foremost, we were born on-prem, obviously with the origins of MongoDB, a little over five years ago, we introduced Atlas and today we run across a hundred different availability zones around the globe, so we're pretty well covered there. The third bit that I think people miss is we also picked up a product called Realm. Realm is an embedded database for mobile devices. So if you think about car companies, Toyota, for example, building connected cars, they'll have Realm in the car for the telemetry, connects back into an Atlas system for the bigger operational side of things. So there's this seamless kind of, or consistency that runs between data center to cloud to edge to device, that MongoDB plays across all the way through. And then taking that to the next level. We talked about this before we sat down, we're also building in the security elements of that because obviously you not only have that data in rest and data in motion, but what happens when you have that data in use? And announced, I think today? We purchased a little company, Aroki, experts in encryption, some of the smartest security minds on the planet. And today we introduce query-able encryption, which basically enables developers, without any security background, to be able to build searchable capabilities into their applications to access data and do it in a way where the security rules and the privacy all remain constant, regardless of whether that developer or the end user actually knows how that works. >> This is a great example of people talk about shift left, designing security in, for the developer, right from the start, not as a bolt-on. It's a great example. >> And I'm actually going to ground that with a real life customer example, if that's okay, Dave. We actually have a utility company in North Carolina that's responsible for energy and water. And so you can imagine, I mean, you alluded to the IO to use case, the industrial use case and this particular customer has to contend with millions of sensors that are constantly streaming data back, right. And now think about the challenge that they were encountering. They had all this data streaming in and in large quantities and they were actually resident on numerous databases, right. And so they had this very real challenge of getting to that quality data that I, data quality that I talked about earlier, as well, they had this challenge of being able to consolidate all of it and make sense of it. And so that's where our partnership with MongoDB really paid off where we were able to leverage Pentaho to integrate all of the data, have that be resident on MongoDB. And now they're leveraging some of the data capabilities, the data fabric capabilities that we bring to the table to actually deliver meaningful insights to their customers. Now their customers are actually able to save on their electricity and water bills. So great success story right there. >> So I love the business impact there, and also you mentioned Pentaho, I remember that acquisition was transformative for Hitachi because it was the beginning of sort of your new vector, which became Hitachi Ventara. What is Lumada? That's, I presume the evolution of Pentaho? You brought in organic, and added capabilities on top of that, bringing in your knowledge of IOT and OT? Explain what Lumada is. >> Yeah, no, that's a great question, Dave. And I'll say this, I mentioned this early on, we fundamentally believe that data is the backbone for all digital transformation. And so to that end, Hitachi has actually been making a series of acquisitions as well as investing organically to build up these data capabilities. And so Pentaho, as you know, gives us some of that front-end capability in terms of integrations and so forth. And the Lumada platform, the umbrella brand name is really connoting everything that we do in the data space that allow customers to go through that, to derive those meaningful insights. Lumada literally stands for illuminating data. And so that's exactly what we do. Irrespective of what vertical, what use case we're talking about. As you know very well, Hitachi is very prominent in just about every vertical. We're in like 90% of the Fortune 500 customers across banking and financial, retail, telecom. And as you know very well, very, very strong in the industrial space as well. >> You know, it's interesting, Peder, you and Radhika were both talking about this sort of edge model. And so if I understand it correctly, and maybe you could bring in sort of the IOT requirements as well. You think about AI, most of the AI that's done today is modeling in the cloud. But in the future and as we're seeing this, it's real-time inferencing at the edge and it's massive amounts of data. But you're probably not, you're going to persist some, I'm hearing, probably not going to persist all of it, some of it's going to be throwaway. And then you're going to send some back to the cloud. I think of EVs or, a deer runs in front of the vehicle and they capture that, okay, send that back. The amounts of data is just massive. Is that the right way to think about this new model? Is that going to require new architectures and hearing that Mongo fits in. >> Yeah. >> Beautifully with that. >> So this is a little bit what we talked about earlier, where historically there have been three silos of data. Whether it's classic system of record, system of engagement or system of intelligence and they've each operated independently. But as applications are pushing in further and further to the edge and real time becomes more and more important, you need to be able to take all three types of workloads or models, data models and actually incorporate it into a single platform. That's the vision we have behind our developer data platform. And it enables us to handle those transactional, operational and analytical workloads in real time, right. One of the things that we announced here this week was our columnar indexing, which enables some of that step into the analytics so that we can actually do in-app analytics for those things that are not going back into the data warehouse or not going back into the cloud, real time happening with the application itself. >> As you add, this is interesting, as basically Mongo's becoming this all-in-one database, as you add those capabilities, are you able to preserve, it sounds like you've still focused on simplicity, developer product productivity. Are there trade off, as you add, does it detract from those things or are you able to architecturally preserve those? >> I think it comes down to how we're thinking through the use case and what's going to be important for the developers. So if you look at the model today, the legacy model was, let's put it all in one big monolith. We recognize that that doesn't work for everyone but the counter to that was this explosion of niche databases, right? You go to certain cloud providers, you get to choose between 15 different databases for whatever workload you want. Time series here, graph here, in-memory here. It becomes a big mess that is pushed back on the company to glue back together and figure out how to work within those systems. We're focused on really kind of embracing the document model. We obviously believe that's a great general purpose model for all types of workloads. And then focusing in on not taking a full search platform that's doing everything from log management all the way through in-app, we're optimizing for in-app experiences. We're optimizing analytics for in-app experiences. We're optimizing all of the different things we're doing for what the developer is trying to go accomplish. That helps us maintain consistency on the architectural design. It helps us maintain consistency in the model by which we're engaging with our customers. And I think it helps us innovate as quickly as we've been been able to innovate. >> Great, thank you. Radhika, we'll give you the last word. We're seeing this convergence of function in the data based, data models, but at the same time, we're seeing the distribution of data. We're not, you're clearly not fighting that, you're embracing that. What does the future look like from Hitachi Ventara's standpoint over the next half decade or even further out? >> So, we're trying to lean into what customers are trying to solve for, Dave. And so that fundamentally comes down to use cases and the approaches just may look dramatically different with every customer and every use case, right? And that's perfectly fine. We're leaning into those models, whether that is data refining on the edge or the core or the cloud. We're leaning into it. And our intent really is to ensure that we're providing that frictionless experience from end to end, right. And I'll give a couple of examples. We had this very large bank, one of the top 10 banks here in the US, that essentially had multiple data catalogs that they were using to essentially sort through their metadata and make sense of all of this data that was coming into their systems. And we were able to essentially, dramatically simplify it. Cut down on the amount of time that it takes to deliver insights to them, right. And it was like, the metric shared was 600% improvement. And so this is the kind of thing that we're manically focused on is, how do we deliver that quantifiable end-customer improvement, right? Whether it's in terms of shortening the amount to drive the insights, whether it's in terms of the number of data practitioners that they have to throw at a problem, the level of manual intervention that is required, so we're automating everything. We're trying to build in a lot of security as Peder talked about, that is a common goal for both sides. We're trying to address it through a combination of security solutions at varying ends of the spectrum. And then finally, as well, delivering that resiliency and scale that is required. Because again, the one thing we know for sure that we can take for granted is data is exploding, right? And so you need that scale, you need that resiliency. You need for customers to feel like there is high quality, it's not dirty, it's not dark and it's something that they can rely upon. >> Yeah, if it's not trusted, they're not going to use it. The interesting thing about the partnership, especially with Hitachi, is you're in so many different examples and use cases. You've got IT. You've got OT. You've got industrial and so many different examples. And if Mongo can truly fit into all those, it's just, the rocket ship's going to continue. Peder, Radhika, thank you so much for coming back in theCUBE, it's great to see you both. >> Thank you, appreciate it. >> Thank you, my pleasure. >> All right. Keep it right there. This is Dave Vellante from the Javits Center in New York City at MongoDB World 2022. We'll be right back. (upbeat music)

>> Live from Las Vegas. It's theCUBE. Covering Informatica World 2019, brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World. I am your host, Rebecca Knight, along with co-host, John Furrier. We have two guests for this segment. We have Abhiman Matlapudi. He is the Product Master at Deloitte. Welcome. >> Thanks for having us. >> And we have Kubalahm Rajeev Krishnan, Specialist Leader at Deloitte. Thank you both so much for coming on theCUBE. >> Thanks Rebecca, John. It's always good to be back on theCUBE. >> Love the new logos here, what's the pins? What's the new take on those? >> It looks like a honeycomb! >> Yeah, so interesting that you ask, so this is our joined Deloitte- Informatica label pin. You can see the Deloitte green colors, >> Nice! They're beautiful. >> And the Informatica colors. This shows the collaboration, the great collaboration that we've had over, you know, the past few years and plans, for the future as well. Well that's what we're here to talk about. So why don't you start the conversation by telling us a little bit about the history of the collaboration, and what you're planning ahead for the future. Yeah. So, you know, if we go like you know, ten years back the collaboration between Deloitte and Informatica has not always been that, that strong and specifically because Deloitte is a huge place to navigate, and you know, in order to have those meaningful collaborations. But over the past few years, we've... built solid relationships with Informatica and vise versa. I think we seek great value. The clear leaders in the Data Management Space. It's easy for us to kind of advise clients in terms of different facets of data management. You know, because no other company actually pulls together you know, the whole ecosystem this well. >> Well you're being polite. In reality, you know where it's weak and where it's real. I mean, the reality is there's a lot of fun out there, a lot of noise, and so, I got to ask you, cause this is the real question, because there's no one environment that's the same. Customers want to get to the truth faster, like, where's the deal? What's the real deal with data? What's gettable? What's attainable? What's aspirational? Because you could say "Hey, well I make data, data-driven organization, Sass apps everywhere." >> Yeah. Yeah absolutely. I mean every, every company wants to be more agile. Business agility is what's driving companies to kind of move all of their business apps to the Cloud. The uh, problem with that is that, is that people don't realize that you also need to have your data management governance house in order, right, so according to a recent Gartner study, they say by next year, 75% of companies who have moved their business apps to the Cloud, is going to, you know, unless they have their data management and data assets under control, they have some kind of information governance, that has, you know, context, or purview over all of these business apps, 50% of their data assets are going to erode in value. So, absolutely the need of the hour. So we've seen that great demand from our clients as well, and that's what we've been advising them as well. >> What's a modern MDM approach? Because this is really the heart of the conversation, we're here at Informatica World. What's- What does it look like? What is it? >> So I mean, there are different facets or functionalities within MDM that actually make up what is the holistic modern MDM, right. In the past, we've seen companies doing MDM to get to that 360-degree view. Somewhere along the line, the ball gets dropped. That 360 view doesn't get combined with your data warehouse and all of the transaction information, right, and, you know, your business uses don't get the value that they were looking for while they invested in that MDM platform. So in today's world, MDM needs to provide front office users with the agility that they need. It's not about someone at the back office doing some data stewardship. It's all about empowering the front office users as well. There's an aspect of AIML from a data stewardship perspective. I mean everyone wants cost take out, right, I mean there's fewer resources and more data coming in. So how how do you manage all of the data? Absolutely you need to have AIML. So Informatica's CLAIRE product helps with suggestions and recommendations for algorithms, matching those algorithms. Deloitte has our own MDM elevate solution that embeds AIML for data stewardship. So it learns from human data inputs, and you know, cuts through the mass of data records that have to be managed. >> You know Rajeev, it was interesting, last year we were talking, the big conversation was moving data around is really hard. Now there's solutions for that. Move the data integrity on premise, on Cloud. Give us an update on what's going on there, because there seems to be a lot of movement, positive movement, around that. In terms of, you know, quality, end to end. We heard Google up here earlier saying "Look, we can go into end to end all you want". This has been a big thing. How are you guys handling this? >> Yeah absolutely, so in today's key note you heard Anil Chakravarthy and Thomas Green up on the stage and Anil announced MDM on GCP, so that's an offering that Deloitte is hosting and managing. So it's going to be an absolutely white-glove service that gives you everything from advice to implement to operate, all hosted on GCP. So it's a three-way ecosystem offering between Deloitte, Informatica, and GCP. >> Well just something about GCP, just as a side note before you get there, is that they are really clever. They're using Sequel as a way to abstract all the under the hood kind of configuration stuff. Smart move, because there's a ton of Sequel people out there! >> Exactly. >> I mean, it's not structured query language for structured data. It's lingua franca for data. They've been changing the game on that. >> Exactly, it should be part of their Cloud journey. So organizations, when they start thinking about Cloud, first of all, what they need to do is they have to understand where all the data assets are and they read the data feeds coming in, where are the data lakes, and once they understand where their datas are, it's not always wise, or necessary to move all their data to the Cloud. So, Deloitte's approach or recommendation is to have a hybrid approach. So that they can keep some of their legacy datas, data assets, in the on premise and some in the Cloud applications. So, Informatica, MDM, and GCP, powered by Deloitte, so it acts as an MDM nimble hub. In respect of where your data assets are, it can give you the quick access to the data and it can enrich the data, it can do the master data, and also it can protect your data. And it's all done by Informatica. >> Describe what a nimble hub is real quick. What does a nimble hub mean? What does that mean? >> So it means that, in respect of wherever your data is coming in and going out, so it gives you a very light feeling that the client wouldn't know. All we- Informatica, MDM, on GCP powered by Deloitte, what we are saying is we are asking clients to just give the data. And everything, as Rajeev said, it's a white-glove approach. It's that from engagement, to the operation, they will just feel a seamless support from Deloitte. >> Yeah, and just to address the nimbleness factor right, so we see clients that suddenly need to get into new market, or they want to say, introduce a new product, so they need the nimbleness from a business perspective. Which means that, well suddenly you've got to like scale up and down your data workloads as well, right? And that's not just transactional data, but master data as well. And that's where the Cloud approach, you know, gives them a positive advantage. >> I want to get back to something Abhiman said about how it's not always wise or necessary to move to the Cloud. And this is a debate about where do you keep stuff. Should it be on on prem, and you said that Deloitte recommends a hybrid approach and I'm sure that's a data-driven recommendation. I'm wondering what evidence you have and what- why that recommendation? >> So, especially when it depends on the applications you're putting on for MDM, and the sources and data is what you are trying to get, for the Informatica MDM to work. So, it's not- some of your social systems are already tied up with so many other applications within your on premise, and they don't want to give every other data. And some might have concerns of sending this data to the Cloud. So that's when you want to keep those old world legacy systems, who doesn't want to get upgrades, to your on premise, and who are all Cloud-savy and they can all starting new. So they can think of what, and which, need a lot of compute power, and storage. And so those are the systems we want to recommend to the Cloud. So that's why we say, think where you want to move your data bases. >> And some of it is also driven by regulation, right, like GDPR, and where, you know, which providers offer in what countries. And there's also companies that want to say "Oh well my product strategy and my pricing around products, I don't want to give that away to someone." Especially in the high tech field, right. Your provider is going to be a confidere. >> Rajeev, one of the things I'm seeing here in this show, is clearly that the importance of the Cloud should not be understated. You see, and you guys, you mentioned you get the servers at Google. This is changing not just the customers opportunity, but your ability to service them. You got a white-glove service, I'm sure there's a ton more head room. Where do you guys see the Cloud going next? Obviously it's not going away, and the on premise isn't going away. But certainly, the importance of the Cloud should not be understated. That's what I'm hearing clearly. You see Amazon, Azure, Google, all big names with Informatica. But with respect to you guys, as you guys go out and do your services. This is good for business. For you guys, helping customers. >> Yeah absolutely, I think there's value for us, there's value for our clients. You know, it's not just the apps that are kind of going to the Cloud, right? I mean you see all data platforms that are going to the Cloud. For example, Cloudera. They just launched CDP. Being GA by July- August. You know, Snowflake's on the Cloud doing great, getting good traction in the market. So eventually what were seeing is, whether it's business applications or data platforms, they're all moving to the Cloud. Now the key things to look out for in the future is, how do we help our clients navigate a multi Cloud environment, for example, because sooner or later, they wouldn't want to have all of their eggs invested in one basket, right? So, how do we help navigate that? How do we make that seamless to the business user? Those are the challenges that we're thinking about. >> What's interesting about Databricks and Snowflake, you mentioned them, is that it really is a tell sign that start-ups can break through and crack the enterprise with Cloud and the ecosystem. And you're starting to see companies that have a Sass-like mindset with technology. Coming into an enterprise marketed with these ecosystems, it's a tough crowd believe me, you know the enterprise. It's not easy to break into the enterprise, so for Databricks and Snowflake, that's a huge tell sign. What's your reaction to that because it's great for Informatica because it's validation for them, but also the start-ups are now growing very fast. I mean, I wouldn't call Snowflake 3 billion dollar start-up their unicorn but, times three. But it's a tell sign. It's just something new we haven't seen. We've seen Cloudera break in. They kind of ramped their way in there with a lot of raise and they had a big field sales force. But Data Bear and Snowflake, they don't have a huge set in the sales force. >> Yeah, I think it's all about clients and understanding, what is the true value that someone provides. Is it someone that we can rely on to keep our data safe? Do they have the capacity to scale? If you can crack those things, then you'll be in the market. >> Who are you attracting to the MDM on Google Cloud? What's the early data look like? You don't have to name names, but whats some of the huge cases that get the white glove service from Deloitte on the Google Cloud? Tell us about that. Give us more data on that. >> So we've just announced that, here at Informatica World, we've got about three to four mid to large enterprises. One large enterprise and about three mid-size companies that are interested in it. So we've been in talks with them in terms of- and that how we want to do it. We don't want to open the flood gates. We'd like to make sure it's all stable, you know, clients are happy and there's word of mouth around. >> I'm sure the end to end management piece of it, that's probably attractive. The end to end... >> Exactly. I mean, Deloitte's clearly the leader in the data analytics space, according to Gartner Reports. Informatica is the leader in their space. GCP has great growth plans, so the three of them coming together is going to be a winner. >> One of the most pressing challenges facing the technology industry is the skills gap and the difficulty in finding talent. Surveys show that I.T. managers can't find qualified candidates for open Cloud roles. What are Deloitte's thought on this and also, what are you doing as a company to address it? >> I mean, this is absolutely a good problem to have, for us. Right, which means that there is a demand. But unless we beat that demand, it's a problem. So we've been taking some creative ways, in terms of addressing that. An example would be our analytics foundry offering, where we provide a pod of people that go from data engineers you know, with Python and Sparks skills, to, you know, Java associates, to front end developers. So a whole stack of developers, a full stack, we provide that full pod so that they can go and address a particular business analytics problem or some kind of visualization issues, in terms of what they want to get from the data. So, we teach Leverate that pod, across multiple clients, I think that's been helping us. >> If you could get an automated, full time employee, that would be great. >> Yeah, and this digital FD concept is something that we'd be looking at, as well. >> I would like to add on that, as well. So, earlier- with the data disruption, Informatica's so busy and Informatica's so busy that Deloitte is so busy. Now, earlier we used plain Informatica folks and then, later on because of the Cloud disruption, so we are training them on the Cloud concepts. Now what the organizations have to think, or the universities to think is that having the curriculum, the Cloud concepts in their universities and their curriculum so that they get all their Cloud skills and after, once they have their Cloud skills, we can train them on the Informatica skills. And Informatica has full training on that. >> I think it's a great opportunity for you guys. We were talking with Sally Jenkins to the team earlier, and the CEO. I was saying that it reminds me of early days of VMware, with virtualization you saw the shift. Certainly the economics. You replaced servers, do a virtual change to the economics. With the data, although not directly, it's a similar concept where there's new operational opportunities, whether it's using leverage in Google Cloud for say, high-end, modern data warehousing to whatever. The community is going to respond. That's going to be a great ecosystem money making opportunity. The ability to add new services, give you guys more capabilities with customers to really move the needle on creating value. >> Yeah, and it's interesting you mention VMware because I actually helped, as VMware stood up there, VMCA, AW's and NSA's offerings on the Cloud. We actually helped them get ready for that GA and their data strategy, in terms of support, both for data and analytics friendliness. So we see a lot of such tech companies who are moving to a flexible consumption service. I mean, the challenges are different and we've got a whole practice around that flex consumption. >> I'm sure Informatica would love the VMware valuation. Maybe not worry for Dell technology. >> We all would love that. >> Rajeem, Abhiman, thank you so much for joining us on theCube today. >> Thank you very much. Good talking to you. >> I'm Rebecca Knight for John Furrier. We will have more from Informatica World tomorrow.

[Music] hi I'm Stu Mittleman and welcome to a cube conversation really excited to have to the program a first-time guest and a user Vinny Chopra is an IT engineer with Medallia Vinny thank you so much for joining us thank you and - Vinny's left we have Krishnan bad Rena Ryan in who's a director of product marketing with Nutanix Chris thanks so much for you here okay so we always love to be able to dig in with the customers understand the challenges they're facing Chris let's set the table first I'm very familiar with Nutanix we go to all the new tannic shows and the like but for customers what is Nutanix to them why do they turn to Nutanix okay absolutely so I think it's a great time to be in IT you see new businesses that are sprouting at all the last 10 years or so starting with uber Airbnb specifically the ones we've really heard of that have disrupted some really really big industries right so technology is making it happen while IT teams are the ones that help make that happen and helps those CEOs disrupt they're not in the best of positions to utilize infrastructure they have today the way it's set up to be able to get more done be more agile and truly serve the needs of the business and help create those competitive differentiation which is why neutronics is here to help our partners within companies such as yourself to be able to be those people to lean in and help CEOs really achieve what they're trying to get that yeah that's great yeah we definitely see it used to be okay IT was a cost center IT you know business would actually ask for something in IT would often be the no or be really slow and do they work with that so Vinnie before we dig into the IDE piece of it tell us a little bit about Medallia the business what's happening what's Sherma Delia's been around for about 15 years now we're located in it we're headquartered in San Mateo we used to be in Palo Alto moved last year we have a brand new building right off 101 a 92 we our analytics company and we and there's a lot of lots of fields in analytics we specialize in an area called CX which stands for customer experience and our goal is to make our customers customers happy which therefore makes our customers happy and we specialize in doing surveys and then especially in designing surveys for different types of companies and then and then we analyze that data you know surveys well Vinny I I find there's very few companies that I talked to whose industries are stagnant or not changing much the analytic space space that we cover heavily you know here here on the cube and with our research it's boy has that changed a lot I mean five years ago we were talking very much about Big Data today you know all the AI ml and and things like that what what give us a little bit about what's it like being in that business you know fast driving your silicon valley-based I have to imagine that the business is going through a lot of changes that put stresses and strains on IT oh definitely so I better the IT industry for many years and IT area different big companies Sun Microsystems Juniper Networks NetApp in the past excite calm which was a search engine way back when before Google days I remember excite you know because Microsoft didn't they buy that or things well there was an early cerulean at home there's a partnership with that on but yeah excited people would confuse as to wait excite calm what kind of site was that it's like no no it's a search engine back before by the way audience for those of you that haven't been around a while it wasn't all just being in Google there were a lot of predecessors that there was four or five big search engines at that time so most of my company had been out we've always been packaging stuff in a box and selling it in this is my first time at an analytics company and it's it's like you said it's a fast-moving field things are being the things there's no development staging production type of stuff things are just continuously being put into production changes are made you know customized you know customer's applications and their interface so it's it's a very fast-moving alright and Vinny you say IT engineers your job what does that encompass what your role how many people in the group what is your sure so we have basically two IT groups we have one that manages our production data centers which are which our customers interface with and we have one that supports our engineers so I'm part of that group and it's kind of a week up art of the IT system and engineering team and that involves traditional IT tasks like backups monitoring application install new server installs managing storage networking basically keeping infrastructure and applications running as efficiently as possible and therefore keeping our engineers happy because they can get their work done and their development done okay sounds like a you know pretty typical from from what I hear from companies is it what do you hear from customers structure-wise challenges they're facing absolutely so it's very much in line with what you were just talking about where there's these multiple needs from the business and customer expectations so how do you really help IT organizations be able to keep up with those needs infrastructure needs to be the big quittez data needs to be Vic witness application services need to be Vic Willis and you need to be able to scale out as your business needs needs to do so to be able to serve all those multiple requirements so whether it's standardizing internal applications that are delivered through virtual desktops or deploying databases are starting up customer websites you need to be able to do that and respond as quickly as possible and if you're spending cycles on acquiring infrastructure deploying it making sure it's well integrated and then once it's up and running figuring out what went wrong and enjoying those multiple nights of pizza right to figure out how to get this thing going back to the way it was it's it just distracts you from what's important so it's only when you make infrastructure invisible and truly scalable very much cloud-like and and make it your own as a process of doing so can you truly be that business partner and you and I hope we've done that with you definitely all right so Bennie let's go inside was there a specific project rollout that you would that led towards Nutanix was there a pain point you were having would give us kind of the before and what was the mature so traditionally an IT you would you want to set up a new application at you in your infrastructure environment you would buy servers and you would buy storage you would buy HBA cards which helps you connect the servers to the storage you've got things like worldwide numbers to worry about getting the right cables getting the right cards and then you put it all together you get all the stuff delivered and then two weeks later you might have things working and but you having some permission issues security issues so it was always a big challenge to get things up and running so it was the fun of ideas let's roll up our sleeves let's turn those geek knobs and you know optimize everything and yeah within six months I'm sure everything's rocking in right everything's rocking rolling but you're still not quite confident that things are running you're worried that a card might go bad you're worried that a world-wide number might change somewhere or somebody might you know mess up your security so you would spend a lot of time just getting things up and running versus spending time on development and you know working with your people you're supporting and trying to try to enhance things versus just keeping things getting things up and running so Nutanix you know with the hyper-converged infrastructure you know what kind of we're not worried about those things anymore it has our storage needs it has our compute needs it has our memory needs so what was it a refresh cycle what was the impetus that led to looking at a new arc sugar as we were growing and entering base was growing an IT was growing and our requests and you know what we need to satisfy was increasing tremendously we before we were working with just individual desks like desktops or blade servers but each one was kind of working individually with its own storage its own applications not the notion things weren't being shared or anything and we were just growing fast so we needed some we need a new infrastructure where we could actually have everything working of most efficiently and be secure and fast and and easy to manage and so we did look at we did some analysis on a few products and Nutanix you know after some a few pocs Nutanix was our product of choice yeah I mean you described something we heard a lot is it used to be every application you would kind of build your own temple for it yeah let me build it let me get the performance I need let me optimize certain things let me forecast how it's gonna grow but I get islands out there as opposed to I want to be able to scale I don't want to worry about you know here's one of the challenges out there most people and across the board forecasting is really hard or impossible I either overestimated a bunch and then I bought stuff I didn't eat her right under missed it estimate it and then oh my gosh I need to look to a new architecture yeah and then things ended up burning like at 10% of you know you utilizing temperature of the resources that you're purchasing yeah I remain poor virtualization it was like you know six seven percent is usually what we were running awesome so challenges before and we had you know silos out there I couldn't share I couldn't do talk about that that role how did you get from that old environment to the new one there's something I said when you you look at this wave of really a distributed architecture in the old world migrations were really really tough yeah and you had to do it with every cycle hopefully moving to an architecture like this this is your last migration it was like you know my wife always said the last time that's the last time I never want to have to move well I T I'm sure those migrations were always painful what was the experience my heading to migrations was is one thing that we went through but also just now it's just setting up new VMs or new applications new servers it's you know within a few minutes versus hours as far as migration we were we were running a hypervisor before but like I said it was on individual servers so the migration was basically picking your VMs or your servers one at a time and just migrating over to Tenex once it was there and you know with the hypervisor tools that are available it's very easy to use it's like things like vmotion or different types of migration tools that Nutanix offers with their hv hypervisor so it was just it was pretty seamless it was just you just pick and choose and identify your destination host ons Nutanix node or Nutanix cluster and all your stories that you want to move it to and just go okay so so Vinnie you went through a bit of a bake-off to figure out the solution tell us when you finish the deployment how are you measuring what does success mean to in deployment of your stand point and give us the after what show does this change for your process your organization sure qualitatively success is when our engineers are smiling and not calling us too much and asking us go to lunch versus telling us about issues they're having so that's qualitatively quantitatively looking at performance CPU memory I ops performance on a storage how our applications responding that that's what we measured it quantitatively yeah did you know like what kind of utilization you're getting on your current infrastructure then with the Nutanix um also currently you meet as far as uh what you said you were lucky to get 10% in the old world do you measure that yeah we met her that week we kind of um you know we have our kind of have our choices of how much storage you want to use how much CPU remember you want to allocate to each VM and we we just monitor it and through the prism interface that Nutanix offers the image you can actually see performance of each VM and you can decide when to throttle things so but as far as you know how much we're utilizing we're you know we have it we have a structured where we have room to grow so yeah absolutely and if we do need to grow later we can easily add nodes or you know chassis wood notes yeah I think back to the early years of you know what we call hyper converge environments and it was like oh well they are monolithic blocks even if they're small and but you don't have flexibility there when I look at you know many of the solutions especially what Nutanix ups there's a lot of flexibility into how I can grow in scale and get the the utilization that I need but get the performance the ops and everything what I think from your customers how is that story play out today yeah I mean ultimately it's all about empowering people right it's about making IT people truly successful broadening their skillset giving them greater control over the full stack if you will right so it's no longer siloed across functions you're no longer found helpless relying on a different team to deliver upon something that was promised based on a certain SLA so how do we do that how do we make evolved functional specialists into IT journalists would then become cloud engineers true cloud engineers right the world is changing technology is adapting businesses are a craving for more and the only way we can keep up is to adapt ourselves and utilize the best of breed technologies that gives us that power so as a result we hear that a lot where we find a lot of a customer's progressing from being either storage admins network specialists but most likely virtualization admins who then become these cloud engineers if you will they reorganize that way they tend to be in a position where they are a lot more infrastructure we're talking about 100x of what they used to do prior in the in the earlier days so the the number of the ratios just grow immensely as well as the quality of service provided the SAS are far reduced as they used to be so all of that goodness that our customers are able to deliver to their state goes in the organization makes us feel good about what we do if any would love we talked about you know this the engineers now they're smiling and going out to further then you know fighting bugs anything complaining about is yeah anything kind of when you look at skill set if they're you know I've talked to some entertainment customer he's like oh you know I had that security project that was sitting on my desk for years I can finally tackle that or there's I can be more responsive to the business so that they don't you know I can engage with them rather than just going off running it and do in stealth IT any anything along those lines that you can share I mean one thing like IT admins we typically want to know everything right so we all know what's happening behind the scenes with Nutanix we don't have to as much but we still like to and so we we take the opportunity to you know do trainings learn what's happening in an interface you support when needed so as far as yeah as far as skills go I think it's you know the skills you keep up with it's just different like Chris mentioned it's different different type of administration like we're managing virtualization or managing cloud you know you're not just managing loans and cables you know I love you sounds like you've got a team that's got that intellectual curiosity wants to understand what's going on how was the how was the on-ramp how was the kind of the cycle to understand the Nutanix piece how did you yeah so we learned a lot of the POC of course that's when you kind of you know you can play around with stuff and break stuff and try to break stuff if you want we use professional we used some freshly served since to help us get set up originally and after that it was just kind of learning day to day and just improving improving our knowledge in different areas like not if we're not used to having everything in one like in you know in one kind of a couple jassi's storage and you know compute so that was a networking as well so that was a little bit not challenged technically but just just you just need to reset the mindset these are the way I used to do things versus the the way now I can't do three and in troubleshooting um you know the great thing is when we have troubleshooting we're not calling three different vendors like a networking company a storage company in a compute company and having them point fingers oh it's networking now we if I ever have an issue or a question I call Nutanix supporting it so if any how long has it been since you the solution was deployed about two and a half years now awesome so it but you first of all I love your viewpoint as to how Nutanix has changed in those two those two years and along those lines too now that you look at things through the lens of 2018 if you could go back to peers of yours what would you tell them now that you wish you had known back when you rolled this out a couple of years ago I would you know how to tell them there's a much easier way to minute you know the deploy and manager infrastructure and you know this is this is one of the new techniques is definitely something you should look at alright Chris what what advice do you give to the IP people of the world that you know I'm sure most of them heard about this but you know what misconceptions might they have what what things do we want to make sure we open the door for sure so as a former developer myself you know several years ago I think it's very easy for us to forget the role we play in our organizations we're not all about the applications we're not all over the speeds and feeds we had a critical core part of how businesses go to market and achieve success right so let us recognize that and use the best approaches that are available out there to be able to deliver that value right if it means going where the good hyper-converged infrastructure solution if it means leaning in and building new disruptive technologies and such that can help your businesses do better the other thing that I want to highlight is just as you are in the the customer service business I believe we are as well we pride ourselves on our support so if you have if ask questions about how hyper-converged infrastructure can add value call us give support a call you would be put in touch with anyone who can speak about all the values we deliver to our customers and begin to get some of those ideas all right Vinnie uh want to ask you you you've got some experience works for some of the you know really well-known companies you not only here in the valley but in tech in general what's exciting you these days what do you look at either in the analytic space or an IT that that's getting you excited for me it's I like to get up without stress and so ease of management ease of deployment in the IT area is very that that's one of things I look forward to like you know being able to do other stuff than just focusing on data you know routine stuff yeah and one of those lines if I could give you you know the one wish to help make that goal even more either from Nutanix or you know the broad ecosystem out there what would what would make your job even easier you know it's it's I don't know I'm trying to think of a good answer but it's typically you know when issues once them all we have application issues it would just be some kind of self-healing type things you know maybe or maybe some automatic adjustments that could be done that maybe something in the future yeah like I just means as far as resources allocated to different types of yeah all right Chris sure I'll let you have the final word there cuz absolutely once we simplify modernize the platform modernizing the application some it's definitely something I've heard from many of your customers as to you know that role of infrastructure really is to serve up and support those applications and that seems to be where it's going that's right that's right the the business partners right partners the business CFO whoever on the other side of the fence they care about applications and services not so much about all the blood sweat and tears we put into the infrastructure so I think it's an opportunity for us to help us elevate beyond the infrastructure and focus on apps and services along with making sure we have some of those self-healing capabilities such that take care of us and not require us to pay heat to all those infrastructure speeds and feeds so it's a great opportunity to do and you know be truly strategic in the company right alright well Chris really appreciate you sharing the updates Vinny really appreciate you sharing your customer story it's our purpose here at the cube to always help bring out the information so make sure to check out the cube net if you actually go to the top there's a search we've got over five or six thousand interviews we've done including many customers including many of Nutanix go in search Nutanix you'll find a plethora of content out there if you ever have any question for us please reach out to us see us at any of the shows or in between so I'm Stu minimun and thanks again for watching the cube thank you

(uplifting music) Hi, I'm Peter Burris. Welcome to another CUBEConversation from our wonderful studios in beautiful Palo Alto, California. Once again, we got a great topic today and we're going to be talking a little bit about the role that security is playing in multicloud. Now to have that conversation we've got Hari Krishnan here with us. Hari is the Senior Director of Product Management for security at Nuage Networks which is a division of Nokia. Hari, welcome to theCUBE. >> Glad to be here, thank you. >> So here's why this is so important, Hari. A lot of people for years have been talking about how, data is going to move to the cloud. Well, there's certainly going to be some of that. Increasingly, people are recognizing it. The more important strategy or the better strategy, think about how we're moving the cloud services to the data. Which means we're going to have multicloud. And as we think about moving data around making data more of a primary citizen within the business, and certainly within the networking world. It means that we have to think differently about the role that networking plays in that multicloud, specifically around security. Talk to us a little bit about first Nuage Networks, who you are? And then let's get into this question of what does it mean for networking, security in this multicloud world? >> Absolutely. I know it's a great, great question, thanks, Peter. So first of all, Nuage Networks. We are a business unit within Nokia, and we are sort of the SDN arm, if you will. Software Defined Networking and security for both data center branch and goes without saying in the multicloud era, we provide solutions that are both secure, as well as connect these an end to end multiple environments across these spread networks, both from a branch perspective as well as from from a data center and cloud perspective. >> So these are all the locations where activity is going to happen, therefore data has to be there, but they still have to be in a connected way. So talk to us about this challenge of networking in a multicloud world. Because it's not all one way. It's going to be all ... It's going to be a very, very complex arrangements of resources that have to be brought together with performance, flexibility and security. What does that require? >> Yes,that's a great question. So we have a lot of customers. We talked about our enterprise customers who have gone down this multicloud plat because they have workloads, and as you said workloads and data, and based upon the application, they are making choices for a particular cloud. Some of them may be more analytics oriented, they chose a particular cloud environment for that workload. So they have workloads invariably across multiple clouds. In addition to that they have a large set of those assets and key assets and data that are residing in their private data center as well. And they are looking at how they can provide better connectivity to these cloud applications from their branch. So as you rightly put, the problem is how do you do that in this sort of heterogeneous environments? And today a lot of the solutions are siloed. What you find is you have multicloud networking and security solutions, but they don't really tackle the problem of connecting these branches or SD-WAN, that SD-WAN vendors focus on. But they really don't address these cloud challenges. So really there are these silos that we find in the enterprise. We also see vendors going in and offering solutions that are focused on particular environments, maybe containers, for example, or maybe specific types of virtual machines. But really from an enterprise perspective, their assets and data are everywhere, and they are in different forms. So what Nuage set out to do from the very beginning, was to provide a platform that really connects these regardless of where these workloads reside, and these workloads can be heterogeneous. Really whether it is containers, whether it is virtual machines, whether it is bare metal, whether it is on-prem or in the public cloud. And really that's really been our core focus, and we have had a lot of success working with service providers on the SD-WAN, and we just announced as SD-WAN 2.0 which is really about more than connectivity, providing IT services over these IP networks, whether it is about visibility, analytics, security. So again, our platform-based approach lends well with not only addressing the SD-WAN use cases, we also have a presence with large customers, large enterprises as well as with cloud service providers using our platform for private cloud offering as well as public cloud offering. >> So if we kind of think about the problem statement. We're talking about a world that is increasingly dependent, from a digital business standpoint on the role of data is going to play. Increasingly thinking about how that data interacts with each other and how we secure that data, because that's the basis for making it private. With a lot of new workloads on the horizon and a lot of new resources that could be running those workloads, whether it's virtual machines or containers or anything that might come along in the future. And the networking has to be flexible enough that it can handle those new classes of workloads, those new notions of data and data security and the new resources, many of them software that are coming on to create these applications. Have I got that right? >> Absolutely. So your networking has to be flexible enough and your security model has to be fundamentally different. And what I mean by that is you know we have a perimeter centric approach earlier which is sufficient if you have all the workloads in one location You know, the workloads in this. >> So perimeter centric is sufficient if the device is the first citizen of the network, right? >> Absolutely. >> So keep going, I'm sorry. >> Absolutely, so with workloads as they are moved around and especially you know in a cloud environment or in a very dynamic environment such as in a container environment, these are spun up and down. The architecture needs to be more tied to the workloads and data. Security needs to be tied to the workload, and we call that the workload centric security model. And again, fundamental to this is the notion of as Forrester talked about zero trust, which is again about you know not assuming any trust, just because your workload is in a particular location, and you cannot allow certain users to just, you know access that workload because by virtue of it being in a particular location as an example, right? So really it should be tied to the workloads, and if the workloads are moved around, the policy should move with the workload. And again fundamental to this is again a change in the architecture, where the policies are enforced closer to the workload, the policies independent of where the workload resides, and the policy should govern not only a particular environment or set of environment, such as multicloud, but access from anywhere to that workload. By that I mean a user can come in from a branch, and we want to make sure that that branch user is only able to access that workload, regardless of where workload resides, right? So today if you look at it, the solutions are very siloed in the sense that you have micro segmentation implementations in a particular environment, but they really don't tie in the policy end to end. They don't do end to end segmentation from the branch to the data center. And that's really where we focus on, is providing this end to end approach to securing workloads and data, regardless of where the workloads are coming. I would say for example, if your workloads and data are moved to Mars, your policy should be able to move with the workload and secure it, right? It's really location independent. >> But fundamentally it's that security capability has to move with the workload. >> Absolutely. >> That's really what the customer... That's really what the enterprise wants. They want the security capability where the policy and some of the other resources that you're talking about are what provide that capability. >> Absolutely. >> And John Kindervag is a very, very smart guy. Ex-Forrester guy who came up with this notion zero trust. Great ex-colleague. So if we think about it, we've got this problem statement that increasingly the world's becoming digital, and now we have to make the workload and the data the first citizen. That's going to require a new architectural approach, new types of technologies, Nuage is the vanguard of providing that approach. Let's get into some of the examples. How are customers using this today to improve their security and avoid problems of the past. >> Absolutely. So, we have, customers who are using this. And I'll give you some examples of it right. And a lot of the customers when they look at us, they really see the architecture as a key advantage, being able to provide end to end security across heterogeneous environments. And I'll give you some example. They typically have a starting point, right? I mean, that's, you know, I'll give you an example of one of the large financial customers we are working with. They are looking at securing workloads in public cloud. And this is a container environment running OpenShift and Kubernetes, and they want to be able to secure the workloads. One of the key requirements in the public cloud is that, and this goes hand in hand with zero trust notion, is that they don't want to actually trust the public cloud vendor and regardless of who their vendor is. So they want to encrypt all the traffic between workloads in the public cloud, not only segmentation and getting full visibility into it, but also providing encryption. And so for for them, you know, what Nuage offers is the ability to do exactly that. We can secure these container workloads in the public cloud. We can enter the communications between the workloads. We brought in the same encryption mechanism that we had, you know SD-WAN into this public cloud, to solve this use case. And not only that, we can also securely connect those public cloud workloads to their on-prem legacy data center. For certain applications they need to connect back into the data center. And so we have a consistent policy model, with security, segmentation, visibility and encryption. That's a great example of from a public cloud and the multicloud example. The other example is in a traditional data center. Often times and this is again a large enterprise, who is currently deploying this micro segmentation technology and for them they don't have sufficient East-West protection within the data center. And so where Nuage comes in is the ability to be able to provide security that is again tied to the workload, and their environment is very heterogeneous. They not only have ESXI, they have a lot of bare metal. They have some KVM deployments. So they are looking for a common way to provide security for the workloads, regardless of what virtual machine type it is or what form factor the workload is. >> And it doesn't diminish the characteristics of those resources that they use because they provide certain advantages to using those resources. >> Absolutely, absolutely. I mean a lot of the key workloads and data that they have, some of them are in, you know, bare metal. Running in bare metal, right? It's a lot important for them, to be able to secure those workloads and do that in a way consistently because you have containers that may be communicating with an infrastructure service which is running on bare metal, for example. So how do you do that in a unified way? And that's really where you know we come in as providing the single policy, unified policy and visibility, in this heterogeneous environment. So that's an example of micro segmentation, a traditional data center. Another great example, and we have lots of service providers who are offering this as our SD-WAN service, where we provide secure connectivity with more than connectivity, but also providing visibility and analytics. So they can look at all the communication from the branch, not only to other branch locations, but also to workloads in the cloud. SAS is a is a great use case, local internet breakout to these cloud applications. So we provide security there and again, we have service providers who are offering this as a service. I mean, we have now several of them. BT-tellers and several service providers, that are offering our SD-WAN service. And just I think a couple of days back we announced the SD-WAN 2.0, where we are providing security, providing visibility, enabling value added services beyond just connecting with the SD-WAN environment. So those are some of the use cases beyond, you know, a single siloed environment. We're encompassing public cloud on-prem data center, but also more importantly, connecting workloads from branch to data center as well. >> So the last thing I want to do, is I want to ask you one quick question about the relationship between, with the evolving relationship between security, models, architectures, SOCs, and networking architectures, models and NOCs, and many people saying that they should be separated. We tend to think that that's a bad idea. But talk to us a little bit about how the evolution of security and networking comes together, especially as we think about both of them, starting with analytics, understanding having a discovery and remediation palette, so that the networking telemetry is informing security, the security telemetry is informing networking and you get a reasonable high quality response, no matter where you are in the organization. >> Absolutely. And you're spot on. I mean essentially networking and security combined will give much better value in terms of use cases protection, but also detection and response. And Gartner has been preaching this in adaptive security architecture which is really around, you know using, having a prediction model which is base lining based upon telemetary, based upon other sources of intelligence that you get and using that to drive protection. And just because your workloads are protected or micro segmented, doesn't mean that attacks would not go through. It's not a matter of when you're.... whether an attack happens or not, it's really when you are attacked, right? >> Well we've discovered the bad guys are patient. >> Absolutely and they'll continue to to find new ways to attack it. And so it's not just about prevention, but also using the intelligence, sources of data in the network to be able to detect and then take an action. Really, this has been referred by Gartner and in the industry as a sort of adaptive security architecture, which really requires a mindset change from sort of this incident response to a continuous response model, right? And we think that software- >> Driven by analytics? >> Exactly. And analytics is really the core of this. Because Analytics helps drive policies, but also helps detect new types of attacks. So really network has a very key role to play here because network is the source of truth. You see a lot of these attacks that are manifested in the network, and we can use this data. We can mine this data to be able to better prevent but also detect and respond quickly to these attacks. And again the change in mindset from sort of an incident response mindset to a continuous response mindset, all built upon this rich analytics that your network provides. >> Hari Krishnan, Nuage Networks talking about the relationship between security, networking and multicloud. Thanks very much for being on theCUBE. >> Thank you. >> And once again this has been a CUBEConversation. I'm Peter Burris. Thank you very much for listening. Until next time. (uplifting music)

>>live from Las Vegas. It's the Cube covering. Inform Attica World 2018 Not you. Buy. Inform Attica. >>Welcome back and run. Live here in Las Vegas at the Venetian Cubes coverage of In From Attica, World 2018. I'm John for the coast to queue with by host the next two days. Peter Barrister, head of research for Wicked Bonds with an Angle and the Cube. Our next two guests from Deloitte. Leo Cabrera, who's senior manager. And Rajeev Krishna, who's the specialist leader on the engineering side. CDO side guys, Thanks for joining us. Thank you, John. Thank you, Lloyd. The leader in a lot of areas, absolutely doing a lot of cutting edge stuff from c'mon, the Blockchain crypto side tax side also in the I t side. You guys have been in a great top customers here in data in from Atticus, leading the charge, looking good with the trends. But the cloud is here. Cloud scale ecosystems developing. How do you guys see in from Attica? Evolving. Going forward, Mostly great messaging. But they still got customers out there that have sold stuff. They want to bring in cloud native new data. What's what's the prospects were in from Attica. >>Foreign Formica, Saudi lawyer. We have this nuanced article data advantage and basically would consider the inflection point between what we call in just 3.0, industry for point. And it's basically now we want to get value out of the data and our data advantage strategy Focus on three pillars. They have engineering wilderness and enable men for as Informatica Isa great component and a great supporter in each of these areas. Right, So, through these study we offer video service is we offer data governance. Studio chief did offer sheet state all of it. Yeah, on. And we partner with Informatica to profile the data to understand what will be the points in which we can find value over the data on off course with the new enterprise catalog to tool to do better governance for our clients. >>I want to get under the hood. I see the catalog is getting a lot of great reviews. Some people think that this is the next big wave in data management, similar to what we've seen in other ways like well, what? Relational databases and every way that comes on cap this catalogue New kind of catalogs emerging. What's your view on this? Is it away? Visit like recycled catalog, is it? >>So get a cataloguing and data. Curation has bean going on for decades, right? But it's never gained traction on, and it's never given Klein's the value because it was so manual takes tons of effort to get it right, right. So what inform Attica is done, which is absolute breakthrough? This embed a i into their enterprise data can log into which kind of accelerates the whole data. Cataloging on basically gives them gives climbs. The value in terms of cutting down on there are packed in terms of how many people, how many data students you need to put together >>So they modernize that. Basically, they exactly all the manual stuff put automation around and put some software to find around at machine learning. Is that kind of the secret to their success? >>Absolutely. And Down Delight has been partnering with Informatica for quite a while. In fact, we are one of the few companies that have a seat on the product advice report s o what we see from the marketplace we cannot feed into in from Attica to say, Hey, here's what you need to build into your products, right? So we be doing that with their MDM solution. For example, we have what we have. Articles indium, elevate. So we build machine learning into their MP and platform and offer. That's a solution similarly, and for America has built the clear platform into their E. D. C s. Oh, that's absolutely driving Valley for clients. And we have a lot of clients that are already leveraging >>a lot of risk and platforms tools, right? I see a lot of data stuff out there that's like like a feature, not a platform, that these guys got a platform, right? So But now the world's changing the cloud. How do you guys take that data advantage program or go to a CDO and saying, Look, you gotta think differently around the data, protect you explain your view on that. >>For us, data is now the center of everything, right? So any business who want to remain competitive in the future needs to get into entire end twin management of the data, getting the value of off data and also understanding what is the data coming from and what is the day they're going to write off course is studded with all the regulations. And now GDP are coming on Friday. It is a big, you know, pusher for companies to realize that over. If >>you have a big party on Friday, a big party or is this what you Katie was a big part. Nothing happened. So you're never mean GDP. Are you guys have a lot going on there? I mean, this is the center of the conversation. >>Yeah. I mean, we do have a lot of clients who need to be compliant on GDP are on informatica is one of the tools that have already pre established the policies, so you can quickly determine where is the data that GPR is gonna be monitoring and looking for compliance on So rather than doing it from a scratch, right? So it takes a lot of it >>for Let's build on this a little bit. So when we talk about different as John was saying, different generations of data management technology, we're coming out of a generation was focused on extract, transform and load where every single application or every single new analytics application wasn't you identify the source is uniquely you build extractions unique. You'd build transformations, you build load scripts. Uniquely all that stuff was done uniquely. Now what we're saying is catalog allows us to think to move into a re use world. We've been reusing code fragments and gets and all these other things for years. In many respects, what we're talking about is the ability to bring a reuse orientation inside the enterprise to data. Have I got that right? You got it >>right. Two minutes. But the most important parties how to get value out of that, right? Because they did >>manage to get value out of using >>it more exactly And understanding, You know, how can improve your operations or you know, the bottom line, or reduce the risk that you have in your data, which is basically CPR is about, >>and one other Salin point is on very scene for America bringing values their completeness of mission. Right. So when you talk about gdp are you need different aspects, right? You need your data integration. Whether it be through cloud around. Promise you need get a governor on top of what you're cataloging, right? You need security data security. Right? So it all comes together in the hole in dramatic solutions. And I think that's very see value is supposed to like pocket pockets >>of guys. I gotta ask you a question. We've seen many ways. I think it's a big way this whole date away. But you guys, you have a term called industry four point. Oh, is what is industry but the Deloitte term. But what is that? What is industry four point? Oh, me. Can you define that? >>You wanna take that door? >>Yeah, sure. So we've seen, you know, revolutions in terms off technology and data on. We've seen people going from kind of the industrial revolution to the dark. Amira, What? Three terms in the street? Four point off where data is annoying, right? So data is an acid that needs to be completely leverage. Not just you look a reactively and retrospectively like How did we do? Right? And not even just for predictive analytics. We've seen that for a few years now. It's also about using data to drive. This is value, right? So are there new ways to monetize data? Are there new ways to leverage data and grow your business? Right? So that's what Industry four. No, no is about. >>That's awesome. Well, we got a lot of things going on here. Thanks for coming on. The Cube had a couple of questions. Got a lot of dishes going on. That preparing for the big opening of the Solutions Expo Hall. We're in the middle of all the action. You're out in the open, accused. What we do. We go out in the open final question, eyes around the CDO. Who should the chief date officer report to the C I O board? What >>do you >>guys seeing? Because the CDO now picking a strategic role if Davis the new oil. That data is the fourth wave of innovation that we've seen over centuries. What does that mean? For the chief Data Officer? More power? Why'd you report to the C i o? Why is the CEO reported the Chief Data officer? What's your take? >>Traditionally our clients in the past, where the mandate for the studios were more in the data governess, right? As of today, it is going more into enablement the data, right? So more than Analytics case. Still, service is so well seen clients going from the studio moving from under the CEO in tow, the CEO and into the CMO in some cases, more about marketing. However, at the lawyer, our proposition is that companies should do a big shift and funded the new data function as a totally new vertical next to H. R next to finance right, which have his own funding and the CDO being the leader of that function, reporting directly to the CEO or >>enablement side CEO handling much of three things engineering, governance and enablement correct. So the CEO will handle Engineering Dept. Which not just its engineering, full stack developers, possibly our cloud native developers. Governance could come into policy, normal stuff. We've seen enablement more tooling, democratization of things. >>Yeah, yeah, >>yeah. I mean, what we've been seeing right in the real world, Liss, you have, for example, finance transformation that CIA full heads, right? So there's a lot of traction at that point to kind of bring the company together. But then that soon fizzles out. Sometimes you have, ah, the CMO bringing on and marketing campaign and, you know, analytics initiative, right? There's a lot of traction. Then it fizzes out. So you need somebody at the chief data officer of the C suite level to maintain that traction that moment, Um, in order freed value. >>But it seems the key issue is someone who is focused on data as an asset generating competitive returns on data as an asset because and the reason why it could be the CEO, it could be somebody else. Historically, an i t. The asset was the hardware on the argument here is that the asset is no longer the hardware now the data data. So whoever whatever you call it, someone and a group who's focused on generating returns out of data, >>Yes. But it has to have that executive level and that new talent mortal that we're proposing right where everybody knows a little bit of data in a sense. >>And the other thing is that I mean, think about this role that's dedicated to creating value of data, right? So you can understand you know how you create value in one function. Take it to the other function and tell them Hey, here's have helped finance right, get more value and then use the same thing marketing our sales. So it's also the cross pollination of ideas across different functions in an organization. S O n roll like that is helpful in terms of >>just to say, the data could very well become the next shared service's organization. That's because you don't want your salespeople to be great with data and your marketing people to be lousy with data. >>Correct. You're totally right on that. That's what we're proposing, right? So data being another vertical in entire business, >>the Lloyd bring all the action here on the Q. With all the data they're sharing here to you. It's the Cuban John for With Peter Burst, more live cover. Stay with us. We're here in Las Vegas. Live for in from Attica, World 2018 day. One of two days of wall to wall comes here out in the open. Bringing you all the data is Thank you. Stay with us.

(energetic music) >> Narrator: Live, from New York City, it's the CUBE. Covering Lenovo Transform 2017. Brought to you by Lenovo. Welcome back to the CUBE's coverage of Lenovo Transform. I'm your host Rebecca Knight, along with my co-host Stu Miniman. We are joined by Radhika Krishnan. She is the VP and GM of Software Defined Infrastructure at Lenovo. Thanks so much for joining us. You've been on before so, welcome back. >> Yes, I have and it's a pleasure to be back on again, thank you. >> So I want to start out by talking about something we've been hearing a lot about today, and that is Lenovo's lack of legacy and how that makes it easier for your company to innovate and to sell to customers. Can you talk a little bit about that from your vantage point? >> Absolutely, Rebecca. So if you look at our, and, you know, there are a lot of legacy vendors that have incumbent businesses that have been built on very customized, very proprietary offerings. I'll point to my own background. I spent a chunk of my career in storage, a chunk of my career in networking, and a chunk of my career in servers, and if you look across all of the offerings that come out from these vendors, these are usually high-margin; they're very rich offerings. And so, as the industry has moved toward software define, there is less of a motivation on the part of these vendors to really embrace software define entirely. Now, Lenovo does not have that baggage. We're not looking to protect any legacy businesses; there is no concern around cannibalizing an existing stream of revenue or profit. And so we are truly able to innovate from the ground up. >> Radhika, so, the software define really is the intersection of pulling some of those pieces into standard, typically x86, components. Can you bring us inside a little bit, the ThinkAgile, the new brand that's announced. Seems maybe you're going to get a new job title (laughter) to match that branding, but it feels like it all kind of pulls together to Lenovo's server as a core piece and then adding software on top of it. >> That is absolutely spot on, Stu. If you think about it, our code expertise is in building highly reliable, high performing servers and if you think about where software define is headed, it's all anchored around a core server platform or a platform that can deliver processing capabilities, which we're extremely capable. I mean, we've got the industry's best supply chain, as you heard. Highly reliable platforms, variety of benchmarks, and so forth. So we've got the basis, the foundation, for being able to innovate with software defined on top of it. >> Can you bring us inside the ThinkAgile family, as it were. There's some partnerships, there's OEM, there's some technology Lenovo has. What fits under this umbrella? What do we have today, and what's coming soon? >> Absolutely. So, the way we think about ThinkAgile is, we want to deliver to our customers the simplicity, the agility, and the cost economics that they may get in a public cloud in on-prem infrastructure. So, if you had to net it out, our vision really is to deliver on the benefits, and more and so, to that end, the way we have it architected is as two sets of offerings. So, we have appliances which essentially take capabilities, like software defined storage and hyper converge, blend them with our very capable platform, and deliver it as a turnkey offering. We're also bringing to market large scale solutions. Keeping in mind that there are customers that want to consume the entire infrastructure, end to end, in a single turnkey offering; we're bringing those to market as well. And we're seeing a very strong response for both of those types of flavors. >> When you're talking about innovation, and you're a tech veteran who has spent your career at various companies, large and small in the industry, how does Lenovo approach innovation? Especially because it is a large company, 43 billion in sales, 52,000 employees around the world. How do you stay in the start-up mindset, or do you? >> Well we absolutely do and that's actually one of the, as I mentioned earlier, Rebecca, we don't have the baggage of legacy and so if you look at how we're really approaching the software define space, you're exactly right; we're approaching it like an entrepreneur, very much in a start up mode. We're able to innovate from the ground up, which is exactly what we're doing. We're able to step back and look at it holistically from a standpoint of customer problems today. So there is no longer a, "Let's see if we can wedge in this other multi-million dollar business here, because that could then generate more revenue stream." It's really more around organically thinking through what customer problems are, applying a first principles-based approach, and then investing in it. So, from that standpoint, it is very exciting to be in an environment where you can truly operate in a start-up mode while you have the benefit of the very large sales teams that you alluded to, and the ability to invest in it as well. >> What is some of the managerial practices that enable that? I mean, one of the things that Rod was talking about in the very beginning, was there's no arrogance at Lenovo and that it really is part of the culture. Can you describe a little bit about how you do get customer feedback and how you do work with customers to solve these problems? >> Absolutely. So, I think a big part of it is the ability to listen. Humility starts with paying attention to your customers, paying attention to the stakeholders around you, so we definitely do a lot of that. The other thing I'll point to as well is there is a very distinct emphasis around agility. It's around the need to move quickly. As Stu and I were talking about prior to this session, this industry is going through a massive disruption. There's transformation happening everyday, as we speak, and therefore, it is very important to be tuned in to what is going on around you and to be able to deliver on what customers are truly seeking. So, yeah, I would stay humility is a big aspect of it. It's the agility, it's the hunger, the desire, to succeed as well. >> Radhika, specifically, what customers are asking for, I'm curious what you're hearing around hybrid cloud. I look at solutions that you're offering including, you've got the new Tenex solution, you've got the Microsoft Azure stack coming soon. What are you hearin' from customers? What do they look for in a hybrid cloud solution and how are you looking to deliver on that? >> Yeah, so that's a very interesting question, Stu, because over the years, many vendors in this space have talked about hybrid cloud but it's never really come of age, so to speak. And I think a large part of it is because there hasn't been enough of an understanding around how customers truly consume hybrid. One of the things we've done, in partnership with Microsoft, is to really profile how customers really want to consume this notion of hybrid. There are environments where you have a disconnected set of data centers, you have the edge and you have the central data center, and they need to be able to keep those two synchronized and aligned, and so on. There are use cases where ... You know, you truly want a hybrid nature. You want data sitting at both ends and you want to be able to execute test dev in your cloud environment and a primary workload running into your on-prem data center. And so, Microsoft Azure stack, in particular, I would point to as one hybrid cloud offering that we do have in the marketplace. A good partnering, very closely around, which truly addresses the problems that customers, or the desires that customers have in this space. >> When you're thinking about your customers, what keeps you up at night? You just were describing how customers aren't even sure themselves how hybrid they want to be and how they will use the cloud. What are your biggest concerns when you think about your customers and how they use Lenovo's offerings? >> Yeah, so, you know, I think at the core of it, you want to enable them to succeed. It's not so much about the IT infrastructure underneath, it's really about enabling them to drive their business as quickly as they can, to drive productivity, and so on. So, for us, it's very important that we stay aligned with their business objectives and eliminate the worry and concern that they typically have with IT infrastructure under their hood. Honestly, as we all in the industry tend to say, IT is a means to an end. And we truly want to enable that. We truly want to make this a non-issue for our customers. That's really what keeps us up at night, is ensuring that we have the right framework, the right portfolio, the right set of offerings, and more importantly, the right set of services to allow them to do that. >> Radhika, we all know that IT is typically spending way too much time with some of the basic blocking and tackling. The number I've heard the last 15 years is somewhere between 75% and 90% of your budget is spent on kind of keeping the lights on. What's holding us back? How are we actually moving the needle forward with some of these new solutions? >> I think a lot of it, interestingly, comes down to software define. I mean, if you think about it, software define enables a level of agility, simplicity, and cost economics as well that we weren't able to previously get from the more legacy hardware-centric offerings. So, I think your logic standard comes down to being able to deliver on the automation, the deep integration across hardware and software, which is really where we at Lenovo think we can add the most value because we've got the platforms, as we just talked about. So, we're really very keen on innovating on the software layer above it, such that customers can expect to get these highly verticalized offerings that they can then deploy for their workloads and various other business use cases. >> Alright, Radhika, we can't let you get out of here without talking about some of the networking pieces, with your background. Kirk talked about it a little bit, but, can you give us a little insight, what's Lenovo doing with the networking piece, some of the integrations that you're helping to deliver? >> Yeah, Stu, that's an area I feel incredibly proud of. I'll say that as I've spent the last couple of decades in the IT industry, it's becoming very evident there is simplicity that is continuing to grow. Obviously, we've come out with hyper converge, it solved the storage problem, it's made it a lot simpler to consume. Networking is really the next frontier. It's the frontier that hasn't been attacked yet. We're still talking about technologies that are in world that are like four decades old. And so this is ripe for a disruption. That's exactly what we're doing. As we go talk to our customers about deploying cloud data centers, scale out data centers, you know, they're telling us network traffic is flowing east, west and the equipment that they have has been architected for traffic that predominantly flows north, south. So, we're really helping simplify that challenge for them. We're coming out with tools, and we're announcing a couple of these today, we're coming out with tools that provide much better visibility with telemetry capabilities. We're providing them tools that allow them to apply policies, so, even as they deploy different types of workloads, they can specify quality of service and have that carried over to the network traffic as well. So, we're incredibly excited about what we're doing here in networking. >> So, what's the end for networking, in the sense of, as you said, it is an industry that is ripe for disruption. Where do you think we'll be 10 years from now, in terms of networking and in terms of visibility? >> Yeah, that's a very interesting question. I think networking has to evolve to where it is much, much, much more simplified. You don't need to have certifications that you have to gain over multiple years in order to qualify you to work in the data center. 'Cause it's, ultimately this is plumber, and as we go to scale out data centers, it's going to be incredibly important that nodes are able to talk to each other and data is fluid and is able to move around very quickly and networking is what enables it. So, the ultimate vision for networking is really making it invisible. Make it invisible to the point that you don't have to worry about it. >> Radhika, thank you so much for joining us. It's always a pleasure to have you on. >> Thank you, it's been my pleasure as well, appreciate it. >> I'm Rebecca Knight, for Stu Miniman, we'll be back with more of the CUBE's coverage of Lenovo Transform after this. (energetic music)

>>Hey, welcome back everyone. We're here live here in San Francisco for Amazon web services summit. This is the smaller event compared to reinvent the big conference in Vegas, which we were broadcasting live. I'm John furry, the founder's SiliconANGLE. This is the cube. Our flagship program where we go out to the events district to see live from the noise and a an Amazon show would not be complete without talking to the Amazon guys directly about what's going on under the hood. And our next guest is ADI Krishnan and Ryan Wade have run the Canisius teams. Guys, welcome to the cube. So we, Dave Vellante and I was not here unfortunately. He has another commitment but we were going Gaga over the says we'd love red shift in love with going with the data. I see glaciers really low cost options, the store stuff, but when you start adding on red shift and you know can, he says you're adding in some new features that really kind of really pointed where the market's game, which is I need to deal with real time stuff. >>I'll need to deal with a lot of data. I need to manage it effectively at a low latency across any work use case. Okay. So how the hell do you come up with an ISA? Give us the insight into how it all came together. We'd love the real time. We'd love how it's all closing the loop if you will for developer. Just take us through how it came about. What are some of the stats now post re-invent share with us will be uh, the Genesis for Canisius was trying to solve our metering problem. The metering problem inside of AWS is how do we keep track with how our customers are using our products. So every time a customer does a read out of dynamo DB or they read a file out of S3 or they do some sort of transaction with any of our products, that generates a meeting record, it's tens of millions of records per second and tens of terabytes per hour. >>So it's a big workload. And what we were trying to do is understand how to transition from being a batch oriented processing where we using large hitting clusters to process all that data to a continuous processing where we could read all of that data in real time and make decisions on that data in real time. So you basically had created an aspirin for yourself is Hey, a little pain point internally, right? Yeah. It's kind of an example of us building a product to solve some of our own problems first and then making that available to the public. Okay. So when you guys do your Amazon thing, which I've gotten to know about it a little bit, the culture there, you guys kind of break stuff, kind of the quote Zuckerberg, you guys build kind of invented that philosophy, you know stuff good. Quickly iterating fast. So you saw your own problem and then was there an aha moment like hell Dan, this is good. We can bring it out in the market. What were customers asking for at the same time was kind of a known use case. Did you bring it to the market? What happened next? >>We spend a lot of time talking to a lot of customers. I mean that was kind of the logistical, uh, we had customers from all different sorts of investigative roles. Uh, financial services, consumer online services from manufacturing conditional attic come up to us and say, we have this canonical workflow. This workflow is about getting data of all of these producers, uh, the sources of data. They didn't have a way to aggregate that data and then driving it through a variety of different crossing systems to ultimately light up different data stores. Are these data source could be native to AWS stores like S3 time would be be uh, they could be a more interesting, uh, uh, higher data warehousing services like Gretchen. But the key thing was how do we deal with all this massive amount of data that's been producing real time, ingested, reliably scale it elastically and enable continuous crossing in the data. >>Yeah, we always loved the word of last tickets. You know, a term that you guys have built your business around being elastic. You need some new means. You have a lot of flexibility and that's a key part of being agile. But I want you guys at while we're here in the queue, define Kenny SIS for the folks out there, what the hell is it? Define it for the record. Then I have some specific questions I want to ask. Uh, so Canisius is a new service for processing huge amounts of streaming data in real time. Shortens and scales elastically. So as your data volume increases or decreases the service grows with you. And so like a no JS error log or an iPhone data. This is an example of this would be example of streaming. Yeah, exactly. You can imagine that you were tailing a whole bunch of logs coming off of servers. >>You could also be watching event streams coming out of a little internet of things type devices. Um, one of our customers we're talking about here is a super cell who's capturing in gain data from their game, Pasha, the plans. So as you're playing clash of the plans, you're tapping on the screen. All of that data is captured in thesis and then processed by my super Supercell. And this is validated. I mean obviously you mentioned some of the use cases you needed of things, just a sensor network to wearable computers or whatever. Mobile phones, I'll see event data coming off machines. So you've got machine data, you've got human data, got application data. That's kind of the data sets we're seeing with Kinesis, right? Traverse set. Um, also attraction with trends like spark out of Berkeley. You seeing in memory does this kind of, is this in your wheelhouse? >>How does that all relate to, cause you guys have purpose-built SSDs now in your new ECQ instances and all this new modern gear we heard in the announcements. How does all the in-memory stuff affect the Canisius service? It's a great question. When you can imagine as Canisius is being a great service for capturing all of that data that's being generated by, you know, hundreds of thousands or millions of sources, it gets sent to Canisius where we replicated across three different availability zones. That data is then made available for applications to process those that are processing that data could be Hadoop clusters, they could be your own Kaloosas applications. And it could be a spark cluster. And so writing spark applications that are processing that data in real time is a, it's a great use case and the in memory capabilities and sparker probably ideal for being able to process data that's stored in pieces. >>Okay. So let's talk about some of the connecting the dots. So Canisius works in conjunction with what other services are you seeing that is being adopted most right now? Now see I mentioned red shift, I'm just throwing that in there. I'll see a data warehousing tool seeing a lot of business tells. So basically people are playing with data, a lot of different needs for the data. So how does connect through the stack? I think they are the number one use case we see is customers capturing all of this data and then archiving all of it right away to S3 just been difficult to capture everything. Right. And even if you did, you probably could keep it for a little while and then you had to get, do you have to get rid of it? But, uh, with the, the prices for us three being so low and Canisius being so easy to capture tiny rights, these little tiny tales of log data, they're coming out of your servers are little bits of data coming off of mobile devices capture all of that, aggregate it and put it in S3. >>That's the number one use case we see as customers are becoming more sophisticated with using Kinesis, they then begin to run real time dashboards on top of Kinesis data. So you could, there's all the data into dynamo DB where you could push all that data into even something like Redshift and run analytics on top of that. The final cases, people in doing real time decision making based on PISA. So once you've got all this data coming in, putting it into a dynamo DB or Redshift or EMR, you then process it and then start making decisions, automated decisions that take advantage of them. So essentially you're taking STEM the life life cycle of kind of like man walking the wreck at some point. Right? It's like they start small, they store the data, usually probably a developer problem just in efficiencies. Log file management is a disaster. >>We know it's a pain in the butt for developers. So step one is solve that pain triage, that next step is okay I'm dashboard, I'm starting to learn about the data and then three is more advanced like real time decision making. So like now that I've got the data coming in in real time and not going to act. Yeah, so when I want to bring that up, this is more of a theoretical kind of orthogonal conversation is where you guys are basically doing is we look, we like that Silicon angles like the point out to kind of what's weird in the market and kind of why it's important and that is the data things. There's something to do with data. It really points to a new developer. Fair enough. And I want to give you guys comments on this. No one's really come out yet and said here's a development kit or development environment for data. >>You see companies like factual doing some amazing stuff. I don't know if you know those guys just met with um, new Relic. They launched kind of this data off the application. So you seeing, you seeing what you guys are doing, you can imagine that now the developer framework is, Hey I had to deal with as a resource constraint so you haven't seen it. So I want to get your thoughts. Do you see that happening in that direction? How will data be presented to developers? Is it going to be abstracted away? Will there be development environments? Is it matter? And just organizing the data, what's your vision around? So >>that's really good person because we've got customers that come up to us and say I want to mail real time data with batch processing or I have my data that is right now lots of little data and now I want to go ahead and aggregate it to make sense of it over a longer period of time. And there's a lot of theory around how data should be modeled, how we should be represented. But the way we are taking the evolution set is really learning from our customers and customers come up and say we need the ability to capture data quickly. But then what I want to do is apply my existing Hadoop stack and tools to my data because then you won't understand that. And as a response to that classroom demand, uh, was the EMR connect. Somehow customers can use say hi queries or cascading scripts and apply that to real time data. That can means is ingesting. Another response to pass was, was the, that some customers that would really liked the, the, the stream processing construct a storm. And so on, our step over there was to say, okay, we shipped the Canisius storm spout, so now customers can bring their choice of matter Dame in and mail back with Canisius. So I think the, the short answer there right now is that, >>you know, it's crazy. It's really early, right? I would also add like, like just with, uh, as with have you, there's so many different ways to process data in the real time space. They're going to be so many different ways that people process that data. There's never going to be a single tool that you use for processing real time data. It's a lot of tools and it adapts to the way that people think about data. So this also brings us back to the dev ops culture, which you guys essentially founded Amazon early in the early days and you know I gotta give you credit for that and you guys deserve it. Dev ops was really about building from the ground good cloud, which post.com bubble. Really the thing about that's Amazon's, you've lived your own, your own world, right? To survive with lesson and help other developers. >>But that brings up a good point, right? So okay, data's early and I'm now going to be advancing slowly. Can there be a single architecture for dealing with data or is it going to be specialized systems? You're seeing Oracle made some mates look probably engineered systems. You seeing any grade stacks work? What's the take on the data equation? I'm not just going to do because of the data out the internet of things data. What is the refer architecture right now? I think what we're going to see is a set of patterns that we can do alone and people will be using those patterns for doing particular types of processing. Uh, one of the other teams that I run at is the fraud detection team and we use a set of machine learning algorithms to be able to continuously monitor usage of the cloud, to identify patterns of behavior which are indicative of fraud. >>Um, that kind of pattern of use is very different than I'm doing clickstream analysis and the kind of pattern that we use for doing that would naturally be different. I think we're going to see a canonical set of patterns. I don't know if we're going to see a very particular set of technologies. Yeah. So that brings us back to the dev ops things. So how do I want to get your take on this? Because dev ops is really about efficiencies. Software guys don't want to be hardware guys the other day. That's how it all started. I don't want to provision the network. I don't want a stack of servers. I just want to push code and then you guys have crazy, really easy ways to make that completely transparent. But now you joke about composite application development. You're saying, Hey, I'm gonna have an EMR over here for my head cluster and then a deal with, so maybe fraud detection stream data, it's going to be a different system than a Duke or could be a relational database. >>Now I need to basically composite we build an app. That's what we're talking about here. Composite construction resource. Is that kind of the new dev ops 2.0 maybe. So we'll try to tease out here's what's next after dev ops. I mean dev ops really means there's no operations. And how does a developer deal with these kinds of complex environments like fraud detection, maybe application here, a container for this bass. So is it going to be fully composite? Well, I don't know if we run the full circuit with the dev ops development models. It's a great model. It's worked really well for a number of startups. However, making it easy to be able to plug different components together. I get just a great idea. So, like as ADI mentioned just a moment ago, our ability to take data and Kinesis and pump that right into a elastic MapReduce. >>It's great. And it makes it easy for people to use their existing applications with a new system like pieces that kind of composing of applications. It's worth well for a long time. And I think you're just going to see us continuing to do more and more of that kind of work. So I'm going to ask both of you guys a question. Give me an example of when something broke internally. This is not in a sound, John, I don't go negative here, but you got your, part of your culture is, is to move fast, iterate. So when you, these important projects like Canisius give me an example of like, that was a helpful way in which I stumbled. What did you learn? What was the key pain points of the evolution of getting it out the door and what key things did you learn from media success or kind of a speed bump or a failure along the way? >>Well, I think, uh, I think one of the first things we learned right after we chipped and we were still in a limited previous and we were trying it out with our customers who are getting feedback and learning with, uh, what they wanted to change in the product. Uh, one of the first things that we learned was that the, uh, the amount of time that it took to put data into Canisius and receive a return code was too high for a lot of our customers. It was probably around a hundred milliseconds for the, that you put the data in to the time that we've replicated that data across multiple availability zones and return success to the client. Uh, that was, that was a moment for us to really think about what it meant to enable people to be pushing tons of data into pieces. And we went back a hundred milliseconds. >>That's low, no bad. But right away we went back and doubled our efforts and we came back in around, you know, somewhere between 30 and 40 milliseconds depending on your network connectivity. Hey, the old days, that was, that was the spitting disc of the art. 10, 20 Meg art. It's got a VC. That's right. Those Lotus files out, you know, seeing those windows files. So you guys improve performance. So that's an example. You guys, what's the biggest surprise that you guys have seen from a customer use case that was kind of like, wow, this is really something that we didn't see happening on a, on a larger scale that caught me by surprise. >>Uh, I is in use case it'd be a corner use case. Like, well, I'd never figured that, you know, I would say like, uh, some of the one thing that actually surprised us was how common it is for people to have multiple applications reading out of the same stream. Uh, like again, the basic use case for so many customers is I'm going to take all this data and I'm just going to throw it into S3. Uh, and we kind of envisioned that there might be a couple of different applications reading data of that stream. We have a couple of customers that actually have uh, as many as three applications that are reading that stream of events that are coming out of Kinesis. Each one of them is reading from a different position in the stream. They're able to read from different locations, process that data differently. >>But uh, but the idea that cleanses is so different from traditional queuing systems and yet provides, uh, a real time emotionality and that multiple applications can read from it. That was, that was a bit of a versa. The number one use case right now, who's adopting, can you sit there, watch folks watching out there, did the Canisius brain trust right here with an Amazon? Um, what are the killer no brainer scenarios that you're seeing on the uptake side right now that people should be aware of that they haven't really kicked the tires on Kinesis where they should be? What should they be looking at? I think the number one use case is log and ingestion. So like I'm tailing logs that are coming off of web servers, my application servers, uh, data that's just being produced continuously who grab all that data. And very easily put it into something like us through the beauty of that model is I now have all the logo that I got it off of all of my hosts as quickly as possible and I can go do log nights later if there's a problem that is the slam dunk use case for using crisis. >>Uh, there are other scenarios that are beginning to emerge as well. I don't know audio if you want to talk, that's many interesting and lots of customers are doing so already is emit data from all sorts of devices. So this is, these devices are not just your smartphones and tablets that are practically food computing machines, but also seemingly low power, seemingly dumb devices. And the design remains the same. There are millions of these out there and having the ability to capture that in a day produce in real time is, you know, I think just, uh, just to highlight that, one of things I'm hearing on the cube interviews, all the customers we talk to is the number one thing is I just got to scroll the date. I know what I want to do with it yet. Now that's a practice that's a hangover from the BI data warehouse in business of just store from a compliance reasons now, which is basically like, that's like laser as far as I'm concerned. >>Traditional business intelligence systems are like their version of Galatians chipped out somewhere and give me those reports. Five weeks later they come back. But that's different. Now you see people store that data and they realize that I need to touch it faster. I don't know yet when, that's why I'm teasing out this whole development 2.0 model because I'm just seeing more and more people want the data hanging around but not fully parked out in Malaysia or some sort of, you know, compliance storage. So there's, you know, I think, I think I kind of understand where you're going. There's a, I'm going to use a model for like how we used to do BI analytics and our own internal data warehouse. I also run the data warehouse for AWS. Um, and the classic BI model there is somebody asks a question, we go off and we just do some analysis and if it's a question that we're going to ask repeatedly, we don't, you know, a special fact table or a dimensional view or something to be able to grind through that particular view and do it very quickly. >>A Kunis is offers a different kind of data processing model, which is I'm collecting all of the data and make it easy to capture everything, but now I can start doing things like, Oh, there's, there's certain pieces of data that I want to respond to you quickly. Just like we would create dimensional views that would give us access to particular sets of data and very quick pace. We can now also respond to when those events are generated very quickly. Well, you guys are the young guns in the industry now. I'm a little bit older and the gray hair showing, we actually use the word data processing back in the day. The data processing that the DP department or the MIS department, if you remember those those days, MIS was the management information. Are we going back to those terms? I mean we're looking at look what's happening. >>Is it the software mainframe in the cloud? I mean these are some of the words you're using. Just data processing data pipeline. Well, I my S that's my work, but I mean we're back to those old school stuff but different, well and I think those kinds of very generic terms make a lot of sense for what we're doing is we, especially as we move into these brand new spaces like wow, what do I do with real time data? Like real time data processing is kind of the third type of big data processing or data warehousing was the first time I know what my data looks like. I've created indices like a pre computation of the data, uh, uh, Hadoop clusters and the MapReduce model was kind of the second wave of big data processing and realtime processing I think will be the third way. I think our process, well, I'm getting the hook here, but I got to just say, you guys are doing an amazing job. >>We're big fans of Amazon. I always say that, uh, you know, it was very rare in the history the world. We look at innovations like the printing press, the Wright brothers discover, you know, flying and things like we, Amazon with cloud. You guys have done something that's pretty amazing. But what I find fascinating is it's very rare to see a company that's commoditizing and disrupting and innovating at the same time. And it's really a unique value proposition and the competition is responding. IBM, Google. So you guys have a lot of targets painted on your back by a lot of big players. So, uh, one congratulations on your success, which means that you, you know, you're not going to go in the open field and fight the, the British if they said use the American revolution analogy. You've got to continue to compete. So what's your view of that? >>I mean, and I'm sure you don't talk about competition. You'd probably told him not to talk about it, but I mean, you got to know that all the guns are on you right now. The big guys are putting up the sea wall for your wave of innovation. How do you guys deal with that? It's just cause it's not like we, we ignore our competitors but we obsess about our customers, right? Like it's just constantly looking for what are people trying to do and how can we help them and can seem like a very simple strategy. But the strategy is built with people want and we get a lot of great feedback on how we can make our products better. And it certainly will force you to up your game when you have the competition citing on you. You've got more focused on the customer, which is cool. >>But like you guys kind of aware of like games on, I mean Amazon is at any given a little pep talk, Hey, game is on guys. Let's rock and roll. Right? You guys are aware, right? I think we're totally wearing, I think we're actually sometimes a little surprised at how long it's taken to our competitors to kind of get into this industry with us. So, uh, again, as Andy talked about earlier today, we've had eight years in the cloud computing market. It's been a great eight years and we have a lot of work to do, a lot of stuff that we're going to be almost ready for middle school. Um, final final question for you guys and give you the final word here. Share the photos on the last word is why is this show so important, right this point in time in this market. Why is this environment of the thousands of people that are here learning about Amazon, why, what should they know about why this is such an important advance? I think our summits are a great opportunity for us to share with customers how to use our AWS services. Learn firsthand from not only our hands on labs, but also our partners that are providing information about how they use AWS resources. It's, it's a great opportunity to meet a lot of people that are taking advantage of the cloud computing wave and see how to use the cloud most effectively. >>It's a great time to be in the cloud right now and the Olin's amazing services coming up. There's no better mind now of people coming together and so that's probably as good reasons. Then you guys are doing a great job disrupting change in the future. Modern enterprise and modern business, modern applications. Excited to watch it. If you guys keep focusing on your customer, but that customer base, you keep up the pace that's sick. That question, can you finish the race? That's what I always tell Dave a lot. They, I know Jay's watching Dave. Shout out to Dave Volante, who's on the mobile app right now is traveling. Guys, thanks for coming inside. Can he says great stuff. Closing the loop real time. Amazon really building it out. Thanks for coming on. If you'd be right back with our next guest after this short break. Thank you.