(upbeat music) >> Announcer: Live from New Orleans, Louisiana, It's theCUBE, covering .NEXT Conference 2018. Brought to you by Nutanix. >> Welcome back. We're here in New Orleans, Louisiana. I'm Stu Miniman with my co-host Keith Townsend. And we're thrilled to welcome to the program, two N users here at the show. We have Sharon Haris, who is the CTO of Assulta Medical Centers out of Israel. I also have Paul Stallings, he's the Vice President of IT infrastructure services, Guidewell with Florida Blue. Gentlemen, thanks so much for joining us. >> Thanks for having us. >> Alright, Paul let's start with you. Just give us a little bit about your role and your organization. >> Sure, I work for Guidewell. We're a health solutions company. We started out as an insurance company, primarily. Now we've moved to a solutions. So, we are the provider side and the payer side. I run IT infrastructure services, which is the shared services among five different companies under the Guidewell brand. >> Great and Sharon? >> Assulta Medical Centers is the largest chain of private hospitals in Israel. We have four hospitals and four clinics spreading across the country from North to South. We are connecting about one million radiology tests and examinations per year, and about 15% of the in-house surgeries in Israel. >> Yeah, well luckily both of you, in your industries, my usual joke is, nothing's changing. You have huge budgets. (laughing) Unlimited staff. And no challenges. >> Sharon: At all. >> Paul, before we get into the Nutanix solutions of course you're using, tell us about some of the drivers for change in your business, your work. You know, some of the challenges and opportunities you're facing. >> Yeah, sure. We are really in a growth mode in our organization. In the last six years, we've actually grown to these five companies. We went from an eight billion dollar company to a $16 billion company. We're in a huge trajectory and transformation is the key. And we have to have high availability. We have to be able to meet our customer's needs. We have to be able to scale and be agile. And that's thrown at me every day. >> Stu: Sharon? >> Yeah, now we're in the healthcare industry. We have both ends. On one end, we have to maintain stability and performance and redundancy. Because we are working 24-7, 365 days a year. And on the other end, we must be innovative in innovation, and make everything for our user and customers very available, very approachable, because users don't want to come to our clinics and hospitals. They want to do everything from home. So, as much as we can, we are giving them the opportunity to do it. >> Stu: Yeah, digitization. >> So, Paul that's amazing growth, eight billion to 16 billion. Whether it's organic, inorganic. That's a major shift in capability. What have been some of the primary challenges from a technology perspective as you guys have gone through that major growth period. >> Yeah, I think the velocity is one of the biggest challenges for us. Being able to grow, we really need solutions that we can really want to modually grow, want pay to grow and scale better. It's really hard when you have that much growth to do the legacy where you think about, in the next three years I need this much capacity, because it's unpredictable because the growth is so fast. If that makes sense. >> Yeah, it's impossible to forecast. >> Right, absolutely. >> It's impossible. >> I had a CIO that tells me the data costs are getting out of control. I say, you know what? As long as the data is growing, that means that the business is growing. >> Paul: Absolutely. >> So, hard drives are definitely the thing that you want to buy. So, as you both deal with growth, stability, capability challenges, What appeals about the Nutanix story to you? >> I think one of the things that I just mentioned. That pay to grow opportunity is huge for us. The simplicity is huge. The availability and really trying to get to automation. I really have to do more with less. We're growing so fast, I can't even onboard folks fast enough. So, I think that simplicity, that automation and that pay to grow model is great for us. >> So, we're in the digital era. So we need to supply our users once again, as I said before, digital application. And to be able to execute those needs very quickly. And we're looking towards the cloud. And you can't really have public cloud readiness in services, unless you have private cloud readiness in services. So, Nutanix for me is the best solution for automation, as Paul said. And to begin the process to achieve the collection between private and public cloud. >> That's an interesting point. Could you expand on that? What do you mean by, what does private cloud mean to you? And most customers you hear, oh, we're doing some development. We're trying some new products in the public cloud. You flipped that some. >> Yeah, I spoke here yesterday in one of the session. And I ask the audience, how much time it takes to fire up a ritual machine from a template? And the answer was like between half and hour and one hour. I thought, one hour, that's cool. And how much time it takes for you to take this machine and join it to the CRM or the SharePoint or the Epic or the SAP farm? And the answer was about a week. So, where did seven days go? Why is the gap so huge between one hour and a week? And the answer is because the lack of automation. For me, the public cloud is exactly like, sorry, private cloud is exactly like public cloud. The same services, the same abilities to execute and generate services level. Not server level, because server level would be Dell. Like if you, 10 or 15 years ago, we are already there. Services level is the same ability that we have in the public level. >> Paul, I would love to hear your comments on how Cloud fits into your environment. >> Yeah, absolutely. 'Cause we're in the health industry, private cloud is paramount. But we really need the hybrid because we want to be able to burst and scale and have that agility. But to a lot of things that Sharon said, I do need that automation, I do need the scaleability, but I definitely need some commonality on my stacks. I have a shared services. I have to build a scale. I have to be able to have best prices. I need to be able to compete and collaborate with the private and public sectors. >> So, let's talk about some of the services that Nutanix offers. First let's start in the private cloud. A lot of great announcements. One of the things that, I have actually from Nutanix, I've heard about them is basically what they're delivering in AFF. I'm sorry, AFS, a foul services solution. Are you guys using any of those foul or type solutions within your own environment? >> No yet, we are not using the foul solution in biomechanics, but we're using the other services such as the big data verification with the Cloud data, because we are using, actually, a built environment for our new research development company that we signed in, big data, cloud data, dupe and in line, and we did it very quickly, and stability-wise and performance-wise, and file services-wise, because it's big data, you know? It's a different kind of perception over there, and Nutanix gives us very quickly a deployment and services that we needed for this project. >> Could you just expand on that? When you say it was a fast deployment, you know, days? >> Yeah, our CEO signed the contract with this company and said, okay, I want it to be ready in like, two weeks from now. And then I thought, okay I can do it traditionally, and it would probably take me a month, or even more, and I can do it with Nutanix, and Nutanix wasn't ready in this time, with Cloud Data verification. Nutanix promised me that they would support me 100%, I got a letter from the VP of R&D of Nutanix, that they would support me, and they would get the certification. Now, most of the vendors that want to sell you something they say, "yeah, we'll get it, no worries", and they deliver. First of all, they give us full support, in the duration of the implementation of the environment. And, they did get the certification a few months later. So, performance-wise, we did the test, so I know that it works. We've duplicated the Cloud there, by the way, when there was performance issues, it was, Cloud Data fine-tuned what we need to do. It wasn't Nutanix' at all. Really, I really like this product, but they really deliver, so, performance-wise, execution-wise, and stability. >> We met the deadline that your-- >> I met the deadline, the medical staff is behind schedule, but I did my part. >> So Paul, what are any, is there any particular service that you use within the Nutanix Private Cloud that you want to talk about? >> Well, we're pretty new to the Nutanix suite of services, but one thing that's unique about our organization is we're one of the first to not do x86, but do power systems as well. So, we wanted that one pane of glass, one cloud management system that we can actually do all of our workloads. So we really just, we started x86 but we just recently got our power infrastructure up and running, about 100 nodes, and that's working well as well. And we're happy to have both sides of the fence, and really look at all our workload through that single pane of glass. >> Great, can you tell me what workload are you running on that, and do you have any AIX that you might look to put on that, now that that's going to be supported? >> Yeah, so we're really now starting to look at things with Kubernetes, then we've started putting our open enrollment applications on, because that's really our season now, right? It's kind of our busiest timeframe, when I have the highest availability, I have to be able to scale, and want to have zero downtimes. So, that one click, we love those kind of capabilities, and that's really helping us with our new applications for open enrollment. >> So, let's talk about Nutanix' vision. You both are cloud-forward thinking organizations, as you look at Zy, as you look at integration of calm with the major cloud providers, what are your initial thoughts? >> I think that, you know, I think that Zy's really interesting, where I can have those recovery options. You know, I really think we really got to move infrastructure to resiliency, and make sure it's resilient, but it's always nice to have that backup and be able to click over very quickly, as opposed to traditional recovery model where you back it up and you have to restore it. We don't want to restore. We want to be able to bring that back up and have that high availability. So I'm really interested in the Zy piece. >> Yeah, and we got the budget for the DR this year. And, we needed to take into consideration the best DR module for Assulta. Now, to be honest with you, if a regulation would allow us, I wouldn't think twice. But this is a variable that I need to check with my legal department, but technology-wise Zy is a amazing solution. In terms of cloud as a centerfold, I believe that there is no other option. There's no other option but to build your private and move it towards public cloud services. By the way, the main barrier for me is the human barrier. Because we need to train our personnel, we need to change the way they think, we need to combine between system guys and networking, and security guys, because now it's one box. So it's quite the challenge, but Nutanix makes a difference. >> Alright, it's the first time for both of you attending this show, Paul, start with you, if you can tell us what brought you to the show, what you're hoping to accomplish, what you've learned so far, general experiences here. >> Yeah, so you know, Nutanix is really helping us build out our private cloud. We definitely know that even though healthcare has a lot of regulatory requirements, we don't want to do full public, we know we're going to have to start moving more and more into the cloudspace. So, we know there's different cloud players out there, but we want to have that mobility of our workloads and move them in and out, and move them back to our environment, and move them from cloud provider to cloud provider and I've definitely started hearing about a lot of the services that Nutanix provides, that it enables those kind of solutions, and I want to learn more about those. >> For me, Nutanix is bringing to the table new ideas, new perception, and the most important thing that they gave us, giving us things that we need. And you talked about Zy, you talked about Com, there's been a new concept and they are always moving ahead and they bring the market to chase them. If I could say this way. And for me, the most important thing is that everything is posted in one box, and able to do it very simple by automation processes. >> So one question around people, you're growing at, doubling the organization, as you go out and look for staff to augment your existing staff, and innovate the change, how does Nutanix help or hinder in the hiring process? Like, onboarding new employees, you said onboarding is a challenge, onboarding and training, commentary around that? >> Yeah, so, you know, people are our most precious assets, right? And, when you hire new, you want to get the best people you can get, right? So, I think that we definitely tried to identify folks that have the type of aptitude we need. We're not always able to find the folks that are skilled with all the solutions we need, because cloud is so diverse, and converge is so diverse with the stacks, but we actually are doing a better job with finding the right talent, or training the ones that we have up, and to prepare and give the training to the new folk that are coming through the door. But our onboarding is definitely an opportunity for us, and I think we'll be able to scale a little bit better with onboarding as we look at automation, automation is going to be the key to getting folks onboarded faster. >> So Sharon, what about you? How has Nutanix helped with your, not necessarily onboarding, because growth is not necessarily changed, but people change. >> Yeah, people change. And the market has changed as well. And people must understand, that they should embrace the change. Even I change each and every day. I learn new things, I implement new things, I dare and I challenge my organization, and I have to convince my finance and my CIO and my CEO that this technology, whether Nutanix or other technology, is the right technology for our organization. Now, Nutanix is helping us in terms of innovation because of the fact that we're beginning to sign contracts with startups. And, we have to build them labs, and combine them with our production environment but do it very smartly, in a sophisticated way. So, Nutanix with the microsegmentation and other features that they are having is very helpful for us in this area, as well. >> Last thing I wanted to ask: lessons learned. You're relatively new in this space, but always things that you look back and say, "What could I have done better", "What I wish I knew a little better", Paul, start with you as to talking with your peers, what would you recommend to them, and what changes might they make? >> You know, I think we're so new into it, we don't have a lot of lessons learned yet, because we're just really going into production with a lot of the systems that we have, especially on the AIXI and the power side, but I do think that we are doing a debrief, probably coming up in the next 30 days to really identify if there are opportunities that we could probably do differently. Now, I will say that I do want to look at the whole private cloud to public cloud opportunities and really understand what those challenges are, because I think from an application perspective, that we don't always build applications that we plan to bring back. So, I need to really partner with my development shops, that when they build applications, how do we make sure that we can bring those workloads back, and I want to understand some of those cost models. >> That's awesome. >> I would say choosing the right use case and to prepare for the implementation, plan as much as you can, because those things will make or break if you're a beginner. If you're already accustomed to things, you know what to do. But if you're a beginner, those things are very important and combined with a good or very good integrator because, once again, if you want to succeed in this project, because it's not a project, it's not that service that we install. If you go with this method, then you didn't learn anything. So, if you want to get the best out of Nutanix, and thanks, to offer a lot of services we discussed, you should do it. >> Alright, Sharon and Paul, thank you so much for sharing your stories. For Keith Townsend and Stu Miniman, we always love to talk to all the users here, and I'm glad to be able to bring them to you, thanks so much for watching theCUBE. (upbeat music)

>> Announcer: Live from Orlando, Florida it's the Cube covering Grace Hopper Celebration of Women in Computing brought to you by SiliconANGLE Media. >> Welcome back to the Cube's coverage of the Grace Hopper Conference here at the Orange County Convention Center. I'm your host, Rebecca Knight. We are joined by Aysegul Gunduz, she is a professor at the University of Florida-College of Engineering. Thanks so much for joining us. >> No, thank you for having me. >> So, congratulations are in order, because you are a ABIE Award winner, which is awards given out by the Anita Borg Institute, and you have been given the Denice Denton Emerging Leader Award. So, tell us a little about, about your award. >> Well, thank you for asking. We've heard a lot about Grace Hopper and Anita Borg throughout the conference, but Denice Denton, she was actually very close friends with Anita. And she was a leader in her field, her field was development of polymers, and she worked on the first development of RAM. But she was actually the first ever dean of a college of engineering at a major university... >> Rebecca: First ever woman. >> First woman dean, yes, so she became dean at the University of Washington, and then she actually became chancellor at University of California, but just beyond her research she really promoted and lifted the people around her, so she was a big proponent of minority issues. So, she supported females, she supported international students, and she was openly gay, so she really had a big influence on the LGBTQ community, so I just wanted to, you know, just recognize her and say that how honored I am to have my name mentioned alongside hers. This award is given to a junior faculty member that has done significant research and also has had an impact on diversity as well. >> So, let's start talking... >> Denice is a great inspiration. >> Yes! The award given an homage to Denice, so your research is about detecting neurological disorders. So, tell our viewers a little bit more about what you're doing. >> Sure, I'm an electrical engineer by training, who does brain research for a living, so this confuses a lot of people, but I basically tell them that our brains have bioelectric fields that generate biopotential signals that we can record and we're really trying to decipher what these signals are trying to tell us. So, we are really trying to understand and treat neurological disorders as well as psychiatric disorders, so I work with a lot of neurosurgical patient populations that receive electrode implants as part of their therapy, and we are trying to now improve these technologies so that we can record these brain signals and decode them in real time, so that we can adapt things like deep brain stimulation for the current pathology that these patients are having. So, deep brain stimulation, currently, is working like, think of an AC and it's working on fan mode so its current, you know, constantly blowing cold air into the room, even though the room might be just the perfect temperature, so we are basically trying to listen to the brain signals and only deliver electricity when the patient is having a pathology, so this way we are basically turning the AC onto the auto mode, so that once they are actually not having symptoms, unnecessary electrical, it is not delivered into their brains, so pace makers, when they invented were functioning that way, so people realized they could stimulate the heart, and the person would not have a cardiac arrest, but now we know that we can detect the heart pulse very easily, so someone thought about 'OK, so when we don't detect the pulse, heartbeat, let's only stimulate the pace maker then,' so that's what we're trying to adapt to the neuro-technologies. >> And what is the patient response? I mean I imagine that's incredible. So, these are people who suffer from things like Parkinson's disease, Tourette's syndrome, I mean, it's a small patient population that you're working with now, but what are you finding? >> So, first of all, our patients are very gracious to volunteer for our studies, we find that, for instance, in Tourette's syndrome we can actually detect when people are having tics, involuntary tics, that is characteristic of Tourette's syndrome. We find that we can differentiate that from voluntary movements, so we can really deliver the stimulation when they are having these symptoms, so this is a paroxysmal disorder, they really don't need continuous stimulation. So, that's one thing that we're developing. We find that in essential tremor, again, when people aren't having tremor we can detect that and stop the stimulation and only deliver it when necessary. We're working on a symptom called freezing of gaits in Parkinson's disease so people define this as the, having the will to walk, but they feel like their feet are glued to the floor so this can cause a lot of falls, and at that, really, age this can be very, very dangerous. So, we can actually tell from the brain when people are walking and then we turn the stimulation in this particular area only during that time so as to prevent any falls that might happen. >> So, it's really changing their life and how they are coping with this disease. >> Yes, true, and it really makes going to work in the morning (laughs) very, very exciting for us. >> So, another element of the ABIE Award is that you are helping improve diversity in your field and in Denice Denton, in the spirit of Denice Denton, helping young women and minorities rise in engineering. >> Yes, so, I'm going to talk about this in my keynote session tomorrow, but I really just realized that all my confidence throughout engineering school was due to the fact that I actually had a female undergraduate advisor, and once I came to that realization, I joined Association for Academic Women at the University of Florida, which was established in 1974, because these pioneering women fought for equal pay for male and female faculty on campus, and this is still honored today, so I'm very honored to be serving the Association as its president today. All of our membership dues go to dissertation awards for female doctoral students that are, you know, emerging scholars in their fields, and I also approached the National Science Foundation and they supported the funding for me to generate a new emerging STEM award for female students in the STEM fields. So, you know, that is my contribution. >> So, you're passing it on... >> I hope so. >> the help and the mentoring that you received as young faculty member. >> I truly hope so. >> I mean, (stammers) right now we're so focused on the technology companies but on campuses, on the undergraduate and graduate school campuses, how big a problem is this, would you say? >> So, I'm a faculty in biomedical engineering, so, in our field we actually have some of the highest female to male ratios compared to other engineering fields. People attribute this to the fact that females like to contribute to the society, so, they like to work on problems, they like to work on problems that have a societal impact and I think working with, basically, you know, disorders in any branch of medicine, it really fires, fires up female students, but yes, when we go to other departments such as electrical engineering, mechanical engineering, the ratio is really, really small. And it still is a problem and therefore we are really trying to mobilize, you know, all female faculty, just to be present, just the fact that you're there, that you're a successful female in this field... >> Rebecca: The role models. >> Yeah, really makes an impact, you know, I think, the most repeated quote at this meeting is that 'You can't be what you can't see." So, we're really trying to support female faculty. So, we're tying to retain female faculty, so that, you know, the younger generation of females can see that they can and the will do it as well. >> You can't be what you can see, I love that. Those are words to live by. >> Right. >> Yeah. Well, thank you so much Aysegul, this is a pleasure, pleasure meeting you, pleasure having you on the show. >> Thank you so much, pleasure's mine. >> We'll be back with more from Grace Hopper just after this.

(upbeat music) >> Hey everyone. Welcome to theCUBE's special program series "Women of the Cloud", brought to you by AWS. I'm your host for the program, Lisa Martin. Very pleased to welcome back one of our alumni to this special series, Dr. Tendu Yogurtcu joins us, the CTO of Precisely. >> Lisa: Tendu, it's great to see you, it's been a while, but I'm glad that you're doing so well. >> Geez, it's so great seeing you too, and thank you for having me. >> My pleasure. I want the audience to understand a little bit about you. Talk to me a little bit about you, about your role and what are some of the great things that you're doing at Precisely. >> Of course. As CTO, my current role is driving technology vision and innovation, and also coming up with expansion strategies for Precisely's future growth. Precisely is the leader in data integrity. We deliver data with trust, with maximum accuracy, consistency, and also with context. And as a CTO, keeping an eye on what's coming in the business space, what's coming up with the emerging challenges is really key for me. Prior to becoming CTO, I was General Manager for the Syncsort big data business. And previously I had several engineering and R&D leadership roles. I also have a bit of academia experience. I served as a part-time faculty in computer science department in a university. And I am a person who is very tuned to giving back to my community. So I'm currently serving as a advisory board member in the same university. And I'm also serving as a advisory board member for a venture capital firm. And I take pride in being a dedicated advocate for STEM education and STEM education for women in particular, and girls in the underserved areas. >> You have such a great background. The breadth of your background, the experience that you have in the industry as well in academia is so impressive. I've known you a long time. I'd love the audience to get some recommendations from you. For those of the audience looking to grow and expand their careers in technology, what are some of the things that you that you've experienced that you would recommend people do? >> First, stay current. What is emerging today is going to be current very quickly. Especially now we are seeing more change and change at the increased speed than ever. So keeping an eye on on what's happening in the market if you want to be marketable. Now, some of the things that I will say, we have shortage of skills with data science, data engineering with security cyber security with cloud, right? We are here talking about cloud in particular. So there is a shortage of skills in the emerging technologies, AI, ML, there's a shortage of skills also in the retiring technologies. So we are in this like spectrum of skills shortage. So stay tuned to what's coming up. That's one. And on the second piece is that the quicker you tie what you are doing to the goals of the business, whether that's revenue growth whether that's customer retention or cost optimization you are more likely to grow in your career. You have to be able to articulate what you are doing and how that brings value to business to your boss, to your customers. So that becomes an important one. And then third one is giving back. Do something for the women in technology while being a woman in technology. Give back to your community whether that's community is gender based or whether it's your alumni, whether it's your community social community in your neighborhood or in your country or ethnicity. Give back to your community. I think that's becoming really important. >> I think so too. I think that paying it forward is so critical. I'm sure that you have a a long list of mentors and sponsors that have guided you along the way. Giving back to the community paying it forward I think is so important. For others who might be a few years behind us or even maybe have been in tech for the same amount of time that are looking to grow and expand their career having those mentors and sponsors of women who've been through the trenches is inspiring. It's so helpful. And it really is something that we need to do from a diversity perspective alone, right? >> Correct. Correct. And we have seen that, we have seen, for example Covid impact in women in particular. Diverse studies done by girls who quote on Accenture that showed that actually 50% of the women above age 35 were actually dropping out of the technology. And those numbers are scary. However, on the other side we have also seen incredible amount of technology innovation during that time with cloud adoption increasing with the ability to actually work remotely if you are even living in not so secure areas, for example that created more opportunities for women to come back to workforce as well. So we can turn the challenges to opportunities and watch out for those. I would say tipping points. >> I love that you bring up such a great point. There are so, so the, the data doesn't lie, right? The data shows that there's a significant amount of churn for women in technology. But to your point, there are so many opportunities. You mentioned a minute ago the skills gap. One of the things we talk about often on theCUBE and we're talking about cybersecurity which is obviously it's a global risk for companies in every industry, is that there's massive opportunity for people of, of any type to be able to grow their skills. So knowing that there's trend, but there's also so much opportunity for women in technology to climb the ladder is kind of exciting. I think. >> It is. It is exciting. >> Talk to me a little bit about, I would love for the audience to understand some of your hands-on examples where you've really been successful helping organizations navigate digital transformation and their entry and success with cloud computing. What are some of those success stories that you're really proud of? >> Let me think about, first of all what we are seeing is with the digital transformation in general, every single business every single vertical is becoming a technology company. Telecom companies are becoming a technology company. Financial services are becoming a technology company and manufacturing is becoming a technology company. So every business is becoming technology driven. And data is the key. Data is the enabler for every single business. So when we think about the challenges, one of the examples that I give a big challenge for our customers is I can't find the critical data, I can't access it. What are my critical data elements? Because I have so high volumes growing exponentially. What are the critical data elements that I should care and how do I access that? And we work at Precisely with 99 of Fortune 100. So we have two 12,000 customers in over a hundred countries which means we have customers whose businesses are purely built on cloud, clean slate. We also have businesses who have very complex set of data platforms. They have financial services, insurance, for example. They have critical transactional workloads still running on mainframes, IBM i servers, SAP systems. So one of the challenges that we have, and I work with key customers, is on how do we make data accessible for advanced analytics in the cloud? Cloud opens up a ton of open source tools, AI, ML stack lots of tools that actually the companies can leverage for that analytics in addition to elasticity in addition to easy to set up infrastructure. So how do we make sure the data can be actually available from these transactional systems, from mainframes at the speed that the business requires. So it's not just accessing data at the speed the business requires. One of our insurance customers they actually created this data marketplace on Amazon Cloud. And the, their challenge was to make sure they can bring the fresh data on a nightly basis initially and which became actually half an hour, every half an hour. So the speed of the business requirements have changed over time. We work with them very closely and also with the Amazon teams on enabling bringing data and workloads from the mainframes and executing in the cloud. So that's one example. Another big challenge that we see is, can I trust my data? And data integrity is more critical than ever. The quality of data, actually, according to HBR Harvard Business Review survey, 47% of every new record of data has at least one critical data error, 47%. So imagine, I was talking with the manufacturing organization couple of weeks ago and they were giving me an example. They have these three letter quotes for parts and different chemicals they use in the manufacturing. And the single letter error calls a shutdown of the whole manufacturing line. >> Wow. >> So that kind of challenge, how do I ensure that I can actually have completeness of data cleanness of data and consistency in that data? Moreover, govern that on a continuous basis becomes one of the use cases that we help customers. And in that particular case actually we help them put a data governance framework and data quality in their manufacturing line. It's becoming also a critical for, for example ESG, environment, social and governance, supply chain, monitoring the supply chain, and assessing ESG metrics. We see that again. And then the third one, last one. I will give an example because I think it's important. Hybrid cloud becoming critical. Because there's a purest view for new companies. However, facilitating flexible deployment models and facilitating cloud and hybrid cloud is also where we really we can help our customers. >> You brought up some amazingly critical points where it comes to data. You talked about, you know, a minute ago, every company in every industry has to become a technology company. You could also say every company across every industry has to become a data company. They have to become a software company. But to your point, and what it sounds like precisely is really helping organizations to do is access the data access data that has high integrity data that is free of errors. Obviously that's business critical. You talked about the high percentage of errors that caused manufacturing shutdown. Businesses can't, can't have that. That could potentially be life-ending for an organization. So it sounds like what you're talking about data accessibility, data integrity data governance and having that all in real time is table stakes for businesses. Whether it's your grocery store, your local coffee shop a manufacturing company, and e-commerce company. It's table stakes globally these days. >> It is, and you made a very good point actually, Lisa when you talked about the local coffee shop or the retail. One other interesting statistic is that almost 80% of every data has a location attribute. So when we talk about data integrity we no longer talk about just, and consistency of data. We also talk about context, right? When you are going, for example, to a new town you are probably getting some reminders about where your favorite coffee shop is or what telecom company has an office in that particular town. Or if you're an insurance company and a hurricane is hitting southern Florida. Then you want to know how the path of that hurricane is going to impact your customers and predict the claims before they happen. Also understand the propensity of the potential customers that you don't yet have. So location and context, those additional attributes of demographics, visitations are creating actually more confident business insights. >> Absolutely. And and as the consumer we're becoming more and more demanding. We want to be able to transact things so easily whether it's in our personal life at the grocery store, at that cafe, or in our business life. So those demands from the customer are also really influencing the direction that companies need to go. And it's actually, I think it's quite exciting that the amount of personalization the location data that you talk about that comes in there and really helps companies in every industry deliver these the cloud can, these amazing, unique personalized experiences that really drive business forward. We could talk about that all day long. I have no problem. But I want to get in our final minutes here, Tendu. What do you see as in your crystal ball as next for the cloud? How do you see your role as CTO evolving? >> Sure. For what we are seeing in the cloud I think we will start seeing more and more focus on sustainability. Sustainable technologies and governance. Obviously cloud migrations cloud modernizations are helping with that. And we, we are seeing many of our customers they started actually assessing the ESG supply chain and reporting on metrics whether it's the percentage of face or energy consumption. Also on the social metrics on diversity age distribution and as well as compliance piece. So sustainability governance I think that will become one area. Second, security, we talked about IT security and data privacy. I think we will see more and more investments around those. Cybersecurity in particular. And ethical data access and ethics is becoming center to everything we are doing as we have those personalized experiences and have more opportunities in the cloud. And the third one is continued automation with AI, ML and more focus on automation because cloud enables that at scale. And the work that we need to do is too time-intensive and too manual with the amount of data. Data is powering every business. So automation is going to be an increased focus how my role evolves with that. So I have this unique combination. I have been open to non-linear career paths throughout my growth. So I have an understanding of how to innovate and build products that solve real business problems. I also have an understanding of how to sell them build partnerships that combined with the the scale of growth, the hyper growth that we have absorbed in precisely 10 times growth within the last 10 years through a combination of organic innovation and acquisitions really requires the speed of change. So change, implementing change at scale as well as at speed. So taking those and bringing them to the next challenge is the evolution of my role. How do I bring those and tackle keep an eye on what's coming as a challenge in the industry and how they apply those skills that I have developed throughout my career to that next challenge and evolve with it, bring the innovation to data to cloud and the next challenge that we are going to see. >> There's so much on the horizon. It's, there are certainly challenges, you know within technology, but there's so much opportunity. You've done such a great job highlighting your career path the, the big impact that you're helping organizations make leveraging cloud and the opportunity that's there for the rest of us to really get in there get our hands dirty and solve problems. Tendu, I always love our conversations. It's been such a pleasure having you back, back on theCUBE. Thank you for joining us on this special program series today. >> Thank you Lisa. And also thanks to AWS for the opportunity. >> Absolutely. This is brought, brought to us by AWS. For Dr.Tendu, you are good to go. I'm Lisa Martin. You're watching theCUBE special program series Women of the Cloud. We thank you so much for watching and we'll see you soon. (upbeat music)

(upbeat music) >> Hi everybody. Welcome back to theCUBE as to continue our coverage here at AWS re:Invent '22. We're in the Venetian. Out in Las Vegas, it is Wednesday. And the PaaS is still happening. I can guarantee you that. We continue our series of discussions as part of the "AWS Startup Showcase". This is the "Global Startup Program", a part of that showcase. And I'm joined by two gentlemen today who are going to talk about what CoreStack is up to. One of them is Ez Natarajan, who is the Founder and CEO. Good to have you- (simultaneous chatter) with us today. We appreciate it. Thanks, EZ. >> Nice to meet you, John. >> And Brad Winney who is the area Sales Leader for startups at AWS. Brad, good to see you. >> Good to see you, John. >> Thanks for joining us here on The Showcase. So Ez, first off, let's just talk about CoreStack a little bit for people at home who might not be familiar with what you do. It's all about obviously data, governance, giving people peace of mind, but much deeper than that. I'll let you take it from there. >> So CoreStack is a governance platform that helps customers maximize their cloud usage and get governance at scale. When we talk about governance, we instill confidence through three layers: solving the problems of the CIO, solving the problems of the CTO, solving the problems of the CFO, together with a single pin of class,- >> John: Mm-hmm. >> which helps them achieve continuous holistic automated outcomes at any given time. >> John: Mm-hmm. So, Brad, follow up on that a little bit- >> Yeah. because Ez touched on it there that he's got a lot of stakeholders- >> Right. >> with a lot of different needs and a lot of different demands- >> Mm-hmm. >> but the same overriding emotion, right? >> Yeah. >> They all want confidence. >> They all want confidence. And one of the trickiest parts of confidence is the governance issue, which is policy. It's how do we determine who has access to what, how we do that scale. And across not only start been a process. This is a huge concern, especially as we talked a lot about cutting costs as the overriding driver for 2023. >> John: Mm-hmm. >> The economic compression being what it is, you still have to do this in a secure way and as a riskless way as possible. And so companies like CoreStack really offer core, no pun intended, (Ez laughs) function there where you abstract out a lot of the complexity of governance and you make governance a much more simple process. And that's why we're big fans of what they do. >> So we think governance from a three dimensional standpoint, right? (speaks faintly) How do we help customers be more compliant, secure, achieve the best performance and operations with increased availability? >> Jaohn: Mm-hmm. >> At the same time do the right spend from a cost standpoint. >> Interviewer: Mm-hmm. So when all three dimensions are connected, the business velocity increases and the customer's ability to cater to their customers increase. So our governance tenants come from these three pillars of finance operations, security operations and air operations at cloud operations. >> Yeah. And... Yeah. Please, go ahead. >> Can I (indistinct)? >> Oh, I'm sorry. Just- >> No, that's fine. >> So part of what's going on here, which is critical for AWS, is if you notice a lot of (indistinct) language is at the business value with key stakeholders of the CTO, the CSO and so on. And we're doing a much better job of speaking business value on top of AWS services. But the AWS partners, again, like CoreStack have such great expertise- >> John: Mm-hmm. >> in that level of dialogue. That's why it's such a key part for us, why we're really interested partnering with them. >> How do you wrestle with this, wrestle may not be the right word, but because you do have, as we just went through these litany, these business parts of your business or a business that need access- >> Ez: Mm-hmm. >> and that you need to have policies in place, but they change, right? I mean, and somebody maybe from the financial side should have a window into data and other slices of their business. There's a lot of internal auditing. >> Man: Mm-hmm. >> Obviously, it's got to be done, right? And so just talk about that process a little bit. How you identify the appropriate avenues or the appropriate gateways for people to- >> Sure. >> access data so that you can have that confidence as a CTO or CSO, that it's all right. And we're not going to let too much- >> out to the wrong people. >> Sure. >> Yeah. So there are two dimensions that drive the businesses to look for that kind of confidence building exercise, right? One, there are regulatory external requirements that say that I know if I'm in the financial industry, I maybe need to following NIST, PCI, and sort of compliances. Or if I'm in the healthcare industry, maybe HIPAA and related compliance, I need to follow. >> John: Mm-hmm. >> That's an external pressure. Internally, the organizations based on their geographical presence and the kind of partners and customers they cater to, they may have their own standards. And when they start adopting cloud; A, for each service, how do I make sure the service is secure and it operates at the best level so that we don't violate any of the internal or external requirements. At the same time, we get the outcome that is needed. And that is driven into policies, that is driven into standards which are consumable easily, like AWS offers well-architected framework that helps customers make sure that I know I'm architecting my application workloads in a way that meets the business demands. >> John: Mm-hmm. >> And what CoreStack has done is taken that and automated it in such a way it helps the customers simplify that process to get that outcome measured easily so they get that confidence to consume more of the higher order services. >> John: Okay. And I'm wondering about your relationship as far with AWS goes, because, to me, it's like going deep sea fishing and all of a sudden you get this big 4, 500 pound fish. Like, now what? >> Mm-hmm. >> Now what do we do because we got what we wanted? So, talk about the "Now what?" with AWS in terms of that relationship, what they're helping you with, and the kind of services that you're seeking from them as well. >> Oh, thanks to Brad and the entire Global Startup Ecosystem team at AWS. And we have been part of AWS Ecosystem at various levels, starting from Marketplace to ISV Accelerate to APN Partners, Cloud Management Tools Competency Partner, Co-Sell programs. The team provides different leverages to connect to the entire ecosystem of how AWS gets consumed by the customers. Customers may come through channels and partners. And these channels and partners maybe from WAs to MSPs to SIs to how they really want to use each. >> John: Mm-hmm. >> And the ecosystem that AWS provides helps us feed into all these players and provide this higher order capability which instills confidence to the customers end of the day. >> Man: Absolutely. Right. >> And this can be taken through an MSP. This can be taken through a GSI. This can be taken to the customer through a WA. And that's how our play of expansion into larger AWS customer base. >> Brad: Yeah. >> Brad, from your side of the fence. >> Brad: No, its... This is where the commons of scale come to benefit our partners. And AWS has easily the largest ecosystem. >> John: Mm-hmm. >> Whether or not it's partners, customers, and the like. And so... And then, all the respective teams and programs bring all those resources to bear for startups. Your analogy of of catching a big fish off coast, I actually have a house in Florida. I spend a lot of time there. >> Interviewer: Okay. >> I've yet to catch a big 500 pound fish. But... (interviewer laughs) >> But they're out there. >> But they're definitely out there. >> Yeah. >> And so, in addition to the formalized programs like the Global Partner Network Program, the APN and Marketplace, we really break our activities down with the CoreStacks of the world into two major kind of processes: "Sell to" and "Sell with". And when we say "Sell to", what we're really doing is helping them architect for the future. And so, that plays dividends for their customers. So what do we mean by that? We mean helping them take advantage of all the latest serverless technologies: the latest chip sets like Graviton, thing like that. So that has the added benefit of just lowering the overall cost of deployment and expend. And that's... And we focus on that really extensively. So don't ever want to lose that part of the picture of what we do. >> Mm-hmm. >> And the "Sell with" is what he just mentioned, which is, our teams out in the field compliment these programs like APN and Marketplace with person-to-person in relationship development for core key opportunities in things like FinTech and Retail and so on. >> Interviewer: Mm-hmm. >> We have significant industry groups and business units- >> Interviewer: Mm-hmm. >> in the enterprise level that our teams work with day in and day out to help foster those relationships. And to help CoreStack continue to develop and grow that business. >> Yeah. We've talked a lot about cost, right? >> Yeah. >> But there's a difference between reducing costs or optimizing your spend, right? I mean there- >> Brad: Right. >> Right. There's a... They're very different prism. So in terms of optimizing and what you're doing in the data governance world, what kind of conversations discussions are you having with your clients? And how is that relationship with AWS allowing you to go with confidence into those discussions and be able to sell optimization of how they're going to spend maybe more money than they had planned on originally? >> So today, because of the extra external micro-market conditions, every single customer that we talk to wanting to take a foster status of, "Hey, where are we today? How are we using the cloud? Are we in an optimized state?" >> Interviewer: Mm-hmm. >> And when it comes to optimization, again, the larger customers that we talk to are really bothered about the business outcome and how their services and ability to cater to their customers, right? >> Interviewer: Mm-hmm. >> They don't want to compromise on that just because they want to optimize on the spend. That conversation trickled down to taking a poster assessment first, and then are you using the right set of services within AWS? Are the right set of services being optimized for various requirements? >> Interviewer: Mm-hmm. >> And AWS help in terms of catering to the segment of customers who need that kind of a play through the patent ecosystem. >> John: Mm-hmm. Yeah. We've talked a lot about confidence too, cloud with confidence. >> Brad: Yeah. Yeah. >> What does that mean to different people, you think? I mean, (Brad laughing) because don't you have to feel them out and say "Okay. What's kind of your tolerance level for certain, not risks, but certain measures that you might need to change"? >> I actually think it's flipped the other way around now. I think the risk factor- >> Okay. >> is more on your on-prem environment. And all that goes with that. 'Cause you... Because the development of the cloud in the last 15 years has been profound. It's gone from... That's been the risky proposition now. With all of the infrastructure, all the security and compliance guardrails we have built into the cloud, it's really more about transition and risk of transition. And that's what we see a lot of. And that's why, again, where governance comes into play here, which is how do I move my business from on-prem in a fairly insecure environment relatively speaking to the secure cloud? >> Interviewer: Sure. >> How do I do that without disrupting business? How do I do that without putting my business at risk? And that's a key piece. I want to come back, if I may, something on cost-cutting. >> Interviewer: Sure. >> We were talking about this on the way up here. Cost-cutting, it's the bonfire of the vanities in that in that everybody is talking about cost-cutting. And so we're in doing that perpetuating the very problem that we kind of want to avoid, which is our big cost-cutting. (laughs) So... And I say that because in the venture capital community, what's happening is two things: One is, everybody's being asked to extend their runways as much as possible, but they are not letting them off the hook on growth. And so what we're seeing a lot of is a more nuanced conversation of where you trim your costs, it's not essential, spend, but reinvest. Especially if you've got good strong product market fit, reinvest that for growth. And so that's... So if I think about our playbook for 2023, it's to help good strong startups. Either tune their market fit or now that they good have have good market fit, really run and develop their business. So growth is not off the hook for 2023. >> And then let me just hit on something- >> Yeah. >> before we say goodbye here that you just touched on too, Brad, about. How we see startups, right? AWS, I mean, obviously there's a company focus on nurturing this environment of innovation and of growth. And for people looking at maybe through different prisms and coming. >> Brad: Yeah. >> So if you would maybe from your side of the fence, Ez from CoreStack, about working as a startup with AWS, I mean, how would you characterize that relationship about the kind of partnership that you have? And I want to hear from Brad too about how he sees AWS in general in the startup world. But go ahead. >> It's kind of a mutually enriching relationship, right? The support that comes from AWS because our combined goal is help the customers maximize the potential of cloud. >> Interviewer: Mm-hmm. >> And we talked about confidence. And we talked about all the enablement that we provide. But the partnership helps us get to the reach, right? >> Interviewer: Mm-hmm. >> Reach at scale. >> Interviewer: Mm-hmm. We are talking about customers from different industry verticals having different set of problems. And how do we solve it together so that like the reimbursement that happens, in fact healthcare customers that we repeatedly talk to, even in the current market conditions, they don't want to save. They want to optimize and re-spend their savings using more cloud. >> Interviewer: Mm-hmm. >> So that's the partnership that is mutually enriching. >> Absolutely. >> Yeah. To me, this is easy. I think the reason why a lot of us are here at AWS, especially the startup world, is that our business interests are completely aligned. So I run a pretty significant business unit in a startup neighbor. But a good part of my job and my team's job is to go help cut costs. >> Interviewer: Mm-hmm. >> So tell me... Show me a revenue responsibility position where part of your job is to go cut cost. >> Interviewer: Right. >> It's so unique and we're not a non-profit. We just have a very good long-term view, right? Which is, if we help companies reduce costs and conserve capital and really make sure that that capital is being used the right way, then their long-term viability comes into play. And that's where we have a chance to win more of that business over time. >> Interviewer: Mm-hmm. >> And so because those business interests are very congruent and we come in, we earn so much trust in the process. But I think that... That's why I think we being AWS, are uniquely successful startups. Our business interests are completely aligned and there's a lot of trust for that. >> It's a great success story. It really is. And thank you for sharing your little slice of that and growing slice of that too- >> Yeah. Absolutely. >> from all appearances. Thank you both. >> Thank you, John. >> Thank you very much, John. >> Appreciate your time. >> This is part of the AWS Startup Showcase. And I'm John Walls. You're watching theCUBE here at AWS re:Invent '22. And theCUBE, of course, the leader in high tech coverage.

>>Now welcome back to the Cube as we continue our coverage here. AWS Reinvent 2022, going out here at the Venetian in Las Vegas. Tens of thousands of attendees. That exhibit Hall is full. Let me tell you, it's been something else. Well, here in the executive summit, sponsored by Accenture. Accenture rather. We're gonna talk about Baptist Health, what's going on with that organization down in South Florida with me. To do that, I have Tony Abro, who's the SVP and Chief Digital and Information Officer. I have Ashley Lane, the managing director of the Accenture Healthcare Practice, and on the far end Poop Kumar, who is the VP and cto Baptist Health Florida won and all. Welcome. Thank you. First off, let's just talk about Baptist Health, the size of your footprint. One and a half million patient visits a year, not a small number. >>That was probably last year's number, but okay. >>Right. But not a small number about your footprint and, and what, I guess the client base basically that you guys are serving in it. >>Absolutely. So we are the largest organization in South Florida system provider and the 11 hospitals soon to be 12, as you said, it's probably about 1.8 million by now. People were, were, were supporting a lot of other units and you know, we're focusing on the four southern counties of South Florida. Okay. >>So got day Broward. Broward, yep. Down that way. Got it. So now let's get to your migration or your cloud transformation. As we're talking about a lot this week, what's been your, I guess, overarching goal, you know, as you worked with Accenture and, and developed a game plan going forward, you know, what was on the front end of that? What was the motivation to say this is the direction we're going to go and this is how we're gonna get there? >>Perfect. So Baptist started a digital transformation initiative before I came about three years ago. The board, the executive steering committee, decided that this is gonna be very important for us to support us, to help our patients and, and consumers. So I was brought in for that digital transformation. And by the way, digital transformation is kind of an umbrella. It's really business transformation with technology, digital technologies. So that's, that's basically where we started in terms of consumer focused and, and, and patient focus. And digital is a big word that really encompasses a lot of things. Cloud is one of, of course. And, you know, AI and ML and all the things that we are here for this, this event, you know, and, and we've started that journey about two years ago. And obviously cloud is very important. AWS is our main cloud provider and clearly in AWS or any club providers is not just the infrastructure they're providing, it's the whole ecosystem that provides us back value into, into our transformation. And then somebody, I think Adam this morning at the keynote said, this is a team sport. So with this big transformation, we need all the help and that we can get to mines and, and, and hands. And that's where Accenture has been invaluable over the last two years. >>Yeah, so as a team sport then depu, you, you've got external stakeholders, otherwise we talked about patience, right? Internal, right. You've, you've got a whole different set of constituents there, basically, but it takes that team, right? You all have to work together. What kind of conversations or what kind of actions, I guess have you had with different departments and what different of sectors of, of the healthcare business as Baptist Health sees it in order to bring them along too, because this is, you know, kind of a shocking turn for them too, right? And how they're gonna be doing business >>Mostly from an end user perspective. This is something that they don't care much about where the infrastructure is hosted or how the services are provided from that perspective. As long as the capabilities function in a better way, they are seemingly not worried about where the hosting is. So what we focus on is in terms of how it's going to be a better experience for, from them, from, from their perspective, right? How is it going to be better responsiveness, availability, or stability overall? So that's been the mode of communication from that perspective. Other than that, from a, from a hosting and service perspective, the clientele doesn't care as much as the infrastructure or the security or the, the technology and digital teams themselves. >>But you know, some of us are resistant to change, right? We're, we're just, we are old dogs. We don't like new tricks and, and change can be a little daunting sometimes. So even though it is about my ease of use and my efficiency and why I can then save my time on so and so forth, if I'm used to doing something a certain way, and that's worked fine for me and here comes Tony and Depo and here comes a, >>They're troublemaker >>And they're stir my pot. Yeah. So, so how do you, the work, you were giving advice maybe to somebody watching this and say, okay, you've got internal, I wouldn't say battles, but discussions to be held. How did you navigate through that? >>Yeah, no, absolutely. And Baptist has been a very well run system, very successful for 60 something odd years. Clearly that conversation did come, why should we change? But you always start with, this is what we think is gonna happen in the future. These are the changes that very likely will happen in the future. One is the consumer expectations are the consumer expectations in terms of their ability to have access to information, get access to care, being control of the process and their, their health and well-being. Everything else that happens in the market. And so you start with the, with that, and that's where clearly there are, there are a lot of signs that point to quite a lot of change in the ecosystem. And therefore, from there, the conversation is how do we now meet that challenge, so to speak, that we all face in, in, in healthcare. >>And then from there, you kind of designed the, a vision of where we want to be in terms of that digital transformation and how do we get there. And then once that is well explained and evangelized, and that's part of our jobs with the help of our colleagues who have, have been doing this with others, then is the, what I call a tell end show. We're gonna say, okay, in this, in this road, we're gonna start with this. It's a small thing and we're gonna show you how it works in terms of, in terms of the process, right? And then as, as you go along and you deliver some things, people understand more, they're on board more and they're ready for for more. So it's iterative from small to larger. >>The proof is always in the place, right? If you can show somebody, so actually I, I obviously we know about Accenture's role, but in terms of almost, almost what Tony was just saying, that you have to show people that it works. How, how do you interface with a client? And when you're talking about these new approaches and you're suggesting changes and, and making these maybe rather dramatic proposals, you know, to how they do things internally, from Accenture's perspective, how do you make it happen? How, how do you bring the client along in this case, batches >>Down? Well, in this case, with Tony and Depu, I mean, they have been on this journey already at another client, right? So they came to Baptist where they had done a similar journey previously. And so it wasn't really about convincing >>Also with Accenture's >>Health, also with Accenture's Health, correct. But it wasn't about telling Tony Dupe, how do we do this? Or anything like that. Cuz they were by far the experts and have, you know, the experience behind it. Well, it's really like, how do we make sure that we're providing the right, right team, the right skills to match, you know, what they wanted to do and their aspirations. So we had brought the, the healthcare knowledge along with the AWS knowledge and the architects and you know, we said that we gotta, you know, let's look at the roadmap and let's make sure that we have the right team and moving at the right pace and, you know, testing everything out and working with all the different vendors in the provider world specifically, there's a lot of different vendors and applications that are, you know, that are provided to them. It's not a lot of custom activity, you know, applications or anything like that. So it was a lot of, you know, working with other third party that we really had to align with them and with Baptist to make sure that, you know, we were moving together at speed. >>Yeah, we've heard about transformation quite a bit. Tony, you brought it up a little bit ago, depu, just, if you had to define transformation in this case, I mean, how big of a, of a, of a change is that? I mean, how, how would you describe it when you say we're gonna transform our, you know, our healthcare business? I mean, I think there are a lot of things that come to my mind, but, but how do you define it and, and when you're, when you're talking to the folks with whom you've got to bring along on this journey? >>So there's the transformation umbrella and compos two or three things. As Tony said, there is this big digital transformation that everybody's talking about. Then there is this technology transformation that powers the digital transformation and business transformation. That's the outcome of the digital transformation. So I think we, we started focusing on all three areas to get the right digital experience for the consumers. We have to transform the way we operate healthcare in its current state or, or in the existing state. It's a lot of manual processes, a lot of antiquated processes, so to speak. So we had to go and reassess some of that and work with the respective business stakeholders to streamline those because in, it's not about putting a digital solution out there with the anti cured processes because the outcome is not what you expect when you do that. So from that perspective, it has been a heavy lifting in terms of how we transform the operations or the processes that facilitates some of the outcomes. >>How do you know it's working >>Well? So I I, to add to what Deep was saying is I think we are fortunate and that, you know, there are a lot of folks inside Baptist who have been wanting this and they're instrumental to this. So this is not a two man plus, you know, show is really a, you know, a, a team sport. Again, that same. So in, in that, that in terms of how do we know it works well when, when we define what we want to do, there is some level of precision along the way. In those iterations, what is it that we want to do next, right? So whatever we introduce, let's say a, a proper fluid check in for a patient into a, for an appointment, we measure that and then we measure the next one, and then we kind of zoom out and we look at the, the journey and say, is this better? >>Is this better for the consumer? Do they like it better? We measure that and it's better for the operations in terms of, but this is the interesting thing is it's always a balance of how much you can change. We want to improve the consumer experience, but as deeply said, there's lot to be changed in, in the operations, how much you do at the same time. And that's where we have to do the prioritization. But you know, the, the interesting thing is that a lot of times, especially on the self servicing for consumers, there are a lot of benefits for the operations as well. And that's, that's where we're in, we're in it together and we measure. Yeah, >>Don't gimme too much control though. I don't, I'm gonna leave the hard lifting for you. >>Absolutely, absolutely right. Thank you. >>So, and, and just real quick, Ashley, maybe you can shine some light on this, about the relationship, about, about next steps, about, you know, you, you're on this, this path and things are going well and, and you've got expansion plans, you want, you know, bring in other services, other systems. Where do you want to take 'em in the big picture in terms of capabilities? >>Well, I, I mean, they've been doing a fantastic job just being one of the first to actually say, Hey, we're gonna go and make an investment in the cloud and digital transformation. And so it's really looking at like, what are the next problems that we need to solve, whether it's patient care diagnosis or how we're doing research or, you know, the next kind of realm of, of how we're gonna use data and to improve patient care. So I think it's, you know, we're getting the foundation, the basics and everything kind of laid out right now. And then it's really, it's like what's the next thing and how can we really improve the patient care and the access that they have. >>Well, it sure sounds like you have a winning accommodation, so I I keep the team together. >>Absolutely. >>Teamwork makes the dream >>Work. Absolutely. It is, as you know. So there's a certain amount of, if you look at the healthcare industry as a whole, and not, not just Baptist, Baptist is, you know, fourth for thinking, but entire industry, there's a lot of catching up to do compared to whatever else is doing, whatever else the consumers are expecting of, of an entity, right? But then once we catch up, there's a lot of other things that we were gonna have to move on, innovate for, for problems that we maybe we don't know we have will have right now. So plenty of work to do. Right. >>Which is job security for everybody, right? >>Yes. >>Listen, thanks for sharing the story. Yeah, yeah. Continued success. I wish you that and I appreciate the time and expertise here today. Thank you. Thanks for being with us. Thank you. Thank you. We'll be back with more. You're watching the Cube here. It's the Executive Summit sponsored by Accenture. And the cube, as I love to remind you, is the leader in tech coverage.

>> Well, thanks for joining us here on theCUBE. I'm John Walls. We're at Reinvent AWS's big show going on here in Las Vegas at the Venetian. Going to be here all week, so be sure to tune in here to theCUBE as we continue our executive summit sponsored by Accenture today. Joined now by Steve Steuart, who's the worldwide principal on mainframe migration at Go to Market at AWS. Steve, good to see you, sir. >> Nice to meet you. >> Just found out we're neighbors, as a matter of fact, down in northeastern Florida. >> That's right. >> So we'll exchange addresses later, I'm sure. And Joel Rosenberger, who is a global mainframe monetization lead for the Accenture AWS business group. Joel, good to see you. >> Nice to meet you. >> Thanks for joining us here on theCUBE. >> Absolutely. >> All right, so what's up with the mainframe? We're kind of kidding about 64 Corvette's versus 22 Teslas and making that old Corvette. Dress it up, take it out for the street ride. Make it nice and fun. But let's just set the stage here first off for our viewers about mainframe and kind of the status in terms of modernization and getting it up to 22 standards. >> Right, I mean, I think the big thing is that, you know modernization for mainframes is different for every customer based on their drivers and where they want to go. You know, at AWS we like to say transform with AWS, augmentation pattern, hybrid pattern, working coexisting or transform too. So move some of those workloads into the cloud. And it's not that, you know mainframes are fantastic machines, but they are in dire need of modernization with their applications. And that's really the driving force and the business needs to make a decision based on their drivers, what's best fit for them. And we're here to help. >> So how, Joel, go ahead. >> Oh, I was going to say, and we're saying that too is basically the mainframe is a great technology platform but it's the processes around that that not kept up. So making changes to the mainframe applications can take a couple years, for the simplest changes. And so when Steve talks about modernizing with or on the mainframe it's really how do we improve those processes? And from our perspective and companies are really struggling with that right now. >> Yeah, and how do you go about this, because the mainframe is so center, right? It is so integral, right? >> Oh it's center. >> Oh yeah, absolutely. >> Absolutely essential. And yet you're talking about changes being made over a period of time of years. A lot of sensitivity there, right? >> Oh absolutely. >> Lot of complexity there. So how do you start factoring all that in and selling that to somebody that this journey might take you till 2025 to get it done? >> Well it could be a multi-year process. The selling is really the business drivers. You have to, businesses today need to leverage the cloud to be competitive. >> Absolutely. >> Right, that's just a fact. Right? So, how do you transform with modernize in place, or transform over. But it is a transformational change. If you look at the number one drivers is agility. The CEO say, I want this green next week and well we can't get it to you next week. We can get it to you Q2 of next year. Born in the cop companies... >> That's probably not the answer they want to hear. >> No, they don't want hear that. >> That is not the answer they want to hear. >> Our number one issue is that there are CEOs saying that we can't be agile, but mainframes can't be agile, if you develop, adopt DevOps for your mainframe. >> Yep. >> IBM has an offering, we have an offering as well. And so they need to start looking at that. So what are your drivers? Go to market responsiveness, competitive, what are the drivers? And then you make a decision as to where you want to move the workload. >> Joel: Yep. >> Is it hard though, Joel, just because as you know this environment is so dynamic now, right? >> Yep. >> And change is rapid, and I mean like capital R. >> Yep, absolutely. Yep. >> So all of a sudden you set this two/three year trajectory and yet opportunities, solutions, options can vary in year one or year two and all of a sudden this path you had set is going to have to take a left turn instead of a right turn because of a new development. Right? So it's... >> Absolutely, I mean, and that's one of the biggest struggles that people have is with business agility. Exactly what you're saying is the market is changing faster, like Steve said, it might be a year or so before I can deliver that but the market has already changed from that perspective. >> Right. >> And so I think a lot of people are trying to modernize with that. So they're connecting a lot of web properties to mainframes but that causes additional problems. >> Right. >> And those problems are the mainframe now scales unpredictably, because I don't know, how do I predict web traffic and from that perspective, so a lot of people are struggling do I have enough capacity on the mainframe to do that? Cause it's not elastic like the cloud from that perspective. So there's a lot of patterns that have to be reinvented, or already been invented with the cloud and how do we do that with the mainframe now? >> So you could get benefits not waiting three to four years. >> Absolutely. >> You get benefit pretty much immediately by doing augmentation patterns consuming processing on the mainframe, consuming it maybe certain movements, certain workloads, bringing on down quicker. You know, if you're a large estate it'll take you time but you are able to drive that. Part of our assessments is bottom up what you currently have, and what are your business drivers. >> Yep, absolutely. >> What are the big boulder items you need to do and tackle those. And so it's a process that we work together with our customers to start transforming their mainframe. >> Right. >> Yeah I hear about, I'm sorry, go on Joel. >> Yeah, and a key thing on that is a lot of people look at the mainframe is this big monolith. >> John: Right. >> It's basically the this big thing, I don't know what to do with, I don't want to touch because if I touch it I might break it. I don't have people to fix it. And so there's a lot of concern around that, but one of the things like Steve said is how Accenture and AWS work together is figuring out how do I take that monolith, divide it into smaller pieces either through data augmentation, through an analysis, and figure out a roadmap through that application or that monolithic applications and figure out how to move. >> Well that's, how you get an elephant, right? Leverage is one part at a time. >> Exactly, one part at a time. >> It's just one. >> Right, it's just leverage AI, leverage or AI and our platforms and machine learning. All these things are available and you can coexist with that. >> All right, so tell me about technical debt. I read about technical debt and you know, it kind of comes with the territory, >> Right. >> in terms of mainframe. So how do you, first off, you know, how do you define that and then how do you deal with that? How do you make that go away as far as concerns go? >> Well, you know, you have to look at your, for my definition for technical debts is the same thing when my wife says I have to do something in the backyard and I push it, I'll do it next time. Right? So it starts piling up, right? There's a lot of to-dos at the house. >> Absolutely. >> Right, it's the same thing, it's the IT to-dos that you just put off. >> I'll catch up to that some other time. >> Yep. >> And there you are, they keep on... And so next thing you know, you have this, oh my gosh I got all this work I got to do. >> Right. And that's part of the technical debt. And then so you got to look at how does that resolving that meet my needs for the cloud. So leveraging the cloud, if you're under mainframe you have limited solutions for addressing your technical debt. Leveraging the cloud with the mainframe, now you have multiple options for you. to tackle and eliminate your technical debt. So that's one of the benefits of leveraging the cloud for that. >> And I would add on to what Steve said about technical debt. It's exactly that, it's I haven't done that yet, but one of the things that I've seen is there's multiple ways to solve any problem, any programming problem technical problem from that, there's a shortcut way to get it done quickly, >> John: Right. >> that may not be clean and scalable and that. And what happens is, especially on the mainframe over 40 or 50 years, a lot of those shortcuts have been taken. And so it's not even as easy as, it's basically, you think about it, I didn't do it but now my grass is this high, >> John: Right. >> And now I got to do it, type of thing. So it's really about... >> And you can't use a lawnmower >> You can't use a lawnmower so you have to figure out different ways. >> You can't bag it, >> No, no. >> No, no, a whole nother >> Absolutely. >> Right. >> So understanding technical debt and overcoming it is realizing that those shortcuts need to be re-architected, redesigned, modernized, >> All right. >> from that perspective. And you need to take that perspective on. >> So you guys have to be kind of sometimes the bearer of bad news in a way, right? Because they have these, you said monolithic of systems in place that need revised they got to be modernized. >> Yep. >> And they've been kicking that can down the road. We've talked about some big companies for a long time. So they got a lot of baggage on that side and they have to get up to speed. So if, if you were talking to a prospective client, about understanding why it's time to start doing that necessary housekeeping, how do you convince people that this is the time? >> What are your top three absolutely mission critical applications that you have today, right? What is the staff that maintains it? What is the average age of those resources? And what is your succession strategy? >> Joel: Yep. >> It's as simple as that. >> Oh. >> I would add on to that. A lot of times we don't have to convince the customer right now. >> John: Right. >> The customers are coming to us, because what's happened is this whole digital transformation that's happening in the web and all that kind of stuff. Their competitors are already moving off of that. Or have come up with something else. So the business is coming and saying, why can't I move that fast? >> Right. >> And then, like Steve said is those are the reasons why you can't move that fast. So let's address those reasons. >> All right, the born of the cloud company is coming in, but also another driving force that's happening, If you look at a lot of our new customers. Are the digital natives arriving in the C-suites. So the folks that have always known the internet understand the benefits of the cloud, or where there's a new CIO, new CEO. >> Yep. >> And so we're seeing that changing of the guard type scenario. >> Because a lot of those people grew up with a mainframe. >> Right. Right. >> And of the old guard. >> Sure. >> And they're like, well it's worked for the last 30 years, why don't I just keep it working the same way it is. >> And don't we need it to work? >> Yeah >> Right? The way it has been? >> Yeah, exactly. >> Yeah. >> Well, and that's the other key thing, is the core applications. So what has happened with the cloud is over the last you know, 10, 15 years is a lot of the applications that could move moved. Now we're left with the core applications on the mainframe and those are the ones that a multi-billion dollar company, if they get that wrong, they're out business. So there's a lot of scrutiny and a lot of other things. So a lot of the stuff that we're doing now is to help understand that risk and get over that risk. >> And do companies have the expertise in house, to do this? And where do you find it outside? Because it, you know, might not be the sexiest thing to do. >> That's a great question because, you know Steve and I talk about this all the time which is running the mainframe is different than modernizing the mainframe. >> Steve: Right. And so I might have a lot of skills in house to run the mainframe, but how do I figure out to get, to break up that monolith into pieces. >> Steve: Right. How do I figure out, you know, how the best way to put that on AWS? How do I figure that out? You need to leverage people like AWS and Accenture and others to be able to do that. >> This is, there's a psychology to this and more technical, there's more psychological than technical. So you got to find your unicorns. People should have gas in the tank that want to adopt. >> Joel: Yep, absolutely. >> And the ones that don't, then, you know, they're out. You know, nothing like passive aggressive people showing up to help, to really cause havoc. (all laugh) And that's really what you got to kind of focus on. >> Yes. We see that a lot. >> Right. Right. But that's where the managing service comes in too right? >> Absolutely. >> You can get people there. You can, this is a worry they can check the box and move on and get help in that. >> Yeah. AWS, this is an industry first, where you have a managed service within your console to provision tooling to analyze, develop for the mainframe or deploy onto AWS. But the running of it, specific servers that have been you know, optimized for mainframe workloads with your monitoring and security and all those things it's an industry first. I've been in this business 30 years it's fantastic with what I'm seeing over here. >> And do you have any kind of a guess about what share is still out there to be had, in terms of modernizing mainframes, in terms of businesses? I mean, are there still, well, you know it might be hard to put a, to quantify it with a number, but there's still a lot of folks... >> Oh yeah. >> who haven't made that commitment yet. >> Well, they're beginning to, so if you look at, I think, I'm going to throw a number out, I think it's like 80% of the Fortune 100 companies have mainframes. >> Absolutely. >> Is that right? >> So yeah, if you paid your mortgage today, if you used your cell phone today, if you've done any of those things, core stuff is run on mainframe. >> Financial transactions are huge. >> Oh huge, huge, you've got airlines, manufacturing, >> Insurance. >> healthcare. >> John: Right. >> Pretty much everything runs on a mainframe, if you go deep enough in the organization. >> And so that's all, you know people are making those decisions. And what we've done is what I call an earn trust moment. You know, AWS standing up and saying, 'hey we're here to help our customers to move' we're a large organization, we're doing heavy investments in this. We have R&Dand staff, to help our customers transform with or to AWS. >> And we're seeing that resonated in the marketplace. So last year AWS announced the mainframe modernization service Over the last year, we've seen clients, like I said is they're coming to us now. >> Right. >> Saying we want to go mainframe zero, for lack of a better expression. And so we're just seeing a lot of activity. So what AWS did last year has really resonated within the marketplace and changed that dynamic. >> Well, the mainframe ain't dead yet. >> No. >> It isn't. >> It's not going to die. I think there's going to be a different >> Too big, two powerful and too necessary. >> Absolutely. >> Yeah I think we're going to coexist with it and some will leave, so. >> But you still need that same functionality, just somewhere else. >> All right. >> That's right. Well, appreciate the conversation, neighbor. >> Thank you. (all laugh) >> And have a great show. Look forward to seeing you down the road here. >> Thank you very much. >> Thanks John, appreciate it. >> Thanks for joining us here. You are watching theCUBE here at Reinvent 22. And theCUBE, as I remind you is the leader in high tech coverage. (soothing music)

>>Hey everyone. Welcome back to the cubes day two coverage of VMware Explorer, 22 from San Francisco. Lisa Martin, back here with you with Dave Nicholson, we have a couple of guests from VMware. Joining us, please. Welcome Jay Workman, senior director, cloud partner, and alliances marketing, and Jeff Thompson, VP cloud provider sales at VMware guys. It's great to have you on the program. >>Ah, good to be here. Thanks for having us on. >>We're gonna be talking about a really interesting topic. Sovereign cloud. What is sovereign cloud? Jeff? Why is it important, but fundamentally, what is >>It? Yeah, well, we were just talking a second ago. Aren't we? And it's not about royalty. So yeah, data sovereignty is really becoming super important. It's about the regulation and control of data. So lots of countries now are being very careful and advising companies around where to place data and the jurisdictional controls mandate that personal data or otherwise has to be secured. We ask, we have to have access controls around it and privacy controls around it. So data sovereign clouds are clouds that have been built by our cloud providers in, in, in VMware that specifically satisfy the requirements of those jurisdictions and regulated industries. So we've built a, a little program around that. We launched it about a year ago and continuing to add cloud providers to that. >>Yeah, and I, I think it's also important just to build on what Jeff said is, is who can access that data is becoming increasingly important data is, is almost in it's. It is becoming a bit of a currency. There's a lot of value in data and securing that data is, is becoming over the years increasingly important. So it's, it's not like we built a problem or we created a solution for problem that didn't exist. It's gotten it's, it's been a problem for a while. It's getting exponentially bigger data is expanding and growing exponentially, and it's becoming increasingly important for organizations and companies to realize where my data sits, who can access it, what types of data needs to go and what type of clouds. And it's very, very aligned with multi-cloud because some data can sit in a, in a public cloud, which is fine, but some data needs to be secure. It needs to be resident within country. And so this is, this is what we're addressing through our partners. >>Yeah, I, yeah, I was just gonna add to that. I think there's a classification there there's data residency, and then there's data sovereignty. So residency is just about where is the data, which country is it in sovereignty is around who can access that data. And that's the critical aspect of, of data sovereignty who's got control and access to that data. And how do we make sure that all the controls are in place to make sure that only the right people can get access to that data? Yeah. >>So let's, let's sort of build from the ground up an example, and let's use Western Europe as an example, just because state to state in the United States, although California is about to adopt European standards for privacy in a, in a unique, in a unique, unique way, pick a country in, in Europe, I'm a service provider. I have an offering and that offering includes a stack of hardware and I'm running what we frequently refer to as the STDC or software defined data center stack. So I've got NEX and I've got vs N and I've got vSphere and I'm running and I have a cloud and you have all of the operational tools around that, and you can spin up VMs and render under applications there. And here we are within the borders of this country, what makes it a sovereign cloud at that? So at that point, is that a sovereign cloud or? >>No, not yet. Not it's close. I mean, you nailed, >>What's >>A secret sauce. You nailed the technology underpinning. So we've got 4,500 plus cloud provider partners around the world. Less than 10% of those partners are running the full STDC stack, which we've branded as VMware cloud verified. So the technology underpinning from our perspective is the starting point. Okay. For sovereignty. So they, they, they need that right. Technology. Okay. >>Verified is required for sovereign. Yes. >>Okay. Cloud verified is the required technology stack for sovereign. So they've got vSphere vs. A NSX in there. Okay. A lot of these partners are also offering a multitenant cloud with VMware cloud director on top of that, which is great. That's the starting point. But then we've, we've set a list of standards above and beyond that, in addition to the technology, they've gotta meet certain jurisdiction requirements, certain local compliance requirements and certifications. They've gotta be able to address the data re data residency requirements of their particular jurisdiction. So it's going above and beyond. But to your point, it does vary by country. >>Okay. So, so in this hypothetical example, this is this country. You a stand, I love it. When people talk about Stan, people talk about EMIA and you know, I, I love AMEA food. Isn't AIAN food. One. There's no such thing as a European until you have an Italian, a Britain, a German yep. In Florida arguing about how our beer and our coffee is terrible. Right. Right. Then they're all European. They go home and they don't like each other. Yeah. So, but let's just pretend that there's a thing called Europe. So this, so there's this, so we've got a border, we know residency, right. Because it physically is here. Yep. But what are the things in terms of sovereignty? So you're talking about a lot of kind of certification and validation, making sure that, that everything maps to those existing rules. So is, this is, this is a lot of this administrative and I mean, administrative in the, in the sort of state administrative terminology, >>I I'm let's build on your example. Yeah. So we were talking about food and obviously we know the best food in the world comes from England. >>Of course it does. Yeah. I, no doubt. I agree. I Don not get that. I do. I do do agree. Yeah. >>So UK cloud, fantastic partner for us. Okay. Whether they're one of our first sovereign cloud providers in the program. So UK cloud, they satisfied the requirements with the local UK government. They built out their cloud verified. They built out a stack specifically that enables them to satisfy the requirements of being a sovereign cloud provider. They have local data centers inside the UK. The data from the local government is placed into those data centers. And it's managed by UK people on UK soil so that they know the privacy, they know the security aspects, the compliance, all of that wrapped up on top of a secure SDDC platform. Okay. Satisfies the requirements of the UK government, that they are managing that data in a sovereign way that, that, that aligns to the jurisdictional control that they expect from a company like UK cloud. Well, >>I think to build on that, a UK cloud is an example of certain employees at UK, UK cloud will have certain levels of clearance from the UK government who can access and work on certain databases that are stored within UK cloud. So they're, they're addressing it from multiple fronts, not just with their hardware, software data center framework, but actually at the individual compliance level and individual security clearance level as to who can go in and work on that data. And it's not just a governmental, it's not a public sector thing. I mean, any highly regulated industry, healthcare, financial services, they're all gonna need this type of data protection and data sovereignty. >>Can this work in a hyperscaler? So you've got you, have, you have VMC AVS, right? GC V C >>O >>CVAs O CVS. Thank you. Can it be, can, can a sovereign cloud be created on top of physical infrastructure that is in one of those hyperscalers, >>From our perspective, it's not truly sovereign. If, if it's a United States based company operating in Germany, operating in the UK and a local customer or organization in Germany, or the UK wants to deploy workloads in that cloud, we wouldn't classify that as totally sovereign. Okay. Because by virtue of the cloud act in the United States, that gives the us government rights to request or potentially view some of that data. Yeah. Because it's, it's coming out of a us based operator data center sitting on foreign soil so that the us government has some overreach into that. And some of that data may actually be stored. Some of the metadata may reside back in the us and the customer may not know. So certain workloads would be ideally suited for that. But for something that needs to be truly sovereign and local data residency, that it wouldn't be a good fit. I think that >>Perspectives key thing, going back to residency versus sovereignty. Yeah. It can be, let's go to our UK example. It can be on a hyperscaler in the UK now it's resident in the UK, but some of the metadata, the profiling information could be accessible by the entity in the United States. For example, there now it's not sovereign anymore. So that's the key difference between a, what we view as a pro you know, a pure sovereign cloud play and then maybe a hyperscaler that's got more residency than sovereignty. >>Yeah. We talk a lot about partnerships. This seems to be a unique opportunity for a certain segment of partners yeah. To give that really is an opportunity for them to have a line of business established. That's unique from some of the hyperscale cloud providers. Yeah. Where, where sort of the, the modesty of your size might be an advantage if you're in a local. Yes. You're in Italy and you are a service provider. There sounds like a great fit, >>That's it? Yeah. You've always had the, the beauty of our program. We have 4,500 cloud providers and obviously not, all of them are able to provide a data, a sovereign cloud. We have 20 in the program today in, in the country. You you'd expect them to be in, you know, the UK, Italy, Italy, France, Germany, over in Asia Pacific. We have in Australia and New Zealand, Japan, and, and we have Canada and Latin America to, to dovetail, you know, the United States. But those are the people that have had these long term relationships with the local governments, with these regulated industries and providing those services for many, many years. It's just that now data sovereignty has become more important. And they're able to go that extra mile and say, Hey, we've been doing this pretty much, you know, for decades, but now we're gonna put a wrap and some branding around it and do these extra checks because we absolutely know that we can provide the sovereignty that's required. >>And that's been one of the beautiful things about the entire initiative is we're actually, we're learning a lot from our partners in these countries to Jeff's point have been doing this. They've been long time, VMware partners they've been doing sovereignty. And so collectively together, we're able to really establish a pretty robust framework from, from our perspective, what does data sovereignty mean? Why does it matter? And then that's gonna help us work with the customers, help them decide which workloads need to go and which type of cloud. And it dovetails very, very nicely into a multi-cloud that's a reality. So some of those workloads can sit in the public sector and the hyperscalers and some of 'em need to be sovereign. Yeah. So it's, it's a great solution for our customers >>When you're in customer conversations, especially as, you know, data sovereign to be is becomes a global problem. Where, who are you talking to? Are you talking to CIOs? Are you talking to chief data officers? I imagine this is a pretty senior level conversation. >>Yeah. I it's, I think it's all of the above. Really. It depends. Who's managing the data. What type of customer is it? What vertical market are they in? What compliance regulations are they are they beholden to as a, as an enterprise, depending on which country they're in and do they have a need for a public cloud, they may already be all localized, you know? So it really depends, but it, it could be any of those. It's generally I think a fair, fairly senior level conversation. And it's, it's, it's, it's consultancy, it's us understanding what their needs are working with our partners and figuring out what's the best solution for them. >>And I think going back to, they've probably having those conversations for a long time already. Yeah. Because they probably have had workloads in there for years, maybe even decades. It's just that now sovereignty has become, you know, a more popular, you know, requirements to satisfy. And so they've gone going back to, they've gone the extra mile with those as the trusted advisor with those people. They've all been working with for many, many years to do that work. >>And what sort of any examples you mentioned some of the highly regulated industries, healthcare, financial services, any customer come to mind that you think really articulates the value of what VMware's delivering through its service through its cloud provider program. That makes the obvious why VMware an obvious answer? >>Wow. I, I, I get there's, there's so many it's, it's actually, it's each of our different cloud providers. They bring their win wise to us. And we just have, we have a great library now of assets that are on our sovereign cloud website of those win wires. So it's many industries, many, many countries. So you can really pick, pick your, your choice. There. That's >>A good problem >>To have, >>To the example of UK cloud they're, they're really focused on the UK government. So some of them aren't gonna be referenced. Well, we may have indication of a major financial services company in Australia has deployed with AU cloud, one of our partners. So we we've also got some semi blind references like that. And, and to some degree, a lot of these are maintained as fairly private wins and whatnot for obvious security reasons, but, and we're building it and building that library up, >>You mentioned the number 4,500, a couple of times, you, you referencing VMware cloud provider partners or correct program partners. So VCP P yes. So 45, 4500 is the, kind of, is the, is the number, you know, >>That's the number >>Globally of our okay. >>Partners that are offering a commercial cloud service based at a minimum with vSphere and they're. And many of 'em have many more of our technologies. And we've got little under 10% of those that have the cloud verified designation that are running that full STDC, stack >>Somebody, somebody Talli up, all of that. And the argument has been made that, that rep that, that would mean that VMware cloud. And although some of it's on IAS from hyperscale cloud providers. Sure. But that, that rep, that means that VMware has the third or fourth largest cloud on the planet already right now. >>Right. Yep. >>Which is kind of interesting because yeah. If you go back to when, what 2016 or so when VMC was at least baned about yeah. Is that right? A lot of people were skeptical. I was skeptical very long history with VMware at the time. And I was skeptical. I I'm thinking, nah, it's not gonna work. Yeah. This is desperation. Sorry, pat. I love you. But it's desperation. Right. AWS, their attitude is in this transaction. Sure. Send us some customers we'll them. Yeah. Right. I very, very cynical about it. Completely proved me wrong. Obviously. Where did it go? Went from AWS to Azure to right. Yeah. To GCP, to Oracle, >>Oracle, Alibaba, >>Alibaba. Yep. Globally. >>We've got IBM. Yep. Right. >>Yeah. So along the way, it would be easy to look at that trajectory and say, okay, wow, hyperscale cloud. Yeah. Everything's consolidating great. There's gonna be five or six or 10 of these players. And that's it. And everybody else is out in the cold. Yeah. But it turns out that long tail, if you look at the chart of who the largest VCP P partners are, that long tail of the smaller ones seem to be carving out specialized yes. Niches where you can imagine now, at some point in the future, you sum up this long tail and it becomes larger than maybe one of the hyperscale cloud providers. Right. I don't think a lot of people predicted that. I think, I think people predicted the demise of VMware and frankly, a lot of people in the VMware ecosystem, just like they predicted the demise of the mainframe. Sure. The storage area network fill in the blank. I >>Mean, Jeff and I we've oh yeah. We've been on the, Jeff's been a little longer than I have, but we've been working together for 10 plus years on this. And we've, we've heard that many times. Yeah. Yeah. Our, our ecosystem has grown over the years. We've seen some consolidation, some M and a activity, but we're, we're not even actively recruiting partners and it's growing, we're focused on helping our partners gain more, share internally, gain, more share at wallet, but we're still getting organic growth in the program. Really. So it, it shows, I think that there is value in what we can offer them as a platform to build a cloud on. >>Yeah. What's been interesting is there's there's growth and there's some transition as well. Right? So there's been traditional cloud providers. Who've built a cloud in their data center, some sovereign, some not. And then there's other partners that are adopting VCP P because of our SA. So we've either converted some technology from product into SA or we've built net new SA or we've acquired companies that have been SA only. And now we have a bigger portfolio that service providers, cloud providers, managed service providers are all interested in. So you get resellers channel partners. Who've historically been doing ELAs and reselling to end customers. They're transitioning their business into doing recurring revenue and the only game in town where you really wanna do recurring revenues, VCP P. So our ecosystem is both growing because our cloud providers with their data center are doing more with our customers. And then we're adding more managed service providers because of our SA portfolio. And that, that, that combo, that one, two punch is creating a much bigger VCP P ecosystem overall. >>Yeah. >>Impressive. >>Do you think we have a better idea of what sovereign cloud means? Yes. I think we do. >>It's not Royal. >>It's all about royalty, >>All royalty. What are some of the things Jeff, as we look on the horizon, obviously seven to 10,000 people here at, at VMwares where people really excited to be back. They want to hear it from VMware. They wanna hear from its partner ecosystem, the community. What are some of the things that you think are on the horizon where sovereign cloud is concerned that are really opportunities yeah. For businesses to get it right. >>Yeah. We're in the early days of this, I think there's still a whole bunch of rules, regulatory laws that have not been defined yet. So I think there's gonna be some more learning. There's gonna be some top down guidance like Gaia X in Europe. That's the way that they're defining who gets access and control over what data and what's in. And what's out of that. So we're gonna get more of these Gaia X type things happening around the world, and they're all gonna be slightly different. Everyone's gonna have to understand what they are, how to interpret and then build something around them. So we need to stay on top of that, myself and Jay, to make sure that we've got the right cloud providers in the right space to capitalize on that, build out the sovereign cloud program over time and make sure that what they're building to support aligns with these different requirements that are out there across different countries. So it's an evolving landscape. That's >>Yeah. And one of the things too, we're also doing from a product perspective to better enable partners to, to address these sovereign cloud workloads is where we have, we have gaps maybe in our portfolio is we're partner partnering with some of our ISVs, like a, Konic like a Forex vem. So we can give our partners object storage or ransomware protection to add on to their sovereign cloud service, all accessible through our cloud director consult. So we're, we're enhancing the program that way. And to Jeff's point earlier, we've got 20 partners today. We're hoping to double that by the end of our fiscal year and, and just take a very methodical approach to growth of the program. >>Sounds great guys, early innings though. Thank you so much for joining Dave and me talking about what software and cloud is describing it to us, and also talking about the difference between that data residency and all the, all of the challenges and the, in the landscape that customers are facing. They can go turn to VMware and its ecosystem for that help. We appreciate your insights and your time. Guys. Thank >>You >>For >>Having us. Our >>Pleasure. Appreciate it >>For our guests and Dave Nicholson. I'm Lisa Martin. You've been watching the cube. This is the end of day, two coverage of VMware Explorer, 2022. Have a great rest of your day. We'll see you tomorrow.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's day one coverage of HPE discover 22 live from the Venetian in Las Vegas. I got a power panel here, Lisa Martin, with Dave Valante, John furrier, Holger Mueller also joins us. We are gonna wrap this, like you've never seen a rap before guys. Lot of momentum today, lot, lot of excitement, about 8,000 or so customers, partners, HPE leaders here. Holger. Let's go ahead and start with you. What are some of the things that you heard felt saw observed today on day one? >>Yeah, it's great to be back in person. Right? 8,000 people events are rare. Uh, I'm not sure. Have you been to more than 8,000? <laugh> yeah, yeah. Okay. This year, this year. I mean, historically, yes, but, um, >>Snowflake was 10. Yeah. >>So, oh, wow. Okay. So 8,000 was my, >>Cisco was, they said 15, >>But is my, my 8,000, my record, I let us down with 7,000 kind of like, but it's in the Florida swarm. It's not nicely. Like, and there's >>Usually what SFI, there's usually >>20, 20, 30, 40, 50. I remember 50 in the nineties. Right. That was a different time. But yeah. Interesting. Yeah. Interesting what people do and it depends how much time there is to come. Right. And know that it happens. Right. But yeah, no, I think it's interesting. We, we had a good two analyst track today. Um, interesting. Like HPE is kind of like back not being your grandfather's HPE to a certain point. One of the key stats. I know Dave always for the stats, right. Is what I found really interesting that over two third of GreenLake revenue is software and services. Now a love to know how much of that services, how much of that software. But I mean, I, I, I, provocate some, one to ones, the HP executives saying, Hey, you're a hardware company. Right. And they didn't even come back. Right. But Antonio said, no, two thirds is, uh, software and services. Right. That's interesting. They passed the one exabyte, uh, being managed, uh, as a, as a hallmark. Right. I was surprised only 120,000 users if I had to remember the number. Right, right. So that doesn't seem a terrible high amount of number of users. Right. So, but that's, that's, that's promising. >>So what software is in there, cuz it's gotta be mostly services. >>Right? Well it's the 70 plus cloud services, right. That everybody's talking about where the added eight of them shockingly back up and recovery, I thought that was done at launch. Right. >>Still who >>Keep recycling storage and you back. But now it's real. Yeah. >>But the company who knows the enterprise, right. HPE, what I've been doing before with no backup and recovery GreenLake. So that was kind of like, okay, we really want to do this now and nearly, and then say like, oh, by the way, we've been doing this all the time. Yeah. >>Oh, what's your take on the installed base of HP. We had that conversation, the, uh, kickoff or on who's their target, what's the target audience environment look like. It certainly is changing. Right? If it's software and services, GreenLake is resonating. Yeah. Um, ecosystems responding. What's their customers cuz managed services are up too Kubernetes, all the managed services what's what's it like what's their it transformation base look like >>Much of it is of course install base, right? The trusted 20, 30 plus year old HP customer. Who's keeping doing stuff of HP. Right. And call it GreenLake. They've been for so many name changes. It doesn't really matter. And it's kind of like nice that you get the consume pain only what you consume. Right. I get the cloud broad to me then the general markets, of course, people who still need to run stuff on premises. Right. And there's three reasons of doing this performance, right. Because we know the speed of light is relative. If you're in the Southern hemisphere and even your email servers in Northern hemisphere, it takes a moment for your email to arrive. It's a very different user experience. Um, local legislation for data, residency privacy. And then, I mean Charles Phillips who we all know, right. Former president of uh, info nicely always said, Hey, if the CIOs over 50, I don't have to sell qu. Right. So there is not invented. I'm not gonna do cloud here. And now I've kind of like clouded with something like HP GreenLake. That's the customers. And then of course procurement is a big friend, right? Yeah. Because when you do hardware refresh, right. You have to have two or three competitors who are the two or three competitors left. Right. There's Dell. Yeah. And then maybe Lenovo. Right? So, so like a >>Little bit channels, the strength, the procurement physicians of strength, of course install base question. Do you think they have a Microsoft opportunity where, what 365 was Microsoft had office before 365, but they brought in the cloud and then everything changed. Does HP have that same opportunity with kind of the GreenLake, you know, model with their existing stuff. >>It has a GreenLake opportunity, but there's not much software left. It's a very different situation like Microsoft. Right? So, uh, which green, which HP could bring along to say, now run it with us better in the cloud because they've been selling much of it. Most of it, of their software portfolio, which they bought as an HP in the past. Right. So I don't see that happening so much, but GreenLake as a platform itself course interesting because enterprise need a modern container based platform. >>I want, I want to double click on this a little bit because the way I see it is HP is going to its installed base. I think you guys are right on say, this is how we're doing business now. Yeah. You know, come on along. But my sense is, some customers don't want to do the consumption model. There are actually some customers that say, Hey, of course I got, I don't have a cash port problem. I wanna pay for it up front and leave me alone. >>I've been doing this since 50 years. Nice. As I changed it, now <laugh> two know >>Money's wants to do it. And I don't wanna rent because rental's more expensive and blah, blah, blah. So do you see that in the customer base that, that some are pushing back? >>Of course, look, I have a German accent, right? So I go there regularly and uh, the Germans are like worried about doing anything in the cloud. And if you go to a board in Germany and say, Hey, we can pay our usual hardware, refresh, CapEx as usual, or should we bug consumption? And they might know what we are running. <laugh> so not whole, no offense against the Germans out. The German parts are there, but many of them will say, Hey, so this is change with COVID. Right. Which is super interesting. Right? So the, the traditional boards non-technical have been hearing about this cloud variable cost OPEX to CapEx and all of a sudden there's so much CapEx, right. Office buildings, which are not being used truck fleets. So there's a whole new sensitivity by traditional non-technical boards towards CapEx, which now the light bulb went on and say, oh, that's the cloud thing about also. So we have to find a way to get our cost structure, to ramp up and ramp down as our business might be ramping up through COVID through now inflation fears, recession, fears, and so on. >>So, okay. HP's, HP's made the statement that anything you can do in the cloud you can do in GreenLake. Yes. And I've said you can't run on snowflake. You can't run Mongo Atlas, you can't run data bricks, but that's okay. That's fine. Let's be, I think they're talking about, there's >>A short list of things. I think they're talking about the, their >>Stuff, their, >>The operating experience. So we've got single sign on through a URL, right. Uh, you've got, you know, some level of consistency in terms of policy. It's unclear exactly what that is. You've got storage backup. Dr. What, some other services, seven other services. If you had to sort of take your best guess as to where HP is now and peg it toward where Amazon was in which year? >>20 14, 20 14. >>Yeah. Where they had their first conference or the second we invent here with 3000 people and they were thinking, Hey, we're big. Yeah. >>Yeah. And I think GreenLake is the building blocks. So they quite that's the >>Building. Right? I mean similar. >>Okay. Well, I mean they had E C, Q and S3 and SQS, right. That was the core. And then the rest of those services were, I mean, base stock was one of that first came in behind and >>In fairness, the industry has advanced since then, Kubernetes is further along. And so HPE can take advantage of that. But in terms of just the basic platform, I, I would agree. I think it's >>Well, I mean, I think, I mean the software, question's a big one. I wanna bring up because the question is, is that software is getting the world. Hardware is really software scales, everything, data, the edge story. I love their story. I think HP story is wonderful Aruba, you know, hybrid cloud, good story, edge edge. But if you look under the covers, it's weak, right? It's like, it's not software. They don't have enough software juice, but the ecosystem opportunity to me is where you plug and play. So HP knows that game. But if you look historically over the past 25 years, HP now HPE, they understand plug and play interoperability. So the question is, can they thread the needle >>Right. >>Between filling the gaps on the software? Yeah. With partners, >>Can they get the partners? Right. And which have been long, long time. Right. For a long time, HP has been the number one platform under ICP, right? Same thing. You get certified for running this. Right. I know from my own history, uh, I joined Oracle last century and the big thing was, let's get your eBusiness suite certified on HP. Right? Like as if somebody would buy H Oracle work for them, right. This 20 years ago, server >>The original exit data was HP. Oracle. >>Exactly. Exactly. So there's this thinking that's there. But I think the key thing is we know that all modern forget about the hardware form in the platforms, right? All modern software has to move to containers and snowflake runs in containers. You mentioned that, right? Yeah. If customers force snowflake and HPE to the table, right, there will be a way to make it work. Right. And which will help HPE to be the partner open part will bring the software. >>I, I think it's, I think that's an opportunity because that changes the game and agility and speed. If HP plays their differentiation, right. Which we asked on their opening segment, what's their differentiation. They got size scale channel, >>What to the enterprise. And then the big benefit is this workload portability thing. Right? You understand what is run in the public cloud? I need to run it local. For whatever reason, performance, local residency of data. I can move that. There that's the big benefit to the ISVs, the sales vendors as well. >>But they have to have a stronger data platform story in my that's right. Opinion. I mean, you can run Oracle and HPE, but there's no reason they shouldn't be able to do a deal with, with snowflake. I mean, we saw it with Dell. Yep. We saw it with, with, with pure and I, if our HPE I'd be saying, Hey, because the way the snowflake deal worked, you probably know this is your reading data into the cloud. The compute actually occurs in the cloud viral HB going snowflake saying we can separate compute and storage. Right. And we have GreenLake. We have on demand. Why don't we run the compute on-prem and make it a full class, first class citizen, right. For all of our customers data. And that would be really innovative. And I think Mongo would be another, they've got OnPrem. >>And the question is, how many, how many snowflake customers are telling snowflake? Can I run you on premise? And how much defo open years will they hear from that? Right? This is >>Why would they deal Dell? That >>Deal though, with that, they did a deal. >>I think they did that deal because the customer came to them and said, you don't exactly that deal. We're gonna spend the >>Snowflake >>Customers think crazy things happen, right? Even, even put an Oracle database in a Microsoft Azure data center, right. Would off who, what as >>Possible snowflake, >>Oracle. So on, Aw, the >>Snow, the snowflakes in the world have to make a decision. Dave on, is it all snowflake all the time? Because what the reality is, and I think, again, this comes back down to the, the track that HP could go up or down is gonna be about software. Open source is now the software industry. There's no such thing as proprietary software, in my opinion, relatively speaking, cloud scale and integrated, integrated integration software is proprietary. The workflows are proprietary. So if they can get that right with the partners, I would focus on that. I think they can tap open source, look at Amazon with open source. They sucked it up and they integrated it in. No, no. So integration is the deal, not >>Software first, but Snowflake's made the call. You were there, Lisa. They basically saying it's we have, you have to be in snowflake in order to get the governance and the scalability, all that other wonderful stuff. Oh, but we we'll do Apache iceberg. We'll we'll open it up. We'll do Python. Yeah. >>But you can't do it data clean room unless you are in snowflake. Exactly. Snowflake on snowflake. >>Exactly. >>But got it. Isn't that? What you heard from AWS all the time till they came out outposts, right? I mean, snowflake is a market leader for what they're doing. Right. So that they want to change their platform. I mean, kudos to them. They don't need to change the platform. They will be the last to change their platform to a ne to anything on premises. Right. But I think the trend already shows that it's going that way. >>Well, if you look at outpost is an signal, Dave, the success of outpost launched what four years ago, they announced it. >>What >>EKS is beating, what outpost is doing. Outpost is there. There's not a lot of buzz and talk to the insiders and the open source community, uh, EKS and containers. To your point mm-hmm <affirmative> is moving faster on, I won't say commodity hardware, but like could be white box or HP, Dell, whatever it's gonna be that scale differentiation and the edge story is, is a good one. And I think with what we're seeing in the market now it's the industrial edge. The back office was gen one cloud back office data center. Now it's hybrid. The focus will be industrial edge machine learning and AI, and they have it here. And there's some, some early conversations with, uh, I heard it from, uh, this morning, you guys interviewed, uh, uh, John Schultz, right? With the world economic 4k birth Butterfield. She was amazing. And then you had Justin bring up a Hoar, bring up quantum. Yes. That is a differentiator. >>HP. >>Yes. Yeah. You, they have the computing shops. They had the R and D can they bring it to the table >>As, as HPC, right. To what they Schultz for of uh, the frontier system. Right. So very impressed. >>So the ecosystem is the key for them is because that's how they're gonna fill the gaps. They can't, they can't only, >>They could, they could high HPC edge piece. I wouldn't count 'em out of that game yet. If you co-locate a box, I'll use the word box, particularly at a telco tower. That's a data center. Yep. Right. If done properly. Yep. So, you know, what outpost was supposed to do actually is a hybrid opportunity. Aruba >>Gives them a unique, >>But the key thing is right. It's a yin and yang, right? It's the ecosystem it's partners to bring those software workload. Absolutely. Right. But HPE has to keep the platform attractive enough. Right. And the key thing there is that you have this workload capability thing that you can bring things, which you've built yourself. I mean, look at the telcos right. Network function, visualization, thousands of man, years into these projects. Right. So if I can't bring it to your edge box, no, I'm not trying to get to your Xbox. Right. >>Hold I gotta ask you since in the Dave too, since you guys both here and Lisa, you know, I said on the opening, they have serious customers and those customers have serious problems, cyber security, ransomware. So yeah. I teach transformation now. Industrial transformation machine learning, check, check, check. Oh, sounds good. But at the end of the day, their customers have some serious problems. Right? Cyber, this is, this is high stakes poker. Yeah. What do you think HP's position for in the security? You mentioned containers, you got all this stuff, you got open source, supply chain, you have to left supply chain issues. What is their position with security? Cuz that's the big one. >>I, I think they have to have a mature attitude that customers expect from HPE. Right? I don't have to educate HP on security. So they have to have the partner offerings again. We're back at the ecosystem to have what probably you have. So bring your own security apart from what they have to have out of the box to do business with them. This is why the shocker this morning was back up in recovery coming. <laugh> it's kind like important for that. Right? Well >>That's, that's, that's more ransomware and the >>More skeleton skeletons in the closet there, which customers should check of course. But I think the expectations HP understands that and brings it along either from partner or natively. >>I, I think it's, I think it's services. I think point next is the point of integration for their security. That's why two thirds is software and services. A lot of that is services, right? You know, you need security, we'll help you get there. We people trust HP >>Here, but we have nothing against point next or any professional service. They're all hardworking. But if I will have to rely on humans for my cyber security strategy on a daily level, I'm getting gray hair and I little gray hair >>Red. Okay. I that's, >>But >>I think, but I do think that's the camera strategy. I mean, I'm sure there's a lot of that stuff that's beginning to be designed in, but I, my guess is a lot of it is services. >>Well, you got the Aruba. Part of the booth was packed. Aruba's there. You mentioned that earlier. Is that good enough? Because the word zero trust is kicked around a lot. On one hand, on the other hand, other conversations, it's all about trust. So supply chain and software is trusting trust, trust and verified. So you got this whole mentality of perimeter gone mentality. It's zero trust. And if you've got software trust, interesting thoughts there, how do you reconcile zero trust? And then I need trust. What's what's you? What are you seeing older on that? Because I ask people all the time, they're like, uh, I'm zero trust or is it trust? >>Yeah. The middle ground. Right? Trusted. The meantime people are man manipulating what's happening in your runtime containers. Right? So, uh, drift control is a new password there that you check what's in your runtime containers, which supposedly impenetrable, but people finding ways to hack them. So we'll see this cat and mouse game going on all the time. Yeah. Yeah. There's always gonna be the need for being in a secure, good environment from that perspective. Absolutely. But the key is edge has to be more than Aruba, right? If yeah. HV goes away and says, oh yeah, we can manage your edge with our Aruba devices. That's not enough. It's the virtual probability. And you said the important thing before it's about the data, right? Because the dirty secret of containers is yeah, I move the code, but what enterprise code works without data, right? You can't say as enterprise, okay, we're done for the day check tomorrow. We didn't persist your data, auditor customer. We don't have your data anymore. So filling a way to transport the data. And there just one last thought, right? They have a super interesting asset. They want break lands for the venerable map R right. Which wrote their own storage drivers and gives you the chance to potentially do something in that area, which I'm personally excited about. But we'll see what happens. >>I mean, I think the holy grail is can I, can I put my data into a cloud who's ever, you know, call it a super cloud and can I, is it secure? Is it governed? Can I share it and be confident that it's discoverable and that the, the person I give it to has the right to use it. Yeah. And, and it's the correct data. There's not like a zillion copies running. That's the holy grail. And I, I think the answer today is no, you can, you can do that maybe inside of AWS or maybe inside of Azure, look maybe certainly inside of snowflake, can you do that inside a GreenLake? Well, you probably can inside a GreenLake, but then when you put it into the cloud, is it cross cloud? Is it really out to the edge? And that's where it starts to break down, but that's where the work is to be done. That's >>The one Exide is in there already. Right. So men being men. Yeah. >>But okay. But it it's in there. Yeah. Okay. What do you do with it? Can you share that data? What can you actually automate governance? Right? Uh, is that data discoverable? Are there multiple copies of that data? What's the, you know, master copy. Here's >>A question. You guys, here's a question for you guys analyst, what do you think the psychology is of the CIO or CSO when HP comes into town with GreenLake, uh, and they say, what's your relationship with the hyperscalers? Cause I'm a CIO. I got my environment. I might be CapEx centric or Hey, I'm open model. Open-minded to an operating model. Every one of these enterprises has a cloud relationship. Yeah. Yeah. What's the dynamic. What do you think the psychology is of the CIO when they're rationalizing their, their trajectory, their architecture, cloud, native scale integration with HPE GreenLake or >>HP service. I think she or he hears defensiveness from HPE. I think she hears HPE or he hears HPE coming in and saying, you don't need to go to the cloud. You know, you could keep it right here. I, I don't think that's the right posture. I think it should be. We are your cloud. And we can manage whether it's OnPrem hybrid in AWS, Azure, Google, across those clouds. And we have an edge story that should be the vision that they put forth. That's the super cloud vision, but I don't hear it >>From these guys. What do you think psycho, do you agree with that? >>I'm totally to make, sorry to be boring, but I totally agree with, uh, Dave on that. Right? So the, the, the multi-cloud capability from a trusted large company has worked for anybody up and down the stack. Right? You can look historically for, uh, past layers with cloud Foundry, right? It's history vulnerable. You can look for DevOps of Hashi coop. You can look for database with MongoDB right now. So if HPE provides that data access, right, with all the problems of data gravity and egres cost and the workability, they will be doing really, really well, but we need to hear it more, right. We didn't hear much software today in the keynote. Right. >>Do they have a competitive offering vis-a-vis or Azure? >>The question is, will it be an HPE offering or will, or the software platform, one of the offerings and you as customer can plug and play, right. Will software be a differentiator for HP, right. And will be close, proprietary to the point to again, be open enough for it, or will they get that R and D format that, or will they just say, okay, ES MES here on the side, your choice, and you can use OpenShift or whatever, we don't matter. That's >>The, that's the key question. That's the key question. Is it because it is a competitive strategy? Is it highly differentiated? Oracle is a highly differentiated strategy, right? Is Dell highly differentiated? Eh, Dell differentiates based on its breadth. What? >>Right. Well, let's try for the control plane too. Dell wants to be an, >>Their, their vision is differentiated. Okay. But their execution today is not >>High. All right. Let me throw, let me throw this out at you then. I'm I'm, I'm sorry. I'm I'm HPE. I wanna be the glue layer. Is that, does that fly? >>What >>Do you mean? The group glue layer? I'll I wanna be, you can do Amazon, but I wanna be the glue layer between the clouds and our GreenLake will. >>What's the, what's the incremental value that, that glue provides, >>Provides comfort and reliability and control for the single pane of glass for AWS >>And comes back to the data. In my opinion. Yeah. >>There, there there's glue levels on the data level. Yeah. And there's glue levels on API level. Right. And there's different vendors in the different spaces. Right. Um, I think HPE will want to play on the data side. We heard lots of data stuff. We >>Hear that, >>But we have to see it. Exactly. >>Yeah. But it's, it's lacking today. And so, Hey, you know, you guys know better than I APIs can be fragile and they can be, there's a lot of diversity in terms of the quality of APIs and the documentation, how they work, how mature they are, what, how, what kind of performance they can provide and recoverability. And so just saying, oh wow. We are living the API economy. You know, the it's gonna take time to brew, chime in here. Hi. >><laugh> oh, so guys, you've all been covering HPE for a long time. You know, when Antonio stood up on stage three years ago and said by 2022, and here we are, we're gonna be delivering everything as a service. He's saying we've, we've done it, but, and we're a new company. Do you guys agree with that? >>Definitely. >>I, yes. Yes. With the caveat, I think, yes. The COVID pandemic slowed them down a lot because, um, that gave a tailwind to the hyperscalers, um, because of the, the force of massive O under forecasting working at home. I mean, everyone I talked to was like, no one forecasted a hundred percent work at home, the, um, the CapEx investments. So I think that was an opportunity that they'd be much farther along if there's no COVID people >>Thought it wasn't impossible. Yeah. But so we had the old work from home thing right. Where people trying to get people fired at IBM and Yahoo. Right. So I would've this question covering the HR side and my other hat on. Right. And I would ask CHS let's assume, because I didn't know about COVID shame on me. Right. I said, big California, earthquake breaks. Right. Nobody gets hurt, but all the buildings have to be retrofitted and checked for seism logic down. So everybody's working from home, ask CHS, what kind of productivity gap hit would you get by forcing everybody working from home with the office unsafe? So one, one gentleman, I won't know him, his name, he said 20% and the other one's going ha you're smoking. It's 40 50%. We need to be in the office. We need to meet it first night. And now we went for this exercise. Luckily not with the California. Right. Well, through the price of COVID and we've seen what it can do to, to productivity well, >>The productivity, but also the impact. So like with all the, um, stories we've done over two years, the people that want came out ahead were the ones that had good cloud action. They were already in the cloud. So I, I think they're definitely in different company in the sense of they, I give 'em a pass. I think they're definitely a new company and I'm not gonna judge 'em on. I think they're doing great. But I think pandemic definitely slowed 'em down that about >>It. So I have a different take on this. I think. So we've go back a little history. I mean, you' said this, I steal your line. Meg Whitman took one for the Silicon valley team. Right. She came in. I don't think she ever was excited that I, that you said, you said that, and I think you wrote >>Up, get tape on that one. She >>Had to figure out how do I deal with this mess? I have EDS. I got PC. >>She never should have spun off the PC, but >>Okay. But >>Me, >>Yeah, you can, you certainly could listen. Maybe, maybe Gerstner never should have gone all in on services and IBM would dominate something other than mainframes. They had think pads even for a while, but, but, but so she had that mess to deal with. She dealt with it and however, they dealt with it, Antonio came in, he, he, and he said, all right, we're gonna focus the company. And we're gonna focus the mission on not the machine. Remember those yeah. Presentations, but you just make your eyes glaze over. We're going all in on Azure service >>And edge. He was all on. >>We're gonna build our own cloud. We acquired Aruba. He made some acquisitions in HPC to help differentiate. Yep. And they are definitely a much more focused company now. And unfortunately I wish Antonio would CEO in 2015, cuz that's really when this should have started. >>Yeah. And then, and if you remember back then, Dave, we were interviewing Docker with DevOps teams. They had composability, they were on hybrid really early. I think they might have even coined the term hybrid before VMware tri-state credit for it. But they were first on hybrid. They had DevOps, they had infrastructure risk code. >>HPE had an HP had an awesome cloud team. Yeah. But, and then, and then they tried to go public cloud. Yeah. You know, and then, you know, just made them, I mean, it was just a mess. The focus >>Is there. I give them huge props. And I think, I think the GreenLake to me is exciting here because it's much better than it was two years ago. When, when we talked to, when we started, it's >>Starting to get real. >>It's, it's a real thing. And I think the, the tell will be partners. If they make that right, can pull their different >>Ecosystem, >>Their scale and their customers and fill the software gas with partners mm-hmm <affirmative> and then create that integration opportunity. It's gonna be a home run if they don't do that, they're gonna miss the operating, >>But they have to have their own to your point. They have to have their own software innovation. >>They have to good infrastructure ways to build applications. I don't wanna build with somebody else. I don't wanna take a Microsoft stack on open source stack. I'm not sure if it's gonna work with HP. So they have to have an app dev answer. I absolutely agree with that. And the, the big thing for the partners is, which is a good thing, right? Yep. HPE will not move into applications. Right? You don't have to have the fear of where Microsoft is with their vocal large. Right. If AWS kind of like comes up with APIs and manufacturing, right. Google the same thing with their vertical push. Right. So HPE will not have the CapEx, but >>Application, >>As I SV making them, the partner, the bonus of being able to on premise is an attractive >>Part. That's a great point. >>Hold. So that's an inflection point for next 12 months to watch what we see absolutely running on GreenLake. >>Yeah. And I think one of the things that came out of the, the last couple events this past year, and I'll bring this up, we'll table it and we'll watch it. And it's early in this, I think this is like even, not even the first inning, the machine learning AI impact to the industrial piece. I think we're gonna see a, a brand new era of accelerated digital transformation on the industrial physical world, back office, cloud data center, accounting, all the stuff. That's applications, the app, the real world from space to like robotics. I think that HP edge opportunity is gonna be visible and different. >>So guys, Antonio Neri is on tomorrow. This is only day one. If you can imagine this power panel on day one, can you imagine tomorrow? What is your last question for each of you? What is your, what, what question would you want to ask him tomorrow? Hold start with you. >>How is HPE winning in the long run? Because we know their on premise market will shrink, right? And they can out execute Dell. They can out execute Lenovo. They can out Cisco and get a bigger share of the shrinking market. But that's the long term strategy, right? So why should I buy HPE stock now and have a good return put in the, in the safe and forget about it and have a great return 20 years from now? What's the really long term strategy might be unfair because they, they ran in survival mode to a certain point out of the mass post equipment situation. But what is really the long term strategy? Is it more on the hardware side? Is it gonna go on the HPE, the frontier side? It's gonna be a DNA question, which I would ask Antonio. >>John, >>I would ask him what relative to the macro conditions relative to their customer base, I'd say, cuz the customers are the scoreboard. Can they create a value proposition with their, I use the Microsoft 365 example how they kind of went to the cloud. So my question would be Antonio, what is your core value proposition to CIOs out there who want to transform and take a step function, increase for value with HPE? Tell me that story. I wanna hear. And I don't want to hear, oh, we got a portfolio and no, what value are you enabling your customers to do? >>What and what should that value be? >>I think it's gonna be what we were kind of riffing on, which is you have to provide either what their product market fit needs are, which is, are you solving a problem? Is it a pain point is a growth driver. Uh, and what's the, what's that tailwind. And it's obviously we know at cloud we know edge. The story is great, but what's the value proposition. But by going with HPE, you get X, Y, and Z. If they can explain that clearly with real, so qualitative and quantitative data it's home >>Run. He had a great line of the analyst summit today where somebody asking questions, I'm just listening to the customer. So be ready for this Steve jobs photo, listening to the customer. You can't build something great listening to the customer. You'll be good for the next quarter. The next exponential >>Say, what are the customers saying? <laugh> >>So I would make an observation. And my question would, so my observation would be cloud is growing collectively at 35%. It's, you know, it's approaching 200 billion with a big, big four. If you include Alibaba, IBM has actually said, Hey, we're gonna gr they've promised 6% growth. Uh, Cisco I think is at eight or 9% growth. Dow's growing in double digits. Antonio and HPE have promised three to 4% growth. So what do you have to do to actually accelerate growth? Because three to 4%, my view, not enough to answer Holger's question is why should I buy HPE stock? Well, >>If they have product, if they have customer and there's demand and traction to me, that's going to drive the growth numbers. And I think the weak side of the forecast means that they don't have that fit yet. >>Yeah. So what has to happen for them to get above five, 6% growth? >>That's what we're gonna analyze. I mean, I, I mean, I don't have an answer for that. I wish I had a better answer. I'd tell them <laugh> but I feel, it feels, it feels like, you know, HP has an opportunity to say here's the new HPE. Yeah. Okay. And this is what we stand for. And here's the one thing that we're going to do that consistently drives value for you, the customer. And that's gonna have to come into some, either architectural cloud shift or a data thing, or we are your store for blank. >>All of the above. >>I guess the other question is, would, would you know, he won't answer a rude question, would suspending things like dividends and stock buybacks and putting it into R and D. I would definitely, if you have confidence in the market and you know what to do, why wouldn't you just accelerate R and D and put the money there? IBM, since 2007, IBM spent is the last stat. And I'm looking go in 2007, IBM way, outspent, Google, and Amazon and R and D and, and CapEx two, by the way. Yep. Subsequent to that, they've spent, I believe it's the numbers close to 200 billion on stock buyback and dividends. They could have owned cloud. And so look at this business, the technology business by and large is driven by innovation. Yeah. And so how do you innovate if >>You have I'm buying, I'm buying HP because they're reliable high quality and they have the outcomes that I want. Oh, >>Buy their products and services. I'm not sure I'd buy the stock. Yeah. >>Yeah. But she has to answer ultimately, because a public company. Right. So >>Right. It's this job. Yeah. >>Never a dull moment with the three of you around <laugh> guys. Thank you so much for sharing your insights, your, an analysis from day one. I can't imagine what day two is gonna bring tomorrow. Debut and I are gonna be anchoring here. We've got a jam packed day, lots going on, hearing from the ecosystem from leadership. As we mentioned, Antonio is gonna be Tony >>Alma Russo. I'm dying. Dr. >>EDMA as well as on the CTO gonna be another action pack day. I'm excited for it, guys. Thanks so much for sharing your insights and for letting me join this power panel. >>Great. Great to be here. >>Power panel plus me. All right. For Holger, John and Dave, I'm Lisa, you're watching the cube our day one coverage of HPE discover wraps right now. Don't go anywhere, cuz we'll see you tomorrow for day two, live from Vegas, have a good night.

>>Hello, everybody. Welcome to Von 2022, the live version. Yes, we're finally back live. Last time we did Von was 2019 live. Of course we did two subsequent years, uh, virtual. My name is Dave Valante and we've got two days of wall to wall coverage of VEON. As usual Veeam has brought together a number of customers, but it's really doing something different this year. Like many, uh, companies that you see, they have a big hybrid event. It's close to 40,000 people online and that's sort of driving the actual program where the content is actually different for the, the, the virtual viewers versus the onsite onsite. There's the, the V I P event going on, they got the keynotes. VM is a company who's a ancy occurred during the, the VMware rise. They brought in a new way of doing data protection. They didn't use agents. They, they protected at the hypervisor level. >>That changed the way that people did things. They're now doing it again in cloud, in SAS, in containers and ransomware. And so we're gonna dig into that. My cohost is Dave Nicholson this week, and we've got a special guest Zs Carava who is the principal at ZK research. He's an extraordinary analyst Zs. Great to see you, David. Thanks for coming out. Absolutely good to see you Beon. Great to be here. Yeah, we've done. Von act, live things have changed so dramatically. Uh, I mean the focus ransomware, it's now a whole new Tam, uh, the adjacency to security data protection. It's just a Zs. It's a whole new ballgame, isn't it? >>Well, it is. And, and in fact, um, during the keynote, they, they mentioned that they've, they're now tied at number one in, for, you know, back of a recovery, which is, I think it's safe to say Veeam. Does that really well? >>I think from a that's tied with Dell. Yes. Right. They didn't, I don't think they met Dell as >>Keto. And, uh, but I, you know, they've been rising Dell, EMC's been falling. And so I think >>It's somebody said 10 points that Dell lost and sharing the I data. >>It's not a big surprise. I mean, they haven't really invested a whole lot, >>I think anyway, >>Anyways, but I think from a Veeam perspective, the question is now that they've kind of hit that number one spot or close to it, what do they do next? This company, they mentioned, I was talking the CTO yesterday. You mentioned they're holding X bite of customer data. That is a lot of data. Right. And so they, they do back recovery really well. They do it arguably better than anybody. And so how do they take that data and then move into other adjacent markets to go create, not just a back recovery company, but a true data management platform company that has relevancy in cyber and analytics and artificial intelligence and data warehousing. Right? All those other areas I think are, are really open territory for this company right now. >>You know, Dave, you were a CTO at, at EMC when you, when you saw a lot of the acquisitions that the company made, uh, you, you know, they really never had a singular focus on data protection. They had a big data protection business, but that's the differentiator with Veeam. That's all it does. And you see that shine through from a, from a CTO's perspective. How do you see this market changing, evolving? And what's your sense as to how Vema is doing here? >>I think a lot of it's being driven by kind of, uh, unfortunately evil genius, uh, out in the market space. Yeah. I know we're gonna be hearing a lot about ransomware, uh, a lot about some concepts that we didn't really talk about outside of maybe the defense industry, air gaping, logical air gaping, um, Zs, you mentioned, you know, this, this, this question of what do you do when you have so many petabytes of data under management exabytes now exabytes, I'm sorry. Yeah, I see there I'm I'm already falling behind. One thing you could do is you could encrypt it all and then ask for Bitcoin in exchange for access to that data. >>Yes. That is what happens a >>Lot of them. So we're, we're getting, we're getting so much of the evil genius stuff headed our way. You start, you start thinking in those ways, but yet to, to your point, uh, dedicated backup products, don't address the scale and scope and variety of threats, not just from operational, uh, uh, you know, mishaps, uh, but now from so many bad actors coming in from the outside, it it's a whole new world. >>See us as analysts. We get inundated with ransomware solutions. Everybody's talking about it across the spectrum. The thing that interested me about what's happening here at VEON is they're, they're sort of trotting out this study that they do Veeam does some serious research, you know, thousands of customers that got hit by ransomware that they dug into. And then a, a larger study of all companies, many of whom didn't realize or said they hadn't been hit by ransomware, but they're really trying to inject thought leadership into the equation. You saw some of that in the analyst session this morning, it's now public. Uh, so we could talk about it. What were your thoughts on that data? >>Yeah, that was, uh, really fascinating data cuz it shows the ransomware industry, the response to it is largely reactive, right? We wait to get breach. We wait to, to uh, to get held at ransom I suppose. And then we, a lot of companies paid out. In fact, I thought there's one hospital in Florida, they're buying lots and lots of Bitcoin simply to pay out ransomware attacks. They didn't even really argue with them. They just pay it out. And I think Veeam's trying to change that mentality a little bit. You know, if you have the right strategy in place to be more preventative, you can do that. You can protect your data and then restore it right when you want to. So you don't have to be in that big bucket of companies that frankly pay and actually don't get their data back. Right. >>And like a third, I think roughly >>It's shocking amount of companies that get hit by that. And for a lot of companies, that's the end of their business. >>You know, a lot of the recovery process is manual is again a technologist. You understand that that's not the ideal way to go. In fact, it's probably a, a way to fail. >>Well, recovery's always the problem when I was in corporate, it used to joke that we were the best at backup, terrible at recovery. Well, you know, that's not atypical. >>My Fred Fred Moore, who was the vice president of strategy at a company called storage tech storage technology, corpor of storage tech. He had a great, uh, saying, he said, backup is one thing. Recovery is everything. And he started, he said that 30 years ago, but, but orchestration and automating that orchestration is, is really vital. We saw in the study, a lot of organizations are using scripts and scripts are fragile here they break. Right? >>Yeah, no, absolutely. Absolutely. Um, unfortunately the idea of the red run book on the shelf is still with us. Uh, uh, you know, scripting does not equal automation necessarily in every case, there's still gonna be a lot of manual steps in the process. Um, but you know, what I hope we get to talk about during the next couple of days is, you know, some of the factors that go into this, we've got day zero exploits that have already been uncovered that are stockpiled, uh, and tucked away. And it's inevitable that they're gonna hit. Yeah. So whether it's a manual recovery process or some level of automation, um, if you don't have something that is air gapped and cut off from the rest of the world in a physical or logical way, you can't guarantee >>That the, the problem with manual processes and scripting is even if you can set it up today, the environment changes so fast, right? With shadow it and business units buying their own services and users storing things and you know, wherever, um, you, you can't keep up with scripts in manual. Automation must be the way and I've been, and I don't care what part of it. You work in, whether it's this area in networking, communications, whatever automation must be the way I think prior to the pandemic, I saw a lot of resistance from it pros in the area of mission. Since the pandemic, I've seen a lot of warming up to it because I think it pros, I just realized they can't do their job without it. So, so you >>Don't, you don't think that edge devices, uh, lend themselves to manual >>Recovery, no process. In fact, I think that's one of the things they didn't talk about. What's that is, is edge. Edge is gonna be huge. More, every retailer, I talk to oil and gas, company's been using it for a long time. I've, you know, manufacturing organizations are looking at edge as a way to put more data in more places to improve experiences. Cuz you're moving the data closer, but we're creating a world where the fragmentation of data, you think it's bad now just wait a couple of years until the edge is a little more, you know, uh, to life here. And I think you ain't see nothing yet. This is this world of data. Everywhere is truly becoming that. And the thing with edge is there's no one definition, edge, you got IOT edge cellular edge, campus edge, right? Um, you know, you look at hotels, they have their own edge. I talked to major league baseball, right? They have every, stadium's got its own edge server in it. So we're moving into a world. We're putting more data in more places it's more fragmented than ever. And we need better ways of managing Of securing that data. But then also being able to recover for when >>Things happen. I was having that Danny Allen, he used the term that we coined called super cloud. He used that in the analyst meeting today. And, and that's a metaphor for this new layer of cloud. That's developing to your point, whether it's on-prem in a hybrid across clouds, not just running on the cloud, but actually abstracting away the complexity of the underlying primitives and APIs. And then eventually to your point, going out to the edge, I don't know if anyone who has an aggressive edge strategy Veeam to its credit, you know, has gone well beyond just virtualization and gone to bare metal into cloud. They were the containers. There was first at SAS. They acquired Caston who was a partner of theirs and they tried to acquire them earlier, but there was some government things and you know, that whole thing that got cleaned up and now they've, they own Caston. And I think the edge is next. I mean, it's gotta be, there's gonna be so much data at the edge. I guess the question is where is it today? How much of that is actually persisted? How much goes back to the cloud? I don't think people really have a good answer for that yet. >>No. In fact, a lot of edge services will be very ephemeral in nature. So it's not like with cloud where we'll take data and we'll store it there forever with the edge, we're gonna take data, we'll store it there for the time, point in time we need it. But I think one of the interesting things about Veeam is because they're decoupled from the airline hardware, they can run virtual machines and containers, porting Veeam to whatever platform you have next actually isn't all that difficult. Right? And so then if you need to be able to go back to a certain point in time, they can do that instantly. It's, it's a fascinating way to do backup. Are >>You you' point about it? I mean, you remember the signs up and down, you know, near the EMC facility, right outside of Southborough no hardware agenda that that was Jeremy Burton when he was running Verto of course they've got a little hardware agenda. So, but Veeam doesn't Veeam is, you know, they they're friendly with all the hardware players of pure play software, couple other stats on them. So they're a billion dollar company. They've now started to talk about their ARR growth. They grew, uh, 27% last year in, in, in annual recurring revenue, uh, 25%, uh, in the most recent quarter. And so they're in, in the vast majority of their business is subscription. I think they said, uh, 73% is now subscription based. So they really trans transitioned that business. The other thing about vem is they they've come up with a licensing model that's very friendly. >>Um, and they sort of removed that friction early on in the process. I remember talking to TIR about this. He said, we are gonna incent our partners and make it transparent to them, whether it's, you know, that when we shift from, you know, the, the, the, the crack of, of perpetual license to a subscription model, we're gonna make that transparent to partners. We'll take care of that. Essentially. They funded that transition. So that's worked very well. So they do stand out, I think from some of the larger companies at these big portfolios, although the big portfolio companies, you know, they get board level contacts and they can elbow their ways in your thoughts on that sort of selling dynamic. >>So navigating that transition to a subscription model is always fraught with danger. Everybody wants you to be there, but they want you to be there now. Mm-hmm <affirmative>, they don't like the transition that happens over 1824 months to get there. Um, >>As a private company, they're somewhat shielded from what they would've been if they were appli. Sure, >>Exactly. But, but that, but that bodes well from a, from a, a Veeam perspective. Um, the other interesting thing is that they sit where customers sit today in the real world, a hybrid world, not everything is in the cloud or a single cloud, uh, still a lot of on-prem things to take care of. And, >>And there will be for >>A long time exactly. Back to this idea. Yeah. There's a very long tail on that. So it's, it's, it's well enough to have a niche product that addresses a certain segment of the market, but to be able to go in and say all data everywhere, it doesn't matter where it lives. We have you covered. Um, that's a powerful message. And we were talking earlier. I think they, they stand a really good shot at taking market share, you know, on an ongoing basis. >>Yeah. The interesting thing about this market, Dave is they're, you know, although, you know, they're tied to number one with Dell now, they're, it's 12%, right? This reminds me of the security industry five, six years ago, where it's so fragmented. There's so many vendors, no one really stood out right. Then what happened in security? It's a little company called Palo Alto networks came around, they created a platform story. They moved into adjacent markets like SDWAN, they did a lot of smart acquisitions and they took off. I think vem is at that similar point where they've now, you know, that 12% number they've got some capital. Now they could go do some acquisitions that they want do. There's lots of adjacent markets as they talk about this company could be the Palo Alto of the data management market, if you know, and based on good execution. But there's certainly the opportunities there with all the data that they're holding. >>That's a really interesting point. I wanna stay that in a second. So there's obviously, there's, there's backup, there's recovery, there's data protection, there's ransomware protection, there's SAS data protection. And now all of a sudden you're seeing even a company like Rubrik is kind of repositioning as a security play. Yeah. Which I'm not sure that's the right move for a company that's really been focused on, on backup to really dive into that fragmented market. But it's clearly an adjacency and we heard Anan the new CEO today in the analyst segment, you know, we asked him, what's your kinda legacy gonna look like? And he said, I want to, I want to, defragment this market he's looking at. Yeah. He wants 25 to 45% of the market, which I think is really ambitious. I love that goal now to your point, agree, he, he sure. But that doubles yeah. >>From today or more, and he gets there to your point, possibly through acquisitions, they've made some really interesting tuck-ins with Castin. They certainly bought an AWS, uh, cloud play years ago. But my, my so, uh, Veeam was purchased by, uh, private equity inside capital inside capital in January of 2020, just before COVID for 5 billion. And at the time, then COVID hit right after you were like uhoh. And then of course the market took off so great acquisition by insight. But I think an IPO is in their future and that's, uh, Zs when they can start picking up some of these adjacent markets through every day. >>And I think one of the challenges for them is now that the Holden XAB bited data, they need to be able to tell customers things they, the customer doesn't know. Right. And that's where a lot of the work they're doing in artificial intelligence machine learning comes into play. Right. And, and nobody does that better than AWS, right? AWS is always looking at your data and telling you things you don't know, which makes you buy more. And so I think from a Veeam perspective, they need to now take all this, this huge asset they have and, and find a way to monetize it. And that's by revealing these key insights to customers that the customers don't even know they have. And >>They've got that monitor monitoring layer. Um, it's if you called it, Danny, didn't like to use the term, but he called it an AI. It's really machine learning that monitors. And then I think makes recommendations. I want to dig into that a little bit with it. >>Well, you can see the platform story starting to build here. Right. And >>Here's a really good point. Yeah. Because they really have been historically a point product company. This notion of super cloud is really a platform play. >>Right. And if you look in the software industry, look across any, any segment of the software industry, those companies that were niche that became big became platforms, Salesforce, SAP, Oracle. Right. And, and they find a way to allow others to build on their platform. You know, companies, they think like a Citrix, they never did that. Yeah. And they kind of taped, you know, petered out at a certain level of growth and had to, you know, change. They're still changing their business model, in fact. But I think that's Veeam's at that inflection point, right. They either build a platform story, enable others to do more on their platform or they stagnate >>HP software is another good example. They never were able to get that platform. And we're not able bunch of spoke with it, a non used to work there. Why is it so important Dave, to have a platform over a product? >>Well, cynical, Dave says, uh, you have a platform because it attracts investment and it makes you look cooler than maybe you really are. Um, but, uh, but really for longevity, you have, you, you, you have to be a platform. So what's >>The difference. How do you know when you have platform versus it? APIs? Is it, yeah. Brett, is it ecosystem? >>Some of it is. Some of it is semantics. Look at when, when I'm worried about my critical assets, my data, um, I think of a platform, a portfolio of point solutions for backing up edge data stuff. That's in the cloud stuff that exists in SAS. I see that holistically. And I think guys, you're doing enough. This is good. Don't, don't dilute your efforts. Just keep focusing on making sure that you can back up my data wherever it lives and we'll both win together. So whenever I hear a platform, I get a little bit, a little bit sketchy, >>Well platform, beats products, doesn't >>It? Yeah. To me, it's a last word. You said ecosystem. Yes. When you think of the big platform players, everybody B in the customer, uh, experience space builds to build for Salesforce. First, if you're a small security vendor, you build for Palo Alto first, right? Right. If you're in the database, you build for Oracle first and when you're that de facto platform, you create an ecosystem around you that you no longer have to fund and build yourself. It just becomes self-fulfilling. And that drives a level of stickiness that can't be replicated through product. >>Well, look at the ecosystem that, that these guys are forming. I mean, it's clear. Yeah. So are they becoming in your view >>Of platform? I think they are becoming a platform and I think that's one of the reasons they brought on and in, I think he's got some good experience doing that. You could argue that ring kind of became that. Right. The, when, you know, when he was ring central. >>Yeah. >>Yeah. And, uh, so I think some, some of his experiences and then moving into adjacencies, I think is really the reason they brought him in to lead this company to the next level. >>Excellent guys, thanks so much for setting up VEON 20, 22, 2 days of coverage on the cube. We're here at the area. It's a, it's a great venue. I >>Love the area. >>Yeah. It's nice. It's a nice intimate spot. A lot of customers here. Of course, there's gonna be a big Veeam party. They're famous for their parties, but, uh, we'll, we'll be here to cover it and, uh, keep it right there. We'll be back with the next segment. You're watching the cube VEON 20, 22 from Las Vegas.

>> Welcome back to the Seaport in Boston and this is theCUBE's coverage of Red Hat Summit 2022. I'm Dave Vellante with my co-host Paul Gillin. Rob Belson is here as the Developer Relations Lead at Verizon. Robbie great to see you. Thanks for coming on theCUBE. >> Thanks for having me. >> So Verizon and developer relations. Talk about your role there. Really interesting. >> Absolutely. If you think about our mobile edge computing portfolio in Verizon 5G Edge, suddenly the developer is a more important persona than ever for actually adopting the cloud itself and adopting the mobile edge. So the question then quickly became how do we go after developers and how do we tell stories that ultimately resonate with them? And so my role has been spearheading our developer relations and experience efforts, which is all about meeting developers in the channels where they actually are, building content that resonates with them. Building out architectures that showcase how do you actually use the technology in the wild? And then ultimately creating automation assets that make their lives easier in deploying to the mobile edge. >> So, you know, telcos get a bad rap, when you're thinking it's amazing what you guys do. You put out all this capital infrastructure, big outlays. You know, we use our phones to drop a call. People like, "Ah, freaking Verizon." But it's amazing what we can actually do too. You think about the pandemic, the shift that the telcos had to go through to landlines to support home, never missed a beat. And yet at the same time you're providing all this infrastructure for people to come over the top, the cost forbid is going down, right? Your cost are going up and yet now we're doing this big 5G buildup. So I feel like there's a renaissance about to occur in edge computing that the telcos are going to lead new forms of monetization new value that you're going to be able to add, new services, new applications. The future's got to be exciting for you guys and it's going to be developer-led, isn't it? >> Absolutely. I mean it's been such an exciting time to be a part of our mobile edge computing portfolio. If you think back to late 2019 we were really asking the question with the advent of high speed 5G mobile networks, how can you drive more immersive experiences from the cloud in a cloud native way without compromising on the tools you know and love? And that's ultimately what caused us to really work with the likes of AWS and others to think about what does a mobile edge computing portfolio look like? So we started with 5G Edge with AWS Wavelength. So taking the compute and storage services you know and love in AWS and bringing it to the edge of our 4G and 5G networks. But then we start to think, well, wait a minute. Why stop at public networks? Let's think about private networks. How can we bring the cloud and private networks together? So you turn back to late 2021 we announced Verizon 5G Edge with AWS Outposts but we didn't even stop there. We said, "Well, interest's cool, but what about network APIs? We've been talking about the ability and the programmability of the 5G network but what does that actually look like to the developers? And one great example is our Edge Discovery Service. So you think about the proliferation of the edge 17 Wavelength Zones today in the US. Well, what edge is the right edge? You think about maybe the airline industry if the closest exit might be behind you absolutely applies to service discovery. So we've built an API that helps answer that seemingly basic question but is the fundamental building block for everything to workload orchestration, workload distribution. A basic network building block has become so important to some of these new sources of revenue streams, as we mentioned, but also the ability to disintermediate that purpose built hardware. You think about the future of autonomous mobile robots either ground and aerial robotics. Well, you want to make those devices as cheap as possible but you don't want to compromise on performance. And that mobile edge layer is going to become so critical for that connectivity, but also the compute itself. >> So I just kind of gave my little narrative up front about telco, but that purpose built hardware that you're talking about is exceedingly reliable. I mean, it's hardened, it's fossilized and so now as you just disaggregate that and go to a more programmable infrastructure, how are you able to and what gives you confidence that you're going to be able to maintain that reliability that I joke about? Oh, but it's so reliable. The network has amazing reliability. How are you able to maintain that? Is that just the pace of technology is now caught up, I wonder if you can explain that? >> I think it's really cool as I see reliability and sort of geo distribution as inextricably linked. So in a world where to get that best in class latency you needed to go to one place and one place only. Well, now you're creating some form of single source of failure whether it's the power, whether it's the compute itself, whether it's the networking, but with a more geo distributed footprint, particularly in the mobile edge more choices for where to deliver that immersive experience you're naturally driving an increase in reliability. But again, infra alone it's not going to do the job. You need the network APIs. So it's the convergence of the cloud and network and infra and the automation behind it that's been incredibly powerful. And as a great example, the work we've been doing in hybrid MEC the ability to converge within one single architecture, the private network, the public network, the AWS Outposts, the AWS Wavelength all in one has been such a fantastic journey and Red Hat has been a really important part in that journey. >> From the perspective of the developer when they're building a full cloud to edge application, where does Verizon pick up? Where do they start working primarily with you versus with their cloud provider? >> Absolutely. And I think you touched on a really important point. I think when you often think about the edge it's thought of as an either, or. Is it the edge? Is it the cloud? Is it both? It's an and I can't emphasize that enough. What we've seen from the customers greenfield or otherwise it's about extending an application or services that were never intended to live at the edge, to the edge itself, to deliver a more performant experience. And for certain control plane operations, metadata, backend operations analytics that can absolutely stay in the cloud itself. And so our role is to be a trusted partner in some of our enterprise customers' journeys. Of course, they can lean on the cloud provider in select cases, but we're an absolutely critical mode of support as you think about what are those architectures? How do you integrate the network APIs? And through our developer relations efforts, we've put a major role in helping to shape what those patterns really look like in the wild. >> When they're developing for 5G I mean, the availability of 5G of particularly you know, the high bandwidth 5G is pretty spotty right now. Mostly urban areas. How should they be thinking in the future developing an application roll out two years from now about where 5G will be at that point? >> Absolutely. I think one of the most important things in this case is the interoperability of our edge computing portfolio with both 4G and 5G. Whenever somebody asks me about the performance of 5G they ask how fast? Or for edge computing. It's always about benchmark. It's not an absolute value. It's always about benchmarking the performance to that next best alternative. What were you going to get if you didn't have edge computing in your back pocket? And so along that line of thought having the option to go either through 4G or 5G, having a mobile edge computing portfolio that works for both modes of connectivity even CAN-AM IoT is incredibly powerful. >> So it sounds like 4G is going to be with us for quite a while still? >> And I think it's an important part of the architecture. >> Yeah. >> Robert, tell us about the developer that's building these applications. Where does that individual come from? What's their persona? >> Oh, boy I think there's a number of different personas and flavors. I've seen everything from the startup in the back of a garage working hard to try to figure out what could I do for a next generation media and entertainment experience but also large enterprises. And I think a great area where we saw this was our 5G Edge Computing Challenge that we hosted last year. Believe it or not 100 submissions from over 22 countries, all building on Verizon 5G Edge. It was so exciting to see because so many different use cases across public safety, healthcare, media and entertainment. And what we found was that education is so important. A lot of developers have great ideas but if you don't understand the fundamentals of the infrastructure you get bogged down in networking and setting up your environment. And that's why we think that developer education is so important. We want to make it easy and in fact, the 5G Edge portfolio was designed in such a way that we'll abstract the complexities of the network away so you can focus on building your application and that's such a central theme and focus for how we approach the development. >> So what kind of services are you exposing via APIs? >> Absolutely, so first and foremost, as you think about 5G Edge with say AWS Wavelength, the infra there are APIs that are exposed by AWS to launch your infra, to patch your infrastructure, to automate your infrastructure. Specifically that Verizon has developed that's our network APIs. And a great example is our Edge Discovery Service. So think of this as like a service registry you've launched an application in all 17 edge zones. You would take that information, you would send it via API to the Edge Discovery Service so that for any mobile client say, you wake up one morning in Boston, you can ask the API or query, "Hey, what's the closest edge zone?" DNS isn't going to be able to figure it out. You need knowledge of the actual topology of the mobile network itself. So the API will answer. Let's say you take a little road trip 1,000 miles south to say Miami, Florida you ask that question again. It could change. So that's the workflow and how you would use the network API today. >> How'd you get into this? You're an engineer it's obvious how'd you stumble into this role? >> Well, yeah, I have a background in networks and distributed systems so I always knew I wanted to stay in the cloud somewhere. And there was a really unique opportunity at Verizon as the portfolio was being developed to really think about what this developer community looked like. And we built this all from scratch. If you look at say our Verizon 5G Edge Blog we launched it just along the timing of the actual GA of Wavelength. You look at our developer newsletter also around the time of the launch of Wavelength. So we've done a lot in such a short period and it's all been sort of organic, interacting with developers, working backwards from the customer. And so it's been a fairly new, but incredibly exciting journey. >> How will your data, architecture, data flow what will that look like in the future? How will that be different than it is sort of historically? >> When I think about customer workloads real time data architecture is an incredibly difficult thing to do. When you overlay the edge, admittedly, it gets more complicated. More places that produce the data, more places that consume data. How do you reconcile all of these environments? Maintain consistency? This is absolutely something we've been working on with the ecosystem at large. We're not going to solve this alone. We've looked at architecture patterns that we think are successful. And some of the things that we found that we believe are pretty cool this idea of taking that embedded mobile database, virtualizing it to the edge, even making it multi-tenant. And then you're producing data to one single source and simplifying how you organize and share data because all of the data being produced to that one location will be relevant to that topology. So Boston, as an example, Boston data being produced to that edge zone will only service Boston clients. So having a geo distributed footprint really does help data architectures, but at the core of all of this database, architectures, you need a compute environment that actually makes sense. That's performant, that's reliable. That's easy to use that you understand how to manage and that the edge doesn't make it any more difficult to manage. >> So are you building that? >> That's exactly what we're doing. So here at Red Hat Summit we've had the unique opportunity to continue to collaborate with our partners at Red Hat to think about how you actually use OpenShift in the context of hybrid MEC. So what have done is we've used OpenShift as is to extend what already exists to some of these new edge zones without adding in an additional layer of complexity that was unmanageable. >> So you use OpenShift so you don't have to cobble this together on your own as a full development environment and that's the role really that OpenShift plays here? >> That's exactly right. And we presented pieces of this at our re:Invent this past year and what we basically did is we said the edge needs to be inextricably linked with the cloud. And you want to be able to manage it from some seamless central pane of glass and using that OpenShift console is a great way. So what we did is we wanted to show a really geo-distributed footprint in action. We started with a Wavelength zone in Boston, the region in Northern Virginia, an outpost in the Texas area. We cobbled it all together in one cluster. So you had a whole compute mesh separated by thousands of miles all within a single cluster, single pane of glass. We take that and are starting to expand on the complexity of these architectures to overlay the network APIs we mentioned, to overlay multi-region support. So when we say you can use all 17 zones at once you actually can. >> So you've been talking about Wavelength and Outposts which are AWS products, but Microsoft and Google both have their distributed architectures as well. Where do you stand with those? Will you support those? Are you working with them? >> That's a great question. We have made announcements with Microsoft and Google but today I focus a lot on the work we do with AWS Wavelength and Outposts and continuing to work backwards from the customer and ultimately meet their needs. >> Yeah I mean, you got to start with an environment that the developers know that obviously a great developer community, you know, you see it at re:Invent. What was the reaction at re:Invent when you showed this from a developer community? >> Absolutely. Developers are excited and I think the best part is we're not the only ones talking about Wavelength not even AWS are the only ones talking about Wavelength. And to me from a developer ecosystem perspective that's when you know it's working. When you're not the one telling the best stories when others are evangelizing the power of your technology on your behalf that's when the ecosystem's starting to pick up. >> Speaking of making a bet on Outposts you know, it's somewhat limited today. I'll say it it's limited today in terms of we think it supports RDS and there's a few storage players. Is it your expectation that Outposts is going to be this essentially the cloud environment on your premises is that? >> That's a great question. I see it more as we want to expand customer choice more than ever and ultimately let the developers and architects decide. That's why I'm so bullish on this idea of hybrid MEC. Let's provide all of the options the most complicated geo distributed hybrid deployment you can imagine and automate it, make it easy. That way if you want to take away components of this architecture all you're doing is simplifying something that's already automated and fairly simple to begin with. So start with the largest problem to solve and then provide customers choice for what exactly meets their requirements their SLAs, their footprint, their network and work backwards from the customer. >> Exciting times ahead. Rob, thanks so much for coming on theCUBE. It's great to have you. >> Appreciate it, thanks for your time. >> Good luck. All right, thank you for watching. Keep it right there. This is Dave Vellante for Paul Gillin. We're live at Red Hat Summit 2022 from the Seaport in Boston. We'll be right back.

(gentle music) >> High profile cyber attacks like the SolarWinds hack, the JBS meat and the Florida municipality breach, have heightened awareness of how exposed, critical infrastructure has become. Because the pandemic has shifted employees to remote modes of work, hackers now have a much easier target to fish for credentials and exploit less secure home networks. Take the recent Log4j vulnerability, that's yet another example, of how hackers can take advantage of weak links in the chain. Now data storage companies have an important role to play in fighting cyber crime. Ultimately, they provide the equivalent of a bank vault if you will, and are responsible for storing and protecting the data that cyber criminals are targeting to steal or encrypt, in an effort to hold companies hostage, in a ransomware attack. Now in an effort to help customers understand how to protect themselves from such vulnerabilities, and how one storage company is addressing these challenges, the Cube is hosting this special presentation InfiniGuard Cyber Resilience: New Cybercrime Solutions. And we're going to speak with Eric Herzog, who's the Chief Marketing Officer of Infinidat, and then we'll bring in Stan Wysocki who is the president of Mark III Systems who is either an expert in IT infrastructure and artificial intelligence. First, let me welcome Eric Herzog back to the Cube, hello, Eric. >> Great, Dave, thank you very much, always love talking to you and the Cube, about leading edge technology solutions for end users. >> Alright let's do it. So, first we want to address the transformation and big business progress of Infinidat. New CEO, he's injected new management, new head of marketing obviously, Phil Bullinger is really been focused on accelerating the company's original vision, and doing so, Eric, in the typically unconventional style of Infinidat, you just put out a press release, capping 2021, can you set the stage for us, and give us the business update? >> Sure, so of course we summarized our 2021 results. What a very, very strong year. What a very, very strong year. We increased our bookings over 40% year to year. Even in Q4, we increased our bookings over 68%. And over 25% of the fortune 50 use an Infinidat solution, either our InfiniBox, or InfiniBox SSA, all flash array, or our Infiniguard, which is the focus of the launch we're doing today, on February 9th. >> Yeah, so I always said that Infinidat is one of the best kept secrets in the storage business. So let's talk about that hard news, what you launched on February 9th, and why it's important. >> Well, what we've done is we've got a high end enterprise purpose-built backup appliance, the InfiniGuard. We made some substantial advances in that. The key is focused on cyber resilience with what we call our infinisafe technology. Infinisafe incorporates a number of subsets, of cyber resilience from immutable snapshots, to logical air gapping, to fenced isolated networks, to almost instantaneous recovery for your backup data sets. In addition, we also dramatically improved the performance of the backup and recovery, which means, for example, if a backup window was taking three hours, now the backup window on that primary backup dataset could take only an hour and a half, which of course, as we all know backup dramatically impacts the performance of your primary applications, your primary servers, and your primary storage. So we've done both the cyber resilience aspect and then, on modern data protection, making sure that the backup and recovery are faster, for a traditional backup workload. >> So tell us a little bit more about Infinisafe, and specifically, Eric I'm interested in how it's different from other solutions, don't make me a liar, I had said, you guys always kind of take nonconventional approaches so tell us, add a little color to Infinisafe and how is it really unique from competitors? >> Sure, well Infinisafe incorporates as I mentioned, several different aspects. First of all, the immutable snapshots. So immutable snapshots can not be deleted, they cannot be altered, you cannot accelerate the rate, you can set the rate of immutable stuff, do I want to do it once a day? Do I want to do it twice a day? And obviously if a hacker could get in, you could accelerate that. Our immutable snaps are physically separated from the management schema. So the inside of an Infiniguard, we have what we call a data dedupe appliance, and that data dedupe engine, it goes ahead and it applies data reduction technology, to that back up data set. But we've divorced the immutable snapshots from the management of what we now call a DDE. So the DDE has kind of access of giving you that gap, that logical gap between the management schema of a DDE, and of course the immutable snapshot. We also combine that with this air gap technology, you've got the immutability and the air gap, which is local in that instance, but we also can do it remotely. So we can replicate from one Infiniguard in data center A, to a different Infiniguard in data center B. You then can configure that backup data set with the same immutable snapshot, and the same length, one day, half a day, six hours, whatever you choose, and then of course it'll have that same capability. The third thing we've done is very unique. We have a fenced isolated network to perform forensics. So, if the Cube has a cyber or malware attack, you need to make sure that once you've cleaned it up, off the primary storage, the primary servers, that you recover, a known good data set. So we set up this isolated fence network in which to perform that forensic analysis, to give you the appropriate good recover point. However, unlike many of our competitors, we can do it with a single InfiniBox. Some of our competitors, right on their websites say, you need two of their purpose-built backup appliances, to do cyber resilience. Meaning, twice the CapEx and twice the OpEx, which we can do with a single Infiniguard solution. And then lastly is our near instantaneous recovery. As you know, we're recovering backup data sets. We can make between 15 and 30 minutes time, the backup data set fully accessible to the backup admin or the storage admin to use their Commvault, their Veeam, their Veritas, their IBM Spectrum Protect, or whatever their backup software is, to do recovery from the InfiniGuard box, back to the primary storage using of course the backup software that they created the original dataset with. That is very unique. When you look out in the industry and look at, whether it be purpose-built backup competitors, or whether you look at primary storage competitors, almost no one talks about the speed of their recovery, and the one or two that do, talk about recovering the data set. We recover the entire environment. We are ready to go, and the backup admin, if they were, for example, Commvault, Veeam or Veritas, they could immediately start the backup, as soon as we did our recovery, which again, takes between 15 and 30 minutes, independent of the data set size. That could be 50 terabytes, it could be a petabyte, it could be two petabytes. And even two petabytes of data can be available in 15 to 30 minutes. And then of course, the backup admin can restore from that backup dataset. Very powerful and very unique in those aspects. >> Whilst the reason why this is so important is like I said, it's like the bank vault, because hackers are going to go after that backup corpus that's where the gold is, that's where all the data is. So this all really sounds good. But there's more than Infinisafe in this launch. What else should we know? >> Well, the other thing we've done is dramatically improved the performance of the purpose-built backup plants at the core. So for example, the last time we publicly announced our numbers, we were at 74 terabytes an hour, now we're 180 terabytes an hour. So of course, as we all know, when you do a backup, it impacts the performance of the primary applications, the primary servers and the primary storage. So if that backup window was taking three hours, now that we've more than doubled the performance, you could be up to 50% better. So a three hour backup window, if that's what the dataset took to be backed up, now we can get that down to an hour and a half or even faster. So that of course minimizes the impact on primary storage, primary applications, and of course your primary storage, making it much, much more efficient, from a backup perspective, and of course less impact on the primary applications, the primary servers, and primary storage. >> So I've talked to a number of Infinidat customers, they're very loyal and kind of passionate. So I wonder if you could kind of put that perspective on this discussion. The impact that InfiniGuard, this announcement, that's going to have for your customers, paint a picture as to how it's going to change their business. >> Sure, so let me give you an example. One of our customers is a cloud service buyer, in North America, they focus only on healthcare. So here's a couple of key benefits that they got. First of all, they use our integration with two different backup vendors. They don't have one, they have two. So we're tightly integrated with our backup software partners. They got a 40% cost savings on CapEX, compared to the previous vendor that they had. And, they used to be able to do 30,000 backup per day, now they can do 90,000 backup a day. And by the way, that's all with the previous version of InfiniGuard, not the version we just announced on the 9th. One of our other customers, which is in AMEA and they happened to be an energy company, they were using purpose-built backup from the other vendor, and they had 14 of them, seven in data center one, and seven in data center two. With InfiniGuard, they've got one in data center one, and one in data center two. So 14 purpose-built backup appliances consolidated down into two. And on top of that, those purpose-built backup appliances from the other vendor actually had a couple recovery failures, where they were not able to recover the data. They've been installed for a year now, they've had zero recovers, zero recovery failures, whereas the previous vendor had some. And lastly, let's talk about a large global fortune financial services. So, one of the biggest in the industry, their cost savings from their previous vendor was 46%. In addition, when you look at their cyber resilience design, they were using one of those vendors that probably talks about needing two system products to do their cyber resiliency. They again were able to take those two systems out, and use one InfiniGuard solution. Again, reducing both their capital expenditure, two going to one. And then the operational expenditure, they only have to manage one InfiniGuard versus two of the other guys appliances. Those are just three examples all over the world. One in cloud service providing, one in the energy space, and one a global fortune 500 financial services company. Just some real world examples. And all those by the way, Dave, were before the enhancements of Infinisafe, and before the additional performance we've added in the launch of InfiniGuard on February 9th. >> So like I'm just kind of sketching out the business case, you know, put my CFO hat on. So you're lowering costs cause you're consolidating, so that means I need less hardware and software. But also there's probably labor costs associated with that. If I could do it faster with less resources, I got less stuff to manage. You're accelerating the backup time, so that frees up resources that I can apply elsewhere, recovery, you know, is really important. So I'm inferring faster recovery, all this lowers my risk, and then I can sort of calculate the probability of having data loss, and then what that means to my business. Am I getting that right? >> Yeah, yeah. And in fact, the other impact is on your primary service and your primary storage. If the backup window shrinks, then you're not slowing down that SAP app, that Oracle app, you know, that SQL app, whatever you're running, whether that be the financials, whether that be your logistics, whether it be your manufacturing system, every time you turn on that backup, to do that backup, that backup window slows you down. So cutting that in half has an impact on the real-world application side, which obviously most storage guys, you know, it's hard for us to quantify. But you are taking the impact of backup, and basically reducing it, if you will shrinking the backup window, so their primary applications don't get hammered as much by the backup while they're still trying to run that SAP, that Oracle or that SQL workload. >> And you're not a backup software vendor, so I have optionality there. I can pretty much choose all the popular, you know. >> Absolutely, so Veeam, Veritas, Commvault, IBM Spectrum Protect, all the majors. And in fact, one of the players I mentioned, as you were talking about the end-users, they use two different backup packages, two of 'em. So, two of the major vendors that I named, we work with them just within one account. So, we're very flexible, the user picks what they want from a backup software perspective, and we can work with anything. So, whatever they want to use, is fine with us. We integrate with all of them, we have integration, for example, also with VMware, for vVols and other aspects in container integration, so you know, whether it be our purpose-built backup appliance, InfiniGuard, or what we do with the InfiniBox, we always make sure we integrate with the surrounding environment. 'Cause storage is not an island, storage needs to exist in your data center, or your hybrid cloud data center, or what you're doing for containers. So we make sure we have integration with our InfiniBox, our InfiniBox SSA, all flash. And of course the product we're enhancing today, the InfiniGuard. >> Yeah, integration is super important in the enterprise. Enterprises want solutions, they're busy. (laughs) They don't have unlimited budget to go, you know, plugging stuff together. So, okay Eric, we got to leave it there. Thank you so much. >> Great, thank you very much Dave. Always love talking to the Cube. >> Okay, in a moment Stan Wysocki is coming in. He's the president of Mark III Systems. He's going to join us for a drill down on how InfiniGuard is impacting customers. You're watching the Cube, your global leader, in enterprise tech coverage. (gentle music)

(gentle music) >> High profile cyber attacks like the SolarWinds hack, the JBS meat and the Florida municipality breach, have heightened awareness of how exposed, critical infrastructure has become. Because the pandemic has shifted employees to remote modes of work, hackers now have a much easier target to fish for credentials and exploit less secure home networks. Take the recent Log4j vulnerability, that's yet another example, of how hackers can take advantage of weak links in the chain. Now data storage companies have an important role to play in fighting cyber crime. Ultimately, they provide the equivalent of a bank vault if you will, and are responsible for storing and protecting the data that cyber criminals are targeting to steal or encrypt, in an effort to hold companies hostage, in a ransomware attack. Now in an effort to help customers understand how to protect themselves from such vulnerabilities, and how one storage company is addressing these challenges, the Cube is hosting this special presentation InfiniGuard Cyber Resilience: New Cybercrime Solutions. And we're going to speak with Eric Herzog, who's the Chief Marketing Officer of Infinidat, and then we'll bring in Stan Wysocki who is the president of Mark III Systems who is either an expert in IT infrastructure and artificial intelligence. First, let me welcome Eric Herzog back to the Cube, hello, Eric. >> Great, Dave, thank you very much, always love talking to you and the Cube, about leading edge technology solutions for end users. >> Alright let's do it. So, first we want to address the transformation and big business progress of Infinidat. New CEO, he's injected new management, new head of marketing obviously, Phil Bullinger is really been focused on accelerating the company's original vision, and doing so, Eric, in the typically unconventional style of Infinidat, you just put out a press release, capping 2021, can you set the stage for us, and give us the business update? >> Sure, so of course we summarized our 2021 results. What a very, very strong year. What a very, very strong year. We increased our bookings over 40% year to year. Even in Q4, we increased our bookings over 68%. And over 25% of the fortune 50 use an Infinidat solution, either our InfiniBox, or InfiniBox SSA, all flash array, or our Infiniguard, which is the focus of the launch we're doing today, on February 9th. >> Yeah, so I always said that Infinidat is one of the best kept secrets in the storage business. So let's talk about that hard news, what you launched on February 9th, and why it's important. >> Well, what we've done is we've got a high end enterprise purpose-built backup appliance, the InfiniGuard. We made some substantial advances in that. The key is focused on cyber resilience with what we call our infinisafe technology. Infinisafe incorporates a number of subsets, of cyber resilience from immutable snapshots, to logical air gapping, to fenced isolated networks, to almost instantaneous recovery for your backup data sets. In addition, we also dramatically improved the performance of the backup and recovery, which means, for example, if a backup window was taking three hours, now the backup window on that primary backup dataset could take only an hour and a half, which of course, as we all know backup dramatically impacts the performance of your primary applications, your primary servers, and your primary storage. So we've done both the cyber resilience aspect and then, on modern data protection, making sure that the backup and recovery are faster, for a traditional backup workload. >> So tell us a little bit more about Infinisafe, and specifically, Eric I'm interested in how it's different from other solutions, don't make me a liar, I had said, you guys always kind of take nonconventional approaches so tell us, add a little color to Infinisafe and how is it really unique from competitors? >> Sure, well Infinisafe incorporates as I mentioned, several different aspects. First of all, the immutable snapshots. So immutable snapshots can not be deleted, they cannot be altered, you cannot accelerate the rate, you can set the rate of immutable stuff, do I want to do it once a day? Do I want to do it twice a day? And obviously if a hacker could get in, you could accelerate that. Our immutable snaps are physically separated from the management schema. So the inside of an Infiniguard, we have what we call a data dedupe appliance, and that data dedupe engine, it goes ahead and it applies data reduction technology, to that back up data set. But we've divorced the immutable snapshots from the management of what we now call a DDE. So the DDE has kind of access of giving you that gap, that logical gap between the management schema of a DDE, and of course the immutable snapshot. We also combine that with this air gap technology, you've got the immutability and the air gap, which is local in that instance, but we also can do it remotely. So we can replicate from one Infiniguard in data center A, to a different Infiniguard in data center B. You then can configure that backup data set with the same immutable snapshot, and the same length, one day, half a day, six hours, whatever you choose, and then of course it'll have that same capability. The third thing we've done is very unique. We have a fenced isolated network to perform forensics. So, if the Cube has a cyber or malware attack, you need to make sure that once you've cleaned it up, off the primary storage, the primary servers, that you recover, a known good data set. So we set up this isolated fence network in which to perform that forensic analysis, to give you the appropriate good recover point. However, unlike many of our competitors, we can do it with a single InfiniBox. Some of our competitors, right on their websites say, you need two of their purpose-built backup appliances, to do cyber resilience. Meaning, twice the CapEx and twice the OpEx, which we can do with a single Infiniguard solution. And then lastly is our near instantaneous recovery. As you know, we're recovering backup data sets. We can make between 15 and 30 minutes time, the backup data set fully accessible to the backup admin or the storage admin to use their Commvault, their Veeam, their Veritas, their IBM Spectrum Protect, or whatever their backup software is, to do recovery from the InfiniGuard box, back to the primary storage using of course the backup software that they created the original dataset with. That is very unique. When you look out in the industry and look at, whether it be purpose-built backup competitors, or whether you look at primary storage competitors, almost no one talks about the speed of their recovery, and the one or two that do, talk about recovering the data set. We recover the entire environment. We are ready to go, and the backup admin, if they were, for example, Commvault, Veeam or Veritas, they could immediately start the backup, as soon as we did our recovery, which again, takes between 15 and 30 minutes, independent of the data set size. That could be 50 terabytes, it could be a petabyte, it could be two petabytes. And even two petabytes of data can be available in 15 to 30 minutes. And then of course, the backup admin can restore from that backup dataset. Very powerful and very unique in those aspects. >> Whilst the reason why this is so important is like I said, it's like the bank vault, because hackers are going to go after that backup corpus that's where the gold is, that's where all the data is. So this all really sounds good. But there's more than Infinisafe in this launch. What else should we know? >> Well, the other thing we've done is dramatically improved the performance of the purpose-built backup plants at the core. So for example, the last time we publicly announced our numbers, we were at 74 terabytes an hour, now we're 180 terabytes an hour. So of course, as we all know, when you do a backup, it impacts the performance of the primary applications, the primary servers and the primary storage. So if that backup window was taking three hours, now that we've more than doubled the performance, you could be up to 50% better. So a three hour backup window, if that's what the dataset took to be backed up, now we can get that down to an hour and a half or even faster. So that of course minimizes the impact on primary storage, primary applications, and of course your primary storage, making it much, much more efficient, from a backup perspective, and of course less impact on the primary applications, the primary servers, and primary storage. >> So I've talked to a number of Infinidat customers, they're very loyal and kind of passionate. So I wonder if you could kind of put that perspective on this discussion. The impact that InfiniGuard, this announcement, that's going to have for your customers, paint a picture as to how it's going to change their business. >> Sure, so let me give you an example. One of our customers is a cloud service buyer, in North America, they focus only on healthcare. So here's a couple of key benefits that they got. First of all, they use our integration with two different backup vendors. They don't have one, they have two. So we're tightly integrated with our backup software partners. They got a 40% cost savings on CapEX, compared to the previous vendor that they had. And, they used to be able to do 30,000 backup per day, now they can do 90,000 backup a day. And by the way, that's all with the previous version of InfiniGuard, not the version we just announced on the 9th. One of our other customers, which is in AMEA and they happened to be an energy company, they were using purpose-built backup from the other vendor, and they had 14 of them, seven in data center one, and seven in data center two. With InfiniGuard, they've got one in data center one, and one in data center two. So 14 purpose-built backup appliances consolidated down into two. And on top of that, those purpose-built backup appliances from the other vendor actually had a couple recovery failures, where they were not able to recover the data. They've been installed for a year now, they've had zero recovers, zero recovery failures, whereas the previous vendor had some. And lastly, let's talk about a large global fortune financial services. So, one of the biggest in the industry, their cost savings from their previous vendor was 46%. In addition, when you look at their cyber resilience design, they were using one of those vendors that probably talks about needing two system products to do their cyber resiliency. They again were able to take those two systems out, and use one InfiniGuard solution. Again, reducing both their capital expenditure, two going to one. And then the operational expenditure, they only have to manage one InfiniGuard versus two of the other guys appliances. Those are just three examples all over the world. One in cloud service providing, one in the energy space, and one a global fortune 500 financial services company. Just some real world examples. And all those by the way, Dave, were before the enhancements of Infinisafe, and before the additional performance we've added in the launch of InfiniGuard on February 9th. >> So like I'm just kind of sketching out the business case, you know, put my CFO hat on. So you're lowering costs cause you're consolidating, so that means I need less hardware and software. But also there's probably labor costs associated with that. If I could do it faster with less resources, I got less stuff to manage. You're accelerating the backup time, so that frees up resources that I can apply elsewhere, recovery, you know, is really important. So I'm inferring faster recovery, all this lowers my risk, and then I can sort of calculate the probability of having data loss, and then what that means to my business. Am I getting that right? >> Yeah, yeah. And in fact, the other impact is on your primary service and your primary storage. If the backup window shrinks, then you're not slowing down that SAP app, that Oracle app, you know, that SQL app, whatever you're running, whether that be the financials, whether that be your logistics, whether it be your manufacturing system, every time you turn on that backup, to do that backup, that backup window slows you down. So cutting that in half has an impact on the real-world application side, which obviously most storage guys, you know, it's hard for us to quantify. But you are taking the impact of backup, and basically reducing it, if you will shrinking the backup window, so their primary applications don't get hammered as much by the backup while they're still trying to run that SAP, that Oracle or that SQL workload. >> And you're not a backup software vendor, so I have optionality there. I can pretty much choose all the popular, you know. >> Absolutely, so Veeam, Veritas, Commvault, IBM Spectrum Protect, all the majors. And in fact, one of the players I mentioned, as you were talking about the end-users, they use two different backup packages, two of 'em. So, two of the major vendors that I named, we work with them just within one account. So, we're very flexible, the user picks what they want from a backup software perspective, and we can work with anything. So, whatever they want to use, is fine with us. We integrate with all of them, we have integration, for example, also with VMware, for vVols and other aspects in container integration, so you know, whether it be our purpose-built backup appliance, InfiniGuard, or what we do with the InfiniBox, we always make sure we integrate with the surrounding environment. 'Cause storage is not an island, storage needs to exist in your data center, or your hybrid cloud data center, or what you're doing for containers. So we make sure we have integration with our InfiniBox, our InfiniBox SSA, all flash. And of course the product we're enhancing today, the InfiniGuard. >> Yeah, integration is super important in the enterprise. Enterprises want solutions, they're busy. (laughs) They don't have unlimited budget to go, you know, plugging stuff together. So, okay Eric, we got to leave it there. Thank you so much. >> Great, thank you very much Dave. Always love talking to the Cube. >> Okay, in a moment Stan Wysocki is coming in. He's the president of Mark III Systems. He's going to join us for a drill down on how InfiniGuard is impacting customers. You're watching the Cube, your global leader, in enterprise tech coverage. (gentle music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> The pandemic has changed the way we think about and predict the future. As we enter the third year of a global pandemic, we see the significant impact that it's had on technology strategy, spending patterns, and company fortunes Much has changed. And while many of these changes were forced reactions to a new abnormal, the trends that we've seen over the past 24 months have become more entrenched, and point to the way that's coming ahead in the technology business. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we welcome our partner and colleague and business friend, Erik Porter Bradley, as we deliver what's becoming an annual tradition for Erik and me, our predictions for Enterprise Technology in 2022 and beyond Erik, welcome. Thanks for taking some time out. >> Thank you, Dave. Luckily we did pretty well last year, so we were able to do this again. So hopefully we can keep that momentum going. >> Yeah, you know, I want to mention that, you know, we get a lot of inbound predictions from companies and PR firms that help shape our thinking. But one of the main objectives that we have is we try to make predictions that can be measured. That's why we use a lot of data. Now not all will necessarily fit that parameter, but if you've seen the grading of our 2021 predictions that Erik and I did, you'll see we do a pretty good job of trying to put forth prognostications that can be declared correct or not, you know, as black and white as possible. Now let's get right into it. Our first prediction, we're going to go run into spending, something that ETR surveys for quarterly. And we've reported extensively on this. We're calling for tech spending to increase somewhere around 8% in 2022, we can see there on the slide, Erik, we predicted spending last year would increase by 4% IDC. Last check was came in at five and a half percent. Gardner was somewhat higher, but in general, you know, not too bad, but looking ahead, we're seeing an acceleration from the ETR September surveys, as you can see in the yellow versus the blue bar in this chart, many of the SMBs that were hard hit by the pandemic are picking up spending again. And the ETR data is showing acceleration above the mean for industries like energy, utilities, retail, and services, and also, notably, in the Forbes largest 225 private companies. These are companies like Mars or Koch industries. They're predicting well above average spending for 2022. So Erik, please weigh in here. >> Yeah, a lot to bring up on this one, I'm going to be quick. So 1200 respondents on this, over a third of which were at the C-suite level. So really good data that we brought in, the usual bucket of, you know, fortune 500, global 2000 make up the meat of that median, but it's 8.3% and rising with momentum as we see. What's really interesting right now is that energy and utilities. This is usually like, you know, an orphan stock dividend type of play. You don't see them at the highest point of tech spending. And the reason why right now is really because this state of tech infrastructure in our energy infrastructure needs help. And it's obvious, remember the Florida municipality break reach last year? When they took over the water systems or they had the ability to? And this is a real issue, you know, there's bad nation state actors out there, and I'm no alarmist, but the energy and utility has to spend this money to keep up. It's really important. And then you also hit on the retail consumer. Obviously what's happened, the work from home shift created a shop from home shift, and the trends that are happening right now in retail. If you don't spend and keep up, you're not going to be around much longer. So I think the really two interesting things here to call out are energy utilities, usually a laggard in IT spend and it's leading, and also retail consumer, a lot of changes happening. >> Yeah. Great stuff. I mean, I recall when we entered the pandemic, really ETR was the first to emphasize the impact that work from home was going to have, so I really put a lot of weight on this data. Okay. Our next prediction is we're going to get into security, it's one of our favorite topics. And that is that the number one priority that needs to be addressed by organizations in 2022 is security and you can see, in this slide, the degree to which security is top of mind, relative to some other pretty important areas like cloud, productivity, data, and automation, and some others. Now people may say, "Oh, this is obvious." But I'm going to add some context here, Erik, and then bring you in. First, organizations, they don't have unlimited budgets. And there are a lot of competing priorities for dollars, especially with the digital transformation mandate. And depending on the size of the company, this data will vary. For example, while security is still number one at the largest public companies, and those are of course of the biggest spenders, it's not nearly as pronounced as it is on average, or in, for example, mid-sized companies and government agencies. And this is because midsized companies or smaller companies, they don't have the resources that larger companies do. Larger companies have done a better job of securing their infrastructure. So these mid-size firms are playing catch up and the data suggests cyber is even a bigger priority there, gaps that they have to fill, you know, going forward. And that's why we think there's going to be more demand for MSSPs, managed security service providers. And we may even see some IPO action there. And then of course, Erik, you and I have talked about events like the SolarWinds Hack, there's more ransomware attacks, other vulnerabilities. Just recently, like Log4j in December. All of this has heightened concerns. Now I want to talk a little bit more about how we measure this, you know, relatively, okay, it's an obvious prediction, but let's stick our necks out a little bit. And so in addition to the rise of managed security services, we're calling for M&A and/or IPOs, we've specified some names here on this chart, and we're also pointing to the digital supply chain as an area of emphasis. Again, Log4j really shone that under a light. And this is going to help the likes of Auth0, which is now Okta, SailPoint, which is called out on this chart, and some others. We're calling some winners in end point security. Erik, you're going to talk about sort of that lifecycle, that transformation that we're seeing, that migration to new endpoint technologies that are going to benefit from this reset refresh cycle. So Erik, weigh in here, let's talk about some of the elements of this prediction and some of the names on that chart. >> Yeah, certainly. I'm going to start right with Log4j top of mind. And the reason why is because we're seeing a real paradigm shift here where things are no longer being attacked at the network layer, they're being attacked at the application layer, and in the application stack itself. And that is a huge shift left. And that's taking in DevSecOps now as a real priority in 2022. That's a real paradigm shift over the last 20 years. That's not where attacks used to come from. And this is going to have a lot of changes. You called out a bunch of names in there that are, they're either going to work. I would add to that list Wiz. I would add Orca Security. Two names in our emerging technology study, in addition to the ones you added that are involved in cloud security and container security. These names are either going to get gobbled up. So the traditional legacy names are going to have to start writing checks and, you know, legacy is not fair, but they're in the data center, right? They're, on-prem, they're not cloud native. So these are the names that money is going to be flowing to. So they're either going to get gobbled up, or we're going to see some IPO's. And on the other thing I want to talk about too, is what you mentioned. We have CrowdStrike on that list, We have SentinalOne on the list. Everyone knows them. Our data was so strong on Tanium that we actually went positive for the first time just today, just this morning, where that was released. The trifecta of these are so important because of what you mentioned, under resourcing. We can't have security just tell us when something happens, it has to automate, and it has to respond. So in this next generation of EDR and XDR, an automated response has to happen because people are under-resourced, salaries are really high, there's a skill shortage out there. Security has to become responsive. It can't just monitor anymore. >> Yeah. Great. And we should call out too. So we named some names, Snyk, Aqua, Arctic Wolf, Lacework, Netskope, Illumio. These are all sort of IPO, or possibly even M&A candidates. All right. Our next prediction goes right to the way we work. Again, something that ETR has been on for awhile. We're calling for a major rethink in remote work for 2022. We had predicted last year that by the end of 2021, there'd be a larger return to the office with the norm being around a third of workers permanently remote. And of course the variants changed that equation and, you know, gave more time for people to think about this idea of hybrid work and that's really come in to focus. So we're predicting that is going to overtake fully remote as the dominant work model with only about a third of the workers back in the office full-time. And Erik, we expect a somewhat lower percentage to be fully remote. It's now sort of dipped under 30%, at around 29%, but it's still significantly higher than the historical average of around 15 to 16%. So still a major change, but this idea of hybrid and getting hybrid right, has really come into focus. Hasn't it? >> Yeah. It's here to stay. There's no doubt about it. We started this in March of 2020, as soon as the virus hit. This is the 10th iteration of the survey. No one, no one ever thought we'd see a number where only 34% of people were going to be in office permanently. That's a permanent number. They're expecting only a third of the workers to ever come back fully in office. And against that, there's 63% that are saying their permanent workforce is going to be either fully remote or hybrid. And this, I can't really explain how big of a paradigm shift this is. Since the start of the industrial revolution, people leave their house and go to work. Now they're saying that's not going to happen. The economic impact here is so broad, on so many different areas And, you know, the reason is like, why not? Right? The productivity increase is real. We're seeing the productivity increase. Enterprises are spending on collaboration tools, productivity tools, We're seeing an increased perception in productivity of their workforce. And the CFOs can cut down an expense item. I just don't see a reason why this would end, you know, I think it's going to continue. And I also want to point out these results, as high as they are, were before the Omicron wave hit us. I can only imagine what these results would have been if we had sent the survey out just two or three weeks later. >> Yeah. That's a great point. Okay. Next prediction, we're going to look at the supply chain, specifically in how it's affecting some of the hardware spending and cloud strategies in the future. So in this chart, ETRS buyers, have you experienced problems procuring hardware as a result of supply chain issues? And, you know, despite the fact that some companies are, you know, I would call out Dell, for example, doing really well in terms of delivering, you can see that in the numbers, it's pretty clear, there's been an impact. And that's not not an across the board, you know, thing where vendors are able to deliver, especially acute in PCs, but also pronounced in networking, also in firewall servers and storage. And what's interesting is how companies are responding and reacting. So first, you know, I'm going to call the laptop and PC demand staying well above pre-COVID norms. It had peaked in 2012. Pre-pandemic it kept dropping and dropping and dropping, in terms of, you know, unit volume, where the market was contracting. And we think can continue to grow this year in double digits in 2022. But what's interesting, Erik, is when you survey customers, is despite the difficulty they're having in procuring network hardware, there's as much of a migration away from existing networks to the cloud. You could probably comment on that. Their networks are more fossilized, but when it comes to firewalls and servers and storage, there's a much higher propensity to move to the cloud. 30% of customers that ETR surveyed will replace security appliances with cloud services and 41% and 34% respectively will move to cloud compute and storage in 2022. So cloud's relentless march on traditional on-prem models continues. Erik, what do you make of this data? Please weigh in on this prediction. >> As if we needed another reason to go to the cloud. Right here, here it is yet again. So this was added to the survey by client demand. They were asking about the procurement difficulties, the supply chain issues, and how it was impacting our community. So this is the first time we ran it. And it really was interesting to see, you know, the move there. And storage particularly I found interesting because it correlated with a huge jump that we saw on one of our vendor names, which was Rubrik, had the highest net score that it's ever had. So clearly we're seeing some correlation with some of these names that are there, you know, really well positioned to take storage, to take data into the cloud. So again, you didn't need another reason to, you know, hasten this digital transformation, but here we are, we have it yet again, and I don't see it slowing down anytime soon. >> You know, that's a really good point. I mean, it's not necessarily bad news for the... I mean, obviously you wish that it had no change, would be great, but things, you know, always going to change. So we'll talk about this a little bit later when we get into the Supercloud conversation, but this is an opportunity for people who embrace the cloud. So we'll come back to that. And I want to hang on cloud a bit and share some recent projections that we've made. The next prediction is the big four cloud players are going to surpass 167 billion, an IaaS and PaaS revenue in 2022. We track this. Observers of this program know that we try to create an apples to apples comparison between AWS, Azure, GCP and Alibaba in IaaS and PaaS. So we're calling for 38% revenue growth in 2022, which is astounding for such a massive market. You know, AWS is probably not going to hit a hundred billion dollar run rate, but they're going to be close this year. And we're going to get there by 2023, you know they're going to surpass that. Azure continues to close the gap. Now they're about two thirds of the size of AWS and Google, we think is going to surpass Alibaba and take the number three spot. Erik, anything you'd like to add here? >> Yeah, first of all, just on a sector level, we saw our sector, new survey net score on cloud jumped another 10%. It was already really high at 48. Went up to 53. This train is not slowing down anytime soon. And we even added an edge compute type of player, like CloudFlare into our cloud bucket this year. And it debuted with a net score of almost 60. So this is really an area that's expanding, not just the big three, but everywhere. We even saw Oracle and IBM jump up. So even they're having success, taking some of their on-prem customers and then selling them to their cloud services. This is a massive opportunity and it's not changing anytime soon, it's going to continue. >> And I think the operative word there is opportunity. So, you know, the next prediction is something that we've been having fun with and that's this Supercloud becomes a thing. Now, the reason I say we've been having fun is we put this concept of Supercloud out and it's become a bit of a controversy. First, you know, what the heck's the Supercloud right? It's sort of a buzz-wordy term, but there really is, we believe, a thing here. We think there needs to be a rethinking or at least an evolution of the term multi-cloud. And what we mean is that in our view, you know, multicloud from a vendor perspective was really cloud compatibility. It wasn't marketed that way, but that's what it was. Either a vendor would containerize its legacy stack, shove it into the cloud, or a company, you know, they'd do the work, they'd build a cloud native service on one of the big clouds and they did do it for AWS, and then Azure, and then Google. But there really wasn't much, if any, leverage across clouds. Now from a buyer perspective, we've always said multicloud was a symptom of multi-vendor, meaning I got different workloads, running in different clouds, or I bought a company and they run on Azure, and I do a lot of work on AWS, but generally it wasn't necessarily a prescribed strategy to build value on top of hyperscale infrastructure. There certainly was somewhat of a, you know, reducing lock-in and hedging the risk. But we're talking about something more here. We're talking about building value on top of the hyperscale gift of hundreds of billions of dollars in CapEx. So in addition, we're not just talking about transforming IT, which is what the last 10 years of cloud have been like. And, you know, doing work in the cloud because it's cheaper or simpler or more agile, all of those things. So that's beginning to change. And this chart shows some of the technology vendors that are leaning toward this Supercloud vision, in our view, building on top of the hyperscalers that are highlighted in red. Now, Jerry Chan at Greylock, they wrote a piece called Castles in the Cloud. It got our thinking going, and he and the team at Greylock, they're building out a database of all the cloud services and all the sub-markets in cloud. And that got us thinking that there's a higher level of abstraction coalescing in the market, where there's tight integration of services across clouds, but the underlying complexity is hidden, and there's an identical experience across clouds, and even, in my dreams, on-prem for some platforms, so what's new or new-ish and evolving are things like location independence, you've got to include the edge on that, metadata services to optimize locality of reference and data source awareness, governance, privacy, you know, application independent and dependent, actually, recovery across clouds. So we're seeing this evolve. And in our view, the two biggest things that are new are the technology is evolving, where you're seeing services truly integrate cross-cloud. And the other big change is digital transformation, where there's this new innovation curve developing, and it's not just about making your IT better. It's about SaaS-ifying and automating your entire company workflows. So Supercloud, it's not just a vendor thing to us. It's the evolution of, you know, the, the Marc Andreessen quote, "Every company will be a SaaS company." Every company will deliver capabilities that can be consumed as cloud services. So Erik, the chart shows spending momentum on the y-axis and net score, or presence in the ETR data center, or market share on the x-axis. We've talked about snowflake as the poster child for this concept where the vision is you're in their cloud and sharing data in that safe place. Maybe you could make some comments, you know, what do you think of this Supercloud concept and this change that we're sensing in the market? >> Well, I think you did a great job describing the concept. So maybe I'll support it a little bit on the vendor level and then kind of give examples of the ones that are doing it. You stole the lead there with Snowflake, right? There is no better example than what we've seen with what Snowflake can do. Cross-portability in the cloud, the ability to be able to be, you know, completely agnostic, but then build those services on top. They're better than anything they could offer. And it's not just there. I mean, you mentioned edge compute, that's a whole nother layer where this is coming in. And CloudFlare, the momentum there is out of control. I mean, this is a company that started off just doing CDN and trying to compete with Okta Mite. And now they're giving you a full soup to nuts with security and actual edge compute layer, but it's a fantastic company. What they're doing, it's another great example of what you're seeing here. I'm going to call out HashiCorp as well. They're more of an infrastructure services, a little bit more of an open-source freemium model, but what they're doing as well is completely cloud agnostic. It's dynamic. It doesn't care if you're in a container, it doesn't matter where you are. They recently IPO'd and they're down 25%, but their data looks so good across both of our emerging technology and TISA survey. It's certainly another name that's playing on this. And another one that we mentioned as well is Rubrik. If you need storage, compute, and in the cloud layer and you need to be agnostic to it, they're another one that's really playing in this space. So I think it's a great concept you're bringing up. I think it's one that's here to stay and there's certainly a lot of vendors that fit into what you're describing. >> Excellent. Thank you. All right, let's shift to data. The next prediction, it might be a little tough to measure. Before I said we're trying to be a little black and white here, but it relates to Data Mesh, which is, the ideas behind that term were created by Zhamak Dehghani of ThoughtWorks. And we see Data Mesh is really gaining momentum in 2022, but it's largely going to be, we think, confined to a more narrow scope. Now, the impetus for change in data architecture in many companies really stems from the fact that their Hadoop infrastructure really didn't solve their data problems and they struggle to get more value out of their data investments. Data Mesh prescribes a shift to a decentralized architecture in domain ownership of data and a shift to data product thinking, beyond data for analytics, but data products and services that can be monetized. Now this a very powerful in our view, but they're difficult for organizations to get their heads around and further decentralization creates the need for a self-service platform and federated data governance that can be automated. And not a lot of standards around this. So it's going to take some time. At our power panel a couple of weeks ago on data management, Tony Baer predicted a backlash on Data Mesh. And I don't think it's going to be so much of a backlash, but rather the adoption will be more limited. Most implementations we think are going to use a starting point of AWS and they'll enable domains to access and control their own data lakes. And while that is a very small slice of the Data Mesh vision, I think it's going to be a starting point. And the last thing I'll say is, this is going to take a decade to evolve, but I think it's the right direction. And whether it's a data lake or a data warehouse or a data hub or an S3 bucket, these are really, the concept is, they'll eventually just become nodes on the data mesh that are discoverable and access is governed. And so the idea is that the stranglehold that the data pipeline and process and hyper-specialized roles that they have on data agility is going to evolve. And decentralized architectures and the democratization of data will eventually become a norm for a lot of different use cases. And Erik, I wonder if you'd add anything to this. >> Yeah. There's a lot to add there. The first thing that jumped out to me was that that mention of the word backlash you said, and you said it's not really a backlash, but what it could be is these are new words trying to solve an old problem. And I do think sometimes the industry will notice that right away and maybe that'll be a little pushback. And the problems are what you already mentioned, right? We're trying to get to an area where we can have more assets in our data site, more deliverable, and more usable and relevant to the business. And you mentioned that as self-service with governance laid on top. And that's really what we're trying to get to. Now, there's a lot of ways you can get there. Data fabric is really the technical aspect and data mesh is really more about the people, the process, and the governance, but the two of those need to meet, in order to make that happen. And as far as tools, you know, there's even cataloging names like Informatica that play in this, right? Istio plays in this, Snowflake plays in this. So there's a lot of different tools that will support it. But I think you're right in calling out AWS, right? They have AWS Lake, they have AWS Glue. They have so much that's trying to drive this. But I think the really important thing to keep here is what you said. It's going to be a decade long journey. And by the way, we're on the shoulders of giants a decade ago that have even gotten us to this point to talk about these new words because this has been an ongoing type of issue, but ultimately, no matter which vendors you use, this is going to come down to your data governance plan and the data literacy in your business. This is really about workflows and people as much as it is tools. So, you know, the new term of data mesh is wonderful, but you still have to have the people and the governance and the processes in place to get there. >> Great, thank you for that, Erik. Some great points. All right, for the next prediction, we're going to shine the spotlight on two of our favorite topics, Snowflake and Databricks, and the prediction here is that, of course, Databricks is going to IPO this year, as expected. Everybody sort of expects that. And while, but the prediction really is, well, while these two companies are facing off already in the market, they're also going to compete with each other for M&A, especially as Databricks, you know, after the IPO, you're going to have, you know, more prominence and a war chest. So first, these companies, they're both looking pretty good, the same XY graph with spending velocity and presence and market share on the horizontal axis. And both Snowflake and Databricks are well above that magic 40% red dotted line, the elevated line, to us. And for context, we've included a few other firms. So you can see kind of what a good position these two companies are really in, especially, I mean, Snowflake, wow, it just keeps moving to the right on this horizontal picture, but maintaining the next net score in the Y axis. Amazing. So, but here's the thing, Databricks is using the term Lakehouse implying that it has the best of data lakes and data warehouses. And Snowflake has the vision of the data cloud and data sharing. And Snowflake, they've nailed analytics, and now they're moving into data science in the domain of Databricks. Databricks, on the other hand, has nailed data science and is moving into the domain of Snowflake, in the data warehouse and analytics space. But to really make this seamless, there has to be a semantic layer between these two worlds and they're either going to build it or buy it or both. And there are other areas like data clean rooms and privacy and data prep and governance and machine learning tooling and AI, all that stuff. So the prediction is they'll not only compete in the market, but they'll step up and in their competition for M&A, especially after the Databricks IPO. We've listed some target names here, like Atscale, you know, Iguazio, Infosum, Habu, Immuta, and I'm sure there are many, many others. Erik, you care to comment? >> Yeah. I remember a year ago when we were talking Snowflake when they first came out and you, and I said, "I'm shocked if they don't use this war chest of money" "and start going after more" "because we know Slootman, we have so much respect for him." "We've seen his playbook." And I'm actually a little bit surprised that here we are, at 12 months later, and he hasn't spent that money yet. So I think this prediction's just spot on. To talk a little bit about the data side, Snowflake is in rarefied air. It's all by itself. It is the number one net score in our entire TISA universe. It is absolutely incredible. There's almost no negative intentions. Global 2000 organizations are increasing their spend on it. We maintain our positive outlook. It's really just, you know, stands alone. Databricks, however, also has one of the highest overall net sentiments in the entire universe, not just its area. And this is the first time we're coming up positive on this name as well. It looks like it's not slowing down. Really interesting comment you made though that we normally hear from our end-user commentary in our panels and our interviews. Databricks is really more used for the data science side. The MLAI is where it's best positioned in our survey. So it might still have some catching up to do to really have that caliber of usability that you know Snowflake is seeing right now. That's snowflake having its own marketplace. There's just a lot more to Snowflake right now than there is Databricks. But I do think you're right. These two massive vendors are sort of heading towards a collision course, and it'll be very interesting to see how they deploy their cash. I think Snowflake, with their incredible management and leadership, probably will make the first move. >> Well, I think you're right on that. And by the way, I'll just add, you know, Databricks has basically said, hey, it's going to be easier for us to come from data lakes into data warehouse. I'm not sure I buy that. I think, again, that semantic layer is a missing ingredient. So it's going to be really interesting to see how this plays out. And to your point, you know, Snowflake's got the war chest, they got the momentum, they've got the public presence now since November, 2020. And so, you know, they're probably going to start making some aggressive moves. Anyway, next prediction is something, Erik, that you and I have talked about many, many times, and that is observability. I know it's one of your favorite topics. And we see this world screaming for more consolidation it's going all in on cloud native. These legacy stacks, they're fighting to stay relevant, but the direction is pretty clear. And the same XY graph lays out the players in the field, with some of the new entrants that we've also highlighted, like Observe and Honeycomb and ChaosSearch that we've talked about. Erik, we put a big red target around Splunk because everyone wants their gold. So please give us your thoughts. >> Oh man, I feel like I've been saying negative things about Splunk for too long. I've got a bad rap on this name. The Splunk shareholders come after me all the time. Listen, it really comes down to this. They're a fantastic company that was designed to do logging and monitoring and had some great tool sets around what you could do with it. But they were designed for the data center. They were designed for prem. The world we're in now is so dynamic. Everything I hear from our end user community is that all net new workloads will be going to cloud native players. It's that simple. So Splunk has entrenched. It's going to continue doing what it's doing and it does it really, really well. But if you're doing something new, the new workloads are going to be in a dynamic environment and that's going to go to the cloud native players. And in our data, it is extremely clear that that means Datadog and Elastic. They are by far number one and two in net score, increase rates, adoption rates. It's not even close. Even New Relic actually is starting to, you know, entrench itself really well. We saw New Relic's adoption's going up, which is super important because they went to that freemium model, you know, to try to get their little bit of an entrenched customer base and that's working as well. And then you made a great list here, of all the new entrants, but it goes beyond this. There's so many more. In our emerging technology survey, we're seeing Century, Catchpoint, Securonix, Lucid Works. There are so many options in this space. And let's not forget, the biggest data that we're seeing is with Grafana. And Grafana labs as yet to turn on their enterprise. Elastic did it, why can't Grafana labs do it? They have an enterprise stack. So when you look at how crowded this space is, there has to be consolidation. I recently hosted a panel and every single guy on that panel said, "Please give me a consolidation." Because they're the end users trying to actually deploy these and it's getting a little bit confusing. >> Great. Thank you for that. Okay. Last prediction. Erik, might be a little out of your wheelhouse, but you know, you might have some thoughts on it. And that's a hybrid events become the new digital model and a new category in 2022. You got these pure play digital or virtual events. They're going to take a back seat to in-person hybrids. The virtual experience will eventually give way to metaverse experiences and that's going to take some time, but the physical hybrid is going to drive it. And metaverse is ultimately going to define the virtual experience because the virtual experience today is not great. Nobody likes virtual. And hybrid is going to become the business model. Today's pure virtual experience has to evolve, you know, theCUBE first delivered hybrid mid last decade, but nobody really wanted it. We did Mobile World Congress last summer in Barcelona in an amazing hybrid model, which we're showing in some of the pictures here. Alex, if you don't mind bringing that back up. And every physical event that we're we're doing now has a hybrid and virtual component, including the pre-records. You can see in our studios, you see that the green screen. I don't know. Erik, what do you think about, you know, the Zoom fatigue and all this. I know you host regular events with your round tables, but what are your thoughts? >> Well, first of all, I think you and your company here have just done an amazing job on this. So that's really your expertise. I spent 20 years of my career hosting intimate wall street idea dinners. So I'm better at navigating a wine list than I am navigating a conference floor. But I will say that, you know, the trend just goes along with what we saw. If 35% are going to be fully remote. If 70% are going to be hybrid, then our events are going to be as well. I used to host round table dinners on, you know, one or two nights a week. Now those have gone virtual. They're now panels. They're now one-on-one interviews. You know, we do chats. We do submitted questions. We do what we can, but there's no reason that this is going to change anytime soon. I think you're spot on here. >> Yeah. Great. All right. So there you have it, Erik and I, Listen, we always love the feedback. Love to know what you think. Thank you, Erik, for your partnership, your collaboration, and love doing these predictions with you. >> Yeah. I always enjoy them too. And I'm actually happy. Last year you made us do a baker's dozen, so thanks for keeping it to 10 this year. >> (laughs) We've got a lot to say. I know, you know, we cut out. We didn't do much on crypto. We didn't really talk about SaaS. I mean, I got some thoughts there. We didn't really do much on containers and AI. >> You want to keep going? I've got another 10 for you. >> RPA...All right, we'll have you back and then let's do that. All right. All right. Don't forget, these episodes are all available as podcasts, wherever you listen, all you can do is search Breaking Analysis podcast. Check out ETR's website at etr.plus, they've got a new website out. It's the best data in the industry, and we publish a full report every week on wikibon.com and siliconangle.com. You can always reach out on email, David.Vellante@siliconangle.com I'm @DVellante on Twitter. Comment on our LinkedIn posts. This is Dave Vellante for the Cube Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (mellow music)

(upbeat music) >> Thank you and good morning or afternoon, everyone, depending on where you're coming to us from and welcome to today's breakout session, Fast Data, a retail industry business imperative. My name is Brent Biddulph, Global Managing Director of Retail and Super Bids here at Cloudera and today's hosts. Joining me today is our feature speaker Brian Kilcourse, Managing Partner from RSR. We'll be sharing insights and implications from recently completed research across retailers of all sizes in empirical segments. At the end of today's session I'll share a brief overview on what I personally learned from retailers and how Cloudera continues to support retail data analytic requirements, and specifically around streaming data ingest, analytics, automation for customers around the world. There really is the next step up in terms of what's happening with data analytics today. So let's get started. So I thought it'd be helpful to provide some background first on how Cloudera is supporting retail industry leaders specifically how they're leveraging Cloudera for leading practice data analytics use cases, primarily across four key business pillars and these will be very familiar to those in the industry. Personalize interactions of course plays heavily into e-commerce and marketing, whether that's developing customer profiles, understanding the omni-channel journey, moving into the merchandising line of business, focused on localizing sorbet, promotional planning, forecasting, demand forecast accuracy, then into supply chain where inventory visibility is becoming more and more critical today, whether it's around fulfillment or just understanding where your stuff is from a customer perspective. And obviously in and outbound route optimization, right now as retailers are taking control of actual delivery, whether it's to a physical store location or to the consumer. And then finally, which is pretty exciting to me as a former store operator, what's happening with physical brick and mortar right now, especially for traditional retailers. The whole re-imagining of stores right now is on fire in a lot of focus because frankly this is where fulfillment is happening, this is where customers steal 80% of revenue is driven through retail through physical brick and mortar. So right now store operations is getting more focused and I would say it probably is had in decades and a lot of it has to do of course with IoT data and analytics in the new technologies that really help drive benefits for retailers from a brick and mortars standpoint. And then finally, to wrap up before handing off to Brian, as you'll see, all of these lines of businesses are rogue, really experiencing the need for speed, fast data. So we're moving beyond just discovery analytics, things that happened five, six years ago with big data, et cetera and we're really moving into real time capabilities because that's really where the difference makers are, that's where the competitive differentiation is across all of these lines of business and these four key pillars within retail. The dependency on fast data is evident, it's something that we all read in terms of those that are students of the industry if you will, that we're all focused on in terms of bringing value to the individual lines of business but more importantly to the overall enterprise. So without further ado, I really want to have Brian speak here as a third party analyst. He's close in touch with what's going on retail talking to all the solution providers, all the key retailers about what's important, what's on their plate, what are they focusing on right now in terms of fast data and how that could potentially make a difference for them going forward. So Brian off to you. >> Well, thanks, Brent. I appreciate the introduction. And I was thinking as you were talking, what is fast data? Well, fast data is fast data, it's stuff that comes at you very quickly. When I think about the decision cycles in retail, they were time phased and there was a time when we could only make a decision perhaps once a month and then met once a week and then once a day, and then intraday. Fast data is data that's coming at you in something approaching real time and we'll explain why that's important in just a second. But first I want to share with you just a little bit about RSR. We've been in business now for 14 years and what we do is we studied the business use cases that drive the adoption of technology in retail. We come from the retail industry. I was a retail technologist my entire working life and so we started this company. So I have a built-in bias of course, and that is that the difference between the winners in the retail world and in fact in the entire business world and everybody else is how they value the strategic importance of information, and really that's where the battle is being fought today. We'll talk a little bit about that. So anyway, one other thing about RSR Research, our research is free to the entire world. We don't have a paywall that you have to get behind, all you have to do is sign into our website, identify yourself and all of our research, including these two reports that we're showing on the screen now are available to you and we'd love to hear your comments. So when we talk about data, there's a lot of business implications to what we're trying to do with fast data and is being driven by the real world. We saw a lot of evidence of that during the COVID pandemic in 2020, when people had to make many decisions very, very quickly, for example, a simple one, do I redirect my replenishments to store B because store A is impacted by the pandemic, those kinds of things. These two drawings are actually from a book that came out in 1997 and it was a really important book for me personally is by a guy named Steven Hegel and the name of the book was "The Adaptive Enterprise." When you think about your business model and you think about the retail business model, most of those businesses are what you see on the left. First of all, the mission of the business doesn't change much at all, it changes once in a generation or maybe once in a lifetime, but it's established quite early. And then from that point on, it's basically a wash, rinse and repeat cycle. You do the things that you do over and over and over again, year in and year out, season in and season out and the most important pieces of information that you have is the transaction data from the last cycle. So Brent knows this from his experience as a retailer, the baseline for next year's forecast is last year's performance. And this is transactional in nature, it's typically pulled from your ERP or from your best of breed solution set. On the right is where the world is really going, and before we get into the details of this, I'll just use a real example. I'm sure like me, you've watched the path of hurricanes as they go up to the Florida Coast. And one of the things you might've noticed is that there are several different possible paths. These are models and you'll hear a lot about models when you talk to people in the AI world. These are models based on lots and lots of information that they're getting from Noah and from the oceanographic people and all those kinds of folks to understand the likely path of the hurricane. Based on their analysis, the people who watch these things will choose the most likely paths and they will warn communities to lock down and do whatever they need to do. And then they see as the real hurricane progresses, they will see if it's following that path or if it's varying, it's going down a different path and based on that they will adapt to a new model. And that is what I'm talking about here. Not everything is of course is life and death as a hurricane but it's basically the same concept. What's happening is you have your internal data that you've had since this command and control model that we've mentioned on the left and you're taking an external data from the world around you and you're using that to make snap decisions or quick decisions based on what you see, what's observable on the outside. Back to my COVID example, when people were tracking the path of the pandemic through communities, they learned that customers or consumers would favor certain stores to pick up what they needed to get. So they would avoid some stores and they would favor other stores and that would cause smart retailers to redirect the replenishments on very fast cycles to those stores where the consumers are most likely to be. They also did the same thing for employees, they wanted to know where they could get their employees to service these customers, how far away were they, were they in a community that was impacted or were they relatively safe. These are the decisions that were being made in real time based on the information that they were getting from the marketplace around them. So first of all, there's a context for these decisions, there's a purpose and the bounds of the adaptive structure, and then there's a coordination of capabilities in real time and that creates an internal feedback loop, but there's also an external feedback loop. This is more of an ecosystem view and based on those two inputs what's happening internally, where your performance is internally and how your community around you is reacting to what you're providing. You make adjustments as necessary and this is the essence of the adaptive enterprise. Engineers might call this a sense and respond model, and that's where retail is going. But what's essential to that is information and information, not just about the products that you sell or the stores that you sell it in or the employees that you have on the sales floor or the number of market baskets you've completed in the day, but something much, much more. If you will, a twin, a digital twin of the physical assets of your business, all of your physical assets, the people, the products, the customers, the buildings, the rolling stock, everything, everything. And if you can create a digital equivalent of a physical thing, you can then analyze it. And if you can analyze it, you can make decisions much, much more quickly. So this is what's happening with the predict pivot based on what you see and then because it's an intrinsically more complicated model to automate decision-making where it makes sense to do so. That's pretty complicated and I talk about new data and as I said earlier, the old data is all transactional in nature, mostly about sales. Retail has been a wash in sales data for as long as I can remember, they throw most of it away but they do keep enough to create the forecast for the next business cycle. But there's all kinds of new information that they need to be thinking about and a lot of this is from the outside world and a lot of this is non-transactional in nature. So let's just take a look at some of them. Competitive information. Retailers are always interested in what the competitor is up to, what are they promoting? How well are they doing? Where are they? What kind of traffic are they generating? Sudden and significant changes in customer behaviors and sentiment, COVID is a perfect example of something that would cause this, consumers changing their behaviors very quickly. And we have the ability to observe this because in a great majority of cases nowadays, retailers have observed that customers start their shopping journey in the digital space. As a matter of fact, Google recently came out and said that 63% of all sales transactions begin in the digital domain, even if many of them end up in the store. So we have the ability to observe changes in consumer behavior, what are they looking at? When are they looking at it? How long do they spend looking at it? What else are they looking at while they're doing that? What is the outcome of them looking? Market metrics certainly, what's going on in the marketplace around you? A good example of this might be something related to a sporting event. If you've planned based on normal demand and for your store and there's a big sporting event, like a football match or a baseball game, suddenly you're going to see a spike in demand, so understanding what's going on in the market is really important. Location, demographics and psychographics. Demographics have always been important to retailers, but now we're talking about dynamic demographics. What customers or what consumers are in your market in something approaching real time. Psychographics has more to do with their attitudes, what kind of folks are in a particular marketplace, what do they think about, what do they favor, and all those kinds of interesting details. Real time environmental and social incidents, of course, I mentioned hurricanes and so that's fairly self-evident. Disruptive events, sporting events, et cetera, these are all real. And then we get the real time Internet-of-Things, these are RFID sensors, beacons, video, et cetera. There's all kinds of stuff. And this is where it really gets interesting, this is where the supply chain people will start talking about the digital twin to their physical world. If you can't say something you can't manage it and retailers want to be able to manage things in real time. So IoT along with AI analytics and the data that's generated is really, really important for them going forward. Community health, we've been talking a lot about that, the progression of the flu, et cetera, et cetera. Business schedules, commute patterns, school schedules, and weather, these are all external data that are interesting to retailers and can help them to make better operational decisions in something approaching real time. I mentioned the automation of decision-making, this is a chart from Gardner and I'd love to share with you. It's a really good one because it describes very simply what we're talking about and it also describes where the inflection of new technology happens. If you look on the left there's data, we have lots and lots of data, we're getting more data all the time. Retailers for a long time now since certainly since the seventies or eighties have been using data to describe what happened, this is the retrospective analysis that we're all very familiar with, data cubes and those kinds of things. And based on that, the human makes some decisions about what they're going to do going forward. Sometime in the not-too-distant past this data was started to be used to make diagnostic decisions, not only what happened but why did it happen? And we might think of this as, for example, if sales were depressed and for a certain product, was it because we had another product on sale that day, that's a good example of fairly straightforward diagnostics. We then move forward to what we might think of as predictive analytics and this was based on what happened in the past and why it happened in the past. This is what's likely to happen in the future. You might think of this as, for example, halo effect or the cannibalization effect of your category plans if you happen to be a grocer. And based on that, the human will make a decision as to what they need to do next. Then came along AI, and I don't want to oversell AI here. AI is a new way for us to examine lots and lots of data, particularly unstructured data. AI if I could simplify it to the next maximum extent, it essentially is a data tool that allows you to see patterns in data which might be interesting. It's very good at sifting through huge data sets of unstructured data and detecting statistically significant patterns. It gets deeper than that of course, because it uses math instead of rules. So instead of an if then or else statement that we might've used with our structured data, we use the math to detect these patterns in unstructured data and based on those we can make some models. For example, my guy in my (chuckles) just turned 70. My 70 year old man, I'm a white guy, I live in California, I have a certain income and a certain educational level. I'm likely to behave in this way based on a model, that's pretty simplistic but based on that, you can see that when another person who meets my psychographics, my demographics, my age group, my income level and all the rest, they might be expected to make a certain action. And so this is where prescriptive really comes into play. AI makes that possible. And then finally, when you start to think about moving closer to the customer or something approaching a personalized level, a one-to-one level, you suddenly find yourself in the situation of having to make not thousands of decisions but tens of millions of decisions and that's when the automation of decision-making really gets to be pretty important. So this is all interesting stuff, and I don't want to oversell it. It's exciting and it's new, it's just the latest turn of the technology screw and it allows us to use this new data to basically automate decision-making in the business in something approaching real time so that we can be much, much more responsive to real-time conditions in the marketplace. Very exciting. So I hope this is interesting. This is a piece of data from one of our recent pieces of research. This happens to be from a location analytics study we just published last week, and we asked retailers, what are the big challenges? What's been going on in the last 12 months for them, and what's likely to be happening for them in the next few years and it's just fascinating because it speaks to the need for faster decision-making. The challenges in the last 12 months are all related to COVID. First of all, fulfilling growing online demand, this is a very real time issue that we all had to deal with. But the next one was keeping forecasts in sync with changing demand and this is one of those areas where retailers are now finding themselves needing to look at that exogenous or that external data that I mentioned to you. Last year sales were not a good predictor of next year sales, they needed to look at sentiment, they needed to look at the path of the disease, they needed to look at the availability of products, alternate sourcing, global political issues, all of these things get to be pretty important and they affect the forecast. And then finally, managing the movement of the supply through the supply chain so that they could identify bottlenecks. Now, point to one of them which we can all laugh at now because it's kind of funny, it wasn't funny at the time. We ran out of toilet paper (laughs) toilet paper was a big problem. Now there is nothing quite as predictable as toilet paper, it's tied directly to the size of the population and yet we ran out. And the thing we didn't expect when the COVID pandemic hit was that people would panic and when people panic they do funny things. One of the things I do is buy up all the available toilet paper, I'm not quite sure why that happen but it did happen and it drained the supply chain. So retailers needed to be able to see that, they needed to be able to find alternative sources, they needed to be able to do those kinds of things. This gets to the issue of visibility, real-time data, fast data. Tomorrow's challenge is kind of interesting because one of the things that retailers put at the top of their list is improve inventory productivity. The reason that they are interested in this is because they will never spend as much money on anything as they will on inventory and they want the inventory to be targeted to those places where it is most likely to be consumed and not to places where it's least likely to be consumed. So this is trying to solve the issue of getting the right product at the right place at the right time to the right consumer and retailers want to improve this because the dollars are just so big. But in this complex, fast moving world that we live in today is this requires something approaching real-time visibility. They want to be able to monitor the supply chain, the DCs and the warehouses and their picking capacity. We're talking about Echo's, we're talking about Echo's level of decision-making about what's flowing through the supply chain all the way from the manufacturing door to the manufacturer through to consumption. There's two sides of the supply chain and retailers want to look at it. You'll hear retailers and people like me talk about the digital twin, this is where this really becomes important. And again, the digital twin is enabled by IoT and AI analytics. And finally, they need to increase their profitability for online fulfillment. This is a huge issue, for some grocers the volume of online orders went from less than 10% to somewhere north of 40%. And retailers did in 2020 what they needed to do to fulfill those customer orders in the year of the pandemic, that now the expectation that consumers have have been raised significantly. They now expect those features to be available to them all the time and many people really like them. Now retailers need to find out how to do it profitably and one of the first things they need to do is they need to be able to observe the process so that they can find places to optimize. This is out of our recent research and I encourage you to read it. Now when we think about the hard one wisdom that retailers have come up with we think about these things, better visibility has led to better understanding which increases their reaction time which increases their profitability. So what are the opportunities? This is the first place that you'll see something that's very common and in our research, we separate over-performers, who we call retail winners from everybody else, average and under-performers. And we've noticed throughout the life of our company that retail winners don't just do all the same things that others do, they tend to do other things and this shows up in this particular graph. This again is from the same study. So what are the opportunities to address these challenges I mentioned to you in the last slide? First of all, strategic placement of inventory throughout the supply chain to better fulfill customer needs. This is all about being able to observe the supply chain, get the inventory into a position where it can be moved quickly to fast changing demand on the consumer side. A better understanding and reacting to unplanned events that can drive a dramatic change in customer behavior. Again, this is about studying the data, analyzing the data and reacting to the data that comes before the sales transaction. So this is observing the path to purchase, observing things that are happening in the marketplace around the retailer so that they can respond very quickly, a better understanding of the dramatic changes in customer preference and path to purchase as they engage with us. One of the things we all know about consumers now is that they are in control and literally the entire planet is the assortment that's available to them. If they don't like the way they're interacting with you, they will drop you like a hot potato and go to somebody else. And what retailers fear justifiably is the default response to that is to just see if they can find it on Amazon. You don't want this to happen if you're a retailer. So we want to observe how we are interacting with consumers and how well we are meeting their needs. Optimizing omni-channel order fulfillment to improve profitability. We've already mentioned this, retailers did what they needed to do to offer new fulfillment options to consumers. Things like buy online pickup curbside, buy online pickup in-store, buy online pick up at a locker, a direct to consumer, all of those things. Retailers offer those in 2020 because the consumers demand it and needed it. So when retailers are trying to do now is to understand how to do that profitably. And finally, this is important and never goes away is the reduction of waste, shrink within the supply chain. I'm embarrassed to say that when I was a retail executive in the nineties, we were no more certain of consumer demand than anybody else was but we wanted to commit to very high service levels for some of our key categories somewhere approaching 95% and we found the best way to do that was to flood the supply chain with inventory. It sounds irresponsible now, but in those days that was a sure-fire way to make sure that the customer had what she was looking for when she looked for it. You can't do that in today's world, money is too tight and we can't have that inventory sitting around and move to the right places once we discover what the right places. We have to be able to predict, observe, and respond in something much closer to real time. Onto the next slide, the simple message here, again a difference between winners and everybody else. The messages, if you can't see it you can't manage it. And so we asked retailers to identify to what extent an AI enabled supply chain can help their company address some issues. Look at the differences here, they're shocking. Identifying network bottlenecks, this is the toilet paper story I told you about. Over half of retail winners feel that that's very important, only 19% of average and under-performers, no surprise that they're average and under-performers. Visibility into available to sell inventory anywhere within the enterprise, 58% of winners and only 32% of everybody else. And you can go on down the list but you get the just, retail winners understand that they need to be able to see their assets and something approaching real time so that they can make the best decisions possible going forward in something approaching real time. This is the world that we live in today and in order to do that you need to be able to number one, see it and number two, you need to be able to analyze it, and number three, you have to be able to make decisions based on what you saw. Just some closing observations and I hope this was interesting for you. I love talking about this stuff, you can probably tell I'm very passionate about it. But the rapid pace of change in the world today is really underscoring the importance, for example, of location intelligence as a key component of helping businesses to achieve sustainable growth, greater operational effectiveness and resilience, and ultimately your success. So this is really, really critical for retailers to understand and successfully evolving businesses need to accommodate these new consumer shopping behaviors and changes and how products are brought to the market. And in order to do that they need to be able to see people, they need to be able to see their assets, and they need to be able to see their processes in something approaching real time, and then they need to analyze it and based on what they've uncovered, they need to be able to make strategic and operational decision making very quickly. This is the new world we live in, it's a real-time world, it's a sense and respond world and it's the way forward. So Brent, I hope that was interesting for you. I really enjoyed talking about this as I said, we'd love to hear a little bit more. >> Hey, Brian, that was excellent. I always love hearing from RSR because you're so close to what retailers are talking about and the research that your company pulls together. One of the higher level research articles around fast data frankly, is the whole notion of IoT, right? Now many does a lot of work in this space. What I find fascinating based off the recent research is believe it or not, there's $1.2 trillion at stake in retail per year between now and 2025. Now, how's that possible? Well, part of it is because of the Kinsey captures not only traditional retail but also QSRs and entertainment venues, et cetera, that's considered all of retail. But it's a staggering number and it really plays to the effect that real time can have on individual enterprises, in this case we're talking of course about retail. So a staggering number and if you think about it, from streaming video to sensors, to beacons, RFID, robotics, autonomous vehicles retailers are asking today, even pizza delivery and autonomous vehicles. If you think about it, it shouldn't be that shocking, but when they were looking at 12 different industries, retail became like the number three out of 12 and there's a lot of other big industries that will be leveraging IoT in the next four years. So retailers in the past have been traditionally a little stodgy about their spend in data and analytics. I think retailers in general have got the religion that this is what it's going to take to compete in today's world, especially in a global economy and IoT really is the next frontier, which is kind of the definition of fast data. So I just wanted to share just a few examples or exemplars of retailers that are leveraging the Cloudera technology today. So now they pay for advertisement at the end of this, right? So what is Cloudera bringing to market here? So across all retail verticals, if we look at, for example, a well-known global mass virtual retailer, they're leveraging Cloudera data flow which is our solution to move data from point to point in wicked fast space. So it's open source technology that was originally developed by the NSA. So it is best to class movement of data from an ingest standpoint, but we're also able to help the round trip. So we'll pull up sensor data off all the refrigeration units for this particular retailer, they'll hit it up against the product lifecycle table, they'll understand temperature fluctuations of 10, 20 degrees based on fresh food products that are in the store, what adjustments might need to be made because frankly store operators, they'll never know refrigeration, they'll know if a cooler goes down and they'll have to react quickly, but they won't know that 10, 20 degree temperature changes have happened overnight. So this particular customer leverages further data flow to understand temperature fluctuations, the impact on the product life cycle and the roundtrip communication back to the individual department manager, let's say a produce department manager, deli manager, meat manager. Hey, you had a 20 degree drop in temperature, we suggest you lower the price on these products that we know are in that cooler for the next couple of days by 20%. So you don't have to worry about freshness issues and or potential shrink. The grocery with fresh product, if you don't sell it, you smell it, you throw it away, it's cost to the bottom line. So critically important and tremendous ROI opportunity that we're helping to enable there. From a leading global drugstore retailer, so this is more about data processing and we're excited of the recent partnership with the Nvidia. So fast data isn't always at the edge with IoT, it's also about workloads. And in retail, if you are processing your customer profiles or segmentation like intra day, you will never achieve personalization, you will never achieve one-on-one communications with retailers or with customers, and why is that? Because customers in many cases are touching your brand several times a week. So if taking you a week or longer to process your segmentation schemes, you've already lost and you'll never achieve personalization, in fact, you may offend customers by offers you might push out based on what they just bought yesterday you had no idea of it. So that's what we're really excited about, again with the computation speed that Nvidia brings to Cloudera. We're already doing this today, we've already been providing levels of exponential speed and processing data, but when Nvidia brings to the party is course GPUs right, which is another exponential improvement to processing workloads like demand forecast, customer profiles. These things need to happen behind the scenes in the back office much faster than retailers have been doing in the past. That's just the world we all live in today. And then finally, from a proximity marketing standpoint or just from an in-store operations standpoint, retailers are leveraging Cloudera today, not only data flow but also of course our compute and storage platform and ML, et cetera, to understand what's happening in store. It's almost like the metrics that we used to look at in the past in terms of conversion and traffic, all those metrics are now moving into the physical world. If you can leverage computer vision in streaming video, to understand how customers are traversing your store, how much time they're standing in front of the display, how much time they're standing in checkout line, you can now start to understand how to better merchandise the store, where the hotspots are, how to in real time improve your customer service. And from a proximity marketing standpoint, understand how to engage with the customer for right at the moment of truth, right, when they're right there in front of the particular department or category, upward leveraging mobile device. So that's the world of fast data in retail and just kind of a summary in just a few examples of how folks are leveraging Cloudera today. From an overall platform standpoint of course, Cloudera is an enterprise data platform, right? So we're helping to enable the entire data life cycle, so we're not a data warehouse, we're much more than that. So we have solutions to ingest data from the Edge, from IoT, leading practice solutions to bring it in. We also have experiences to help leverage the analytic capabilities of data engineering, data science, analytics and reporting. We're not encroaching upon the legacy solutions that many retailers have today, we're providing a platform that's open source that helps weave all this mess together that existed retail today from legacy systems because no retailer frankly is going to rip and replace a lot of stuff that they have today. Right. And the other thing the Cloudera brings to market is this whole notion of on-prem hybrid cloud and multicloud, right. So our whole culture has been built around open source technology as the company that provides most of the source code to the Apache network around all these open source technologies. We're kind of religious about open source and lack of vendor lock-in, maybe to our fault, but as a company we pull that together from a data platform standpoint so it's not a rip or replace situation. It's like helping to connect legacy systems, data and analytics, weaving that whole story together to be able to solve this whole data life cycle from beginning to end. And then finally, I want to thank everyone for joining today's session, I hope you found it informative. I can't thank Brian Kilcourse enough, like he's my trusted friend in terms of what's going on in the industry. He has much broader reach of course in talking to a lot of our partners in other technology companies out there as well. But I really appreciate everyone joining the session, and Brian, I'm going to kind of leave it open to you to any closing comments that you might have based on what we're talking about today in terms of fast data and retail. >> First of all, thank you, Brent. And this is an exciting time to be in this industry. And I'll just leave it with this. The reason that we are talking about these things is because we can, the technology has advanced remarkably in the last five years. Some of this data has been out there for a lot longer than that and it frankly wasn't even usable. But what we're really talking about is increasing the cycle time for decisions, making them go faster and faster so that we can respond to consumer expectations and delight them in ways that make us a trusted provider of their lifestyle needs. So this is really a good time to be a retailer, a real great time to be servicing the retail technology community and I'm glad to be a part of it and I'm glad to be working with you. So thank you, Brent. >> Yeah, of course, Brian. And one of the exciting things for me too, I've being in the industry as long as I have and being a former retailer is it's really exciting for me to see retailers actually spending money on data and IT for a change, right? (Brian laughs) They've all kind of come to this final pinnacle of this is what it's going to take to compete. You and I talked to a lot of colleagues, even salespeople within Cloudera, like, oh, retail, very stodgy, slow to move. That's not the case anymore. >> No. >> Everyone gets the religion of data and analytics and the value of that. And what's exciting for me to see as all this infusion of immense talent within the industry that we couldn't see years ago, Brian. I mean, retailers are like pulling people from some of the greatest tech companies out there, right? From a data science, data engineering standpoint, application developers. Retail is really getting its legs right now in terms of go to market and the leverage of data and analytics, which to me is very exciting. >> Well, you're right. I mean, I became a CIO around the time that point of sale and data warehouses were starting to happen, data cubes and all those kinds of things. And I never thought I would see a change that dramatic as the industry experience back in those days, 1989, 1990, this changed doors that, but the good news is again, as the technology is capable, we're talking about making technology and information available to retail decision-makers that consumers carry around in their purses and pockets as they're right now today. So the question is, are you going to utilize it to win or are you going to get beaten? That's really what it boils down to. >> Yeah, for sure. Hey, thanks everyone. We'll wrap up, I know we ran a little bit long, but appreciate everyone hanging in here with us. We hope you enjoyed the session. Our contact information is right there on the screen, feel free to reach out to either Brian and I. You can go to cloudera.com, we even have joint sponsored papers with RSR, you can download there as well as other eBooks, other assets that are available if you're interested. So thanks again, everyone for joining and really appreciate you taking the time today.

>>Thank you and good morning or afternoon, everyone, depending on where you're coming to us from and welcome to today's breakout session, fast data, a retail industry business imperative. My name is Brent Bedell, global managing director of retail, consumer bids here at Cloudera and today's hosts joining today. Joining me today is our feature speaker Brian Hill course managing partner from RSR. We'll be sharing insights and implications from recently completed research across retailers of all sizes in vertical segments. At the end of today's session, I'll share a brief overview on what I personally learned from retailers and how Cloudera continues to support retail data analytic requirements, and specifically around streaming data, ingest analytics, automation for customers around the world. There really is the next step up in terms of what's happening with data analytics today. So let's get started. So I thought it'd be helpful to provide some background first on how Clare to Cloudera is supporting and retail industry leaders specifically how they're leveraging Cloudera for leading practice data analytics use cases primarily across four key business pillars. >>And these will be very familiar to, to those in the industry. Personalize interactions of course, plays heavily into e-commerce and marketing, whether that's developing customer profiles, understanding the OB omni-channel journey, moving into the merchandising line of business focused on localized promotional planning, forecasting demand, forecast accuracy, then into supply chain where inventory visibility is becoming more and more critical today, whether it's around fulfillment or just understanding where your stuff is from a customer perspective. And obviously in and outbound route optimization right now, as retailers are taking control of actual delivery, whether it's to a physical store location or to the consumer. And then finally, uh, which is pretty exciting to me as a former store operator, you know, what's happening with physical brick and mortar right now, especially for traditional retailers. Uh, the whole re-imagining of stores right now is on fire in a lot of focus because, you know, frankly, this is where fulfillment is happening. >>Um, this is where customers, you know, still 80% of revenue is driven through retail, through physical brick and mortar. So right now store operations is getting more focused and I would say it probably is had and decades. Uh, and a lot of has to do for us with IOT data and analytics in the new technologies that really help, uh, drive, uh, benefits for retailers from a brick and mortar standpoint. And then, and then finally, um, you know, to wrap up before handing off to Brian, um, as you'll see, you know, all of these, these lines of businesses are raw, really experiencing the need for speed, uh, you know, fast data. So we're, we're moving beyond just discovery analytics. You don't things that happened five, six years ago with big data, et cetera. And we're really moving into real time capabilities because that's really where the difference makers are. >>That's where the competitive differentiation as across all of these, uh, you know, lines of business and these four key pillars within retail, um, the dependency on fast data is, is evident. Um, and it's something that we all read, you know, you know, in terms of those that are students of the industry, if you will, um, you know, that we're all focused on in terms of bringing value to the individual, uh, lines of business, but more importantly to the overall enterprise. So without further ado, I, I really want to, uh, have Brian speak here as a, as a third party analyst. You know, he, he's close in touch with what's going on, retail talking to all the solution providers, all the key retailers about what's important, what's on their plate. What are they focusing on right now in terms of fast data and how that could potentially make a difference for them going forward? So, Brian, uh, off to you, >>Well, thanks, Brent. I appreciate the introduction. And I was thinking, as you were talking, what is fast data? Well, data is fast. It is fast data it's stuff that comes at you very quickly. When I think about the decision cycles in retail, they were, they were, they were time phased and there was a time when we could only make a decision perhaps once a month and then met once a week and then once a day, and then intraday fast data is data that's coming at you and something approaching real time. And we'll explain why that's important in just a second. But first I want to share with you just a little bit about RSR. We've been in business now for 14 years. And what we do is we studied the business use cases that drive the adoption of technology in retail. We come from the retail industry, I was a retail technologist, my entire working life. >>And so we started this company. So I'm, I have a built in bias, of course, and that is that the difference between the winners in the retail world and in fact, in the entire business world and everybody else is how they value the strategic importance of information, and really that's where the battle is being fought today. We'll talk a little bit about that. So anyway, uh, one other thing about RSR research, our research is free to the entire world. Um, we don't, we don't have a paywall. You have to get behind. All you have to do is sign into our website, uh, identify yourself and all of our research, including these two reports that we're showing on the screen now are available to you. And we'd love to hear your comments. So when we talk about data, there's a lot of business implications to what we're trying to do with fast data and as being driven by the real world. >>Uh, we saw a lot of evidence of that during the COVID pandemic in 2020, when people had to make many decisions very, very quickly, for example, a simple one. Uh, do I redirect my replenishments to store B because store a is impacted by the pandemic, those kinds of things. Uh, these two drawings are actually from a book that came out in 1997. It was a really important book for me personally is by a guy named Steven Hegel. And it was the name of the book was the adaptive enterprise. When you think about your business model, um, and you think about the retail business model, most of those businesses are what you see on the left. First of all, the mission of the business doesn't change much at all. It changes once in a generation or maybe once in a lifetime, um, but it it's established quite early. >>And then from that point on it's, uh, basically a wash rinse and repeat cycle. You do the things that you do over and over and over again, year in and year out season in and season out. And the most important piece of information that you have is the transaction data from the last cycle. So a Brent knows this from his experience as a, as a retailer, the baseline for next year's forecast is last year's performance. And this is transactional in nature. It's typically pulled from your ERP or from your best of breed solution set on the right is where the world is really going. And before we get into the details of this, I'll just use a real example. I'm I'm sure like, like me, you've watched the path of hurricanes as they go up to the Florida coast. And one of the things you might've noticed is that there's several different possible paths. >>These are models, and you'll hear a lot about models. When you talk to people in the AI world, these are models based on lots and lots of information that they're getting from Noah and from the oceanographic people and all those kinds of folks to understand the likely path of the hurricane, based on their analysis, the people who watch these things will choose the most likely paths and they will warn communities to lock down and do whatever they need to do. And then they see as the, as the real hurricane progresses, they will see if it's following that path, or if it's varying, it's going down a different path and based on that, they will adapt to a new model. And that is what I'm talking about here now that not everything is of course is life and death as, as a hurricane. But it's basically the same concept what's happening is you have your internal data that you've had since this, a command and control model that we've mentioned on the left, and you're taking an external data from the world around you, and you're using that to make snap decisions or quick decisions based on what you see, what's observable on the outside, back to my COVID example, um, when people were tracking the path of the pandemic through communities, they learn that customers or consumers would favor certain stores to pick up their, what they needed to get. >>So they would avoid some stores and they would favor other stores. And that would cause smart retailers to redirect the replenishments on very fast cycles to those stores where the consumers are most likely to be. They also did the same thing for employees. Uh, they wanted to know where they could get their employees to service these customers. How far away were they, were they in a community that was impacted or were they relatively safe? These are the decisions that were being made in real time based on the information that they were getting from the marketplace around them. So, first of all, there's a context for these decisions. There's a purpose and the bounds of the adaptive structure, and then there's a coordination of capabilities in real time. And that creates an internal feedback loop, but there's also an external feedback loop. This is more of an ecosystem view. >>And based on those two, those two inputs what's happening internally, what your performance is internally and how your community around you is reacting to what you're providing. You make adjustments as necessary. And this is the essence of the adaptive enterprise. Engineers might call this a sense and respond model. Um, and that's where retail is going. But what's essential to that is information and information, not just about the products that you sell or the stores that you sell it in, or the employees that you have on the sales floor or the number of market baskets you've completed in the day, but something much, much more. Um, if you will, a twin, a digital twin of the physical assets of your business, all of your physical assets, the people, the products, the customers, the buildings, the rolling stock, everything, everything. And if you can create a digital equivalent of a physical thing, you can then analyze it. >>And if you can analyze it, you can make decisions much, much more quickly. So this is what's happening with the predict pivot based on what you see, and then, because it's an intrinsically more complicated model to automate, decision-making where it makes sense to do so. That's pretty complicated. And I talk about new data. And as I said earlier, the old data is all transactional in nature. Mostly about sales. Retail has been a wash in sales data for as long as I can remember throw, they throw most of it away, but they do keep enough to create the forecast the next for the next business cycle. But there's all kinds of new information that they need to be thinking about. And a lot of this is from the outside world. And a lot of this is non-transactional nature. So let's just take a look at some of them, competitive information. >>Those are always interested in what the competitor is up to. What are they promoting? How well are they they doing, where are they? What kind of traffic are they generating sudden and stuff, significant changes in customer behaviors and sentiment COVID is a perfect example of something that would cause this consumers changing their behaviors very quickly. And we have the ability to, to observe this because in a great majority of cases, nowadays retailers have observed that customers start their, uh, shopping journey in the digital space. As a matter of fact, Google recently came out and said, 60%, 63% of all, all sales transactions begin in the digital domain. Even if many of them end up in the store. So we have the ability to observe changes in consumer behavior. What are they looking at? When are they looking at it? How long do they spend looking at it? >>What else are they looking at while they're, while they're doing that? What are the, what is the outcome of that market metrics? Certainly what's going on in the marketplace around you? A good idea. Example of this might be something related to a sporting event. If you've planned based on normal demand and for, for your store. And there's a big sporting event, like a football match or a baseball game, suddenly you're going to see a spike in demand. So understanding what's going on in the market is really important. Location, demographics and psychographics, demographics have always been important to retailers, but now we're talking about dynamic demographics, what customers, or what consumers are, are in your market, in something approaching real time, psychographics has more to do with their attitudes. What kind of folks are, are, are in them in a particular marketplace? What do they think about what do they favor? >>And all those kinds of interesting deep tales, real-time environmental and social incidents. Of course, I mentioned hurricanes. And so that's fairly, self-evident disruptive events, sporting events, et cetera. These are all real. And then we get the real time internet of things. These are, these are RFID sensors, beacons, video, et cetera. There's all kinds of stuff. And this is where, yeah, it's interesting. This is where the supply chain people will start talking about the difference, little twin to their physical world. If you can't say something, you can manage it. And retailers want to be able to manage things in real time. So IOT, along with it, the analytics and the data that's generated is really, really important for them going forward, community health. We've been talking a lot about that, the progression of the flu, et cetera, et cetera, uh, business schedules, commute patterns, school schedules, and whether these are all external data that are interesting to retailers and can help them to make better operational in something approaching real time. >>I mentioned the automation of decision making. This is a chart from Gardner, and I'd love to share with you. It's a really good one because it describes very simply what we're talking about. And it also describes where the inflection of new technology happens. If you look on the left there's data, we have lots and lots of data. We're getting more data all the time, retailers for a long time. Now, since certainly since the seventies or eighties have been using data to describe what happened, this is the retrospective analysis that we're all very familiar with, uh, data cubes and those kinds of things. And based on that, the human makes some decisions about what they're going to do going forward. Um, sometime in the not too distant past, this data was started to be used to make diagnostic decisions, not only what happened, but why did it happen? >>And me might think of this as, for example, if sales were depressed for a certain product, was it because we had another product on sale that day, that's a good example of fairly straightforward diagnostics. We then move forward to what we might think of as predictive analytics. And this was based on what happened in the past and why it happened in the past. This is what's likely to happen in the future. You might think of this as, for example, halo effect or, or the cannibalization effect of your category plans. If you're, if you happen to be a grocer and based on that, the human will make a decision as to what they need to do next then came along AI, and I don't want to oversell AI here. AI is a new way for us to examine lots and lots of data, particularly unstructured data AI. >>If I could simplify it to its maximum extent, it essentially is a data tool that allows you to see patterns in data, which might be interesting. It's very good at sifting through huge data sets of unstructured data and detecting statistically significant patterns. It gets deeper than that, of course, because it uses math instead of rules. So instead of an if then, or else a statement that we might've used with our structured data, we use the math to detect these patterns in unstructured data. And based on those, we can make some models. For example, uh, my guy in my, in my, uh, just turned 70 on my 70 year old man, I'm a white guy. I live in California. I have a certain income and a certain educational level. I'm likely to behave in this way based on a model that's pretty simplistic. But based on that, you can see that. >>And when another person who meets my psychographics, my demographics, my age group, my income level and all the rest, um, you, they might, they might be expected to make a certain action. And so this is where prescriptive really comes into play. Um, AI makes that possible. And then finally, when you start to think about moving closer to the customer on something, approaching a personalized level, a one-to-one level, you, you suddenly find yourself in this situation of having to make not thousands of decisions, but tens of millions of decisions. And that's when the automation of decision-making really gets to be pretty important. So this is all interesting stuff, and I don't want to oversell it. It's exciting. And it's new. It's just the latest turn of the technology screw. And it allows us to use this new data to basically automate decision-making in the business, in something approaching real time so that we can be much, much more responsive to real-time conditions in the marketplace. >>Very exciting. So I hope this is interesting. This is a piece of data from one of our recent pieces of research. Uh, this happens to be from a location analytics study. We just published last week and we asked retailers, what are the big challenges what's been going on in the last 12 months for them? And what's likely to be happening for them in the next few years. And it's just fascinating because it speaks to the need for faster decision-making there. The challenges in the last 12 months were all related to COVID. First of all, fulfilling growing online demand. This is a very, very real time issue that we all had to deal with. But the next one was keeping forecasts in sync with changing demand. And this is one of those areas where retailers are now finding themselves, needing to look at that exoticness for that external data that I mentioned to you last year, sales were not a good predictor of next year of sales. >>They needed to look at sentiment. They needed to look at the path of the disease. They needed to look at the availability of products, alternate sourcing, global political issues. All of these things get to be pretty important and they affect the forecast. And then finally managing a supply them the movement of the supply through the supply chain so that they could identify bottlenecks now, point to one of them, which we can all laugh at now because it's kind of funny. It wasn't funny at the time we ran out of toilet paper, toilet paper was a big problem. Now there is nothing quite as predictable as toilet paper, it's tied directly to the size of the population. And yet we ran out and the thing we didn't expect when the COVID pandemic hit was that people would panic. And when people panic, they do funny things. >>One of the things I do is buy up all the available toilet paper. I'm not quite sure why that happened. Um, but it did happen and it drained the supply chain. So retailers needed to be able to see that they needed to be able to find alternative sources. They needed to be able to do those kinds of things. This gets to the issue of visibility, real time data, fast data tomorrow's challenge. It's kind of interesting because one of the things that they've retailers put at the top of their list is improved inventory productivity. Uh, the reason that they are interested in this is because then we'll never spend as much money, anything as they will on inventory. And they want the inventory to be targeted to those places where it is most likely to be consumed and not to places where it's least likely to be consumed. >>So this is trying to solve the issue of getting the right product at the right place at the right time to the right consumer and retailers want to improve this because the dollars are just so big, but in this complex, fast moving world that we live in today, it's this requires something approaching real-time visibility. They want to be able to monitor the supply chain, the DCS and the warehouses. And they're picking capacity. We're talking about each of us, we're talking about each his level. Decision-making about what's flowing through the supply chain all the way from the, from the manufacturing doctor, the manufacturer through to consumption. There's two sides of the supply chain and retailers want to look at it, you'll hear retailers and, and people like me talk about the digital twin. This is where this really becomes important. And again, the digital twin is, is enabled by IOT and AI analytics. >>And finally they need to re to increase their profitability for online fulfillment. Uh, this is a huge issue, uh, for some grocers, the volume of online orders went from less than 10% to somewhere north of 40%. And retailers did in 2020, what they needed to do to fulfill those customer orders in the, in the year of the pandemic, that now the expectation that consumers have have been raised significantly. They now expect those, those features to be available to them all the time. And many people really liked them. Now retailers need to find out how to do it profitably. And one of the first things they need to do is they need to be able to observe the process so that they can find places to optimize. This is out of our recent research and I encourage you to read it. >>And when we think about the hard one wisdoms that retailers have come up with, we think about these things better visibility has led to better understanding, which increases their reaction time, which increases their profitability. So what are the opportunities? This is the first place that you'll see something that's very common. And in our research, we separate over performers, who we call retail winners from everybody else, average and under-performers, and we've noticed throughout the life of our company, that retail winners, don't just do all the same things that others do. They tend to do other things. And this shows up in this particular graph, this again is from the same study. So what are the opportunities to, to address these challenges? I mentioned to you in the last slide, first of all, strategic placement of inventory throughout the supply chain to better fulfill customer needs. This is all about being able to observe the supply chain, get the inventory into a position where it can be moved quickly to fast changing demand. >>And on the consumer side, a better understanding and reacting to unplanned events that can drive a dramatic change in customer behavior. Again, this is about studying the data, analyzing the data and reacting to the data that comes before the sales transaction. So this is observing the path to purchase observing things that are happening in the marketplace around the retailer, so that they can respond very quickly, a better understanding of the dramatic changes in customer preference and path to purchase. As they engage with us. One of the things we, all we all know about consumers now is that they are in control and the literally the entire planet is the assortment that's available to them. If they don't like the way they're interacting with you, they will drop you like a hot potato and go to somebody else. And what retailers fear justifiably is the default response to that is to just see if they can find it on Amazon. >>You don't want this to happen if you're a retailer. So we want to observe how we are interacting with consumers and how well we are meeting their needs, optimizing omni-channel order fulfillment to improve profitability. We've already mentioned this, uh, retailers did what they needed to do to offer new fulfillment options to consumers. Things like buy online pickup curbside, buy online pickup in store, buy online, pick up at a locker, a direct to consumer all of those things. Retailers offer those in 2020 because the consumers demand it and needed it. So when retailers are trying to do now is to understand how to do that profitably. And finally, this is important. It never goes away. Is the reduction of waste shrink within the supply chain? Um, I'm embarrassed to say that when I was a retail executive in the nineties, uh, we were no more certain of consumer demand than anybody else was, but we, we wanted to commit to very high service levels for some of our key county categories somewhere approaching 95%. >>And we found the best way to do that was to flood the supply chain with inventory. Uh, it sounds irresponsible now, but in those days, that was a sure-fire way to make sure that the customer had what she was looking for when she looked for it. You can't do that in today's world. Money is too tight and we can't have that, uh, inventory sitting around and move to the right places. Once we discovered what the right place is, we have to be able to predict, observe and respond in something much closer to your time. One of the next slide, um, the simple message here, again, a difference between winners and everybody else, the messages, if you can't see it, you can't manage it. And so we asked retailers to identify, to what extent an AI enabled supply chain can help their company address some issues. >>Look at the differences here. They're shocking identifying network bottlenecks. This is the toilet paper story I told you about over half of retail winners, uh, feel that that's very important. Only 19% of average and under performers, no surprise that their average and under-performers visibility into available to sell inventory anywhere within the enterprise, 58% of winners and only 32% of everybody else. And you can go on down the list, but you get the just retail winners, understand that they need to be able to see their assets and something approaching real time so that they can make the best decisions possible going forward in something approaching real time. This is the world that we live in today. And in order to do that, you need to be able to number one, see it. And number two, you need to be able to analyze it. And number three, you have to be able to make decisions based on what you saw, just some closing observations on. >>And I hope this was interesting for you. I love talking about this stuff. You can probably tell I'm very passionate about it, but the rapid pace of change in the world today is really underscoring the importance. For example, of location intelligence, as a key component of helping businesses to achieve sustainable growth, greater operational effectiveness and resilience, and ultimately your success. So this is really, really critical for retailers to understand and successfully evolving businesses need to accommodate these new consumer shopping behaviors and changes in how products are brought to the market. So that, and in order to do that, they need to be able to see people. They need to be able to see their assets, and they need to be able to see their processes in something approaching real time, and then they need to analyze it. And based on what they've uncovered, they need to be able to make strategic and operational decision making very quickly. This is the new world we live in. It's a real-time world. It's a, it's a sense and respond world and it's the way forward. So, Brent, I hope that was interesting for you. I really enjoyed talking about this, as I said, we'd love to hear a little bit more. >>Hey, Brian, that was excellent. You know, I always love me love hearing from RSR because you're so close to what retailers are talking about and the research that your company pulls together. Um, you know, one of the higher level research articles around, uh, fast data frankly, is the whole notion of IOT, right? And he does a lot of work in this space. Um, what I find fascinating based off the recent research is believe it or not, there's $1.2 trillion at stake in retail per year, between now and 2025. Now, how is that possible? Well, part of it is because the Kinsey captures not only traditional retail, but also QSRs and entertainment then use et cetera. That's considered all of retail, but it's a staggering number. And it really plays to the effect that real-time can have on individual enterprises. In this case, we're talking of course, about retail. >>So a staggering number. And if you think about it from streaming video to sensors, to beacons, RFID robotics, autonomous vehicles, retailers are testing today, even pizza delivery, you know, autonomous vehicle. Well, if you think about it, it shouldn't be that shocking. Um, but when they were looking at 12 different industries, retail became like the number three out of 12, and there's a lot of other big industries that will be leveraging IOT in the next four years. So, um, so retailers in the past have been traditionally a little stodgy about their spend in data and analytics. Um, I think retailers in general have got the religion that this is what it's going to take to compete in today's world, especially in a global economy. And in IOT really is the next frontier, which is kind of the definition of fast data. Um, so I, I just wanted to share just a few examples or exemplars of, of retailers that are leveraging Cloudera technology today. >>So now, so now the paid for advertisement at the end of this, right? So, so, you know, so what bringing to market here. So, you know, across all retail, uh, verticals, you know, if we look at, you know, for example, a well-known global mass virtual retailer, you know, they're leveraging Cloudera data flow, which is our solution to move data from point to point in wicked fast space. So it's open source technology that was originally developed by the NSA. So, um, it is best to class movement of data from an ingest standpoint, but we're also able to help the roundtrip. So we'll pull the sensor data off all the refrigeration units for this particular retailer. They'll hit it up against the product lifecycle table. They'll understand, you know, temperature fluctuations of 10, 20 degrees based on, you know, fresh food products that are in the store, what adjustments might need to be made because frankly store operators, they'll never know refrigeration don't know if a cooler goes down and they'll have to react quickly, but they won't know that 10, 20 degree temperature changes have happened overnight. >>So this particular customer leverages father a data flow understand temperature, fluctuations the impact on the product life cycle and the round trip communication back to the individual department manager, let's say a produce department manager, deli manager, meat manager, Hey, you had, you know, a 20 degree drop in temperature. We suggest you lower the price on these products that we know are in that cooler, um, for the next couple of days by 20%. So you don't have to worry, tell me about freshness issues and or potential shrink. So, you know, the grocery with fresh product, if you don't sell it, you smell it, you throw it away. It's lost to the bottom line. So, you know, critically important and, you know, tremendous ROI opportunity that we're helping to enable there, uh, from a, a leading global drugstore retailer. So this is more about data processing and, you know, we're excited to, you know, the recent partnership with the Vidia. >>So fast data, isn't always at the edge of IOT. It's also about workloads. And in retail, if you are processing your customer profiles or segmentation like intra day, you will ever achieve personalization. You will never achieve one-on-one communications with readers killers or with customers. And why is that? Because customers in many cases are touching your brand several times a week. So taking you a week or longer to process your segmentation schemes, you've already lost and you'll never achieve personalization in frack. In fact, you may offend customers by offering. You might push out based on what they just bought yesterday. You had no idea of it. So, you know, that's what we're really excited about. Uh, again, with, with the computation speed, then the video brings to, to Cloudera, we're already doing this today already, you know, been providing levels, exponential speed and processing data. But when the video brings to the party is course GPU's right, which is another exponential improvement, uh, to processing workloads like demand forecast, customer profiles. >>These things need to happen behind the scenes in the back office, much faster than retailers have been doing in the past. Um, that's just the world we all live in today. And then finally, um, you know, proximity marketing standpoint, or just from an in-store operation standpoint, you know, retailers are leveraging Cloudera today, not only data flow, but also of course our compute and storage platform and ML, et cetera, uh, to understand what's happening in store. It's almost like the metrics that we used to look at in the past in terms of conversion and traffic, all those metrics are now moving into the physical world. If you can leverage computer vision in streaming video, to understand how customers are traversing your store, how much time they're standing in front of the display, how much time they're standing in checkout line. Um, you can now start to understand how to better merchandise the store, um, where the hotspots are, how to in real time improve your customer service. >>And from a proximity marketing standpoint, understand how to engage with the customer right at the moment of truth, right? When they're right there, um, in front of a particular department or category, you know, of course leveraging mobile devices. So that's the world of fast data in retail and just kind of a summary in just a few examples of how folks are leveraging Cloudera today. Um, you know, from an overall platform standpoint, of course, father as an enterprise data platform, right? So, you know, we're, we're helping to the entire data life cycle. So we're not a data warehouse. Um, we're much more than that. So we have solutions to ingest data from the edge from IOT leading practice solutions to bring it in. We also have experiences to help, you know, leverage the analytic capabilities of, uh, data engineering, data science, um, analytics and reporting. Uh, we're not, uh, you know, we're not, we're not encroaching upon the legacy solutions that many retailers have today. >>We're providing a platform, this open source that helps weave all of this mess together that existed retail today from legacy systems because no retailer, frankly, is going to rip and replace a lot of stuff that they have today. Right. And the other thing that Cloudera brings to market is this whole notion of on-prem hybrid cloud and multi-cloud right. So our whole, our whole culture has been built around open source technology as the company that provides most of the source code to the Apache network around all these open source technologies. Um, we're kind of religious about open source and lack of vendor lock-in, uh, maybe to our fault. Uh, but as a company, we pull that together from a data platform standpoint. So it's not a rip and replace situation. It's like helping to connect legacy systems, data and analytics, um, you know, weaving that whole story together to be able to solve this whole data life cycle from beginning to end. >>And then finally, you know, just, you know, I want to thank everyone for joining today's session. I hope you found it informative. I can't say Brian killed course enough. Um, you know, he's my trusted friend in terms of what's going on in the industry. He has much broader reach of course, uh, in talking to a lot of our partners in, in, in, in other, uh, technology companies out there as well. But I really appreciate everyone joining the session and Brian, I'm going to kind of leave it open to you to, you know, any closing comments that you might have based on, you know, what we're talking about today in terms of fast data and retail. >>First of all, thank you, Brent. Um, and this is an exciting time to be in this industry. Um, and I'll just leave it with this. The reason that we are talking about these things is because we can, the technology has advanced remarkably in the last five years. Some of this data has been out there for a lot longer than that in it, frankly wasn't even usable. Um, but what we're really talking about is increasing the cycle time for decisions, making them go faster and faster so that we can respond to consumer expectations and delight them in ways that that make us a trusted provider of their life, their lifestyle needs. So this is really a good time to be a retailer, a real great time to be servicing the retail technology community. And I'm glad to be a part of it. And I was glad to be working with you. So thank you, Brian. >>Yeah, of course, Brian, and one of the exciting things for me to not being in the industry, as long as I have and being a former retailer is it's really exciting for me to see retailers actually spending money on data and it for a change, right? They've all kind of come to this final pinnacle of this is what it's going to take to compete. Um, you know, you know, and I talked to, you know, a lot of colleagues, even, even salespeople within Cloudera, I like, oh, retail, very stodgy, you know, slow to move. That's not the case anymore. Um, you know, religion is everyone's, everyone gets the religion of data and analytics and the value of that. And what's exciting for me to see as all this infusion of immense talent within the industry years ago, Brian, I mean, you know, retailers are like, you know, pulling people from some of the, you know, the greatest, uh, tech companies out there, right? From a data science data engineering standpoint, application developers, um, retail is really getting this legs right now in terms of, you know, go to market and in the leverage of data and analytics, which to me is very exciting. Well, >>You're right. I mean, I, I became a CIO around the time that, uh, point of sale and data warehouses were starting to happen data cubes and all those kinds of things. And I never thought I would see a change that dramatic, uh, as the industry experience back in those days, 19 89, 19 90, this changed doors that, but the good news is again, as the technology is capable, uh, it's, it's, we're talking about making technology and information available to, to retail decision-makers that consumers carry around in their pocket purses and pockets is there right now today. Um, so the, the, the question is, are you going to utilize it to win or are you going to get beaten? That's really what it boils down to. Yeah, >>For sure. Uh, Hey, thanks everyone. We'll wrap up. I know we ran a little bit long, but, uh, appreciate, uh, everyone, uh, hanging in there with us. We hope you enjoyed the session. The archive contact information is right there on the screen. Feel free to reach out to either Brian and I. You can go to cloudera.com. Uh, we even have, you know, joint sponsored papers with RSR. You can download there as well as eBooks and other assets that are available if you're interested. So thanks again, everyone for joining and really appreciate you taking the time. >>Hello everyone. And thanks for joining us today. My name is Brent Bedell, managing director retail, consumer goods here at Cloudera. Cloudera is very proud to be partnering with companies like three soft to provide data and analytic capabilities for over 200 retailers across the world and understanding why demand forecasting could be considered the heartbeat of retail. And what's at stake is really no mystery to most, to most retailers. And really just a quick level set before handing this over to my good friend, uh, Camille three soft, um, you know, IDC Gartner. Um, many other analysts have kind of summed up an average, uh, here that I thought would be important to share just to level set the importance of demand forecasting or retail. And what's at stake. I mean the combined business value for retailers leveraging AI and IOT. So this is above and beyond. What demand forecasting has been in the past is a $371 billion opportunity. >>And what's critically important to understand about demand forecasting. Is it directly impacts both the top line and the bottom line of retail. So how does it affect the top line retailers that leverage AI and IOT for demand forecasting are seeing average revenue increases of 2% and think of that as addressing the in stock or out of stock issue in retail and retail is become much more complex now, and that is no longer just brick and mortar, of course, but it's fulfillment centers driven by e-commerce. So inventory is now having to be spread over multiple channels. Being able to leverage AI and IOT is driving 2% average revenue increases. Now, if you think about the size of most retailers or the average retailer that on its face is worth millions of dollars of improvement for any individual retailer on top of that is balancing your inventory, getting the right product in the right place and having productive inventory. >>And that is the bottom line. So the average inventory reduction, leveraging AI and IOT as the analyst have found, and frankly, having spent time in this space myself in the past a 15% average inventory reduction is significant for retailers not being overstocked on product in the wrong place at the wrong time. And it touches everything from replenishment to out-of-stocks labor planning and customer engagement for purposes of today's conversation. We're going to focus on inventory and inventory optimization and reducing out-of-stocks. And of course, even small incremental improvements. I mentioned before in demand forecast accuracy have millions of dollars of direct business impact, especially when it comes to inventory optimization. Okay. So without further ado, I would like to now introduce Dr. Camille Volker to share with you what his team has been up to. And some of the amazing things that are driving at top retailers today. So over to you, Camille, >>Uh, I'm happy to be here and I'm happy to speak to you, uh, about, uh, what we, uh, deliver to our customers. But let me first, uh, introduce three soft. We are a 100 person company based in Europe, in Southern Poland. Uh, and we, uh, with 18 years of experience specialized in providing what we call a data driven business approach, uh, to our customers, our roots are in the solutions in the services. We originally started as a software house. And on top of that, we build our solutions. We've been automation that you get the software for biggest enterprises in Poland, further, we understood the meaning of data and, and data management and how it can be translated into business profits. Adding artificial intelligence on top of that, um, makes our solutions portfolio holistic, which enables us to realize very complex projects, which, uh, leverage all of those three pillars of our business. However, in the recent time, we also understood that services is something which only the best and biggest companies can afford at scale. And we believe that the future of retail, uh, demon forecasting is in the product solutions. So that's why we created occupy our AI platform for data driven retail. That also covers this area that we talked about today. >>I'm personally proud to be responsible for our technology partnerships with other on Microsoft. Uh, it's a great pleasure to work with such great companies and to be able to, uh, delivered a solution store customers together based on the common trust and understanding of the business, uh, which cumulates at customer success at the end. So why, why should you analyze data at retail? Why is it so important? Um, it's kind of obvious that there is a lot of potential in the data per se, but also understanding the different areas where it can be used in retail is very important. We believe that thanks to using data, it's basically easier to the right, uh, the good decisions for the business based on the facts and not intuition anymore. Those four areas that we observe in retail, uh, our online data analysis, that's the fastest growing sector, let's say for those, for those data analytics services, um, which is of course based on the econ and, uh, online channels, uh, availability to the customer. >>Pandemic only speeds up this process of engagement of the customers in that channel, of course, but traditional offline, um, let's say brick and mortar shops. Uh, they still play the biggest role for most of the retailers, especially from the FMCG sector. However, it's also very important to remember that there is plenty of business, uh, related questions that meet that need to be answered from the headquarter perspective. So is it actually, um, good idea to open a store in a certain place? Is it a good idea to optimize a stock with Saturday in producer? Is it a good idea to allocate the goods to online channel in specific way, those kinds of questions they are, they need to be answered in retail every day. And with that massive amount of factors coming into that question, it's really not, not that easy to base, only on the intuition and expert knowledge, of course, uh, as Brent mentioned at the beginning, the supply chain and everything who's relates to that is also super important. We observe our customers to seek for the huge improvements in the revenue, just from that one single area as well. Okay. >>So let me present you a case study of one of our solutions, and that was the lever to a leading global grocery retailer. Uh, the project started with the challenge set of challenges that we had to conquer. And of course the most important was how to limit overstocks and out of stocks. Uh, that's like the holy grail in of course, uh, how to do it without flooding the stores with the goods and in the same time, how to avoid empty shelves, um, from the perspective of the customer, it was obvious that we need to provide a very well, um, a very high quality of sales forecast to be able to ask for, uh, what will be the actual sales of the individual product in each store, uh, every day, um, considering huge role of the perishable goods in the specific grocery retailer, it was a huge challenge, uh, to provide a solution that was able to analyze and provide meaningful information about what's there in the sales data and the other factors we analyzed on daily basis at scale, however, uh, our holistic approach implementing AI with data management, uh, background, and these automation solutions all together created a platform that was able to significantly increase, uh, the sales for our customer just by minimizing out of stocks. >>In the same time we managed to not overflow the stock, the shops with the goods, which actually decreased losses significantly, especially on the fresh fruit. >>Having said that this results of course translate into the increase in revenue, which can be calculated in hundreds of millions of dollars per year. So how the solution actually works well in its principle, it's quite simple. We just collect the data. We do it online. We put that in our data lake, based on the cloud, there are technology, we implement our artificial intelligence models on top of it. And then based on the aggregated information, we create the forecast and we do it every day or every night for every single product in every single store. This information is sent to the warehouses and then the automated replenishment based on the forecast is on the way the huge and most important aspect of that is the use of the good tools to do the right job. Uh, having said that you can be sure that there is too many information in this data, and there is actually two-minute forecast created every night that any expert could ever check. >>This means our solution needs to be, uh, very robust. It needs to provide information with high quality and high porosity. There is plenty of different business process, which is on our forecast, which need to be delivered on time for every product in each individual shop observing the success of this project and having the huge market potential in mind, we decided to create our QB, which can be used by many retailers who don't want to create a dedicated software for that. We'll be solving this kind of problem. Occupy is, uh, our software service offering, which is enabling retailers to go data driven path management. >>We create occupant with retailers, for retailers, uh, implementing artificial intelligence, uh, on top of data science models created by our experts, uh, having data, data analysis in place based on data management tools that we use we've written first, um, attitude. The uncertain times of pandemic clearly shows that it's very important to apply correction factors, which are sometimes required because we need to respond quickly to the changes in the sales characteristics. That's why occupy B is open box solution, which means that you basically can implement that in your organization. We have without changing the process internally, it's all about mapping your process into this into the system, not the other way around the fast trends and products, collection possibilities allow the retailers to react to any changes, which are pure in the sales every day. >>Also, it's worth to mention that really it's not only FMCG. And we believe that different use cases, which we observed in fashion health and beauty, common garden pharmacies and electronics, flavors of retail are also very meaningful. They also have one common thread. That's the growing importance of e-commerce. That's why we didn't want to leave that aside of occupant. And we made everything we can to implement a solution, which covers all of the needs. When you think about the factors that affect sales, there is actually huge variety of data and that we can analyze, of course, the transactional data that every dealer possesses like sales data from sale from, from e-commerce channel also, uh, averaging numbers from weeks, months, and years makes sense, but it's also worth to mention that using the right tool that allows you to collect that data from also internal and external sources makes perfect sense for retail. Uh, it's very hard to imagine a competitive retailer that is not analyzing the competitor's activity, uh, changes in weather or information about some seasonal stores, which can be very important during the summer during the holidays, for example. Uh, but on the other hand, um, having that information in one place makes the actual benefit and environment for the customer. >>Okay. Demon forecasting seems to be like the most important and promising use case. We can talk about when I think about retail, but it's also their whole process of replenishment that can cover with different sets of machine learning models. And they done management tools. We believe that analyzing data from different parts of the retail, uh, replenishment process, uh, can be achieved with implementing a data management solution based on caldera products and with adding some AI on top of it, it makes perfect sense to focus on not only demand forecasting, but also further use cases down the line when it comes to the actual benefits from implementing solutions for demand management, we believe it's really important to analyze them holistically. First is of course, out of stocks, memorization, which can be provided by simply better sales focus, but also reducing overstocks by better inventory management can be achieved in, in the same time. Having said that we believe that analyzing data without any specific new equipment required in point of sales is the low hanging fruit that can be easily achieved in almost every industry in almost every regular customer. >>Hey, thanks, Camille, having worked with retailers in this space for a couple of decades, myself, I was really impressed by a couple of things and they might've been understated, frankly. Um, the results of course, I mean, you, you know, as I kind of set up this session, you doubled the numbers on the statistics that the analysts found. So obviously in customers you're working with, um, you know, you're, you're doubling average numbers that the industry is having and, and most notably how the use of AI or occupy has automated so many manual tasks of the past, like tour tuning, item profiles, adding new items, et cetera. Uh, and also how quickly it felt like, and this is my, my core question. Your team can cover, um, or, or provide the solution to, to not only core center store, for example, in grocery, but you're covering fresh products. >>And frankly, there are, there are solutions out on the market today that only focus on center store non-perishable department. So I was really impressed by the coverage that you're able to provide as well. So can you articulate kind of what it takes to get up and running and your overall process to roll out the solution? I feel like based on what you talked about, um, and how you were approaching this in leveraging AI, um, that you're, you're streamlining processes of legacy demand, forecasting solutions that required more manual intervention, um, how quickly can you get people set up and what is the overall process like to get started with soft? >>Yeah, it's usually it takes three to six months, uh, to onboard a new customer to that kind of solution. And frankly it depends on the data that the customer, uh, has. Uh, usually it's different, uh, for smaller, bigger companies, of course. Uh, but we believe that it's very important to start with a good foundation. The platform needs to be there, the platform that is able to, uh, basically analyze or process different types of data, structured, unstructured, internal, external, and so on. But when you have this platform set, it's all about starting ingesting data there. And usually for a smaller companies, it's easier to start with those, let's say, low hanging fruits. So the internal data, which is there, this data has the highest veracity is already easy to start with, to work with them because everyone in the organization understands this data for the bigger companies. It might be important to ingest also kind of more unstructured data, some kind of external data that need to be acquired. So that may, that may influence the length of the process. But we usually start with the customers. We have, uh, workshops. That's very important to understand their business because not every deal is the same. Of course, we believe that the success of our customers comes also due to the fact that we train those models, those AI models individually to the needs of our >>Totally understand and POS data, every retailer has right in, in one way shape or form. And it is the fundamental, uh, data point, whether it's e-comm or the brick and mortar data, uh, every retailer has that data. So that, that totally makes sense. But what you just described was bunts. Um, there are, there are legacy and other solutions out there that this could be a, a year or longer process to roll out to the number of stores, for example, that you're scaling to. So that's highly impressive. And my guess is a lot of the barriers that have been knocked down with your solution are the fact that you're running this in the cloud, um, you know, on, from a compute standpoint on Cloudera from a public cloud stamp point on Microsoft. So there's, there's no, it intervention, if you will, or hurdles in preparation to get the database set up and in all of the work, I would imagine that part of the time-savings to getting started, would that be an accurate description? >>Yeah, absolutely. Uh, in the same time, this actually lowering the business risks, because we simply take data and put that into the data lake, which is in the cloud. We do not interfere with the existing processes, which are processing this data in the combined. So we just use the same data. We just already in the company, we ask some external data if needed, but it's all aside of the current customers infrastructure. So this is also a huge gain, as you said, right? >>And you're meeting customers where they are. Right. So, as I said, foundationally, every retailer POS data, if they want to add weather data or calendar event data or, you know, want incorporate a course online data with offline data. Um, you have a roadmap and the ability to do that. So it is a building block process. So getting started with, for data, uh, as, as with POS online or offline is the foundational component, which obviously you're very good at. Um, and then having that ability to then incorporate other data sets is critically important because that just improves demand, forecast accuracy, right. By being able to pull in those, those other data sources, if you will. So Camille, I just have one final question for you. Um, you know, there, there are plenty of not plenty, but I mean, there's enough demand forecasting solutions out on the market today for retailers. One of the things that really caught my eye, especially being a former retailer and talking with retailers was the fact that you're, you're promoting an open box solution. And that is a key challenge for a lot of retailers that have, have seen black box solutions come and go. Um, and especially in this space where you really need direct input from the, to continue to fine tune and improve forecast accuracy. Could you give just a little bit more of a description or response to your approach to open box versus black box? >>Yeah, of course. So, you know, we've seen in the past the failures of the projects, um, based on the black box approach, uh, and we believe that this is not the way to go, especially with this kind of, uh, let's say, uh, specialized services that we provide in meaning of understanding the customer's business first and then applying the solution, because what stands behind our concept in occupy is the, basically your process in the organization as a retailer, they have been optimized for years already. That's where retailers put their, uh, focus for many years. We don't want to change that. We are not able to optimize it properly. For sure as it combined, we are able to provide you a tool which can then be used for mapping those very well optimized process and not to change them. That's our idea. And the open box means that in every process that you will map in the solution, you can then in real time monitor the execution of those processes and see what is the result of every step. That way we create truly explainable experience for our customers, then okay, then can easily go for the whole process and see how the forecast, uh, was calculated. And what is the reason for a specific number to be there at the end of the day? >>I think that is, um, invaluable. Um, can be, I really think that is a differentiator and what three soft is bringing to market with that. Thanks. Thanks everyone for joining us today, let's stay in touch. I want to make sure to leave, uh, uh, Camille's information here. Uh, so reach out to him directly or feel free at any, any point in time, obviously to reach out to me, um, again, so glad everyone was able to join today, look forward to talking to you soon.

(upbeat music) >> From around the globe, it's theCUBE with digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, hi everybody John Walls here on theCUBE and we're now welcoming Jeremy Wilmot who is the chief product officer at ACI Worldwide part of the Postgres movement, you might say or certainly benefiting from the great value that Postgres is providing a number of enterprises across the globe. Jeremy good to see you today and first off, congratulations you are the first guest I've talked to maybe in a year and a half in their office. So good for you. >> Thanks (chuckles) John that's very kind of you John and great to see you and thanks for having me here. Yeah, it's great to be in the office, it really is. I'm here in Miami in South Florida and getting some sort of normalcy back is great for all of us and I'm certainly enjoying it. So thank you before (indistinct) has been. >> I'm sure you are, yeah, congratulations on that front. First off, let's talk about ACI Worldwide for the folks in our audience who aren't familiar with the payments, your role in terms of that payment ecosystem. Tell us a little bit about ACI Worldwide. >> Sure, well, primarily we're a software company. That's ACI, we started 1975 in Omaha, Nebraska built the first debit card system and ATM system for first National Bank of Omaha and over the last 45 years, we've globalized ourselves, we have, we are delivering mission-critical real-time payment systems across the world to banks to merchants to billers, we help them meet the payment needs of their consumers and their corporates. So we process, manage digital payments, we power omni-commerce and e-commerce payments, we present and process bill payments, we manage fraud, we manage the risk all within that and as I said on a global basis 13 of the G20 countries with a leading DDA account or current account payment processing software in those countries and have been for many years. >> So, as the CPO then quite obviously in the financial space your plate is quite full these days in terms of providing for your client base. How would you characterize maybe the evolution in terms of product development that you've been through in the financial world here over the past say, three to five years, where were you back then to where you are now and what role has Postgres played in that journey? >> Sure, yeah. So, specific to the Postgres part of the ecosystem, previously five-plus years ago our previous database solution was complex, it was expensive, it was hard to change and maintain and we leveraged multiple pieces of software from multiple vendors as a result of that. So at that time we looked for an alternative that was simpler and better and we went through a very comprehensive due diligence process, we explored both open source and license models of database to support our solution and when we looked at all of the options we determined that 2ndQuadrant Postgres was the one that provided the most comprehensive solution we were looking for. It had the right mix of capabilities and performance at the right total cost of ownership that we were looking for. And in the payments world as you can imagine, you've got to to be 24/7 365. And we also required a lower cost of ownership than we had before. But we also wanted a greater flexibility and time to market that we could pass on to our customers. And then the last thing I'd say that we were looking for was a multi-deployment capability. And what I mean by that is that we would be able to use this new platform, Postgres platform in our own data centers in our own private cloud, but we could also deploy it in the public cloud, whether we would run it or whether our customers would run it. We wanted that ability to mix and match between these different deployment options. >> So you've talked about a lot of key elements here attributes in terms of availability, accessibility reliability, security obviously. Walk us through those in terms of why you think 2ndQuadrant was addressing your needs in those particular areas or any others for that matter but what it was that checked the box specifically about what Postgres was offering you as opposed to what these other possible solutions and services were that you were looking at. >> Yeah, I think, we're very focused on being able to identify what our customers need and when they're offering services to consumers and to their corporates what is it that they require that's going to enable them to win and compete. And payments industry has a lot of cost pressures within it. It has regulation, it has consumer convenience and the whole movement of digitalization that puts a lot of downward pressure on the cost space. And those who are going to win in the payment space need to be able to address that. So, that is relevant for our banks, for our merchants, for the billers. They all come under very similar regulatory pressure and market pressure and as a result, the ability to reduce dramatically in a very significant way, the total cost of ownership upon which the payment software was going to be operating that was one of the key elements that was very important to us as we made that decision. The second one I think was to enable us to be able to do what we are good at and what our customers expect us to do. And that in turn enables them to focus on their core competencies. We're a software company, we own our own IP we manage our own software for the needs of the 24/7 365 payment requirements and therefore the merchant or the biller or the bank can really focus in on the digital experience for their customers, focusing on their core competencies and what they need to do to win. That was a second key factor for us. I think the third one for us was as well speed to market. Speed to market for ourselves and being competitive to the alternative to ACI, but also more importantly a speed to market for our customers. And there are, the payment world is highly regulated requires significant certification in order to launch new services that's often the long pole in the tent. So we want to be able to get to that point as quickly as possible. And being able to have a public cloud deployment open systems capabilities that would really allow us to pass on that speed to market to those customers. So for example, an acquirer, a payment acquirer moving into a new geographical country they want to compete in they can (indistinct) on their competitors by launching minimum viable products in six to nine months that is five years ago, that could have been a 24 to 30 months endeavor for them to take on. So I, those were important considerations for us as we were choosing a longterm partner for the Postgres world and the public cloud world. >> Obviously, so you've talked a lot about your relationship with your clients and I know you have a really keen awareness of the need to ensure that trust, to ensure that reliability to ensure the collaboration. How about your relationship on the other side with EDB and in terms of all those elements so how has that evolved over a period of time and what kind of service and what kind of value do you think are you deriving from that relationship now? >> So with EDB, first of all, our journey started with 2ndQuadrant and now EDB. And we were specifically looking at the, one area was at the Bi-Directional Replication BDR that we were wanting to support with our solutions particularly in the public cloud. And that was going to enable us to replace multiple pieces of software from multiple vendors. And so we were to create that solution that was right for ACI, it was right for our customers from a functionality and agility and a cost perspective. So technologically with the non-functional requirements and the reliability, availability, serviceability aspects that we were looking for that was in partnership with 2ndQuadrant and EDB, that was a key element. I think the second piece of it is we worked really well with 2ndQuadrant EDB in terms of partnering to meet the needs of the market. It's great to have the right technology in place but then you need your partners really to be able to work with you tactically real-time in order to win in the market and make it work. And I found that they'd been a great partner for us to be able to do that and to be able to react quickly, do the right thing and really enable us to be a great partner to our customers as we deliver real-time payments, as we deliver the acquiring capabilities, as we deliver a modernization for the big banks that we work with as well. >> Now, before I let you go, I'm going to give you a two-part question here. That's always one way to squeeze a little more info (laughing) to the guest. First off advice. You've been through this transformation obviously you're very happy with all that has transpired, so your advice to others who are considering this journey. And then secondly, what can they and you do you think expect in terms of future challenges, opportunities how we might want to frame that with Postgres? Like, where are we going from here, basically? So, two parts, advice and then where do you think this is headed? >> So advice, I certainly learnings from us versus advice is number one, be very thorough in the due diligence that you do and be very clear on what you want and what are your goals that you're looking for. So from an AGI perspective, we were clear that total cost of ownership in terms of the stack that we were going to be providing to our customers. That was very important, number one number two, nonfunctional requirements. So I've talked about the mission criticality of payments 24/7 365. That was a key second piece. And then the third one, ease of deployment. I talked about that, multi-cloud deployment that we were looking for. So we were clear what we wanted and we we took our time from a due diligence point of view. It's a multi-year decision being made so it's not something specifically I think we want to rush into. In terms of looking forward and where do we go from here? Performance is critical so further up performance enhancements, ability for rapid failover availability, near 100% availability that we're looking for five-nines and above, working together with Postgres in order to make those failovers more seamless because they will happen, particularly in the real-time payments world, where we're now seeing billions of transactions happening in a week and soon that will be in a day, they will need to be able to deal with. And for all of this to happen in a public cloud environment, we, I think all understand a lot of the benefits of public cloud and we need to be able to provide this failover availability capability in the public cloud but also in a hybrid cloud environments we're in a multi-cloud environment, so we need to keep working that and make that happen that will make Postgres a payment-grade infrastructure that could power the world's real-time payments and we would love to be able to do that into the future. >> Well, Jeremy thanks for the insights, we appreciate that and once again, congratulations on getting back in that office. I know it's probably a pretty welcomed addition to your regimen now. >> Yeah, John, thank you very much and thanks to everyone who's dialed in for this and John I look forward to welcoming you in the office soon. >> Very good sir, I look forward to that as well. I'll take you up on that in Miami for sure. John Walls here on theCUBE talking with Jeremy Wilmot is the chief product officer at ACI Worldwide. part of our Postgres Vision 2021 coverage. (upbeat music)