(upbeat music) >> Hello, welcome to the Cube's coverage of International Women's Day 2023. I'm John Furrier, host of the CUBE series of profiles around leaders in the tech industry sharing their stories, advice, best practices, what they're doing in their jobs their vision of the future, and more importantly, passing it on and encouraging more and more networking and telling the stories that matter. Our next guest is a great executive leader talking about how to lead in challenging times. Krista Satterthwaite, who is Senior Vice President and GM of Mainstream Compute. Krista great to see you're Cube alumni. We've had you on before talking about compute power. And by the way, congratulations on your BPT and Black Professional Tech Network 2023 Black Tech Exec of the Year Award. >> Thank you very much. Appreciate it. And thanks for having me. >> I knew I liked you the first time we were doing interviews together. You were so smart and so on top of it. Thanks for coming on. >> No problem. >> All kidding aside, let's get into it. You know, one of the things that's coming out on these interviews is leadership is being showcased and there's a network effect happening in the industry and you're starting to see people look and hear stories that they may or may not have heard before or news stories are coming out. So, one of the things that's interesting is that also in the backdrop of post pandemic, there's been a turn in the industry a little bit, there's a little bit of headwind in certain areas, some tailwinds in cloud and other areas. Compute, your area is doing very well. It could be challenging. And as a leader, has the conversation changed? And where are you at right now in the network of folks you're working with? What's the mood? >> Yeah, so actually I, things are much better. Obviously we had a chip shortage last year. Things are much, much better. But I learned a lot when it came to going through challenging times and leadership. And I think when we talk to customers, a lot of 'em are in challenging situations. Sometimes it's budget, sometimes it's attracting and retaining talent and sometimes it's just demands because, it's really exciting that technology is behind everything. But that means the demands on IT are bigger than ever before. So what I find when it comes to challenging times is that there's really three qualities that are game changers when it comes to leading and challenging times. And the first one is positivity. People have to feel like there's a light at the end of the tunnel to make sure that, their attitudes stay up, that they stay working really really hard and they look to the leader for that. The second one is communication. And I read somewhere that communication is leadership. And we had a great example from our CEO Antonio Neri when the pandemic hit and everything shut down. He had an all employee meeting every week for a month and we have tens of thousands of employees. And then even after that month, we had 'em very regularly. But he wanted to make sure that everybody heard from, him his thoughts had all the updates, knew how their peers were doing, how we were helping customers. And I really learned a lot from that in terms of communicating and communicating more during tough times. And then I would say the third one is making sure that they are informed and they feel empowered. So I would say a leader who is able to do that really, really stands out in a challenging time. >> So how do you get yourself together? Obviously you the chip shortage everyone knows in the industry and for the folks not in the tech industry, it was an economic potential disaster, because you don't get the chips you need. You guys make servers and technology, chips power everything. If you miss a shipment, it could cause a lot of backlash. So Cisco had an earnings impact. It has impact to the business. When do you have that code red moment where it's like, okay, we have to kind of put the pause and go into emergency mode. And how do you handle that? >> Well, you know, it is funny 'cause when it, when we have challenges, I come to learn that people can look at challenges and hard work as a burden or a mission and they behave totally different. If they see it as a burden, then they're doing the bare minimum and they're pointing fingers and they're complaining and they're probably not getting a whole lot done. If they see it as a mission, then all of a sudden they're going above and beyond. They're working really hard, they're really partnering. And if it affects customers for HPE, obviously we, HPE is a very customer centric company, so everyone pays attention and tries to pitch in. But when it comes to a mission, I started thinking, what are the real ingredients for a mission? And I think it's important. I think it's, people feel like they can make an impact. And then I think the third one is that the goal is clear, even if the path isn't, 'cause you may have to pivot a lot if it's a challenge. And so when it came to the chip shortage, it was a mission. We wanted to make sure that we could ship to customers as quickly as possible. And it was a mission. Everybody pulled together. I learned how much our team could pull off and pull together through that challenge. >> And the consequences can be quantified in economics. So it's like the burn the boats example, you got to burn the boats, you're stuck. You got to figure out a solution. How does that change the demands on people? Because this is, okay, there's a mission it they're not, it's not normal. What are some of those new demands that arise during those times and how do you manage that? How do you be a leader? >> Yeah, so it's funny, I was reading this statement from James White who used to be the CEO of Jamba Juice. And he was talking about how he got that job. He said, "I think it was one thing I said that really convinced them that I was the right person." And what he said was something like, "I will get more out of people than nine out of 10 leaders on the planet." He said, "Because I will look at their strengths and their capabilities and I will play to their passions." and their capabilities and I will play their passions. and getting the most out people in difficult times, it is all about how much you can get out of people for their own sake and for the company's sake. >> That's great feedback. And to people watching who are early in their careers, leading is getting the best out of your team, attitude. Some of the things you mentioned. What advice would you give folks that are starting to get into the workforce, that are starting to get into that leadership track or might have a trajectory or even might have an innate ability that they know they have and they want to pursue that dream? >> Yeah so. >> What advice would you give them? >> Yeah, what I would say, I say this all the time that, for the first half of my career I was very job conscious, but I wasn't very career conscious. So I'd get in a role and I'd stay in that role for long periods of time and I'd do a good job, but I wasn't really very career conscious. And what I would say is, everybody says how important risk taking is. Well, risk taking can be a little bit of a scary word, right? Or term. And the way I see it is give it a shot and see what happens. You're interested in something, give it a shot and see what happens. It's kind of a less intimidating way of looking at risk because even though I was job conscious, and not career conscious, one thing I did when people asked me to take something on, hey Krista, would you like to take on more responsibility here? The answer was always yes, yes, yes, yes. So I said yes because I said, hey I'll give it a shot and see what happens. And that helped me tremendously because I felt like I am giving it a try. And the more you do that, the the better it is. >> It's great. >> And actually the the less scary it is because you do that, a few times and it goes well. It's like a muscle that builds. >> It's funny, a woman executive was on the program. I said, the word balance comes up a lot. And she stopped and said, "Let's just talk about balance for a second." And then she went contrarian and said, "It's about not being unbalanced. It's about being, taking a chance and being a little bit off balance to put yourself outside your comfort zone to try new things." And then she also came up and followed and said, "If you do that alone, you increase your risk. But if you do it with people, a team that you trust and you're authentic and you're vulnerable and you're communicating, that is the chemistry." And that was a really good point. What's your reaction? 'Cause you were talking about authentic conversations good communications with Antonio. How does someone get, feel, find that team and do you agree with it? And what was your, how would you react to that? >> Yes, I agree with that. And when it comes to being authentic, that's the magic and when someone isn't, if someone's not really being themselves, it's really funny because you can feel it, you can sense it. There's kind of a wall between you and them. And over time people won't be able to put their finger on it, but they'll feel a distance from you. But when you're authentic and you share who you are, what you find is you find things in common with other people. 'Cause you're sharing more of who you are and it's like, oh, I do that too. Oh, I'm interested in that too. And build the bonds between people and the authenticity. And that's what people crave. They want people to be authentic and people can tell when you're authentic and when you're not. >> Is managing and leading through a crisis a born talent or can you learn it? >> Oh, definitely learned. I think that we're born knowing nothing and I once read people are nurtured into greatness and I think that's true. So yeah, definitely learned. >> What are some examples that can come out of a tough time as folks may look at a crisis and be shy away from it? How do they lean into it? What advice would you give folks? How do you handle it? I mean, everyone's got different personality. Okay, they get to a position but stepping through that door. >> Yeah, well, I do this presentation called, "10 things I Wish I Knew Earlier in my Career." And one of those things is about the growth mindset and the growth mindset. There's a book called "Mindset" by Carol Dweck and the growth mindset is all about learning and not always having to know everything, but really the winning is in the learning. And so if you have a growth mindset it makes you feel better about everything because you can't lose. You're winning because you're learning. So when I've learned that, I started looking at things much differently. And when it comes to going through tough times, what I find is you're exercising muscles that you didn't even know you had, which makes you stronger when the crisis is over, obviously. And I also feel like you become a lot a much more creative when you're in challenging times. You're forced to do things that you hadn't had to do before. And it also bonds the team. It's almost like going through bootcamp together. When you go through a challenge together it bonds you for life. >> I mean, you could have bonding, could be trauma bonding or success bonding. People love to be on the success side because that's positive and that's really the key mindset. You're always winning if you have that attitude. And learnings is also positive. So it's not, it's never a failure unless you make it. >> That's right, exactly. As long as you learn from it. And that's the name of the game. So, learning is the goal. >> So I have to ask you, on your job now, you have a really big responsibility HPE compute and big division. What's the current mindset that you have right now in your career, where you're at? What are some of the things on your mind that you think about? We had other, other seniors leaders say, hey, you know I got the software as my brain and the hardware's my body. I like to keep software and hardware working together. What is your current state of your career and how you looking at it, what's next and what's going on in your mind right now? >> Yeah, so for me, I really want to make sure that for my team we're nurturing the next generation of leadership and that we're helping with career development and career growth. And people feel like they can grow their careers here. Luckily at HPE, we have a lot of people stay at HPE a long time, and even people who leave HPE a lot of times they come back because the culture's fantastic. So I just want to make sure I'm contributing to that culture and I'm bringing up the next generation of leaders. >> What's next for you? What are you looking at from a career personal standpoint? >> You know, it's funny, I, I love what I'm doing right now. I'm actually on a joint venture board with H3C, which is HPE Joint Venture Company. And so I'm really enjoying that and exploring more board service opportunities. >> You have a focus of good growth mindset, challenging through, managing through tough times. How do you stay focused on that North star? How do you keep the reinforcement of the mission? How do you nurture the team to greatness? >> Yeah, so I think it's a lot of clarity, providing a lot of clarity about what's important right now. And it goes back to some of the communication that I mentioned earlier, making sure that everybody knows where the North Star is, so everybody's focused on the same thing, because I feel like with the, I always felt like throughout my career I was set up for success if I had the right information, the right guidance and the right goals. And I try to make sure that I do that with my team. >> What are some of the things that you could share as we wrap up here for the folks watching, as the networks increase, as the stories start to unfold more and more on digital like we're doing here, what do you hope people walk away with? What's working, what needs work, and what is some things that people aren't talking about that should be discussed publicly? >> Do you mean from a career standpoint or? >> For career? For growing into tech and into leadership positions. >> Okay. >> Big migration tech is now a wide field. I mean, when I grew up, broke into the eighties, it was computer science, software engineering, and three degrees in engineering, right? >> I see huge swath of AI coming. So many technical careers. There's a lot more women. >> Yeah. And that's what's so exciting about being in a technical career, technical company, is that everything's always changing. There's always opportunity to learn something new. And frankly, you know, every company is in the business of technology right now, because they want to closer to their customers. Typically, they're using technology to do that. Everyone's digitally transforming. And so what I would say is that there's so much opportunity, keep your mind open, explore what interests you and keep learning because it's changing all the time. >> You know I was talking with Sue, former HP, she's on a lot of boards. The balance at the board level still needs a lot of work and the leaderships are getting better, but the board at the seats at the table needs work. Where do you see that transition for you in the future? Is that something on your mind? Maybe a board seat? You mentioned you're on a board with HPE, but maybe sitting on some other boards? Any, any? >> Yes, actually, actually, we actually have a program here at HPE called the Board Ready Now program that I'm a part of. And so HPE is very supportive of me exploring an independent board seat. And so they have some education and programming around that. And I know Sue well, she's awesome. And so yes, I'm looking into those opportunities right now. >> She advises do one no more than two. The day job. >> Yeah, I would only be doing one current job that I have. >> Well, kris, it was great to chat with you about these topics and leadership and challenging times. Great masterclass, great advice. As SVP and GM of mainstream compute for HPE, what's going on in your job these days? What's the most exciting thing happening? Share some of your work situations. >> Sure, so the most exciting thing happening right now is HPE Gen 11, which we just announced and started shipping, brings tremendous performance benefit, has an intuitive operating experience, a trusted security by design, and it's optimized to run workloads so much faster. So if anybody is interested, they should go check it out on hpe.com. >> And of course the CUBE will be at HPE Discover. We'll see you there. Any final wisdom you'd like to share as we wrap up the last minute here? >> Yeah, so I think the last thing I'll say is that when it comes to setting your sights, I think, expecting it, good things to happen usually happens when you believe you deserve it. So what happens is you believe you deserve it, then you expect it and you get it. And so sometimes that's about making sure you raise your thermostat to expect more. And I always talk about you don't have to raise it all up at once. You could do that incrementally and other people can set your thermostat too when they say, hey, you should be, you should get a level this high or that high, but raise your thermostat because what you expect is what you get. >> Krista, thank you so much for contributing to this program. We're going to do it quarterly. We're going to do getting more stories out there, so we'll have you back and if you know anyone with good stories, send them our way. And congratulations on your BPTN Tech Executive of the Year award for 2023. Congratulations, great prize there and great recognition for your hard work. >> Thank you so much, John, I appreciate it. >> Okay, this is the Cube's coverage of National Woodman's Day. I'm John Furrier, stories from the front lines, management ranks, developers, all there, global coverage of international events with theCUBE. Thanks for watching. (soft music)

>> Narrator: TheCUBE presents Ignite '22, brought to you by Palo Alto Networks. >> Greetings from the MGM Grand Hotel in beautiful Las Vegas. It's theCUBE Live Day two of our coverage of Palo Alto Networks, ignite 22. Lisa Martin, Dave Vellante. Dave, what can I say? This has been a great couple of days. The amount of content we have created and shared with our viewers on theCUBE is second to none. >> Well, the cloud has completely changed the way that people think about security. >> Yeah. You know at first it was like, oh, the cloud, how can that be secure? And they realized, wow actually cloud is pretty secure if we do it right. And so shared responsibility model and partnerships are critical. >> Partnerships are critical, especially as more and more organizations are multicloud by default. Right? These days we're going to be bring Google into the conversation. Josh Haslet joins us. Strategic Partnership Manager at Google. Welcome. Great to have you Josh. >> Hi Lisa, thanks for having me here. >> So you are a secret squirrel from Palo Alto Networks. Talk to me a little bit about your background and about your role at Google in terms of partnership management. >> Sure, I feel like we need to add that to my title. [Lisa] You should, secret squirrel. >> Great. Yeah, so as a matter of fact, I've been at Google for two and a half years. Prior to that, I was at Palo Alto Networks. I was managing the business development relationship with Google, and I was kind of at the inception of when the cash came in and, and decided that we needed to think about how to do security in a new way from a platform standpoint, right? And so it was exciting because when I started with the partnership, we were focusing on still securing you know, workloads in the cloud with next generation firewall. And then as we went through acquisitions the Palo Alto added it expanded the capabilities of what we could do from cloud security. And so it was very exciting, you know, to, to make sure that we could onboard with Google Cloud, take a look at how not only Palo Alto was enhancing their solutions as they built those and delivered those from Google Cloud. But then how did we help customers adopt cloud in a more easy fashion by making things, you know more tightly integrated? And so that's really been a lot of what I've been involved in, which has been exciting to see the growth of both organizations as we see customers shifting to cloud transformation. And then how do they deploy these new methodologies and tools from a security perspective to embrace this new way of working and this new way of, you know creating applications and doing digital transformation. >> Important, since work is no longer a place, it's an activity. Organizations have have to be able to cater to the distributed workforce. Of course, the, the, the workforce has to be able to access everything that they need to, but it has to be done in a secure way regardless of what kind of company you are. >> Yeah, you're right, Lisa. It's interesting. I mean, the pandemic has really changed and accelerated that transformation. I think, you know really remote working has started previous to that. And I think Nikesh called that out in the keynote too right? He, he really said that this has been ongoing for a while, but I think, you know organizations had to figure out how to scale and that was something that they weren't as prepared for. And a lot of the technology that was deployed for VPN connectivity or supporting remote work that was fixed hardware. And so cloud deployment and cloud architecture specifically with Prisma access really enabled this transformation to happen in a much faster, you know, manner. And where we've come together is how do we make sure that customers, no matter what device, what user what application you're accessing. As we take a look at ZTNA, Zero Trust Network Access 2.0, how can we come together to partner to make sure the customers have that wide range of coverage and capability? >> How, how do you how would you describe Josh Google's partner strategy generally and specifically, you know, in the world of cyber and what makes it unique and different? >> Yeah, so that's a great question. I think, you know, from Google Cloud perspective we heard TK mention this in the keynote with Nikesh. You know, we focus on on building a secure platform first and foremost, right? We want to be a trusted cloud for customers to deploy on. And so, you know, we find that as customers do one of two things, they're looking at, you know, reducing cost as they move to cloud and consolidate workloads or as they embrace innovation and look at, you know leveraging things like BigQuery for analytics and you know machine learning for the way that they want to innovate and stay ahead of the competition. They have to think about how do they secure in a new way. And so, not only do we work on how do we secure our own platform, we work with trusted partners to make sure that customers have you mentioned it earlier, Dave the shared security model, right? How do they take a look at their applications and their workloads and this new way of working as they go to CI/CD pipelines, they start thinking about DevSecOps. How do they integrate tooling that is frictionless and seamless for their, for their teams to deploy but allows them to quickly embrace that cloud transformation journey. And so, yes, partners are critical to that. The other thing is, you know we find that, you mentioned earlier, Lisa that customers are multicloud, right? That's kind of the the new normal as we look at enterprises today. And so Google Cloud's going to do a great job at securing our platform, but we need partners that can help customers deploy policy that embraces not only the things that they put in Google Cloud but as they're in their transformation journey. How that embraces the estates that are in data centers the things that are still on-prem. And really this is about making sure that the applications no matter where they are, the databases no matter where they are, and the users no matter where they are are all secure in that new framework of deploying and embracing innovation on public cloud. >> One of the things that almost everybody from Palo Alto Networks talks about is their partnering strategy their acquisition strategy integrations. And I was doing some research. There's over 50 joint integrations that Google Cloud and Palo Alto Networks. Have you talked about Zero Trust Network Access 2.0 that was announced yesterday. >> Correct. >> Give us a flavor of what that is and what does it deliver that 1.0 did not? >> Well, great. And what I'd like to do is touch a little bit on those 50 integrations because it's been, you know, a a building rolling thunder, shall we say as far as how have we taken a look at customers embracing the cloud. The first thing was we took a look at at how do we make sure that Palo Alto solutions are easier for customers to deploy and to orchestrate in Google Cloud making their journey to embracing cloud seamless and easy. The second thing was how could we make that deployment and the infrastructure even more easy to adopt by doing first party integrations? So earlier this year we announced cloud IDS intrusion detection system where we actually have first party directly in our console of customers being able to simply select, they want to turn on inspection of the traffic that's running on Google Cloud and it leverages the threat detection capability from Palo Alto Networks. So we've gone from third party integration alone to first party integration. And that really takes us to, you know, the direction of what we're seeing customers need to embrace now which is, this is your Zero Trusts strategy and Zero Trust 2.0 helps customers do a number of things. The first is, you know, we don't want to just verify a user and their access into the environment once. It needs to be continuous inspection, right? Cause their state could change. I think, you know, the, the teams we're talking about some really good ways of addressing, you know for instance, TSA checkpoints, right? And how does that experience look? We need to make sure that we're constantly evaluating that user's access into the environment and then we need to make sure that the content that's being accessed or, you know, loaded into the environment is inspected. So we need continuous content inspection. And that's where our partnership really comes together very well, is not only can we take care of any app any device, any user, and especially as we take a look at you know, embracing contractor like use cases for instance where we have managed devices and unmanaged devices we bring together beyond Corp and Prisma access to take a look at how can we make sure any device, any user any application is secure throughout. And then we've got content inspection of how that ZTNA 2.0 experience looks like. >> Josh, that threat data that you just talked about. >> Yeah. >> Who has access to that? Is it available to any partner, any customer, how... it seems like there's gold in them, NAR hills, so. >> There is. But, this could be gold going both ways. So how, how do you adjudicate and, how do you make sure that first of all that that data's accessible for, for good and not in how do you protect it against, you know, wrong use? >> Well, this is one of the great things about partnering with Palo Alto because technically the the threat intelligence is coming from their ingestion of malware, known threats, and unknown threats right into their technology. Wildfire, for instance, is a tremendous example of this where unit 42 does, you know, analysis on unknown threats based upon what Nikesh said on stage. They've taken their I think he said 27 days to identification and remediation down to less than a minute, right? So they've been able to take the intelligence of what they ingest from all of their existing customers the unknown vulnerabilities that are identified quickly assessing what those look like, and then pushing out information to the rest of their customers so that they can remediate and protect against those threats. So we get this shared intelligence from the way that Palo Alto leverages that capability and we've brought that natively into Google Cloud with cloud intrusion detection. >> So, okay, so I'm, I'm I dunno why I have high frequency trading in my mind cause it used to be, you know, like the norm was, oh it's going to take a year to identify an intrusion. And, and, and now it's down to, you know take was down to 27 days. Now it's down to a minute. Now it's not. That's best practice. And I'm, again, I'm thinking high frequency trading how do I beat the speed of light? And that's kind of where we're headed, right? >> Right. >> And so that's why he said one minute's not enough. We have to keep going. >> That's right. >> So guys got your best people working on that? >> Well, as a matter of fact, so Palo Alto Networks, you know when we take a look at what Nikesh said from stage, he talked about using machine learning and AI to get ahead of what we what they look at as far as predictability not only about behaviors in the environment so things that are not necessarily known threats but things that aren't behaving properly in the environment. And you can start to detect based on that. The second piece of it then is a lot of that technology is built on Google Cloud. So we're leveraging, their leveraging the capabilities that come together with you know, aggregation of, of logs the file stitching across the entire environment from the endpoint through to cloud operations the things that they detect for network content inspection putting all those files together to understand, you know where has the threat vector entered how has it gone lateral inside the environment? And then how do you make sure that you remediate all of those points of intrusion. And so yeah it's been exciting to see how our product teams have worked together to continue to advance the capabilities for speed for customers. >> And secure speed is critical. We had the opportunity this morning to speak with Lee Claridge, the chief product officer, and you know one of the things that I had heard about Lee is that despite all of the challenges in cybersecurity and the amorphous expansion of the threat network and the sophistication of the adversaries he's really optimistic about what it's going to enable organizations to do. I see you smiling. Do you share that optimism? >> I, I do. I think, you know, when you bring, when you bring leaders together to tackle big problems, I think, you know we've got the right teams working on the right things and we understand the problems that the customers are facing. And so, you know, from a a Google cloud perspective we understand that partnering with Palo Alto Networks helps to make sure that that optimism continues. You know, we work on continuous innovation when it comes to Google Cloud security framework, but then partnering with Palo Alto brings additional capabilities to the table. >> Vision for the, for the partnership. Where do you want to see it go? What's... we're two to five years down the road, what's it look like? Maybe two to three years. Let's go. >> Well, it was interesting. I, I think neer was the one that mentioned on stage about, you know how AI is going to start replacing us in our main jobs, right? I I think there's a lot of truth to that. I think as we look forward, we see that our teams are going to continue to help with automation remediation and we're going to have the humans working on things that are more interesting and important. And so that's an exciting place to go because today the reality is that we are understaffed in cybersecurity across the industry and we just can't hire enough people to make sure that we can detect, remediate and secure, you know every user endpoint and environment out there. So it's exciting to see that we've got a capability to move in a direction to where we can make sure that we get ahead of the threat actors. >> Yeah. So he said within five years your SOC will be AI based and and basically he elaborated saying there's a lot of stuff that you're doing today that you're not going to be doing tomorrow. >> That's true. >> And that's going to continue to be a moving target I would think Google is probably ahead in that game and ahead of most, right? I mean, you guys were there early. I mean, I remember when Hadoop was all the rage like just at the beginning you guys like, yeah, you know Google's like, no, no, no, we're not doing Hadoop anymore. That's like old news. So you tended to be, I don't know, at least five maybe seven years ahead of the industry. So I imagine you using a lot of those AI techniques in your own business today. >> Absolutely. I mean, I think you see it in our consumer products, and you certainly see it in the the capabilities we make available to enterprise as far as how they can innovate on our cloud. And we want to make sure that we continue to provide those capabilities, you know not only for the tools that we build but the tools that customers use. >> What's the, as we kind of get towards the end of our conversation here, we we talk about zero trust as, as a journey, as an approach. It's not a product, it's not a tool. What is the, who's involved in the zero trust journey from the customers perspective? Is this solely with the CSO, CSO, CIOs or is this at the CEO level going, we have to be a data company but we have to be a secure data company 24/7. >> It's interesting as you've seen malware, phishing, ransomware attacks. >> Yeah. >> This is not only just a CSO CIO conversation it's a board level conversation. And so, you know the way to address this new way of working where we have very distributed environments where you can't create a perimeter anymore. You need to strategize with zero trust. And so continuously, when we're talking to customers we're hearing that as a main initiative, you know from the CIO's office and from the board level. >> Got it, last question. The upgrade path for existing customers from 1., ZTNA 1.0 to 2.0. How simple is that? >> It's easy. You know, when we take- >> Is there an easy button? >> So here's the great thing [Dave] If you're feeling lucky. [Lisa] Yeah. (group laughs) >> Well, Palo Alto, right? Billing prisma access has really taken what was traditional security that was an on-prem or a data center deployed strategy to cloud-based. And so we've worked with customers like Princeton University who had to quickly transition from in-person learning to distance learning find a way to ramp their staff their faculty and their students. And we were able to, you know Palo Alto deploy it on Google Cloud's, you know network that solution in very quick order and had those, you know, everybody back up and running. So deployment and upgrade path is, is simple when you look at cloud deployed architectures to address zero trusts network. >> That's awesome. Some of those, some of those use cases that came out of the pandemic were mind blowing but also really set the table for other organizations to go, yes, this can be done. And it doesn't have to take forever because frankly where security is concerned, we don't have time. >> That's right. And it's so much faster than traditional architectures where you had to procure hardware. >> Yeah. >> Deploy it, configure it, and then, you know push agents out to all the endpoints and and get your users provisioned. In this case, we're talking about cloud delivered, right? So I've seen, you know, with Palo Alto deploying for customers that run on Google Cloud they've deployed tens of thousands of users in a very short order. You know, we're talking It was, it's not months anymore. It's not weeks anymore. It's days >> Has to be days. Josh, it's been such a pleasure having you on the program. Thank you for stopping by and talking with Dave and me about Google Cloud, Palo Alto Networks in in addition to secret squirrel. I feel like when you were describing your background that you're like the love child of Palo Alto Networks and Google Cloud, you might put that on your cartoon. >> That is a huge compliment. I really appreciate that, Lisa, thank you so much. >> Thanks so much, Josh. [Josh] It's been a pleasure being here with you. [Dave] Thank you >> Oh, likewise. For Josh Haslett and Dave, I'm Lisa Martin. You're watching theCUBE, the leader in live coverage for emerging and enterprise tech. (upbeat outro music)

(upbeat music) >> Hello, welcome back to theCUBE's AWS RE:Invent 2022 Coverage. I'm John Furrier, host of theCUBE. Got a great lineup here, Itamar Ankorion SVP Technology Alliance at Qlik and Peter McDonald, vice President, cloud partnerships and business development Snowflake. We're going to talk about bringing SAP data to life, for joint Snowflake, Qlik and AWS Solution. Gentlemen, thanks for coming on theCUBE Really appreciate it. >> Thank you. >> Thank you, great meeting you John. >> Just to get started, introduce yourselves to the audience, then going to jump into what you guys are doing together, unique relationship here, really compelling solution in cloud. Big story about applications and scale this year. Let's introduce yourselves. Peter, we'll start with you. >> Great. I'm Peter MacDonald. I am vice president of Cloud Partners and business development here at Snowflake. On the Cloud Partner side, that means I manage AWS relationship along with Microsoft and Google Cloud. What we do together in terms of complimentary products, GTM, co-selling, things like that. Importantly, working with other third parties like Qlik for joint solutions. On business development, it's negotiating custom commercial partnerships, large companies like Salesforce and Dell, smaller companies at most for our venture portfolio. >> Thanks Peter and hi John. It's great to be back here. So I'm Itamar Ankorion and I'm the senior vice president responsible for technology alliances here at Qlik. With that, own strategic alliances, including our key partners in the cloud, including Snowflake and AWS. I've been in the data and analytics enterprise software market for 20 plus years, and my main focus is product management, marketing, alliances, and business development. I joined Qlik about three and a half years ago through the acquisition of Attunity, which is now the foundation for Qlik data integration. So again, we focus in my team on creating joint solution alignment with our key partners to provide more value to our customers. >> Great to have both you guys, senior executives in the industry on theCUBE here, talking about data, obviously bringing SAP data to life is the theme of this segment, but this reinvent, it's all about the data, big data end-to-end story, a lot about data being intrinsic as the CEO says on stage around in the organizations in all aspects. Take a minute to explain what you guys are doing as from a company standpoint. Snowflake and Qlik and the solutions, why here at AWS? Peter, we'll start with you at Snowflake, what you guys do as a company, your mission, your focus. >> That was great, John. Yeah, so here at Snowflake, we focus on the data platform and until recently, data platforms required expensive on-prem hardware appliances. And despite all that expense, customers had capacity constraints, inexpensive maintenance, and had limited functionality that all impeded these organizations from reaching their goals. Snowflake is a cloud native SaaS platform, and we've become so successful because we've addressed these pain points and have other new special features. For example, securely sharing data across both the organization and the value chain without copying the data, support for new data types such as JSON and structured data, and also advance in database data governance. Snowflake integrates with complimentary AWS services and other partner products. So we can enable holistic solutions that include, for example, here, both Qlik and AWS SageMaker, and comprehend and bring those to joint customers. Our customers want to convert data into insights along with advanced analytics platforms in AI. That is how they make holistic data-driven solutions that will give them competitive advantage. With Snowflake, our approach is to focus on customer solutions that leverage data from existing systems such as SAP, wherever they are in the cloud or on-premise. And to do this, we leverage partners like Qlik native US to help customers transform their businesses. We provide customers with a premier data analytics platform as a result. Itamar, why don't you talk about Qlik a little bit and then we can dive into the specific SAP solution here and some trends >> Sounds great, Peter. So Qlik provides modern data integration and analytics software used by over 38,000 customers worldwide. Our focus is to help our customers turn data into value and help them close the gap between data all the way through insight and action. We offer click data integration and click data analytics. Click data integration helps to automate the data pipelines to deliver data to where they want to use them in real-time and make the data ready for analytics and then Qlik data analytics is a robust platform for analytics and business intelligence has been a leader in the Gartner Magic Quadrant for over 11 years now in the market. And both of these come together into what we call Qlik Cloud, which is our SaaS based platform. So providing a more seamless way to consume all these services and accelerate time to value with customer solutions. In terms of partnerships, both Snowflake and AWS are very strategic to us here at Qlik, so we have very comprehensive investment to ensure strong joint value proposition to we can bring to our mutual customers, everything from aligning our roadmaps through optimizing and validating integrations, collaborating on best practices, packaging joint solutions like the one we'll talk about today. And with that investment, we are an elite level, top level partner with Snowflake. We fly that our technology is Snowflake-ready across the entire product set and we have hundreds of joint customers together and with AWS we've also partnered for a long time. We're here to reinvent. We've been here with the first reinvent since the inaugural one, so it kind of gives you an idea for how long we've been working with AWS. We provide very comprehensive integration with AWS data analytics services, and we have several competencies ranging from data analytics to migration and modernization. So that's our focus and again, we're excited about working with Snowflake and AWS to bring solutions together to market. >> Well, I'm looking forward to unpacking the solutions specifically, and congratulations on the continued success of both your companies. We've been following them obviously for a very long time and seeing the platform evolve beyond just SaaS and a lot more going on in cloud these days, kind of next generation emerging. You know, we're seeing a lot of macro trends that are going to be powering some of the things we're going to get into real quickly. But before we get into the solution, what are some of those power dynamics in the industry that you're seeing in trends specifically that are impacting your customers that are taking us down this road of getting more out of the data and specifically the SAP, but in general trends and dynamics. What are you hearing from your customers? Why do they care? Why are they going down this road? Peter, we'll start with you. >> Yeah, I'll go ahead and start. Thanks. Yeah, I'd say we continue to see customers being, being very eager to transform their businesses and they know they need to leverage technology and data to do so. They're also increasingly depending upon the cloud to bring that agility, that elasticity, new functionality necessary to react in real-time to every evolving customer needs. You look at what's happened over the last three years, and boy, the macro environment customers, it's all changing so fast. With our partnerships with AWS and Qlik, we've been able to bring to market innovative solutions like the one we're announcing today that spans all three companies. It provides a holistic solution and an integrated solution for our customer. >> Itamar let's get into it, you've been with theCUBE, you've seen the journey, you have your own journey, many, many years, you've seen the waves. What's going on now? I mean, what's the big wave? What's the dynamic powering this trend? >> Yeah, in a nutshell I'll call it, it's all about time. You know, it's time to value and it's about real-time data. I'll kind of talk about that a bit. So, I mean, you hear a lot about the data being the new oil, but it's definitely, we see more and more customers seeing data as their critical enabler for innovation and digital transformation. They look for ways to monetize data. They look as the data as the way in which they can innovate and bring different value to the customers. So we see customers want to use more data so to get more value from data. We definitely see them wanting to do it faster, right, than before. And we definitely see them looking for agility and automation as ways to accelerate time to value, and also reduce overall costs. I did mention real-time data, so we definitely see more and more customers, they want to be able to act and make decisions based on fresh data. So yesterday's data is just not good enough. >> John: Yeah. >> It's got to be down to the hour, down to the minutes and sometimes even lower than that. And then I think we're also seeing customers look to their core business systems where they have a lot of value, like the SAP, like mainframe and thinking, okay, our core data is there, how can we get more value from this data? So that's key things we see all the time with customers. >> Yeah, we did a big editorial segment this year on, we called data as code. Data as code is kind of a riff on infrastructure as code and you start to see data becoming proliferating into all aspects, fresh data. It's not just where you store it, it's how you share it, it's how you turn it into an application intrinsically involved in all aspects. This is the big theme this year and that's driving all the conversations here at RE:Invent. And I'm guaranteeing you, it's going to happen for another five and 10 years. It's not stopping. So I got to get into the solution, you guys mentioned SAP and you've announced the solution by Qlik, Snowflake and AWS for your customers using SAP. Can you share more about this solution? What's unique about it? Why is it important and why now? Peter, Itamar, we'll start with you first. >> Let me jump in, this is really, I'll jump because I'm excited. We're very excited about this solution and it's also a solution by the way and again, we've seen proven customer success with it. So to your point, it's ready to scale, it's starting, I think we're going to see a lot of companies doing this over the next few years. But before we jump to the solution, let me maybe take a few minutes just to clarify the need, why we're seeing, why we're seeing customers jump to do this. So customers that use SAP, they use it to manage the core of their business. So think order processing, management, finance, inventory, supply chain, and so much more. So if you're running SAP in your company, that data creates a great opportunity for you to drive innovation and modernization. So what we see customers want to do, they want to do more with their data and more means they want to take SAP with non-SAP data and use it together to drive new insights. They want to use real-time data to drive real-time analytics, which they couldn't do to date. They want to bring together descriptive with predictive analytics. So adding machine learning in AI to drive more value from the data. And naturally they want to do it faster. So find ways to iterate faster on their solutions, have freedom with the data and agility. And I think this is really where cloud data platforms like Snowflake and AWS, you know, bring that value to be able to drive that. Now to do that you need to unlock the SAP data, which is a lot of also where Qlik comes in because typical challenges these customers run into is the complexity, inherent in SAP data. Tens of thousands of tables, proprietary formats, complex data models, licensing restrictions, and more than, you have performance issues, they usually run into how do we handle the throughput, the volumes while maintaining lower latency and impact. Where do we find knowledge to really understand how to get all this done? So these are the things we've looked at when we came together to create a solution and make it unique. So when you think about its uniqueness, because we put together a lot, and I'll go through three, four key things that come together to make this unique. First is about data delivery. How do you have the SAP data delivery? So how do you get it from ECC, from HANA from S/4HANA, how do you deliver the data and the metadata and how that integration well into Snowflake. And what we've done is we've focused a lot on optimizing that process and the continuous ingestion, so the real-time ingestion of the data in a way that works really well with the Snowflake system, data cloud. Second thing is we looked at SAP data transformation, so once the data arrives at Snowflake, how do we turn it into being analytics ready? So that's where data transformation and data worth automation come in. And these are all elements of this solution. So creating derivative datasets, creating data marts, and all of that is done by again, creating an optimized integration that pushes down SQL based transformations, so they can be processed inside Snowflake, leveraging its powerful engine. And then the third element is bringing together data visualization analytics that can also take all the data now that in organizing inside Snowflake, bring other data in, bring machine learning from SageMaker, and then you go to create a seamless integration to bring analytic applications to life. So these are all things we put together in the solution. And maybe the last point is we actually took the next step with this and we created something we refer to as solution accelerators, which we're really, really keen about. Think about this as prepackaged templates for common business analytic needs like order to cash, finance, inventory. And we can either dig into that a little more later, but this gets the next level of value to the customers all built into this joint solution. >> Yeah, I want to get to the accelerators, but real quick, Peter, your reaction to the solution, what's unique about it? And obviously Snowflake, we've been seeing the progression data applications, more developers developing on top of Snowflake, data as code kind of implies developer ecosystem. This is kind of interesting. I mean, you got partnering with Qlik and AWS, it's kind of a developer-like thinking real solution. What's unique about this SAP solution that's, that's different than what customers can get anywhere else or not? >> Yeah, well listen, I think first of all, you have to start with the idea of the solution. This are three companies coming together to build a holistic solution that is all about, you know, creating a great opportunity to turn SAP data into value this is Itamar was talking about, that's really what we're talking about here and there's a lot of technology underneath it. I'll talk more about the Snowflake technology, what's involved here, and then cover some of the AWS pieces as well. But you know, we're focusing on getting that value out and accelerating time to value for our joint customers. As Itamar was saying, you know, there's a lot of complexity with the SAP data and a lot of value there. How can we manage that in a prepackaged way, bringing together best of breed solutions with proven capabilities and bringing this to market quickly for our joint customers. You know, Snowflake and AWS have been strong partners for a number of years now, and that's not only on how Snowflake runs on top of AWS, but also how we integrate with their complementary analytics and then all products. And so, you know, we want to be able to leverage those in addition to what Qlik is bringing in terms of the data transformations, bringing data out of SAP in the visualization as well. All very critical. And then we want to bring in the predictive analytics, AWS brings and what Sage brings. We'll talk about that a little bit later on. Some of the technologies that we're leveraging are some of our latest cutting edge technologies that really make things easier for both our partners and our customers. For example, Qlik leverages Snowflakes recently released Snowpark for Python functionality to push down those data transformations from clicking the Snowflake that Itamar's mentioning. And while we also leverage Snowpark for integrations with Amazon SageMaker, but there's a lot of great new technology that just makes this easy and compelling for customers. >> I think that's the big word, easy button here for what may look like a complex kind of integration, kind of turnkey, really, really compelling example of the modern era we're living in, as we always say in theCUBE. You mentioned accelerators, SAP accelerators. Can you give an example of how that works with the technology from the third party providers to deliver this business value Itamar, 'cause that was an interesting comment. What's the example? Give an example of this acceleration. >> Yes, certainly. I think this is something that really makes this truly, truly unique in the industry and again, a great opportunity for customers. So we kind talked earlier about there's a lot of things that need to be done with SP data to turn it to value. And these accelerator, as the name suggests, are designed to do just that, to kind of jumpstart the process and reduce the time and the risk involved in such project. So again, these are pre-packaged templates. We basically took a lot of knowledge, and a lot of configurations, best practices about to get things done and we put 'em together. So think about all the steps, it includes things like data extraction, so already knowing which tables, all the relevant tables that you need to get data from in the contexts of the solution you're looking for, say like order to cash, we'll get back to that one. How do you continuously deliver that data into Snowflake in an in efficient manner, handling things like data type mappings, metadata naming conventions and transformations. The data models you build all the way to data mart definitions and all the transformations that the data needs to go through moving through steps until it's fully analytics ready. And then on top of that, even adding a library of comprehensive analytic dashboards and integrations through machine learning and AI and put all of that in a way that's in pre-integrated and tested to work with Snowflake and AWS. So this is where again, you get this entire recipe that's ready. So take for example, I think I mentioned order to cash. So again, all these things I just talked about, I mean, for those who are not familiar, I mean order to cash is a critical business process for every organization. So especially if you're in retail, manufacturing, enterprise, it's a big... This is where, you know, starting with booking a sales order, following by fulfilling the order, billing the customer, then managing the accounts receivable when the customer actually pays, right? So this all process, you got sales order fulfillment and the billing impacts customer satisfaction, you got receivable payments, you know, the impact's working capital, cash liquidity. So again, as a result this order to cash process is a lifeblood for many businesses and it's critical to optimize and understand. So the solution accelerator we created specifically for order to cash takes care of understanding all these aspects and the data that needs to come with it. So everything we outline before to make the data available in Snowflake in a way that's really useful for downstream analytics, along with dashboards that are already common for that, for that use case. So again, this enables customers to gain real-time visibility into their sales orders, fulfillment, accounts receivable performance. That's what the Excel's are all about. And very similarly, we have another one for example, for finance analytics, right? So this will optimize financial data reporting, helps customers get insights into P&L, financial risk of stability or inventory analytics that helps with, you know, improve planning and inventory management, utilization, increased efficiencies, you know, so in supply chain. So again, these accelerators really help customers get a jumpstart and move faster with their solutions. >> Peter, this is the easy button we just talked about, getting things going, you know, get the ball rolling, get some acceleration. Big part of this are the three companies coming together doing this. >> Yeah, and to build on what Itamar just said that the SAP data obviously has tremendous value. Those sales orders, distribution data, financial data, bringing that into Snowflake makes it easily accessible, but also it enables it to be combined with other data too, is one of the things that Snowflake does so well. So you can get a full view of the end-to-end process and the business overall. You know, for example, I'll just take one, you know, one example that, that may not come to mind right away, but you know, looking at the impact of weather conditions on supply chain logistics is relevant and material and have interest to our customers. How do you bring those different data sets together in an easy way, bringing the data out of SAP, bringing maybe other data out of other systems through Qlik or through Snowflake, directly bringing data in from our data marketplace and bring that all together to make it work. You know, fundamentally organizational silos and the data fragmentation exist otherwise make it really difficult to drive modern analytics projects. And that in turn limits the value that our customers are getting from SAP data and these other data sets. We want to enable that and unleash. >> Yeah, time for value. This is great stuff. Itamar final question, you know, what are customers using this? What do you have? I'm sure you have customers examples already using the solution. Can you share kind of what these examples look like in the use cases and the value? >> Oh yeah, absolutely. Thank you. Happy to. We have customers across different, different sectors. You see manufacturing, retail, energy, oil and gas, CPG. So again, customers in those segments, typically sectors typically have SAP. So we have customers in all of them. A great example is like Siemens Energy. Siemens Energy is a global provider of gas par services. You know, over what, 28 billion, 30 billion in revenue. 90,000 employees. They operate globally in over 90 countries. So they've used SAP HANA as a core system, so it's running on premises, multiple locations around the world. And what they were looking for is a way to bring all these data together so they can innovate with it. And the thing is, Peter mentioned earlier, not just the SAP data, but also bring other data from other systems to bring it together for more value. That includes finance data, these logistics data, these customer CRM data. So they bring data from over 20 different SAP systems. Okay, with Qlik data integration, feeding that into Snowflake in under 20 minutes, 24/7, 365, you know, days a year. Okay, they get data from over 20,000 tables, you know, over million, hundreds of millions of records daily going in. So it is a great example of the type of scale, scalability, agility and speed that they can get to drive these kind of innovation. So that's a great example with Siemens. You know, another one comes to mind is a global manufacturer. Very similar scenario, but you know, they're using it for real-time executive reporting. So it's more like feasibility to the production data as well as for financial analytics. So think, think, think about everything from audit to texts to innovate financial intelligence because all the data's coming from SAP. >> It's a great time to be in the data business again. It keeps getting better and better. There's more data coming. It's not stopping, you know, it's growing so fast, it keeps coming. Every year, it's the same story, Peter. It's like, doesn't stop coming. As we wrap up here, let's just get customers some information on how to get started. I mean, obviously you're starting to see the accelerators, it's a great program there. What a great partnership between the two companies and AWS. How can customers get started to learn about the solution and take advantage of it, getting more out of their SAP data, Peter? >> Yeah, I think the first place to go to is talk to Snowflake, talk to AWS, talk to our account executives that are assigned to your account. Reach out to them and they will be able to educate you on the solution. We have packages up very nicely and can be deployed very, very quickly. >> Well gentlemen, thank you so much for coming on. Appreciate the conversation. Great overview of the partnership between, you know, Snowflake and Qlik and AWS on a joint solution. You know, getting more out of the SAP data. It's really kind of a key, key solution, bringing SAP data to life. Thanks for coming on theCUBE. Appreciate it. >> Thank you. >> Thank you John. >> Okay, this is theCUBE coverage here at RE:Invent 2022. I'm John Furrier, your host of theCUBE. Thanks for watching. (upbeat music)

(upbeat music) >> Hello, welcome back to theCUBE's AWS RE:Invent 2022 Coverage. I'm John Furrier, host of theCUBE. Got a great lineup here, Itamar Ankorion SVP Technology Alliance at Qlik and Peter McDonald, vice President, cloud partnerships and business development Snowflake. We're going to talk about bringing SAP data to life, for joint Snowflake, Qlik and AWS Solution. Gentlemen, thanks for coming on theCUBE Really appreciate it. >> Thank you. >> Thank you, great meeting you John. >> Just to get started, introduce yourselves to the audience, then going to jump into what you guys are doing together, unique relationship here, really compelling solution in cloud. Big story about applications and scale this year. Let's introduce yourselves. Peter, we'll start with you. >> Great. I'm Peter MacDonald. I am vice president of Cloud Partners and business development here at Snowflake. On the Cloud Partner side, that means I manage AWS relationship along with Microsoft and Google Cloud. What we do together in terms of complimentary products, GTM, co-selling, things like that. Importantly, working with other third parties like Qlik for joint solutions. On business development, it's negotiating custom commercial partnerships, large companies like Salesforce and Dell, smaller companies at most for our venture portfolio. >> Thanks Peter and hi John. It's great to be back here. So I'm Itamar Ankorion and I'm the senior vice president responsible for technology alliances here at Qlik. With that, own strategic alliances, including our key partners in the cloud, including Snowflake and AWS. I've been in the data and analytics enterprise software market for 20 plus years, and my main focus is product management, marketing, alliances, and business development. I joined Qlik about three and a half years ago through the acquisition of Attunity, which is now the foundation for Qlik data integration. So again, we focus in my team on creating joint solution alignment with our key partners to provide more value to our customers. >> Great to have both you guys, senior executives in the industry on theCUBE here, talking about data, obviously bringing SAP data to life is the theme of this segment, but this reinvent, it's all about the data, big data end-to-end story, a lot about data being intrinsic as the CEO says on stage around in the organizations in all aspects. Take a minute to explain what you guys are doing as from a company standpoint. Snowflake and Qlik and the solutions, why here at AWS? Peter, we'll start with you at Snowflake, what you guys do as a company, your mission, your focus. >> That was great, John. Yeah, so here at Snowflake, we focus on the data platform and until recently, data platforms required expensive on-prem hardware appliances. And despite all that expense, customers had capacity constraints, inexpensive maintenance, and had limited functionality that all impeded these organizations from reaching their goals. Snowflake is a cloud native SaaS platform, and we've become so successful because we've addressed these pain points and have other new special features. For example, securely sharing data across both the organization and the value chain without copying the data, support for new data types such as JSON and structured data, and also advance in database data governance. Snowflake integrates with complimentary AWS services and other partner products. So we can enable holistic solutions that include, for example, here, both Qlik and AWS SageMaker, and comprehend and bring those to joint customers. Our customers want to convert data into insights along with advanced analytics platforms in AI. That is how they make holistic data-driven solutions that will give them competitive advantage. With Snowflake, our approach is to focus on customer solutions that leverage data from existing systems such as SAP, wherever they are in the cloud or on-premise. And to do this, we leverage partners like Qlik native US to help customers transform their businesses. We provide customers with a premier data analytics platform as a result. Itamar, why don't you talk about Qlik a little bit and then we can dive into the specific SAP solution here and some trends >> Sounds great, Peter. So Qlik provides modern data integration and analytics software used by over 38,000 customers worldwide. Our focus is to help our customers turn data into value and help them close the gap between data all the way through insight and action. We offer click data integration and click data analytics. Click data integration helps to automate the data pipelines to deliver data to where they want to use them in real-time and make the data ready for analytics and then Qlik data analytics is a robust platform for analytics and business intelligence has been a leader in the Gartner Magic Quadrant for over 11 years now in the market. And both of these come together into what we call Qlik Cloud, which is our SaaS based platform. So providing a more seamless way to consume all these services and accelerate time to value with customer solutions. In terms of partnerships, both Snowflake and AWS are very strategic to us here at Qlik, so we have very comprehensive investment to ensure strong joint value proposition to we can bring to our mutual customers, everything from aligning our roadmaps through optimizing and validating integrations, collaborating on best practices, packaging joint solutions like the one we'll talk about today. And with that investment, we are an elite level, top level partner with Snowflake. We fly that our technology is Snowflake-ready across the entire product set and we have hundreds of joint customers together and with AWS we've also partnered for a long time. We're here to reinvent. We've been here with the first reinvent since the inaugural one, so it kind of gives you an idea for how long we've been working with AWS. We provide very comprehensive integration with AWS data analytics services, and we have several competencies ranging from data analytics to migration and modernization. So that's our focus and again, we're excited about working with Snowflake and AWS to bring solutions together to market. >> Well, I'm looking forward to unpacking the solutions specifically, and congratulations on the continued success of both your companies. We've been following them obviously for a very long time and seeing the platform evolve beyond just SaaS and a lot more going on in cloud these days, kind of next generation emerging. You know, we're seeing a lot of macro trends that are going to be powering some of the things we're going to get into real quickly. But before we get into the solution, what are some of those power dynamics in the industry that you're seeing in trends specifically that are impacting your customers that are taking us down this road of getting more out of the data and specifically the SAP, but in general trends and dynamics. What are you hearing from your customers? Why do they care? Why are they going down this road? Peter, we'll start with you. >> Yeah, I'll go ahead and start. Thanks. Yeah, I'd say we continue to see customers being, being very eager to transform their businesses and they know they need to leverage technology and data to do so. They're also increasingly depending upon the cloud to bring that agility, that elasticity, new functionality necessary to react in real-time to every evolving customer needs. You look at what's happened over the last three years, and boy, the macro environment customers, it's all changing so fast. With our partnerships with AWS and Qlik, we've been able to bring to market innovative solutions like the one we're announcing today that spans all three companies. It provides a holistic solution and an integrated solution for our customer. >> Itamar let's get into it, you've been with theCUBE, you've seen the journey, you have your own journey, many, many years, you've seen the waves. What's going on now? I mean, what's the big wave? What's the dynamic powering this trend? >> Yeah, in a nutshell I'll call it, it's all about time. You know, it's time to value and it's about real-time data. I'll kind of talk about that a bit. So, I mean, you hear a lot about the data being the new oil, but it's definitely, we see more and more customers seeing data as their critical enabler for innovation and digital transformation. They look for ways to monetize data. They look as the data as the way in which they can innovate and bring different value to the customers. So we see customers want to use more data so to get more value from data. We definitely see them wanting to do it faster, right, than before. And we definitely see them looking for agility and automation as ways to accelerate time to value, and also reduce overall costs. I did mention real-time data, so we definitely see more and more customers, they want to be able to act and make decisions based on fresh data. So yesterday's data is just not good enough. >> John: Yeah. >> It's got to be down to the hour, down to the minutes and sometimes even lower than that. And then I think we're also seeing customers look to their core business systems where they have a lot of value, like the SAP, like mainframe and thinking, okay, our core data is there, how can we get more value from this data? So that's key things we see all the time with customers. >> Yeah, we did a big editorial segment this year on, we called data as code. Data as code is kind of a riff on infrastructure as code and you start to see data becoming proliferating into all aspects, fresh data. It's not just where you store it, it's how you share it, it's how you turn it into an application intrinsically involved in all aspects. This is the big theme this year and that's driving all the conversations here at RE:Invent. And I'm guaranteeing you, it's going to happen for another five and 10 years. It's not stopping. So I got to get into the solution, you guys mentioned SAP and you've announced the solution by Qlik, Snowflake and AWS for your customers using SAP. Can you share more about this solution? What's unique about it? Why is it important and why now? Peter, Itamar, we'll start with you first. >> Let me jump in, this is really, I'll jump because I'm excited. We're very excited about this solution and it's also a solution by the way and again, we've seen proven customer success with it. So to your point, it's ready to scale, it's starting, I think we're going to see a lot of companies doing this over the next few years. But before we jump to the solution, let me maybe take a few minutes just to clarify the need, why we're seeing, why we're seeing customers jump to do this. So customers that use SAP, they use it to manage the core of their business. So think order processing, management, finance, inventory, supply chain, and so much more. So if you're running SAP in your company, that data creates a great opportunity for you to drive innovation and modernization. So what we see customers want to do, they want to do more with their data and more means they want to take SAP with non-SAP data and use it together to drive new insights. They want to use real-time data to drive real-time analytics, which they couldn't do to date. They want to bring together descriptive with predictive analytics. So adding machine learning in AI to drive more value from the data. And naturally they want to do it faster. So find ways to iterate faster on their solutions, have freedom with the data and agility. And I think this is really where cloud data platforms like Snowflake and AWS, you know, bring that value to be able to drive that. Now to do that you need to unlock the SAP data, which is a lot of also where Qlik comes in because typical challenges these customers run into is the complexity, inherent in SAP data. Tens of thousands of tables, proprietary formats, complex data models, licensing restrictions, and more than, you have performance issues, they usually run into how do we handle the throughput, the volumes while maintaining lower latency and impact. Where do we find knowledge to really understand how to get all this done? So these are the things we've looked at when we came together to create a solution and make it unique. So when you think about its uniqueness, because we put together a lot, and I'll go through three, four key things that come together to make this unique. First is about data delivery. How do you have the SAP data delivery? So how do you get it from ECC, from HANA from S/4HANA, how do you deliver the data and the metadata and how that integration well into Snowflake. And what we've done is we've focused a lot on optimizing that process and the continuous ingestion, so the real-time ingestion of the data in a way that works really well with the Snowflake system, data cloud. Second thing is we looked at SAP data transformation, so once the data arrives at Snowflake, how do we turn it into being analytics ready? So that's where data transformation and data worth automation come in. And these are all elements of this solution. So creating derivative datasets, creating data marts, and all of that is done by again, creating an optimized integration that pushes down SQL based transformations, so they can be processed inside Snowflake, leveraging its powerful engine. And then the third element is bringing together data visualization analytics that can also take all the data now that in organizing inside Snowflake, bring other data in, bring machine learning from SageMaker, and then you go to create a seamless integration to bring analytic applications to life. So these are all things we put together in the solution. And maybe the last point is we actually took the next step with this and we created something we refer to as solution accelerators, which we're really, really keen about. Think about this as prepackaged templates for common business analytic needs like order to cash, finance, inventory. And we can either dig into that a little more later, but this gets the next level of value to the customers all built into this joint solution. >> Yeah, I want to get to the accelerators, but real quick, Peter, your reaction to the solution, what's unique about it? And obviously Snowflake, we've been seeing the progression data applications, more developers developing on top of Snowflake, data as code kind of implies developer ecosystem. This is kind of interesting. I mean, you got partnering with Qlik and AWS, it's kind of a developer-like thinking real solution. What's unique about this SAP solution that's, that's different than what customers can get anywhere else or not? >> Yeah, well listen, I think first of all, you have to start with the idea of the solution. This are three companies coming together to build a holistic solution that is all about, you know, creating a great opportunity to turn SAP data into value this is Itamar was talking about, that's really what we're talking about here and there's a lot of technology underneath it. I'll talk more about the Snowflake technology, what's involved here, and then cover some of the AWS pieces as well. But you know, we're focusing on getting that value out and accelerating time to value for our joint customers. As Itamar was saying, you know, there's a lot of complexity with the SAP data and a lot of value there. How can we manage that in a prepackaged way, bringing together best of breed solutions with proven capabilities and bringing this to market quickly for our joint customers. You know, Snowflake and AWS have been strong partners for a number of years now, and that's not only on how Snowflake runs on top of AWS, but also how we integrate with their complementary analytics and then all products. And so, you know, we want to be able to leverage those in addition to what Qlik is bringing in terms of the data transformations, bringing data out of SAP in the visualization as well. All very critical. And then we want to bring in the predictive analytics, AWS brings and what Sage brings. We'll talk about that a little bit later on. Some of the technologies that we're leveraging are some of our latest cutting edge technologies that really make things easier for both our partners and our customers. For example, Qlik leverages Snowflakes recently released Snowpark for Python functionality to push down those data transformations from clicking the Snowflake that Itamar's mentioning. And while we also leverage Snowpark for integrations with Amazon SageMaker, but there's a lot of great new technology that just makes this easy and compelling for customers. >> I think that's the big word, easy button here for what may look like a complex kind of integration, kind of turnkey, really, really compelling example of the modern era we're living in, as we always say in theCUBE. You mentioned accelerators, SAP accelerators. Can you give an example of how that works with the technology from the third party providers to deliver this business value Itamar, 'cause that was an interesting comment. What's the example? Give an example of this acceleration. >> Yes, certainly. I think this is something that really makes this truly, truly unique in the industry and again, a great opportunity for customers. So we kind talked earlier about there's a lot of things that need to be done with SP data to turn it to value. And these accelerator, as the name suggests, are designed to do just that, to kind of jumpstart the process and reduce the time and the risk involved in such project. So again, these are pre-packaged templates. We basically took a lot of knowledge, and a lot of configurations, best practices about to get things done and we put 'em together. So think about all the steps, it includes things like data extraction, so already knowing which tables, all the relevant tables that you need to get data from in the contexts of the solution you're looking for, say like order to cash, we'll get back to that one. How do you continuously deliver that data into Snowflake in an in efficient manner, handling things like data type mappings, metadata naming conventions and transformations. The data models you build all the way to data mart definitions and all the transformations that the data needs to go through moving through steps until it's fully analytics ready. And then on top of that, even adding a library of comprehensive analytic dashboards and integrations through machine learning and AI and put all of that in a way that's in pre-integrated and tested to work with Snowflake and AWS. So this is where again, you get this entire recipe that's ready. So take for example, I think I mentioned order to cash. So again, all these things I just talked about, I mean, for those who are not familiar, I mean order to cash is a critical business process for every organization. So especially if you're in retail, manufacturing, enterprise, it's a big... This is where, you know, starting with booking a sales order, following by fulfilling the order, billing the customer, then managing the accounts receivable when the customer actually pays, right? So this all process, you got sales order fulfillment and the billing impacts customer satisfaction, you got receivable payments, you know, the impact's working capital, cash liquidity. So again, as a result this order to cash process is a lifeblood for many businesses and it's critical to optimize and understand. So the solution accelerator we created specifically for order to cash takes care of understanding all these aspects and the data that needs to come with it. So everything we outline before to make the data available in Snowflake in a way that's really useful for downstream analytics, along with dashboards that are already common for that, for that use case. So again, this enables customers to gain real-time visibility into their sales orders, fulfillment, accounts receivable performance. That's what the Excel's are all about. And very similarly, we have another one for example, for finance analytics, right? So this will optimize financial data reporting, helps customers get insights into P&L, financial risk of stability or inventory analytics that helps with, you know, improve planning and inventory management, utilization, increased efficiencies, you know, so in supply chain. So again, these accelerators really help customers get a jumpstart and move faster with their solutions. >> Peter, this is the easy button we just talked about, getting things going, you know, get the ball rolling, get some acceleration. Big part of this are the three companies coming together doing this. >> Yeah, and to build on what Itamar just said that the SAP data obviously has tremendous value. Those sales orders, distribution data, financial data, bringing that into Snowflake makes it easily accessible, but also it enables it to be combined with other data too, is one of the things that Snowflake does so well. So you can get a full view of the end-to-end process and the business overall. You know, for example, I'll just take one, you know, one example that, that may not come to mind right away, but you know, looking at the impact of weather conditions on supply chain logistics is relevant and material and have interest to our customers. How do you bring those different data sets together in an easy way, bringing the data out of SAP, bringing maybe other data out of other systems through Qlik or through Snowflake, directly bringing data in from our data marketplace and bring that all together to make it work. You know, fundamentally organizational silos and the data fragmentation exist otherwise make it really difficult to drive modern analytics projects. And that in turn limits the value that our customers are getting from SAP data and these other data sets. We want to enable that and unleash. >> Yeah, time for value. This is great stuff. Itamar final question, you know, what are customers using this? What do you have? I'm sure you have customers examples already using the solution. Can you share kind of what these examples look like in the use cases and the value? >> Oh yeah, absolutely. Thank you. Happy to. We have customers across different, different sectors. You see manufacturing, retail, energy, oil and gas, CPG. So again, customers in those segments, typically sectors typically have SAP. So we have customers in all of them. A great example is like Siemens Energy. Siemens Energy is a global provider of gas par services. You know, over what, 28 billion, 30 billion in revenue. 90,000 employees. They operate globally in over 90 countries. So they've used SAP HANA as a core system, so it's running on premises, multiple locations around the world. And what they were looking for is a way to bring all these data together so they can innovate with it. And the thing is, Peter mentioned earlier, not just the SAP data, but also bring other data from other systems to bring it together for more value. That includes finance data, these logistics data, these customer CRM data. So they bring data from over 20 different SAP systems. Okay, with Qlik data integration, feeding that into Snowflake in under 20 minutes, 24/7, 365, you know, days a year. Okay, they get data from over 20,000 tables, you know, over million, hundreds of millions of records daily going in. So it is a great example of the type of scale, scalability, agility and speed that they can get to drive these kind of innovation. So that's a great example with Siemens. You know, another one comes to mind is a global manufacturer. Very similar scenario, but you know, they're using it for real-time executive reporting. So it's more like feasibility to the production data as well as for financial analytics. So think, think, think about everything from audit to texts to innovate financial intelligence because all the data's coming from SAP. >> It's a great time to be in the data business again. It keeps getting better and better. There's more data coming. It's not stopping, you know, it's growing so fast, it keeps coming. Every year, it's the same story, Peter. It's like, doesn't stop coming. As we wrap up here, let's just get customers some information on how to get started. I mean, obviously you're starting to see the accelerators, it's a great program there. What a great partnership between the two companies and AWS. How can customers get started to learn about the solution and take advantage of it, getting more out of their SAP data, Peter? >> Yeah, I think the first place to go to is talk to Snowflake, talk to AWS, talk to our account executives that are assigned to your account. Reach out to them and they will be able to educate you on the solution. We have packages up very nicely and can be deployed very, very quickly. >> Well gentlemen, thank you so much for coming on. Appreciate the conversation. Great overview of the partnership between, you know, Snowflake and Qlik and AWS on a joint solution. You know, getting more out of the SAP data. It's really kind of a key, key solution, bringing SAP data to life. Thanks for coming on theCUBE. Appreciate it. >> Thank you. >> Thank you John. >> Okay, this is theCUBE coverage here at RE:Invent 2022. I'm John Furrier, your host of theCUBE. Thanks for watching. (upbeat music)

>>In late 2009 when the industry was just beginning to offer so-called converged infrastructure, CI Nutanix was skating to the puck, so to speak, meaning unlike conversion infrastructure, which essentially bolted together compute and networking and storage into a single skew that was very hardware centric. Nutanix was focused on creating HCI hyperconverged infrastructure, which was a software led architecture that unified the key elements of data center infrastructure. Now, while both approaches saved time and money, HCI took the concept to new heights of cost savings and simplicity. Hyperconverged infrastructure became a staple of private clouds creating a cloudlike experience. OnPrem. As the public cloud evolved and grew, more and more customers are now taking a cloud first approach to it. So the challenge becomes how do you remodel your IT house so that you can connect your on-prem workloads to the cloud, to both simplify cloud migration, while at the same time creating an identical experience across your estate? >>Hello, and welcome to this special program, Accelerate Hybrid Cloud with Nutanix and Microsoft Made Possible by By Nutanix and produced by the Cube. I'm Dave Ante, one of your hosts today. Now, in this session, we'll hear how Nutanix is evolving its initial vision of simplifying infrastructure, deployment and management to support modern applications by partnering with Microsoft to enable that consistent experience that we talked about earlier, to extend hybrid cloud to Microsoft Azure and take advantage of cloud native tooling. Now, what's really important to stress here, and you'll hear this in our second segment, substantive engineering work has gone into this partnership. A lot of partnerships are sealed with a press release. We sometimes call it a Barney deal. You know, I love you, you love me. Like Barney, the once popular children's dinosaur character. We dig into the critical engineering aspects that enable that seamless connection between on-prem infrastructure and the public cloud. >>Now, in our first segment, Lisa Martin talks to Alro Salise, who is the vice president of Global ISD Commercial Solutions at Microsoft, and Michael Les Chica, who is the vice president of business development for the cloud and database partner ecosystem at Nutanix. Now, after that, Lisa will kick it back to me in our Boston studios to speak with Eric Lockard, who is the corporate vice president of Microsoft Azure specialized, along with Thomas Cornell, who is the senior vice president of products at Nutanix. And Indu Carey, who's the senior vice president of of engineering for NCI and NNC two at Nutanix. And we'll dig deeper into the announcement and it's salient features. Thanks for being with us. We hope you enjoy the program. Over to Lisa. >>Hi everyone. Welcome to our event Accelerate Hybrid Cloud with Nutanix and Microsoft. I'm your host Lisa Martin, and I've got two great guests here with me to give you some exciting news. Please welcome Alva Salise, the Vice President of Global ISD Commercial Solutions at Microsoft, and Michael Les Chika, VP of Business Development Cloud and database partner ecosystem at Nutanix. Guys, it's great to have you on the program. Thanks so much for joining me today. Great to be here. >>Thank you, Lisa. Looking forward, >>Yeah, so let's go ahead and start with you. Talk to me from your lens, what are you seeing in terms of the importance of the role of the the ISV ecosystem and really helping customers make their business outcomes successful? >>Oh, absolutely. Well, first of all, thank you for the invitation and thank you Michael and the Nutanix team for the partnership. The the ISV ecosystem plays a critical role as we support our customers and enable them in their data transformation journeys to create value, to move at their own pace, and more important to be sure that every one of them, as they transform themselves, have the right set of solutions for the long term with high differentiation, cost effectiveness and resiliency, especially given the times that we're living. >>Yeah, that resiliency is getting more and more critical as each day goes on. Ava was sticking with you. We got Microsoft Ignite going on today. What are some of the key themes that we should expect this year and how do they align to Microsoft's vision and strategy? >>Ah, great question. Thank you. When you think about it, we wanna talk about the topics that are very relevant and our customers have asked us to go deeper and, and share with them. One of them, as you may imagine, is how can we do more with less using Azure, especially given the current times that we're living in the, the business context has changed so much, they have different imperative, different different amount of pressure and priorities. How can we help? How can we combine the platform, the value that Microsoft can bring and our Microsoft ISV partner ecosystem to deliver more value and enable them to have their own journey? Actually, in that frame, if I may, we are making this announcement today with Nutanix. I, the Nutanix cloud clusters are often the fastest way on which customers will be able to do that journey into the cloud because it's very consistent with environments that they already know and use on premise. And once they go into the cloud, then they have all the benefit of scale, agility, resiliency, security, and cost benefits that they're looking for. So that topic and this type of announcements will be a big part of what we doing. Ignite, >>Exciting. Michael, let's bring you into the conversation now. Big milestone of our RDTs that the general availability of Nutanix Cloud clusters on Azure. Talk to us about that from Nutanix's perspective and also gimme a little bit of color, Michael, on the partnership, the relationship. >>Yeah, sure, absolutely. So we actually entered a partnership couple years ago, so we've been working on this solution quite a while, but really our ultimate goal from day one was really to make our customers journeys to hybrid cloud simpler and faster. So really for both companies, I think our goal is really being that trusted partner for our customers in their innovation journey. And as mentioned, you know, in the current macroeconomic conditions, really our customers really care about, but they have to be mindful of their bottom line as well. So they're really looking to leverage their existing investments in technology skill sets and leverage the most out of that. So the things like, for example, cost to operations and keeping those things consistent, cost on premises and the cloud are really important as customers are thinking about growth initiatives that they wanna implement. And of course, going to Azure public cloud is an important one as they think about flexibility, scale and modernizing their apps. >>And of course, as we look at the customer landscape, a lot of customers have an on on footprint, right? Whether that's for regulatory reasons for business or other technical reasons. So hybrid cloud has really become an ideal operating model for a lot of the customers that we see today. So really our partnership with Microsoft is critical because together, I really do see our US together simplifying that journey to the public cloud and making sure that it's not only easy but secure and really seamless. And really, I see our partnership as bringing the strengths of each company together, right? So Nutanix, of course, is known in the past versus hyperconverge infrastructure and really breaking down those silos between networking, compute, storage, and simplifying that infrastructure and operations. And our customers love that for the products and our, our NPS score of 90 over the last seven years. And if you look at Azure, at Microsoft, they're truly best in class cloud infrastructure with cutting edge services and innovation and really global scale. So when you think about those two combinations, right, that's really powerful for customers to be able to take their applications and whether they're on or even, and really combining all those various hybrid scenarios. And I think that's something that's pretty unique that we're to offer customers. >>Let's dig into that uniqueness of our, bringing you back into the conversation. You guys are meeting customers where they are helping them to accelerate their cloud transformations, delivering that consistency, you know, whether they're on-prem in Azure, in in the cloud. Talk to me about, from Microsoft's perspective about the significance of this announcement. I understand that the, the preview was oversubscribed, so the demand from your joint customers is clear. >>Thank you, Lisa. Michael, personally, I'm very proud and at the company we're very proud of the world that we did together with Nutanix. When you see two companies coming together with the mission of empowering customers and with the customer at the center and trying to solve real problems in this case, how to drive hybrid cloud and what is the best approach for them, opening more opportunities is, is, is extremely inspiring. And of course the welcome reception that we have from customer reiterates that we generating that value. Now, when you combine the power of Azure, that is very well known by resiliency, the scale, the performance, the elasticity, and the range of services with the reality of companies that might have hundreds or even thousands of different applications and data sources, those cloud journeys are very different for each and every one of them. So how do we combine our capabilities between Nutanix and Microsoft to be sure that that hybrid cloud journey that every one is gonna take can be simplified, you can take away the risk, the complexity on that transformation creates tones of value. >>And that's what a customers are asking us today. Either because they're trying to move and modernize their environment to Azure, or they're bringing their, you know, a enable ordinate services and cluster and data services on premise to a Nutanix platform, we together can combine and solve for that adding more value for any scenario that customers may have. And this is not once and done, this is not that we building, we forget it. It's a partnership that keeps evolving and also includes work that we do with our solution sales alliances that go to market seems to be sure that the customers have diverse service and support to make, to create the outcomes that they're asking us to deliver. >>Talk to me a little bit about the customers that were in the beta, as we mentioned, Alva, the, the preview was oversubscribed. So as I talked about earlier, the demand is clearly there. Talk to me about some of the customers in beta, you can even anonymize them or maybe talk about them by industry, but what, what were some of the, the key things they came to these two companies looking to, to solve, get to the cloud faster, be able to deliver the same sets of services with familiarity so that from a, they're able to do more with less? >>Maybe I could take that one out of our abital lines. It did. It means, but yeah, so like, like we, like you mentioned Lisa, you know, we've had a great preview oversubscribe, we had lots of, of cu not only customers, but also partners battle testing the solution. And you know, we're obviously very pleased now to have GN offered to everyone else, but one of our customers, Camper J was really looking forward to seeing how do they leverage Ncq and Azure to, like I mentioned, reduce that work workload, my, my migration and a risk for that and making sure, hey, some of the applications, maybe we are going to go and rewrite them, refactor them to take them natively to Azure. But there's others where we wanna lift and shift them to Azure. But like I mentioned, it's not just customers, right? We've been working with partners like PCs and Citrix where they share the same goal as Microsoft and Nutanix provides that superior customer experience where whatever the operating model might be for that customer. So they're going to be leveraging NC two on Azure to really provide those hybrid cloud experiences for their solutions on top of building on top of the, the work that we've done together. >>So this really kind of highlights the power of that Alva, the power of the ISV ecosystem and what you're all able to do together to really help customers achieve the outcomes that they individually need. >>A absolutely, look, I mean, we strongly believe that when you partner properly with an V you get to the, to the magical framework, one plus one equals three or more because you are combining superpowers and you are solving the problem on behalf of the customer so they can focus on their business. And this is a wonderful example, a very inspiring one where when you see the risk, the complexity that all these projects normally have, and Michael did a great job framing some of them, and the difference that they have now by having NC to on Azure, it's night and day. And we are fully committed to keep driving this innovation, this partnership on service of our customers and our partner ecosystem because at the same time, making our partners more successful, generating more value for customers and for all of us. >>Abar, can you comment a little bit on the go to market? Like how, how do your joint customers engage? What does that look like from their perspective? >>You know, when you think about the go to market, a lot of that is we have, you know, teams all over the world that will be aligned and working together in service of the customer. There is marketing and demand generation that will be done, that will be also work on enjoying opportunities that we will manage as well as a very tight connection on projects to be sure that the support experience for customers is well aligned. I don't wanna go into too much detail, but I will like to guarantee that our intent is not only to create an incredible technological experience, which the, the development teams are done, but also a great experience for the customers that are going through these projects, interacting with both teams that will work as one in service to empower the customer to achieve the outcomes that they need. >>Yeah, and just to comment maybe a little bit more on what Albar said, you know, it's not just about the product integration or it's really the full end to end experience for our customers. So when we embarked on this partnership with Microsoft, we really thought about what is the right product integration and with our engineering teams, but also how do we go and talk to customers with value prop together and all the way down through to support. So we actually been worked on how do we have a single joint support for our customers. So it doesn't really matter how the customer engages, they really see this as an end to end single solution across two companies. >>And that's so critical given just the, the natural challenges that that organizations face and the dynamics of the macro economic environment that we're living in. For them, for customers to be able to have that really seamless single point of interaction, they want that consistent experience on-prem to the cloud. But from an engagement perspective that you're, what sounds like what you're doing, Michael and Avaro is, is goes a long way to really giving customers a much more streamlined approach so that they can be laser focused on solving the business problems that they have, being competitive, getting products to market faster and all that good stuff. Michael, I wonder if you could comment on maybe the cultural alignment that Nutanix and Microsoft have. I know Microsoft's partner program has been around for decades and decades. Michael, what does that cultural alignment look like from, you know, the sales and marketing folks down to engineering, down to support? >>Yeah, I think honestly that was, that was something that kind of fit really well and we saw really a long alignment from day one. Of course, you know, Nutanix cares a lot about our customer experience, not just within the products, but again, through the entire life cycle to support and so forth. And Microsoft's no different, right? There's a huge emphasis on making sure that we provide the best customer experience and that we're also focusing on solving real world customer problems, right? And really focusing on the biggest problems that customers have. So really culturally it felt, it felt really natural. It felt like we were a single team, although it's, you know, two bar organizations working together, but I really felt like a single team working day in, day out on, on solving customer problems together. >>Yeah, >>Let, go ahead. >>No, I would say, well say Michael, the, the one element that we complement, the, I think the answer was super complete, is the, the fact that we work together from the outside in, look at it from the customer lenses is extremely powerful and inspire, as I mentioned, because that's what it's all about. And when you put the customer at the center, everything else falls in part on its its own place very, very quickly. And then it's hard work and innovation and, you know, doing what we do best, which is combining over superpowers in service of that customer. So that was the piece that, you know, I, I cannot emphasize enough how inspiring he's been. And again, the, the response for the previous is a great example of the opportunity that we have in there. >>And you've taken a lot of complexity out of the customer environment and I can imagine that the GA of Nutanix cloud clusters on Azure is gonna be a huge benefit for customers in every industry. Last question guys, I wanna get both your perspectives on Michael, we'll start with you and then Lvra will wrap with you. What's next? Obviously a lot of exciting stuff. What's next for the partnership of these, these two superheroes together, Michael? >>Yeah, so I think our goal doesn't change, right? I think our North star is to continue to make it easy for our customers to adopt, migrate and modernize their applications, leveraging Nutanix and Microsoft Azure, right? And I think NC two and Azure is just the start of that. So kind of maybe more immediate, like, you know, we mentioned obviously we have, we announced the ga that's J in Americas, but kind of the next more immediate step over the next few months look for us to continue expanding beyond Americas and making sure that we have support across all the global regions. And then beyond that, you know, again, as of our mentioned, it's working from kind of the s backwards. So we're, we're not, no, we're not waiting for ega. We're already working on the next set of solutions saying what are other problems that customer facing, especially across, they're running their workload cross on premises and public cloud, and what are the next set of solutions that we can deliver to the market to solve those real challenges for. >>It sounds really strongly that, that the partnership here, we're talking about Nutanix and Microsoft, it's really Nutanix and Microsoft with the customer at this center. I think you've both done a great job of articulating that there's laser focus there. Our last word to you, what excites you about the momentum that Microsoft and Nutanix have for the customers? >>Well, thank you Lisa. Michael, I will tell you, when you hear the customer feedback on the impact that you're having, that's the most inspiring part because you know you're generating value, you know, you're making a difference, especially in these complex times when the, the partnership gets tested where the, the right, you know, relationship gets built. We're being there for customers is extremely inspiring. Now, as Michael mentioned, this is all about what customer needs and how do we go even ahead of the game, being sure that we're ready not for what is the problem today, but the opportunities that we have tomorrow to keep working on this. We have a huge TA task ahead to be sure that we bring this value globally in the right way with the right quality. Every word, which is a, is never as small fist as you may imagine. You know, the, the world is a big place, but also the next wave of innovations that will be customer driven to keep and, and raise the bar on how, how much more value can we unlock and how much empowerment can we make for the customer to keep in innovating at their own pace, in their own terms. >>Absolutely that customer empowerment's key. Guys, it's been a pleasure talking to you about the announcement Nutanix cloud clusters on Azure of our Michael, thank you for your time, your inputs and helping us understand the impact that this powerhouse relationship is making. >>Thank you for having Lisa and thank you AAR for joining >>Me. Thank you Lisa, Michael, it's been fantastic. I looking forward and thank you to the audience for being here with us. Yeah, stay >>Tuned. Thanks to the audience. Exactly. And stay tuned. There's more to come. We have coming up next, a deeper conversation on the announcement with Dave and product execs from both Microsoft. You won't wanna.

>>Hi everyone. Welcome to our event Accelerate Hybrid Cloud with Nutanix and Microsoft. I'm your host Lisa Martin, and I've got two great guests here with me to give you some exciting news. Please welcome Alva Salise, the Vice President of Global ISV Commercial Solutions at Microsoft. And Michael Luka, VP of Business Development Cloud and database partner ecosystem at Nutanix. Guys, it's great to have you on the program. Thanks so much for joining me today. Great to be here. >>Thank you, Lisa. Looking forward, >>Yeah, so a, let's go ahead and start with you. Talk to me from your lens, what are you seeing in terms of the importance of the role of the the ISV ecosystem and really helping customers make their business outcomes successful? >>Well, absolutely. Well, first of all, thank you for the invitation and thank you Michael and the Nutanix team for the partnership. So the, the ISV ecosystem plays a critical role as we support our customers and enable them in their data transformation journeys to create value, to move at the own pace, and more important to ensure that every one of them as they transform themselves, have the right set of solutions for the long term with high differentiation, cost effectiveness and resiliency, especially given the times that we're living in. >>Yeah, that resiliency is getting more and more critical as each day goes on. Ava was sticking with you. We got Microsoft Ignite going on today. What are some of the key themes that we should expect this year and how do they align to Microsoft's vision and strategy? >>Ah, great question. Thank you. When you think about it, we wanna talk about the topics that are very relevant and our customers have asked us to go deeper and, and share with them. One of them, as you may imagine, is how can we do more with less using Azure, especially given the current times that we're living in the, the business context has changed so much. They have different imperative, different different amount of pressure and priorities. How can we help, how can we combine the platform, the value that Microsoft can bring and or Microsoft ISV power ecosystem to deliver more value and enable them to have their own journey? Actually, in that frame, if I may, we are making this announcement today with Nutanix. The Nutanix cloud clusters are often the fastest way on which customers will be able to do that journey into the cloud because it's very consistent with environments that they already know and use on premise. And once they go into the cloud, then they have all the benefit of scale, agility, resiliency, security and cost benefits that they're looking for. So that topic and this type of announcements will be a big part of what we doing. Ignite >>Then exciting. Michael, let's bring you into the conversation now. Sure. Big milestone of our RDTs that the general availability of Nutanix Cloud clusters on Azure. Talk to us about that from Nutanix's perspective and also gimme a little bit of color, Michael, on the partnership, the relationship. >>Yeah, sure. Absolutely. So we actually entered a partnership couple years ago, so we've been working on this quite a while. But really our ultimate goal from day one was really to make our customers journeys to hybrid cloud simpler and faster. So really for both companies, I think our goal is really being that trusted partner for our customers in their innovation journey. And as I mentioned, you know, in the current macroeconomic conditions, really our customers really care about growing their top line, but they have to be mindful of their bottom line as well. So they're really looking to leverage their existing investments in technology skill and leverage the most that, So the things like, for example, cost to operations and keeping those things cost on premises and are really important as customers are thinking about growth initiatives that they wanna implement. And of course going to Azure public cloud is an important one as they think about flexibility, scale and modernizing in their apps. >>And of course as we look at the customer landscape, a lot of customers have an footprint, right? Whether that's for regulatory reasons for business or other technic for reasons. So hybrid cloud has really become an ideal operating model for a lot of the customers that we see today. So really our partnership with Microsoft is critical because together, I really do see our US together simplifying that journey to the public cloud and making sure that it's not only easy but secure and really seamless. And really, I see our partnership as bringing the strengths of each company together, right? So Nutanix, of course, is known in the past versus hyperconverge infrastructure and really breaking down those silos between networking, compute, storage, and simplifying that infrastructure and operations. And our customers love that for the products and our, our NPS score of 90 over the last seven years. And if you look at Azure, at Microsoft, they're truly best in class cloud infrastructure with cutting edge services and innovation and really global scale. So when you think about those two combinations, right, that's really powerful for customers to be able to take their applications and whether they're on pre the cloud or even the edge and really combining all those various hybrid scenarios. And I think that's something that's pretty unique that we're able to offer our joint customers. >>Let's into that uniqueness of our, bringing you back into the conversation, you guys are meeting customers where they are helping them to accelerate their cloud transformations, delivering that consistency, you know, whether they're on-prem in Azure, in in the cloud. Talk to me about, from Microsoft's perspective about the significance of this announcement. I understand that the, the preview was oversubscribed, so the demand from your joint customers is clear. >>Thank you, Lisa. Michael, personally, I'm very proud and at the company we're very proud of the world that we did together with Nutanix. When you see two companies coming together with the mission of empowering customers and with the customer at the center and trying to solve real problems in this case, how to drive hybrid cloud and what is the best approach for them, opening more opportunities is, is is extremely inspiring. And of course the welcome reception that we have from customer reiterates that we generating that value. Now, when you combine the power of Azure, that is very well known by resiliency, the scale, the performance, the elasticity, and the range of services with the reality of companies that might have hundreds of even thousands of different applications and data sources, those cloud journeys are very different for each and every one of them. So how do we combine our capabilities between Nutanix and Microsoft to be sure that that hybrid cloud journey that every one is gonna take can be simplified, you can take away the risk, the complexity on that transformation creates tons of value. >>And that's what a customers are asking us today. Either because they're trying to move and modernize their environment to Azure, or they're bringing their, you know, a enable services and cluster and data services on premise to the Nutanix platform, we together can combine and solve for that adding more value for any scenario that customers may have. And this is not once and done, this is not that we building, we forget it, it's a partnership that keeps evolving and also includes work that we do with our solution sales alliances that go to market seems to be sure that the customers have diverse service and support to make, to, to create the outcomes that they're asking us to deliver. >>And can you comment a little bit further, maybe both of you, of our, starting with you and then Michael, what are some of those business outcomes that customers are coming to Microsoft and Nutanix saying, help us, we've gotta be more competitive, we've gotta get, we've gotta be able to get solutions to market faster, et cetera. What are those key outcomes that these two powerhouse companies are helping customers to unlock? >>Yeah, I will say, look, the range of imperative of customers varies greatly depending on the industry, depending on the positioning. I think that the fundamental question is given your imperative, do we have the ability to empower you to achieve the outcome that you want? And these days, of course, the tons of companies, given the the business context that are being very conscious on cost and efficiency, how do you do more with less? How do I keep innovating? Because innovation will be at the heart of the solutions, but I do that on my own pace with my own priorities. That higher level answer is the one that we're enabling through partnership, like the one we're we're sharing today to the market with Nutanix. >>Yeah, I think >>From you, >>Go ahead. I was just gonna comment ON'S pump as well is that absolutely really depends on the customer and what they're trying to achieve, right? As they think about the next set of innovation that they're trying to develop. But for example, we take a, a web, a use case that we've seen with some of the customers is like migration to the cloud, right? And you know, a lot of companies, they embark on that migration. We see there's a lot of data that says basically, you know, it's much harder than it looks, right? And a lot of these projects become years behind schedule and millions and millions of dollars over budget, right? So reducing that risk and saying, Hey, how do I, can I land in Azure? And then bit by bit start thinking, how do I continue to innovate to get, since now I have easy and secure access while I'm in Azure with, and seek with Nutanix Nutanix clusters on Azure to continue my innovation by taking advantage of Azure native services, right? But again, like Aaro said, it's, it really depends on what the customer goals are. >>Talk to me a little bit about the customers that were in the beta, as we mentioned, Alva, the, the preview was oversubscribed. So as I talked about earlier, the demand is clearly there. Talk to me about some of the customers and beta, you can even anonymize them or maybe talk about them by industry, but what, what were some of the, the key things they came to these two companies looking to, to solve, get to the cloud faster, be able to deliver the same sets of services with familiarity so that from a, they're able to do more with less? >>Maybe I could take that one out of our rebuttal lines. It does means, but yeah, so like, like, like you mentioned, Lisa, you know, we've had a great preview oversubscribe, we had lots of CU not only s but also partners battle solution. And you know, we're obviously very pleased now to have offered to everyone else, but one of our customers Camp Day was really looking forward to seeing how do they leverage Nstitute and Azure to, like I mentioned, reduce that work workload, migration and risk for that and making sure, hey, some of the applications maybe we are going to go and rewrite them, refactor them to take them natively to Azure. But there's others where we wanna lift and shift them to Azure. But like I mentioned, it's not just customers, right? We've been working with partners like PCs and Citrix where they share the same goal as Microsoft and Nutanix provides that superior customer experience where whatever the operating model might be for that customer. So they're going to be leveraging NC two on Azure to really provide those hybrid cloud experiences for their solutions on top of building on top of the, the work that we've done together. >>So this really kind of highlights the power of that Ava, the power of the ISB ecosystem and what you're all able to do together to really help customers achieve the outcomes that they individually need. >>A absolutely, look, I mean, we strongly believe that when you partner properly with an isv, you get to the, to the magical framework, one plus one equals three or more because you are combining superpowers and you are solving the problem on behalf of the customer so they can focus on their business. And this is a wonderful example, a very inspiring one where when you see the risk, the complexity that all these projects normally have, and Michael did a great job framing some of them, and the difference that they have now by having NC to on Azure, it's night and day. And we are fully committed to keep driving this innovation, this partnership on service of our customers and our power ecosystem. Because at the same time, making our powers more successful, generating more value for customers and for all of us >>Of, Can you comment a little bit on the go to market? Like how, how do your joint customers engage? What does that look like from their perspective? >>You know, when you think about the go to market, a lot of that is we have, you know, teams all over the world that will be aligned and working together in service of the customer. There's marketing and demand generation that will be done, that will be also work on joy opportunities that we will manage as well as a very tight connection on projects to be sure that the support experience for customers is well aligned. I don't wanna talk, go into too much detail, but I would like to guarantee that our intent is not only to create an incredible technological experience, which the, the development teams are done, but also a great experience for the customers that are going through these projects, interacting with both teams that will work as one in service to empower the customer to achieve the outcomes that they need. >>Yeah, and just to comment maybe a little bit more on what all Borrow said, you know, it's not just about the product integration area, it's really the full end to end experience for our customers. So when we embarked on this partnership with Microsoft, we really thought about what is the right product integration and with our engineering teams, but also how do we go and talk to customers with value prop together and all the way down through to support. So we actually even worked on how do we have a single joint support for our customer. So it doesn't really matter how the customer engages, they really see this as an end to end single solution across two companies. >>And that's so critical given just the, the natural challenges that that organizations face and the dynamics of the macro economic environment that we're living in. For them, for customers to be able to have that really seamless single point of interaction, they want that consistent experience on-prem to the cloud. But from an engagement perspective that you're, what sounds like what you're doing, Michael and Avaro is, is goes a long way to really giving customers a much more streamlined approach so that they can be laser focused on solving the business problems that they have, being competitive, getting products to market faster and all that good stuff. Michael, I wonder if you could comment on maybe the cultural alignment that Nutanix and Microsoft have. I know Microsoft's partner program has been around for decades and decades. Michael, what does that cultural alignment look like from, you know, the sales and marketing folks down to engineering, down to support? >>Yeah, I think honestly that was, that was something that kind of fit really well and we saw really a lot alignment from day one. Of course, you know, Nutanix cares a lot about our customer experience, not just within the products, but again, through the entire life cycle to support and so forth. And Microsoft's no different, right? There's a huge emphasis on making sure that we provide the best customer experience and that we're also focusing on solving real world customer problems, right? And really focus on the biggest problems the customers have. So really culturally it felt, it felt really natural. It felt like we were a single team, although it's, you know, two bar drug organizations working together, but I really felt like a single team working day in, day out on, on solving customer problems together. >>Yeah. >>Let me, Go ahead. >>No, I will say, well say Michael, I think that the, the one element that we complement, I think the answer was super complete, is the, the fact that we work together from the outside in, look at it from the customer lenses is extremely powerful and far as I mentioned, because that's what it's all about. And when you put the customer at the center, everything else falls in part on its its own place very, very quickly. And then it's hard work and innovation and, you know, doing what we do best, which is combining over superpowers in service of that customer. So that was the piece that, you know, I i, I cannot emphasize enough how inspiring he's been. And again, the, the response for the previous is a great example of the opportunity that we have in there. >>Yeah. And, and you know, with every hard problem there's challenges along the way, right? And so I'm actually really proud of both of the teams that stepped up and, you know, figure it out. How do we go solve some of these technical problems? How do we go solve, making sure we continue to provide world class support for sports organizations? And, you know, these weren't easy things to solve and, and you know, everyone really stepped up the challenge >>And you've taken a lot of complexity out of the customer environment and I can imagine that the GA of Nutanix cloud clusters on Azure is gonna be a huge benefit for customers and every industry. Last question guys, I wanna get both your perspectives on Michael, we'll start with you and then Lvra will wrap with you. What's next? Obviously a lot of exciting stuff. What's next for the partnership of these, these two superheroes together, Michael? >>Yeah, so I think our goal doesn't change, right? I think our North star is to continue to make it easy for our customers to adopt, migrate and modernize their applications, leveraging Nutanix and Microsoft Azure, right? And I think NC two and Azure is just the start of that. So kind of maybe more immediate, like, you know, we mentioned obviously we have, we announced the GA that's J in Americas kind of the next more immediate step over the next few months. Look for us to continue expanding beyond Americas and making sure that we have support across all the global regions. And then beyond that, you know, again, as of our mentioned is working from kind of the customers backwards. So we're, we're not, no, we're not waiting for the ga, we're already working on the next set of solutions saying what are other problems that customer facing, especially across as they're running their workloads cross on premises and public cloud, and what are the next set of solutions that we can deliver to the market to solve those real challenges for them. >>It sounds really strongly that, that the partnership here, we're talking about Nutanix and Microsoft. It's really Nutanix and Microsoft with the customer at this center. I think you've do both, done a great job of articulating that there's laser focus there. Of our last word to you, what excites you about the momentum that Microsoft and Nutanix have for the customers? >>Well, thank you Lisa. Michael, I will tell you, when you hear the customer feedback on the impact that you're having, that's the most inspiring part because you know, you're generating value, you know, you're making a difference, especially in this complex times when the, the partnership gets tested where the, the right, you know, relationship gets built. We're being there for customers is extremely inspired. Now, as Michael mentioned, this is all about what customer needs and how do we go even ahead of the game so that we're ready not for what is the problem today, but the opportunities that we have tomorrow to keep working on this. We have a huge task ahead to be sure that we bring this value globally in the right way with the right quality. Every word, which is a, is never a small fist as you may imagine. You know, the, the world is a big place, but also the next wave of innovations that will be customer driven to keep and, and raise the bar on how, how much more value can we unlock and how much empowerment can we make for the customer to keep in innovating at their own pace, in their own terms. >>Absolutely that customer empowerment's key. Guys, it's been a pleasure talking to you about the announcement, Nutanix cloud clusters on Azure of our Michael, thank you for your time, your inputs and helping us understand the impact that this powerhouse relationship is making. >>Thank you for having Lisa and thank you Avara for joining me. >>Thank you, Lisa, Michael, it's been fantastic and looking forward and thank you to the audience for being here with us. Yeah, stay >>Tuned. Exactly. Thanks to the audience. >>Exactly. >>And stay tuned. There's more to come. We have coming up next, a deeper conversation on the announcement with Dave Valante and product execs from both and Microsoft. You won't wanna miss it.

welcome back everyone to thecube's live coverage in san francisco for vmware explorer 2022 formerly vmworld i'm john furrier david live dave 12 years we've been covering this event formerly vmware first time in west now it's explore we've been in north we've been in south we've been in vegas multi-cloud is now the exploration vmware community is coming in john siegel svp at dell cube alumni dave mccraw vp at vmware guys thanks for coming back both cube alumni it's great to see you very senior organizations senior roles in the organizations of vmware and dell one year since the split great partnership continuing i mean some of the conversations we've been having over the past few years is that control plane the management layer making everything work together it's essentially been the multi-cloud hybrid cloud story what's the update what's how's the partnership look yeah i you know i just to start off i mean i would say i don't think our partnership's been any has ever been any better um if you look at you mention our vision very much a shared vision in terms of the multi-cloud world and i don't think we've ever had more joint innovation projects at one time i think we have over 40 now dave that are going on across multi-cloud ai cyber security uh modern applications and and uh you know here just at you just vmworld vmware explorer we have over 30 uh vmware sessions that are featuring dell um and this is i think more than we've ever had so look i think um there's a lot of momentum there and we're really looking forward to what's to come so you guys obviously spent a lot of time together when vmware was part of dell and then you've been it's been a year since the spin and then you codified i think it was a five-year agreement you know so you had some time to figure that out and then put it into paper so you just kind of quantified some of the stuff that's going on but now we're entering a yet another phase so that that that that agreement's probably more important than ever now i mean list in terms of getting it documented and an understanding right yeah that agreement really defines a framework for solution development and for go to market so we've been doing it and refining it for the last five years so now you know putting and codifying it into a written signed agreement it basically is instantiating what we've been doing that we know works uh where we can drive uh solution development we can drive deep architectural co-innovation together as well and as john said across multiple you know project and solution areas so we we've been talking to years to you know a lot of these strat guys guys like matt baker about things like you know you see aws do nitro and then of course project monterey and and i know that you guys have had a you know a big sort of input into that and so now to see it come to fruition is is huge because you know from our view it's the future of computing architectures how do you handle you know data rich applications ai applications that's what are your thoughts on here i couldn't agree more uh project monterey is a great example of how we're innovating together we just talked about i mean first of all it's all so we have vxrail which let's let's start there right we have over 19 000 joint customers right now we continue to innovate more and more on the vxrail architecture great example of that as our partnership with project monterey and taking essentially vsphere 8 and running it for the first time on an hci system directly on the dp used itself right on the dpus ability now to offload nsxt from from the cpus to the dpus uh hope you know in the short term first of all great benefits for customers in terms of better performance but as you just mentioned it's game changing in terms of laying the foundation for the future architectures that we plan on together helping out customers there's one other dynamic for you on is um and it's not unique to dell but dell's the biggest you know supply supplier partner etc but you're able to take vmware software and drive it through your business and and that enables you to get more subscription revenue and makes it stickier and that's a really important change from you know 10 years ago yeah and it's it's a combination as you know of dell software and vmware software together absolutely and i think what's with this is a game-changing innovation that you can run on top of our joint system vxrail if you will um and now what our customers can expect is life cycle automation of now you know the dpus as well as tanzu as well as everything else we layer on top of that core foundation that we have over 19 000 customers running today so i mean like that 19 000 number i want to get back up to the vx rail and you mentioned vsphere that's big news here this year vsphere 8 big release a lot of going on what's the hci angle you mentioned that what's in it for the customer what does that mean for the folks here because let's face it the vsphere aids got everyone in that they've all the v-sections are going going crazy right another vsphere release getting training they have the labs here what's it mean for the customers what's the value there with that hci solution with the gpus well first of all vsphere 8 as we know it has a lot of goodies in it but you know what what i think to me what's been most powerful about this is the ability to run vsphere 8 uh and and specifically on the dpus now you can run it it is open up all new possibilities now and so that nsxt that i mentioned you know running that on gpus opens up a whole new uh architecture now for our customers going forward and now really sets us up for modern distributed architecture for the future so like edge okay yeah and vsphere 8 brings in you know cloud connectivity as well so you know customers can run in a cloud disconnected mode they can run in a cloud connected mode so you know that's going to bring in the ability to do specialized things on security cycle management there's a whole series of services that can now be added as well as you know leveraging you know vcenter management capabilities so what's happening at the edge we had i think it was lows on hotel tech world right okay good not the other one um but so so that's got to be exploding now with that with that because it just changes the game for for these stores there's i mean retail uh manufacturing maybe you can give us an update on there's so much happening on the edge side as you know i mean that's where most of the a lot of the innovations happening right now is at the edge and a lot of the companies we talked to 8x right 8x expectation of increase in uh edge workloads over the next and the data challenge too and the data challenge is huge so you heard about the innovations with vsphere 8. in addition to that we just introduced today as well the smallest vx rail for the edge ever this thing is it's like think picture a couple eight and a half by 11 notebooks not much not much you know maybe a little wider than that but not much more um you know these these are stacked on top of each other these are you can rack and stack and mount these things anywhere and it also is the first aci system that has you know a built-in hardware witness so this helps set it up for environments that are you know network bandwidth constrained or have high high latency no longer an issue next gen app is going to want to have a local data server at the edge right and with compute there right high performance right right so now you're getting it across the wire yes you get racket stack a couple of these small things i mean they can they can fit into like a you know clark kent's briefcase right these things are so small um you want to do the analytics on site and return responses back you don't want to be moving massive data payloads off the egg so you got to have the right level of compute to run machine learning algorithms and and do the analytics type work that you want to do to make local decisions yeah i mean we just had david lithimon who was one of the keynote speakers here at the event and we've been talking about super cloud and multi-cloud meta cloud all the different versions of what we see as this next-gen and this brings up a point of like his advice to young people learn how multi-cloud learn about system architecture because if you can figure out how to put it together you're going to have to make more money anyway that this whole edge piece opens up huge challenges and opportunities around how do you configure these next-gen apps what does the ai look like what's the data architecture this is not like get some training curriculum online and you get you know 101 and you're getting a job no this is more complicated but with the hardware you guys make it easier so where's the complexity shift between having a powerful edge device like the vxrail with the vsphere what's the ec button on that like how do you guys what's the vision because this is going to be a major battleground this whole edge piece yeah it's going to be huge well i think when you look at the innovation that dell is bringing to market with technologies like outlander and then designing that into vxrail and then you combine that with our tonzu capabilities to manage development and deployment of applications this is about heterogeneous deployment and management at scale of applications with technologies like tons of mission control then deploying service mesh right for security being able to use sassy to be able to secure you know with cloud security over the wire so it's bringing together multiple technologies to deliver simplicity to the customer the ability to go one to many you know in terms of being able to deploy and manage and update whether that's a security patch or an application update and do that very rapidly at a low cost so the benefit with this solution now just putting this together is i can ship a box small and or stack them and essentially it's done remotely it's that's provision the provisioning issues not a truck roll as they say or professional services enabled you can just drop that out there and this is where the customers need to be yeah that absolutely is that the vision don't get that right exactly you don't you don't need the you don't need the skills yeah you don't need the specialized skills you don't need a lot of space you don't need you know high network bandwidth all these things right all these innovations that we're talking about here um really combined into really enabling a whole new whole new future here for edge is are you doing apex now is that i think thickest part sure part of yours okay so um is apex fitting into the to the edge how does it fit yeah i mean well first of all you know a lot of what we talked with apex is really about a consumption a way to ensure there's a common cloud experience wherever the data is and where the applications are and so absolutely edge fits into this as well and so we have we have common ways to consume our infrastructure today our joint infrastructure whether it's in the data center at the edge um or you know uh in the cloud usain ragu when he was on i said it was great keynote loved it one of the things that i didn't think there was enough of was security and he's like yeah we only had so much time but vmware is a very strong security story we heard a really strong security story at dell tech world i mean half the innovations and the new you know storage products were security and the new os's and it was impressive what what's how are you guys working together on security is that one of those let me give you a few key things you know our teams are working together at the engineer to engineer level you know reference architectures for zero trust as an example being able to look you know hardware root of trust up into the application layer right so we're looking at really defense in depth here you know i mentioned what we're doing with sassy right with cloud security capabilities so you really have to look at this from the edge to the core with the you know from a networking perspective getting the network the insights on things that maybe anomalies that may be happening on the network so using our network insight technology you know uh nsx and then being able to ultimately uh have a secure development pipeline as well i mean you we all know about the supply chain attacks that happen right and so being able to have a you know secure pipeline for development is critical for both of our companies working together i think the tan zoo and you mentioned the developer self-service that experience combined with kind of the power of the dell you know let's face it the boxes are awesome hardware matters and software matters so bringing that expertise together michael daley always used to say on thecube better together in respect to vmware and dell a lot of fruit has been born from that labor right specifically around and now when you add the tan zoo and you get vsphere you got the operational excellence you got the you got the performance and scale with the dell boxes and hardware and software and now you've got the tan zoo what's missing or is it all there now i mean where how would you how would you guys peg the progress bar is it like it's all rocking right now or or i'd say you're never done first of all but i you know i look at some of the innovations that we've brought to market recently where we've are combining and stacking these technologies into a more defense in-depth like solution you know bringing nsx onto vxrail so that you can flip a switch easily and light up the firewall the new plug-in yeah that's a great example simple simple um carbon black workload another example where we're taking carbon black technology that was typically on endpoints you know on pcs bringing that into the data center right and leveraging all the analytics and insights around you know being able to identify anomalies and then remediate those anomalies so we're seeing very good traction with those and the cloud native developers containers they're all native container working with compute and container storage object store in the cloud kubernetes we've embraced it yeah i mean yeah containers running containers and vms on the same infrastructure common way to manage it all i mean that that's been a big part of it as well obviously a lot of the focus that dell's bringing here as well is is the inability to run that stack easily right you heard the announcement on uh tanzu for kubernetes operators right earlier today tko we call it uh you know that running on vxrail now is really targeted at the i.t operator in allowing them to easily stand up a self-service developer devops environment on vxrail going forward and then a piece that might be invisible to them is back to monterey isolation right encryption and data moving you know absolutely storage the security the compute right the management right that's that's a complete and it's about reducing attack services as well right the security perspective as well when you when you're moving nsxt onto a dpu you're doing that as well so there's it takes the little things right at the end of the day security is a mindset up across both companies in terms of how we approach our architectures um and it's the you know a lot of times it's the little things as well that we make sure right so shared vision working at the engineering levels together for many many years know that you guys are validating more of that coming what's next take us through okay we're here 2022 we got super cloud multi-cloud hybrid full throttle right now it's hybrid's a steady state that's cloud operations infrastructure as code has happened it's happening what's next for you guys in the relationship can you share a little bit that you can if you can what we can expect what you see uh with monterrey is the start of a re-architecting of i.t infrastructure not just in the data center but also at the edge right these technologies will move out and be pervasive you know across i think edge to colo to core data center to cloud right and so that's a starting point now we're looking at memory tiering right i think we talked last time about capitola and memory tiering and you know being able to bring that forward uh being able to do more with confidential computing as an example right secure enclaves and confidential computing so you know a lot of this is focused around simplicity and security going forward and ease of management around take the heavy lifting away from the customer abstract that in offer the power and performance that's right and it's going to come down to delivering time to value for our customers you know can we cut that time to value by 25 50 percent so they can be in production faster yeah i think project monterey is something we'll be building on for a long time right i mean this is the start of a major new future architecture of these companies so if you had to pick one we have 40 initiatives that are joined together real literally project monterey is one of my favorites for sure in terms of what it's going to do not just for that common cloud experience but for the edge and and we talked a lot about the edge today and where that's headed you think it's going to explode up new apps i really do think so well it's going to put you in a new it's going to put in curve yeah absolutely right and operationally uh security wise um from a modern apps perspective i mean all it checks all the boxes and it's going to allow us to to help and take our existing customers on that journey as well what's great about this conversation we've been following both you guys for a long time and your companies and and technology upgrades and and the business impact and open source and all doing all this for customers but the wave that's coming we're seeing the expo hall here i mean it's people are really excited they're enthused they're committed highly confident that this this wave is coming they kind of see it people kind of seeing the fog lift they're seeing money making value creation people kind of feeling more comfortable but still a little nervous around you know what's coming next because it's still uncertainty but pretty good ecosystem i'd have to say that's pretty pretty interesting yeah a lot of them are excited about you know what they can do at the edge and how they can differentiate their businesses i mean that's right well congratulations guys thanks for coming on thecube and sharing the update thank you it more innovation it's not stopping here at vmware explorer dell and vm we're continuing to have that kind of relationship joint engineering it's all coming together and you can mix and match this and the stack but it's ultimately going to be cloud operations edge is the action of course hybrid cloud as well it's thecube thanks for watching [Music] you

(upbeat music) (upbeat music) (upbeat music) >> Welcome back to Las Vegas. Lisa Martin here, with Dave Vellante. We are covering day two of our coverage of Snowflake Summit '22. of Snowflake Summit '22. It's been a cannon of content coming your way, the last couple of days. We love talking with customers, with partners. We've got a partner on the program from ThoughtSpot. We're going to be diving into digital transformation with self-service analytics for the modern data stack. Please welcome Kuntal Vahalia, SVP of Channel and Alliances at ThoughtSpot. Welcome Kuntal. >> Thank you, Lisa. Dave, thank you for having us. >> Dave: Good to see you. >> Talk to the audience a little bit about ThoughtSpot. Give 'em an overview, and then de dive into the partnership with Snowflake. >> Yeah, absolutely. So ThoughtSpot is the, what we call live analytics, for the modern data stack, right? We want to be the experience layer for all the data that's getting modernized and moving into the cloud, right? And then specifically to Snowflake, we, of course, we have seen over the last two days here Snowflake has made tremendous innovations where they've accelerated a customer's journey into the cloud, especially the data cloud. Our job is to go really unlock that data, right? Generate that value, make it consumable at the at the experience level layer, right? So what we want to do here with Snowflake is here with Snowflake is make analytics self service for the end users, for the end users, on top of the Snowflake data cloud, right? And we want to empower everyone to create, consume, and operationalize data driven insights. We think if the end users can gender their own insights through live analytics, we could do have a completely different operating model for a business, right? And I think we can do that in accelerated fashion on, sitting on top of Snowflake data cloud. >> End users? Lines of business? >> It's line of business users, so we directly go to end users. That's one of our differentiation, not just IT, not just IT, but as end users as well, so we could be all things to all enterprise, to all enterprise, across our line of businesses. >> So what kind of impact are you seeing with your customers? You know, ones that are leaning into ThoughtSpot and Snowflake and sort of rethinking their data approach? >> Yeah. I mean the impact could be immense, right? As I said, this is not just about analytics. If we are successful in empowering end users, it completely changes the velocity of the business. We are now driving innovation at every node, at every layer in the organization. Not just IT, not just smaller segments in the organization, we are doing this anywhere, in any pocket, right? So I think the impact could be massive, if we do this right. And I think we are starting to see that, we have a lot of customers here actually, joint customers, Capital One, Canadian Tires, Walmart, they're all joint customers, where we have seen starting to see some of those impacts, where we have data getting modernized, the stack being ready, and then we're coming in at the top as the experience layer, which is driving that new digital operating model. >> Describe the maturity curve when you go, you mentioned some of the the the leaders, I mean, take a Walmart. I mean, they kind of invented the whole, you know, beer and diapers thing, right? So obviously a company with tremendous resources and and and advanced technology. Compare. Compare. So some of those leaders with sort of the other end of the spectrum, when you come into a company and you see, okay, here's, okay, here's, what does that spectrum look like? And and what's the upside for the, I don't want to call 'em laggards, but I'll call 'em laggards. >> Yeah, yeah, absolutely. I mean, this, this, I think we are still early on. I mean, as this is not just a exercise in getting the data ready, this is also an exercise in in change management, because now, as I said, we are going beyond IT. We are going to line of business users as well, so a lot of change management required, and we have seen companies that are actually putting this in front of the frontline workers, empowering frontline workers to consume analytics and to drive self-service via search and AI, and AI, they're on a different curve. They are actually being competitive in the market. That's an advantage for them, right? >> Right. >> So we are seeing a lot of companies, like Walmart, already ahead in that journey with us still early days, right? We got to go, land in one line of business, go from there to other line of business till we go enterprise wide. >> Can you, it sounds like you might be a facilitator of connecting heads of business with the IT and the tech folks at ThoughtSpot. >> Absolutely. I mean, that is the Holy Grail. How do we get IT And line of business work frictionless, where everyone has their roles defined, right? And still get to the outcome where innovation is happening now with IT on the data cloud and then go beyond IT into the broader business? So yeah, I think that's definitely one of the our goals and outcomes of what we do. >> So what are the roles there? So the business obviously wants to do more business. Okay. They put analytics in their hands and it helps them get there. What role does IT play? Making sure that those services are available? Are they a service provider? Is it more of a governance and compliance thing? >> Yeah, I mean, step number one is still to get the data ready and I think IT still owns the key to that kingdom, especially around governance, security, so I think IT still has to get the data stack ready, right? Step number two is for IT to really build a framework for how to consume analytics for how to consume analytics for the end users. Step number three then is, is the rule is, Hey, we don't need IT to now deliver dashboards or KPIs to the business every day that that's how traditional dashboards work. In our world, once IT does step number one and step number two the business can take over and they can now go operate the business on their own using live analytics. >> Creating self-serve >> Absolutely. Self-service analytics using service in AI. >> What have you seen, in terms of from the IT folks perspective, we talked about change management a minute ago, It's very challenging to do, but these days every company has to be a data company. >> Kuntal: Yeah. >> They don't have a choice. >> Yeah. >> What are you seeing from a change management perspective within the IT function across your customers and then be willing to let go in some cases? and then be willing to let go in some cases? >> Actually, >> Actually, what we have seen is, you know, think about the the technical debt that IT is owning over the last few years, it's just increasing, right? IT is looking for ways to A. cut cost, to A. cut cost, B. deliver more B. deliver more with probably the same amount of resources they have, so in some ways they welcome this new operating model, as long as they can keep the governance, they can keep the security, they can keep the framework around how business is run, as long as IT has a say in that, they're more than welcome to invite business, to really drive innovation at the edges through self-service analytics, so what we found is IT is a is a welcome partner, in this journey, especially when they have to get the data ready and modernize the data set for us. >> You guys announcing a partnership with Matillion this week, what? Tell us what that's all about. The one earlier. >> We did. So we did announce a partnership, so I think, as I said, step number one is getting the data ready, and I think we have heard from Frank and the rest of this team this week, even Snowflake is taking a best of breed approach on the data stack, right? So we want the computer So we want the computer and the storage to be ready, but for that, the data pipeline has to be ready, which is where Matillion comes in with the low code, no code approach, so we think between Matillion, Snowflake, and ThoughtSpot, we could be the accelerated best of breed approach for customers to realize value and and be live on the, on the modern data stack. >> Is that your, is that your stack? >> As we said, we, we meet the customers where they are, but we think this is accelerated path. >> What are the advantages of, you know, what are you optimizing on in that stack? in that stack? >> First with Matillion, we have, what we concept, we have this concept of Spot Apps, so this is ThoughtSpot's way to really capture the IP and the templates for customers to move fast, right? That's where we bake in a lot of the industry IP, a lot of functional IP around end sources, and and endpoints, so we have some of those spot apps built with Matillion, built with Matillion, so now customers able to ingest data into the so now customers able to ingest data into the into the cloud faster using Matillion, right? So that's, that's something we worked with, same thing with Snowflake, you know, we are now starting to go verticalize with Snowflake, So we are starting to build a lot of IP around financial services, healthcare and whatnot, which is where I think we are, again, accelerating customer's path on the modern data stack, all the way to the experience layer. >> A as a partner of Snowflake's, what does all the narrative around the data cloud, we've been talking about that for a while, a lot of conversation around the data cloud the last couple of days, where do partners fit into that overall narrative? >> Yeah, I think multiple places, right? First thing, First thing, First thing, every layer of the data cloud still needs innovation, still needs partners, and every partner adds a different set of value. Just like we add value at the, at the top layer, which is the experience layer, But I think, you know, we have channel partners we have a lot of SIs and GSIs here, and GSIs here, especially once we take a best of breed approach, to delivering customer outcomes, SIs are the neutral ground. They're the ones who are going to have the Matillion expertise, and the Snowflake expertise, and thoughts for expertise, all baked into one DNA practice, data analytics practice, so I think at every layer, partners have a role to play and every layer partners have role, have value to add. have value to add. >> What's the engagement process like for customers when you you're talking about the the the the three way partnership Matillion, Matillion, ThoughtSpot, and stuff like, how do customers get involved, what's your go to market look like? >> Right. I mean, obviously, I mean, we, we, we are humble, we know where we are. I mean, we, a little bit smaller than, than Snowflake Snowflake has a head start, so they've been about five years ahead of us, so we are largely targeting customers that are that are Snowflake ready, where there is some semblance of data cloud, where data seems to be organized and ready to go, right? so once we think the customer is at that point in the journey, we have very strong partnership across both, across entire organization, at a product level, at a field engagement level, and our field teams really understand the value the joint value between the two organizations, so we, we start to see Snowflake feel, and ThoughtSpot feel, starting to work together on key accounts, once we think the data is ready, and wherever we need to accelerate the data, that's where we bring in Matillion as well, to ingest more data into, into the data cloud, but that's largely been the engagement model between the three companies. >> How do you see the announcements that they made around applications affecting what you guys are doing and your ecosystem? >> Yeah, I mean, I think that's a validation. I think to us, I think to us, we always said step number one is to modernize the data, move into the cloud. That's step number one, but we still have to unlock the data. Like the data still needs to be consumed, And we always said, Hey, we are that app that could drive the consumption of data, but now with some of the announcement we have seen, I think the validation is there saying, "Hey, yes." There, even Snowflake is ready to move in a more accelerated fashion into the application world where they want to drive consumption, not just with the analytics layer, but with lot of other applications that's out there. >> Yeah. >> What are some of the things that you've heard this week, in the last couple of days, that really validate that really validate the the partnership with Snowflake, from your perspective? >> Yeah. I mean, I think the first thing is, is this concept of modern data stack, which is best of breed. I think we have been thinking about that for a long time, for the last year or so. We have seen this come through at this event here, right? We see Matillion, Snowflake, and then the SIs around it, all coming together, so I think to us, that's the biggest validation that the modern data stack is the right approach, especially best of breed, to drive the right customer outcomes, so to me, that's big. Second is this concept of really accelerating applications on top of the data cloud. I think that's, again a validation of what we've been trying to do over the last few years, which is, the data has modernized, let's now drive consumption and adoption of that data, so I think those are the two big take areas. >> So, so the modern data stack, to get to the modern data stack, you got to do some work. >> Yep. >> But so the, the play is to hold out the carrot, which you just kind of just did, 'cause once you get there, then you can really start to hit the steep part of the S-curve, right? >> That's right. >> What, what are the, what would you say are are the sort of prerequisites that customers need to think about to really jump on that modern data stack curve? >> Um, I think they they got to first have a vision around the outcomes, what outcomes we are driving. I think it's one thing to say, "Hey, we just going to move the data over from from legacy into the cloud." I mean, that's just, that's just migration, that doesn't drive the outcomes. To us, what makes sense is, let's start with the right outcomes around supply chain, around retail, around e-commerce, let's name it, right? I think, it starts there. From there on, let's figure out, what do we need? What's what, what technologies do we need in the stack to enable those outcomes, right? It could be ThoughtSpot at the top, it could be something else at the top, and same thing, it's Matillion, and Snowflake, right? But it really starts with what outcomes we going to drive in what industry and what KPIs are important for our customers. >> What's next for ThoughtSpot and Snowflake? I was just looking at the notes here. Over 250 plus joint customers, you mentioned some Disney+, Capital One, I've seen them around here. What's next for these two powerhouses? >> Well, I think we're just getting started, to be honest. I mean those 250 customers, first, we got to go drive success for them. I mean, we are a 10 year old company with a two year runway because we transferred our business transformed our business to cloud, less than two years ago, so this 250 joint logos are actually all happened in the last two years and that's driven us to be in the, probably in the top five adoption drivers for Snowflake, all in the last two years, So goal number one is to really, let's go drive customer success for these joint logos. Second, let's go expand them, right? Consumption is the key criteria, both for Snowflake, as well as ThoughtSpot. We are very well aligned, our pricing models aligned there, our incentives aligned there, We really want customers to go adopt and consume the stack, and then of course, really, we want to go verticalize ourselves, start speaking the language of the customers, and really just get bigger. I mean, we still got to build a machine around this. >> Lisa: Yep. >> Lisa, this is, this is all still early days for us. >> Early innings. A lot of, but a ton of potential. The, the field is ripe. >> The field is right open. I think in, and we will, I think we are, bottom of the third or bottom of the second, I think you still have a long game to play, right? >> Well good. Most people always use bottom the first. I'm glad to hear it's really bottom of the second or third. That's pretty good. >> Yeah, well, 250 logos are there. >> Lisa: Yeah. >> And it's further along 'cause of the, the I don't want to say it like this, but I'm going to say it anyway. The failure of the big data movement, it pushed us along quite, quite a ways, in terms of thinking, putting data at the core, the technology kind of failed us, you know and the, and the, you know and the, and the, the centralization of the architectures, the centralization of the architectures, it failed us, But then the cloud came along. >> That's right. >> We learned a lot and now, you know, technology's advanced I think people's thinking is advanced and they realize increasingly the importance of data >> And ecosystem is coming. I mean, I think you look around here, this is a secret sauce for the future. >> Dave: Yep. This is what's going to really get us moving faster over the next few innings because now the rest of the ecosystem is coming along. >> Yep. The momentum is here. That flywheel is moving. >> That's right. >> Definitely. Kuntal, thank you very much for joining David and me on the program talking about >> Kuntal: Lisa, Dave, thank you so much for your time. >> what ThoughtSpot's all about, what you're up to, a lot of momentum. We wish you the best of luck as you progress into those later innings. >> Thank you >> For Dave Vellante. I'm Lisa Martin. You're watching theCube. We are live in Las Vegas at Snowflake Summit '22. Dave and I are going to be right back with our next guest, so stick around. (mellow techno music) (mellow techno music) (mellow techno music) (mellow techno music)

(upbeat music) >> Good morning. Welcome back to theCUBE's continuing coverage of Snowflake Summit 22, live from Las Vegas. Lisa Martin, here with Dave Villante. We are at Caesar's Forum, having lots of great conversations. As I mentioned, this is just the start of day two, a tremendous amount of content yesterday. I'm coming at you today. Two guests join us from Slalom, now, we've got Chris Samuels, Principal Machine Learning, and Bethany Mudd, Senior Director, Experience Design. Welcome to theCube, guys. >> Hi, thanks for having us. >> Thank you. >> So, Slalom and Snowflake, over 200 joint customers, over 1,800 plus engagements, lots of synergies there, partnership. We're here today to talk about intelligent products. Talk to us about what- how do you define intelligent products, and then kind of break that down? >> Yeah, I can, I can start with the simple version, right? So, when we think about intelligent products, what they're doing, is they're doing more than they were explicitly programmed to do. So, instead of having a developer write all of these rules and have, "If this, then that," right, we're using data, and real time insights to make products that are more performing and improving over time. >> Chris: Yeah, it's really bringing together an ecosystem of a series of things to have integrated capabilities working together that themselves offer constant improvement, better understanding, better flexibility, and better usability, for everyone involved. >> Lisa: And there are four pillars of intelligent products that let's walk through those: technology, intelligence, experiences, and operations. >> Sure. So for technology, like most modern data architectures, it has sort of a data component and it has a modern cloud platform, but here, the key is is sort of things being disconnected, things being self contained, and decoupled, such that there's better integration time, better iteration time, more cross use, and more extensibility and scalability with the cloud native portion of that. >> And the intelligence piece? >> The intelligence piece is the data that's been processed by machine learning algorithms, or by predictive analytics that provides sort of the most valuable, or more- most insightful inferences, or conclusions. So, by bringing together again, the tech and the intelligence, that's, you know, sort of the, two of the pillars that begin to move forward that enable sort of the other two pillars, which are- >> Experiences and operations. >> Yeah. >> Perfect. >> And if we think about those, all of the technology, all of the intelligence in the world, doesn't mean anything if it doesn't actually work for people. Without use, there is no value. So, as we're designing these products, we want to make sure that they're supporting people. As we're automating, there are still people accountable for those tasks. There are still impacts to people in the real world. So, we want to make sure that we're doing that intentionally. So, we're building the greater good. >> Yeah. And from the operations perspective, it's you can think of traditional DevOps becoming MLOps, where there's an overall platform and a framework in place to manage not only the software components of it, but the overall workflow, and the data flow, and the model life cycle such that we have tools and people from different backgrounds and different teams developing and maintaining this than you would previously see with something like product engineering. >> Dave: Can you guys walk us through an example of how you work with a customer? I'm envisioning, you know, meeting with a lot of yellow stickies, and prioritization, and I don't know if that's how it works, but take us through like the start and the sequence. >> You have my heart, I am a workshop lover. Anytime you have the scratch off, like, lottery stickers on something, you know it's a good one. But, as we think about our approach, we typically start with either a discovery or mobilized phase. We're really, we're starting by gathering context, and really understanding the business, the client, the users, and that full path the value. Who are all the teams that are going to have to come together and start working together to deliver this intelligent product? And once we've got that context, we can start solutioning and ideating on that. But, really it comes down to making sure that we've earned the right, and we've got the smarts to move into the space intelligently. >> Yeah, and, truly, it's the intelligent product itself is sort of tied to the use case. The business knows what the most- what is potentially the most valuable here. And so, so by communicating and working and co-creating with the business, we can define then, okay, here are the use cases and here are where machine learning and the overall intelligent product can maybe add more disruptive value than others. By saying, let's pretend that, you know, maybe your ML model or your predictive analytics is like a dial that we could turn up to 11. Which one of those dials turning turned up to 11 could add the most value or disruption to your business? And therefore, you know, how can we prioritize and then work toward that pie-in-the-sky goal. >> Okay. So the client comes and says, "This is the outcome we want." Okay, and then you help them. You gather the right people, sort of extract all the little, you know, pieces of knowledge, and then help them prioritize so they can focus. And then what? >> Yeah. So, from there we're going to take the approach that seeing is solving. We want to make sure that we get the right voices in the room, and we've got the right alignment. So, we're going to map out everything. We're going to diagram what that experience is going to look like, how technology's going to play into it, all of the roles and actors involved. We're going to draw a map of the ecosystem that everyone can understand, whether you're in marketing, or the IT sort of area, once again, so we can get crisp on that outcome and how we're going to deliver it. And, from there, we start building out that roadmap and backlog, and we deliver iteratively. So, by not thinking of things as getting to the final product after a three year push, we really want to shrink those build, measure, and learn loops. So, we're getting all of that feedback and we're listening and evolving and growing the same way that our products are. >> Yeah. Something like an intelligent product is is pretty heady. So it's a pretty heavy concept to talk about. And so, the question becomes, "What is the outcome that ultimately needs to be achieved?" And then, who, from where in the business across the different potentially business product lines or business departments needs to be brought together? What data needs to be brought together? Such that the people can understand how they themselves can shape. The stakeholders can, how the product itself can be shaped. And therefore, what is the ultimate outcome, collectively, for everybody involved? 'Cause while your data might be fueling, you know, finances or someone else's intelligence and that kind of thing, bringing it all together allows for a more seamless product that might benefit more of the overall structure of the organization. >> Can you talk a little bit about how Slalom and Snowflake are enabling, like a customer example? A customer to take that data, flex that muscle, and create intelligent products that delight and surprise their customers? >> Chris: Yeah, so here's a great story. We worked to co-create with Kawasaki Heavy Industries. So, we created an intelligent product with them to enable safer rail travel, more preventative, more efficient, preventative maintenance, and a more efficient and real time track status feedback to the rail operators. So, in this case, we brought, yeah, the intelligent product itself was, "Okay, how do you create a better rail monitoring service?" And while that itself was the primary driver of the data, multiple other parts of the organization are using sort of the intelligent product as part of their now daily routine, whether it's from the preventative maintenance perspective, or it's from route usage, route prediction. Or, indeed, helping KHI move forward into making trains a more software centered set of products in the future. >> So, taking that example, I would imagine when you running- like I'm going to call that a project. I hope that's okay. So, when I'm running a project, that I would imagine that sometimes you run into, "Oh, wow. Okay." To really be successful at this, the company- project versus whole house. The company doesn't have the right data architecture, the right skills or the right, you know, data team. Now, is it as simple as, oh yeah, just put it all into Snowflake? I doubt it. So how do you, do you encounter that often? How do you deal with that? >> Bethany: It's a journey. So, I think it's really about making sure we're meeting clients where they are. And I think that's something that we actually do pretty well. So, as we think about delivery co-creation, and co-delivering is a huge part of our model. So, we want to make sure that we have the client teams, with us. So, as we start thinking about intelligent products, it can be incorporating a small feature, with subscription based services. It doesn't have to be creating your own model and sort of going deep. It really does come down to like what value do you want to get out of this? Right? >> Yeah. It is important that it is a journey, right? So, it doesn't have to be okay, there's a big bang applied to you and your company's tech industry or tech ecosystem. You can just start by saying, "Okay, how will I bring my data together at a data lake? How do I see across my different pillars of excellence in my own business?" And then, "How do I manage, potentially, this in an overall MLOps platform such that it can be sustainable and gather more insights and improve itself with time, and therefore be more impactful to the ultimate users of the tool?" 'Cause again, as Bethany said that without use, these things are just tools on the shelf somewhere that have little value. >> So, it's a journey, as you both said, completely agree with that. It's a journey that's getting faster and faster. Because, I mean, we've seen so much acceleration in the last couple of the years, the consumer demands have massively changed. >> Bethany: Absolutely. >> In every industry, how do Slalom and Snowflake come together to help businesses define the journey, but also accelerate it, so that they can stay ahead or get ahead of the competition? >> Yeah. So, one thing I think is interesting about the technology field right now is I feel like we're at the point where it's not the technology or the tools that's limiting us or, you know, constraining what we can build, it's our imaginations. Right? And, when I think about intelligent products and all of the things that are capable, that you can achieve with AI and ML, that's not widely known. There's so much tech jargon. And, we put all of those statistical words on it, and you know the things you don't know. And, instead, really, what we're doing is we're providing different ways to learn and grow. So, I think if we can demystify and humanize some of that language, I really would love to see all of these companies better understand the crayons and the tools in their toolbox. >> Speaking from a creative perspective, I love it. >> No, And I'll do the tech nerd bit. So, there is- you're right. There is a portion where you need to bring data together, and tech together, and that kind of thing. So, something like Snowflake is a great enabler for how to actually bring the data of multiple parts of an organization together into, you know, a data warehouse, or a data lake, and then be able to manage that sort of in an MLOps platform, particularly with some of the press that Snowflake has put out this week. Things becoming more Python-native, allowing for more ML experimentation, and some more native insights on the platform, rather than going off Snowflake platform to do some of that kind of thing. Makes Snowflake an incredibly valuable portion of the data management and of the tech and of the engineering of the overall product. >> So, I agree, Bethany, lack of imagination sometimes is the barrier we get so down into the weeds, but there's also lack of skills, as mentioned the organizational, you know, structural issues, politics, you know, whatever it is, you know, specific agendas, how do you guys help with that? Can, will you bring in, you know, resources to help and fill gaps? >> Yeah, so we will bring in a cross-disciplinary team of experts. So, you will see an experienced designer, as well as your ML architects, as well as other technical architects, and what we call solution owners, because we want to make sure that we've got a lot of perspectives, so we can see that problem from a lot of different angles. The other thing that we're bringing in is a repeatable process, a repeatable engineering methodology, which, when you zoom out, and you look at it, it doesn't seem like that big of a deal. But, what we're doing, is we're training against it. We're building tools, we're building templates, we're re-imagining what our deliverables look like for intelligent products, just so, we're not only speeding up the development and getting to those outcomes faster, but we're also continuing to grow and we can gift those things to our clients, and help support them as well. >> And not only that, what we do at Slalom is we want to think about transition from the beginning. And so, by having all the stakeholders in the room from the earliest point, both the business stakeholders, the technical stakeholders, if they have data scientists, if they have engineers, who's going to be taking this and maintaining this intelligent product long after we're gone, because again, we will transition, and someone else will be taking over the maintenance of this team. One, they will understand, you know, early from beginning the path that it is on, and be more capable of maintaining this, and two, understand sort of the ethical concerns behind, okay, here's how parts of your system affect this other parts of the system. And, you know, sometimes ML gets some bad press because it's misapplied, or there are concerns, or models or data are used outside of context. And there's some, you know, there are potentially some ill effects to be had. By bringing those people together much earlier, it allows for the business to truly understand and the stakeholders to ask the questions that they- that need to be continually asked to evaluate, is this the right thing to do? How do I, how does my part affect the whole? And, how do I have an overall impact that is in a positive way and is something, you know, truly being done most effectively. >> So, that's that knowledge transfer. I hesitate to even say that because it makes it sound so black and white, because you're co-creating here. But, essentially, you're, you know, to use the the cliche, you're teaching them how to fish. Not, you know, going to ongoing, you know, do the fishing for them, so. >> Lisa: That thought diversity is so critical, as is the internal alignment. Last question for you guys, before we wrap here, where can customers go to get started? Do they engage Slalom, Snowflake? Can they do both? >> Chris: You definitely can. We can come through. I mean, we're fortunate that snowflake has blessed us with the title of partner of the year again for the fifth time. >> Lisa: Congratulations. >> Thank you, thank you. We are incredibly humbled in that. So, we would do a lot of work with Snowflake. You could certainly come to Slalom, any one of our local markets, or build or emerge. We'll definitely work together. We'll figure out what the right team is. We'll have lots and lots of conversations, because it is most important for you as a set of business stakeholders to define what is right for you and what you need. >> Yeah. Good stuff, you guys, thank you so much for joining Dave and me, talking about intelligent products, what they are, how you co-design them, and the impact that data can make with customers if they really bring the right minds together and get creative. We appreciate your insights and your thoughts. >> Thank you. >> Thanks for having us guys. Yeah. >> All right. For Dave Villante, I am Lisa Martin. You're watching theCUBE's coverage, day two, Snowflake Summit 22, from Las Vegas. We'll be right back with our next guest. (upbeat music)

>>Hey everyone. Welcome back to Las Vegas. This is the Cube's live coverage of day. One of snowflake summit 22 fourth annual. We're very happy to be here. A lot of people here, Lisa Martin with Dave Valante, David's always great to be at these events with you, but me. This one is shot out of the cannon from day one, data, data, data, data. That's what you heard of here. First, we have two guests joining us next, please. Welcome Matthew Scalian. Who's an alumni of the cube CEO and founder of Matillion and Jer staying chief data architect and global head of data engineering from Western union. Welcome gentlemen. Thank >>You. Great to be here. >>We're gonna unpack the Western union story in a second. I love that, but Matthew, I wanted to start with you, give the audience who might not be familiar with Matillion an overview, your vision, your differentiators, your joint value statement with snowflake, >>Of course. Well, first of all, thank you for having me on the cube. Again, Matillion S mission is to make the world's data useful, and we do that by providing a technology platform that allows our customers to load transform, synchronize, and orchestrate data on the snowflake data cloud. And on, on the cloud in general, we've been doing that for a number of years. We're co headquartered in the UK and the us, hence my dat accents. And we work with all sorts of companies, commercial scale, large end enterprises, particularly including of course, I'm delighted to say our friends at Western union. So that's why we're here today. >>And we're gonna talk about that in a second, but I wanna understand what's new with the data integration platform from Matillion perspective, lots of stuff coming out, give us an overview. >>Yeah, of course, it's been a really busy year and it's great to be here at snowflake summit to be able to share some of what we've been working on. You know, the Matillion platform is all about making our customers as productive as possible in terms of time to value insight on that analytics, data science, AI projects, like get you to value faster. And so the more technology we can put in the platform and the easier we can make it to use, the better we can achieve that goal. So this year we've, we've shipped a product that we call MDL 2.0, that's enterprise focused, exquisitely, easy to use batch data pipelines. So customers can load data even more simply into the snowflake data cloud, very excitingly we've also launched Matillion CDC. And so this is an industry first cloud native writer, head log based change data capture. >>I haven't come up with a shorter way of saying that, but, and surprise customers need this technology and it's been around for years, but mostly pre-cloud technology. That's been repurposed for the cloud. And so Matillion has rebuilt that concept for the cloud. And we launched that earlier this year. And of course we've continued to build out the core Matillion ETL platform that today over a thousand joint snowflake Matillion customers use, including Western union, of course we've been adding features there such as universal connectivity. And so a challenge that all data integration vendors have is having the right connectors for their source systems. Universal connectivity allows you to connect to any source system without writing code point and click. We shape that as well. So it's been a busy year, >>Was really simple. Sorry. I love that. He said that and it also sounded great with your accent. I didn't wanna >>Thank you. Excellent. Javier, talk about your role at Western union in, in what you've seen in terms of the evolution of the, the data stack. >>So in the last few years, well, a little bit of Western union, a 70 or 170 year old company, pretty much everybody knows what Western union is, right? Driving an interesting synergy from what Matthew says, when data moves money moves, that's what we do when he moves the da, he moves the data. We move the money. That's the synergy between, you know, us and the organization that support us from data move perspective. So what I've seen in the last few years is obviously a shift towards the cloud, but, you know, within the cloud itself, obviously there's a lot of players as well. And we as customers have always been wishing to have a short, smaller footprint of data so that the movement becomes a little lesser. You know, interestingly enough, in this conference, I've heard some very interesting stuff, which kind of helping me to bring that footprint down to a manageable number, to be more governed, to be more, you know, effective in terms of delivering more end results for my customers as well. >>So Matillion has been a great partner for us from our cloud adoption perspective. During the COVID times, we were a re we are a, you know, multi-channel organization. We have retail stores as well, our digital presence, but people just couldn't go to the retail stores. So we had to find ways to accelerate our adoption, make sure our systems are scaling and making sure that we are delivering the same experience to our customers. And that's where, you know, tools like Matillion came in and really, really partnered up with us to kind of bring it up to the level. >>So talk specifically about the stack evolution. Cause I have this sort of theory that everybody talks about injecting data and, and machine intelligence and AI and machine learning into apps. But the application development stack is like totally separate from the, the data analytics and the data pipeline stack. And the database is somewhere over here as well. How is that evolving? Are those worlds coming together? >>Some part of those words are coming together, but where I still see the difference is your heavy lifting will still happen on the data stack. You cannot have that heavy lifting on the app because if once the apps becomes heavy, you'll have trouble communicating with, with, with the organizations. You know, you need to be as lean as possible in the front end and make sure things are curated. Things are available on demand as soon as possible. And that's why you see all these API driven applications are doing really, really well because they're delivering those results back to the, the leaner applications much faster. So I'm a big proponent of, yes, it can be hybrid, but the majority of the heavy lifting still needs to happen down at the data layer, which is where I think snowflake plays a really good role >>In APIs are the connective tissue >>APIs connections. Yes. >>Also I think, you know, in terms of the, the data stack, there's another parallel that you can draw from applications, right? So technology is when they're new, we tend to do things in a granular way. We write a lot of code. We do a lot of sticking of things together with plasters and sticky tape. And it's the purview of high end engineers and people enthusiastic about that to get started. Then the business starts to see the value in this stuff, and we need to move a lot faster. And technology solutions come in and this is what the, the data cloud is all about, right? The technology getting out of the way and allowing people to focus on higher order problems of innovating around analytics, data applications, AI, machine learning, you know, that's also where Matillion sit as well as other companies in this modern enterprise data stack is technology vendors are coming in allowing organizations to move faster and have high levels of productivity. So I think that's a good parallel to application development. >>And's just follow up on that. When you think about data prep and you know, all the focus on data quality, you've got a data team, you know, in the data pipeline, a very specialized, maybe even hyper specialized data engineers, quality engineers, data, quality engineers, data analysts, data scientist, but they, and they serve a lot of different business lines. They don't necessarily have the business, they don't have the business context typically. So it's kind of this back and forth. Do you see that changing in your organization or, or the are the lines of business taking more responsibility for the data and, and addressing that problem? It's, >>It's like you die by thousand paper cuts or you just die. Right? That's the kind >>Of, right, >>Because if I say it's, it's good to be federated, it comes with its own flaws. But if I say, if it's good to be decentralized, then I'm the, the guy to choke, right? And in my role, I'm the guy to choke. So I've selectively tried to be a pseudo federated organization, where do I do have folks reporting into our organization, but they sit close to the line of business because the business understands data better. We are working with them hand in glove. We have dedicated teams that support them. And our problem is we are also regional. We are 200 countries. So the regional needs are very different than our us needs. Majority of the organizations that you probably end up talking to have like very us focused, 50 per more than 50% of our revenue is international. So we do, we are dealing with people who are international, their needs for data, their needs for quality and their needs for the, the delivery of those analytics and the data is completely different. And so we have to be a little bit more closer to the business than traditionally. Some, some organizations feel that they need >>To, is there need for the underlying infrastructure and the operational details that as diverse, or is that something that you bring standardization to the, >>So the best part about this, the cloud that happened to us is exactly that, because at one point of time, I had infrastructure in one country. I had another infrastructure sitting in another country, regional teams, making different different decisions of bringing in different tools. Now I can standardize. I will say, Matillion is our standard for doing ETL work. If this is the use case, but then it gets deployed across the geographies because the cloud helps us or the cloud platform helps us to manage it. Sitting down here. I have three centers around the world, you know, Costa Rica, India, and the us. I can manage 24 7 sitting here. No >>Problem. So the underlying our infrastructure is, is global, but the data needs are dealt with locally. Yep. >>One of the pav question, I was just thinking JVE is super well positioned funds for you, which is around that business domain knowledge versus technical expertise. Cause again, early in technology journeys tend, things tend to be very technical and therefore only high end engineers can do it, but high end engineers are scar. Right? Right. And, and also, I mean, we survey our hundreds of large enterprise customers and they tell us they spend two thirds of their time doing stuff they don't really want to do like reinventing the wheel, basic data movement and the low order staff. And so if you can make those people more productive and allow them to focus on higher value problems, but also bring pseudo technical people into it. Overall, the business can go a lot faster. And the way you do that is by making it easier. That's why Matillion is a low code NOCO platform, but Jer and Western union are doing this right. I >>Mean, I can't compete with AWS and Google to hire people. So I need to find people who are smart to figure the products that we have to make them work. I don't want them to spend time on infrastructure, Adam, I don't want them to spend time on trying to manage platforms. I want them to deliver the data, deliver the results to the business so that they can build and serve their customers better. So it's a little bit of a different approach, different mindset. I used to be in consulting for 17 years. I thought I knew it all, but it changed overnight when I own all of these systems. And I'm like, I need to be a little bit more smarter than this. I need to be more proactive and figure out what my business needs rather than what just from a technology needs. It's more what the business needs and how I can deliver that needs to them. So simple analogy, you know, I can build the best architecture in the world. It's gonna cost me an arm and leg, but I can't drive it because the pipeline is not there. So I can have a Ferrari, but I can't drive it. It's still capped at 80, 80 miles an hour. So rather than spend, rather than building one Ferrari, let me have 10 Toyotas or 10 Fs, which will go further along and do better for my cus my, for my customers. >>So how do you see this whole, we hearing about the data cloud. We hear about the marketplace, data products now, application development inside the data cloud. How do you see that affecting not so much the productivity of the data teams. I don't wanna necessarily say, but the product, the value that, that customers like you can get out >>Data. So data is moving closer to the business. That's the value I see, because you are injecting the business and you're injecting the application much more closer to the data because it, in the past, it was days and days of, you know, churn the data to actually clear results. Now the data has moved much closer. So I have a much faster turnaround time. The business can adapt and actually react much, much faster. It took us like 16 to 30 days to deliver, you know, data for marketing. Now I can turn it down in four hours. If I see something happening, I'll give you an example. The war in Ukraine happened. Let is shut down operations in Russia. Ukraine is cash swamp. There's no cash in Ukraine. We have cash. We roll out campaign, $0 money, transferred to Ukraine within four hours of the world going on. That's the impact that we have >>Massive impact. That's huge, especially with such a macro challenge going on, on the, in, in the world. Thank you so much for sharing the Matillion snowflake partnership story, how it's helping Western union really transform into a data company. We love hearing stories of organizations that are 170 years old that have always really been technology focused, but to see it come to life so quickly is pretty powerful. Guys. Thank you so much for your time. Thanks >>Guys. Thank you, having it. Thank >>You >>For Dave Velante and our guests. I'm Lisa Martin. You're watching the cubes live coverage of snowflake summit 22 live from Las Vegas. Stick around. We'll be back after a short break.

(gentle music) >> Hey everybody. Welcome back to theCUBE. We are live in Las Vegas at Caesar's Forum, Lisa Martin with Dave Vellante, covering Snowflake Summit 22, this is day one action packed, it kind of feels like we were shot out of a cannon, which is great. We love that at theCUBE. Our next guest from Slalom joins us, Hilary Feier the GM of Data and Analytics. Hilary, it's great to have you on the program. >> It's great to be here, so excited to be here. >> Isn't it great to be back in person? >> It is, it's amazing, it's like filling my cup just to be back with people again. >> I felt the same. And you could tell that on stage during the keynote which was not only standing room only, but there was an overflow room. >> I was in the overflow room. >> Lisa: Were you? >> I have to admit it. We had a breakfast meeting and we got there right on time and we ended up in overflow, but it was great. We, there was just great energy and it was exciting to see all the progress that's coming down the pipe. >> Tremendous progress, tremendous innovation, a lot of evolution since we last saw Snowflake in person, which was 2019. Talk to us from Slalom's partnership perspective how is data evolving, the use of data evolving, what are you hearing from the front lines of the customer? >> From the front lines of the customer, we're seeing a lot of customers go to the cloud, and Snowflake's at the forefront of that evolution. We're seeing them take advantage of this separation of compute and storage to be able to scale to different levels and concurrency at different levels and collaborate. And we always say, what we're actually seeing them unlock is this modern culture of data, where people and organizations can fully take advantage at all different levels of this accessible but governed data. And I think Snowflake makes that a reality. >> So we go to a lot of events of course, and you hear both sides of the story when you talk to a company like Snowflake, or one of the hyperscalers, like yeah, cloud makes ton of sense. When you talk to some of the more established companies, call 'em legacy companies, everybody's like oh no, people are repatriating, they're moving back on-prem, or they can't move data, or they won't move data in the cloud. The truth is probably someplace in the middle. But when you look at the numbers cloud is growing, substantially faster. What are you seeing with customers when, with regard to modernization, the role of cloud and the role of Snowflake? >> I think they're flocking to the cloud, I think COVID had people flock there right. You realize the agility it provides for you, it is unparalleled. And to some extent, I'd had conversations with customers years ago that they were like, hey I know security, I do it better than anybody. And I go, honestly AWS, Google, like the the hyper cloud providers, they know security, and Snowflake doing that data layer across all of 'em. They do security at a whole different level than any data center or any IT group that I've seen out there. >> Have you, we've seen the secure, the threat landscape changed dramatically in the last couple of years where it's now no longer, are we going to get hit, it's when. >> Right. >> How have you seen the security conversation elevate when you're talking with customers in terms of up the executive stack? Is that now something that it, since we? >> It's a top priority, it's a board priority. I can tell you last year I actually spent time internally helping implement Snowflake for us at Slalom, and it's our president's top priority was security. And that was one of the reasons honestly that we went that way, we were a little out of date, we needed to modernize, we needed to migrate, and we wanted to practice what we preach with our customers. So we did a little bit of both, and we did more than technology. We did a lot of process change, a lot of people up leveling, 'cause we really feel like technology's only a piece of the puzzle. You have to bring the people along for the journey in order to make that a reality. >> So what was the business driver to make that change? >> I think it was honestly to empower more people, and then we also had the threat of systems that were falling over and just not meeting the needs of the business. We were pretty data driven and the systems weren't keeping up. >> And they were on-prem systems, they were hosted in the cloud? >> They were kind of on-prem, kind of hosted in the cloud. They were SQL1, EC2 instances, but we just, we didn't, we weren't able to scale, literally was falling over. Like we have a day a week where all of the reporting comes out because we're time driven, and it would fall over, literally. >> Dave: So you had a halfway house, sort of? >> Yeah. >> Okay, and then you moved much of it, most of it, all of it, into Snowflake? >> All of it. >> All of it into Snowflake? >> All of it. >> Dave: And. >> And then some. >> Dave: Okay. >> Because we had certain systems that we were afraid, like Workday, right. All the PII, all the privacy data. We were afraid to bring that into our SQL server before, but we were able to bring that into Snowflake now and it unlocks in a governed, we have security, in very compliant ways, we have a lot of interesting things that we've done in this past year. To both empower more people, but do it in a governed and secured way. >> And how long did that migration take? >> I'd say it took about a year, and it was. >> Dave: Pretty fast. >> And it was a tough year, honestly. >> Yeah they're ugly, migrations. >> We do it with internal consultants and some of them in the beginning of COVID, we were looked at as an opportunity. Let's get them, let's do it internally. And then we got super busy, the market just took off and then we were begging for resources. We were like, okay where can we find somebody to help us with this? >> Cobblers kids. >> Yeah, we were the cobblers kids. But we got it done. >> And as a partner drinking the Snowflake champagne. Talk to me about the ability to influence the technology, the direction, the roadmap. We've heard so much innovation announced this morning alone. Do you have that capability as a Snowflake partner? >> Yeah, for sure. So I feel like we're always on the forefront. We're doing these strategy projects with our clients, and so we want to keep our ears to what's going on in the innovation. We look at a lot of the other partners that are here. There's a whole ecosystem that's grown up around Snowflake and it's amazing to see the advancements that are happening and the cloud allows you to leapfrog just so quickly the advancements. And, you know we talked about this before we started that you know, I've been in this data space for 30 years and it's changed a lot, the progression, the real time data, what you can do, the separation of compute and storage. It's amazing what you can do. And yet some of the same problems are pervasive. I have too much data, not enough information. And so we're seeing the advent of more governance and catalogs, and you know that whole semantic layer is coming into play. >> Yeah, the problem is data is plentiful, insights aren't, and then monetizing data is really, really hard. I, what's your take on Snowflake's ability to change that dynamic? >> I think they're making it a lot easier. I mean, some of the advancements they're coming out with, and more and more companies are looking to monetize and we're doing that in partnership with some companies like Meredith Corporation. They're a, I don't know if you know who they are? But they're like allrecipes.com. If you go there, they collect a lot of that data. We have a partnership together where we're looking, and they're on Snowflake and we're doing a joint data monetization offering out to customers. >> Snowflake and Slalom have over 200 joint customers. Slalom has won Partner of the Year now, five times. Congratulations by that. >> Hilary: Thank you. >> What is the secret, what's the secret sauce? What does the future of the partnership look like given the flywheel that is Snowflake, that is incredibly fast. >> Yeah, I think the secret sauce to me is we started early, and we liked the product, but we had a lot of core values in common. If you look you know, the customer obsession, do the right thing always, just get it done, right. Like, you know really very, very similar. And so that translates out in the field and that's why we team so well together. But at the end of the day our secret sauce is we know the product. We invested really early in getting skilled up on Snowflake, and we did, we were the first partner to do Train the Trainer, and so we've literally certified hundreds of folks on the product, and we stay on the leading and bleeding edge. And we're now working with their professional services arm to really take a joint offering to the market around, helping organizations, not just migrate but really modernize because that's when you truly take advantage of the cloud. And some people were quick to migrate and they're not seeing those advantages and we want to make sure we're unlocking all the advantages of actually modernizing. >> What do you think last question is we are almost out of time here. What do you think in the 30 years you said you've been in this business, you talked about the modern culture of data. What does it take for a legacy organization to pivot, to be able to pivot, to be able to adopt a modern culture of data, if they're so used to old school processes? >> I think it's having someone with a bold vision at the top. That's willing to say, hey, we want to go to the new frontier, and then sticking to the guns and taking a holistic approach. Don't just put in technology, don't just change a process, But think about it holistically, we have a whole framework where we look at five different dimensions, and we help our customers go through and maybe you don't want to get to, the most mature stage across all five, but figure out where you want to get to and then start actually slogging it out and going step by step to get it done. >> And it's all about people, process and technology. Those three together are absolutely critical. >> It sure is. >> Excellent, Hilary, thank you for joining Dave and me on theCUBE talking about the Slalom partnership. What you're doing with Snowflake and on top of Snowflake we appreciate your time and your insights. >> Thank you so much, really appreciate it. >> Dave: Thanks Hilary. >> For our guest and Dave Vellante, I am Lisa Martin. You're watching theCUBE's live coverage from Snowflake Summit 22, live from Las Vegas. (gentle music)

>>Okay. We're back here in the cube, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest terror do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to >>See Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer know cloud migration momentum and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central, our company's strategy. They always have been, we recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner, community and strategy now addresses several kinds of partners, spanning solution providers to global size and technology partners, such as snowflake and together, we help our customers realize that business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform guidance, deployment, support, and other professional services. Okay, >>Great. Let's get a little bit more into the relationship between Altrix and in snowflake the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing our costs. Altrix proudly achieves highest elite tier and their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the strength solution. We developed two great assets. One is the Altrix starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows and videos, helping customers to get going more easily with an Alteryx and snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Ultrix and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems, much faster. Cool. >>Tara, can you give us your perspective on the >>Yeah, definitely. Dave. So as Bart mentioned, we've got this standing very successful partnership going back, whereas with hundreds of happy joint customers. And when I look at the beginning, Ultrix has helped pioneer the concept of self-service analytics actually with use cases that we've worked on with, for, for data prep for BI users like Tableau and as Altrix has evolved to now becoming from data prep to now becoming a full end to end data science platform, it's really opened up a lot more opportunities for our partnership. Ultrix has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud with Alteryx orchestrating the end to end machine learning workflows, Altryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources. But so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful that I can come up with today. The big challenges or trends for us, and Altrix really helps us across all of them. There are three particular ones I'm going to talk about the first one being self service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, you know, the, the technology users, but the business users, right? I think every, every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with all traits is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So with self-service analytics, with Ultrix designer, they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. And then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. And with Altryx creating this platform. So they can cater to both the everyday business user, the quote, unquote, citizen data scientists, and making it code friendly for data scientists, to be able to get at their notebooks and all the different tools that they want to use. They fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution catering to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx, if we look at mobilizing your data, getting access to third-party data sets to enrich with your own data sets to enrich with, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view within their, their data applications. And so with Altryx is we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with, with the snowflake data marketplace so that we can enrich these workflows, these great rate workflows that Ultrix rating provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities date. So those are three. I see easily that we're going to be able to solve a lot of customer challenges with. >>Excellent. Thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having a managed infrastructure to even be able to, to get applications off the ground. And so we created something to be Claudia. We created to be a SAS managed service. So now that that Altrix is moving into the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster. They don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had to pray desktop products. And today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products, we're committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers cloud and analytic ambitions. >>How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, games agencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Tara, how do you see it? You'd go to market strategy. >>Yeah. Dave we've. So we initially started selling, we initially sold snowflake as technology, right? Looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we were starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Ultrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so mark talked about these, these starter kits where it's prescriptive, you've got a demo and a way that customers can get off the ground and running, right? >>Because we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working on healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map to lines of business with Altryx >>Great. Thanks Derek, Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. We're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the alternative partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra we're providing our partners with earlier access to benefits, I could talk about our program for 30 minutes. I know we don't have time, but the key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Great Tarik. We'll give you the last word. What should we be looking for from, >>Yeah. Thanks. Thanks, Dave. As BARR mentioned, Ultrix has been the forefront of innovating with us. They've been integrating into making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before, but extensibility is really what we're excited about. The ability for Altrix to plug into this extensibility framework that we call snow park and to be able to extend out ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala now Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right? If they're PI day sets and in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right. I think it's exciting to see what we're going to be able to do together with these upcoming innovations. >>Great stuff, Bob, Derek, thanks so much for coming on the program. Got to leave it right there in a moment. I'll be back with some closing thoughts in summary, don't go away.

>>Alteryx is a company with a long history that goes all the way back to the late 1990s. Now the one consistent theme over 20 plus years has been that Ultrix has always been a data company early in the big data and Hadoop cycle. It saw the need to combine and prep different data types so that organizations could analyze data and take action Altrix and similar companies played a critical role in helping companies become data-driven. The problem was the decade of big data, brought a lot of complexities and required immense skills just to get the technology to work as advertised this in turn limited, the pace of adoption and the number of companies that could really lean in and take advantage of the cloud began to change all that and set the foundation for today's theme to Zuora of digital transformation. We hear that phrase a ton digital transformation. >>People used to think it was a buzzword, but of course we learned from the pandemic that if you're not a digital business, you're out of business and a key tenant of digital transformation is democratizing data, meaning enabling, not just hypo hyper specialized experts, but anyone business users to put data to work. Now back to Ultrix, the company has embarked on a major transformation of its own. Over the past couple of years, brought in new management, they've changed the way in which it engaged with customers with the new subscription model and it's topgraded its talent pool. 2021 was even more significant because of two acquisitions that Altrix made hyper Ana and trifecta. Why are these acquisitions important? Well, traditionally Altryx sold to business analysts that were part of the data pipeline. These were fairly technical people who had certain skills and were trained in things like writing Python code with hyper Ana Altryx has added a new persona, the business user, anyone in the business who wanted to gain insights from data and, or let's say use AI without having to be a deep technical expert. >>And then Trifacta a company started in the early days of big data by cube alum, Joe Hellerstein and his colleagues at Berkeley. They knocked down the data engineering persona, and this gives Altryx a complimentary extension into it where things like governance and security are paramount. So as we enter 2022, the post isolation economy is here and we do so with a digital foundation built on the confluence of cloud native technologies, data democratization and machine intelligence or AI, if you prefer. And Altryx is entering that new era with an expanded portfolio, new go-to market vectors, a recurring revenue business model, and a brand new outlook on how to solve customer problems and scale a company. My name is Dave Vellante with the cube and I'll be your host today. And the next hour, we're going to explore the opportunities in this new data market. And we have three segments where we dig into these trends and themes. First we'll talk to Jay Henderson, vice president of product management at Ultrix about cloud acceleration and simplifying complex data operations. Then we'll bring in Suresh Vetol who's the chief product officer at Altrix and Adam Wilson, the CEO of Trifacta, which of course is now part of Altrix. And finally, we'll hear about how Altryx is partnering with snowflake and the ecosystem and how they're integrating with data platforms like snowflake and what this means for customers. And we may have a few surprises sprinkled in as well into the conversation let's get started. >>We're kicking off the program with our first segment. Jay Henderson is the vice president of product management Altryx and we're going to talk about the trends and data, where we came from, how we got here, where we're going. We get some launch news. Well, Jay, welcome to the cube. >>Great to be here, really excited to share some of the things we're working on. >>Yeah. Thank you. So look, you have a deep product background, product management, product marketing, you've done strategy work. You've been around software and data, your entire career, and we're seeing the collision of software data cloud machine intelligence. Let's start with the customer and maybe we can work back from there. So if you're an analytics or data executive in an organization, w J what's your north star, where are you trying to take your company from a data and analytics point of view? >>Yeah, I mean, you know, look, I think all organizations are really struggling to get insights out of their data. I think one of the things that we see is you've got digital exhaust, creating large volumes of data storage is really cheap, so it doesn't cost them much to keep it. And that results in a situation where the organization's, you know, drowning in data, but somehow still starving for insights. And so I think, uh, you know, when I talk to customers, they're really excited to figure out how they can put analytics in the hands of every single person in their organization, and really start to democratize the analytics, um, and, you know, let the, the business users and the whole organization get value out of all that data they have. >>And we're going to dig into that throughout this program data, I like to say is plentiful insights, not always so much. Tell us about your launch today, Jay, and thinking about the trends that you just highlighted, the direction that your customers want to go and the problems that you're solving, what role does the cloud play in? What is what you're launching? How does that fit in? >>Yeah, we're, we're really excited today. We're launching the Altryx analytics cloud. That's really a portfolio of cloud-based solutions that have all been built from the ground up to be cloud native, um, and to take advantage of things like based access. So that it's really easy to give anyone access, including folks on a Mac. Um, it, you know, it also lets you take advantage of elastic compute so that you can do, you know, in database processing and cloud native, um, solutions that are gonna scale to solve the most complex problems. So we've got a portfolio of solutions, things like designer cloud, which is our flagship designer product in a browser and on the cloud, but we've got ultra to machine learning, which helps up-skill regular old analysts with advanced machine learning capabilities. We've got auto insights, which brings a business users into the fold and automatically unearths insights using AI and machine learning. And we've got our latest edition, which is Trifacta that helps data engineers do data pipelining and really, um, you know, create a lot of the underlying data sets that are used in some of this, uh, downstream analytics. >>Let's dig into some of those roles if we could a little bit, I mean, you've traditionally Altryx has served the business analysts and that's what designer cloud is fit for, I believe. And you've explained, you know, kind of the scope, sorry, you've expanded that scope into the, to the business user with hyper Anna. And we're in a moment we're going to talk to Adam Wilson and Suresh, uh, about Trifacta and that recent acquisition takes you, as you said, into the data engineering space in it. But in thinking about the business analyst role, what's unique about designer cloud cloud, and how does it help these individuals? >>Yeah, I mean, you know, really, I go back to some of the feedback we've had from our customers, which is, um, you know, they oftentimes have dozens or hundreds of seats of our designer desktop product, you know, really, as they look to take the next step, they're trying to figure out how do I give access to that? Those types of analytics to thousands of people within the organization and designer cloud is, is really great for that. You've got the browser-based interface. So if folks are on a Mac, they can really easily just pop, open the browser and get access to all of those, uh, prep and blend capabilities to a lot of the analysis we're doing. Um, it's a great way to scale up access to the analytics and then start to put it in the hands of really anyone in the organization, not just those highly skilled power users. >>Okay, great. So now then you add in the hyper Anna acquisition. So now you're targeting the business user Trifacta comes into the mix that deeper it angle that we talked about, how does this all fit together? How should we be thinking about the new Altryx portfolio? >>Yeah, I mean, I think it's pretty exciting. Um, you know, when you think about democratizing analytics and providing access to all these different groups of people, um, you've not been able to do it through one platform before. Um, you know, it's not going to be one interface that meets the, of all these different groups within the organization. You really do need purpose built specialized capabilities for each group. And finally, today with the announcement of the alternates analytics cloud, we brought together all of those different capabilities, all of those different interfaces into a single in the end application. So really finally delivering on the promise of providing analytics to all, >>How much of this you've been able to share with your customers and maybe your partners. I mean, I know OD is fairly new, but if you've been able to get any feedback from them, what are they saying about it? >>Uh, I mean, it's, it's pretty amazing. Um, we ran a early access, limited availability program that led us put a lot of this technology in the hands of over 600 customers, um, over the last few months. So we have gotten a lot of feedback. I tell you, um, it's been overwhelmingly positive. I think organizations are really excited to unlock the insights that have been hidden in all this data. They've got, they're excited to be able to use analytics in every decision that they're making so that the decisions they have or more informed and produce better business outcomes. Um, and, and this idea that they're going to move from, you know, dozens to hundreds or thousands of people who have access to these kinds of capabilities, I think has been a really exciting thing that is going to accelerate the transformation that these customers are on. >>Yeah, those are good. Good, good numbers for, for preview mode. Let's, let's talk a little bit about vision. So it's democratizing data is the ultimate goal, which frankly has been elusive for most organizations over time. How's your cloud going to address the challenges of putting data to work across the entire enterprise? >>Yeah, I mean, I tend to think about the future and some of the investments we're making in our products and our roadmap across four big themes, you know, in the, and these are really kind of enduring themes that you're going to see us making investments in over the next few years, the first is having cloud centricity. You know, the data gravity has been moving to the cloud. We need to be able to provide access, to be able to ingest and manipulate that data, to be able to write back to it, to provide cloud solution. So the first one is really around cloud centricity. The second is around big data fluency. Once you have all of the data, you need to be able to manipulate it in a performant manner. So having the elastic cloud infrastructure and in database processing is so important, the third is around making AI a strategic advantage. >>So, uh, you know, getting everyone involved and accessing AI and machine learning to unlock those insights, getting it out of the hands of the small group of data scientists, putting it in the hands of analysts and business users. Um, and then the fourth thing is really providing access across the entire organization. You know, it and data engineers, uh, as well as business owners and analysts. So, um, cloud centricity, big data fluency, um, AI is a strategic advantage and, uh, personas across the organization are really the four big themes you're going to see us, uh, working on over the next few months and, uh, coming coming year. >>That's good. Thank you for that. So, so on a related question, how do you see the data organizations evolving? I mean, traditionally you've had, you know, monolithic organizations, uh, very specialized or I might even say hyper specialized roles and, and your, your mission of course is the customer. You, you, you, you and your customers, they want to democratize the data. And so it seems logical that domain leaders are going to take more responsibility for data, life cycles, data ownerships, low code becomes more important. And perhaps this kind of challenges, the historically highly centralized and really specialized roles that I just talked about. How do you see that evolving and, and, and what role will Altryx play? >>Yeah. Um, you know, I think we'll see sort of a more federated systems start to emerge. Those centralized groups are going to continue to exist. Um, but they're going to start to empower, you know, in a much more de-centralized way, the people who are closer to the business problems and have better business understanding. I think that's going to let the centralized highly skilled teams work on, uh, problems that are of higher value to the organization. The kinds of problems where one or 2% lift in the model results in millions of dollars a day for the business. And then by pushing some of the analytics out to, uh, closer to the edge and closer to the business, you'll be able to apply those analytics in every single decision. So I think you're going to see, you know, both the decentralized and centralized models start to work in harmony and a little bit more about almost a federated sort of a way. And I think, you know, the exciting thing for us at Altryx is, you know, we want to facilitate that. We want to give analytic capabilities and solutions to both groups and types of people. We want to help them collaborate better, um, and drive business outcomes with the analytics they're using. >>Yeah. I mean, I think my take on another one, if you could comment is to me, the technology should be an operational detail and it has been the, the, the dog that wags the tail, or maybe the other way around, you mentioned digital exhaust before. I mean, essentially it's digital exhaust coming out of operationals systems that then somehow, eventually end up in the hand of the domain users. And I wonder if increasingly we're going to see those domain users, users, those, those line of business experts get more access. That's your goal. And then even go beyond analytics, start to build data products that could be monetized, and that maybe it's going to take a decade to play out, but that is sort of a new era of data. Do you see it that way? >>Absolutely. We're actually making big investments in our products and capabilities to be able to create analytic applications and to enable somebody who's an analyst or business user to create an application on top of the data and analytics layers that they have, um, really to help democratize the analytics, to help prepackage some of the analytics that can drive more insights. So I think that's definitely a trend we're going to see more. >>Yeah. And to your point, if you can federate the governance and automate that, then that can happen. I mean, that's a key part of it, obviously. So, all right, Jay, we have to leave it there up next. We take a deep dive into the Altryx recent acquisition of Trifacta with Adam Wilson who led Trifacta for more than seven years. It's the recipe. Tyler is the chief product officer at Altryx to explain the rationale behind the acquisition and how it's going to impact customers. Keep it right there. You're watching the cube. You're a leader in enterprise tech coverage. >>It's go time, get ready to accelerate your data analytics journey with a unified cloud native platform. That's accessible for everyone on the go from home to office and everywhere in between effortless analytics to help you go from ideas to outcomes and no time. It's your time to shine. It's Altryx analytics cloud time. >>Okay. We're here with. Who's the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate their businesses with that in mind, you know, we know designer and are the products that Altrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyper Rana now kind of renamed, um, Altrix auto. We even speak with the business owner and the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so fact made so much sense for us. >>Yeah. Thank you for that. I mean, you, look, you could have built it yourself would have taken, you know, who knows how long, you know, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birth Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical? And, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those. So, so a broader set of, of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I could use it with the right level of quality and I'm happy to be, but don't tell me to be more data-driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company and I think is, as we, um, saw over the course of the last 5, 6, 7 years that, um, you know, uh, real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push-down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making is, is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making, because we've looked, we've contextualized most of our operational systems, but the big data pipeline is hasn't gotten there. But, and maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform for analytics, automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely Alcon's has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics, for AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. Um, and so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's applied and so multiple personas. Um, and we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now at least three personas the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that? How is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market is not crack the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that was painted and got us really energized about the acquisition and about the potential of the combination. >>And you're really, you're obviously writing the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, Snowflake's doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just what Adam said resonates with me deeply. Um, analytics is one of those, um, massive disciplines inside an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was all drinks and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altrix it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? Yeah, >>I think, I think you should think about them. And, uh, um, as, as very complimentary right designer cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, the really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with, um, Trifacta, um, I think we have to get deeper inside to think about what does the data engineer really need? What's the business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the trifecta on the amazing Trifacta cloud platform. >>You know, >>I think we're just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but one of the reasons I always liked Altrix is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the organization said, wow, this big data stuff has taken off, but we need security. We need governance. And it's interesting because you've got, you know, ETL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like? Uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Um, thanks for asking about our sales kickoff. So we met for the first time and you've got a two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was a, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we added a Trifacta to, um, the, the potty such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for other the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working out him and I will, when he's so hot on, on the deal and the core hypotheses and so on. And then you step back and you're going to share the vision with the field organization, and it blows you away, the energy that it creates among our sellers out of partners. >>And I'm sure Madam will and his team were mocked, um, every single day, uh, with questions and opportunities to bring them in. But Adam, maybe you should share. Yeah, no, it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended, the story that we told was just, you have this opportunity to really cater to what the end users care about, which is a lot about interactivity and self-service, and at the same time. >>And that's, and that's a lot of the goodness that, um, that Altryx is, has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that jets. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube you're leader in enterprise tech coverage. >>This is your data housed neatly insecurely in the snowflake data cloud. And all of it has potential the potential to solve complex business problems, deliver personalized financial offerings, protect supply chains from disruption, cut costs, forecast, grow and innovate. All you need to do is put your data in the hands of the right people and give it an opportunity. Luckily for you. That's the easy part because snowflake works with Alteryx and Alteryx turns data into breakthroughs with just a click. Your organization can automate analytics with drag and drop building blocks, easily access snowflake data with both sequel and no SQL options, share insights, powered by Alteryx data science and push processing to snowflake for lightning, fast performance, you get answers you can put to work in your teams, get repeatable processes they can share in that's exciting because not only is your data no longer sitting around in silos, it's also mobilized for the next opportunity. Turn your data into a breakthrough Alteryx and snowflake >>Okay. We're back here in the queue, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest Terek do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to see >>Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security, and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer, you know, cloud migration momentum, and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central company's strategy. They always have been. We recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner community and strategy now addresses several kinds of partners, spanning solution providers to global SIS and technology partners, such as snowflake and together, we help our customers realize the business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform, guidance, deployment, support, and other professional services. >>Great. Let's get a little bit more into the relationship between Altrix and S in snowflake, the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing their costs. Um, Altrix proudly achieved. Snowflake's highest elite tier in their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the destroyed solution. We developed two great assets. One is the officer starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows, and videos, helping customers to get going more easily with an altered since snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Altryx and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems much faster. >>Cool. Kara, can you give us your perspective on the partnership? >>Yeah, definitely. Dave, so as Barb mentioned, we've got this standing very successful partnership going back years with hundreds of happy joint customers. And when I look at the beginning, Altrix has helped pioneer the concept of self-service analytics, especially with use cases that we worked on with for, for data prep for BI users like Tableau and as Altryx has evolved to now becoming from data prep to now becoming a full end to end data science platform. It's really opened up a lot more opportunities for our partnership. Altryx has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud, uh, with Alteryx orchestrating the end to end machine learning workflows Alteryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources, but so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful, um, that I can come up with today, the big challenges or trends for us, and Altrix really helps us across all of them. Um, there are three particular ones I'm going to talk about the first one being self-service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, um, you know, the, the technology users, but the business users, right? I think every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with Altrix is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So, um, with self-service analytics, with Ultrix designer they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst, um, report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now, with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. Um, and then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. Um, and with Altryx creating this platform so they can cater to both the everyday business user, the quote unquote, citizen data scientists, and making a code friendly for data scientists to be able to get at their notebooks and all the different tools that they want to use. Um, they fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution caring to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx um, if we look at mobilizing your data, getting access to third-party datasets, to enrich with your own data sets, to enrich with, um, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view, um, within their, their data applications. And so with Altryx alterations, we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with the snowflake data marketplace so that we can enrich these workflows, these great, great workflows that Altrix writing provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities, Dave. So those are three I see, uh, easily that we're going to be able to solve a lot of customer challenges with. >>So thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having imagine infrastructure to even be able to do it, to get applications off the ground. And so we created something to be cloud-native. We created to be a SAS managed service. So now that that Altrix is moving to the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster and they don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, um, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had two pre desktop products, and today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products were committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers, cloud and analytic >>Are. How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, gain efficiencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through discovery questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Dark. How do you see it? You'll go to market strategy. >>Yeah. Dave we've. Um, so we initially started selling, we initially sold snowflake as technology, right? Uh, looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we're starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Altrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so, um, Barb talked about these, these starter kits where it's prescriptive, you've got a demo and, um, a way that customers can get off the ground and running, right? >>Cause we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working in healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map two lines of business with Alteryx. >>Great. Thanks Derek. Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. Uh, we're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the ultra partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra score, providing our partners with earlier access to benefits, um, I could talk about our program for 30 minutes. I know we don't have time. The key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Tarik will give you the last word. What should we be looking for from, >>Yeah, thanks. Thanks, Dave. As BARR mentioned, Altrix has been the forefront of innovating with us. They've been integrating into, uh, making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before that extensibility is really what we're excited about. Um, the ability for Ultrix to plug into this extensibility framework that we call snow park and to be able to extend out, um, ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala, not Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right there probably day sets in, in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right? I think it's exciting to see what we're going to be able to do together with these upcoming innovations. Great >>Barb Tara, thanks so much for coming on the program, got to leave it right there in a moment, I'll be back with some closing thoughts in a summary, don't go away. >>1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops make that 2.3. The sector times out the wazoo, whites are much of this velocity's pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into insights, they turn to Altryx Qualtrics analytics, automation, >>Okay, let's summarize and wrap up the session. We can pretty much agree the data is plentiful, but organizations continue to struggle to get maximum value out of their data investments. The ROI has been elusive. There are many reasons for that complexity data, trust silos, lack of talent and the like, but the opportunity to transform data operations and drive tangible value is immense collaboration across various roles. And disciplines is part of the answer as is democratizing data. This means putting data in the hands of those domain experts that are closest to the customer and really understand where the opportunity exists and how to best address them. We heard from Jay Henderson that we have all this data exhaust and cheap storage. It allows us to keep it for a long time. It's true, but as he pointed out that doesn't solve the fundamental problem. Data is spewing out from our operational systems, but much of it lacks business context for the data teams chartered with analyzing that data. >>So we heard about the trend toward low code development and federating data access. The reason this is important is because the business lines have the context and the more responsibility they take for data, the more quickly and effectively organizations are going to be able to put data to work. We also talked about the harmonization between centralized teams and enabling decentralized data flows. I mean, after all data by its very nature is distributed. And importantly, as we heard from Adam Wilson and Suresh Vittol to support this model, you have to have strong governance and service the needs of it and engineering teams. And that's where the trifecta acquisition fits into the equation. Finally, we heard about a key partnership between Altrix and snowflake and how the migration to cloud data warehouses is evolving into a global data cloud. This enables data sharing across teams and ecosystems and vertical markets at massive scale all while maintaining the governance required to protect the organizations and individuals alike. >>This is a new and emerging business model that is very exciting and points the way to the next generation of data innovation in the coming decade. We're decentralized domain teams get more facile access to data. Self-service take more responsibility for quality value and data innovation. While at the same time, the governance security and privacy edicts of an organization are centralized in programmatically enforced throughout an enterprise and an external ecosystem. This is Dave Volante. All these videos are available on demand@theqm.net altrix.com. Thanks for watching accelerating automated analytics in the cloud made possible by Altryx. And thanks for watching the queue, your leader in enterprise tech coverage. We'll see you next time.

hello and welcome to this special cube conversation i'm dave nicholson and this is part of our continuing coverage of google cloud next 2021 i have two very special guests with me and we are going to talk about the topic of security uh i have sunil potti who is vice president and general manager of google cloud security uh who in a previous life had senior leadership roles at nutanix and citrix along with lior div who is the ceo and co-founder of cyber reason lior was formerly a commander in the much famed unit 8200 uh part of the israeli defense forces uh where he was actually a medal of honor recipient uh very uh honored to have him here this morning sunil and lior welcome to the cube sunil welcome back to the cube yeah great to be here david and and to be in the presence of a medal of honor recipient by the way a good friend of mine leor so be here well good to have both of you here so uh i'm the kind of person who likes my dessert before my uh before my entree so why don't we just get right to it you're the two of you are here to announce something very very significant uh in the field of security uh sunil do you want to start us out what are we here to talk about yeah i mean i think maybe uh you know just to set this context um as as many of you know about a decade ago a nation's sponsored attack you know actually got into google plus a whole bunch of tech companies you know the project aurora was quite uh you know infamous for a certain period of time and actually google realized almost a decade ago that look you know security can't just be a side thing it has to be the primary thing including one of the co-founders becoming for lack of a better word the chief security officer for a while but one of the key takeaways from that whole incident was that look you have to be able to detect everything and trust nothing and and the underpinning for at least one of them led to this whole zero trust architectures that everybody now knows about but the other part which is not as popular at least in industry vernacular but in many ways equally important and some ways more important is the fact that you need to be able to detect everything so that you can actually respond and that led to the formation of you know a project internal to google to actually say that look let's democratize uh storage and make sure that nobody has to pay for capturing security events and that led to the formation of this uh new industry concept called a security data lake in chronicle was born and then as we started evolving that over into the enterprise segment partnering with you know cyber reason on one hand created a one plus one equals three synergy between say the presence around what do you detect from the end point but also generally just so happens that as lior will tell you the cyber reason technology happens to start with endpoint but it's actually the core tech is around detecting events but doing it in a smart way to actually respond to them in much more of a contextual manner but beyond just that you know synergy between uh you know a world-class planet scale you know security data like forming the foundation and integrating you know in a much more cohesive way with uh cyber reasons detection response offering the spirit was actually that this is the first step of a long journey to really hit the reset button in terms of going from reactive mode of security to a proactive mode of security especially in a nation-state-sponsored attack vector so maybe leo you can speak a few minutes on that as well absolutely so um as you said i'm coming from a background of uh nation state hacking so for us at cyberism it's uh not is foreign uh what the chinese are doing uh on a daily basis and the growing uh ransomware cartel that's happening right now in russia um when we looked at it we said then uh cyberism is very famous by our endpoint detection and response capability but when we establish cyber reason we establish the cyberism on a core or almost fundamental idea of finding malicious operation we call it the male idea so basically instead of looking for alerts or instead of looking for just pieces of data we want to find the hackers we want to find the attack we want to be able to tell basically the full story of what's going on uh in order to do that we build the inside cyberism basically from day one the ability to analyze any data in real time in order to stitch it into the story of the male the malicious operation but what we realize very quickly that while our solution can process more than 27 trillion events a week we cannot feed it fast enough just from end point and we are kind of blind when it comes to the rest of the attack surface so we were looking uh to be honest quite a while for the best technology that can feed this engine and to as sunil said the one plus one equal three or four or five to be able to fight against those hackers so in this journey uh we we found basically chronicle and the combination of the scale that chronicle bringing the ability to feed the engine and together basically to be able to find those hackers in real time and real time is very very important and then to response to those type of attack so basically what is uh exciting here we created a solution that is five times faster than any solution that exists right now in the market and most importantly it enables us to reverse the atmospheric advantage and basically to find them and to push them out so we're moving from hey just to tell you a story to actually prevent hackers to being in your environment so leor can you i want to double click on that just just a little bit um can you give give us a kind of a concrete example of this difference between simply receiving alerts and uh and actually um you know taking taking uh uh correlating creating correlations and uh and actually creating actionable proactive intelligence can you give us an example of that working in in the real world yeah absolutely we can start from a simple example of ransomware by the time that i will tell you that there is a ransomware your environment and i will send an alert uh it will be five computers that are encrypted and by the time that you gonna look at the alert it's gonna be five thousand uh basically machines that are encrypted and by the time that you will do something it's going to be already too little too late and this is just a simple example so preventing that thing from happening this is critical and very timely manner in order to prevent the damage of ransomware but if you go aside from ransomware and you look for example of the attack like solarwind basically the purpose of this attack was not to create damage it was espionage the russian wanted to collect data on our government and this is kind of uh the main purpose that they did this attack so the ability to be able to say hey right now there is a penetration this is the step that they are doing and there is five ways to push them out of the environment and actually doing it this is something that today it's done manually and with the power of chronicle and cyberism we can do it automatically and that's the massive difference sunil are there specific industries that should be really interested in this or is this a is this a broad set of folks that should be impacted no you know in some ways uh you know the the the saying these days to learn's point on ransomware is that you know if if a customer or an enterprise has a reasonable top-line revenue you're a target you know you're a target to some extent so in that sense especially given that this has moved from pure espionage or you know whether it be you know government oriented or industrial espionage to a financial fraud then at that point in time it applies to pretty much a wide gamut of industries not just financial services or you know critical infrastructure companies like oil and gas pipeline or whatever it could be like any company that has any sort of ip that they feel drives their top line business is now a target for such attacks so when you talk about the idea of partnership and creating something out of a collaboration what's the meat behind this what what what do you what are you guys doing beyond saying you know hey sunil lior these guys really like each other and they respect what the other is doing what's going on behind the scenes what are you actually implementing here moving forward so every partnership is starting with love so it's good [Laughter] but then it need to translate to to really kind of pure value to our customers and pure value coming from a deep integration when it's come to the product so basically uh what will happen is every piece of data that we can collect at cyber is in uh from endpoint any piece of data that the chronicle can collect from any log that exists in the world so basically this is kind of covering the whole attack surface so first we have access to every piece of information across the full attack surface then the main question is okay once you collect all this data what you're gonna do with it and most of companies or all the companies today they don't have an answer they're saying oh we're gonna issue an alert and we hope that there is a smart person behind the keyboard that can understand what just happened and make a decision and with this partnership and with this integration basically we're not asking and outsourcing the question what to do to the user we're giving them the answer we're telling them hey this is the story of the attack this is all the pieces that's going on right now and in most cases we're gonna say hey and by the way we just stopped it so you can prevent it from the future when will people be able to leverage this capability in an integrated way and and and by the way restate how this is going to market as an integrated solution what is what is the what is what are we going to call this moving forward so basically this is the cyber reason xdr uh powered by chronicle and we are very very um uh happy about it yeah and i think just to add to that i would say look the the meta strategy here and the way it'll manifest is in this offering that comes out in early 2022 um is that if you think about it today you know a classical quote-unquote security pipeline is to detect you know analyze and then respond obviously you know just just doing those three in a good way is hard doing it in real time at scale is even harder so just that itself was where cyber reason and chronicle would add real value where we are able to collect a lot of events react in real time but a couple of things that i think that you know to your original point of why this is probably going to be a little for game changer in the years to come is we're trying to change that from detect analyze respond to detect understand and anticipate so because ultimately that's really how we can change you know the profile from being reactive in a world of ransomware or anything else to being proactive against a nation sponsored or nation's influenced attacks because they're not going to stop right so the only way to do this is to rather than just go back up the hatches is just really you know change change the profile of how you'll actually anticipate what they were probably going to do in 6 months or 12 months and so the the graph technology that powers the heart of you know cyber reason is going to be intricately woven in with the contextual information that chronicle can get so that the intermediate step is not just about analysis but it's about truly understanding the overall strategy that has been employed in the past to predict what could happen in the future so therefore then actions could be taken downstream that you can now say hey most likely this these five buckets have this kind of personal information data there's a reasonable chance that you know if they're exposed to the internet then as you create more such buckets in that project you're going to be susceptible to more ransomware attacks or some other attacks right and that's the the the kind of thinking or the transformation that we're trying to bring out with this joint office so lior uh this this concept of uh of mallops and uh cyber reason itself you weren't just born yesterday you've been you've been uh you have thousands of customers around the globe he does look like he was born i i know i know i know well you you know it used to be that the ideal candidate for ceo of a startup company was someone who dropped out of stanford i think it's getting to the point where it's people who refused admission to stanford so uh the the dawn of the 14 year old ceo it's just it's just around the corner but uh but lior do you get frustrated when you see um you know when you become aware of circumstances that would not have happened had they implemented your technology as it exists today yeah we have a for this year it was a really frustrating year that starting with solarwind if you analyze the code of solarwind and we did it but other did it as well basically the russians were checking if cyberism is installed on the machine and if we were installed on the machine they decided to stop the attack this is something that first it was a great compliment for us from you know our not friend from the other side that decided to stop the attack but on a serious note it's like we were pissed because if people were using this technology we know that they are not going to be attacked when we analyze it we realize that we have three different ways to find the solar wind hackers in a three different way so this is just one example and then the next example in the colonial pipeline hack we were the one that found darkseid as a group that we were hacking we were the first one that released a research on them and we showed how we can prevent the basically what they are doing with our technology so when you see kind of those type of just two examples and we have many of them on a daily basis we just know that we have the technology in order to do that now when we're combining uh the chronicle technology into the the technology that we already have we basically can reverse the adversary advantage this is something that you're not doing in a single day but this is something that really give power to the defenders to the communities of siso that exist kind of across the us um and i believe that if we're going to join forces and lean into this community and and basically push the solution out the ability for us to fight against those cartels specifically the ransomware cartels is going to be massive sunil this time next year when we are in uh google cloud next 2022 um are you guys going to come back on and offer up the we told you so awards because once this is actually out there and readily available the combination of chronicle and cyber reasons technology um it's going to be hard for some csos to have an excuse uh it may be it may be a uncomfortable to know that uh they could have kept the door secure uh but didn't yeah where's that bad business is that bad business to uh hand out awards for doing dumb things i don't know about uh you know a version of darwin awards probably don't make sense but but but generally speaking so i do think uh you know we're all like as citizens in this right because you know we talk about customers i mean you know alphabet and google is a customer in some ways cyber reason is a customer the cube is a customer right so i think i think the robot hitting the road a year from now will be we should we should do this where i don't know if the cube does more than two folks at the same time david but we should i mean i'm sure we'll have enough to have at least a half a dozen in in the room to kind of talk about the solution because i think the the you know as you can imagine this thing didn't materialize i mean it's been being cooked for a while between your team and our team and in fact it was inspired by feedback from some joint customers out in the market and all that good stuff so so a year from now i think the best thing would be not just having customers to talk about the solution but to really talk about that transformation from respond to anticipate and do they feel better on their security posture in a world that they know like and leo should probably spend a few minutes on this is i think we're on the tip of the sphere of this nation-state era and what we've just seen in the last few years is what maybe the nation-states have seen over two decades ago and they're going to run those playbooks on the enterprise for the next decade or so yeah leor talk about that for a minute yeah it's it's really you know just to continue the sunil thought it's it's really about finding the unknown because what's happening on the other side it's like specifically china and russia and lately we saw iran starting to gain uh power um basically their job is to become better and better and to basically innovate and create a new type of attack on a daily basis as technology has evolved so basically there is a very simple equation as we're using more technology and relying more on technology the other side is going to exploit it in order to gain more power espionage and create financial damage but it's important to say that this evolution it's not going to stop this is just the beginning and a lot of the data that was belong just to government against government fight basically linked in the past few years now criminals starting to use it as well so in a sense if you think about it what's happening right now there is basically a cold war that nobody is talking about it between kind of the giant that everybody is hacking everybody and in the crossfire we see all of those enterprises across the world it was not a surprise that um you know after the biden and putin uh meeting suddenly it was a quiet it was no ransomware for six weeks and after something changing the politics suddenly we can see a a groin kind of attack when it's come to ransomware that we know that was directed from russia in order to create pressure on the u.s economy sunil wrap us up what are your f what are what are your final thoughts and uh what's what's the what's the big takeaway here no i think you know i i think the key thing for everyone to know is look i think we are going into an era of state-sponsored uh not espionage as much as threat vectors that affect every business and so in many ways the chiefs the chief information security officer the chief risk officer in many ways the ceo and the board now have to pay attention to this topic much like they paid attention to mobile 15 years ago as a transformation thing or maybe cloud 10 years ago i think cyber has been one of those it's sort of like the wireless error david like it existed in the 90s but didn't really break around until iphone hit or the world of consumerization really took off right and i think we're at the tip of the spear of that cyber really becoming like the era of mobile for 15 years ago and so i think that's the if there's like a big takeaway i think yes there's lots of solutions the good news is great innovations are coming through companies like cyber reason working with you know proven providers like google and so forth and so there's a lot of like support in the ecosystem but i think if there was one takeaway that was that everybody should just be ready internalized we don't have to be paranoid about it but we anticipate that this is going to be a long game that we'll have to play together well with that uh taking off my journalist hat for a moment and putting on my citizen hat uh it's reassuring to know that we have really smart people working on this uh because when we talk about critical infrastructure control systems and things like that being under threat um that's more significant than simply having your social security number stolen in a in a data breach so um with that uh i'd like to thank you sunil leor thank you so much for joining us on this special cube conversation this is dave nicholson signing off from our continuing coverage of google cloud next 2021 [Music] you

>>Hello. Welcome back to the cubes coverage of splunk.com virtual this year. I'm John ferry, host of the cube. And one of the great reasons of great reasons of being on site with the team here is we have to bring remote guests in real guests from all no stories, too small. We bring people into the cube to have the right conversations. We've got Brooke Cunningham area, VP of global partner marketing experience. Brooke, welcome to the cube. Thanks for coming on. >>Hey, thank you, John. This is my sixth dot conflict, but this is actually my first time being on the cube. So I'm delighted. >>Great to have you on these new hybrid events. We can bring people in. You don't have to be here. All the execs are here, the partners are here. Great news is happening all around the world. You guys just announced a new partner program for the cloud called partner verse program. This is kind of, you know, mostly partner news is okay. Okay. Partner news partner ecosystem. But I think this is an important story because Splunk is kind of going to the next level of scale. That's to me is my observations walking away from the keynote, a lot of the partners, great technology, great platform, a lot of growth with cloud. We had formula one on you guys have a growing ecosystem. What is the new announcement partner versus about? >>Yes. Thanks, John. And you are spot on. We are growing for scale and Splunk's partner ecosystem is 2200 strong and we were so delighted to have so much partner success highlighted today on the keynotes. And specifically we have announced an all new spunk Splunk partner program called the Splunk partner verse. So we're taking it to new frontiers for our partners, really built for the cloud to help our partners lean into those cloud transformations with their customer. >>Great. Fro can you walk me through some of the numbers inside the numbers for a second? How many partners do you have and what is this program about specifically? >>Yeah, so 2200 partners that we featured some amazing stories in the keynotes today, around some of the momentum we have with partners like AWS, a center blue buoyant, a partner that just recently rearchitected all of their managed services from Splunk enterprise to Splunk cloud, because as they put it, Splunk is the only solution that can truly offer that hybrid solution for their customers. So all new goodness for our partners to help them lean in, to get enabled around all of the Splunk products, as well as to differentiate, differentiate their offerings with a new badging system. And we're going to help our partners really take that to the market by extending and expanding our marketing and creating an all new solutions catalog for our partners to differentiate themselves to their customers. >>You mentioned a couple things I want to double down on this badging thing, get in some of the nuances, but I want to just point out that, you know, and get your reaction to this when you see growth. And I saw this early on with AWS early on, when they performing, when you start to see the ecosystem grow like this, you start to see more enablement. You see more, money-making going on more, more, um, custom solutions, more agility you. So you started to see these things develop around you guys. So what does all this badging mean? How what's in it for me as a partner? Like how do I win on this? >>Yeah, great question. So first of all, John partner listening is a big part of what we do here at Splunk. And it's specifically a major part of what I do in my role. So we create a lot of forums to get that real deal partner feedback. What do they need to be successful with their customers? Especially as Splunk continues to expand our portfolio. And we heard some really clear feedback from our partners. Number one, they need more enablement faster, especially all those new products. They really want to get enabled around new product areas like observability, their customers are asking for it. They secondly told us that being able to differentiate themselves to customers was key. And that showing that they had core expertise around specific solution areas, types of services, as well as specializations. For example, some of our partners that are authorized learning partners, they really want it to be able to showcase these skills and differentiate that to their customers in the market. And it's not a role for us at Splunk to really help them do that. And so we took that feedback and really incorporated it into this new program, badging specifically will help to address some of those things I mentioned. So for example, a lot of badging around those use case areas, security, observability, AOD migrations, as well as specializations. Like I mentioned, for things like, uh, partners that are doing, uh, learning specific partners that are really helping us extend our reach in, in different international markets and so on. >>Okay. Let me just ask a question on the badge if you don't mind. Um, so you mentioned, you mentioned almost like you were going through like verticals is badging to be much more about discovery from a client customer, uh, end user customer standpoint. Are you looking to create kind of much more categorical differentiation is what's the, what, what's the purpose of the badge? Cause I noticed it was like different verticals. I heard security and >>Yeah, so I would say it's think of it as both. So for example, our partners go to market with us in many different ways. Some of them are selling servicing building. So there'll be partner motion badges to really differentiate the different ways that they're supporting customers from a go-to-market approach and then additional badging to help really identify some of those specialization areas around whether that's clunky use cases, specializations and more, uh, for example, a specific badge that we're rolling out right here at.com is around cloud migrations and partners will be able to get started to get engaged on that badge in preparation for our full-scale launch in February, we'll, they'll start to be able to take advantage of learning pathways, get their teams skilled up, and that will then unlock some new incentives as well as, uh, benefits that they can take advantage of things like accessing or of the Splunk's I've experience and the proof of concept platform and really giving their teams more, uh, capability. And, >>You know, I such a recent cross in the hallway here at dot confidence. She was, she and I were talking about how AI and data is enabling a lot of people to create these solutions. So, you know, you got kind of this almost like Amazon web services dynamic, where it's growing really fast and we're hearing stories, how data is driving value. We had formula one on the cube, the keynotes were giving some examples as you start to see this momentum kind of scaling up to the next level, if you're enabling customers, which you are with data, the monetization or the economic shifts, right? So it's healthy ecosystems, the partners create solutions, they deal with the customer, they're making some money, right? So, so can you share your vision on the unit on the economic equation of how partners are tapping into this? Because I almost imagine, um, a thousand flowers are blooming and then you start to see more value being created and Splunk also gets a cut of it, but there's, there should be that kind of deck. And you can talk about that. >>Yeah, absolutely. In fact, one of the things that I have the opportunity to do with our partners is study our partners, success and profitability. And some of the things that we learned from those studies with our partners is that what's really helping our partners to grow their practices with Blanca and their profitability with that business is really the stickiness that they have with their customers, being able to deliver solutions and services and really be those subject matter experts for their customers. And we know that our most successful and profitable partners are servicing their customers across the Splunk cases. So for example, many of our partners came from a security background and they are super deep, super knowledgeable around security, and they are trusted by their customers as the, you know, subject matter experts around security. And so many of them are starting to lean in on some of the new, additional use cases. Observability is a hot topic with our partners right now it's a new and emerging use cases case for them to transition some of the same sets of data that they are addressing in their current appointments with our customers and bring new value with those new use cases. But that's where we're seeing partner profitability growth. >>I love the channel dynamic. There we go, indirect and real and value creation. I got to ask you about the day-to-day dynamic. Of course we all know about the mark injuries and story. Software's eating the world, okay. Software ate the world. Okay. Now that's done. Now we're data is continuing to drive the value proposition. And so that's going to have an impact on how customer your partners serve their customers, ultimately your customer at the end of the day. How, how is that happening? And from a success standpoint, how would you talk to, uh, where people are on the progress of bringing the most innovative solutions? What, where's the headroom, where do you see that going Brook >>There's? I would say there's just endless opportunity here. And we just see so much innovation in our partner ecosystem to create purpose built solutions for their customers business problems. And that's where I think the value of the data comes to life. Really turning that data into doing as is really the Matic for all the things that we're talking about here, uh, at.com 21, that our partners really see these opportunities and then can replicate some of those same solutions for other customers in the same spaces. So for example, you know, really specialized solutions for healthcare where they're, uh, providing, you know, access to all the data across the hospital, or, um, you heard in guard's keynote about unlocking the value of SAP data. This is just a huge opportunity accessing all that data and really turning that data into doing. And we'll be talking even more about the new SAP relationship and the value for the partner ecosystem to go address those FP data sets in their customers. We'll be talking more about that on our partner feature session, which is tomorrow in day two of dotcom. >>Well, you guys to have a nice mix of business in the partner ecosystem from, you know, small boutiques to high-end system integrators and everything in between, I noticed you're doing a lot with censure. Could you talk about how you guys are partnering with the large global system integrators because they're becoming their own clouds. So, you know, as Jerry Chen at Greylock says, are these castles being built in the cloud with real competitive advantage with data? Again, this is a new phenomenon in the past really two years, you're starting to see explosion of, of scale and refactoring business models with data. What's your, what's your reaction to that? >>Absolutely. In fact, we are really leading in with some of these global systems integrators, and you've heard this exciting news in Theresa Carlson's portion of the keynote earlier today, where we've announced a partner, a center partner business group together. And we're so excited about the center and Splunk partner business group. It's going to elevate the Splunk and essential partnership eCenter has invested in thousands and thousands of joint professionals that are skilled up on flunk. They are building a purpose patients. We have so many amazing examples where Splunk and essential work together to solve real life problems. For example, there's a joint solution that helps address anti-human trafficking. Uh, there's a joint solution that helped with vaccine tracking. I mean, just really powerful examples that are just really extending value to customers and solving real life, data problems. >>Well, you guys have a lot of momentum, bro. Congratulations on the success and partner versus we're going to follow it again. It was built for the cloud. I know it's in the headline. It says flunked launches, new partner program for the cloud. Was there a partner program for the on premises and what's different about on the cloud? Was it kind of new, everything is cloud what's that? What does that mean? That statement? Yeah, >>Absolutely. So we, you know, as we've all seen, customers are leaning into the class that growth to the movement, to the cloud, just accelerated during COVID. And so part of that feedback that I referenced earlier that we heard from our partners, they said, we need help. We need help moving faster. And so that's really the underpinning of the all-new Splunk partner vers program is to really that acceleration to skill up our partners and give them the tools to be successful. And so with that, we did want to rebrand and reinvigorate it to really signal this newness. And as it was mentioning earlier, when we were talking about the badges, it's really about making sure we're providing the partners the right enablement so that they can be ready and able to support their customers on this journey, to the cloud, as well as the access, the resources, the support and the marketing so that they can be successful and really featured their expertise and value in the market. >>Well, Brooke, I want to get one final question before we go. Cause I know you have a lot of experience in the partner ecosystems and over your career. And we just interviewed the formula one CEO, uh, Zach brown, and, and they've been very popular with the, with the Netflix series driving to survive. And I was joking with him driving value with data as channel partners and your partners look to the post pandemic survive and thrive trend that people are going through right now. What should they be thinking about when they look at partner versus, and how Splunk can help them drive an advantage, not only just survive, but to actually drive to an advantage. >>I, I just see this as an opportunity for partners that haven't already leaned into the cloud and helping their customers migrate to the cloud now is the time rapid five acceleration is just essential for organizations to reach their most critical missions and their outcomes. And this one partner versus program is a significant move forward for Splunk partners. And we want to pursue a massive market opportunity focused on the cloud with our partners, for our customers. So I just really encourage our partners to engage, participate and join us on this journey. >>Well, it's a lot of evidence to support this vision. Uh, with pandemic, we saw refab replatforming and refactoring the businesses in the cloud at speeds, that unprecedented deployments. So, uh, cloud can, can bring that scale and speed to the table. It's really incredible. So thank you very much for coming on the cube remotely. Thanks have you had, >>Thank you. This was a delight. Really appreciate the time, John and very excited to have my first opportunity to be a >>Okay. You're a cube alumni. We are here in the studios, Splunk studios for their virtual event here with all the top executives and partners bringing in guests remotely. It's a virtual event. So we'll be back in person. I'm Jennifer, the cube. Thanks for watching.

>>From the Bellagio hotel in Las Vegas. It's the cube covering UI path forward for brought to you by UI path. >>Hey, welcome back to Las Vegas. Lisa Martin, with Dave Volante, the cube is here, live at UI path forward for very excited to be here in person. Next topic, the smart factory, a couple of guests here to unpack that for us, Jason Brixton joins us the smart factory lead at Deloitte and Thomas Hanson, the CRO of UI path gentlemen, and welcome to the program. Thank you. Thank you for having us great to have you great to be in person. Let's talk about smart track factory factory Ford auto. What is it from Deloitte perspective and then UI path. >>So if you think about smart factory, it's really that transition from the old kind of analog manufacturing environment to the digital, digital operating type environment that we see today. So technology has really changed in the last three or four years. And as a result of that elevation of technology, we're able to do a lot more on the manufacturing floor than we ever could. So what used to be more analog or hybrid with a little bit of technology is now starting to shift really to end to end integrated manufacturing operations that are based on digital platforms and we're loving it. It's a great place to be >>Great. Tell us what's your perspective? >>Well, first of all, it's great to be here. Thank you for the invite. It's so nice to be away from soon calls or, or other type of, uh, of calls, right. And be in person. Uh, look, we have an amazing partnership with the lights. Um, we have worked together for years. We've done more than 400 joint engagements with the large companies across the world. And in that process, we've really gone deeper from a vertical and industry perspective and smart factory is really the starting point of going super specific and figuring out what does automation or how does automation rather play into, um, to a, to a smart factory, like a beautiful trombone, that music from a beautiful trombone. >>So years ago, we wrote a piece talking about the cloud as an opportunity and how to take advantage of it. And one of the, the premise of the piece was you've got to build ecosystems and maybe it's within an industry or within a practice and build data in different disciplines because the power of many versus the capabilities of one, this smart factory initiative that you guys have going, it feels like an ecosystem play. Can you describe that ecosystem? Who's involved? I know SAP in for AWS, but, but tell us more about the ECOS. >>Yeah, sure. So your, your hunch, there is a great one, right? We, we learned early on that trying to do this as Deloitte or Deloitte plus one just, wasn't going to get it done, right? You really needed to harness the power of the many. And so at the, at the core of what we're doing at the smart factory at Wichita, that you alluded to is about bringing an ecosystem to life. So we have 21 partners that are going to be participating out of the gate with the smart factory. Wichitan the intent is to show a seamless solution and actual end-to-end production facility that showcases 21 amazing technologies and partners. And we're just really thrilled about what we're able to show our clients. So, >>Yep. So Koch industries owns Inforce. So obviously that's the Wichita connection, is that right? So they got to be involved in this. I mean, they were amazing company, but what can you tell us about, uh, their, their involvement? >>Yep. So Coke, obviously the in for connection, uh, Dragos, which is another in four company as a founder within, uh, within the ecosystem, which is fantastic. There they play at the core. They're also an incredibly important client, right? So the Coke business on the whole is critical to how we think about manufacturing across a whole range of industries from discreet production to scale process. Um, they're fantastic partners and we've had a great time working with them. And you guys are just, >>It's about to launch through soft launch. Can you tell us more where you are in the progression? >>Sure. So soft launch started two days ago. Oh wow. So the building, we have the keys, uh, we are doing some visits with a handful of friends and family, that ecosystem partners that you mentioned, there'll be coming out, uh, to see it and to provide some feedback. And then we go live in earnest in January >>At Thomas where's UI path fit. >>Well, we fit in essay as a key part in this initiative. Um, look, we, as a company, we are part the preferred partner. First, we do all our business together with partners and we have right about almost 5,000 partners now, globally. And then there's a few, then there's a few in that 5,000 that are unique that really stand out. And Deloitte of course is one of those very, very special partners that we work with globally, but also locally here in the us, across all the states across all the industries. So we're thrilled to be part of this automation plays a key key part of smart factory. When you think about it, the evolution of work there's so much boring, mundane work on there. Humankind is better served, spending their time and effort on the non mundane on the innovative on the creative. And that's what we try to ensure that the humans in the loop so to speak are focused on the innovative work, the graded work, and we have software robots, RPA automation handle all that boring and mundane work, >>Right? Letting the folks focus on the value, add to themselves a value add to the organization, more strategic investments. Thomas question for you is in terms of you talked about this being horizontal across industries, but I'm curious about what some of the feedback is from some of your customers, 8,000 customers. Now you've got a very large what, 726 million ARR, huge lot of customers over a hundred million ARR. What's been the feedback from some of those guys. >>Well, so first of all, uh, personally, I I've been in enterprise software for more than 20 years. And what I've experienced over the years are most large scale enterprise software projects tends to be multi-year in nature, be rather complex. And the failure rate can be rather high. Then in comes RPA and automation, which is a complete different kettle of fish in the sense that from conceptualization of identifying a process, to getting it built, getting it tested, getting it into production, you're talking days and weeks only. So the path to seeing value is so fast. What I've learned yesterday and today from the 1516 customer meetings I've had so far is the same unique trend or learning across all industries and also from various parts of the world. And that is very fast realization of value, perhaps starting initially with 5, 10 20 processes and then scaling super fast because the find that return on investment incredibly quickly with our solution. So that's what unifies it across geographies and across industries. >>What'd you think about the smart factory? And one of the things we've learned during COVID is there's so much unknown. So sometimes these processes aren't linear like a trombone, you know, going back and forth in and out, but is there unknown in the smart factory processes or is it pretty well known? And you can do the process mining on that known base. What's the dynamic >>Back there. So there's a few different dimensions to it. So yes, it is well known because it's a controlled environment, but one of the things that we're doing is we're actually actively introducing a lot of unknown factors to try to let the bots and the process mining kick into effect. Right? So we're artificially, let's just say injecting opportunity for us to do that. The other thing that we're doing is, and what's really unique about the smart factory at Wichita is it's one of four across the globe for Deloitte. And so we're bringing data in from the other three sites, which is data, that'll be less controlled. We're going to do process mining on that. Just try to take advantage of some of the, some of the capabilities associated with the solutions. >>Okay. So, so w when you think about process mining, do you start there, or do you start with, I sometimes call it paving the cow path, you know, taking what you've known, that linear process that, that hit that as the quick win, and then worry about the process money, or do you step back and say, wait a minute, we have to rethink the entire factory experience. Where do you start? >>I think it depends in the case of the smart factory with that, we've got a few different places, so we're using it to do ingestion of orders. So that's obviously a very controlled environment. We're then using it to do a lot of work around inventory management and optimization as well as month end close plays, which will be a lot more we're learning as we go. Right. So I think on the spectrum, it could be on either end my personal belief. If you look at it more long-term or actually out in the real world is that this is all about learning new things. It's about generating insights from data that frankly, you don't want human beings to have to go do that. And so having the ability to take advantage of an intelligent automation solution, as powerful as UI path is really a great advantage. >>One of the things that's misunderstood, I think about UI path is they look at what happened post let's say 2015, 2016, and say, oh, just like, just like every other Silicon valley company, double, double, triple, triple. And that's not how you guys started. You sort of let things bake for the better part of a decade and then got product market fit and then exploded. Um, and so that's, that to me was a key to your success in scaling this. I feel like you guys are building a new offering here. This is not just doing a one-off the product market fit. It's not like a point product. It's a, it's a big thing. So can you talk about the go to market, your product market fit? You're testing it out now, your goals, are you trying to scale this up? What, what are some of the things that you can share about your aspirations? So >>The partnership from a UI path perspective to Deloitte is a critical partnership. One of the select few on a global level, uh, we have enjoyed tremendous, uh, amount of engagements together. I mentioned early on 400, and I believe we, we now have together right about 1000 developers trained within your organization on your iPod, right? That's right. Yep. So we have a strong base that, of course we want to build full and hopefully put a syrup behind the thousand to 10,000. And over time, we want to make sure that it's globally inclusive, that we can serve all the marketers across the world where we have giant presence. And there's a select number of verticals and industries where we really have had success together that we of course want to go and specifically shoe in on what would have caused now be manufacturing together. And of course, a classic vertical we've been very strong in together as BFSI bank and financial services industry. So those are good areas. >>Well, Jason, you're building a business out of this, right? I mean, you've got a business plan around it and you're going to scale this thing. >>Oh, absolutely. Yeah. That's 100% the case. So we have smart factory at Wichita. That is part of our positioning in the marketplace. What we found is that telling people about tech and about solutions is one thing, showing it to them in a production environment is altogether different, right? Giving clients the opportunity to explore the art of the possible in a real setting like that is incredibly impactful. And so you talked about go to market, we see this relationship with the ecosystem and what we're trying to do in Wichita, that's sort of the epicenter of building an entire business, which ultimately will have huge global potential. >>We talk about speed for a minute. And the growth trajectory that UI path Thomas has been on for the last five years or so. I think I was reading, I think it was analysis that Dave wrote that in 2016 revenue was 1,000,020, 20, 15, 20, 20 600 million. So massive growth very quickly. My question, Jason is for you in terms of the speed. Ha how quickly are you looking to see the smart factory for Dato really impacting organizations around the globe because these guys are on a fast bulleted. >>Yeah. So I wish we had those growth rates. I will say though, selling and delivering these solutions holistically to manufacturers takes more time. So we think of our cycle as be measured, certainly in many months, certainly not years. We are starting to see an acceleration of that entire sales cycle and delivery cycle, just because of things like the pandemic driving organizations to just need to move faster. Frankly, if you're not moving towards digital manufacturing operations right now, you're probably behind. And so we're seeing that urgency from the market start to pick up, but we don't have that kind of growth rate, unfortunately. >>Well, what's it. What's interesting about Deloitte to me is you guys here, I think of you as a virtual company. I mean, I know you got a lot of bodies out there, but it's not like you've got a lot of physical locations. Right. And so now, but now you're just, you're investing in a physical plant essentially, >>Which is extremely exciting. We, we keep telling ourselves when we talk to folks, they own lots of buildings. So just because we're excited about our building doesn't mean they are, but you're exactly right, right. We're obviously a global services and products company. So this is one of a handful of buildings that are going to start to represent us as an organization. And we're really excited about what should we watch? >>It's kind of milestones for progress success. What are the markers that we should be paying attention to is independence. >>I think specifically on this, um, rapid experiment together, I think one of the key learnings we can take away that we can apply to other companies in the manufacturing industry specifically look from a UI perspective. We work with many large scale manufacturers around the world, but we've seen amazing fast progress with Bridgestone. For example, we implemented a smaller set of, uh, uh, bots that help them reduce their paperwork by 85% onto their branches with a Turkish e-commerce retailer called Archer. Lik I think I get the pronunciation correctly. They put 85 processes in place with our bots and are now to date transacting or running. I think it's 3 million e-commerce transactions with our processes. So the impact we can have in manufacturing together with the learnings from this, my factory, I think is just so exciting. Really? >>Yeah. The impact, the potential there is, is unlimited. Guys. Thank you for joining David, me talking to us about smart factory Ford auto, what it means for both businesses, how the partnership is evolving. It sounds like music from a beautiful trombone. Thank you so much for joining Dave and me today. Thank you For Dave Volante. I'm Lisa Martin. The Cubas live in Las Vegas at the Bellagio at UI path forward for we'll be right back.

>>Hello. And we're here at the cube startup showcase made possible by a Ws. Thanks so much for joining us today. You know when Jim McDaid Ghani was formulating her ideas around data mesh, She wasn't the only one thinking about decentralized data architecture. Hello, Fresh was going into hyper growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of last decade, Hello Fresh relied on a monolithic data architecture and the internal team. It had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture which possessed many principles of so called data mesh even though they didn't use that term. Specifically, the company is a strong example of an early but practical pioneer of data mission. Now there are many practitioners and stakeholders involved in evolving the company's data architecture, many of whom are listed here on this on the slide to are highlighted in red are joining us today, we're really excited to welcome into the cube Clements cheese, the Global Senior Director for Data at Hello Fresh and christoph Nevada who's the Global Senior Director of data also, of course. Hello Fresh folks. Welcome. Thanks so much for making some time today and sharing your story. >>Thank you very much. Hey >>steve. All right, let's start with Hello Fresh. You guys are number one in the world in your field, you deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling christoph. Tell us a little bit more about your company and its vision. >>Yeah. Should I start or Clements maybe maybe take over the first piece because Clements has actually been a longer trajectory yet have a fresh. >>Yeah go ahead. Climate change. I mean yes about approximately six years ago I joined handle fresh and I didn't think about the startup I was joining would eventually I. P. O. And just two years later and the freshman public and approximately three years and 10 months after. Hello fresh was listed on the German stock exchange which was just last week. Hello Fresh was included in the Ducks Germany's leading stock market index and debt to mind a great great milestone and I'm really looking forward and I'm very excited for the future for the future for head of fashion. All our data. Um the vision that we have is to become the world's leading food solution group and there's a lot of attractive opportunities. So recently we did lounge and expand Norway. This was in july and earlier this year we launched the U. S. Brand green >>chef in the U. K. As >>well. We're committed to launch continuously different geographies in the next coming years and have a strong pipe ahead of us with the acquisition of ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. We're diversifying our offer now reaching even more and more untapped customer segments and increase our total addressable market. So by offering customers and growing range of different alternatives to shop food and consumer meals. We are charging towards this vision and the school to become the world's leading integrated food solutions group. >>Love it. You guys are on a rocket ship, you're really transforming the industry and as you expand your tam it brings us to sort of the data as a as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company specifically as it relates to your data journey. You began as a start up. You had a basic architecture like everyone. You made extensive use of spreadsheets. You built a Hadoop based system that started to grow and when the company I. P. O. You really started to explode. So maybe describe that journey from a data perspective. >>Yes they saw Hello fresh by 2015 approximately had evolved what amount of classical centralized management set up. So we grew very organically over the years and there were a lot of very smart people around the globe. Really building the company and building our infrastructure. Um This also means that there were a small number of internal and external sources. Data sources and a centralized the I team with a number of people producing different reports, different dashboards and products for our executives for example of our different operations teams, christian company's performance and knowledge was transferred um just via talking to each other face to face conversations and the people in the data where's team were considered as the data wizard or as the E. T. L. Wizard. Very classical challenges. And those et al. Reserves indicated the kind of like a silent knowledge of data management. Right? Um so a central data whereas team then was responsible for different type of verticals and different domains, different geographies and all this setup gave us to the beginning the flexibility to grow fast as a company in 2015 >>christoph anything that might add to that. >>Yes. Um Not expected to that one but as as clement says it right, this was kind of set up that actually work for us quite a while. And then in 2017 when L. A. Freshman public, the company also grew rapidly and just to give you an idea how that looked like. As was that the tech department self actually increased from about 40 people to almost 300 engineers And the same way as a business units as Clemens has described, also grew sustainable, sustainably. So we continue to launch hello fresh and new countries launching brands like every plate and also acquired other brands like much of a factor and with that grows also from a data perspective the number of data requests that centrally we're getting become more and more and more and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very or basically get a very deep understanding about the business. And also suffered a lot from this context switching back and forth, essentially there to prioritize across our product request from our physical product, digital product from the physical from sorry, from the marketing perspective and also from the central reporting uh teams. And in a nutshell this was very hard for these people. And this that also to a situation that, let's say the solution that we have became not really optimal. So in a nutshell, the central function became a bottleneck and slowdown of all the innovation of the company. >>It's a classic case, isn't it? I mean Clements, you see you see the central team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own hands. And then of course I I. T. And the technical team is called in later to clean up the mess. Uh maybe, I mean was that maybe I'm overstating it, but that's a common situation, isn't it? >>Yeah. Uh This is what exactly happened. Right. So um we had a bottleneck, we have the central teams, there was always a little of tension um analytics teams then started in this business domains like marketing, trade chain, finance, HR and so on. Started really to build their own data solutions at some point you have to get the ball rolling right and then continue the trajectory um which means then that the data pipelines didn't meet the engineering standards. And um there was an increased need for maintenance and support from central teams. Hence over time the knowledge about those pipelines and how to maintain a particular uh infrastructure for example left the company such that most of those data assets and data sets are turned into a huge step with decreasing data quality um also decrease the lack of trust, decreasing transparency. And this was increasing challenge where majority of time was spent in meeting rooms to align on on data quality for example. >>Yeah. And and the point you were making christoph about context switching and this is this is a point that Jemaah makes quite often is we've we've we've contextualized are operational systems like our sales systems, our marketing system but not our our data system. So you're asking the data team, Okay. Be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it start stop, start, stop, it's a paper cut environment and it's just not as productive. But but on the flip side of that is when you think about a centralized organization you think, hey this is going to be a very efficient way, a cross functional team to support the organization but it's not necessarily the highest velocity, most effective organizational structure. >>Yeah, so so I agree with that. Is that up to a certain scale, a centralized function has a lot of advantages, right? That's clear for everyone which would go to some kind of expert team. However, if you see that you actually would like to accelerate that and specific and this hyper growth, right, you wanna actually have autonomy and certain teams and move the teams or let's say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load and you can either internally start splitting your team into a different kind of sub teams focusing on different areas. However, that is then again, just adding another peace where actually collaboration needs to happen busy external sees, so why not bridging that gap immediately and actually move these teams and to end into into the function themselves. So maybe just to continue what, what was Clements was saying and this is actually where over. So Clements, my journey started to become one joint journey. So Clements was coming actually from one of these teams to build their own solutions. I was basically having the platform team called database housed in these days and in 2019 where basically the situation become more and more serious, I would say so more and more people have recognized that this model doesn't really scale In 2019, basically the leadership of the company came together and I identified data as a key strategic asset and what we mean by that, that if we leverage data in a proper way, it gives us a unique competitive advantage which could help us to, to support and actually fully automated our decision making process across the entire value chain. So what we're, what we're trying to do now or what we should be aiming for is that Hello, Fresh is able to build data products that have a purpose. We're moving away from the idea. Data is just a by problem products, we have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to for the company as a business, we also want to provide them as a trust versi asset to the rest of the organization. We say there's the best customer experience, but at least in a way that users can easily discover, understand and security access high quality data. >>Yeah, so and and and Clements, when you c J Maxx writing, you see, you know, she has the four pillars and and the principles as practitioners you look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's and that's where the devil meets the details. So it's the four, you know, the decentralized data ownership data as a product, which we'll talk about a little bit self serve, which you guys have spent a lot of time on inclement your wheelhouse which is which is governance and a Federated governance model. And it's almost like if you if you achieve the first two then you have to solve for the second to it almost creates a new challenges but maybe you could talk about that a little bit as to how it relates to Hello fresh. >>Yes. So christophe mentioned that we identified economic challenge beforehand and for how can we actually decentralized and actually empower the different colleagues of ours. This was more a we realized that it was more an organizational or a cultural change and this is something that somebody also mentioned I think thought words mentioned one of the white papers, it's more of a organizational or cultural impact and we kicked off a um faced reorganization or different phases we're currently and um in the middle of still but we kicked off different phases of organizational reconstruct oring reorganization, try unlock this data at scale. And the idea was really moving away from um ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do, what shall we do? This is value creation and how, which is capability building and both are equal in authority. This actually then creates a high urge and collaboration and this collaboration breaks up the different silos that were built and of course this also includes different needs of stuffing forward teams stuffing with more, let's say data scientists or data engineers, data professionals into those business domains and hence also more capability building. Um Okay, >>go ahead. Sorry. >>So back to Tzemach did johnny. So we the idea also Then crossed over when she published her papers in May 2019 and we thought well The four colors that she described um we're around decentralized data ownership, product data as a product mindset, we have a self service infrastructure and as you mentioned, Federated confidential governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then leads to a not only organisational restructure but also in completely new approach of how we need to manage data, show data. >>Got it. Okay, so your business is is exploding. Your data team will have to become domain experts in too many areas, constantly contact switching as we said, people started to take things into their own hands. So again we said classic story but but you didn't let it get out of control and that's important. So we actually have a picture of kind of where you're going today and it's evolved into this Pat, if you could bring up the picture with the the elephant here we go. So I would talk a little bit about the architecture, doesn't show it here, the spreadsheet era but christoph maybe you can talk about that. It does show the Hadoop monolith which exists today. I think that's in a managed managed hosting service, but but you you preserve that piece of it, but if I understand it correctly, everything is evolving to the cloud, I think you're running a lot of this or all of it in A W. S. Uh you've got everybody's got their own data sources, uh you've got a data hub which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure. That is really not the focus of this conversation today. But the key here, if I understand it correctly is these domains are autonomous and not only that this required technical thinking, but really supportive organizational mindset, which we're gonna talk about today. But christoph maybe you could address, you know, at a high level some of the architectural evolution that you guys went through. >>Yeah, sure. Yeah, maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning with the model is on the operation of playing right? Actually, it wasn't just one model is both to one for the back end and one for the for the front and and or analytical plane was essentially a couple of spreadsheets and I think there's nothing wrong with spreadsheets, right, allows you to store information, it allows you to transform data allows you to share this information. It allows you to visualize this data, but all the kind of that's not actually separating concern right? Everything in one tool. And this means that obviously not scalable, right? You reach the point where this kind of management set up in or data management of isn't one tool reached elements. So what we have started is we've created our data lake as we have seen here on Youtube. And this at the very beginning actually reflected very much our operational populace on top of that. We used impala is a data warehouse, but there was not really a distinction between borders, our data warehouse and borders our data like the impala was used as a kind of those as the kind of engine to create a warehouse and data like construct itself and this organic growth actually led to a situation as I think it's it's clear now that we had to centralized model is for all the domains that will really lose kimball modeling standards. There was no uniformity used actually build in house uh ways of building materialized use abuse that we have used for the presentation layer, there was a lot of duplication of effort and in the end essentially they were missing feedbacks, food, which helped us to to improve of what we are filled. So in the end, in the natural, as we have said, the lack of trust and that's basically what the starting point for us to understand. Okay, how can we move away and there are a lot of different things that you can discuss of apart from this organizational structure that we have said, okay, we have these three or four pillars from from Denmark. However, there's also the next extra question around how do we implement our talking about actual right, what are the implications on that level? And I think that is there's something that we are that we are currently still in progress. >>Got it. Okay, so I wonder if we could talk about switch gears a little bit and talk about the organizational and cultural challenges that you faced. What were those conversations like? Uh let's dig into that a little bit. I want to get into governance as well. >>The conversations on the cultural change. I mean yes, we went through a hyper growth for the last year since obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company which then results that collaboration uh >>got a bit more difficult. Of course >>there are times and changes, you have different different artifacts that you were created um and documentation that were flying around. Um so we were we had to build the company from scratch right? Um Of course this then resulted always this tension which I described before, but the most important part here is that data has always been a very important factor at l a fresh and we collected >>more of this >>data and continued to improve use data to improve the different key areas of our business. >>Um even >>when organizational struggles, the central organizational struggles data somehow always helped us to go through this this kind of change. Right? Um in the end those decentralized teams in our local geography ease started with solutions that serve the business which was very very important otherwise wouldn't be at the place where we are today but they did by all late best practices and standards and I always used sport analogy Dave So like any sport, there are different rules and regulations that need to be followed. These rules are defined by calling the sports association and this is what you can think about data governance and compliance team. Now we add the players to it who need to follow those rules and bite by them. This is what we then called data management. Now we have the different players and professionals, they need to be trained and understand the strategy and it rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in a different domains. And one of our mission of our data literacy program for example is to really empower >>every employee at hello >>fresh everyone to make the right data informs decisions by providing data education that scaled by royal Entry team. Then this can be different things, different things like including data capabilities, um, with the learning paths for example. Right? So help them to create and deploy data products connecting data producers and data consumers and create a common sense and more understanding of each other's dependencies, which is important, for example, S. S. L. O. State of contracts and etcetera. Um, people getting more of a sense of ownership and responsibility. Of course, we have to define what it means, what does ownership means? But the responsibility means. But we're teaching this to our colleagues via individual learning patterns and help them up skill to use. Also, there's shared infrastructure and those self self service applications and overall to summarize, we're still in this progress of of, of learning, we are still learning as well. So learning never stops the tele fish, but we are really trying this um, to make it as much fun as possible. And in the end we all know user behavior has changed through positive experience. Uh, so instead of having massive training programs over endless courses of workshops, um, leaving our new journalists and colleagues confused and overwhelmed. >>We're applying um, >>game ification, right? So split different levels of certification where our colleagues can access, have had access points, they can earn badges along the way, which then simplifies the process of learning and engagement of the users and this is what we see in surveys, for example, where our employees that your justification approach a lot and are even competing to collect Those learning path batteries to become the # one on the leader board. >>I love the game ification, we've seen it work so well and so many different industries, not the least of which is crypto so you've identified some of the process gaps uh that you, you saw it is gloss over them. Sometimes I say paved the cow path. You didn't try to force, in other words, a new architecture into the legacy processes. You really have to rethink your approach to data management. So what what did that entail? >>Um, to rethink the way of data management. 100%. So if I take the example of Revolution, Industrial Revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. Um, so we needed to establish a new set of cross functional business processes to run faster, dry faster, um, more robustly and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector with internal, I'm always referring to the data operations around new things like data catalog, how to identify >>ownership, >>how to change ownership, how to certify data assets, everything around classical software development, which we know apply to data. This this is similar to a new thinking, right? Um deployment, versioning, QA all the different things, ingestion policies, policing procedures, all the things that suffer. Development has been doing. We do it now with data as well. And in simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes and as a creation as management and as a consumption. >>So data has become kind of the new development kit. If you will um I want to shift gears and talk about the notion of data product and, and we have a slide uh that we pulled from your deck and I'd like to unpack it a little bit. Uh I'll just, if you can bring that up, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems where customers, both internal and external. So pretty straightforward. I know you've gone much deeper and you're thinking and into your organization, but how do you think about that And how do you determine for instance who owns what? How did you get everybody to agree? >>I can take that one. Um, maybe let me start with the data product. So I think um that's an ongoing debate. Right? And I think the debate itself is an important piece here, right? That visit the debate, you clarify what we actually mean by that product and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say okay that our product is something which is important for the company has come to its value what you mean by that. Okay, it's it's a solution to a customer problem that delivers ideally maximum value to the business. And yes, it leverages the power of data and we have a couple of examples but it had a fresh year, the historical and classical ones around dashboards for example, to monitor or error rates but also more sophisticated ways for example to incorporate machine learning algorithms in our recipe recommendations. However, I think the important aspects of the data product is a there is an owner, right? There's someone accountable for making sure that the product that we are providing is actually served and is maintained and there are, there is someone who is making sure that this actually keeps the value of that problem thing combined with the idea of the proper documentation, like a product description, right that people understand how to use their bodies is about and related to that peace is the idea of it is a purpose. Right? You need to understand or ask ourselves, Okay, why does this thing exist does it provide the value that you think it does. That leads into a good understanding about the life cycle of the data product and life cycle what we mean? Okay from the beginning from the creation you need to have a good understanding, we need to collect feedback, we need to learn about that. We need to rework and actually finally also to think about okay benefits time to decommission piece. So overall, I think the core of the data product is product thinking 11 right that we start the point is the starting point needs to be the problem and not the solution and this is essentially what we have seen what was missing but brought us to this kind of data spaghetti that we have built there in in Russia, essentially we built at certain data assets, develop in isolation and continuously patch the solution just to fulfill these articles that we got and actually these aren't really understanding of the stakeholder needs and the interesting piece as a result in duplication of work and this is not just frustrating and probably not the most efficient way how the company should work. But also if I build the same that assets but slightly different assumption across the company and multiple teams that leads to data inconsistency and imagine the following too narrow you as a management for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kind of grass, different kind of data and numbers and in the end you do not know which ones to trust. So there's actually much more ambiguity and you do not know actually is a noise for times of observing or is it just actually is there actually a signal that I'm looking for? And the same is if I'm running in a B test right, I have a new future, I would like to understand what has it been the business impact of this feature. I run that specific source in an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you've seen in a B test is actually not what you see then in production typical thing then is you're asking some analytics tend to actually do a deep dive to understand where the discrepancies are coming from. The worst case scenario. Again, there's a different kind of source. So in the end it's a pretty frustrating scenario and that's actually based of time of people that have to identify the root cause of this divergence. So in a nutshell, the highest degree of consistency is actually achieved that people are just reusing Dallas assets and also in the media talk that we have given right, we we start trying to establish this approach for a B testing. So we have a team but just providing or is kind of owning their target metric associated business teams and they're providing that as a product also to other services including the A B testing team, they'll be testing team can use this information defines an interface is okay I'm joining this information that the metadata of an experiment and in the end after the assignment after this data collection face, they can easily add a graph to the dashboard. Just group by the >>Beatles Hungarian. >>And we have seen that also in other companies. So it's not just a nice dream that we have right. I have actually worked in other companies where we worked on search and we established a complete KPI pipeline that was computing all this information. And this information was hosted by the team and it was used for everything A B test and deep dives and and regular reporting. So uh just one of the second the important piece now, why I'm coming back to that is that requires that we are treating this data as a product right? If you want to have multiple people using the things that I am owning and building, we have to provide this as a trust mercy asset and in a way that it's easy for people to discover and actually work with. >>Yeah. And coming back to that. So this is to me this is why I get so excited about data mesh because I really do think it's the right direction for organizations. When people hear data product they say well, what does that mean? Uh but then when you start to sort of define it as you did, it's it's using data to add value, that could be cutting costs, that could be generating revenue, it could be actually directly you're creating a product that you monetize, So it's sort of in the eyes of the beholder. But I think the other point that we've made is you made it earlier on to and again, context. So when you have a centralized data team and you have all these P NL managers a lot of times they'll question the data because they don't own it. They're like wait a minute. If they don't, if it doesn't agree with their agenda, they'll attack the data. But if they own the data then they're responsible for defending that and that is a mindset change, that's really important. Um And I'm curious uh is how you got to, you know, that ownership? Was it a was it a top down with somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what in other words, you know, did you get, how did you get the business to take ownership of the data and what is owning? You know, the data actually mean? >>That's a very good question. Dave I think this is one of the pieces where I think we have a lot of learnings and basically if you ask me how we could start the feeling. I think that would be the first piece. Maybe we need to start to really think about how that should be approached if it stopped his ownership. Right? It means somehow that the team has a responsibility to host and self the data efforts to minimum acceptable standards. This minimum dependencies up and down string. The interesting piece has been looking backwards. What what's happening is that under that definition has actually process that we have to go through is not actually transferring ownership from the central team to the distributor teams. But actually most cases to establish ownership, I make this difference because saying we have to transfer ownership actually would erroneously suggests that the data set was owned before. But this platform team, yes, they had the capability to make the changes on data pipelines, but actually the analytics team, they're always the ones who had the business understands, you use cases and but no one actually, but it's actually expensive expected. So we had to go through this very lengthy process and establishing ownership. We have done that, as in the beginning, very naively. They have started, here's a document here, all the data assets, what is probably the nearest neighbor who can actually take care of that and then we we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent over years and these people who have built this thing have already left the company. So there's actually not a nice thing that is that you want to see and people build up a certain resistance, e even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, but what needs to happen as first, the company needs to really understand what our core business concept that they have, they need to have this mapping from. These are the core business concept that we have. These are the domain teams who are owning this concept and then actually link that to the to the assets and integrated better with both understanding how we can evolve actually, the data assets and new data build things new in the in this piece in the domain. But also how can we address reduction of technical death and stabilizing what we have already. >>Thank you for that christoph. So I want to turn a direction here and talk about governance and I know that's an area that's passionate, you're passionate about. Uh I pulled this slide from your deck, which I kind of messed up a little bit sorry for that, but but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks. But it's one of the most challenging aspects of data mesh, if you're going to decentralize you, you quickly realize this could be the Wild West as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy, compliance etcetera. So, so how did you approach this? >>It's yeah, it's about connecting those dots. Right. So the aim of the data governance program is about the autonomy of every team was still ensuring that everybody has the right interoperability. So when we want to move from the Wild West riding horses to a civilised way of transport, um you can take the example of modern street traffic, like when all participants can manoeuvre independently and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights in the different signals. Um, so likewise as a business and Hello Fresh, we do operate autonomously and consequently need to follow those external and internal rules and standards to set forth by the redistribution in which we operate so in order to prevent a car crash, we need to at least ensure compliance with regulations to account for society's and our customers increasing concern with data protection and privacy. So teaching and advocating this advantage, realizing this to everyone in the company um was a key community communication strategy and of course, I mean I mentioned data privacy external factors, the same goes for internal regulations and processes to help our colleagues to adapt to this very new environment. So when I mentioned before the new way of thinking the new way of um dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. Um in a nutshell then this means the data governance provides a framework for managing our people the processes and technology and culture around our data traffic. And those components must come together in order to have this effective program providing at least a common denominator, especially critical for shared dataset, which we have across our different geographies managed and shared applications on shared infrastructure and applications and is then consumed by centralized processes um for example, master data, everything and all the metrics and KPI s which are also used for a central steering. Um it's a big change day. Right. And our ultimate goal is to have this noninvasive, Federated um ultimatum and computational governance and for that we can't just talk about it. We actually have to go deep and use case by use case and Qc buy PVC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status by identifying together with the business teams with the different domains have a risk assessment for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of illiteracy comes into place where we go in and trade based on the findings based on the most valuable use case um and based on that help our teams to do this change to increase um their capability just a little bit more and once they hand holding. But a lot of guidance >>can I kind of kind of trying to quickly David will allow me I mean there's there's a lot of governance piece but I think um that is important. And if you're talking about documentation for example, yes, we can go from team to team and tell these people how you have to document your data and data catalog or you have to establish data contracts and so on the force. But if you would like to build data products at scale following actual governance, we need to think about automation right. We need to think about a lot of things that we can learn from engineering before. And that starts with simple things like if we would like to build up trust in our data products, right, and actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do and we should probably think about what we can copy and one example might be. So the level of service level agreements, service level objectives. So that level indicators right, that represent on on an engineering level, right? If we're providing services there representing the promises we made to our customers or consumers, these are the internal objectives that help us to keep those promises. And actually these are the way of how we are tracking ourselves, how we are doing. And this is just one example of that thing. The Federated Governor governance comes into play right. In an ideal world, we should not just talk about data as a product but also data product. That's code that we say, okay, as most as much as possible. Right? Give the engineers the tool that they are familiar basis and actually not ask the product managers for example to document their data assets in the data catalog but make it part of the configuration. Have this as a, as a C D C I, a continuous delivery pipeline as we typically see another engineering task through and services we say, okay, there is configuration, we can think about pr I can think about data quality monitoring, we can think about um the ingestion data catalog and so on and forest, I think ideally in the data product will become of a certain templates that can be deployed and are actually rejected or verified at build time before we actually make them deploy them to production. >>Yeah, So it's like devoPS for data product um so I'm envisioning almost a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where there's there's learning, there's literacy, there's training, education, there's kind of self governance and then there's some kind of oversight, some a lot of manual stuff going on and then you you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >>Yeah, I would rather think think about automation as early as possible in the way and yes, there needs to be certain rules but then actually start actually use case by use case. Is there anything that small piece that we can already automate? It's as possible. Roll that out and then actually extended step by step, >>is there a role though that adjudicates that? Is there a central Chief state officer who is responsible for making sure people are complying or is it how do you handle that? >>I mean from a from a from a platform perspective, yes, we have a centralized team to uh implement certain pieces they'll be saying are important and actually would like to implement. However, that is actually working very closely with the governance department. So it's Clements piece to understand and defy the policies that needs to be implemented. >>So Clements essentially it's it's your responsibility to make sure that the policy is being followed. And then as you were saying, christoph trying to compress the time to automation as fast as possible percent. >>So >>it's really it's uh >>what needs to be really clear that it's always a split effort, Right? So you can't just do one thing or the other thing, but everything really goes hand in hand because for the right automation for the right engineering tooling, we need to have the transparency first. Uh I mean code needs to be coded so we kind of need to operate on the same level with the right understanding. So there's actually two things that are important which is one its policies and guidelines, but not only that because more importantly or even well equally important to align with the end user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >>Got it. So just a couple more questions because we gotta wrap I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment but but major learnings, we've got some of the challenges that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks. But my question, I mean this is the advice for your peers question if you had to do it differently if you had a do over or a Mulligan as we like to say for you golfers, what would you do differently? Yeah, >>I mean can we start with from a from the transformational challenge that understanding that it's also high load of cultural change. I think this is this is important that a particular communication strategy needs to be put into place and people really need to be um supported. Right? So it's not that we go in and say well we have to change towards data mesh but naturally it's in human nature, you know, we're kind of resistance to to change right? Her speech uncomfortable. So we need to take that away by training and by communicating um chris we're gonna add something to that >>and definitely I think the point that I have also made before right we need to acknowledge that data mesh is an architecture of scale, right? You're looking for something which is necessary by huge companies who are vulnerable, data productive scale. I mean Dave you mentioned it right, there are a lot of advantages to have a centralized team but at some point it may make sense to actually decentralized here and at this point right? If you think about data Mash, you have to recognize that you're not building something on a green field. And I think there's a big learning which is also reflected here on the slide is don't underestimate your baggage. It's typically you come to a point where the old model doesn't doesn't broke anymore and has had a fresh right? We lost our trust in our data and actually we have seen certain risks that we're slowing down our innovation so we triggered that this was triggering the need to actually change something. So this transition implies that you typically have a lot of technical debt accumulated over years and I think what we have learned is that potentially we have decentralized some assets to earlier, this is not actually taking into account the maturity of the team where we are actually distributed to and now we actually in the face of correcting pieces of that one. Right? But I think if you if you if you start from scratch you have to understand, okay, is are my team is actually ready for taking on this new uh, this news capabilities and you have to make sure that business decentralization, you build up these >>capabilities and the >>teams and as Clements has mentioned, right, make sure that you take the people on your journey. I think these are the pieces that also here, it comes with this knowledge gap, right? That we need to think about hiring and literacy the technical depth I just talked about and I think the last piece that I would add now which is not here on the flight deck is also from our perspective, we started on the analytical layer because that's kind of where things are exploding, right, this is the thing that people feel the pain but I think a lot of the efforts that we have started to actually modernize the current state uh, towards data product towards data Mash. We've understood that it always comes down basically to a proper shape of our operational plane and I think what needs to happen is is I think we got through a lot of pains but the learning here is this need to really be a commitment from the company that needs to happen and to act. >>I think that point that last point you made it so critical because I I hear a lot from the vendor community about how they're gonna make analytics better and that's that's not unimportant, but but through data product thinking and decentralized data organizations really have to operationalize in order to scale. So these decisions around data architecture an organization, their fundamental and lasting, it's not necessarily about an individual project are why they're gonna be project sub projects within this architecture. But the architectural decision itself is an organizational, its cultural and what's the best approach to support your business at scale. It really speaks to to to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data driven driven companies is yields tremendous results. So I'll ask each of you to give give us your final thoughts and then we'll wrap maybe >>maybe it quickly, please. Yeah, maybe just just jumping on this piece that you have mentioned, right, the target architecture. If we talk about these pieces right, people often have this picture of mind like OK, there are different kind of stages, we have sources, we have actually ingestion layer, we have historical transformation presentation layer and then we're basically putting a lot of technology on top of that kind of our target architecture. However, I think what we really need to make sure is that we have these different kind of viewers, right? We need to understand what are actually the capabilities that we need in our new goals. How does it look and feel from the different kind of personas and experience view? And then finally, that should actually go to the to the target architecture from a technical perspective um maybe just to give an outlook but what we're what we're planning to do, how we want to move that forward. We have actually based on our strategy in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data, cultural, data literacy, data organizational structure and so on that. We're talking about governance as Clements has actually mentioned that, right, compliance, governance, data management and so on. You talk about technology and I think we could talk for hours for that one. It's around data platform, better science platform and then finally also about enablement through data, meaning we need to understand that a quality data accessibility and the science and data monetization. >>Great, thank you christophe clement. Once you bring us home give us your final thoughts. >>Can't can just agree with christoph that uh important is to understand what kind of maturity people have to understand what the maturity level, where the company where where people organization is and really understand what does kind of some kind of a change replies to that those four pillars for example, um what needs to be taken first and this is not very clear from the very first beginning of course them it's kind of like Greenfield you come up with must wins to come up with things that we really want to do out of theory and out of different white papers. Um only if you really start conducting the first initiatives you do understand. Okay, where we have to put the starts together and where do I missed out on one of those four different pillars? People, process technology and governance. Right? And then that kind of an integration. Doing step by step, small steps by small steps not boiling the ocean where you're capable ready to identify the gaps and see where either you can fill um the gaps are where you have to increase maturity first and train people or increase your text text, >>you know Hello Fresh is an excellent example of a company that is innovating. It was not born in Silicon Valley which I love. It's a global company. Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? >>Yes, >>definitely. We do >>uh as many rights as was one of these aspects distributing. And actually we are hiring as an entire company specifically for data. I think there are a lot of open roles serious. Please visit or our page from better engineering, data, product management and Clemens has a lot of rules that you can speak about. But yes >>guys, thanks so much for sharing with the cube audience, your, your pioneers and we look forward to collaborations in the future to track progress and really want to thank you for your time. >>Thank you very much. Thank you very much. Dave >>thank you for watching the cubes startup showcase made possible by A W. S. This is Dave Volonte. We'll see you next time. >>Yeah.