(upbeat music) >> Hey everyone, welcome back to theCUBE live in Miami on the floor of IFS Unleashed. I'm your host, Lisa Martin. Had some great conversations. Have more great conversations coming your way. I have two guests joining me. Please welcome Martin Schirmer, the President of Enterprise Service Management, IFS Assyst. And Parminder Khosa, the Senior IT Manager at Parexel. Guys, it's great to have you on the program. >> Lovely to be here. >> It's good to be here. >> Martin, talk to me a little bit... tell the audience a little bit about Assyst so that that get that context before we start asking questions. >> Yeah. Absolutely. So IFS Assyst is a recent acquisition. It's an acquisition we made about a year ago. And fundamentally, it's a platform that takes care of IT service management, enterprise service management and IT operations management. So think of it, of managing sort of the ERP for IT and then broadening that out into the sort of enterprise where you're driving enterprise use cases for all lines of businesses like HR, finance, facilities, so on and so forth. >> Got it. And then Parminder, give the audience just a little bit of a flavor of Parexel, who you guys are, what you do. >> Sure. >> Maybe the impact that you make. >> Yeah, so Parexel is a clinical research organization. And what that means is that we manage drug trials for big pharmaceutical companies. So we're a big company. We're 25,000 people. We have offices in 150 locations all the way from Japan and the east through to the West Coast of the USA. >> Big company. >> Yeah, we are. We are a lot of people. >> And let's start chatting now Martin with some of the questions that you have so we get the understanding of how IFS and Parexel are working together. >> Yeah. Absolutely. I suppose... I mean the first thing is and thank you for traveling here all the way from the UK. (Lisa chuckles) Appreciate it and great energy and vibe. So just what the first question I had really was, you're customer of ours for the last 15 years plus. Maybe just give the audience a bit of context into your journey and how you've evolved from the sort of early years to where you're going into the future. >> Sure. So our history, I was part of a company that Parexel acquired that was already using Assyst. And as Parexel acquired us, they were in the process of also buying Assyst. So it became a kind of natural fit where I carried on with Assyst. And we started relatively small, sort of just the service desktop. And throughout the ongoing 15 years or so, we've just grown and expanded into kind of being a critical tool for Parexel right now. >> Okay, that's fantastic. I mean part of that journey, I know you started in sort of the more they call a ticketing space or IT service management space. Expand a little bit how you've expanded out of that and really moved into the enterprise. >> Sure. So yeah. So when we first rolled Assyst out, it was as I say, purely IT. And eventually we reached out to other business units to say asking questions like, Are you managing your workload through email? Are you managing your workload through Excel spreadsheets? In which case, if you are, we've got a solution for you that will make it a much better experience for your customers. They're all internal. It'll make it much easier for you because you will have official tracking going on through our system. I'll make it better for your management because we can drive metrics from all of the data that we're getting. So if you imagine finance we're getting, kind of 200 miles a day because of the size of our company. And they were just working through them one by one responding, and they becomes just a mess. So we developed forms for them to say, "Okay, Larry raise all your requests here. We will pick it up. We will manage it. We will communicate with you. And once the piece of work that you've asked for is done, we will let you know." And as we go through that process, we'll make it better for us because as I say we're getting those metrics. And we'll make it better for you because we can spot where our gaps are. If a request is taking three days, and of that three days, two days is waiting for someone on our end to respond to you or is waiting for us waiting for a customer to respond, we can iron those out and make it a much better experience for everyone. >> That's fantastic. It's really music to my ears because we always pushing the industry to say move away from just the IT side and really get into the enterprise. And it sounds like you've really gotten a lot of sort of productivity and efficiency gains out of that. >> Definitely, definitely. And it becomes kind of a happy circle. So the finance guys will work with the procurement guys. And they also look... Well, we're doing all of our work through Assyst now. So procurement's a little turnaround. So, well we're using this big spreadsheet to manage all of ours. Can we do the same? And they'll reach out to us and we'll say, "Of course we can. What is your process?" For example, they will say, okay, if someone asks for a new laptop, we need to get the approval from their line manager, from the supplier. We need to do our own internal work and then we will send it out. So imagine if you're doing that in a an email chain. It just becomes chaos. >> Yeah. >> So we will build all of that out for them. And then procurement will talk to HR and it just becomes a snowball. And before you know it, we are doing about 4,000 tickets per day in our Assyst system. And of those, 50% perhaps maybe more than 50% now will be non IT related. >> Oh, that's fantastic. Really music to my ears. And it really breaking down the boundaries or silos within an organization. It's really good. Let the teams work together. Right? >> Definitely. And that's one of the key things that we've learned is that we have to engage completely with our business partners. And our business partners are becoming more and more IT literate as well. So for example, we had a recent big HR solution provided to us. And as part of that, we know there are going to be questions, and queries and perhaps even issues to do with our HR system. So we have to work with us guys, the Assyst front end, the IT HR guys who look after the databases, all of the technology in the background. Then there'll be IT HR who are Workday experts. And then kind of not necessarily at the bottom of the chain will be the HR people themselves who are in their own way, experts in their area, experts in IT in a certain way. So all of those people have to work together. We become the front end, but we have to work with all of those parts of the business. >> That's really great. It's basically what you just said is taking business, IT processes and underpinning solutions. Effectively digital transformation, right? >> Exactly. Yeah. So HR is a great example. They used to have paper flying around with leave request, with sickness requests, with all of those kind of issues. And you said, well if you have an issue with your HR system, you can't raise a leave request, or you can't raise a sickness request, tell us. We will take care of it. We will fix it for you. We will give you the instructions. And we will get rid of all of that paper. >> That's brilliant. Just sort of turning the attention. And all of that, how do you drive the sort of, we'll talk about the autonomous enterprise. How do you drive automation in that process? >> Yeah. Of course, we have to map all of those processes out. Because we're not the experts in HR or procurement or whatever the business area may be. We have to really dig into their work methods, their working areas. What is necessary for them? What is a must have? What is a like to have? What is we don't really need? So we really drive into that processes. Once we've got those, we will automate them. We will build them out in Assyst with the process designer. It's very intuitive now. The latest version is really good to work with. We will do some pretty clever stuff in there. We'll say, okay the manager approval. If the manager is not there, then escalate it to the next person. Then we go to HR and say, okay HR have taken two days to do this. We're not particularly okay with that. So we will escalate it to the next person. And all of that process is completely automated, completely in Assyst. >> Brilliant. I mean obviously, we have a codeless workflow engine with a designer. And if you look at one of the trends from post covid is a war in talent in particular developers. The IDC says there's going to be around 4 million shortage of developers. What is your view on, how easy... Do I need developers? Is it easy, is it difficult to do these workflow extensions and automations? >> Definitely not, no. So the two key areas that you mentioned that with the customizer to develop the forms to make them available to our end users, drag and drop. Really easy to do. You can put some nice filters in there. You can put some nice variables in there. You can drive intelligent drive the forms from there as well. So if option A is correct, then don't show me option B, show me option C. And all of that is codeless, entirely codeless. I don't need to type any code. And when we move on to a process designer that hooks in nicely with the form customizer because we can say, "Okay, if option B on that form is selected, then runs this process." And all of that process is entirely codeless as well. Drag and drop. Creates some tasks. Create some decisions. >> Fantastic. >> Brilliant. >> Sounds really good. Switching gears a little bit. You spoke about experience, and that's also obviously very topical post, well, Covid becoming a remote workforce. Clearly, we need to be digitally connected to our business and organization because the hybrid workforce, as we all know, is here to stay. And that employee experience is fundamental because it is their sort of channel to the engagement of the organization. Of course, that has retention impacts and productivity impact. So just from your perspective, how was Covid, from your perspective, and how easy or difficult was it to get your employees engaged and productive and working? >> Yeah. And for us, it's a double edged sword Covid was. Because of the nature of our business. We do covid stuff. We do drug stuff. So we may have issues with some trials that are related to that. So we need to escalate those. We need to be aware of them and move them to the top of the chain as soon as possible. And then Assyst becomes a source of truth. Everybody knows that if I've got an issue with the current environment that we're living in, I can raise it in Assyst. And everybody knows that's where that information is. There's no need to have huge conference calls or huge email chains to try and follow those around. So with our Assyst platform, with our employees as well, everybody knew that this is where the source of truth was. We didn't have any dropouts. We didn't have any concerns with our system or performance. We knew it was there. We had to do some work like, as I say, around covid issues just to make sure they get pushed up to the top of the chain. But otherwise, we were fine. And great credit to our IT operations team as well who managed that pretty much seamlessly. >> That's brilliant. That's good news. >> Yeah. >> It really is. Just taking a little bit further and talking a little bit about what next. My team has been, I know, talking to your team about the whole area of asset management. Maybe talk to us a little bit about that journey. >> Sure, sure. So we're an ITOM customer as well. So all of our hardware data is stored within the ITOM platform. So we've pushed out the agents to all of our end user machines, so 25,000 agents. And we're in the process of integrating that into our Assyst platform to make that the single source of truth. And that part of that we're working on the software asset management side as well. So we've got a really good idea of where our software assets are. It comes to all license auditing, we know exactly how much we've got there. And the more complex side of it is of course server. So software management management as well. So we're in the process of getting all of that data as well. So once we've done all that, there is other all as the next step. The next step will be to perhaps do monitoring or pushing out software using the ITOM platform and getting rid of some of the disparate systems that we have right now. >> Well that's good news. And I think I saw a study. I think, every single person as an employee carries around 15 or 20 assets with him at any one time. Be it from a PC, phone, physical software licenses, so on and so forth. In that context, I can imagine the business case around it. >> Definitely. Yeah. And every, again, we map every user to their assets and (indistinct) their assets. And again Assyst as a source of truth for that. So if you want to look at my record, so, all right. Pam's got a laptop. He's got a mobile phone. We're thinking about giving him a tablet, but we'll find out. That he's in the process of getting a tablet as well. So I can have a look at my user record and know exactly what I've got with all of the asset tags and the various links that it has to the software pieces so it becomes a big tree of my assets. >> That's wonderful. Just the question I had was, we spoke about breaking down silos and the enterprise use cases and the effect that has. Do you envisage that Assyst can really get to being enterprisewide as, when I say enterprisewide, everybody in the organization effectively using this tool as their sort of source of experience, and level of automation of process? >> Definitely, definitely. As I say, we're getting... We're really pushing to get to that. As I say, 4,000 tickets a day with a user base of 25,000 kind of means that everybody will interact with the system perhaps every two weeks or so. So we're getting to that point and with the new functionality that's coming out with the Assyst product, with the team's integration, and the bot and everything that will bring to us because we are a big. We use teams. We use bots. We use that kind of technology. It will just fit in seamlessly. And trying to break down the silos, as I say finance, procurement, all of the big beasts within our company already are using the Assyst tool. And we want to bring in more and more of those processes as we mature. >> Brilliant. I think Omnichannel's critical. We want to connect from any device from anywhere. It's just the way we work. So I think that's critical. Teams is of course a a tool that most of us have become too familiar with. >> Yup. (chuckles) >> To be fair. (chuckles) It's better to be here in person finally, right? >> Yeah. >> So I think, that's all exciting news. And it's really fantastic. >> Great. >> So I suppose maybe in the time that we have left, what's next? >> What's next for us is that we're in the process of migrating our solution to the cloud, to the IFS cloud. That will open up a huge new user base for us. If we think all of our customers, all of our people who work on studies will have the ability to connect to Assyst and ask questions. That's a lot of it is just ask a question, or raise an issue or ask for something. So we're talking, it could be expanded by hundreds of thousands of new users that will meet more people on the backend to manage those requests as well. So yeah. It's just going to get bigger and bigger. And as you say, with the CMDB work that we're doing as well, that's another big ongoing stream for us. >> It's great because as you know, with Assyst we have a disruptive licensing model. >> Yeah. >> We have a t-shirt size pricing. All you can need based a number of employees. So there's no barriers to entry for you. >> There really is. And that really helps us because as I said initially, particularly when finance came on board and now they're expanding, there is no cost implication for it. The more that we use it, the better it is for. The more bang for buck that we get. >> Yep. That's our mantra. Enterprise users, right? For the price of a cup of coffee, for the price of a user. That's our mantra. >> I love it. You guys have done such a great job of articulating the synergies in the relationship that IFS Assyst has with Paraxel. You talked about the great outcomes that you're achieving. And it's all about Martin, I know, from IFS Assyst perspective, it's all about helping customers achieve those outcomes and those moments of service that are so critical to your customers on the other end staying with you, doing more business. Whether it's the end user customer, whether it's the actual employee. You talked a lot about the customer experience, the employee experience, and what you guys are doing together to enable that. And I always think that the employee experience and the customer experience are like this. They're inextricably linked. You can't, you shouldn't. Otherwise you're going to have problems. >> Yeah, no, absolutely. And there's actually a study on that saying that, 70% of customers generally don't feel they get what they want from organizations. >> 70. Wow! >> And if you take that one step further to what you said, the interconnectivity between customer employee, employee shops on Amazon, right? It's on those websites. So you can't be rolling out and digitally connect to the employee with something that is clunky and has the wrong experience. Like I said, it really affects that level of engagement the employee has with the company which happens to be largely these days remote. >> It does. Last question Martin, is for you. Talk to us about what's next for IFS Assyst. Obviously, we're back in person. There's a lot of momentum about the company. I was talking with Darren, the growth and first half was great. He kind of gave us some teaser about second half, but what's next from your perspective? >> Yeah. So what's next for us is achieving our goal. We are here to disrupt the industry. It's an industry that's dominated by one player and a fair amount of legacy players. We've disrupted the business model as I've told you. We here to do more because it's a simple thing. And that's the word simple. We want to keep things simple. We're going to keep engineering and driving our product forward, right? We've made sure that our platform is up there with the best. Yeah. We've just been certified by pink. Pink is a verification of ITIL four they call it. So it's a body. And the top level is you can get 20 out of 20. We got 17 out of 20. There's only one other vendor that has more than us and it's only by little. And after it's a big white space, the next one is 14. So we on the right track. We are going to of course drive and capture the market. So watch this space. We here to grow. >> We will watch this space. Congratulations on being that disrupter. >> Thank you. >> Parminder great work with what you guys are doing. You did a great job of articulating, as I said, the customers tour here. We appreciate your insights, your time. >> Thank you very much. >> Pleasure. >> All right, my pleasure. >> Thank you. For my guests, I'm Lisa Martin. You're watching The Cube live from Miami on the show floor of IFS Unleashed. We'll be back after a short break.

(upbeat music) >> Welcome back to Boston, everybody. This is the birthplace of theCUBE. In 2010, May of 2010 at EMC World, right in this very venue, John Furrier called it the chowder and lobster post. I'm Dave Vellante. We're here at RE:INFORCE 2022, Ed Walsh, CEO of ChaosSearch. Doing a drive by Ed. Thanks so much for stopping in. You're going to help me wrap up in our final editorial segment. >> Looking forward to it. >> I really appreciate it. >> Thank you for including me. >> How about that? 2010. >> That's amazing. It was really in this-- >> Really in this building. Yeah, we had to sort of bury our way in, tunnel our way into the Blogger Lounge. We did four days. >> Weekends, yeah. >> It was epic. It was really epic. But I'm glad they're back in Boston. AWS was going to do June in Houston. >> Okay. >> Which would've been awful. >> Yeah, yeah. No, this is perfect. >> Yeah. Thank God they came back. You saw Boston in summer is great. I know it's been hot, And of course you and I are from this area. >> Yeah. >> So how you been? What's going on? I mean, it's a little crazy out there. The stock market's going crazy. >> Sure. >> Having the tech lash, what are you seeing? >> So it's an interesting time. So I ran a company in 2008. So we've been through this before. By the way, the world's not ending, we'll get through this. But it is an interesting conversation as an investor, but also even the customers. There's some hesitation but you have to basically have the right value prop, otherwise things are going to get sold. So we are seeing longer sales cycles. But it's nothing that you can't overcome. But it has to be something not nice to have, has to be a need to have. But I think we all get through it. And then there is some, on the VC side, it's now buckle down, let's figure out what to do which is always a challenge for startup plans. >> In pre 2000 you, maybe you weren't a CEO but you were definitely an executive. And so now it's different and a lot of younger people haven't seen this. You've got interest rates now rising. Okay, we've seen that before but it looks like you've got inflation, you got interest rates rising. >> Yep. >> The consumer spending patterns are changing. You had 6$, $7 gas at one point. So you have these weird crosscurrents, >> Yup. >> And people are thinking, "Okay post-September now, maybe because of the recession, the Fed won't have to keep raising interest rates and tightening. But I don't know what to root for. It's like half full, half empty. (Ed laughing) >> But we haven't been in an environment with high inflation. At least not in my career. >> Right. Right. >> I mean, I got into 92, like that was long gone, right?. >> Yeah. >> So it is a interesting regime change that we're going to have to deal with, but there's a lot of analogies between 2008 and now that you still have to work through too, right?. So, anyway, I don't think the world's ending. I do think you have to run a tight shop. So I think the grow all costs is gone. I do think discipline's back in which, for most of us, discipline never left, right?. So, to me that's the name of the game. >> What do you tell just generally, I mean you've been the CEO of a lot of private companies. And of course one of the things that you do to retain people and attract people is you give 'em stock and it's great and everybody's excited. >> Yeah. >> I'm sure they're excited cause you guys are a rocket ship. But so what's the message now that, Okay the market's down, valuations are down, the trees don't grow to the moon, we all know that. But what are you telling your people? What's their reaction? How do you keep 'em motivated? >> So like anything, you want over communicate during these times. So I actually over communicate, you get all these you know, the Sequoia decks, 2008 and the recent... >> (chuckles) Rest in peace good times, that one right? >> I literally share it. Why? It's like, Hey, this is what's going on in the real world. It's going to affect us. It has almost nothing to do with us specifically, but it will affect us. Now we can't not pay attention to it. It does change how you're going to raise money, so you got to make sure you have the right runway to be there. So it does change what you do, but I think you over communicate. So that's what I've been doing and I think it's more like a student of the game, so I try to share it, and I say some appreciate it others, I'm just saying, this is normal, we'll get through this and this is what happened in 2008 and trust me, once the market hits bottom, give it another month afterwards. Then everyone says, oh, the bottom's in and we're back to business. Valuations don't go immediately back up, but right now, no one knows where the bottom is and that's where kind of the world's ending type of things. >> Well, it's interesting because you talked about, I said rest in peace good times >> Yeah >> that was the Sequoia deck, and the message was tighten up. Okay, and I'm not saying you shouldn't tighten up now, but the difference is, there was this period of two years of easy money and even before that, it was pretty easy money. >> Yeah. >> And so companies are well capitalized, they have runway so it's like, okay, I was talking to Frank Slootman about this now of course there are public companies, like we're not taking the foot off the gas. We're inherently profitable, >> Yeah. >> we're growing like crazy, we're going for it. You know? So that's a little bit of a different dynamic. There's a lot of good runway out there, isn't there? >> But also you look at the different companies that were either born or were able to power through those environments are actually better off. You come out stronger in a more dominant position. So Frank, listen, if you see what Frank's done, it's been unbelievable to watch his career, right?. In fact, he was at Data Domain, I was Avamar so, but look at what he's done since, he's crushed it. Right? >> Yeah. >> So for him to say, Hey, I'm going to literally hit the gas and keep going. I think that's the right thing for Snowflake and a right thing for a lot of people. But for people in different roles, I literally say that you have to take it seriously. What you can't be is, well, Frank's in a different situation. What is it...? How many billion does he have in the bank? So it's... >> He's over a billion, you know, over a billion. Well, you're on your way Ed. >> No, no, no, it's good. (Dave chuckles) Okay, I want to ask you about this concept that we've sort of we coined this term called Supercloud. >> Sure. >> You could think of it as the next generation of multi-cloud. The basic premises that multi-cloud was largely a symptom of multi-vendor. Okay. I've done some M&A, I've got some Shadow IT, spinning up, you know, Shadow clouds, projects. But it really wasn't a strategy to have a continuum across clouds. And now we're starting to see ecosystems really build, you know, you've used the term before, standing on the shoulders of giants, you've used that a lot. >> Yep. >> And so we're seeing that. Jerry Chen wrote a seminal piece on Castles in The Cloud, so we coined this term SuperCloud to connote this abstraction layer that hides the underlying complexities and primitives of the individual clouds and then adds value on top of it and can adjudicate and manage, irrespective of physical location, Supercloud. >> Yeah. >> Okay. What do you think about that concept?. How does it maybe relate to some of the things that you're seeing in the industry? >> So, standing on shoulders of giants, right? So I always like to do hard tech either at big company, small companies. So we're probably your definition of a Supercloud. We had a big vision, how to literally solve the core challenge of analytics at scale. How are you going to do that? You're not going to build on your own. So literally we're leveraging the primitives, everything you can get out of the Amazon cloud, everything get out of Google cloud. In fact, we're even looking at what it can get out of this Snowflake cloud, and how do we abstract that out, add value to it? That's where all our patents are. But it becomes a simplified approach. The customers don't care. Well, they care where their data is. But they don't care how you got there, they just want to know the end result. So you simplify, but you gain the advantages. One thing's interesting is, in this particular company, ChaosSearch, people try to always say, at some point the sales cycle they say, no way, hold on, no way that can be fast no way, or whatever the different issue. And initially we used to try to explain our technology, and I would say 60% was explaining the public, cloud capabilities and then how we, harvest those I guess, make them better add value on top and what you're able to get is something you couldn't get from the public clouds themselves and then how we did that across public clouds and then extracted it. So if you think about that like, it's the Shoulders of giants. But what we now do, literally to avoid that conversation because it became a lengthy conversation. So, how do you have a platform for analytics that you can't possibly overwhelm for ingest. All your messy data, no pipelines. Well, you leverage things like S3 and EC2, and you do the different security things. You can go to environments say, you can't possibly overrun me, I could not say that. If I didn't literally build on the shoulders giants of all these public clouds. But the value. So if you're going to do hard tech as a startup, you're going to build, you're going to be the principles of Supercloud. Maybe they're not the same size of Supercloud just looking at Snowflake, but basically, you're going to leverage all that, you abstract it out and that's where you're able to have a lot of values at that. >> So let me ask you, so I don't know if there's a strict definition of Supercloud, We sort of put it out to the community and said, help us define it. So you got to span multiple clouds. It's not just running in each cloud. There's a metadata layer that kind of understands where you're pulling data from. Like you said you can pull data from Snowflake, it sounds like we're not running on Snowflake, correct? >> No, complimentary to them in their different customers. >> Yeah. Okay. >> They want to build on top of a data platform, data apps. >> Right. And of course they're going cross cloud. >> Right. >> Is there a PaaS layer in there? We've said there's probably a Super PaaS layer. You're probably not doing that, but you're allowing people to bring their own, bring your own PaaS sort of thing maybe. >> So we're a little bit different but basically we publish open APIs. We don't have a user interface. We say, keep the user interface. Again, we're solving the challenge of analytics at scale, we're not trying to retrain your analytics, either analysts or your DevOps or your SOV or your Secop team. They use the tools they already use. Elastic search APIs, SQL APIs. So really they program, they build applications on top of us, Equifax is a good example. Case said it coming out later on this week, after 18 months in production but, basically they're building, we provide the abstraction layer, the quote, I'm going to kill it, Jeff Tincher, who owns all of SREs worldwide, said to the effect of, Hey I'm able to rethink what I do for my data pipelines. But then he also talked about how, that he really doesn't have to worry about the data he puts in it. We deal with that. And he just has to, just query on the other side. That simplicity. We couldn't have done that without that. So anyway, what I like about the definition is, if you were going to do something harder in the world, why would you try to rebuild what Amazon, Google and Azure or Snowflake did? You're going to add things on top. We can still do intellectual property. We're still doing patents. So five grand patents all in this. But literally the abstraction layer is the simplification. The end users do not want to know that complexity, even though they ask the questions. >> And I think too, the other attribute is it's ecosystem enablement. Whereas I think, >> Absolutely >> in general, in the Multicloud 1.0 era, the ecosystem wasn't thinking about, okay, how do I build on top and abstract that. So maybe it is Multicloud 2.0, We chose to use Supercloud. So I'm wondering, we're at the security conference, >> RE: INFORCE is there a security Supercloud? Maybe Snyk has the developer Supercloud or maybe Okta has the identity Supercloud. I think CrowdStrike maybe not. Cause CrowdStrike competes with Microsoft. So maybe, because Microsoft, what's interesting, Merritt Bear was just saying, look, we don't show up in the spending data for security because we're not charging for most of our security. We're not trying to make a big business. So that's kind of interesting, but is there a potential for the security Supercloud? >> So, I think so. But also, I'll give you one thing I talked to, just today, at least three different conversations where everyone wants to log data. It's a little bit specific to us, but basically they want to do the security data lake. The idea of, and Snowflake talks about this too. But the idea of putting all the data in one repository and then how do you abstract out and get value from it? Maybe not the perfect, but it becomes simple to do but hard to get value out. So the different players are going to do that. That's what we do. We're able to, once you land it in your S3 or it doesn't matter, cloud of choice, simple storage, we allow you to get after that data, but we take the primitives and hide them from you. And all you do is query the data and we're spinning up stateless computer to go after it. So then if I look around the floor. There's going to be a bunch of these players. I don't think, why would someone in this floor try to recreate what Amazon or Google or Azure had. They're going to build on top of it. And now the key thing is, do you leave it in standard? And now we're open APIs. People are building on top of my open APIs or do you try to put 'em in a walled garden? And they're in, now your Supercloud. Our belief is, part of it is, it needs to be open access and let you go after it. >> Well. And build your applications on top of it openly. >> They come back to snowflake. That's what Snowflake's doing. And they're basically saying, Hey come into our proprietary environment. And the benefit is, and I think both can win. There's a big market. >> I agree. But I think the benefit of Snowflake's is, okay, we're going to have federated governance, we're going to have data sharing, you're going to have access to all the ecosystem players. >> Yep. >> And as everything's going to be controlled and you know what you're getting. The flip side of that is, Databricks is the other end >> Yeah. >> of that spectrum, which is no, no, you got to be open. >> Yeah. >> So what's going to happen, well what's happening clearly, is Snowflake's saying, okay we've got Snowpark. we're going to allow Python, we're going to have an Apache Iceberg. We're going to have open source tooling that you can access. By the way, it's not going to be as good as our waled garden where the flip side of that is you get Databricks coming at it from a data science and data engineering perspective. And there's a lot of gaps in between, aren't there? >> And I think they both win. Like for instance, so we didn't do Snowpark integration. But we work with people building data apps on top of Snowflake or data bricks. And what we do is, we can add value to that, or what we've done, again, using all the Supercloud stuff we're done. But we deal with the unstructured data, the four V's coming at you. You can't pipeline that to save. So we actually could be additive. As they're trying to do like a security data cloud inside of Snowflake or do the same thing in Databricks. That's where we can play. Now, we play with them at the application level that they get some data from them and some data for us. But I believe there's a partnership there that will do it inside their environment. To us they're just another large scaler environment that my customers want to get after data. And they want me to abstract it out and give value. >> So it's another repository to you. >> Yeah. >> Okay. So I think Snowflake recently added support for unstructured data. You chose not to do Snowpark because why? >> Well, so the way they're doing the unstructured data is not bad. It's JSON data. Basically, This is the dilemma. Everyone wants their application developers to be flexible, move fast, securely but just productivity. So you get, give 'em flexibility. The problem with that is analytics on the end want to be structured to be performant. And this is where Snowflake, they have to somehow get that raw data. And it's changing every day because you just let the developers do what they want now, in some structured base, but do what you need to do your business fast and securely. So it completely destroys. So they have large customers trying to do big integrations for this messy data. And it doesn't quite work, cause you literally just can't make the pipelines work. So that's where we're complimentary do it. So now, the particular integration wasn't, we need a little bit deeper integration to do that. So we're integrating, actually, at the data app layer. But we could, see us and I don't, listen. I think Snowflake's a good actor. They're trying to figure out what's best for the customers. And I think we just participate in that. >> Yeah. And I think they're trying to figure out >> Yeah. >> how to grow their ecosystem. Because they know they can't do it all, in fact, >> And we solve the key thing, they just can't do certain things. And we do that well. Yeah, I have SQL but that's where it ends. >> Yeah. >> I do the messy data and how to play with them. >> And when you talk to one of their founders, anyway, Benoit, he comes on the cube and he's like, we start with simple. >> Yeah. >> It reminds me of the guy's some Pure Storage, that guy Coz, he's always like, no, if it starts to get too complicated. So that's why they said all right, we're not going to start out trying to figure out how to do complex joins and workload management. And they turn that into a feature. So like you say, I think both can win. It's a big market. >> I think it's a good model. And I love to see Frank, you know, move. >> Yeah. I forgot So you AVMAR... >> In the day. >> You guys used to hate each other, right? >> No, no, no >> No. I mean, it's all good. >> But the thing is, look what he's done. Like I wouldn't bet against Frank. I think it's a good message. You can see clients trying to do it. Same thing with Databricks, same thing with BigQuery. We get a lot of same dynamic in BigQuery. It's good for a lot of things, but it's not everything you need to do. And there's ways for the ecosystem to play together. >> Well, what's interesting about BigQuery is, it is truly cloud native, as is Snowflake. You know, whereas Amazon Redshift was sort of Parexel, it's cobbled together now. It's great engineering, but BigQuery gets a lot of high marks. But again, there's limitations to everything. That's why companies like yours can exist. >> And that's why.. so back to the Supercloud. It allows me as a company to participate in that because I'm leveraging all the underlying pieces. Which we couldn't be doing what we're doing now, without leveraging the Supercloud concepts right, so... >> Ed, I really appreciate you coming by, help me wrap up today in RE:INFORCE. Always a pleasure seeing you, my friend. >> Thank you. >> All right. Okay, this is a wrap on day one. We'll be back tomorrow. I'll be solo. John Furrier had to fly out but we'll be following what he's doing. This is RE:INFORCE 2022. You're watching theCUBE. I'll see you tomorrow.

(upbeat music) >> Welcome back everyone, theCUBE's three days of wall to wall coverage of Snowflake Summit '22 is coming to an end, but Dave Vellante and I, Lisa Martin are so pleased to have our final guest as none other than the co-founder and president of products at Snowflake, Benoit Dageville. Benoit, thank you so much for joining us on the program. Welcome. >> Thank you. Thank you, thank you. >> So this is day four, 'cause you guys started on Monday. This is Thursday. The amount of people that are still here speaks volumes. We've had close to 10,000 people here. >> Yeah. >> Could you ever have imagined back in the day, 10 years ago that it would come to something like this in such a short period of time? >> Absolutely not. And I always say if I had imagined that I might not have started Snowflake, right. This is somehow scary. I mean and yeah, it's huge. And you can feel the excitement of everyone. It is like mind boggling and the fact that so many people are still there after four days is great. >> Your keynote on Tuesday was fantastic. Your energy was off the charts. It was standing room only. There were overflow rooms. Like we just mentioned, a lot of people are still here. Talk about the evolution of Snowflake, this week's announcements and what it means for the future of the data cloud. >> Yeah, so evolution, I mean, I will start with the evolution. It's true that that's what we have announced. This week is not where we started necessarily. So we started really very quickly with big data combined with data warehouse as one thing. We saw that the world was moving into fragmented siloing data and we thought with Thierry, we are going to combine big data and data warehouse in one system for the cloud with this elasticity and this service simplicity. So simplicity, amazing elasticity, which is this multi workload architecture that I was explaining during the keynotes and really extreme simplicity with the service. Then we realized that there is one other attribute in the cloud, which is unique, which doesn't exist on-premise, which is collaboration. How you can connect different tenets of the platform together. And Google showed that with Google Docs. I always say to me, it was amazing that you could share document and have direct access to document that you didn't produce and you can collaborate on this document. So we wanted to do the same thing for data and this is where we created the data cloud and the marketplace where you can have all these data sets available and really the next evolution I would say is really about applications that are (indistinct) by that data, but are way simpler to use for all the tenets of the data cloud. And this is the way you can share expertise also, including, ML model, everyone talks about ML and the democratization of ML. How are you going to democratize ML? It's not by making necessary training super easy. Such that everyone can train their ML for themselves. It's by having very specialized application where data and ML is at the core, which are shared, through the marketplace and we shall leverage by many tenets of this marketplace that have no necessary knowledge about building this ML models. So that's where, yeah. >> When you and Thierry started the company, I go back to the improbable rise of Kubernetes and there were other more sophisticated container management systems back then, but they chose to focus on simplicity. And you've told me before, that was our main tenet. We are not going to worry about all the complex database stuff. You knew how to do that, but you chose not to. So my question is, did you envision solving those complex problems over time yourselves or through an ecosystem? Was this by design or did you... As you started to get into it, say let's not even try to go there let's partner to go there. >> Yeah, I mean, it's both. It's a combination of both. Snowflake, the simplicity of the platform is really important because if our partners are struggling to put their solution and build solution on top of Snowflake they will not build it. So it's very important that number one, our platform is really easy to use from day one. And that really has to be built inside the platform. You cannot build simplicity on top. You cannot have a complex solution and all of a sudden realize that, oh, this is complex. I need to build another layer on top of it to make it simpler, that will not work. So it had to be built from day one, but you're right. What is going to be Snowflake? I always say in 10 years from now, we just turn 10 years old or we are going to turn 10 years old in few months. Actually a few months, yes. >> Right. >> So for the next 10 years I really believe that most of Snowflake will not be built by Snowflake. And that's the power of the partners and these applications. When you are going to say I'm using Snowflake, actually, probably you are not going to use directly code developed by Snowflake. That code will leverage our platform, but you will use a solution that has been built on top of Snowflake. And this is the way we are going to decouple, the effort of Snowflake and multiply it. >> It's an interesting balance, isn't it? When I think of what you did with Apache Iceberg, if I use Iceberg and I'm not going to get as much functionality, but I may want that openness, but I'm going to get more functionality inside of the data cloud. And I don't know, but if you know the answer to what's going to happen. >> No, that's a super good question. So to explain what we did with Apache Iceberg, and the fact that now it's a native format for us. So everything that you can do with our internal formats, you can do it with Apache Iceberg, including security, defining masking, data masking all the governors that we have, fine grain security aspects, the replications you can define you can use (indistinct) on top of... >> But there's a but, right? But if I do that with native Snowflake tools, I'm going to get an even greater advantage, am I not? >> Yes. So that's what I'm saying. So that's why we embraced Iceberg, because I think we can bring all the benefit of Snowflake to people who have decided to use Iceberg, I mean open formats. Iceberg is a table format. So and why it was important because people had massive investments in open source in Hadoop. And we had a lot of companies saying, we love Snowflake. We want to be a Snowflake customer, but we cannot really migrate all our data. I mean, it will be really costly. And we have a lot of tools that need access, direct access. So this is why we created Iceberg because we can really... I mean, we really think that we can bring the benefit of Snowflake to this data. >> Gives customers optionality. Okay. I use this term super cloud. You don't use the term, but that's okay. And I get a lot of heat for it. But to me, what you're doing is quite a bit different than multicloud because you're creating that abstraction layer. You're bringing value above it. My question to you is, the most of the heat I get is, oh, that's just SaaS. Are you just SaaS? >> No. I mean, no, absolutely not. I mean, you're right we are a super cloud. I mean it's a much better word than saying we are multicloud. Multicloud is often viewed as oh, I have my system and now I can run this system in the different cloud providers. Snowflake is different. We have one single platform for the world, which happens to have some regions are AWS region, some regions are Azure, some regions are GCP, Google and we merge them together. We have this Snowgrid technology that connects all our regions together so that we have really one platform for the world. And that's very important because when you talk about connections of data and expertise applications you want to have global reach, right. It doesn't exist. We are not siloed by region of the world, right? You have a lot of companies which are multinational that have presence everywhere. And you want to have this global reach. The world is not a independent set of regions and countries, right. And that's the realization. So we had to create this global platform for our customers. >> And now you have people building clouds on top of your data cloud, well that to me is the next signal. In your keynote, you talked about seven pillars, all data, all workloads, global architecture, self-managed, programmable, marketplace, governance, which ones are the most important? >> All of them. It's like when you have kids, you don't want to pick and say, this one is my preferred one, so they are really important. All of them, as I said without data, there is no Snowflake, right? So all data is so important that we can reach every data, wherever it is. And Iceberg is a part of that, but all workload is really important because you don't want to put your data in one platform, if you cannot run all your workloads and workloads are much broader than just data warehousing, there is data engineering, data science, ML engineering, (indistinct) all these workloads applications. So that's critical. Programmable is where we are moving, right. We want to be the place where data applications are built. And we think we have a lot of advantages because data application needs to use many workloads at once, right? It's not that that application will do only data warehousing, they need to store their states, they need to use this new workload that we define, which is Unistore. They need to do data engineering because they need to get data, right. They have to save this data. So they need to combine many workload and if they have to stitch this workload, because the platform was not designed as one single product where everything is consistent and works together, that you have to stitch, it's complicated for this application to make it work. So Snowflake is we believe an ideal platform to run these data applications. So all workloads, programmable, obviously, so that you can program. And programmable has two aspects, which is big part of our announcement. Is both data programmability, which is running Python against petabyte, terabytes of data at scale and doing it scale out. So that's what we call data programmability. So both Java, Python and (indistinct), but also running applications like UI. And we had this acquisition of Streamlit. Streamlit now has been fully integrated in Snowflake. We announced that such that not only you can have this data programmability, but you can expose your data through this nice UIs, interactive UI to business users potentially. So it goes all the way there. Global is super important. As we say, we want to be one platform for the world. And of course, as I said, the last pillar, which is somehow critical for us, because we are cloud, we need to have governance. We need to have security of our data. And why it took us so long to do Python is not because it's out to run Python, right? Everyone can run Python it's because we had to secure it. And I talk about it creating this amazing sandboxing technology, such that when you include third party libraries and third party codes, you are guaranteed that this third party code will not reach to infiltrate your data, right. We control the environment that Snowflake provides. >> Can you share us some of the feedback from the customer? You probably had many customer conversations over the last four days. >> Look at that smile. (interviewer laughing) (Lisa laughing) >> Actually not because I was so busy everywhere. Unfortunately, I didn't speak to many customers. Saying that, I had everyone stopping me and talking about what they heard and yeah, there is a huge excitement about all of this. >> What's been the feedback around the theme of the event? The world of data collaboration. Data collaboration is so critical as every company these days must be a data company to compete, to win. What's been from just some of the feedback that you've had customers really embracing data collaboration, what Snowflake is enabling. >> Yeah. I mean, almost every company which is using Snowflake, is collaborating with data. You have heard, the number of stable edges that we have, and there is a real need for that because your data alone... You cannot make sense of your data if it is just alone. It needs to be connected with other data. You haven't not generated. So all data, when you say the first pillar of Snowflake is all data is not only about your data, but is about all the data that's created around you. That puts perspective on your own data. And that's critical and it's so painful to get. I mean, even your data is difficult to have access to your data, but imagine data that you didn't produce. And so yes, so the data collaboration is critical, and then now we expanded it to application and expertise, sharing models, for example, That's going to have a huge impact. >> All data includes now transaction data, right? >> Yes. >> That's a big part of the announcements that you guys made. >> Yeah. So and that's the motivation for that was really, if we want to run application, full application, we announced native applications, which are fully executed and run inside the (indistinct) data cloud, right. They need all the services that application need and in particular managing their states. And so we created Unistore, which is a new workload, which allows you to combine transactional data, which are generated by this application. And at the same time being able to do analytics directly on this data. So we call it Hybrid Table because it has this hybrid aspect. You can do both transactional access to this data and at the same time analytic here without having data pipeline and moving data and transforming it from the transactional system to the analytical system, right. Snowflake is one system. Again, in the spirit of simplifying everything, this is the Snowflake (indistinct). >> I can ask the same question I ask at first, (indistinct) when was the aha moment that you and Thierry had that said, this is not just a better data warehouse, it's actually more than that. You probably didn't call it a data cloud until later on, but did you know that from the beginning or was that something you kind of stumbled into? >> No. So as I said, we founded Snowflake in 2012 and Thierry and I, we locked in my apartment and we were doing the blueprint of Snowflake and trying to find what is the revolution with the cloud for this data warehouse system and analytical system, both big data and data warehouse. And the aha moment was but of course cloud, okay. What is cloud? It's elasticity, it's service and later collaboration. So in the elasticity aspect, when you ask database people, what is elasticity, they will tell you, oh, you have a cluster of nodes. Like if it is Oracle, it would be a (indistinct) cluster. And the elasticities that you can add one node, two node to this cluster without having too much impact on the existing workload, because you need to shuffle data, right. It's hard and doing it online, right, that's elasticity. If you can do that, you are elastic. We thought that that was not very interesting to do that. What is interesting with elasticity is to plug new workloads. You can plug a workload like that and that workload is running without having any impact on other workloads, which are running on the platform. So elasticity for us was having dedicated computer resources to workloads. And these computer resources could start and be part as soon as the workload starts and will shut down when the workload finishes and they will be sized exactly for the demand of that workload. And we thought the aha moment was, okay if we can do that, now we can run a workload with, let's say 10X more computer resources than what you would have used or 100X more. Okay, let's say 100X more because we paralyzed things. Now this workload can run 100X faster, right? That's assuming we do a good job in the scale, which is our IP. And if we can do that, now the computer resources that you have used, you have used them for 100 times less. So you have used 100 times more resources because you have more nodes, but because you go fast, you use them for less time, right? So if you multiply the two it's constant. So you can run and accelerate workload dramatically 10X, 100X for the same price. Even if we are not better in efficiency than competition, just having that was the magic, right? >> You know how Google founders originally had trouble raising money because who needs another search engine? Did you get from original, like when you started going to raise money, Amazon's got a database, so who needs another cloud database? Did you get that early on or was it just obvious Speiser and companies as well. >> Speiser is a little bit on the crazy side and ambitious and so Speiser is Speiser. And of course he had no doubt, but even him was saying Benoit, Thierry, Hadoop, right. Everyone is saying Hadoop is going to be the revolution. And you guys are betting actually against Hadoop because we told Speiser, Hadoop is a bad system, it's going to fail, but at the time everyone was so bullish about Hadoop, everyone was implementing Hadoop that it didn't look like it was going to fail and we were probably wrong. So there was a lot of skepticism about not leveraging Hadoop and not being an Hadoop. Okay, something being on top of Hadoop. That was number one. There was no cloud warehouse at the time we started. Redshift was not started. It was the pioneer somewhere when Snowflake was founded. So creating a data warehouse in the cloud sounded crazy to people. How am I going to move my data over there? And security and what about security, the cloud is not secure. So that was another... >> So you guys predated that Parexel move by... >> Yes. >> Okay, so that's interesting. And I thought when Redshift... I mean, Amazon announced Redshift, I was sure that Mike Speiser will come and say, guys it's too sad, but they beat you guys and they build something and actually it was the reverse. Mike Speiser was super excited and so it was interesting to me. >> Wow, that's amazing. 'Cause John Furrier and I, we were early with theCUBE. when theCUBE started it was like the beginning of Hadoop. And so we brought theCUBE to, I think it was the second Hadoop World and we was rubbing nickels together at the time. And I was so excited bring compute to storage and it made so much sense. But I remember and I won't say who it was, but an early Hadoop committer told me this is going to fail. And I'm like, what? And he started going age basis crap and all this stuff. And I was sad because I was so excited, but it turned out that you had the same (indistinct). >> Because of complexity. Okay, Hadoop failed for two reasons. One is because they decided that, oh, a lot of this database thing, you don't need transaction, you don't need SQL, you don't necessarily, you don't need to go fast. It'll be batch, normal real time interaction with data, no one needs that. >> Cheap storage. >> So a lot of compromise on the very important technology. And at the same time, extreme complexity and complexity for me was, where I was I knew that it was going to fail big time and we bet Snowflake on the failure of Hadoop indeed. >> And there was no cloud early on in Hadoop. >> And there was no cloud too. >> And that was what killed it. That was like... >> You're right. And the model that Hadoop had for data didn't work on block storage. Block storage is not as efficient as HGFS. So that was also another figure. >> Do you ever sit back and think about... So you think about how much money has poured in to separating compute from storage and cloud databases and you started it all. (interviewer laughing) >> Yeah. No, this is... >> Pretty amazing. >> Yeah. >> Right, so that's good. That means that you're onto a good idea, but a lot of people get confused that again, they think that you're a cloud data warehouse and you're not, I mean, you're much more than that. >> Yeah, I hate that. I have to say, because from day one we were not a cloud data warehouse. As I said, it was all about combining the big data, massive amount of unstructured data, petabytes stored as files. Okay, that's very important, store as files where it's very easy to drop data in the system without... Very low cost to combine with data warehouse, full multi statement transaction when people will tell you today, oh, now we are a data warehouse. They don't have multi statement transaction, right. So we had from day one multi statement transaction really efficient SQL. You could run your dashboard. So combining these two worlds was I think the crazy thing, that's the crazy innovation that Snowflake did initially. >> Yeah. >> And I know it's really easy to build data warehouse somewhere, because if you don't think about big data, petabytes, extremely structured data, you remove a lot of complexity. >> This is why Lisa, when you get excited about technology, but you always have to have a, somebody who really deeply understands technology to stink test it, all right so awesome. Thank you for sharing that story. >> Yeah. >> Fantastic. So over 5,900 customers now. I saw over 500 in the Forbes G2K, over almost 10,000 people here this year. If we think back to 2019, there was about what? Less than 2000 people. >> Yeah. >> What do you think is going to happen next year? >> I don't know. I don't like to think about next year. I mean, I always say, Snowflake is so exciting to me because it is like a TV show, right. Where you wait the next season and we have one season every year. So I'm really excited to know what is going to happen next year. And I don't want to project what I think will happen, but all these movements to the Snowflake being the platform for data application. I want to see what people are going to build on our platform. I mean, that's the excitement. >> Season 11 coming up. >> Yes. Season 11. Yes. >> No binge watching here. Benoit, it's been a pleasure to have you on the program. >> Thank you. >> Congratulations on incredible success, the momentum, the energy is contagious. We love it. (Benoit laughing) >> Thank you so much. >> Thank you. >> Bye bye. >> For Benoit Dageville and Dave Vellante, I'm Lisa Martin. You're watching theCUBE's coverage of Snowflake Summit '22. Dave and I will be right back with a wrap. (upbeat music)