(upbeat music) >> Hello, welcome to this CUBE conversation. I'm John Furrier your host of theCUBE here in our Palo Alto studio. We got a great conversation with the CEO of Lacework, David Hatfield. Who's in on theCUBE remote. David great to see you guys, a security platform at Lacework, you're at the helm as CEO. Welcome to theCUBE conversation. >> Thank you, John. Great to see you congrats to you and the team and all the success. I think what you guys are doing is really important so happy to be part of it. >> Great to have you in the community and you guys are doing great work. I know about Lacework I've done some due diligence on you guys. I love your business model, but for the folks who don't know what you guys do, take a minute to explain who is Lacework? What do you guys do? What's your positioning? And what's your focus? >> Yeah, well, we're a modern data security platform for the cloud. And so I think data science meets cloud security ultimately. The company has been around since 2015. We received one of the largest financing rounds that we're aware of I think in history in security business, $525 million in January. Led by Sutter Hill Ventures which many people may know about they founded PureStorage with the notion that we're going to go fundamentally change and revamp the ownership model for a high speed data storage using flash versus using spinning disc drives. I spent eight years with that company. Love with what we built there. Then Mike Speiser considered an investment in a company called Snowflake computing. I think you're aware of what Snowflake does which is bringing data warehousing into the cloud. And the third big investment that Sutter Hill made is really to help disrupt security, and that's in Lacework. So north of a billion dollar valuation a 300% year over year growth and have a ton of momentum. So at the core of what we do, it's really trying to merge, when we look at we look at security as a data problem, security and compliance the data problem. And when you apply that to the cloud, it's a massive data problem. you literally have trillions of data points across shared infrastructure that we need to be able to ingest and capture and then you need to be able to process efficiently and provide context back to the end-user. And so we approached it very differently than how legacy approaches have been in place, you know largely rules-based engines that are written to be able to try and stop the bad guys. And they miss a lot of things. And so our data-driven approach that we patented is called a polygraph. It's a, it's a security architecture and there are three primary benefits. It does a lot of things, but the three things that we think are most profound first is it eliminates the need for, you know dozens of point solutions. I was shocked when I, you know kind of learned about security. I was at Symantec back in the day. And just to see how fragmented this market is, it's one of the biggest markets in tech. $124 billion in annual spend growing at, to $300 billion in the next three years. And it's massively fragmented. And the average number of point solutions that customers have to deal with is dozens. Like literally 75 is the average number. And so we wanted to take a platform approach to solve this problem where the larger the attack surface that you put in the more data that you put into our machine learning algorithms the smarter it gets and the higher, the efficacy. So eliminating point solutions is his value proposition one. Point two is that we have to be 10 X better than everybody else in the business. Otherwise the merchant companies don't get a breakout and become long and during companies. And so there's a number of different dimensions. The first dimension that I think is probably the most important is efficacy, you know in anomaly detection or in, you know threat detection where you're trying to identify what risks we have in the business. It's, it's generally a very noisy activity. And so rules-based approaches on average will produce a hundred alerts to our one or two. Those, the signal to noise ratio, is, is, you know is a massive a 100x, but call it 10x a reduction. And so we're actually delivering the needle versus the haystack for security administrators and dev developers to actually solve the problem. So it's 10x, higher efficacy it's 10x faster to be able to resolve the problems. And obviously the ROI is, is a no-brainer because you're eliminating all these points which is in having to manage it. And the third, and probably the thing that I'm most excited about what we're doing and what our customers are already realizing is that we're transforming security and compliance teams from kind of compliance into business enablers. when you automate all these processes and you build it into, you know the CICD platforms for the developers you actually enable the developers to write code to differentiate their business, you know to create new customer experiences to get competitive advantage and drive revenue for their businesses. And, and you know that's not what security has done up to this point. We oftentimes, they're the ones we're the ones having to say, no, you know we're slow down or it's too risky, etc. But when you automate that and you increase the efficacy you can enable the developers to do their thing. And it allows the CSOs and allows the security professionals to up level their responsibility into selling and driving revenue. And that is increasingly going to become more and more important for supply chains and partners of these cloud native businesses of how secure am I working with you, etc. And so we think that that transformation of the role of security is going to be as, as meaningful as the technology that we're providing the business. So we're super excited about it. >> I could tell you have so much going on this investment team Sutter Hill, you mentioned big time players huge success track record. Just saw them written up in the wall street journal as one of the best venture capital firms and returns. It's just that the bets are all coming home, but their bet strategy is simple. Disrupting the market that's growing and changing PureStorage, you mentioned company you've worked for, you know people were saying, oh, they'll never get escape velocity. They disrupted an existing, boring storage market changed the game there, security, right for change. A lot of tools, a lot of people have buying tools off the shelf, you know and everyone fighting for the platform. That seems to be the conversation. So I have to ask you, you guys want to be the player that that platform you are, that platform what's different in this platform where everyone's trying to be a security platform, what's makes you different. >> Yeah. So I mean, I think the platform wars are, are clearly, upon us, you know I think what's different about our approach is that we were built on the cloud, for the cloud so we're a cloud native business that, you know runs our business on AWS and everything that we do. We don't have hardware, we don't own data centers. we don't have any of the legacy elements that are there. we use software run on the cloud to enable this. So that's point number one point number two is we did the hard work of mapping the data elements that are out there and adjusting them in and then have this polygraph, you know behavioral anomaly detection, that is it can be applied to today. It's being applied to vulnerability and discovery management and containers and Kubernetes. But over time we believe it extends very naturally to a larger part of the attack server. So we don't have to rewrite the data engine to develop solutions across broader attack services. We already have that, you know so I think our time to develop and innovate will be profound. And I think the third thing that we're seeing companies do and largely the legacy bigger companies is that they're just acquiring their way there. And, it's very, very difficult to acquire 8 to 10 to 20, 30 companies, 30 different CTOs 30 different code bases and try and integrate them to provide a delightful customer experience. And, the parallels, you know in the storage business are, are are pretty similar actually, Dell bought EMC, EMC bought a hundred companies. And, we went after a platform approach to be able to go attack them with a unified file system in a in a unified customer experience that was native for the media that we're working with. We're doing the same playbook here, you know which is you have to have the hard work of the foundation elements in place to be cloud native to deliver great outcomes, great efficacy and and a really great customer experience. So when we get head to head with any of these points coming out and trying to solve something for containers or Kubernetes, or just vulnerability discovery and management, etc, or we're competing with the legacy companies that have, a hodgepodge of acquisitions that they're trying to pull together we went North of 95% of the time. our POC win rates are phenomenal better than anything I've ever seen. We had a pretty good one to appear too. And the, the product and the experience and the efficacy kind of stand on their own once we're in those fights. So part of why we enjoy working with AWS and are really focused on building the partnership together is that it creates awareness of what could be and what possibilities all we want is a shot. And, our approach is such that you can be up and running in minutes, you know and every single one of our customers does a POC. So we'll stand behind our technology as our real differentiator compared to anybody else that's out there. >> Great. You guys had great traction going on with the company certainly saw the investment news that you mentioned earlier at the top. Why did you come on as CEO? And when did you come on and join the team? And what was the reason? What, what, what attracted you to join as the CEO of Lacework? >> Well, I've been involved in the company for since the beginning actually I invested in the early rounds participated on the board and I've always bought into this. The thesis that security is fundamentally a data problem. And if we can get the data problem and the data processing right, you know you can fundamentally change the industry but you need to have a major inflection. And that inflection is people moving to the cloud. And we all have seen it during the pandemic. things are accelerating. AWS just did their earnings yesterday. I think they increased their top-line guidance from 46 billion to 56 billion this year. I mean, it's a machine that is continuing to move forward. They have 30% market share. Azure's investing at 20% GCP still investing people are moving their businesses online aggressively. And as they shift to the cloud the rules-based approach just doesn't work. It doesn't scale. And so a new approach needs to be done. And so by being cloud native and best of breed and solving the thorny problem of this data processing problem first, you know it gives us an opportunity to use that to then extend and build a business, you know at an enduring level over the next 10 to 20 years. And that's Sutter's model, that's their playbook. They don't invest in 400 companies and kind of spray and pray, which is what most venture funds do. And I love them. They're great. And we appreciate the investment in tech, but Sutter's focus is find a really big market find a catalyst for change. In our case, it's moving to the cloud and then build a modern approach. that is 10x better in every dimension. And that attracted to me. I mean, it's, it's a, it's one of the biggest markets in tech and it's one of the most important things that we can do is a digital business is to ensure that we're secure and we're safe and the threats are becoming much more skilled much more deliberate, much better funded. And so the importance for us to ensure that company's security is really tight is, is increasingly critical. So the combination of those factors, and then as I dove back into it and talked to a bunch of customers and talk to partners and seeing the outcomes and enthusiasm that they had and the, the team is phenomenal. And so talking to them, and I just kind of got energized by the opportunity to go build a really important company that really delivers great outcomes. So I'm having a ball great to be back into it. >> Yeah. It's great to have leadership that has experienced that you have and go to the next level because this is classic next level. When you talk about Amazon's earnings and cloud scale and hybrid and edge right around the corner at scale as well. So you start to see that transformation really hit the tipping point, which is changing the landscape on the developer side, which I think is super valuable. I think you hit that. You mentioned core problem. You guys look at that through the lens of data problem. How does this trend of everything going hybrid and soon to be, you know edge core to edge impact your businesses of tailwind? How do you see you capturing that next level of scale from a business perspective for lease work? >> Well, I think that the trend, you know from core to edge, you know, hybrid and, you know ultimately cloud a hundred percent, there we've started with the cloud native businesses. Like, we've been focusing on those companies that are already there, you know and so now we're we just had finished a phenomenal record-breaking Q1 and multiple seven figure deals, you know with very complex global environments where they do have a hybrid environment and they are leveraging the edge. And we're perfect for that. I mean, as you think about what we deliver in its most simplistic context, you know we're effectively delivering a security solution from the container to control plane, right. You know we want to be able to have a granular understanding of operated trillions of data points coming in and those can be collected in the core. They can be collected on-prem. They can be collected in the cloud. Ultimately they need to be collected and then contextualized so, you know and this is where our behavioral polygraph technology transitions data into information that's useful via the polygraph. And so we think that, the complexity that's added with environments that are hybrid environments that are leveraging the edge environments that are leveraging the cloud native all need a control plane to run across that to deliver efficacy, you know, for our customers. And, we work with, you know AWS has their own security tools. Azure has some security tools UCPs security tools, but ultimately, our, our challenge and opportunity is to be best of breed to deliver incremental value on top of that and that horizontal value across it. so customers have choice but they know that their security posture is, is, is secure. And so we, we see it as a tailwind for our businesses as we go forward. >> I always said the companies that have the horizontal scalability with cloud and then have that vertical AI kind of vibe where you can get in the context of the data is there to win it all. And I think that you guys have a great solution potentially there. I want to get more information if you don't mind double clicking on that with me, this is kind of a different take on cloud security because you've got the scalability, which gives you the observation space. And then you got to get the context to get the right patterns or whatever magic you guys have in the, in the secret sauce. But you doing that on top of massive exponential velocity. >> Yeah. >> Where's that secret sauce? Is it in the compute? Is it in the software? What's different about what you guys have in security to give us a- >> It's all in the, it's all in the software. Ultimately, it's the intelligence of how you capture it how you ingest it, how you, you process it but then ultimately how you, how you contextualize it and then how you apply it to different problems. and so the attack surface area and security is a very broad, that's why there's so many point solutions that are out there. And so the breadth of solutions, you know we just want to continue to add solutions and capabilities on top of this polygraph security architecture that allows for the same kind of simple experience, the same kind of 10x value proposition, but, but, but wider. And so we can eliminate more and more of those of those point solutions. So, our, our thinking on it is that, you know we can participate once we have a customer the land and expand motion of what we have. We want to make it really really frictionless for customers to try our technology. And so that's why we do POC. That's why it only takes a couple of minutes and you can do it for just Kubernetes or just containers or just vulnerability discovery and managed like wherever your specific pain point is. We want to help identify what that is, you know give you a chance to try it. And then once we prove ourselves it's very easy to extend that across the board. So we get natural growth in velocity from people moving to cloud and just, you know more usage of, of compute and storage and sort of etc, but breadth of actually the security or posture or a tax service that they have as well. So, you know so I think we have an opportunity to benefit from, from both the depth and the breadth, you know but the value that we're delivering is ultimately the software that we're running on top of the infrastructure. And you mentioned observability, there's a number of companies that are leveraging the data and insights collected in different ways to converge security and observability over time. And, we see that, you know that ultimately there's a very very big security company that needs to be built. That really is best of breed, but the data and the insights that we're providing to our primary customer, which is really DevOps. I mean, it's really the development communities and the builders or who we're changing security for and enabling, in addition to the security teams, you know we think that we're going to continue to drive software that adds value on that data set and it can be applied to multiple problems in the future. So today security is a massive market. We're going to focus there, but it does. It does extend pretty naturally to other markets >> It's a hot market security. Everyone needs to have the latest and greatest and also has to be effective. I got to ask you specifically around startup transition to a rapidly growing company to now you're going to the next level where you're starting to having to get into some serious, big complex enterprise go to market sales motions. So what's in it for the customer. What's the, what's the pain point? What's the customer orientation. What do you marketing into as a solution? Is it the developer? Is it the CSO? Is it the CXO, what's in it for the enterprise? Why Lacework, why are they engaging? You guys get record numbers. What's the, what's in it for them. What's the, if I'm the customer what's in it for me? >> Ultimately efficacy, which is your security posture is it goes up significantly, simplicity, which is makes it easier for you to do your other jobs, you know and I'll have to look for those needles in a haystack and ROI, you know which is it's just compelling, and much, much more efficient than what, what you're doing today. So that that's a pretty universal value proposition and applies to cloud native businesses that are high growth that applies to government agencies. It applies to a large complex enterprises. We have a wonderful kind of go to market motion right now. I think Andy Byron and the team who've been here have really done a wonderful job of really making the customer buying experience and the journey really efficient, you know and help them quantify the impact and the risks and then deliver value. And I think, that that applies in sort of the commercial mid-market and cloud native space. And like I mentioned, we had, a number of deals in the quarter that were seven figure deals, you know in very complex organizations with massive demands. And, you know it ultimately selling is a team sport and, you know and still having the process and the rigor, that's there fine tuning that to make sure you have the people and the partnerships, you know, that deliver solutions in the way that customers want to buy them and then ultimately deliver a value proposition that is just unquestionably better. And I think we have all of those elements, you know we'll be entering the, the large enterprise very aggressively in the quarters to come. I that's where I've come from, you know running a multi-tool, you know, kind of go to market engines where you've got mid-market commercial enterprise large enterprise government across all geographies is, is really fun to expand. And, we're we're hiring as fast as we can maintain quality, you know? And so we're out of that startup phase now and entering into real scale. And, I think that, you know in the AWS marketplace I think we're the number one startup vendor. If I, if I got my facts, right. for, for private offers, we're one of the top security players and top 50 ISBs in the marketplace overall. And so in order for us to get the motion we need to make sure that we're delivering our value in the context of how companies want to buy it. And people want to use AWS credits, you know to apply to their solutions. And so it's really important for us to make that frictionless buying experience occur. And so we're excited about it. I think we've got a really nice start and it's the fun part of building companies, which is how do you attune things to make sure you're making it really really easy for the market to absorb your technology. And then once you're there, delight the hell out of them and just make sure that, that there's that they're excited in our, our net retention rates are the best I've seen in the marketplace. Our net promoter scores, you know, are in the high fifties low sixties, which, which is fantastic in this space. I think it's best in class by order of magnitude some players, big SIM players that are out there, you know have a customer in net promoter score of four. You know that means 96% of the people or 96 boats that says they wouldn't recommend the solution to their, to their peers. So, at pure, we've got this at scale. So from 70 to, in the, in the low eighties I think we have the opportunity to do the same thing here. So, combination of tailoring the motion that we have making it really easy for the buyer to buy what they want with whom they want from whom they want, you know and then just spreading a value proposition. That is a no brainer is, is I think the secret recipe >> If anything, it's interesting, you know you're so much experience in the enterprise and tech with cloud native you're basically laying out the success formula, which is if you have a value proposition you should be able to get it in quickly. You don't need the top down. win everything you can have a value proposition that can be enabled for usage and then grow rapidly when it's successful and that's cloud, that's the cloud business model. So it's not so much about organic versus this. It's really what the preferred motion is. >> It's speed, and I think developers in particular it's why the cloud happened, right? I.T wasn't delivering services in, in the speed and the efficacy that, that, that the developers wanted. And so in order to appeal to the developer community you need to deliver something that's frictionless and easy and fits into JIRA and fits into their workflow processes and speaks their language. And so we built our platform and our solutions for builders because that's where the money is. That's where the pain point is and that's and they want to build secure code. They just don't want to be told no. And so, we want to automate that process and make code secure and do that, you know in the build phase and then do it in the runtime. And then across the CICD pipeline we want to continuously be adding value across that. And, and the developers, candidly when pure bought the solution, many years ago and I introduced him to the company, it was it was the general manager of our software business unit that bought it not the security team. And I think that's a trend that is continuing that we're going to focus on. >> A lot of people realize that security and compliance and automation kind of all go together where you don't want to disrupt developers to kind of engineer something just to do an integration, for instance. So there's a real business model impact that you're hitting on here. That's not just a technical solution. It's really how the business is operating. And I think that to me is super interesting use case. What's your reaction to that? Do you see this as a, as a- >> No it's, that's that's that third part that I was talking about, you know which is that's most exciting is that, you know people are calling shift left, right. so moving, you know security into the development pipeline as it's happening and in integrating security architects as value added into the development organizations themselves and leveraging automated machine learning tools like ours to be able to simplify and automate the process versus slowing it down. So we think that shift left is, is super exciting and, and will continue. And we actually think we're the leaders in that space. We want to continue to be the leaders in that. >> Congratulations, great insight. Awesome to have you on and to hear from your experience and also the great venture that your scaling up and to the next level. Lacework, David thanks for coming on, but I'll give you the last minute to close us out. Give us a quick plug for the company vitals, what you're working on now, what you're looking for, you're obviously hiring give a quick plug for Lacework. What you, what are you working on? >> So, number one, we love our partnership with AWS. And so we're going to continue to invest, invest there. Two the businesses growing North of 300% year over year. That means that we've got record breaking growth and lots of hiring. So we're hiring across all functions. And three give us an opportunity. I, I think that, you know, you can fundamentally we want to be the bar of what you define all other security companies and all the technology companies. So it's a high bar. We want to make it frictionless, frictionless to try give us a shot, give us some feedback. And I'm grateful and privileged to be part of this, this wonderful team. So look forward to spending more time with you, John, in the future. >> Man, looking forward to a lot lots of talk about David Hatfield CEO of Lacework great company scaling up again. Another success story in cloud, cloud native as Po, COVID comes to a close, if you will for this phase and people get back to real life. The scale of cloud is going to be leading it and a new technology is going to be powering it. This is theCube conversation. I'm John Furrier. Thanks for watching. (soft music playing) (music fades)

(upbeat music) >> In 2010 Wikibon predicted that the all flash data center was coming. The forecast at the time was that flash memory consumer volumes, would drive prices of enterprise flash down faster than those of high spin speed, hard disks. And by mid decade, buyers would opt for flash over 15K HDD for virtually all active data. That call was pretty much dead on and the percentage of flash in the data center continues to accelerate faster than that, of spinning disk. Now, the analyst that made this forecast was David FLoyer and he's with me today, along with Renen Hallak who is the founder and CEO of Vast Data. And they're going to discuss these trends and what it means for the future of data and the data center. Gentlemen, welcome to the program. Thanks for coming on. >> Great to be here. >> Thank you for having me. >> You're very welcome. Now David, let's start with you. You've been looking at this for over a decade and you know, frankly, your predictions have caused some friction, in the marketplace but where do you see things today? >> Well, what I was forecasting was based on the fact that the key driver in any technology is volume, volume reduces the cost over time and the volume comes from the consumers. So flash has been driven over the years by initially by the iPod in 2006 the Nano where Steve Jobs did a great job with Samsung and introducing large volumes of flash. And then the iPhone in 2008. And since then, all of mobile has been flash and mobile has been taking in a greater and greater percentage share. To begin with the PC dropped. But now the PCs are over 90% are using flash when there delivered. So flash has taken over the consumer market, very aggressively and that has driven down the cost of flash much much faster than the declining market of HDD. >> Okay and now, so Renen I wonder if we could come to you, we've got I want you to talk about the innovations that you're doing, but before we get there, talk about why you started Vast. >> Sure, so it was five years ago and it was basically the kill of the hard drive. I think what David is saying resonates very, very well. In fact, if you look at our original presentation for Vast Data. It showed flash and tape. There was no hard drive in the middle. And we said 10 years from now, and this was five years ago. So even the dates match up pretty well. We're not going to have hard drives anymore. Any piece of information that needs to be accessible at all will be on flash and anything that is dormant and never gets read will be on tape. >> So, okay. So we're entering this kind of new phase now, with which is being driven by QLC. David maybe you could give us a quick what is QLC? Just give us a bumper sticker there. >> There's 3D NAND, which is the thing that's growing, very very fast and it's growing on several dimensions. One dimension is the number of layers. Another dimension is the size of each of those pieces. And the third dimension is the number of bits which a QLC is five bits per cell. So those three dimensions have all been improving. And the result of that is that on a wafer of, that you create, more and more data can be stored on the whole wafer on the chip that comes from that wafer. And so QLC is the latest, set of 3D NAND flash NAND flash. That's coming off the lines at the moment. >> Okay, so my understanding is that there's new architectures that are entering the data center space, that could take advantage of QLC enter Vast. Someone said they've rented this, a nice set up for you and maybe before we get into the architecture, can you talk a little bit more about the company? I mean, maybe not everybody's familiar with with Vast, you share why you started it but what can you tell us about the business performance and any metrics you can share would be great? >> Sure, so the company as I said is five years old, about 170, 180 people today. We started selling product just around two years ago and have just hit $150 million in run rate. That's with eight sales people. And so, as you can imagine, there's a lot of demand for flash all the way down the stack in the way that David predicted. >> Wow, okay. So you got pretty comfortable. I think you've got product market fit, right? And now you're going to scale. I would imagine you're going to go after escape velocity and you're going to build your moat. Now part of that, I mean a lot of that is product, right? Product is sales. Those are the cool two golden pillars, but, and David when you think back to your early forecast last decade it was really about block storage. That was really what was under attack. You know, kind of fusion IO got it started with Facebook. They were trying to solve their SQL database performance problems. And then we saw pure storage. They hit escape velocity. They drove a truck through EMC sym metrics HDD based install base which precipitated the acquisition of XtremeIO by EMC. Something Renan knows a little bit about having led development, of the product but flash was late to the NAS party guys, Renan let me start with you. Why is that? And what is the relevance of QLC in that regard? >> The way storage has been always, it looks like a pyramid and you have your block devices up at the top and then your NAS underneath. And today you have object down at the bottom of that pyramid. And the pyramid basically represents capacity and the Y axis is price performance. And so if you could only serve a small subset of the capacity, you would go for block. And that is the subset that needed high performance. But as you go to QLC and PLC will soon follow the price of all flash systems goes down to a point where it can compete on the lower ends of that pyramid. And the capacity grows to a point where there's enough flash to support those workloads. And so now with QLC and a lot of innovation that goes with it it makes sense to build an all flash, NAS and object store. >> Yeah, okay. And David, you and I have talked about the volumes and Renan sort of just alluded to that, the higher volumes of NAS, not to mention the fact that NAS is hard, you know files difficult, but that's another piece of the equation here, isn't it? >> Absolutely, NAS is difficult. It's a large, very large scale. We're talking about petabytes of data. You're talking about very important data. And you're talking about data, which is at the moment very difficult to manage. It takes a lot of people to manage it, takes a lot of resources and it takes up a lot, a lot of space as well. So all of those issues with NAS and complexity is probably the biggest single problem. >> So maybe we could geek out a little bit here. You guys go at it, but Renan talk about the Vast architecture. I presume it was built from the ground up for flash since you were trying to kill HTD. What else do we need to know? >> It was built for flash. It was also built for Crosspoint which is a new technology that came out from Intel and micron about three years ago. Cross point is basically another level of persistent media above flash and below Ram. But what we really set out to do is, as I said to kill the hard drive, and for that what you need is to get the price parity. And of course, flash and hard drives are not at price parity today. As David said, they probably will be in a few years from now. And so we wanted to, jumpstart that, to accelerate that. And so we spent a lot of time in building a new type of architecture with a lot of new metadata structures and algorithms on top to bring that effective price down to a point where it's competitive today. And in fact, two years ago the way we did it was by going out to talk to these vendors Intel with 3D Crosspoint and QLC flash Mellanox with NVMe over fabrics, and very fast ethernet networks. And we took those building blocks and we thought how can we use this to build a completely different type of architecture, that doesn't just take flash one level down the stack but actually allows us to break that pyramid, to collapse it down and to build a single system that is as fast as your fastest all flash block device or faster but as affordable as your hard drive based archives. And once that happens you don't need to think about storage anymore. You have a single system that's big enough and cheap enough to throw everything at it. And it's fast enough such that everything is accessible as sub-millisecond latencies. The way the architecture is built is pretty much the opposite of the way scale-out storage has been done. It's not based on shared nothing. The way XtremIO was the way Isilon is the way Hadoop and the Google file system are. We're basing it on a concept called Dis-aggregated Shared Everything. And what that means is that we have the media on one set of devices, the logic running in containers, just software and you can scale each of those independently. So you can scale capacity independently from performance and you have this shared metadata space, that all of the containers can see. So the containers don't actually have to talk to each other in the synchronous path. That means that it's much more scalable. You can go up to hundreds of thousands of nodes rather than just a few dozen. It's much more resilient. You can have all of them fail and you still didn't lose any data. And it's much more easy to use to David's point about complexity. >> Thank you for that. And then you, you mentioned up front that you not only built for flash, but built for Crosspoint. So you're using Crosspoint today. It's interesting. There was always been this sort of debate about Crosspoint It's less expensive than Ram, or maybe I got that wrong but it's persistent, >> It is. >> Okay, but it's more expensive than flash. And it was sort of thought it was a fence sitter cause it didn't have the volume but you're using it today successfully. That's interesting. >> We're using it both to offset the deficiencies of the low cost flash. And the nice thing about QLC and PLC is that you get the same levels of read performance as you would from high-end flash. The only difference between high cost and low cost flash today is in right cycles and in right performance. And so Crosspoint helps us offset both of those. We use it as a large right buffer and we use it as a large metadata store. And that allows us not just to arrange the information in a very large persistent right buffer before we need to place it on the low cost flash. But it also allows us to develop new types of metadata structures and algorithms that allow us to make better use of the low cost flash and reduce the effective price down even lower than the rock capacity. >> Very cool. David, what are your thoughts on the architecture? give us kind of the independent perspective >> I think it's brilliant architecture. I'd like to just go one step down on the network side of things. The whole use of NBME over fabric allows the users all of the servers to get any data across this whole network directly to it. So you've got great performance right away across the stack. And then the other thing is that by using RDMA for NASS, you're able, if you need to, to get down in microseconds to the data. So overall that's a thousand times faster than any HDD system could manage. So this architecture really allows an any to any simple, single level of storage which is so much easier to think about, architect use or manage is just so much simpler. >> If you had I mean, I said I don't know if there's an answer to this question but if you had to pick one thing Renan that you really were dogmatic about and you bet on from an architectural standpoint, what would that be? >> I think what we bet on in the early days is the fact that the pyramid doesn't work anymore and that tiering doesn't work anymore. In fact, we stole Johnson and Johnson's tagline No More Tears. Only, It's not spelled the same way. The reason for that is not because of storage. It's because of the applications as we move to applications more and more that are machine-based and machines are now not just generating the data. They're also reading the data and analyzing it and providing insights for humans to consume. Then the workloads changed dramatically. And the one thing that we saw is that you can't choose which pieces of information need to be accessible anymore. These new algorithms, especially around AI and machine learning and deep learning they need fast access to the entirety of the dataset and they want to read it over and over and over again in order to generate those insights. And so that was the driving force behind us building this new type of architecture. And we're seeing every single day when we talk to customers how the old architecture is simply break down in the face of these new applications. >> Very cool speaking of customers. I wonder if you could talk about use cases, customers you know, and this NASS arena maybe you could add some color there. >> Sure, our customers are large in data. We started half a petabyte and we grow into the exabyte range. The system likes to be big as, as it grows it grows super linearly. If you have a 100 nodes or a 1000 nodes you get more than 10X in performance, in capacity efficiency and resilience, et cetera. And so that's where we thrive. And those workloads are today. Mainly analytics workloads, although not entirely. If you look at it geographically we have a lot of life science in Boston research institutes medical imaging, genomics universities pharmaceutical companies here in New York. We have a lot of financials, hedge funds, Analyzing everything from satellite imagery to trade data to Twitter feeds out in California. A lot of AI, autonomous driving vehicles as well as media and entertainment both generation of films like animation, as well as content distribution are being done on top of best. >> Great thank you and David, when you look at the forecast that you've made over the years and when I imagine that they match nicely with your assumptions. And so, okay, I get that, but that doesn't, not everybody agrees, David. I mean, certainly the HDD guys don't agree but they, they're obviously fighting to hang on to their awesome run for 50 years, but as well there's others to do in hybrids and the like, and they kind of challenge your assumptions and you don't have a dog in this fight. We just want the truth and try to do our best to report it. But let me start with this. One of the things I've seen is that you're comparing deduped and compressed flash with raw HDD. Is that true or false? >> It's in terms of the fundamentals of the forecast, et cetera, it's false. What I'm taking is the new egg price. And I did it this morning and I looked up a two terabyte disc drive, NAS disc drive. I think it was $54. And if you look at the cost of a a NAND for two terabytes, it's about $200. So it's a four to one ratio. >> So, >> So and that's coming down from what people saw last year, which was five or six and every year has been, that ratio has been coming down. >> The ratio between the cost Delta, between HDD is still cheaper. So Renan I wonder one of the other things that Floyer has said is that because of the advantages of flash, not only performance but also data sharing, et cetera, which really drives other factors like TCO. That it doesn't have to be at parody in order for customers to consume that. I certainly saw that on my laptop, I could have got more storage and it could have been cheaper for per bit for my laptop. I took the flash. I mean, no problem. That that was an intelligence test but what are you seeing from customers? And by the way Floyer I think is forecasting by what, 2026 there will be actually a raw to raw crossover. So then it's game over. But what are you seeing in terms of what customers are telling you or any evidence you have that it doesn't have to be, even that customers actually get more value even if it's more expensive from flash, what are you seeing? >> Yeah in the enterprise space customers aren't buying raw flash they're buying storage systems. And so even if the raw numbers flash versus hard drive are still not there there is a lot of things that can be done at the system level to equalize those two. In fact, a lot of our IP is based on that we are taking flash today is, as David said more expensive than hard drives, but at the system level it doesn't remain more expensive. And the reason for that is storage systems waste space. They waste it on metadata, they waste it on redundancy. We built our new metadata structures, such that they everything lives in Crosspoint and is so much smaller because of the way Crosspoint is accessible at byte level granularity, we built our erasure codes in a way where you can sustain 10, 20, 30 drive failures but you only pay two or 1% in overhead. We built our data reduction mechanisms such that they can reduce down data even if the application has already compressed it and already de-duplicated it. And so there's a lot of innovation that can happen at the software level as part of this new direct dis-aggregated shared everything architecture that allows us to bridge that cost gap today without having customers do fancy TCO calculations. And of course, as prices of flash over the next few years continue declining, all of those advantages remain and it will just widen the gap between hard drives and flash. And there really is no advantage to hard drives once the price thing is solved. >> So thank you. So David, the other thing I've seen around these forecasts is that the comments that you can't really data reduce effectively hard disk. And I understand why the overhead and of course you can in flash you can use all kinds of data reduction techniques and not affect performance, or it's not even noticeable like put the cloud guys, do it upstream. Others do it upstream. What's your comment on that? >> Yes, if you take sequential data and you do a lot of work upfront you can write out in very lot big blocks and that's a perfect sequentially, good way of doing it. The challenge for the HDD people is if they go for that for that sort of sequential type of application that the cheapest way of doing that is to use tape which comes back to the discussion that the two things that are going to remain are tape and flash. So that part of the HDD market in my assertion will go towards tape and tape libraries. And those are serving very well at the moment. >> Yeah I mean, It's just the economics of tape are really attractive. I just feel like I've said this many times that the marketing of tape is lacking. Like I'd like to see, better thinking around how it could play. Cause I think customers have this perception tape, but there's actually a lot of value there. I want to carry on, >> Small point there. Yeah, I mean, there's an opportunity in the same way that Vast have created an architecture for flash. There's an opportunity out there for the tech people with flash to make an architecture that allows you to take that workload and really lower the price, enormously. >> You've called it Flape >> Flape yes. >> There's some interesting metadata opportunities there but we won't go into that. And then David, I want to ask you about NAND shortages. We saw this in 2016 and 2017. A lot of people saying there's an NAND shortage again. So that's a flaw in your forecast prices of you're assuming prices of flash continue to come down faster than those of HDD but the shortages of NAND could be problematic. What do you say to that? >> Well, I've looked at that in some detail and one of the big, important things is what's happening in the flash market and the Chinese, YMTC Chinese company has introduced a lot more volume into the market. They're making 100,000 wafers a month for this year. That's around six to 8% of market of NAND at this year, as a result, Samsung, micron, Intel, Hynix they're all increasing their volumes of NAND so that they're all investing. So I don't see that NAND itself is going to be a problem. There is certainly a shortage of processor chips which drive the intelligence in the NAND itself. But that's a problem for everybody. That's a problem for cars. It's a problem for disk drives. >> You could argue that's going to create an oversupply, potentially. Let's not go there, but you know what at the end of the day it comes back to the customer and all this stuff. It's interesting. I love talking about the architecture but it's really all about customer value. And so, so Renan, I want you to sort of close there. What should customers be paying attention to? And what should observers of Vast Data really watch as indicators for progress for you guys milestones and things in the market that we should be paying attention to but start with the customers. What's your advice to them? >> Sure, for any customer that I talked to I always ask the same thing. Imagine where you'll be five years from now because you're making an investment now that is at least five years long. In our case, we guaranteed the lifespan of the devices for a decade, such that you know that it's going to be there for you and imagine what is going to happen over those next five years. What we're seeing in most customers is that they have a lot of doormen data and with the advances in analytics and AI they want to make use of that data. They want to turn it from a cost center to a profit center and to gain insight from that data and to improve their business based on that information that they have the same way the hyperscalers are doing in order to do that, you need one thing you need fast access to all of that information. Once you have that, you have the foundation to step into this next generation type world where you can actually make money off of your information. And the best way to get very, very fast access to all of your information is to put it on Vast media like flash and Crosspoint. If I can give one example, Hedge Funds. Hedge funds do a lot of back-testing on Vast. And what makes sense for them is to test as much information back as they possibly can but because of storage limitations, they can't do that. And the other thing that's important to them is to have a real-time experience to be able to run those simulations in a few minutes and not as a batch process overnight, but because of storage limitations, they can't do that either. The third thing is if you have many different applications and many different users on the same system they usually step on each other's toes. And so the Vast architecture is solves those three problems. It allows you a lot of information very fast access and fast processing an amazing quality of service where different users of the system don't even notice that somebody else is accessing the same piece of information. And so Hedge Funds is one example. Any one of these verticals that make use of a lot of information will benefit from this architecture in this system. And if it doesn't cost any more, there's really no real reason delay this transition into all flash. >> Excellent very clear thinking. Thanks for laying that out. And what about, you know, things that we should how should we judge you? What are the things that we should watch? >> I think the most important way to judge us is to look at customer adoption and what we're seeing and what we're showing investors is a very high net dollar retention number. What that means is basically a customer buys a piece of kit today, how much more will they buy over the next year, over the next two years? And we're seeing them buy more than three times more, within a year of the initial purchase. And we see more than 90% of them buying more within that first year. And that to me indicates that we're solving a real problem and that they're making strategic decisions to stop buying any other type of storage system. And to just put everything on Vast over the next few years we're going to expand beyond just storage services and provide a full stack for these AI applications. We'll expand into other areas of infrastructure and develop the best possible vertically integrated system to allow those new applications to thrive. >> Nice, yeah. Think investors love that lifetime value story. If you can get above 3X of the customer acquisition cost is to IPO in the way. Guys hey, thanks so much for coming to the Cube. We had a great conversation and really appreciate your time. >> Thank you. >> Thank you. >> All right, Thanks for watching everybody. This is Dave Volante for the Cube. We'll see you next time. (gentle music)

>> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hey welcome back everybody, Jeff Frick here with theCUBE we're in our Palo Alto studio, it's still 2020, we're still gettin' through the COVID crisis and we're still reaching out to our community really to talk to leaders who have lead through difficult times, led through transitions, and really go out to the experts and get some advice from people who have been around the block a few times, and I'm really, really excited to have one of my all time favorite business executives joining us, I haven't talked to him in years and years and almost decades, David Pottruck is joining us, he is formerly the CEO of Schwab, how he kind of made his name, now he's an author, he's teaching at the Wharton School, he's a New York Times best selling author and he's also the chairman of Red Eagle Ventures, David, great to see you. >> Thanks, Jeff, it's good to be with you today. >> Absolutely, so before we get in, just to check in, how are you doing, how are you gettin' through 2020, I can't believe we're already on the backside of this crazy year. >> Well, it's been a pretty challenging year as you know, and we've seen companies learn to operate in a virtual world. Zoom has been one of the huge beneficiaries, but technology companies in general, the whole FAANG group of Facebook, Amazon, Netflix and such, they've all benefited from people getting more virtual, and one of the non profits I'm involved with sends out videos to schools on social and emotional learning and that's seen a big uptick. So, the world is changing, and changing in very substantial ways, and I don't think we'll ever go back to the way it was in total, we will go back to having face to face meetings, of course, but I do think that operating virtually and doing more things remotely, remote business meetings over zoom are going to be a fixed part of the future, >> Right, right. >> At least in my opinion. >> So, the reason I wanted to reach out to you is you've managed through some crazy transitions and some crazy disruptions back in the day and for a lot of the young people that don't remember, there was a time before we did everything online. There was a time where you had a broker and you called him on the phone and you paid a pretty big price based on a percentage of the transactions. You were at Schwab in the late 90s when this new thing called the internet came along, and these new things called internet only businesses to compete with you, I wonder if you can kind of take us back as you started to see some of these new kinds of threats, coming not necessarily from people that you recognize from up and down the street, but people who are coming over horizons that you've never ever seen before. And how did you start to get a feel for hmm, the landscapes a changin'. >> You know it's really funny to look back that there actually was a day when something called the internet didn't exist. And, there was no connectivity, there was no internet. We were, of course, at that time a telephone based brokerage firm, what used to be called discount brokers. We don't use that phrase very much anymore at Schwab, but, we were a telephone based discount broker, and the internet popped up and started becoming commercialized, and some online only brokerage firms popped up. And these firms didn't have call centers, they didn't have branch offices, if you wanted to do a trade you did it over your computer, online, and the pricing was dramatically less. To give you some idea, to buy 100 shares of IBM, Merrill Lynch would have charged you $250, for that one trade, Schwab would have charged you $80 and E-Trade would have charged you $25. So, we were much cheaper than Merrill Lynch, but E-Trade was much cheaper than us. So, we were, at the time, we were worried about is there enough security on the internet, can we do trades. We have a reputation to protect, a brand new company they don't have a reputation to protect, we have customer security, we have a reputation to protect. Well, we started doing online trades, and the way we did it was we gave all of our customers a 20% discount on our normal pricing, so instead of charging 80-something dollars, you paid something like $60. So, it was a nice discount, customers liked it, they were doing online trades, and we're seeing that is just taking off, it's getting huge, and we're getting great press, the analysts love it, Wall Street loves it, we're a public company and it's going great, but of course at the same time I'm getting, a basket full of letters and emails from our customers saying "why can't you do trades for $25 like E-Trade? Why are they able to do an online trade for $25 and you're charging $65? I thought you stood for value, I thought you guys wanted to be the best value for the money." So, I'm in this dilemma where Wall Street doesn't see these letters, they don't get reported, I see them, and there dozens and then hundreds, and then thousands. >> Wow. >> We had millions of customers, so to get a thousand letters or emails in a month that's very possible. And so I go to Chuck with this and I said you know, I think we need to make a change because no great company was built on the back of unhappy customers. >> Right, right. But you know, it's so funny, not funny, I'm sure it was a huge challenge in the moment, but you know, Clayton Christensen's another one of my favorite business leaders and why I like him so much, and rest in peace he passed earlier this year, is his very simple statement in "The Innovator's Dilemma" that smart people making sound business decisions based on their customer feedback will always miss discontinuous change. You were right in the middle of this thing and you had to get discontinuous change and it's funny, you've mentioned quite a bit in some of your other conversations about looking for faint signals, well this was not a faint signal, this was pretty much, sounds like came up and banged you over the head. So, how do you make and convince the rest of the people of the team that this is kind of a short-term pain but it's a long-term gain, really thinking about this long-term relationship with our customers, even though it's going to cost us on a per transaction basis in the short-term. >> Well, I had our financial staff run some models, and show me what would be the impact if we reduced our pricing from 60 something dollars a trade to $29 a trade, and the assumption of more and more trades moving to the internet. We also had a model into that the fact that people trade a little more when prices go down, costs go down cause I don't have the cost of someone answering the telephone, so there were some benefits, and I had to run the math to understand how long would it take us to go through the trough to get to the other side. A big important part of this is modeling the numbers. You don't just make this decision as a public company and just hope for the best >> Jeff: Right. >> You need to model it out, you need to run math and say how long will it take, what do we have to assume, what do we need to do, what costs do we need to cut, how are we going to protect ourselves as best as we can? And we knew that the math said that our profitability will go down 25% when we make this change of internet pricing, and we expected that Wall Street would be so upset, because they didn't see this coming, no analyst saw this coming cause they don't know about complaint letters I'm getting, so, analysts would be upset and the stock would go down 40%, going to your board and telling them you want approval for a 25% reduction in profits and a 40% reduction in your stock price is not what you want to do as a CEO, you don't want to go to your board with that and when they ask you, well how sure are you that we're going to climb out of this, you say it's going to take 18 months, what if it takes three years, you know, I was, I didn't see the choice we had, honestly, in my heart, you don't build a great company with an increasing number of unhappy customers. I didn't think we had a choice, and Clayton Christensen was one of the consultants that I used to help me think all this through because it was really hard to make this change, Jeff, because we were doing so well. >> Right. >> Ostensibly, we were killing it. >> Right, so it's interesting, I wonder if you could contrast it to what's happening say now with COVID, right, it was this, didn't sneak up on anyone, it was a really kind of a light switch moment in mid-March where suddenly everyone has to work from home, all your digital transformation initiatives are now put on fast forward, but we still have this situation where there's a variety of potential outcomes and timing that's really hard to gauge, so when you're thinking about managing through change within perfect information and you almost have kind of will we go back to normal, will we stay where we are or some spectrum in between, how do you help people think about how they should come up with contingency plans and think about managing through a number of options with imperfect information and really kind of no clear line, you said you had an 18 month ROI that the analytics point to, we're not really sure how long this thing is going to go and what it's going to look like when we get to the other side. >> Well, I think there's two issues there, one of them is how we get through this pandemic period. Until we get to, there's three things we need, we need inexpensive testing that is not done by a professional that we can do at home to see if we're safe. That's number one. Number two, we need a treatment that helps us get through this and get to the other side without dying, we need the fatality rate to even drop further. And number three we need a vaccine. So those are the three things that we need, that the world is working on all three of those, and my guess is that in the first half of 2021 we will have all three of those, we'll have all three of those and this will be a thing, basically, a thing of the past. >> Jeff: Right. >> So, but I don't think the world goes back, to exactly the way it was. People have learned they can have very effective meetings without everybody flying to Chicago, or New York, or Las Angeles, they can do it over Zoom, that doesn't mean meetings go away, but I think they're going to go down in numbers and more online things are going to happen. More people are going to be working from home at least part of the week. It's going to be different. >> Yeah. >> Those CEO's who sit in a somewhat of an ivory tower and get numbers fed to them from their financial staff, and they're not out talking to customers directly, people look at that as anecdotal information, I think it's more important than that, I think you need to see the passion behind the voice and the eyeballs of some of your best customers to understand what's going on with them, and a lot of CEO's don't actually do that. >> Right. You've made a really interesting comment in another interview that you did earlier, and you talked about the high gain questions. And one of the challenges of all CEO's is nobody wants to be the one that tells his CEO bad news, whether that be someone on your staff, whether that be some lower level person who's on the front lines and really knows there's some broken things, or whether it's a good customer as you said and kind of a social setting, how you doin', oh we love you, blah blah blah. But as a CEO you really have stressed that that is really some important hard to find, and hard to filter information up to the executive suite, so what were some of the tips and tricks you used to make sure that people either A. weren't afraid to tell you bad news, and B. that you could kind of go out and sniff it out a little bit more creatively than just kind of waiting for it to come through in the weekly reports. >> Well, obviously, you know, I think all kinds of executives get out and they talk to their customers on a regular basis, they're out and they're talking to them, the problem with those kind of discussions are no one wants to be disrespectful, people want to be nice in those meetings by and large, and you ask questions "how are we doing" "oh you guys are doing great", meanwhile the guy who tells you you're doing great is also looking at some newer technology that might replace you. (laughs) So that kind of question doesn't get you very far. So what we used to do, to be quite specific, is that we used to do a monthly luncheon where I had 12 of my mostly top executives but some people a level or two down, 12 Schwab people with 24 customers. And so they were tables of six, two of us, four customers, and we had a theme that we would talk through and the themes were always around things of, if you had to pick out three things we don't do well, what would they be? Give the customer permission to be comfortable being critical. What are the three things that you've heard about our customers, our competitors doing, that are better than us? What are the things that we need to change to make you even more delighted? You need to ask those kinds of high gain questions where there's no polite answer, the customer is permitted and given the opportunity to answer in a truthful and critical fashion. >> That's a great lesson, as you said give them permission and give them the format and the forum to say some of those things so that you get some of that information. Another great leadership principle that you shared many times, I want to dig into a little bit is kind of motivation verses inspiration. And that those are often confused, but very different concepts in the way that you lead people. I wonder if you can dig in a little bit on your philosophy on those two things. >> Sure, you know it's funny, those terms motivation and inspiration are used almost interchangeably as if they're the same thing. And they're not. Motivation is fundamental in business, and it's the exchange of behaviors for rewards. I was a psychology major in college, this was one of the things we learned about the exchange of behaviors for rewards and that's motivation. Inspiration on the other hand, is the effort to make people want to do something for, not for rewards that are tangible, but to be part of something great. We want you to be part of a movement, we want you to be part of something special, something that's going to change the world for the better and trying to get your employees to buy into this notion that we are on a mission and that mission is to make the world a somewhat better place, it doesn't mean we don't make money, of course we make money, but we're also out for more than a financial bottom line, we're out for a bottom line that's great for customers and maybe pretty great for employees as well. >> So it's interesting, cause you've seen 'em right, you've been in finance for ever, it's always about the shareholders, you've talked about the stock price a number of times in terms of a measure, but it seems more purposed led or purpose forward organizations now are more appealing to the younger generation, I think the search for a little bit more meaning in our day to day job and what that company is all about seems to have elevated over the last several years and taken a higher role in what they used to call triple line accounting, is it not only your shareholders who always are at the top of the list and have been traditionally, but your customers, your employee, and more and more your community and even the environment. Have you seen the swing towards, it's not just about shareholder value? >> Well, not on Wall Street. (laughs) I think, Wall Street is about money, and the people who go to work on Wall Street, and the way Wall Street operates, it's measured in dollars and cents and share price and profits and distributions to private equity partners and so forth, it's a numbers game and it is a profit game on Wall Street, we should be honest about that, it is what it is. >> Jeff: Sure. >> And, I have yet to see the Wall Street firm that is talking about triple bottom lines cause that just doesn't happen very much on Wall Street, it doesn't happen from my perspective, it almost doesn't happen at all. But there are other companies where they do talk about a more triple bottom line, and I think as a leader if you want to be that kind of company and you want to be that kind of leader you have to be comfortable talking about that, and not feel embarrassed by it, not feel that oh, that's too airy fairy, that's too goody two shoes. If you really believe that our goal is to have a triple bottom line, profitability, great for employees, and great for customers and the world at large, then as a leader you need to talk about that. You need to be willing to stand up and have those kinds of conversations and let yourself be challenged by perhaps the press, employees, shareholders, who think that that's not a good strategy. I believe that in many cases that's a great strategy because on a long-term basis you don't want every employee in your company, and all of your senior executives to basically be up for sale, that if a bigger job comes in with a bigger compensation, they're out the door. You're looking for loyalty, you're looking for buy in, for participation, for wanting to give every bit of themselves for the mission of the company. And as the CEO, if you want to take that path, you got to be willing to put yourself out there and talk about it and suffer the slings and arrows from those who don't believe that that's the best path for the company. >> Right, right. Well and that's another thing that you've talked about quite often, is really that the company feeds off the passion of the CEO, and the CEO has to have that passion because they're lookin', they're watchin', they're lookin' at your moves, they're lookin' at what you say, they're lookin' at your body language, they're lookin' at everything that you do. And I think within the context of these transitions and these difficult times, you have another great line that you've used a number of times, which is: "You need to have a perception of momentum." I love that line, so everyone needs to think that we're on the right path, we're not there yet, I feel it, he looks like he feels it, he looks like he's confident, so now I'm confident and I'm going to jump in and help be part of this change process. You've seen that time and time. >> Well, momentum is a tricky thing, you can have momentum and not have the perception of momentum. Because if you're doing a turn around, what often happens is in the early stages of the turn around, the numbers start to change but they're small, and you really haven't seen, it's not as steep. The turn around doesn't go steep, the turn around goes and builds slowly. And, what you need to be measuring in the beginning, are kind of the inputs and behaviors rather than the outputs, sales and profits. Those take longer. But you need to build belief, you need to build buy in, because it can take a long time before things start getting better and you don't want your best people to wonder whether this is the right move, should I be looking for another job, so, you have to build the perception of momentum even as you're building the reality of momentum. >> Right, right. So another thing we cover a lot of tech conferences, obviously, Cloud and AI, machine learning are hot things. But, you know, it always goes back to the big three. It's the technology, okay, but it's also people, and more importantly I think that gets left out is process. So, when you're thinking about, you know you're management is, and again, especially through a transition or a difficult time or some unknown and choppy waters, how do you think about those three, prioritizing those three and organizing those three between people, process and technology? >> Okay, well, you know always looking for technology that can be implemented to give you productivity, better customer service, you need to be monitoring what you're competitors are doing, and be looking out, sometimes at the bleeding edge, where you don't need to implement those kinds of changes right away, but you need to know where you want to go down the road, so you have some sense of that. As far as process goes, your processes are both a strength and a weakness because the strength of how well you run your processes today is also how hard they're going to be to change tomorrow. You know, companies are built for predictability, reliability, risk minimization, and all of your processes are built for those things. But those are also the things that are the opposite of big breakthrough changes. So you need to be thinking about, all right, are we strengthening our processes but also, if we have a change coming that's going to require a change of some of those processes, how is that going to get in our way and how are we going to get past that? >> Jeff: Right. >> I've left people for the last because to me that's the heart and soul of a successful executive. One person never gets everything done, it's all about the quality of your team. You've got to be a recruiter, you've got to be always on the look out for new talent that can help your company, and you've got to be thinking about how you're going to recruit that talent. You have to be a magnet for talent. When I sit on boards and I talk to the CEOs, I ask them, what are you doing to be a magnet for talent? What does that mean? What are you doing for great people to want to work for you? For you, and your company, what are you doing, how are you reinvesting in people, how are you putting time and energy in their professional development, in their growth? How are you getting to know them? How are you understanding their ambitions, their hopes and desires for the future? How much time and effort do you spend on that? And that's all part of having people not leave, everyone, in a way you can look at the world and think everyone is for sale. But you want people that are not for sale, that are committed to you and committed to the mission and in today's world where everything seems so fluid, I know my ideas about this probably seem very old and perhaps out of date, but I still believe in them with all my heart, that you want people that are committed to you and what we are accomplishing together. And you have to be reinforcing that with your words, and even more importantly with your actions. >> Yeah, I think it goes back to your inspiration, people are much more motivated by inspiration than just collecting a paycheck or getting a compensation back for what they're doing, which is a great segue to the last topic I wanted to cover with you, and I remember this, we had dinner, I think it was 1996 at the Wharton's Zweig Series, and you were such a phenomenal speaker, and I remember asking you the question and I remember your answer, and I've repeated it ad nauseam for the last 20 years. I said, "David, you're such a great speaker, why, how?" And you were so matter of fact in that you just said "hey, it's an important part of my job, I treat it as a skill, I hired a coach, I practiced like I would do any other skill", and why that's such a powerful story is you clearly are in a position of power, you could clearly have a crazy ego that got in the way of such a matter of fact accomplishment of these tasks and all the PR people I talk to and they hear this story "oh my gosh, we got to get him talking to my executives" because so many people let ego get in the way of what is really an important task for a CEO and a leader which is communication and you recognize that early on and really went after it to make sure that you were very good at this very important task. >> Well, what happened to me, I got lucky, I got lucky. When I got promoted to be the CEO of Schwab, I knew I was going to have to do a lot more public speaking and I already thought I was pretty good at being a public speaker, but I thought I needed to fine tune my messaging, I needed to get it better. So, I looked around and I got some referrals and I hired a guy that I thought was going to be a speech writer for me, that would help craft the message. And, we had our first meeting, and we're talking about an upcoming speech and he says to me things like, "Well, Dave, I want to know more about your life. Tell me how you grew up, tell me what you're proudest moments were, I want to learn about you." And I said to him, "Terry, I'm not looking for a biographer, I want a speech writer, I need a guy that can help me craft my message." And he said, "Well, Dave, that's not how I do things. I need to know who you are, I need to know what your passions are and where they come from so that we can give a message that has more than just words it has meaning, it has your passion built into it, that's what we need to do." And that's what Terry taught me, was that it's not just the words, it's also the passion, energy, and meaning and connection behind the words. And I want to mention one other thing that I think is very important. When people talk about being really good communicators, they often talk about speaking. They don't focus on listening. And listening is a tremendously important skill. So for example, you give a speech, you're the CEO or Senior Executive, you give a speech, do you stay there and do you do a Q+A session? The Q+A session can even be more important than the speech sometimes, because all the employees know that the speech is something that was pre-arranged, it's not on the cuff, it's something that's been thought about and prepared. But the questions and answers are authentic and in the moment. People are clamoring for authentic leadership. That Q+A session, where you're listening for the question and maybe the question behind the question. So you're not just trying to get through them as fast as you can, but you're trying to really answer and listen for the question and the question behind the question. And then answer those from the heart with passion, and that's how you will score the most points with your audience. >> That's great. And then who knows what comes from it, in getting ready for this I came across your blog post talking about Gopi Kallayil a mutual friend at Wharton who reached out to you after that same dinner, and you were happy enough, or you were kind enough to respond and grow a friendship and a relationship that again is lasted for decades. So that's such an important message to listen, as somebody said right, "God gave you two ears and one mouth should try to use them in that ratio." (laughs) Well David, thank you so much for taking some time, again I think these are really trying times in leadership, I think it's really an opportunity for great leaders to shine and those that don't there's really no place to hide. So I really appreciate you sharing your insight and taking a few minutes with us. >> Thanks, Jeff, I hope all the people that follow you and listen to your broadcasts learn something today and come away with some benefit from this time we've spent together. >> Undoubtedly, undoubtedly. Well, thanks again. All right, he's Dave Pottruck, I'm Jeff Frick, you're watching theCUBE, thanks for watching and we'll see you next time. (upbeat music)

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hey welcome back everybody. Jeff Frick here with theCUBE. Coming to you today from our Palo Alto studios. It's COVID is still going on. So, there's still no shows, but the good news is we've got the technology we can reach out to the community, and bring them in from far, far away. So today joining us from Virginia across the country is Dave Scott. He is the director of Product Management for Veritas, Dave, great to see you. >> Thanks Jeff, great to be here. >> Absolutely. So let's jump into it. You guys have been about backup and recovery for years and years and years, but oh my goodness, how the landscape continues to evolve between, you know, public cloud and you know, all the things happening with Amazon and Google, and Microsoft. And then now, of course big push for Hybrid. And, you know, we're the workloads, and kind of application centric infrastructure. You guys still got a backup and secure all this things. I wonder if you can give us a little bit of your perspective on, you know, kind of the increasing complexity of the computing environment, has all these different kind of pieces of the puzzle, are kind of gaining traction at the same time. >> Yeah, absolutely. I mean, I'm on the compliance side of the company. So I'm more on looking after requirements around collection of content preparation for litigation, making sure you're adhering to compliance regulations in different parts of the world. And, I mean that's a constantly evolving space. One of the, so basically the products I look after are Enterprise Vaults, Enterprise Vault.cloud, and eDiscovery platform. And, as you say, I mean, one of the biggest challenges is that customers are starting to move, you know, customers are looking for flexibility in how they deploy our solutions. We've had a product in market with enterprise vault for about 20 years. And so, we have a lot of customers that have a lot of data on premise, and now they're starting, you know, they've got cloud mandates, they want to move that content to the cloud. So we have gotten very aggressive at building out our SaaS, archiving solution, Enterprise Vault.cloud. But we also provide other options. Like if you want to move enterprise vault from your data center on premise, to your tenant in Azure, Amazon, we fully support that. In fact, we're taking advantage of cloud services to make that a much more viable option for our customers. >> So let's get into the regulation and the compliance, 'cause that's a big piece of the motivation beyond just, you know, making sure that the business can recover, that the regulation and compliance thing is huge. You know, the GDPR, which has been around now for a couple of years, California protection act. And I think what I find interesting from your perspective is you have this kind of crazy sea of regulations that are different by country, by industry, by data type, and they're evolving all the time. So, that's got to be a relatively complex little grid you got to keep track of. >> Yeah, it makes the job interesting. But it also is a huge competitive advantage for us. We have a team that researches data privacy regulations around the world, and it's been a competitive advantage in that we can be incredibly nimble in creating a new policy. We had some opportunities come up in Turkey, there's a regulation there that mirrors GDPR called KVKK or KVKK I think they call it locally. And it's, a joke that it's kind of like GDPR, but with jail time for noncompliance. So there's a lot more motivation on the part of an IT department, to make sure they're meeting that requirement. But it has to do with dealing with, you know, data privacy again, and ensuring the safety of the continent. That's proliferating throughout the world. You mentioned California Consumer Privacy Act, many other States are starting to follow what the California Consumer Privacy Act. And I'm sure, it won't be long before we have a data privacy act in the US, that's nationwide instead of at the state level. In other industries that we serve, like the financial services industry. There's, you know, there's always been a lot of regulation around SEC and FINRA in the US, that's spreading to other countries now, you know, MiFID II in the European union has been huge. And that dictates you need to capture all voice conversations, all text conversations, instant messages, everything that goes on between a broker and the end customer, has to be captured, has to be supervised, and has to be maintained on warm storage. So that's a great segment for us as well. That's an area we play very well in. >> So it's interesting. 'Cause in preparing for this, I saw some of the recent announcements around the concept of data supervision. So I think a lot of people are familiar with backup and recovery, and continuity, but specifically data supervision. What does that really mean? How is that different than kind of traditional backup and recovery, and what are some of the really key features or attributes to make that a successful platform? >> Yeah, no, it is really outside of the realm of backup and recovery. Archiving is very different from backup and recovery. And then archiving is about preserving the communication, and being able to monitor that communication, for the purposes of meeting compliance regulations. So, in the case of our solution, Veritas advanced supervision, It sounds a bit big brotherish, if I'm being honest, but it is a requirement for the financial service community that you sample a subset of those communications looking for violations. So you're looking for insider trading, you're looking for money laundering. In some companies, at the HR departments, or even just trying to ensure that their employees are being compliant. And so you may sample a subset of content. But it's absolutely required within the financial services community. And we're starting to see a lot of other industries, you know, leveraging this technology just to ensure compliance with different regulations, or compliance with their own internal policies. Ensuring a safe work place, ensuring that there's not any sexual harassment, or that type of thing going on through office communications. So it is a way of just monitoring your employees communications. >> So it's while I remember when, when people used to talk about messaging, and kind of the generic sense, like I could never understand why, you know, it's an email, it's a text. I mean, little did I know that every single application is now installed on every single device that I have, has a messaging app, you know, has a direct messaging feature. So, I mean the complexity and, and I guess the, the variability in the communication methods, across all these applications and, you know, probably more than half of them, that most of us work on are SaaS as well, really adds a ton of complexity to the challenge that you were just talking about. >> Oh, absolutely. I mean, I'm old. You know, when I started, all of my communications were on a Microsoft mail server, all my files were in the file, you know, the server room down the hall. Now I've got about 20 different ways to communicate on my phone. And, the fragmentation of communication does make that job a lot more, more challenging. You know, now you need to take a voice conversation, convert it to text. With COVID and with, you know, the dawn of telemedicine, or at least the rapid growth, and telemessaging, telemedicine sorry. There is a whole new potential market for this kind of supervision tool. Now you can capture every doctor patient interaction that takes place over Zoom or over a Team's video, transcribe that content, and there's a wealth of value in that conversation. Not only can you tell if the doctor is responding to the patient, if the interaction is positive or negative, is the doctor helping to calm the patient down? Do they have good quality of interaction? That sort of thing. And so there's incredible value in capturing those communications, so you can learn from the... you know learn best practices, I guess. And then, feed that into a broader data lake, and correlate the interaction with patient outcomes, who are your great doctors? who are your, you know, that type of thing. So that's an area that we're very excited about going forward. >> Wow, that's pretty interesting. I never kind of thought that through, because I would have assumed that, you know, kind of most of the calls for this type of data were based on some type of a litigation. You know, it was some type of an ask or a request, that I was going to ask you, now how does that actually work within the context of this sea of data, that you have. Is it usually around a specific individual, who's got some issues and you're kind of looking at their ecosystem of communications, or is it more of a pattern, or is it potentially more of a keyword type of thing that's triggering, You know, kind of this forensics into this tremendous amount of data that's in all these enterprises. >> Yeah, it's a little bit of everything. Like, so first of all, we have the ability to capture a lot of different native content sources. But we also leverage partners to bring in other content sources. We can capture over 80 different content sources, all the, you know, instant messaging, social media, of course email, but even voice communications and video communications. And to answer your question as far as litigation, I mean, it really depends on the incident right? in the past, in the old days, any kind of litigation resulted in a fire drill where you're trying to find every scrap of evidence, every piece of information related to the case. By being a little bit proactive and capturing your email, and your communication streams into immutable storage in an archive, you're ready for that litigation event. And you've already indexed that content, you've already classified that content. So you can find the needle in the haystack. You can find the relevant content to prove your innocence, or at least to comply with the request for information. Now that has also led to solving similar issues for public sector. US federal, with the Freedom of Information Act. They're getting all kinds of requests for right now for COVID related communications. And that could be related to lawsuits. it could be related to just information around how stimulus funds are being spent. And they've got to respond to these requests very, very quickly. Our team came up with a COVID-19 classification policy, where we can actually weed out the communications related to COVID-19. To allow those federal agencies, and even state and local agencies, to quickly respond to those types of requests. So that's been an exciting area for us. And then there's still the SEC requirements to monitor broker dealers and conversations with end users, to ensure they're not doing anything, they shouldn't be doing like insider trading, >> Right. Which is so different, than kind of a post event, you know, kind of forensics investigation, and then collecting that data. So I'm curious, you know, how often are you having to update policies and update, you know, kind of the sniffers and the intelligence that goes behind the monitoring to trigger a flag, And then that just go into their own internal kind of compliance reg and set off a whole another chain of events? I would imagine. >> Yeah. I mean, there's a lot of things we can do with our classification policies. And like, in the case of the COVID policy, we just kind of crowd source that internally, and created a policy, in about a week, really. That we, you know, we shaped the basic policy and then kept refining it, refining it, testing it. And we were able to go from start to finish, and have it publicly available within about a week and a half. It was really a great effort. And we have that kind of ability to be very nimble, to react to different types of regulations as they become, you know, get out there. And then there's also a constant refining of even data privacy for every country that we support. You know, we have data privacy regulations for the entire European union and for most countries around the world, obviously the US, Canada, Australia, and so on. And, you can always make those policies better. So we've introduced feedback loops where our customers can give us feedback on what works and what isn't working, and we can tweak the policies as needed. But it is a great way to respond to whatever's going on in the world, to help our customer base, which, you know, is largely the financial verticals, the public sector verticals, but even healthcare is becoming more important for us. >> So Dave, I wonder if there's some other use cases that people aren't thinking about, where you guys have seen value in this type of analytics. >> Yeah, I mean, definitely the one thing that I think is just starting to emerge as the value that's inherent in communications. So I mentioned earlier the telemedicine idea, and, you know, can you learn from doctor-patient interactions if you're capturing them over telemedicine vehicles, you know again, Video Chat, Zoom, and that sort of thing. But similarly, if you've captured communications for a long time, as many of our customers have, what can you do with that data? And how can it feed into a broader data lake to give you new insights? So for example, if you want to gauge whether a major deal is about to close, you know, you can rely on your sales reps to populate the CRM and give you an indication it's 10% complete, it's 50% complete, whatever. But you're dependent on all the games that salespeople play. It would be far better to look at the pattern of a traditional deal Closing. You know, first you start out with one person at your company talking, to one person at the target customer that leads to meetings, that leads to calendar invites, that leads to emails being sent back and forth. You can look at the time of response, how quickly does the target customer respond to the sales rep? How often are they interacting? How many people are they interacting with? Is it spanning different GEOS? Is it spanning different groups within the company? Are there certain documents being sent back and forth, like, a quote for example. All of this can give you a higher confidence that that deal is going to close, or that deals failing. You don't really know. You can also look at historical data, and compare the current account manager to his predecessor. You know, does the current account manager interact with his customer as much as the former rep did? And is there a correlation in their effectiveness? You know, based on kind of their interactions, and their just basic skills. So I think that's an exciting field, and it shines a new light on the data that you have to collect, to comply with regulations, the data you have to collect for litigation and other reasons. Now there's other value there. >> Right. That's a fascinating story. So the reason that you guys would be involved in this, is because you're sitting on, you're sitting all that comms data, because you have to, for the regulation. I mean, what you're describing sounds like a perfect, you know, kind of sales force. Plug in. >> Absolutely. >> With a much richer dataset, versus as you said, relying on the sales person to input the sales force, information which would require them to remember their password, which gets reset every three weeks. So the chances of that are pretty slim. (laughs) >> Yeah. There's a fact, I think I've read a stat recently that about, you know, only 10% of information is actually captured in a CRM. You know, contact information and that sort of thing. But if you're looking at their emails, if you're looking at their phone calls and their texts, and that sort of thing, you get a rich set of data on contacts and people that you're interacting with at a target customer, and, you know, sales. More than any other job, I think sales has high turnover. And so you need that record of, you know, off the counter. One account rep leaves, you don't want to lose all their contacts and start over again. You want a smooth handover to the next person. >> Right. >> If you capture all that content from their communications into CRM, you're in great shape. >> Dave, I want to get your take on something that's happening now, because you're so dialed into policy, and policy and regulations, which are such a giant determinant of what people can and should and should not do, with data. When you take something like COVID and the conversations about people going back to work, and contact tracing. To me it's like, Wow! You know, it's kind of this privacy clash against HIPAA, and, you know, that's medical information. And yet it's like this particular disease has been deemed such that it kind of falls outside the traditional, you know, kind of HIPAA rules. They're not going to test me for any other ailments before I come in the door at work, but they, you know, eventually we're going to be scanning people. So, you know, the levels of complexity and dynamicism, if that's even a word, around something like that, that's even a one off, within a specific, you know, kind of medical data is got to be, you know, I guess, interesting and challenging, but from a policy perspective and an actual handling of that information, that's got to be a crazy challenge. >> Yeah. I mean, we do expect that COVID it's going to lead to all kinds of litigation and Freedom of Information Act request. And that's a big reason why we saw the importance very quickly, that we need a classification policy to highlight that content. So what we can do in this case is we can, first of all, identify where that content is stored. We have a product called data insight that can monitor your file system and quickly locate. If you've got a document that includes, you know, patient data or anything related to COVID-19, we can find that. And now as we bring in the communications, we can flag communications, as we archive them and say, this is related to COVID-19. Then when a litigation happens, you can look, you can do a quick search and you can filter on the COVID-19 tag. And the people you're concerned with, and the date range you're concerned with, you can easily pull in all of the communications, all of the file content, anything related to COVID-19. And this is huge for, again, for public sector, where there are subject to finance, you know, sorry, Freedom of Information Act request. But it's also going to affect every company, because like, it's going to be litigation around, when a company decided that they would work from home, and did they wait too long. You know, and did someone get sick because they weren't aggressive enough. There's going to be frivolous lawsuits, there's going to be more tangible lawsuits, and, there's going to be all kinds of activity around how stimulus funds were spent and that sort of thing. So, yeah. That's a great example of a case where you've got to find the content quickly and respond to requests very quickly. Classification go a long way there. >> Yeah. That's the lawyers have hardly gotten involved in this COVID thing yet. And, to your point, it's going to be both frivolous as well as justified. And did people come back too early? Did they take the right steps? It's going to be messy and sloppy, but it sounds like you're in a good position to help people get through it. So, you know, just kind of your final thoughts you've been in this business for a long time. The rate and pace of change is only increasing the complexity of veracity, stealing some good, old, big data words. Velocity of the data is only increasing, the sources are growing exponentially. You know, as you kind of sit back and reflect obviously, a lot of exciting stuff ahead, but what do you think about what gets you up in the morning beyond just continuing to race to keep up with the neverending see of changing regulatory environment? >> Yeah, that's a great question. I mean, I think we have a great portfolio that can really help us react to change, and to take advantage of some of these new trends. And that is exciting, like telemedicine, the changes that come with COVID-19, what we could do for telemedicine rating doctors gauging their performance. We could do the same sort of thing for tele-education. You know, like I have two kids that have had, you know, homeschooling for the last three months, and, probably are going to face that in the fall. And, there might be some needs to just rate how the teachers are doing, how well are the classes interacting, and what can we learn from best practices there. So I think that's interesting and interesting space as well. But what keeps me going is the fact that we've got market leading products in archiving, eDiscovery, and supervision. We're putting a lot of new energy into those solutions. They've been around a long time. We've been archiving since 1998 I think, and doing supervision and discovery for 20 years. And, it's strange, the market's still there, it's still expanding, it's still growing. And, it's kind of just keeping up to change and, trying to find better ways of surfacing the relevant human communications content that said that's kind of the key to the job, I think. >> Right. Well yeah, Finding that signal amongst the noise is going to get increasingly... >> Exactly. >> More difficult than has been kind of a recurring theme here over the last 12 weeks or 15 weeks, or however long it's been. As you know, this kind of light switch moment on digital transformation is no longer, when are we going to get to it, or we're going to do a POC or let's experiment a little bit, you know, here and there it's, you know, ready, set, go. Whether you're ready or not, whether that's a kindergarten teacher, that's never taught online, a high school teacher running a big business. So nothing but a great opportunity. (laughs) >> Absolutely. >> All right. >> Absolutely. I mean, it's a very, a changing world and lots of opportunity comes with that. >> All right. Well Dave, thank you for sharing your insight, obviously regulation compliance, and I like that, you know, data supervision is not just backup and recovery is much, much bigger opportunity, in a lot higher value activity. So congrats to you and the team. And thanks for the update. >> All right. Thank you, Jeff. Thanks for the time. >> All right. He's Dave and I'm Jeff. You're watching theCUBE. Thanks for watching, we'll see you next time. (upbeat music)

>> From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Hi, I'm Stu Miniman, and welcome to a CUBE conversation. Always love when we can dig into practitioner discussions, and one of the editorial themes I've been really looking into in 2020 has been discussion of server lists. So really excited to welcome to the program, Dave Anderson, he is director of technology at Liberty Mutual, coming to me from Ireland. Dave, thanks so much for joining us. >> Thank you Stu, delighted to be here. >> All right, so I think most of our audience is probably familiar with Liberty Mutual. You work in the software group, Liberty IT, as part of Liberty Mutual. If you could just start us off, give us a little bit about your background, and your group's role inside the organization. >> Sure, Liberty IT started 20 years ago as really sort of an internal software host. Part of the Liberty Mutual group, we're part of Liberty Mutual Technologies. So we kind of work across all the markets in Liberty Mutual and all the kind of global locations. My role as director of technology is really think about what's the technical direction of Liberty IT? I can lead the architects with my group and really thinking about global architecture of Liberty Mutual and how can we provide business value in the mission going forward. >> Excellent, so Dave I guess what is the just kind of overall business and IT relationship? When I think of companies like yours, usually MNA comes in their growth expansions and digital transformation's been one of those buzzword discussions. But absolutely you need to be close to your customers there's lots of services that you need to provide online. How are some of those overall dynamic impacting how IT is supporting the business? >> That's a great question Stu. I mean technology has always been a key differentiator in Liberty Mutual. Even as my group was setup, like I said 20 years ago. It was always seen as a differentiator as something that we can be very good at. We've always been quite close to be in the cutting edge of technology. Many companies would say, "We're not an insurance company, we're a technology company that sells insurance." We are an insurance company, that's very important but we also need to understand that using the latest technology i.e. the cloud providers, really helps us deliver value to our business partners and customers. It is critical that we have a very tight partnership with our business partner. >> Excellent so yeah 20 years, a lot has changed in that time. Give us a little bit if you can, share a snapshot of where you are kind of in the cloud discussion. And what are the relationships between kind of the infrastructure side of the team and the development side of the team? And excepting that'll lead us forward to the server discussion. >> Sure I mean I joined Liberty about 12 years ago, 13 years ago and I actually started in one of the digital channels, that existence of digital channels. And probably almost 10 years ago our CEO James McGlannan quite a visionary, started kind of pressing the public cloud agenda and we started discussing public cloud as a potential future. It was a really exciting time. Cause I think the infrastructure development we all are in, gosh what's the possibilities of public cloud. And as you know the cloud itself it probably changes every year, it's redefined, there's new capabilities. I'm not sure we could envisage where we are today back when we started that conversation. Like every large enterprise, the initial conversation's around how do we enable this? How do we make this safe? How do we protect our data? All the usual kind of questions you would have. But in a way we kind of really joined together the very different departments. We thought, well how do we move the enterprise forward? And as well I mean we want to get a global capability for cloud was very important. And bringing up the velocity that we can deliver value quickly to our business partners. We didn't do it for technology's sake we did it to contribute real value for the business. And one of the really interesting things that we talked about is we shied away from counting how many virtual machines do we have in the cloud. That wasn't really a good metric for us. How are we delivering value to your business partners? That was kind of the metric that we chased and continue to chase. >> Well that's excellent how you kind of laid that out. I'm wondering if you could help extend that and bring us into where serverless fit into that discussion. I loved how you say it's not about number of VM's or the new shiny thing. So, what was it that led to your first use of serverless? And bring us a little bit along that journey that you've been going through. >> Sure, well one of the things that I've always found critical working in technology is that curiosity. But in a search for what's next. So, within micro IOS charts my people will say, "Where do we need to get to? What is 3 to 5 years out?" And we've a lot of really fantastic peers right across Liberty Mutual. Bright, open minded, they can think ahead. So one of my team was at I think it was re:Invent in I think it was 2013, where the launched Lambda for 2014. And each my crew were excited. They can build their first small application. It was actually a document generation. I think they were using some propriety systems. So they built a document generation solution. I couldn't believe the amount of ROM cost that was saved. It probably knocked something like 97% off the cost. Couldn't believe it. And we started saying, "Wow this is potential." But back then, again 5 or 6 years ago the stack was very immature. There was a lot of things you needed to figure out. Like the observability, the developer environment. There's a whole bunch of stuff that wasn't quite right. So it's something that we shared to our peers across the organization. We talked about it. We really started to kind of think, "Well this is interesting, this idea of serverless or manage servers." It started to really change how we thought and it really started to make the concept of a cloud native application very real. Cause we started to think of cloud native architecture loaded into application architecture. And that started to really flip how we thought. So it's just been a real journey these past couple of years. And a big thing for me is we started with engineers thinking of cloud as a mindset not necessarily as a platform. That opened the door to a lot of possibilities. >> Yeah, that's really interesting that you said that. Often times we say cloud is an operational model not a physical location. Are you using multiple clouds today? >> Yes, we probably tend to have a multi cloud strategy. And really to be very clear, serverless for us it's not just functions of service. Its not saying, "We're just using kind of something like Lambda." It's really about that idea using managed service. Thinking about evolution of architecture. How can we kind of try and cut out anything that is actually not differentiating? There's a great term which I always like is the stack policy is sometimes a technology companies we get obsessed by the stack. We think that the piece near the customer is quite easy. But think from the technology perspective we need to think about, we can deliver the most value by making the customer experience kind of best. And it can be even ramp the stack from whoever we need. >> Yeah, no, its a fascinating discussion. I've seen even today. You say serverless functions as a service. A lot of it is I don't want the developer to have to think about those underlying layer. Which reminds me of the discussion we've been having about platform as a service for more than a decade but PaaS was supposed to be platform independent. So I could have my code where ever it goes. Serverless today, right now we've talked about Lambda, Amazon there's certain things that I could only do on Amazon. There are discussions and working groups and the cloud data computing foundation. Working on how we can do serverless functions as a service that could expand between multiple clouds or use the same sort of code. So how do you look at that space? You talk about cloud native. How do you make sure that you're leveraging the technologies of the specific cloud but I guess I'll throw out not being locked into any one provider? >> I think about it for me it starts with the empowerment of the engineering team. We talk about a serverless first strategy that means that we've got the capability to build anything you need to. But to rent where you can. We had a fascinating story one of our best stories is a company called Workgrid. Workgrid Software is one of the companies that we spun out of Liberty Mutual. That was a project that we had an internal digital assistant that we built with some of our teams, it'd be back 4, 5 years ago. And our CEO James McGlannan decided to fund that as a kind of a startup. They broke off around 3 years ago and that initial team had 4 people in that engineering team. So they kind of decided that they would be serverless first in their approach. They didn't have time to think about operability or rights for portability. They had to realize business value really quickly. So they took a evolutionary architectural approach which meant they kept incrementing and iterating delivering value where possible. What's the next best thing that they can build to deliver value to the customer? So when you think in that regard, if you ever come to an Amazon of a grid, no one way doors, keep the two way doors. Don't lock yourself into anything. Make decisions that you can always build upon. So with that kind of constant iterative work our teams and that's serverless first strategy. It means that when you do rent the service if you need to change to another service it's just a matter of if you've your boundaries set up practically, it's very easy to get out of that. You dig yourself in deep to something, that's the difference. So I think there's an engineering mindset and culture that we certainly have proudness in our teams. But they kind of go fast, focus on business value and try and be sort cloud native in their outlook. >> Excellent, yeah, I just heard Andy Jassy in the AWS Summit online talking about those one way door. So sounds like from your standpoint, serverless is a two-way door for architecting in your mindset? >> Absolutely, I mean I think really for me it brings architecture back into the team. It's one of the really nice things is if your team use managed services that focus is on business value. If our infrastructure is set up to support that type of team then you have minimal hand offs within the team. Through the single team, its their job to create value, engineer the solution, make sure the security is good enough, build the operation, the visibility it's all contained within one team. We get a huge responsibility from that one team. As an engineer that is super powerful, super huge autonomy. So we can talk with the serverless engineer and for me it's been absolutely fascinating to see teams come into this environment and once they understand that event driven way of creating their systems. And I use the words systems rather than applications to create event driven systems they're constantly building upon. It's just fascinating to see where they go. You start to see the creativity and innovation of the engineers. So its truly unbelievable to watch. They're really very cool. >> Dave, I'm curious when you look at the application portfolio that your team manages, how do you decide what goes serverless? Is it new development all goes serverless? Has there been a migration? How do you look at the overall application portfolio that you have? >> It kind of depends I suppose on, I'm not going to sit here and say that we're going to refactor everything to serverless. I think when you do a migration there's usually six or seven paths you can go down and you do what's best for the business. But for new development, it's definitely interesting we haven't found many used cases that are really a bad fit. It's a spectrum we may decide what different servers to use. We built a system last year which was absolutely fascinating to see. It's like a a financial aggregation system where we do a lot of our accounting. So it was kind of serverless ETL, we're trying to do like an end of month batch system to detect a lot accounts from different countries and kind of pipe them into a kind of general ledger. Not something I would've thought about for serverless, to be honest. But then when you think about it and some of our engineering leads they have put this together. They can design this fantastic system using serverless workflows. Cause you're taking lots of various different types of data orchestrated in a single destination. And we put live in that this year and I think one of the monthly ends that they recently ran I think they ran something like 100 million transactions. Relatively low cost and of course being a month end system the rest of the months there's zero cost. You don't pay for idle. We only actually pay for wireless roaming in that month end process for maybe like FDRs or something. >> Dave, you talked about the early days 2014 when Lambda was announced, re:Invent, when you first started using it in the first year or so. There's the maturity of that ecosystem solutions set. Where do you see things now? What's working well? What's on your wishlist? Kind of mature or increase overall functionality to help? >> I think that the developer environment and developer experience is a big part. One of the key messages in trying to kind of get into our culture is code is a liability. It's not an asset. If you have a bunch of engineers writing lots of code that in fact is a liability. There's no business asset in that. The asset is in the system that you create. Trying to get engineers into the mindset to write less code and they actually engineer systems. So one of the things we've been trying to do is maybe using patterns as building blocks. People became kind of like a Lego building block way of creating their systems. Piecing somethings like CDK code development kit patterns. Using the world architect process to make sure that teams are looking after their cost, their security, their performance, their liability, and their kind of optimizations. Some of those things are really important in that whole ownership of an operational view of their systems. And also even things like observability. When you create a system with a lot of events laying around it starts getting complex. But then if you do it correctly you can start to layer on well, what better insights can we build on top of the system? So it's really opening up teams a different way of working. And then of course there's lots of operational challenges when you get into more complex environment. So as we often say, it's not easier, different, built difficulty building systems, but it's different, that's what's definitely easier but better. >> All right, how about anything that you're looking out towards the future? You talked about the early days when you look at these and while you're not necessarily throwing the latest shiny thing into production, there's that curiosity. So what's exciting you now? Anything else kind of looking forward that you prepare? >> I think one of the fantastic success stories we've had is with a project we call Virtual Assistant. And really to answer your question, its about how teams can properly work at MVP. So, one of the things that we really find fascinating is when you put a good engineering team. And I mean a team who you're really solid engineers you then layer on the cloud and security best practices and verification. We then put them in a coded serverless environment with real business problem. They then create a MVP. You're virtual assistant in, raises an MVP. So if you call into a call center and you have a fairly straightforward request, like if you have an auto claim you might say, "Well when can I pick up my ramp bill?" If you already done your claim. We have an NLP a natural language assistant that can help you with that conversation. So when you start with an MVP system like that you can start them off at a fairly small traffic, until you actually tune that until it's kind of perfect. And then you gradually scale up and add on other data driven potential AI services, integrations to that. So I think when you start to take the MVP approach, and have a very, very novel solution see what that's like in the wild and then start to scale out. We scale that system for taking maybe 30 calls maybe taking about a quarter on your calls. It's fantastic how you can start to scale these system up. Well I think what I'm really looking for is more kind of support to see how we can you know, it's the art of the possible. How can we use this skillset and this serverless mindset to create really fascinating business applications. Because when you get under that kind of creative conversation with business partners, I mean they don't want to hear about Lambda or events or observability. They want to say, "Well, what can I do with AI? What can I do with Voice, what can I do with Vision?" So we start to open up really fantastic conversations like that. So I'd like to see more of that, but in a creative product development. >> Excellent, well yeah Dave, so important that you brought back as to how IT in the business. Working together, it's not about the technical widget or knobs or anything. But the services and the value that ultimately you can provide for the business and the impact that has on your ultimate end customer. All right, Dave, thanks so much. Real pleasure having a chat with you. >> Thanks Stu really appreciate it, thank you. >> All right, be sure to check out theCUBE.net. Lots of backgrounds, if you go hit the search, you can actually type serverless, find out more about what we've been covering as well as what events we will be at in the future. I'm Stu Miniman and thank you for watching theCube. (gentle music)

(energetic music) >> Announcer: From our studios in the heart of Silicon Valley, Palo Alto, California, this is a Cube Conversation. >> Hi, welcome to our Palo Alto, California studios for another Cube Conversation, where we go in depth with thought leaders about some of the most pressing topics of the day in business and technology. I'm your host Peter Burris. One of the biggest challenges that any company faces is how to get more out of their people, even though we are increasingly distributed, we are increasingly utilizing digital means to interact and work together, and we are increasingly trying to do this with customers and with other third parties that are crucial to making business work, profitable, and grow revenue. A number of things have occurred in the last few years that are actually making it possible to envision how we can be more distributed and yet be more productive. And one of the most important ones is the use of video as a basis for connecting people. How're we going to to do that? Well, to have that conversation, we're here with David Maldow who's the CEO of, Let's Do Video. David, welcome to theCUBE. >> Hey, thanks for having me Peter, appreciate it. >> So, tell us a little bit about, very quickly, about, Let's Do Video, and then let's jump into it. >> Sure. Let's Do Video's, a boutique analyst blog on www.letsdovideo.com. We cover everything having to do with remote technology, anything that allows teams to be more productive whether they're working together or working across the country. >> All right, so in your name is, "video." Let's identify some of the key trends. What really is making it possible to utilize video in this way today where it really was nothing more than a promise made, put forward by a lot of companies 10 years ago. >> I think, well, there's been a lot of factors, but big part of that has been the cloud. A few years ago we had the big cloud software revolution in video conferencing. Before then you had to buy these expensive video appliances to have them at your workplace, and you really needed a team of experts to run them. By running the video in the cloud, all we need is our apps on our phones, and apps in our meeting rooms. And it makes it a lot easier, and it made it a lot more affordable. So, now it's available for everyone, and it was just a matter of whether we were ready for it, and appears that we are. >> So, we're getting the service that we need without having to worry about the technology that's required, the formats that are being employed, the operational complexities associated with video. Have I got that right? >> Yeah, actually there was a long list of reasons we weren't using video. Analyst like myself looked at the video conferencing industry and said, "Guys, you need to fix all of these things "or no one's going to use it. "It needs to be easier, one click to join. "It needs to be more affordable." The stuff was expensive. Needs to be reliable. Balls were dropping. It needs to use less bandwidth. It was taking over our networks. All of these things it needed to be, and they fixed all of that. And we promised if they fixed all of that, people would start to use it. Now we are seeing an absolute explosion in the market of people taking these apps into the workplace and actually using them. >> It seems to me, David, I want to get your take on this. That some of the early suppliers of some of these video related services were treating it largely as a means to an end, and typically that end was, what type of things can we put in the marketplace that's going to increase the amount of network bandwidth that's required so we can sell more networking equipment, or sell more networking services? Let me ask you a question. Because that has been fixed by utilizing the cloud. Does it now mean that we are getting a whole bunch of new technology companies that are stepping into the market place to provide video services as the end itself? And that's leading to better engineering, better innovation, and better customer experience? >> That's exactly what happened. We went from a top-down adoption model, to a ground-up adoption model. And what I mean by that is. It used to be a top-down thing, where these video conferencing companies would go talk to the CEO or CTO of a big company and do an amazing demo in the meeting room, and say, "look at this amazing video quality that you get." And they would show these studies that people like me help write (laughs), showing that if you do use video you'll be more productive. If you do use video you'll have more impact, and if you do use video you'll get all these benefits. So, buy this expensive stuff and then force your people to use them. And that didn't work 'cause they bought the stuff, and they tried to force people to use them. But, like we talked about, it was complicated. it was inconvenient. Now what's happening is, instead of the top-down we're getting the bottom-up. We're getting people walking into the workplace saying, "I'm using this app. I'm using this app. "I need video to talk to my teammates." And the boss CEO has to say, "Okay, okay, we'll accommodate that. "Don't use the consumer apps, though. "Let us find a nice business app that's secure for you." So instead of having, "You should use this "'cause we were sold on it." We're having a great new cloud video industry that's saying, "oh, let's give you what you want." >> So, when adoption happens from a bottom-up stand point, it means that the benefits have to be that much more obvious to everybody, otherwise, you don't get the adoption. So, what are some of the key productivity measures that this rank and file, this ground swell of interest in these technologies, are utilizing to evaluate and to judge how they want to use video within their business lives, workflows, engaging the customers, etc. >> For a long time it was just anecdotal. It just seemed obvious, if you, we all know that when you have a face-to-face meeting you get the work done. If it's a phone call, "oh, I'll explain to them why it's not done." We all know things get done more effectively in meetings. We all know a face-to-face meeting can last 20 minutes and get the work done. While a phone call can go on for hours. But now that we are starting to use it, instead of anecdotal, we're actually getting real data. Companies are reporting that they use to have a... Their web app development team used to take eight weeks before every release. Now they're doing it every six weeks. We're seeing real results. Frost & Sullivan, a big analyst firm in the space recently came out with some statistics. A survey of CEOs, CTOs, and they reported that using video among their team accelerated decision making. 86% of them agreed with that, 83% that agree, that it improves productivity, that's massive. 79% said it boosts innovation. So not only people getting more work done, more leading work, getting ahead of the competition, coming up with new things. And this is a huge one, 79%, this is self-reporting, believe that it improved their customer experience. We know, you know, the customer relationship is everything in sales. >> Why? >> Now we're actually measuring the results. >> Why is that, what is it about video that is so important to allowing us to not only accelerate workflows and achieve the outcomes, but also as we take on more complex workflows, even as we distribute work greater, what is it about video that makes the difference? >> There's a lot to it. I think a lot of it is that human connection. It's really hard to focus on a phone call. You lose track, I mean, you know, one of the reasons that my I named my company "Let's Do Video" is 'cause I'd be on the phone with a partner, a colleague, a teammate, and I'm like, "is he or she checking her email? "Did you hear, do I have to repeat what I just said?" We need to get work done, let's do video. And I think teams across all industries are finding that out now. Once they get on video, the work just gets done. >> But it's not just that they're on video, it's that they're utilizing video as a way of connecting with each other. That you can see whether or not somebody's paying attention to you at the most simple level. You can also register whether or not someone is a little bit agitated with what you're saying, even though you may not hear that on the phone. But video is being utilized as a way of adding to how other work gets done. It's not like we're suddenly, you know, putting a whole bunch of presentations up in the video. We're looking at faces, we're listening to people. We're having a connection as we work in other medium. Have I got that right? >> Exactly, yeah. I used to... When video conferencing first hit the scene 20 years ago, we were marketing it as a replacement for travel. Instead of flying across the country for that big meeting, you do it over a video. And what we realized is you still need to travel for that really, really big meeting once or twice a year, you still get on a plane. Video conferencing isn't getting rid of that niche meeting. It's not fixing that one big meeting, It's not cutting your travel costs. It's upgrading the phone call. It's upgrading the text message, the imChat. It's upgrading the e-mail. It's becoming, like you're saying, a part of how we're normally working. And it's changing the way remote workers see their teams. Let's Do Video, my team is completely remote. I've never met one of my teammates in person till we were two or three years in. We met up at an airport and said, "oh my God, I actually get to see you in three dimensions! "It's amazing!" And if we had started this company 10 years ago, I would say, I don't really have a team. I'm a sole guy, it's all me, I have some contractors. I send them an email, and a month later, they send me the result. But with video, I have a team, there's accountability. We're friends, we know what's going on with each other's lives. And there's a lot more motivation there, because instead of just, "Hey, you're my graphics person, "get this graphics for me. "You're my web person, fix the thing on the site." My colleagues, they're part of the team, and they want the company to succeed, 'cause they look at me in the face and they say, "I got this project done!" They feel good about it. It's a lot more of an investment, and it sounds like happy fluffy stuff, but it affects your bottom line. I don't think my... I know my company would not be as successful if I did not regularly meet with my team over video. >> Well, who doesn't want (laughing) a little bit of happy fluffy stuff every now and then? It's nice to bring a smile to your job. Let's pivot a little bit and just talk about the difference between internally to now externally. Because one of the other things that a lot of these video conferencing solutions offered, was they offered the opportunity to connect with video on a single network, your company's network with specialized end points. Now we're talking about trying to find new ways to enhance the experience that sales people have, service people have. Utilizing video to engage customers, to drive new types of experience, to drive new forms of revenue. How is video starting to alter the way we engage not just internally but also externally? >> That's more starting to happen than already happening. I think video in the workplace is becoming just a normal thing. I meet with my team over video. We're still finding ways to engage our externals. But the drive is definitely there, because we're seeing the results from working with our teams, and we know the impact. I think anyone in sales, they'll do anything to get that face-to-face meeting. They'll do anything to get you to come into their office or let you into their office to sit down. If you give a salesperson a choice between face-to-face or a phone call. That salesperson wants to be face-to-face. So, as we're getting the technology to make it easier for customers to get face-to-face with us, and partners, and externals. The demand will be there, and what's great is that the cloud enables that. The real problem is, like you said, they were on our own network. So, if I wanted to talk to a customer or a partner, I had to open a hole in my firewall, and let someone else into my network, and my IT people would go crazy. Now, the call's hosted up on whatever video conferencing company's cloud, it's safe. So, we're ready for that sort of thing. >> Lot of changes, lot of opportunities, tremendous potential. The types of changes we see in five years are going to dwarf the changes we've seen in the last five years. Again, as folks get used to using video internally, they're going to start demanding it as they engage each other externally as well. David Maldow, CEO of, Let's Do Video. Thanks for being on theCUBE. >> Thanks so much, this was fun. >> And once again, I'm Peter Burris. Until next time, thanks for watching. (upbeat music)

(gentle upbeat music) >> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright upbeat music) >> We're back in Barcelona at the Fira. My name is Dave Vellante. I'm here with David Nicholson. We're live at MWC23, day four of the coverage. The show is still rocking. You walk the floor, it's jamming. People are lined up to get in the copter, in the right. It's amazing. Planes, trains, automobiles, digitization of analog businesses. We're going to talk private wireless here with Dell. Sarvesh Sharma, the Global Director for Edge and Private Mobility Solutions practice at Dell. And John McCready is a Senior Director for 5G Solutions and product management at Dell Technologies. Guys, good to see you. >> Likewise, likewise. >> Good to see you too. >> Private wireless. It's the buzz of the show. Everybody's talking about it. What's Dell's point of view on that? >> So Dell is, obviously, interested entering the private wireless game, as it's a good part of the overall enterprise IT space. As you move more and more into the different things. What we announced here, is sort of our initial partnerships with some key players like Airspan and expedo and AlphaNet. Players that are important in the space. Dell's going to provide an overall system integration solution wrap along with our Edge BU as well. And we think that we can bring really good solutions to our enterprise customers. >> Okay, I got to ask you about AlphaNet. So HPE pulled a little judo move they waited till you announced your partnership and then they bought the company. What, you know, what's your opinion on that? You going to, you going to dump AlphaNet, you're going to keep 'em? >> No. >> We're open Ecosystem. >> Yeah, it's an open ecosystem. We announce these are our initial partners, you know we're going to announce additional partners that was always the case. You know, there's a lot of good players in this space that bring different pros and cons. We got to be able to match the solution requirements of all our customers. And so we'll continue to partner with them and with others. >> Good, good answer, I like that. So some of these solutions are sort of out of the box, others require more integration. Can you talk about your, the spectrum of your portfolio? >> So I'm glad you brought up the integration part, right? I mean, if you look at private wireless, private mobility it is not a sell by itself. At the end of the day what the enterprise wants is not just private mobility. They're looking for an outcome. Which means from an integration perspective, you need somebody who can integrate the infrastructure stack. But that's not enough. You need somebody who can bring in the application stack to play and integrate that application stack with the enterprises IT OT. And that's not enough. You need somebody to put those together. And Dell is ideally suited to do all of this, right? We have strong partners that can bring the infrastructure stack to play. We have a proven track record of managing the IT and the enterprise stack. So we are very excited to say, "Hey, this is the sweet spot for us. And if there was a right to win the edge, we have it." >> Can you explain, I mean, people might be saying, well, why do I even need private wireless? I got Wi-Fi. I know it's kind of a dumb question for people who are in the business, but explain to folks in the audience who may not understand the intersection of the two. >> So, yeah, so I think, you know, wireless is a great techno- pardon me, Wi-Fi is a great technology for taking your laptop to the conference room. You know, it's effectively wireless LAN Where private 5G and before that private LTE had come into play is where there's a number of attributes of your application, what you're using it for, for which Wi-Fi is not as well suited. And so, you know, that plays out in different verticals in different ways. Either maybe you need a much higher capacity than Wi-Fi, better security than Wi-Fi, wider coverage like outdoor, and in many cases a more predictable reliability. So cellular is just a different way of handling the wireless interface that provides those attributes. So, you know, I think at the beginning, the first several years, you know Wi-Fi and 5G are going to live side by side in the enterprise for their different roles. How that plays out in the long term? We'll see how they each evolve. >> But I think anybody can relate to that. I mean, Wi-Fi's fine, you know, we have our issues with Wi-Fi. I'm having a lot of issues with Wi-Fi this week, but generally speaking, it works just fine. It's ubiquitous, it's cheap, okay. But I would not want to run my factory on it and rely on it for my robots that are shipping products, right? So that really is kind of the difference. It's really an industry 4.0 type. >> Yeah, exactly. So I mean, manufacturing's an important vertical, but things of energy and mining and things like that they're all outdoor, right? So you actually need the scale that comes, with a higher power technology, and even, you know just basic things like running cameras in a retail store and using AI to watch for certain things. You get a much better latency performance on private 5G and therefore are able to run more sophisticated applications. >> So I could be doing realtime inference. I can imagine Dave, I got an arm processor I'm doing some realtime inference AI at the Edge. You know, you need something like 5G to be able to do that, you can't be doing that over Wi-Fi. >> Yeah >> You nailed it. I mean that's exactly the difference, right? I mean if you look at Wi-Fi, it grow out from a IT enabled mode, right? You got to replace an ethernet. It was an IT extension. A LAN extension. Cellular came up from the mode of, "Hey, when I have that call, I need for it to be consistent and I need for it to be always available," right? So it's a different way of looking at it. Not to say one is better, the other is not better. It's just a different philosophy behind the technologies and they're going to coexist because they meet diverse needs. >> Now you have operators who embrace the idea of 5G obviously, and even private 5G. But the sort of next hurdle to overcome for some, is the idea of open standards. What does the landscape look like right now in terms of those conversations? Are you still having to push people over that hump, to get them beyond the legacy of proprietary closed stacks? >> Yeah, so I think I look, there are still people who are advocating that. And I think in the carrier's core networks it's going to take a little longer their main, you know macro networks that they serve the general public. In the private network though, the opportunity to use open standard and open technology is really strong because that's how you bring the innovation. And that's what we need in order to be able to solve all these different business problems. You know, the problems in retail, and healthcare and energy, they're different. And so you need to be able to use this open stack and be able to bring different elements of technology and blend it together in order to serve it. Otherwise we won't serve it. We'll all fail. So that's why I think it's going to have a quicker path in private. >> And the only thing to add to that is if you look at private 5G and the deployment of private LTE or private 5G, right? There is no real technology debt that you carry. So it's easy for us to say, "Hey, the operators are not listening, they're not going open." But hey, they have a technical debt, they have 2G, 3G, 4G, 5G, systems, right? >> Interviewer: Sure. >> But the reason we are so excited about private 5G and private 4G, is right off the bat when we go into an enterprise space, we can go open. >> So what exactly is Dell's role here? How do you see, obviously you make hardware and you have solutions, but you got to open ecosystems. You got, you know, you got labs, what do you see your role in the ecosystem? Kind of a disruptor here in this, when I walk around this show. >> Well a disruptor, also a solution provider, and system integrator. You know, Sarvesh and I are part of the telecom practice. We have a big Edge practice in Dell as well. And so for this space around private 5G, we're really teamed up with our cohort in the Edge business unit. And think about this as, it's not just private 5G. It's what are you doing with it? That requires storage, it requires compute, it requires other applications. So Dell brings that entire package. There definitely are players who are just focused on the connectivity, but our view is, that's not enough. To ask the enterprise to integrate that all themself. I don't think that's going to work. You need to bring the connectivity and the application to storage compute the whole solution. >> Explain Telecom and and Edge. They're different but they're like cousins in the Dell organization. Where do you guys divide the two? >> You're saying within Dell? >> Yeah, within Dell. >> Yeah, so if you look at Dell, right? Telecom is one of our most newest business units. And the way it has formed is like we talk Edge all the time, right? It's not new. Edge has always been around. So our enterprise Edge has always been around. What has changed with 5G is now you can seamlessly move between the enterprise Edge and the telecom Edge. And for that happen you had to bring in a telecom systems business unit that can facilitate that evolution. The next evolution of seamless Edge that goes across from enterprise all the way into the telco and other places where Edge needs to be. >> Same question for the market, because I remember at Dell Tech World last year, I interviewed Lowe's and the discussion was about the Edge. >> John: Yep. >> What they're doing in their Edge locations. So that's Edge. That's cool. But then I had, I had another discussion with an agriculture firm. They had like the massive greenhouses and they were growing these awesome tomatoes. Well that was Edge too. It was actually further Edge. So I guess those are both Edge, right? >> Sarvesh: Yeah, yeah, yeah. >> Spectrum there, right? And then the telecom business, now you're saying is more closely aligned with that? >> Right. >> Depending on what you're trying to do. The appropriate place for the Edge is different. You, you nailed it exactly, right. So if you need wide area, low latency, the Edge being in the telecom network actually makes a lot of sense 'cause they can serve wide area low latency. If you're just doing your manufacturing plant or your logistics facility or your agricultural growing site, that's the Edge. So that's exactly right. And the tech, the reason why they're close cousins between telecom and that is, you're going to need some kind of connectivity, some kind of connectivity from that Edge, in order to execute whatever it's you're trying to do with your business. >> Nature's Fresh was the company. I couldn't think of Nature's Fresh. They're great. Keith awesome Cube guest. >> You mentioned this mix of Wi-Fi and 5G. I know it's impossible to predict with dates certain, you know, when this, how's this is going to develop. But can you imagine a scenario where at some point in time we don't think in terms of Wi-Fi because everything is essentially enabled by a SIM or am I missing a critical piece there, in terms of management of spectrum and the complicated governmental? >> Yeah, there is- >> Situation, am I missing something? It seems like a logical progression to me, but what am I missing? >> Well, there is something to be said about spectrum, right? If you look at Wi-Fi, as I said, the driver behind the technology is different. However, I fully agree with you that at some point in time, whether it's Wi-Fi behind, whether it's private 5G behind becomes a moot point. It's simply a matter of, where is my data being generated? What is the best technology for me to use to ingest that data so I can derive value out of that data. If it means Wi-Fi, so be it. If it means cellular, so be it. And if you look at cellular right? The biggest thing people talk about SIMs. Now if you look at 5G standard. In 5G standard, you have EAPTLS, which means there is a possibility that SIMs in the future go away for IoT devices. I'm not saying they need to go away for consumer devices, they probably need to be there. But who's to say going ahead for IoT devices, they all become SIM free. So at that point, whether you Wi-Fi or 5G doesn't matter. >> Yeah, by the way, on the spectrum side people are starting to think about the concept. You might have heard this NRU, new radio unlicensed. So it's running the Wi-Fi standard, but in the unlicensed bands like Wi-Fi. So, and then the last piece is of course you know, the cost, the reality it stays 5G still new technology, the endpoints, you know, what would go in your laptop or a sensor et cetera. Today that's more expensive than Wi-Fi. So we need to get the volume curve down a little bit for that to really hit every application. I would guess your vision is correct. >> David: Yep >> But who can predict? >> Yeah, so explain more about what the unlicensed piece means for organizations. What does that for everybody? >> That's more of a future thing. So you know, just- >> No, right, but let's put on our telescope. >> Okay, so it's true today that Wi-Fi traditionally runs in the bands that have been licensed by the government and it's a country by country thing, right? >> Dave: Right. >> What we did in the United States was CBRS, is different than what they've done in Germany where they took part of the Zurich C-band and gave it to the enterprises. The telco's not involved. And now that's been copied in Japan and Korea. So it's one of the complications unfortunately in the market. Is that you have this different approach by regulators in different countries. Wi-Fi, the unlicensed band is a nice global standard. So if you could run NR just as 5G, right? It's another name for 5G, run that in the unlicensed bands, then you solve the spectrum problem that Dave was asking about. >> Which means that the market really opens up and now. >> It would be a real enabler >> Innovation. >> Exactly. >> And the only thing I would add to that is, right, there are some enterprises who have the size and scale to kind of say, "Hey, I'm going the unlicensed route. I can do things on my own." There are some enterprises that still are going to rely on the telcos, right? So I don't want to make a demon out of the telcos that you own the spectrum, no. >> David: Sure. >> They will be offering a very valuable service to a massive number of small, medium enterprises and enterprises that span regional boundaries to say, hey we can bring that consistent experience to you. >> But the primary value proposition has been connectivity, right? >> Yes. >> I mean, we can all agree on that. And you hear different monetization models, we can't allow the OTT vendors to do it again. You know, we want to tax Netflix. Okay, we've been talking about that all week. But there may be better models. >> Sarvesh: Yes. >> Right, and so where does private network fit into the monetization models? Let's follow the money here. >> Actually you've brought up an extremely important point, right? Because if you look at why haven't 5G networks taken off, one of the biggest things people keep contrasting is what is the cost of a Wi-Fi versus the cost of deploying a 5G, right? And a portion of the cost of deploying a 5G is how do you commercialize that spectrum? What is going to be the cost of that spectrum, right? So the CSPs will have to eventually figure out a proper commercialization model to say, hey listen, I can't just take what I've been doing till date and say this is how I make. Because if you look at 5G, the return of investment is incremental. Any use case you take, unless, let's take smart manufacturing, unless the factory decides I'm going to rip and replace everything by a 5G, they're going to introduce a small use case. You look at the investment for that use case, you'll say Hmm, I'm not making money. But guess what? Once you've deployed it and you bring use case number two, three, four, five, now it starts to really add value. So how can a CSP acknowledge that and create commercial models to enable that is going to be key. Like one of the things that Dell does in terms of as a service solution that we offer. I think that is a crucial way of really kick starting 5G adoption. >> It's Metcalfe's Law in this world, right? The first telephone, not a lot of value, second, I can call one person, but you know if I can call a zillion now it's valuable. >> John: Now you got data. >> Yeah, right, you used a phrase, rip and replace. What percentage of the market that you are focusing on is the let's go in and replace something, versus the let's help you digitally transform your business. And this is a networking technology that we can use to help you digitally transform? The example that you guys have with the small breweries, a perfect example. >> Sarvesh: Yeah. >> You help digitize, you know, digitally transform their business. You weren't going in and saying, I see that you have these things connected via Wi-Fi, let's rip those out and put SIMs in. >> No. >> Nope, so you know- >> That's exactly right. It's enabling new things that either couldn't be achieved before or weren't. So from a private 5G perspective, it's not going to be rip and replaced. As I said, I think we'll coexist with Wi-Fi, it's still got a great role. It's enabling those, solving those business problems that either hadn't been solved before or could not be solved with other technology. >> How are you guys using AI? Everybody's talking about ChatGPT. I love ChatGPT, we use it all the time. Love it, hate it, you know, whatever. It's a fun topic. But AI generally is here in a way that it wasn't when the enterprise disaggregated. >> John: Right. >> So there's AI, there's automation, there's opportunities there. How do they fit into private 5G? >> So if you look at it, right, AI, AI/ML is actually crucial to value extraction from that data, because all private 5G is doing is giving you access to that precious data. But that data by itself means nothing, right? You get access to the data, extracting value out of the data that bring in business value is all going to be AI/ML. Whether it's computer vision, whether it's data analytics on the fly so that you can, you know do your closed loop controls or what have you. All of these are going to be AI/ML models. >> Dave: Does it play into automation as well? >> Absolutely, 'cause they drive the automation, right? You learn your AI models, drive their automation. Control, closed loop control systems are a perfect example of their automation. >> Explain that further. Like give us an example. >> So for example, let's say we're talking about a smart manufacturing, right? So you have widgets coming down the pipe, right? You have your computer vision, you have your AI/ML model that says, "Hey, I'm starting to detect a consistent error in the product being manufactured. I'm going to close loop that automation and either tweak the settings of the machine, shut down the machine, open a workflow, escalate it for human intervention." All that automation is facilitated by the AI/ML models >> And that, and by the way, there's real money in that, right? If you're making your power and you're making it wrong, you don't detect it for hours, there's real money in fixing that >> Right. >> So I've got a, I've got an example albeit a slight, not even slightly, but a tragic one. Let's say you have a train that's rolling down the tracks at every several miles or so, temperature readings are taken from bearings in the train. >> Sarvesh: Yes, yes. >> Wouldn't it be nice to have that be happening in real time? >> Sarvesh: Yes. >> So it doesn't reach that critical point >> Yes. >> Where then you have a derailment. >> Yes. >> Yeah, absolutely. >> I mean, those are, it's doesn't sound sexy in terms of "Hey, what a great business use case that we can monetize." >> John: Yeah. >> But I'll bet you in hindsight that operator would've loved to have that capability. >> John: Yeah. >> Sarvesh: Right. >> To be able to shut the train down and not run. >> That's a great example where the carrier is actually, probably in a good position, right? Cause you got wide area, you want low latency. So the traditional carriers would be able in great position to provide that exact service. Telemetry is another great example. We've been talking about other kinds of automation, but just picking up measurements and so on. The other example of that is in oil and gas, right? As you've got pipelines running around you're measuring pressure, temperature, you detect a leak, >> David: Right. >> in minutes, not weeks. >> David: Right. >> So there's a lot of good examples of things like that >> To pick up in a point, Dave. You know, it's like you look at these big huge super tankers, right? They have big private networks on that super tanker to monitor everything. If on this train we had, you know, we hear about so many Edges, let's call one more the rolling Edge. >> Yeah. >> Right, that, that Edge is right on that locomotive tracking everything with AI/ML models, detecting things, warning people ahead of time shutting it down as needed. And that connectivity doesn't have to be wired. It can be a rolling wireless. It potentially could be a spectrum that's you know, open spectrum in the future. Or as you said, an operator could facilitate that. So many options, right? >> Yeah, got to double down on this. Look, I know 'cause I've been involved in some of these projects. Amusement park operators are doing this for rides. >> John: Yes. >> Sarvesh: Yep. >> So that they can optimize the amount of time the ride is up, so they can shorten lines >> Yes. >> So that they can get people into shops to buy food and souvenirs. >> John: Yes. >> Certainly we should be able to do it to protect infrastructure. >> Sarvesh: Absolutely. >> Right, so- >> But I think the ultimate point you're making is, it's actually quite finally segmented. There's so many different applications. And so that's why again, we come back to what we started with is at Dell, we're bringing the solution from Edge, compute, application, connectivity, and be able to bring that across all these different verticals and these different solutions. The other amusement park example, by the way, is as the rides start to invest in virtual reality, so you're moving, but you're seeing something, you need some technology like 5G to have low latency and keep that in sync and have a good experience on the ride. >> To 5G and beyond, gents. Thanks so much for coming on theCUBE. >> All right, thank you Dave. >> It was great to have you. >> Thank, thank you guys. >> Great to meet you guys. Thank you very much. >> Great, all right. Keep it right there. For David Nicholson and Dave Vellante, This is theCUBE's coverage of MWC23. Check out siliconangle.com for all the news. theCUBE.net is where all these videos live. John Furrier is in our Palo Alto office, banging out that news. Keep it right there. Be right back after this short break. (gentle upbeat music)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with David Nicholson, day four of MWC '23. Show's winding down a little bit, but it's still pretty packed here. Lot of innovation, planes, trains, automobiles, and we're talking 5G all week, private networks, connected breweries. It's super exciting. Really happy to have Warren Jackson here as the Edge Gateway Product Technologist at Dell Technologies, and Scott Waller, the CTO of the 5G Open Innovation Lab. Folks, welcome to theCUBE. >> Good to be here. >> Really interesting stories that we're going to talk about. Let's start, Scott, with you, what is the Open Innovation Lab? >> So it was hatched three years ago. Ideated about a bunch of guys from Microsoft who ran startup ventures program, started the developers program over at Microsoft, if you're familiar with MSDN. And they came three years ago and said, how does CSPs working with someone like T-Mobile who's in our backyard, I'm from Seattle. How do they monetize the edge? You need a developer ecosystem of applications and use cases. That's always been the thing. The carriers are building the networks, but where's the ecosystem of startups? So we built a startup ecosystem that is sponsored by partners, Dell being one sponsor, Intel, Microsoft, VMware, Aspirant, you name it. The enterprise folks who are also in the connectivity business. And with that, we're not like a Y Combinator or a Techstars where it's investment first and it's all about funding. It's all about getting introductions from a startup who might have a VR or AI type of application or observability for 5G slicing, and bring that in front of the Microsoft's of the world, or the Intel's and the Dell's of the world that they might not have the capabilities to do it because they're still a small little startup with an MVP. So we really incubate. We're the connectors and build a network. We've had 101 startups over the last three years. They've raised over a billion dollars. And it's really valuable to our partners like T-Mobile and Dell, et cetera, where we're bringing in folks like Expedo and GenXComm and Firecell. Start up private companies that are around here they were cohorts from our program in the past. >> That's awesome because I've often, I mean, I've seen Dell get into this business and I'm like, wow, they've done a really good job of finding these guys. I wonder what the pipeline is. >> We're trying to create the pipeline for the entire industry, whether it's 5G on the edge for the CSPs, or it's for private enterprise networks. >> Warren, what's this cool little thing you got here? >> Yeah, so this is very unique in the Dell portfolio. So when people think of Dell, they think of servers laptops, et cetera. But what this does is it's designed to be deployed at the edge in harsh environments and it allows customers to do analytics, data collection at the edge. And what's unique about it is it's got an extended temperature range. There's no fan in this and there's lots of ports on it for data ingestion. So this is a smaller box Edge Gateway 3200. This is the product that we're using in the brewery. And then we have a bigger brother of this, the Edge Gateway 5200. So the value of it, you can scale depending on what your edge compute requirements are at the edge. >> So tell us about the brewery story. And you covered it, I know you were in the Dell booth, but it's basically an analog brewery. They're taking measurements and temperatures and then writing it down and then entering it in and somebody from your company saw it and said, "We can help you with this problem." Explain the story. >> Yeah, so Scott and I did a walkthrough of the brewery back in November timeframe. >> It's in Framingham, Mass. >> Framingham, Mass, correct. And basically, we talked to him, and we said, what keeps you guys up at night? What's a problem that we can solve? Very simple, a kind of a lower budget, didn't have a lot money to spend on it, but what problem can we solve that will realize great benefit for you? So we looked at their fermentation process, which was completely analog. Somebody was walking around with a clipboard looking at analog gauges. And what we did is we digitized that process. So what this did for them rather than being completely reactive, and by the time they realized there was something going wrong with the fermentation process, it's too late. A batch of scrap. This allowed them to be proactive. So anytime, anywhere on the tablet or a phone, they can see if that fermentation process is going out of range and do something about it before the batch gets scrapped. >> Okay. Amazing. And Scott, you got a picture of this workflow here? >> Yeah, actually this is the final product. >> Explain that. >> As Warren mentioned, the data is actually residing in the industrial side of the network So we wanted to keep the IT/OT separation, which is critical on the factory floor. And so all the data is brought in from the sensors via digital connection once it's converted and into the edge gateway. Then there's a snapshot of it using Telit deviceWISE, their dashboarding application, that is decoding all the digital readings, putting them in a nice dashboard. And then when we gave them, we realized another problem was they're using cheap little Chromebooks that they spill beer on once a week and throw them out. That's why they bought the cheap ones 'cause they go through them so fast. So we got a Dell Latitude Rugged notebook. This is a brand new tablet, but they have the dashboarding software. So no matter if they're out there on the floor, but because the data resides there on the factory they have access to be able to change the parameters. This one's in the maturation cycle. This one's in the crashing cycle where they're bringing the temperature back down, stopping the fermentation process, getting it ready to go to the canning side of the house. >> And they're doing all that from this dashboard. >> They're doing all from the dashboard. They also have a giant screen that we put up there that in the floor instead of walking a hundred yards back behind a whole bunch of machinery equipment from a safety perspective, now they just look up on the screen and go, "Oh, that's red. That's out of range." They're actually doing a bunch of cleaning and a bunch of other things right now, too. So this is real time from Boston. >> Dave: Oh okay. >> Scott: This is actually real time from Boston. >> I'm no hop master, but I'm looking at these things flashing at me and I'm thinking something's wrong with my beer. >> We literally just lit this up last week. So we're still tweaking a few things, but they're also learning around. This is a new capability they never had. Oh, we have the ability to alert and monitor at different processes with different batches, different brews, different yeast types. Then now they're also training and learning. And we're going to turn that into eventually a product that other breweries might be able to use. >> So back to the kind of nuts and bolts of the system. The device that you have here has essentially wifi antennas on the back. >> Warren: Correct. >> Pull that up again if you would, please. >> Now I've seen this, just so people are clear, there are also paddle 5G antennas that go on the other side. >> Correct. >> That's sort of the connection from the 5G network that then gets transmogrified, technical term guys, into wifi so the devices that are physically connected to the brew vats, don't know what they're called. >> Fermentation tanks. >> Fermentation tanks, thank you. Those are wifi. That's a wifi signal that's going into this. Is that correct? >> Scott: No. >> No, it's not. >> It's a hard wire. >> Okay, okay. >> But, you're right. This particular gateway. >> It could be wifi if it's hard wire. >> It could be, yes. Could be any technology really. >> This particular gateway is not outfitted with 5G, but something that was very important in this application was to isolate the IT network, which is on wifi and physically connected from the OT network, which is the 5G connection. So we're sending the data directly from the gateway up to the cloud. The two partners that we worked with on this project were ifm, big sensor manufacturer that actually did the wired sensors into an industrial network called IO-Link. So they're physically wired into the gateway and then in the gateway we have a solution from our partner Telit that has deviceWISE software that actually takes the data in, runs the analytics on it, the logic, and then visualizes that data locally on those panels and also up to their cloud, which is what we're looking at. So they can look at it locally, they're in the plant and then up in the cloud on a phone or a tablet, whatever, when they're at home. >> We're talking about a small business here. I don't know how many employees they have, but it's not thousands. And I love that you're talking about an IT network and an OT network. And so they wanted, it is very common when we talk about industrial internet of things use cases, but we're talking about a tiny business here. >> Warren: Correct. >> They wanted to separate those networks because of cost, because of contention. Explain why. >> Yeah, just because, I mean, they're running their ERP system, their payroll, all of their kind of the way they run their business on their IT network and you don't want to have the same traffic out on the factory floor on that network, so it was pretty important. And the other thing is we really, one of the things that we didn't want to do in this project is interrupt their production process at all. So we installed this entire system in two days. They didn't have to shut down, they didn't have to stop. We didn't have to interrupt their process at all. It was like we were invisible there and we spun the thing up and within two days, very simple, easy, but tremendous value for their business. >> Talk about new markets here. I mean, it's like any company that's analog that needs to go digital. It's like 99% of the companies on the planet. What are you guys seeing out there in terms of the types of examples beyond breweries? >> Yeah, I could talk to that. So I spent a lot of time over the last couple years running my own little IoT company and a lot of it being in agriculture. So like in Washington state, 70% of the world's hops is actually grown in Washington state. It's my hometown. But in the Ag producing regions, there's lack of connectivity. So there's interest in private networks because the carriers aren't necessarily deploying it. But because we have the vast amount of hops there's a lot of IPAs, a lot of hoppy IPAs that come out of Seattle. And with that, there's a ton of craft breweries that are about the same size, some are a little larger. Anheuser-Busch and InBev and Heineken they've got great IoT platforms. They've done it. They're mass scale, they have to digitize. But the smaller shops, they don't, when we talk about IT/OT separation, they're not aware of that. They think it's just, I get local broadband and I get wifi and one hotspot inside my facility and it works. So a little bit of it was the education. I have got years in IT/OT security in my background so that education and we come forward with a solution that actually does that for them. And now they're aware of it. So now when they're asking questions of other vendors that are trying to sell them some type of solution, they're inherently aware of what should be done so they're not vulnerable to ransomware attacks, et cetera. So it's known as the Purdue Model. >> Well, what should they do? >> We came in and keep it completely separated and educated them because in the end too we'll build a design guide and a starter kit out of this that other brewers can use. Because I've toured dozens of breweries in Washington, the exact same scenario, analog gauges, analog process, very manual. And in the end, when you ask the brewer, what do they want out of this? It keeps them up at night because if the temperature goes out of range, because the chiller fails, >> They ruined. >> That's $30,000 lost in beer. That's a lot to a small business. However, it's also once they start digitizing the data and to Warren's point, it's read-only. We're not changing any of the process. We augmented on top of their existing systems. We didn't change their process. But now they have the ability to look at the data and see batch to batch consistency. Quality doesn't always mean best, it means consistency from batch to batch. Every beer from exhibit A from yesterday to two months from now of the same style of beer should be the same taste, flavor, boldness, et cetera. This is giving them the insights on it. >> It's like St. Louis Buds, when we were kids. We would buy the St. Louis Buds 'cause they tasted better than the Merrimack Buds. And then Budweiser made them all the same. >> Must be an East coast thing. >> It's an old guy thing, Dave. You weren't born yet. >> I was in high school. Yeah, I was in high school. >> We like the hops. >> We weren't 21. Do me a favor, clarify OT versus IT. It's something we talk about all the time, but not everyone's familiar with that separation. Define OT for me. >> It's really the factory floor. You got IT systems that are ERP systems, billing, you're getting your emails, stuff like that. Where the ransomware usually gets infected in. The OT side is the industrial control network. >> David: What's the 'O' stand for? >> Operation. >> David: Operation? >> Yeah, the operations side. >> 'Cause some people will think objects 'cause we think internet of things. >> The industrial operations, think of it that way. >> But in a sense those are things that are connected. >> And you think of that as they are the safety systems as well. So a machine, if someone doesn't push the stop button, you'd think if there's a lot of traffic on that network, it isn't guaranteed that that stop button actually stops that blade from coming down, someone's going to lose their arm. So it's very tied to safety, reliability, low latency. It is crafted in design that it never touches the internet inherently without having to go through a security gateway which is what we did. >> You mentioned the large companies like InBev, et cetera. You're saying they're already there. Are they not part of your target market? Or are there ways that you can help them? Is this really more of a small to mid-size company? >> For this particular solution, I think so, yeah. Because the cost to entry is low. I mean, you talk about InBev, they have millions of dollars of budgets to spend on OT. So they're completely automated from top to bottom. But these little craft brewers, which they're everywhere in the US. Vermont, Washington state, they're completely manual. A lot of these guys just started in their garage. And they just scaled up and they got a cult kind of following around their beers. One thing that we found here this week, when you talk around edge and 5G and beer, those things get people excited. In our booth we're serving beer, and all these kind of topics, it brings people together. >> And it lets the little guy compete more effectively with the big giants. >> Correct. >> And how do you do more with less as the little guy is kind of the big thing and to Warren's point, we have folks come up and say, "Great, this is for beer, but what about wine? What about the fermentation process of wine?" Same materials in the end. A vessel of some sort, maybe it's stainless steel. The clamps are the same, the sensors are the same. The parameters like temperature are key in any type of fermentation. We had someone talking about olive oil and using that. It's the same sanitary beverage style equipment. We grabbed sensors that were off the shelf and then we integrated them in and used the set of platforms that we could. How do we rapidly enable these guys at the lowest possible cost with stuff that's at the shelf. And there's four different companies in the solution. >> We were having a conversation with T-Mobile a little earlier and she mentioned the idea of this sounding scary. And this is a great example of showing that in fact, at a relatively small scale, this technology makes a lot of sense. So from that perspective, of course you can implement private 5G networks at an industrial scale with tens of millions of dollars of investment. But what about all of the other things below? And that seems to be a perfect example. >> Yeah, correct. And it's one of the things with the gateway and having flexibility the way Dell did a great job of putting really good modems in it. It had a wide spectrum range of what bands they support. So being able to say, at a larger facility, I mean, if Heineken wants to deploy something like this, oh, heck yeah, they probably could do it. And they might have a private 5G network, but let's say T-Mobile offers a private offering on their public via a slice. It's easy to connect that radio to it. You just change the sims. >> Is that how the CSPs fit here? How are they monetized? >> Yeah, correct. So one of our partners is T-Mobile and so we're working with them. We've got other telco partners that are coming on board in our lab. And so we'll do the same thing. We're going to take this back and put it in the lab and offer it up as others because the baseline building blocks or Lego blocks per se can be used in a bunch of different industries. It's really that starter point of giving folks the idea of what's possible. >> So small manufacturing, agriculture you mentioned, any other sort of use cases we should tune into? >> I think it's environmental monitoring, all of that stuff, I see it in IoT deployments all over the world. Just the simple starter kits 'cause a farmer doesn't want to get sold a solution, a platform, where he's got to hire a bunch of coders and partner with the big carriers. He just wants something that works. >> Another use case that we see a lot, a high cost in a lot of these places is the cost of energy. And a lot of companies don't know what they're spending on electricity. So a very simple energy monitoring system like that, it's a really good ROI. I'm going to spend five or $10,000 on a system like this, but I'm going to save $20,000 over a year 'cause I'm able to see, have visibility into that data. That's a lot of what this story's about, just giving visibility into the process. >> It's very cool, and like you said, it gets people excited. Is it a big market? How do you size it? Is it a big TAM? >> Yeah, so one thing that Dell brings to the table in this space is people are buying their laptops, their servers and whatnot from Dell and companies are comfortable in doing business with Dell because of our model direct to customer and whatnot. So our ability to bring a device like this to the OT space and have them have that same user experience they have with laptops and our client products in a ruggedized solution like this and bring a lot of partners to the table makes it easy for our customers to implement this across all kinds of industries. >> So we're talking to billions, tens of billions. Do we know how big this market is? What's the TAM? I mean, come on, you work for Dell. You have to do a TAM analysis. >> Yes, no, yeah. I mean, it really is in the billions. The market is huge for this one. I think we just tapped into it. We're kind of focused in on the brewery piece of it and the liquor piece of it, but the possibilities are endless. >> Yeah, that's tip of the spear. Guys, great story. >> It's scalable. I think the biggest thing, just my final feedback is working and partnering with Dell is we got something as small as this edge gateway that I can run a Packet Core on and run a 5G standalone node and then have one of the small little 5G radios out there. And I've got these deployed in a farm. Give the farmer an idea of what's possible, give him a unit on his tractor, and now he can do something that, we're providing connectivity he had never had before. But as we scale up, we've got the big brother to this. When we scale up from that, we got the telco size units that we can put. So it's very scalable. It's just a great suite of offerings. >> Yeah, outstanding. Guys, thanks for sharing the story. Great to have you on theCUBE. >> Good to be with you today. >> Stop by for beer later. >> You know it. All right, Dave Vellante for Dave Nicholson and the entire CUBE team, we're here live at the Fira in Barcelona MWC '23 day four. Keep it right there. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While never really meant to be a consumer tech event, the rapid ascendancy of smartphones sucked much of the air out of Mobile World Congress over the years, now MWC. And while the device manufacturers continue to have a major presence at the show, the maturity of intelligent devices, longer life cycles, and the disaggregation of the network stack, have put enterprise technologies front and center in the telco business. Semiconductor manufacturers, network equipment players, infrastructure companies, cloud vendors, software providers, and a spate of startups are eyeing the trillion dollar plus communications industry as one of the next big things to watch this decade. Hello, and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we bring you part two of our ongoing coverage of MWC '23, with some new data on enterprise players specifically in large telco environments, a brief glimpse at some of the pre-announcement news and corresponding themes ahead of MWC, and some of the key announcement areas we'll be watching at the show on theCUBE. Now, last week we shared some ETR data that showed how traditional enterprise tech players were performing, specifically within the telecoms vertical. Here's a new look at that data from ETR, which isolates the same companies, but cuts the data for what ETR calls large telco. The N in this cut is 196, down from 288 last week when we included all company sizes in the dataset. Now remember the two dimensions here, on the y-axis is net score, or spending momentum, and on the x-axis is pervasiveness in the data set. The table insert in the upper left informs how the dots and companies are plotted, and that red dotted line, the horizontal line at 40%, that indicates a highly elevated net score. Now while the data are not dramatically different in terms of relative positioning, there are a couple of changes at the margin. So just going down the list and focusing on net score. Azure is comparable, but slightly lower in this sector in the large telco than it was overall. Google Cloud comes in at number two, and basically swapped places with AWS, which drops slightly in the large telco relative to overall telco. Snowflake is also slightly down by one percentage point, but maintains its position. Remember Snowflake, overall, its net score is much, much higher when measuring across all verticals. Snowflake comes down in telco, and relative to overall, a little bit down in large telco, but it's making some moves to attack this market that we'll talk about in a moment. Next are Red Hat OpenStack and Databricks. About the same in large tech telco as they were an overall telco. Then there's Dell next that has a big presence at MWC and is getting serious about driving 16G adoption, and new servers, and edge servers, and other partnerships. Cisco and Red Hat OpenShift basically swapped spots when moving from all telco to large telco, as Cisco drops and Red Hat bumps up a bit. And VMware dropped about four percentage points in large telco. Accenture moved up dramatically, about nine percentage points in big telco, large telco relative to all telco. HPE dropped a couple of percentage points. Oracle stayed about the same. And IBM surprisingly dropped by about five points. So look, I understand not a ton of change in terms of spending momentum in the large sector versus telco overall, but some deltas. The bottom line for enterprise players is one, they're just getting started in this new disruption journey that they're on as the stack disaggregates. Two, all these players have experience in delivering horizontal solutions, but now working with partners and identifying big problems to be solved, and three, many of these companies are generally not the fastest moving firms relative to smaller disruptive disruptors. Now, cloud has been an exception in fairness. But the good news for the legacy infrastructure and IT companies is that the telco transformation and the 5G buildout is going to take years. So it's moving at a pace that is very favorable to many of these companies. Okay, so looking at just some of the pre-announcement highlights that have hit the wire this week, I want to give you a glimpse of the diversity of innovation that is occurring in the telecommunication space. You got semiconductor manufacturers, device makers, network equipment players, carriers, cloud vendors, enterprise tech companies, software companies, startups. Now we've included, you'll see in this list, we've included OpeRAN, that logo, because there's so much buzz around the topic and we're going to come back to that. But suffice it to say, there's no way we can cover all the announcements from the 2000 plus exhibitors at the show. So we're going to cherry pick here and make a few call outs. Hewlett Packard Enterprise announced an acquisition of an Italian private cellular network company called AthoNet. Zeus Kerravala wrote about it on SiliconANGLE if you want more details. Now interestingly, HPE has a partnership with Solana, which also does private 5G. But according to Zeus, Solona is more of an out-of-the-box solution, whereas AthoNet is designed for the core and requires more integration. And as you'll see in a moment, there's going to be a lot of talk at the show about private network. There's going to be a lot of news there from other competitors, and we're going to be watching that closely. And while many are concerned about the P5G, private 5G, encroaching on wifi, Kerravala doesn't see it that way. Rather, he feels that these private networks are really designed for more industrial, and you know mission critical environments, like factories, and warehouses that are run by robots, et cetera. 'Cause these can justify the increased expense of private networks. Whereas wifi remains a very low cost and flexible option for, you know, whatever offices and homes. Now, over to Dell. Dell announced its intent to go hard after opening up the telco network with the announcement that in the second half of this year it's going to begin shipping its infrastructure blocks for Red Hat. Remember it's like kind of the converged infrastructure for telco with a more open ecosystem and sort of more flexible, you know, more mature engineered system. Dell has also announced a range of PowerEdge servers for a variety of use cases. A big wide line bringing forth its 16G portfolio and aiming squarely at the telco space. Dell also announced, here we go, a private wireless offering with airspan, and Expedo, and a solution with AthoNet, the company HPE announced it was purchasing. So I guess Dell and HPE are now partnering up in the private wireless space, and yes, hell is freezing over folks. We'll see where that relationship goes in the mid- to long-term. Dell also announced new lab and certification capabilities, which we said last week was going to be critical for the further adoption of open ecosystem technology. So props to Dell for, you know, putting real emphasis and investment in that. AWS also made a number of announcements in this space including private wireless solutions and associated managed services. AWS named Deutsche Telekom, Orange, T-Mobile, Telefonica, and some others as partners. And AWS announced the stepped up partnership, specifically with T-Mobile, to bring AWS services to T-Mobile's network portfolio. Snowflake, back to Snowflake, announced its telecom data cloud. Remember we showed the data earlier, it's Snowflake not as strong in the telco sector, but they're continuing to move toward this go-to market alignment within key industries, realigning their go-to market by vertical. It also announced that AT&T, and a number of other partners, are collaborating to break down data silos specifically in telco. Look, essentially, this is Snowflake taking its core value prop to the telco vertical and forming key partnerships that resonate in the space. So think simplification, breaking down silos, data sharing, eventually data monetization. Samsung previewed its future capability to allow smartphones to access satellite services, something Apple has previously done. AMD, Intel, Marvell, Qualcomm, are all in the act, all the semiconductor players. Qualcomm for example, announced along with Telefonica, and Erickson, a 5G millimeter network that will be showcased in Spain at the event this coming week using Qualcomm Snapdragon chipset platform, based on none other than Arm technology. Of course, Arm we said is going to dominate the edge, and is is clearly doing so. It's got the volume advantage over, you know, traditional Intel, you know, X86 architectures. And it's no surprise that Microsoft is touting its open AI relationship. You're going to hear a lot of AI talk at this conference as is AI is now, you know, is the now topic. All right, we could go on and on and on. There's just so much going on at Mobile World Congress or MWC, that we just wanted to give you a glimpse of some of the highlights that we've been watching. Which brings us to the key topics and issues that we'll be exploring at MWC next week. We touched on some of this last week. A big topic of conversation will of course be, you know, 5G. Is it ever going to become real? Is it, is anybody ever going to make money at 5G? There's so much excitement around and anticipation around 5G. It has not lived up to the hype, but that's because the rollout, as we've previous reported, is going to take years. And part of that rollout is going to rely on the disaggregation of the hardened telco stack, as we reported last week and in previous Breaking Analysis episodes. OpenRAN is a big component of that evolution. You know, as our RAN intelligent controllers, RICs, which essentially the brain of OpenRAN, if you will. Now as we build out 5G networks at massive scale and accommodate unprecedented volumes of data and apply compute-hungry AI to all this data, the issue of energy efficiency is going to be front and center. It has to be. Not only is it a, you know, hot political issue, the reality is that improving power efficiency is compulsory or the whole vision of telco's future is going to come crashing down. So chip manufacturers, equipment makers, cloud providers, everybody is going to be doubling down and clicking on this topic. Let's talk about AI. AI as we said, it is the hot topic right now, but it is happening not only in consumer, with things like ChatGPT. And think about the theme of this Breaking Analysis in the enterprise, AI in the enterprise cannot be ChatGPT. It cannot be error prone the way ChatGPT is. It has to be clean, reliable, governed, accurate. It's got to be ethical. It's got to be trusted. Okay, we're going to have Zeus Kerravala on the show next week and definitely want to get his take on private networks and how they're going to impact wifi. You know, will private networks cannibalize wifi? If not, why not? He wrote about this again on SiliconANGLE if you want more details, and we're going to unpack that on theCUBE this week. And finally, as always we'll be following the data flows to understand where and how telcos, cloud players, startups, software companies, disruptors, legacy companies, end customers, how are they going to make money from new data opportunities? 'Cause we often say in theCUBE, don't ever bet against data. All right, that's a wrap for today. Remember theCUBE is going to be on location at MWC 2023 next week. We got a great set. We're in the walkway in between halls four and five, right in Congress Square, stand CS-60. Look for us, we got a full schedule. If you got a great story or you have news, stop by. We're going to try to get you on the program. I'll be there with Lisa Martin, co-hosting, David Nicholson as well, and the entire CUBE crew, so don't forget to come by and see us. I want to thank Alex Myerson, who's on production and manages the podcast, and Ken Schiffman, as well, in our Boston studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at SiliconANGLE.com. He does some great editing. Thank you. All right, remember all these episodes they are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. I publish each week on Wikibon.com and SiliconANGLE.com. All the video content is available on demand at theCUBE.net, or you can email me directly if you want to get in touch David.Vellante@SiliconANGLE.com or DM me @DVellante, or comment on our LinkedIn posts. And please do check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Mobile World Congress '23, MWC '23, or next time on Breaking Analysis. (bright music)

(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

(upbeat music beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. Best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (upbeat music beginning) (upbeat music ending)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

>> Narrator: From theCUBE Studios in Palo Alto and Boston bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante >> Enterprise tech practitioners, like most of us they want to make their lives easier so they can focus on delivering more value to their businesses. And to do so, they want to tap best of breed services in the public cloud, but at the same time connect their on-prem intellectual property to emerging applications which drive top line revenue and bottom line profits. But creating a consistent experience across clouds and on-prem estates has been an elusive capability for most organizations, forcing trade-offs and injecting friction into the system. The need to create seamless experiences is clear and the technology industry is starting to respond with platforms, architectures, and visions of what we've called the Supercloud. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis we give you a preview of Supercloud 2, the second event of its kind that we've had on the topic. Yes, folks that's right Supercloud 2 is here. As of this recording, it's just about four days away 33 guests, 21 sessions, combining live discussions and fireside chats from theCUBE's Palo Alto Studio with prerecorded conversations on the future of cloud and data. You can register for free at supercloud.world. And we are super excited about the Supercloud 2 lineup of guests whereas Supercloud 22 in August, was all about refining the definition of Supercloud testing its technical feasibility and understanding various deployment models. Supercloud 2 features practitioners, technologists and analysts discussing what customers need with real-world examples of Supercloud and will expose thinking around a new breed of cross-cloud apps, data apps, if you will that change the way machines and humans interact with each other. Now the example we'd use if you think about applications today, say a CRM system, sales reps, what are they doing? They're entering data into opportunities they're choosing products they're importing contacts, et cetera. And sure the machine can then take all that data and spit out a forecast by rep, by region, by product, et cetera. But today's applications are largely about filling in forms and or codifying processes. In the future, the Supercloud community sees a new breed of applications emerging where data resides on different clouds, in different data storages, databases, Lakehouse, et cetera. And the machine uses AI to inspect the e-commerce system the inventory data, supply chain information and other systems, and puts together a plan without any human intervention whatsoever. Think about a system that orchestrates people, places and things like an Uber for business. So at Supercloud 2, you'll hear about this vision along with some of today's challenges facing practitioners. Zhamak Dehghani, the founder of Data Mesh is a headliner. Kit Colbert also is headlining. He laid out at the first Supercloud an initial architecture for what that's going to look like. That was last August. And he's going to present his most current thinking on the topic. Veronika Durgin of Sachs will be featured and talk about data sharing across clouds and you know what she needs in the future. One of the main highlights of Supercloud 2 is a dive into Walmart's Supercloud. Other featured practitioners include Western Union Ionis Pharmaceuticals, Warner Media. We've got deep, deep technology dives with folks like Bob Muglia, David Flynn Tristan Handy of DBT Labs, Nir Zuk, the founder of Palo Alto Networks focused on security. Thomas Hazel, who's going to talk about a new type of database for Supercloud. It's several analysts including Keith Townsend Maribel Lopez, George Gilbert, Sanjeev Mohan and so many more guests, we don't have time to list them all. They're all up on supercloud.world with a full agenda, so you can check that out. Now let's take a look at some of the things that we're exploring in more detail starting with the Walmart Cloud native platform, they call it WCNP. We definitely see this as a Supercloud and we dig into it with Jack Greenfield. He's the head of architecture at Walmart. Here's a quote from Jack. "WCNP is an implementation of Kubernetes for the Walmart ecosystem. We've taken Kubernetes off the shelf as open source." By the way, they do the same thing with OpenStack. "And we have integrated it with a number of foundational services that provide other aspects of our computational environment. Kubernetes off the shelf doesn't do everything." And so what Walmart chose to do, they took a do-it-yourself approach to build a Supercloud for a variety of reasons that Jack will explain, along with Walmart's so-called triplet architecture connecting on-prem, Azure and GCP. No surprise, there's no Amazon at Walmart for obvious reasons. And what they do is they create a common experience for devs across clouds. Jack is going to talk about how Walmart is evolving its Supercloud in the future. You don't want to miss that. Now, next, let's take a look at how Veronica Durgin of SAKS thinks about data sharing across clouds. Data sharing we think is a potential killer use case for Supercloud. In fact, let's hear it in Veronica's own words. Please play the clip. >> How do we talk to each other? And more importantly, how do we data share? You know, I work with data, you know this is what I do. So if you know I want to get data from a company that's using, say Google, how do we share it in a smooth way where it doesn't have to be this crazy I don't know, SFTP file moving? So that's where I think Supercloud comes to me in my mind, is like practical applications. How do we create that mesh, that network that we can easily share data with each other? >> Now data mesh is a possible architectural approach that will enable more facile data sharing and the monetization of data products. You'll hear Zhamak Dehghani live in studio talking about what standards are missing to make this vision a reality across the Supercloud. Now one of the other things that we're really excited about is digging deeper into the right approach for Supercloud adoption. And we're going to share a preview of a debate that's going on right now in the community. Bob Muglia, former CEO of Snowflake and Microsoft Exec was kind enough to spend some time looking at the community's supercloud definition and he felt that it needed to be simplified. So in near real time he came up with the following definition that we're showing here. I'll read it. "A Supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." So not only did Bob simplify the initial definition he's stressed that the Supercloud is a platform versus an architecture implying that the platform provider eg Snowflake, VMware, Databricks, Cohesity, et cetera is responsible for determining the architecture. Now interestingly in the shared Google doc that the working group uses to collaborate on the supercloud de definition, Dr. Nelu Mihai who is actually building a Supercloud responded as follows to Bob's assertion "We need to avoid creating many Supercloud platforms with their own architectures. If we do that, then we create other proprietary clouds on top of existing ones. We need to define an architecture of how Supercloud interfaces with all other clouds. What is the information model? What is the execution model and how users will interact with Supercloud?" What does this seemingly nuanced point tell us and why does it matter? Well, history suggests that de facto standards will emerge more quickly to resolve real world practitioner problems and catch on more quickly than consensus-based architectures and standards-based architectures. But in the long run, the ladder may serve customers better. So we'll be exploring this topic in more detail in Supercloud 2, and of course we'd love to hear what you think platform, architecture, both? Now one of the real technical gurus that we'll have in studio at Supercloud two is David Flynn. He's one of the people behind the the movement that enabled enterprise flash adoption, that craze. And he did that with Fusion IO and he is now working on a system to enable read write data access to any user in any application in any data center or on any cloud anywhere. So think of this company as a Supercloud enabler. Allow me to share an excerpt from a conversation David Flore and I had with David Flynn last year. He as well gave a lot of thought to the Supercloud definition and was really helpful with an opinionated point of view. He said something to us that was, we thought relevant. "What is the operating system for a decentralized cloud? The main two functions of an operating system or an operating environment are one the process scheduler and two, the file system. The strongest argument for supercloud is made when you go down to the platform layer and talk about it as an operating environment on which you can run all forms of applications." So a couple of implications here that will be exploring with David Flynn in studio. First we're inferring from his comment that he's in the platform camp where the platform owner is responsible for the architecture and there are obviously trade-offs there and benefits but we'll have to clarify that with him. And second, he's basically saying, you kill the concept the further you move up the stack. So the weak, the further you move the stack the weaker the supercloud argument becomes because it's just becoming SaaS. Now this is something we're going to explore to better understand is thinking on this, but also whether the existing notion of SaaS is changing and whether or not a new breed of Supercloud apps will emerge. Which brings us to this really interesting fellow that George Gilbert and I RIFed with ahead of Supercloud two. Tristan Handy, he's the founder and CEO of DBT Labs and he has a highly opinionated and technical mind. Here's what he said, "One of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse inside of your data lake. These are core concepts that the business should be able to create applications around very easily. In fact, that's not the case because it involves a lot of data engineering pipeline and other work to make these available. So if you really want to make it easy to create these data experiences for users you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes and they don't need to." A lot of implications to this statement that will explore at Supercloud two versus Jamma Dani's data mesh comes into play here with her critique of hyper specialized data pipeline experts with little or no domain knowledge. Also the need for simplified self-service infrastructure which Kit Colbert is likely going to touch upon. Veronica Durgin of SAKS and her ideal state for data shearing along with Harveer Singh of Western Union. They got to deal with 200 locations around the world in data privacy issues, data sovereignty how do you share data safely? Same with Nick Taylor of Ionis Pharmaceutical. And not to blow your mind but Thomas Hazel and Bob Muglia deposit that to make data apps a reality across the Supercloud you have to rethink everything. You can't just let in memory databases and caching architectures take care of everything in a brute force manner. Rather you have to get down to really detailed levels even things like how data is laid out on disk, ie flash and think about rewriting applications for the Supercloud and the MLAI era. All of this and more at Supercloud two which wouldn't be complete without some data. So we pinged our friends from ETR Eric Bradley and Darren Bramberm to see if they had any data on Supercloud that we could tap. And so we're going to be analyzing a number of the players as well at Supercloud two. Now, many of you are familiar with this graphic here we show some of the players involved in delivering or enabling Supercloud-like capabilities. On the Y axis is spending momentum and on the horizontal accesses market presence or pervasiveness in the data. So netscore versus what they call overlap or end in the data. And the table insert shows how the dots are plotted now not to steal ETR's thunder but the first point is you really can't have supercloud without the hyperscale cloud platforms which is shown on this graphic. But the exciting aspect of Supercloud is the opportunity to build value on top of that hyperscale infrastructure. Snowflake here continues to show strong spending velocity as those Databricks, Hashi, Rubrik. VMware Tanzu, which we all put under the magnifying glass after the Broadcom announcements, is also showing momentum. Unfortunately due to a scheduling conflict we weren't able to get Red Hat on the program but they're clearly a player here. And we've put Cohesity and Veeam on the chart as well because backup is a likely use case across clouds and on-premises. And now one other call out that we drill down on at Supercloud two is CloudFlare, which actually uses the term supercloud maybe in a different way. They look at Supercloud really as you know, serverless on steroids. And so the data brains at ETR will have more to say on this topic at Supercloud two along with many others. Okay, so why should you attend Supercloud two? What's in it for me kind of thing? So first of all, if you're a practitioner and you want to understand what the possibilities are for doing cross-cloud services for monetizing data how your peers are doing data sharing, how some of your peers are actually building out a Supercloud you're going to get real world input from practitioners. If you're a technologist, you're trying to figure out various ways to solve problems around data, data sharing, cross-cloud service deployment there's going to be a number of deep technology experts that are going to share how they're doing it. We're also going to drill down with Walmart into a practical example of Supercloud with some other examples of how practitioners are dealing with cross-cloud complexity. Some of them, by the way, are kind of thrown up their hands and saying, Hey, we're going mono cloud. And we'll talk about the potential implications and dangers and risks of doing that. And also some of the benefits. You know, there's a question, right? Is Supercloud the same wine new bottle or is it truly something different that can drive substantive business value? So look, go to Supercloud.world it's January 17th at 9:00 AM Pacific. You can register for free and participate directly in the program. Okay, that's a wrap. I want to give a shout out to the Supercloud supporters. VMware has been a great partner as our anchor sponsor Chaos Search Proximo, and Alura as well. For contributing to the effort I want to thank Alex Myerson who's on production and manages the podcast. Ken Schiffman is his supporting cast as well. Kristen Martin and Cheryl Knight to help get the word out on social media and at our newsletters. And Rob Ho is our editor-in-chief over at Silicon Angle. Thank you all. Remember, these episodes are all available as podcast. Wherever you listen we really appreciate the support that you've given. We just saw some stats from from Buzz Sprout, we hit the top 25% we're almost at 400,000 downloads last year. So really appreciate your participation. All you got to do is search Breaking Analysis podcast and you'll find those I publish each week on wikibon.com and siliconangle.com. Or if you want to get ahold of me you can email me directly at David.Vellante@siliconangle.com or dm me DVellante or comment on our LinkedIn post. I want you to check out etr.ai. They've got the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Supercloud two or next time on breaking analysis. (light music)

(upbeat music) >> Welcome back to Supercloud 2, which is an open industry collaboration between technologists, consultants, analysts, and of course, practitioners, to help shape the future of cloud. And at this event, one of the key areas we're exploring is the intersection of cloud and data, and how building value on top of hyperscale clouds and across clouds is evolving, a concept we call supercloud. And we're pleased to welcome Harvir Singh, who's the chief data architect and global head of data at Western Union. Harvir, it's good to see you again. Thanks for coming on the program. >> Thanks, David, it's always a pleasure to talk to you. >> So many things stand out from when we first met, and one of the most gripping for me was when you said to me, "When data moves, money moves." And that's the world we live in today, and really have for a long time. Money has moved as bits, and when it has to move, we want it to move quickly, securely, and in a governed manner. And the pressure to do so is only growing. So tell us how that trend is evolved over the past decade in the context of your industry generally, and Western Union, specifically. Look, I always say to people that we are probably the first ones to introduce digital currency around the world because, hey, somebody around the world needs money, we move data to make that happen. That trend has actually accelerated quite a bit. If you look at the last 10 years, and you look at all these payment companies, digital companies, credit card companies that have evolved, majority of them are working on the same principle. When data moves, money moves. When data is stale, the money goes away, right? I think that trend is continuing, and it's not just the trend is in this space, it's also continuing in other spaces, specifically around, you know, acquisition of customers, communication with customers. It's all becoming digital, and it's, at the end of the day, it's all data being moved from one place or another. At the end of the day, you're not seeing the customer, but you're looking at, you know, the data that he's consuming, and you're making actionable items on it, and be able to respond to what they need. So I think 10 years, it's really, really evolved. >> Hmm, you operate, Western Union operates in more than 200 countries, and you you have what I would call a pseudo federated organization. You're trying to standardize wherever possible on the infrastructure, and you're curating the tooling and doing the heavy lifting in the data stack, which of course lessens the burden on the developers and the line of business consumers, so my question is, in operating in 200 countries, how do you deal with all the diversity of laws and regulations across those regions? I know you're heavily involved in AWS, but AWS isn't everywhere, you still have some on-prem infrastructure. Can you paint a picture of, you know, what that looks like? >> Yeah, a few years ago , we were primarily mostly on-prem, and one of the biggest pain points has been managing that infrastructure around the world in those countries. Yes, we operate in 200 countries, but we don't have infrastructure in 200 countries, but we do have agent locations in 200 countries. United Nations says we only have like 183 are countries, but there are countries which, you know, declare themselves countries, and we are there as well because somebody wants to send money there, right? Somebody has an agent location down there as well. So that infrastructure is obviously very hard to manage and maintain. We have to comply by numerous laws, you know. And the last few years, specifically with GDPR, CCPA, data localization laws in different countries, it's been a challenge, right? And one of the things that we did a few years ago, we decided that we want to be in the business of helping our customers move money faster, security, and with complete trust in us. We don't want to be able to, we don't want to be in the business of managing infrastructure. And that's one of the reasons we started to, you know, migrate and move our journey to the cloud. AWS, obviously chosen first because of its, you know, first in the game, has more locations, and more data centers around the world where we operate. But we still have, you know, existing infrastructure, which is in some countries, which is still localized because AWS hasn't reached there, or we don't have a comparable provider there. We still manage those. And we have to comply by those laws. Our data privacy and our data localization tech stack is pretty good, I would say. We manage our data very well, we manage our customer data very well, but it comes with a lot of complexity. You know, we get a lot of requests from European Union, we get a lot of requests from Asia Pacific every pretty much on a weekly basis to explain, you know, how we are taking controls and putting measures in place to make sure that the data is secured and is in the right place. So it's a complex environment. We do have exposure to other clouds as well, like Google and Azure. And as much as we would love to be completely, you know, very, very hybrid kind of an organization, it's still at a stage where we are still very heavily focused on AWS yet, but at some point, you know, we would love to see a world which is not reliant on a single provider, but it's more a little bit more democratized, you know, as and when what I want to use, I should be able to use, and pay-per-use. And the concept started like that, but it's obviously it's now, again, there are like three big players in the market, and, you know, they're doing their own thing. Would love to see them come collaborate at some point. >> Yeah, wouldn't we all. I want to double-click on the whole multi-cloud strategy, but if I understand it correctly, and in a perfect world, everything on-premises would be in the cloud is, first of all, is that a correct statement? Is that nirvana for you or not necessarily? >> I would say it is nirvana for us, but I would also put a caveat, is it's very tricky because from a regulatory perspective, we are a regulated entity in many countries. The regulators would want to see some control if something happens with a relationship with AWS in one country, or with Google in another country, and it keeps happening, right? For example, Russia was a good example where we had to switch things off. We should be able to do that. But if let's say somewhere in Asia, this country decides that they don't want to partner with AWS, and majority of our stuff is on AWS, where do I go from there? So we have to have some level of confidence in our own infrastructure, so we do maintain some to be able to fail back into and move things it needs to be. So it's a tricky question. Yes, it's nirvana state that I don't have to manage infrastructure, but I think it's far less practical than it said. We will still own something that we call it our own where we have complete control, being a financial entity. >> And so do you try to, I'm sure you do, standardize between all the different on-premise, and in this case, the AWS cloud or maybe even other clouds. How do you do that? Do you work with, you know, different vendors at the various places of the stack to try to do that? Some of the vendors, you know, like a Snowflake is only in the cloud. You know, others, you know, whether it's whatever, analytics, or storage, or database, might be hybrid. What's your strategy with regard to creating as common an experience as possible between your on-prem and your clouds? >> You asked a question which I asked when I joined as well, right? Which question, this is one of the most important questions is how soon when I fail back, if I need to fail back? And how quickly can I, because not everything that is sitting on the cloud is comparable to on-prem or is backward compatible. And the reason I say backward compatible is, you know, there are, our on-prem cloud is obviously behind. We haven't taken enough time to kind of put it to a state where, because we started to migrate and now we have access to infrastructure on the cloud, most of the new things are being built there. But for critical application, I would say we have chronology that could be used to move back if need to be. So, you know, technologies like Couchbase, technologies like PostgreSQL, technologies like Db2, et cetera. We still have and maintain a fairly large portion of it on-prem where critical applications could potentially be serviced. We'll give you one example. We use Neo4j very heavily for our AML use cases. And that's an important one because if Neo4j on the cloud goes down, and it's happened in the past, again, even with three clusters, having all three clusters going down with a DR, we still need some accessibility of that because that's one of the biggest, you know, fraud and risk application it supports. So we do still maintain some comparable technology. Snowflake is an odd one. It's obviously there is none on-prem. But then, you know, Snowflake, I also feel it's more analytical based technology, not a transactional-based technology, at least in our ecosystem. So for me to replicate that, yes, it'll probably take time, but I can live with that. But my business will not stop because our transactional applications can potentially move over if need to. >> Yeah, and of course, you know, all these big market cap companies, so the Snowflake or Databricks, which is not public yet, but they've got big aspirations. And so, you know, we've seen things like Snowflake do a deal with Dell for on-prem object store. I think they do the same thing with Pure. And so over time, you see, Mongo, you know, extending its estate. And so over time all these things are coming together. I want to step out of this conversation for a second. I just ask you, given the current macroeconomic climate, what are the priorities? You know, obviously, people are, CIOs are tapping the breaks on spending, we've reported on that, but what is it? Is it security? Is it analytics? Is it modernization of the on-prem stack, which you were saying a little bit behind. Where are the priorities today given the economic headwinds? >> So the most important priority right now is growing the business, I would say. It's a different, I know this is more, this is not a very techy or a tech answer that, you know, you would expect, but it's growing the business. We want to acquire more customers and be able to service them as best needed. So the majority of our investment is going in the space where tech can support that initiative. During our earnings call, we released the new pillars of our organization where we will focus on, you know, omnichannel digital experience, and then one experience for customer, whether it's retail, whether it's digital. We want to open up our own experience stores, et cetera. So we are investing in technology where it's going to support those pillars. But the spend is in a way that we are obviously taking away from the things that do not support those. So it's, I would say it's flat for us. We are not like in heavily investing or aggressively increasing our tech budget, but it's more like, hey, switch this off because it doesn't make us money, but now switch this on because this is going to support what we can do with money, right? So that's kind of where we are heading towards. So it's not not driven by technology, but it's driven by business and how it supports our customers and our ability to compete in the market. >> You know, I think Harvir, that's consistent with what we heard in some other work that we've done, our ETR partner who does these types of surveys. We're hearing the same thing, is that, you know, we might not be spending on modernizing our on-prem stack. Yeah, we want to get to the cloud at some point and modernize that. But if it supports revenue, you know, we'll invest in that, and get the, you know, instant ROI. I want to ask you about, you know, this concept of supercloud, this abstracted layer of value on top of hyperscale infrastructure, and maybe on-prem. But we were talking about the integration, for instance, between Snowflake and Salesforce, where you got different data sources and you were explaining that you had great interest in being able to, you know, have a kind of, I'll say seamless, sorry, I know it's an overused word, but integration between the data sources and those two different platforms. Can you explain that and why that's attractive to you? >> Yeah, I'm a big supporter of action where the data is, right? Because the minute you start to move, things are already lost in translation. The time is lost, you can't get to it fast enough. So if, for example, for us, Snowflake, Salesforce, is our actionable platform where we action, we send marketing campaigns, we send customer communication via SMS, in app, as well as via email. Now, we would like to be able to interact with our customers pretty much on a, I would say near real time, but the concept of real time doesn't work well with me because I always feel that if you're observing something, it's not real time, it's already happened. But how soon can I react? That's the question. And given that I have to move that data all the way from our, let's say, engagement platforms like Adobe, and particles of the world into Snowflake first, and then do my modeling in some way, and be able to then put it back into Salesforce, it takes time. Yes, you know, I can do it in a few hours, but that few hours makes a lot of difference. Somebody sitting on my website, you know, couldn't find something, walked away, how soon do you think he will lose interest? Three hours, four hours, he'll probably gone, he will never come back. I think if I can react to that as fast as possible without too much data movement, I think that's a lot of good benefit that this kind of integration will bring. Yes, I can potentially take data directly into Salesforce, but I then now have two copies of data, which is, again, something that I'm not a big (indistinct) of. Let's keep the source of the data simple, clean, and a single source. I think this kind of integration will help a lot if the actions can be brought very close to where the data resides. >> Thank you for that. And so, you know, it's funny, we sometimes try to define real time as before you lose the customer, so that's kind of real time. But I want to come back to this idea of governed data sharing. You mentioned some other clouds, a little bit of Azure, a little bit of Google. In a world where, let's say you go more aggressively, and we know that for instance, if you want to use Google's AI tools, you got to use BigQuery. You know, today, anyway, they're not sort of so friendly with Snowflake, maybe different for the AWS, maybe Microsoft's going to be different as well. But in an ideal world, what I'm hearing is you want to keep the data in place. You don't want to move the data. Moving data is expensive, making copies is badness. It's expensive, and it's also, you know, changes the state, right? So you got governance issues. So this idea of supercloud is that you can leave the data in place and actually have a common experience across clouds. Let's just say, let's assume for a minute Google kind of wakes up, my words, not yours, and says, "Hey, maybe, you know what, partnering with a Snowflake or a Databricks is better for our business. It's better for the customers," how would that affect your business and the value that you can bring to your customers? >> Again, I would say that would be the nirvana state that, you know, we want to get to. Because I would say not everyone's perfect. They have great engineers and great products that they're developing, but that's where they compete as well, right? I would like to use the best of breed as much as possible. And I've been a person who has done this in the past as well. I've used, you know, tools to integrate. And the reason why this integration has worked is primarily because sometimes you do pick the best thing for that job. And Google's AI products are definitely doing really well, but, you know, that accessibility, if it's a problem, then I really can't depend on them, right? I would love to move some of that down there, but they have to make it possible for us. Azure is doing really, really good at investing, so I think they're a little bit more and more closer to getting to that state, and I know seeking our attention than Google at this point of time. But I think there will be a revelation moment because more and more people that I talk to like myself, they're also talking about the same thing. I'd like to be able to use Google's AdSense, I would like to be able to use Google's advertising platform, but you know what? I already have all this data, why do I need to move it? Can't they just go and access it? That question will keep haunting them (indistinct). >> You know, I think, obviously, Microsoft has always known, you know, understood ecosystems. I mean, AWS is nailing it, when you go to re:Invent, it's all about the ecosystem. And they think they realized they can make a lot more money, you know, together, than trying to have, and Google's got to figure that out. I think Google thinks, "All right, hey, we got to have the best tech." And that tech, they do have the great tech, and that's our competitive advantage. They got to wake up to the ecosystem and what's happening in the field and the go-to-market. I want to ask you about how you see data and cloud evolving in the future. You mentioned that things that are driving revenue are the priorities, and maybe you're already doing this today, but my question is, do you see a day when companies like yours are increasingly offering data and software services? You've been around for a long time as a company, you've got, you know, first party data, you've got proprietary knowledge, and maybe tooling that you've developed, and you're becoming more, you're already a technology company. Do you see someday pointing that at customers, or again, maybe you're doing it already, or is that not practical in your view? >> So data monetization has always been on the charts. The reason why it hasn't seen the light is regulatory pressure at this point of time. We are partnering up with certain agencies, again, you know, some pilots are happening to see the value of that and be able to offer that. But I think, you know, eventually, we'll get to a state where our, because we are trying to build accessible financial services, we will be in a state that we will be offering those to partners, which could then extended to their customers as well. So we are definitely exploring that. We are definitely exploring how to enrich our data with other data, and be able to complete a super set of data that can be used. Because frankly speaking, the data that we have is very interesting. We have trends of people migrating, we have trends of people migrating within the US, right? So if a new, let's say there's a new, like, I'll give you an example. Let's say New York City, I can tell you, at any given point of time, with my data, what is, you know, a dominant population in that area from migrant perspective. And if I see a change in that data, I can tell you where that is moving towards. I think it's going to be very interesting. We're a little bit, obviously, sometimes, you know, you're scared of sharing too much detail because there's too much data. So, but at the end of the day, I think at some point, we'll get to a state where we are confident that the data can be used for good. One simple example is, you know, pharmacies. They would love to get, you know, we've been talking to CVS and we are talking to Walgreens, and trying to figure out, if they would get access to this kind of data demographic information, what could they do be better? Because, you know, from a gene pool perspective, there are diseases and stuff that are very prevalent in one community versus the other. We could probably equip them with this information to be able to better, you know, let's say, staff their pharmacies or keep better inventory of products that could be used for the population in that area. Similarly, the likes of Walmarts and Krogers, they would like to have more, let's say, ethnic products in their aisles, right? How do you enable that? That data is primarily, I think we are the biggest source of that data. So we do take pride in it, but you know, with caution, we are obviously exploring that as well. >> My last question for you, Harvir, is I'm going to ask you to do a thought exercise. So in that vein, that whole monetization piece, imagine that now, Harvir, you are running a P&L that is going to monetize that data. And my question to you is a there's a business vector and a technology vector. So from a business standpoint, the more distribution channels you have, the better. So running on AWS cloud, partnering with Microsoft, partnering with Google, going to market with them, going to give you more revenue. Okay, so there's a motivation for multi-cloud or supercloud. That's indisputable. But from a technical standpoint, is there an advantage to running on multiple clouds or is that a disadvantage for you? >> It's, I would say it's a disadvantage because if my data is distributed, I have to combine it at some place. So the very first step that we had taken was obviously we brought in Snowflake. The reason, we wanted our analytical data and we want our historical data in the same place. So we are already there and ready to share. And we are actually participating in the data share, but in a private setting at the moment. So we are technically enabled to share, unless there is a significant, I would say, upside to moving that data to another cloud. I don't see any reason because I can enable anyone to come and get it from Snowflake. It's already enabled for us. >> Yeah, or if somehow, magically, several years down the road, some standard developed so you don't have to move the data. Maybe there's a new, Mogli is talking about a new data architecture, and, you know, that's probably years away, but, Harvir, you're an awesome guest. I love having you on, and really appreciate you participating in the program. >> I appreciate it. Thank you, and good luck (indistinct) >> Ah, thank you very much. This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more great coverage from Supercloud 2. (uplifting music)