>>How do y'all and welcome back to the cube where we're live from Dallas at a Supercomputing 2022. My name is Savannah Peterson. Joined with L AED today, as well as some very exciting guests talking about one of my favorite and most complex topics out there, talking about quantum a bit today. Please welcome Ken and Matthew. Thank you so much for reading here. Matthew. Everyone's gonna be able to see your shirt. What's going on with hybrid quantum? I have >>To ask. Wait, what is hybrid quantum? Yeah, let's not pretend that. >>Let's not >>Pretend that everybody knows, Everyone already knows what quantum computing is if we goes straight to highway. Yeah. Okay. So with the brief tour detour took qu regular quantum computing. Yeah, >>No, no. Yeah. Let's start with quantum start before. >>So you know, like regular computers made of transistors gives us ones and zeros, right? Binary, like you were talking about just like half of the Cheerios, right? The joke, it turns out there's some problems that even if we could build a computer as big as the whole universe, which would be pretty expensive, >>That might not be a bad thing, but >>Yeah. Yeah. Good for Dell Got mill. >>Yeah. >>Yeah. We wouldn't be able to solve them cuz they scale exponentially. And it turns out some of those problems have efficient solutions in quantum computing where we take any two state quantum system, which I'll explain in a sec and turn it into what we call a quantum bit or qubit. And those qubits can actually solve some problems that are just infeasible on even these world's largest computers by offering exponential advantage. And it turns out that today's quantum computers are a little too small and a little too noisy to do that alone. So by pairing a quantum computer with a classical computer, hence the partnership between IQ and Dell, you allow each kind of compute to do what it's best at and thereby get answers you can't get with either one alone. >>Okay. So the concept of introducing hybridity, I love that word bridge. I dunno if I made it up, but it's it for it. Let's about it. Abri, ding ding. So does this include simulating the quantum world within the, what was the opposite? The classical quantum world? Classical. Classical, classical computer. Yeah. So does it include the concept of simulating quantum in classical compute? >>Absolutely. >>Okay. How, how, how do, how do you do that? >>So there's simulators and emulators that effectively are programmed in exactly the same way that a physical quantum machine is through circuits translated into chasm or quantum assembly language. And those are the exact same ways that you would program either a physical q p or a simulated >>Q p. So, so access to quantum computing today is scarce, right? I mean it's, it's, it's, it's limited. So having the ability to have the world at large or a greater segment of society be able to access this through simulation is probably a good idea. >>Fair. It's absolutely a wonderful one. And so I often talk to customers and I tell them about the journey, which is hands on keyboard, learning, experimentation, building proof of concepts, and then finally productization. And you could do much of that first two steps anyway very robustly with simulation. >>It's much like classical computing where if you imagine back in the fifties, if, if the cube was at some conference in 1955, you know, we wouldn't have possibly been able to predict what we'd be doing with computing 70 years later, right? Yeah. That teenagers be making apps on their phones that changed the world, right? And so by democratizing access this way, suddenly we can open up all sorts of new use cases. We sort of like to joke, there's only a couple hundred people in the world who really know how to program quantum computers today. And so how are we gonna make thousands, tens of thousands, millions of quantum programmers? The answer is access and simulators are an amazingly accessible way for everyone to start playing around with the >>Fields. Very powerful tool. >>Wow. Yeah. I'm just thinking about how many, there's, are there really only hundreds of people who can program quantum computing? >>I kind of generally throw it out there and I say, you know, if you looked at a matrix of a thousand operations with hundreds of qubits, there's probably, I don't know, 2000 people worldwide that could program that type of a circuit. I mean it's a fairly complex circuit at that point and >>I, I mean it's pretty phenomenal When you think about how early we are in adoption and, and the rollout of this technology as a whole, can you see quite a bit as, as you look across your customer portfolio, what are some of the other trends you're seeing? >>Well, non quantum related trends or just any type you give us >>Both. >>Yeah. So >>We're a thought leader. This is >>Your moment. Yeah, so we do quite a bit. We see quite a bit actually. There's a lot of work happening at the edge as you're probably well aware of. And we see a lot of autonomous mobile robots. I actually lead the, the research office. So I get to see all the cool stuff that's really kind of emerging before it really regrets >>What's coming next. >>Let's see, Oh, I can't tell you what's coming next, but we see edge applications. Yes, we see a lot of, of AI applications and artificial intelligence is morphing dramatically through the number of frameworks and through the, the types and places you would place ai, even places I, I personally never thought we would go like manufacturing environments. Some places that were traditionally not very early adopters. We're seeing AI move very quickly in some of those areas. One of the areas that I'm really excited about is digital twins and the ability to eventually do, let's come up on acceleration with quantum technologies on, on things like computational fluid dynamics. And I think it's gonna be a wonderful, wonderful area for us moving forward. >>So, So I can hear the people screaming at the screen right now. Wait a minute, You said it was hybrid, you're only talking the front half. That's, that's cat. What about the back half? That's dog. What about the quantum part of it? So I, on Q and, and I apologize. Ion Q >>Ion >>Q, Yeah Ion Q cuz you never know. You never never know. Yeah. Where does the actual quantum come in? >>That's a great >>Question. So you guys have one of these things. >>Yeah, we've built, we currently have the world's best quantum computer by, by sub measures I drop there. Yeah, no big deal. Give me some snaps for that. Yeah, Ken knows how to pick em. Yeah, so right. Our, our approach, which is actually based on technology that's 50 years old, so it's quite, quite has a long history. The way we build atomic clocks is the basis for trapped eye quantum computing. And in fact the first quantum logic gate ever made in 1995 was at NIST where they modified their atomic clock experiment to do quantum gates. And that launched really the hardware experimentalist quantum Peter Revolution. And that was by Chris Monroe, our co-founder. So you know that history has flown directly into us. So to simplify, we start with an ion trap. Imagine a gold block with a bunch of electrodes that allow you to make precisely shaped electromagnetic fields, sort of like a rotating saddle. >>Then take a source of atoms. Now obviously we're all sources of atoms. We have a highly purified source of metal atium. We heat it up, we get a nice hot plume of atoms, we ionize those atoms with an ionizing later laser. Now they're hot and heavy and charged. So we can trap them in one of these fields. And now our electromagnetic field that's spitting rapidly holds the, the ions like balls in a bowl if you can imagine them. And they line up in a nice straight line and we hold them in place with these fields and with cooling laser beams. And up to now, that's how an atomic clock works. Trap an item and shine it with a laser beam. Count the oscillations, that's your clock. Now if you got 32 of those and you can manipulate their energy states, in our case we use the hyper fine energy states of the atom. >>But you can basically think of your high school chemistry where you have like an unexcited electron, an excited electron. Take your unexcited state as a zero, your excited state as a one. And it turns out with commercially available lasers, you can drive anywhere between a zero, a one or a super position of zero and one. And so that is our quantum bit, the hyper fine energy state of the atrium atom. And we just line up a bunch of them and through there access the magical powers of supervision entanglement, as we were talking about before, they don't really make sense to us here in the regular world, but >>They do exist. But what you just described is one cubit. That's right. And the way that you do it isn't exactly the same way that others who are doing quantum computing do it. That's right. Is that okay? >>And there's a lot of advantages to the trapped iron approach. So for example, you can also build a super conducting qubit where you, where you basically cool a chip to 47 mil kelvin and coerce millions of atoms to work together as a single system. The problem is that's not naturally quantum. So it's inherently noisy and it wants to deco here does not want to be a quantum bit. Whereas an atom is very happy to be by itself a qubit because we don't have to do anything to it. It's naturally quantum, if that makes sense. And so atomic qubits, like we use feature a few things. One the longest coherence times in the industry, meaning you can run very deep circuits, the most accurate operations, very low noise operations. And we don't have any wires. Our atoms are connected by laser light. That means you can connect any pair. So with some other technologies, the qubits are connected by wires. That means you can only run operations between physically connected qubits. It's like programming. If you could only use, for example, bits that are adjacent with an i untrapped approach, you can connect any pair so that all to all connectivity means your compilation is much more efficient and you can do much wider and deeper circuits. >>So what's the, what is the closest thing to a practical application that we've been able to achieve at this point? Question. And when I say practical, it doesn't have to be super practical. I mean, what is the, what is the sort of demonstration, the least esoteric demonstration of this at this point? >>To tie into what Ken was saying earlier, I think there's at least two areas that are very exciting. One is chemistry. Chemistry. So for example, you know, we have water in our cup and we understand water pretty well, but there's lots of molecules that in order to study them, we actually have to make them in a lab and do lots of experiments. And to give you a sense of the order of magnitude, if you wanted to understand the ground state of the caffeine molecule, which we all know and has 200 electrons, you would need to build a computer bigger than the moon. So, which is, you know, again, would be good profit for Dell, but probably not gonna happen time soon. That's >>Kind of fun to think about though. Yeah, that's a great analogy. That >>Was, yeah. And in fact it'd be like 10 moons of compute. Okay. So build 10 moons of >>Computer. I >>Love the sci-fi issue. Exactly. And now you can calculate caffeine, it's crazy or it just fits in a quantum computer the size of this table. And so we're using hybrid quantum computing now to start proving out these algorithms not for molecules as complex as caffeine or what we want in the future. Like biologics, you know, new cancer medications, new materials and so forth. But we are able to show, for example, the ground state of smaller molecules and prove a path to where, you know, decision maker could see in a few years from now, Oh, we'll be able to actually simulate not molecules we already understand, but molecules we've never been able to study a prayer, if that makes sense. And then, >>Yeah, I think there's a key point underneath that, and I think goes back to the question that you asked earlier about the why hybrid applications inherently run on the classical infrastructure and algorithms are accelerated through qs, the quantum processing units. >>And so are you sort of time sharing in the sense that this environment that you set up starts with classical, with simulation and then you get to a point where you say, okay, we're ready, you pick up the bat phone and you say I wanna, >>I would say it's more like a partnership, really. Yeah, >>Yeah. And I think, I think it's kind of the, the way I normally describe it is, you know, we've taken a look at it it from a really kind of a software development life cycle type of perspective where again, if you follow that learn experiment, pro proof of concept, and then finally productize, we, we can cover and allow for a developer to start prototyping and proofing on simulators and when they're ready all they do is flip a switch and a manifest and they can automatically engage a qu a real quantum physical quantum system. And so we've made it super simple and very accessible in a democratizing access for developers. >>Yeah. Makes such big difference. Go ahead. >>A good analogy is to like GPUs, right? Where it's not really like, you know, you send it away, but rather the GPU accelerates certain operations. The q p. Yeah, because quantum mechanics, it turns out the universe runs on linear algebra. So one way to think about the q p is the most efficient way of doing linear algebra that exists. So lots of problems that can be expressed in that form. Combinatorial optimization problems in general, certain kinds of machine learning, et cetera, get an exponential speed up by running a section of the algorithm on the quantum computer. But of course you wouldn't like port Microsoft Word. Yeah, exactly. You know, you're not gonna do that in your product. It would be a waste of your quantum computer. >>Not just that you wanna know exactly how much money is in your bank account, not probabilistically how much might be ballpark. Yeah. Realm 10, moon ballpark, right? >>10 moon ballpark. Be using that for the rest of the show. Yeah. Oh, I love that. Ken, tell me a little bit about how you identify companies and like I n Q and and end up working with Matthew. What, what's that like, >>What's it like or how do you >>Find it's the process? Like, so, you know, let's say I've got the the >>We're not going there though. Yeah. We're not >>Personal relationship. >>Well, >>You can answer these questions however you want, you know. No, but, but what does that look like for Dell? How do you, how do you curate and figure out who you're gonna bring into this partnership nest? >>Yeah, you know, I, I think it was a, it's, it was a, a very long drawn out learning opportunity. We started actually our working quantum back in 2016. So we've been at it for a long time. And only >>In quantum would we say six years is a long time. I love >>That. Exactly. >>By the way, that was like, we've been doing this for age for a >>Long time. Yeah. Very long time before >>You were born. Yes. >>Feels like it actually, believe it or not. But, so we've been at it for a long time and you know, we went down some very specific learning paths. We took a lot of different time to, to learn about different types of qubits available, different companies, what their approaches were, et cetera. Yeah. And, and we ended up meeting up with, with I N Q and, and we also have other partners as well, like ibm, but I N q you know, we, there is a nice symbiotic relationship. We're actually doing some really cool technologies that are even much, much further ahead than the, you know, strict classical does this, quantum does that where there's significant amount of interplay between the simulation systems and between the real physical QS. And so it's, it's turning out to be a great relationship. They're, they're very easy to work with and, and a lot of fun too, as you could probably tell. Yeah. >>Clearly. So before we wrap, I've got it. Okay. Okay. So get it. Let's get, let's get, yeah, let's get deep. Let's get deep for a second or a little deeper than we've been. So our current, our current understanding of all this, of the universe, it's pretty limited. It's down to the point where we effectively have it assigned to witchcraft. It's all dark energy and dark matter. Right. What does that mean exactly? Nobody knows. But if you're in the quantum computing space and you're living this every day, do you believe that it represents the key to us understanding things that currently we just can't understand classical models, including classical computing, our brains as they're constructed aren't capable of understanding the real real that's out there. Yeah. If you're in the quantum computing space, do you possess that level of hubris? Do you think that you are gonna deliver the answers? >>I'm just like, I think the more you're in the space, the more mysterious and amazing it all seems. There's a, but there is a great quote by Richard Feinman that sort of kicked off the quantum exploration. So he gave a lecture in 1981, so, you know, long before any of this began, truly ages ago, right? Yeah. And in this lecture he said, you know, kind of wild at that time, right? We had to build these giant supercomputers to simulate just a couple atoms interacting, right? And it's kind of crazy that you need all this compute to simulate what nature does with just a handful >>Particles. Yeah. >>Really small. So, and, and famously he said, you know, nature just isn't classical. Damn it. And so you need to build a computer that works with nature to understand nature. I think, you know, the, the quantum revolution has only just begun. There's so many new things to learn, and I'm sure the quantum computers of 40 years from now are not gonna look like the, you know, the computers of today, just as the classical computers of 40 years ago look quite different to us now, >>And we're a bunch of apes. But you think we'll get there? >>I, yeah, I, I mean, I, I have, I think we have, I feel incredibly optimistic that this tool, quantum computing as a tool represents a sea change in what's possible for humans to compute. >>Yeah. I think it's that possibility. You know, I, when I tell people right now in the quantum era, we're in the inac stage of the quantum era, and so we have a long way to go, but the potential is absolutely enormous. In fact, incomprehensibly enormous, I >>Was just gonna say, I don't even think we could grasp >>In the, from the inac is they had no idea of computers inside of your hand, right? Yeah. >>They're calculating, you know, trajectories, right? Yeah. If you told them, like, we'd all be video chatting, you >>Know, >>Like, and kids would be doing synchronized dances, you know, you'd be like, What? >>I love that. Well, well, on that note, Ken Matthew, really great to have you both, everyone now will be pondering the scale and scope of the universe with their 10 moon computer, 10 moons. That's right. And, and you've given me my, my new favorite bumper sticker since we've been on a, on a roll here, David and I, which is just naturally quantum. Yeah, that's, that's, that's, that's one of my new favorite phrases from the show. Thank you both for being here. David, thank you for hanging out and thank all of you for tuning in to our cube footage live here in Dallas. We are at Supercomputing. This is our last show for the day, but we look forward to seeing you tomorrow morning. My name's Savannah Peterson. Y'all have a lovely night.

(atmospheric music) >> Welcome to theCUBE Coverage of Data Citizens 2022 Collibra's Customer event. My name is Dave Vellante. With us is Kirk Haslbeck, who's the Vice President of Data Quality of Collibra. Kirk, good to see you, welcome. >> Thanks for having me, Dave. Excited to be here. >> You bet. Okay, we're going to discuss data quality, observability. It's a hot trend right now. You founded a data quality company, OwlDQ, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >> Yeah, absolutely. It's definitely exciting times for data quality which you're right, has been around for a long time. So why now? And why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before, and the variety has changed and the volume has grown. And while I think that remains true there are a couple other hidden factors at play that everyone's so interested in as to why this is becoming so important now. And I guess you could kind of break this down simply and think about if Dave you and I were going to build a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, what the ramifications could be, what those incidents would look like. Or maybe better yet, we try to build a new trading algorithm with a crossover strategy where the 50 day crosses the 10 day average. And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, kind of starts there, where everybody's realizing that we're all data companies, and if we are using bad data we're likely making incorrect business decisions. But I think there's kind of two other things at play. I bought a car not too long ago and my dad called and said, "How many cylinders does it have?" And I realized in that moment, I might have failed him cause I didn't know. And I used to ask those types of questions about any lock breaks and cylinders, and if it's manual or automatic. And I realized, I now just buy a car that I hope works. And it's so complicated with all the computer chips. I really don't know that much about it. And that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the individuals loading and consuming all of this data for the company actually may not know that much about the data itself and that's not even their job anymore. So, we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >> You know, the other thing too about data quality, and for years we did the MIT, CDO, IQ event. We didn't do it last year at COVID, messed everything up. But the observation I would make there, your thoughts is, data quality used to be information quality, used to be this back office function, and then it became sort of front office with financial services, and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well they sort of flipped the bit from sort of a data as a risk to data as an asset. And now as we say, we're going to talk about observability. And so it's really become front and center, just the whole quality issue because data's so fundamental, hasn't it? >> Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my favorite stock ticker app, and I check out the Nasdaq market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And that's kind of what's going on. There's so many numbers and they're coming from all of these different sources, and data providers, and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before Collibra. And what's been so exciting is, we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting, and why I think the CDO is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale, and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's not ever going to be based on one or two domain experts anymore. >> So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they cousins? What's your perspective on that? >> Yeah, it's super interesting. It's an emerging market. So the language is changing, a lot of the topic and areas changing. The way that I like to say it or break it down because the lingo is constantly moving, as a target on the space is really breaking records versus breaking trends. And I could write a condition when this thing happens it's wrong, and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. Everybody's talking about fresh data and stale data, and why would that matter? Well, if your data never arrived, or only part of it arrived, or didn't arrive on time, it's likely stale, and there will not be a condition that you could write that would show you all the good and the bads. That was kind of your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data. But it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there, there's more than a couple of these happening every day. >> So what's the Collibra angle on all this stuff? Made the acquisition, you got data quality, observability coming together. You guys have a lot of expertise in this area, but you hear providence of data. You just talked about stale data, the whole trend toward realtime. How is Collibra approaching the problem and what's unique about your approach? >> Well I think where we're fortunate is with our background. Myself and team, we sort of lived this problem for a long time in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with, before it was called data observability or reliability, was basically the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution. It's more advanced than some of the observation techniques that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights. And they want to see break records and breaking trends together, so they can correlate the root cause. And we hear that all the time. "I have so many things going wrong just show me the big picture. Help me find the thing that if I were to fix it today would make the most impact." So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows you can actually achieve total data governance. At this point with the acquisition of what was a Lineage company years ago, and then my company OwlDQ, now Collibra Data Quality. Collibra may be the best positioned for total data governance and intelligence in the space. >> Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was. They would just say, "Oh, it's a glitch." So they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you got to announce new products, right? It is your yearly event. What's new? Give us a sense as to what products are coming out but specifically around data quality and observability. >> Absolutely. There's this, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and BigQuery, and Databricks, Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook into these databases, and while we've always worked with the same databases in the past they're supported today. We're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now? Is everyone's concerned with something called Egress. Did my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? And with these native integrations that we're building and about to unveil here as kind of a sneak peak for next week at Data Citizens, we're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >> So this is interesting because what you just described, you mentioned Snowflake, you mentioned Google, oh actually you mentioned yeah, Databricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool. But then Google's got the open data cloud. If you heard, Google next. And now Databricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way, up until now I'm hearing, to really understand the relationships between all those and have confidence across, it's like yamarket AMI, you should just be a note on the mesh. I don't care if it's a data warehouse or a data lake, or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And that's what you're bringing to the table. Is that right? Did I get that right? >> Yeah, that's right. And it's, for us, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now we can send them the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network cost, zero egress cost, zero latency of time. And so when you were to log into BigQuery tomorrow using our tool, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage in access, privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there just like all of the major brands that you mentioned but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And we think that this positions us to be the leader there. >> I love this example because, we've got talks about well the cloud guys you're going to own the world. And of course now we're seeing that the ecosystem is finding so much white space to add value connect across cloud. Sometimes we call it super cloud and so, or inter clouding. Alright, Kirk, give us your final thoughts on the trends that we've talked about and data Citizens 22. >> Absolutely. Well I think, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there they want to know where everything is, where their sensitive data is, if it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're going to see more one click solutions, more SaaS based solutions, and solutions that hopefully prove faster time to value on all of these modern cloud platforms. >> Excellent. All right, Kirk Haslbeck, thanks so much for coming on theCUBE and previewing Data Citizens 22. Appreciate it. >> Thanks for having me, Dave. >> You're welcome. All right. And thank you for watching. Keep it right there for more coverage from theCUBE. (atmospheric music)

>>Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions and they were largely confined to regulatory regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become and the value proposition for data quality and trust. It evolved from primarily a compliance driven issue to becoming a lynchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. >>And it resulted in a lot of frustration with data initiatives for most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today for example, this quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like data mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business Uni users, you hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that, but also how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. >>In other words, while it's enticing to experiment and run fast and loose with data initiatives kinda like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated. And intelligence governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is gonna use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. >>Hello and welcome to the Cube's coverage of Data Citizens made possible by Calibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Ante and I'm one of the hosts of our program, which is running in parallel to data citizens. Now at the Cube we like to say we extract the signal from the noise, and over the, the next couple of days, we're gonna feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives. Felix Von Dala, who is the co-founder and CEO of Collibra, will join us along with one of the other founders of Collibra, Stan Christians, who's gonna join my colleague Lisa Martin. I'm gonna also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the, the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Hasselbeck. >>He's the vice president of Data quality at Collibra. He's an amazingly smart dude who founded Owl dq, a company that he sold to Col to Collibra last year. Now many companies, they didn't make it through the Hado era, you know, they missed the industry waves and they became Driftwood. Collibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio, and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. >>Last year, the Cube Covered Data Citizens Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hado movement, we had data lakes, we'd spark the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of ai, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights for data, trust the data, and begin to use that data in new ways, fueling data, products, monetization and insights data citizens 2022 is back and we're pleased to have Felix Van Dema, who is the founder and CEO of Collibra. He's on the cube or excited to have you, Felix. Good to see you again. >>Likewise Dave. Thanks for having me again. >>You bet. All right, we're gonna get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Collibra has been up to over the past year and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >>Yeah, absolutely. And, and I think you said it well, Dave, and and the intro that that rising complexity and fragmentation in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kinda more, more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well, which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. >>So it's become much more acute. And, and to your earlier point, we do live in a different world and and the the past couple of years we could probably just kind of brute for it, right? We could focus on, on the top line. There was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are, are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, How do we truly get value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale it data, not just from a a technology and infrastructure perspective, but how do you actually scale data from an organizational perspective, right? You said at the the people and process, how do we do that at scale? And that's only, only only becoming much more important. And we do believe that the, the economic environment that we find ourselves in today is gonna be catalyst for organizations to really dig out more seriously if, if, if, if you will, than they maybe have in the have in the best. >>You know, I don't know when you guys founded Collibra, if, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >>Yeah, absolutely. We, we started Colli in 2008. So in some sense and the, the last kind of financial crisis, and that was really the, the start of Colli where we found product market fit, working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis and kind of here we are again in a very different environment, of course 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we are still relatively early in that, in that journey. >>Well, that's interesting because, you know, in my observation it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your, your current momentum? >>Yeah, absolutely. Again, there's, there's a lot of tail organizations that are only maturing the data practices and we've seen it kind of transform or, or, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in, in the, in the markets with some of the cloud partners like Google, Amazon, Snowflake, data bricks and, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners and of course our customers to help them kind of transition to the cloud even faster. >>And so we see a lot of excitement and momentum there within an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging ai, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architecture arch architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical so that they're really excited about about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believe. Then federated focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations. And so that aligns really well with our vision and, and from a product perspective, we've seen a lot of momentum with our customers there as well. >>Yeah, you know, a couple things there. I mean, the acquisition of i l dq, you know, Kirk Hasselbeck and, and their team, it's interesting, you know, the whole data quality used to be this back office function and, and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh. You mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the, the products. We're gonna go deeper in into products later on at, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the, the the under the covers in security, sort of making data more accessible for people just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >>Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission, either customers are still start, are just starting on that, on that journey. We wanna make it as easy as possible for the, for our organization to actually get started because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to, to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving. >>A lot of kind of ease of adoption, ease of use, but also then how do we make sure that lio becomes this kind of mission critical enterprise platform from a security performance architecture scale supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme from an innovation perspective, From a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction, how to make it easy. How do we make, how do we make available to true kind of shopping experience that anybody in your organization can, in a very easy search first way, find the right data product, find the right dataset, that data can then consume usage analytics. How do you, how do we help organizations drive adoption, tell them where they're working really well and where they have opportunities homepages again to, to make things easy for, for people, for anyone in your organization to kind of get started with ppia, you mentioned workflow designer, again, we have a very powerful enterprise platform. >>One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around K Bear Protect, which in partnership with Snowflake, which has been a strategic investor in kib, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as much more effective, effective rate, really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. >>So we launch more data quality cloud product as well as making use of those, those native compute capabilities in platforms like Snowflake, Data, Bricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down. So actually pushing down the computer and data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is gonna make a massive difference. And then more broadly, we, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So there's a lot coming out. The, the team has been work at work really hard and we are really, really excited about what we are coming, what we're bringing to markets. >>Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard. So how do you see sort of the future and, you know, give us the, your closing thoughts please? >>Yeah, absolutely. And I, and I think we we're really at this pivotal moment, and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can. It's kind of, of our, it's our mission. And so I'm really, really excited to see what we, what we are gonna, how the marks gonna evolve over the next, next few quarters and years. I think the trend is clearly there when we talk about data mesh, this kind of federated approach folks on data products is just another signal that we believe that a lot of our organization are now at the time. >>The understanding need to go beyond just the technology. I really, really think about how do we actually scale data as a business function, just like we've done with it, with, with hr, with, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in much more focus on control, much more focused on productivity efficiency and now's the time. We need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >>Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much and good luck in, in San Diego. I know you're gonna crush it out there. >>Thank you Dave. >>Yeah, it's a great spot for an in-person event and, and of course the content post event is gonna be available@collibra.com and you can of course catch the cube coverage@thecube.net and all the news@siliconangle.com. This is Dave Valante for the cube, your leader in enterprise and emerging tech coverage. >>Hi, I'm Jay from Collibra's Data Office. Today I want to talk to you about Collibra's data intelligence cloud. We often say Collibra is a single system of engagement for all of your data. Now, when I say data, I mean data in the broadest sense of the word, including reference and metadata. Think of metrics, reports, APIs, systems, policies, and even business processes that produce or consume data. Now, the beauty of this platform is that it ensures all of your users have an easy way to find, understand, trust, and access data. But how do you get started? Well, here are seven steps to help you get going. One, start with the data. What's data intelligence? Without data leverage the Collibra data catalog to automatically profile and classify your enterprise data wherever that data lives, databases, data lakes or data warehouses, whether on the cloud or on premise. >>Two, you'll then wanna organize the data and you'll do that with data communities. This can be by department, find a business or functional team, however your organization organizes work and accountability. And for that you'll establish community owners, communities, make it easy for people to navigate through the platform, find the data and will help create a sense of belonging for users. An important and related side note here, we find it's typical in many organizations that data is thought of is just an asset and IT and data offices are viewed as the owners of it and who are really the central teams performing analytics as a service provider to the enterprise. We believe data is more than an asset, it's a true product that can be converted to value. And that also means establishing business ownership of data where that strategy and ROI come together with subject matter expertise. >>Okay, three. Next, back to those communities there, the data owners should explain and define their data, not just the tables and columns, but also the related business terms, metrics and KPIs. These objects we call these assets are typically organized into business glossaries and data dictionaries. I definitely recommend starting with the topics that are most important to the business. Four, those steps that enable you and your users to have some fun with it. Linking everything together builds your knowledge graph and also known as a metadata graph by linking or relating these assets together. For example, a data set to a KPI to a report now enables your users to see what we call the lineage diagram that visualizes where the data in your dashboards actually came from and what the data means and who's responsible for it. Speaking of which, here's five. Leverage the calibra trusted business reporting solution on the marketplace, which comes with workflows for those owners to certify their reports, KPIs, and data sets. >>This helps them force their trust in their data. Six, easy to navigate dashboards or landing pages right in your platform for your company's business processes are the most effective way for everyone to better understand and take action on data. Here's a pro tip, use the dashboard design kit on the marketplace to help you build compelling dashboards. Finally, seven, promote the value of this to your users and be sure to schedule enablement office hours and new employee onboarding sessions to get folks excited about what you've built and implemented. Better yet, invite all of those community and data owners to these sessions so that they can show off the value that they've created. Those are my seven tips to get going with Collibra. I hope these have been useful. For more information, be sure to visit collibra.com. >>Welcome to the Cube's coverage of Data Citizens 2022 Collibra's customer event. My name is Dave Valante. With us is Kirk Hasselbeck, who's the vice president of Data Quality of Collibra Kirk, good to see you. Welcome. >>Thanks for having me, Dave. Excited to be here. >>You bet. Okay, we're gonna discuss data quality observability. It's a hot trend right now. You founded a data quality company, OWL dq, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >>Yeah, absolutely. It's, it's definitely exciting times for data quality, which you're right, has been around for a long time. So why now and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And, and while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as, as to why this is becoming so important now. And, and I guess you could kind of break this down simply and think about if Dave, you and I were gonna build, you know, a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, you know, what the ramifications could be, what, what those incidents would look like, or maybe better yet, we try to build a, a new trading algorithm with a crossover strategy where the 50 day crosses the, the 10 day average. >>And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, you know, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. You know, I, I bought a car not too long ago and my dad called and said, How many cylinders does it have? And I realized in that moment, you know, I might have failed him because, cause I didn't know. And, and I used to ask those types of questions about any lock brakes and cylinders and, and you know, if it's manual or, or automatic and, and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips, I, I really don't know that much about it. >>And, and that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the, the individuals loading and consuming all of this data for the company actually may not know that much about the data itself, and that's not even their job anymore. So we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >>You know, the other thing too about data quality, and for years we did the MIT CDO IQ event, we didn't do it last year, Covid messed everything up. But the observation I would make there thoughts is, is it data quality? Used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a, a risk to data as a, as an asset. And now as we say, we're gonna talk about observability. And so it's really become front and center just the whole quality issue because data's so fundamental, hasn't it? >>Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my, my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And, and that's kind of what's going on. There's, there's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before calibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is, is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, you know, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's, it's not ever going to be based on one or two domain experts anymore. >>So, So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they, are they cousins? What's your perspective on that? >>Yeah, it's, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the, the lingo is constantly moving is, you know, as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens, it's wrong and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. You know, everybody's talking about fresh data and stale data and, and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good in the bads. That was kind of your, your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data, but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >>So what's the Collibra angle on all this stuff made the acquisition, you got data quality observability coming together, you guys have a lot of expertise in, in this area, but you hear providence of data, you just talked about, you know, stale data, you know, the, the whole trend toward real time. How is Calibra approaching the problem and what's unique about your approach? >>Well, I think where we're fortunate is with our background, myself and team, we sort of lived this problem for a long time, you know, in, in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the, the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution, it's more advanced than some of the observation techniques that that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights, and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong, just show me the big picture, help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows, you can actually achieve total data governance at this point with the acquisition of what was a Lineage company years ago, and then my company Ldq now Collibra, Data quality Collibra may be the best positioned for total data governance and intelligence in the space. >>Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, you know, they just said, Oh, it's a glitch, you know, so they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you gotta announce new products, right? You're yearly event what's, what's new. Give us a sense as to what products are coming out, but specifically around data quality and observability. >>Absolutely. There's this, you know, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks is Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook in to these databases. And while we've always worked with the the same databases in the past, they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did your, my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? >>And with these native integrations that we're building and about to unveil, here's kind of a sneak peek for, for next week at Data Citizens. We're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration, you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress, cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >>So this is interesting because what you just described, you know, you mentioned Snowflake, you mentioned Google, Oh actually you mentioned yeah, data bricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool, but then Google's got the open data cloud. If you heard, you know, Google next and now data bricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm, I'm hearing to, to really understand the relationships between all those and have confidence across, you know, it's like Jak Dani, you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And, and, and that's what you're bringing to the table, Is that right? Did I get that right? >>Yeah, that's right. And it's, for us, it's, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now, we can send them the, the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network costs, zero egress cost, zero latency of time. And so when you were to log into Big Query tomorrow using our tool or like, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there, just like all of the major brands that you mentioned, but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And, and we think that this positions us to be the leader there. >>I love this example because, you know, Barry talks about, wow, the cloud guys are gonna own the world and, and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. All right, Kirk, give us your, your final thoughts and on on the trends that we've talked about and Data Citizens 22. >>Absolutely. Well, I think, you know, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there, they wanna know where everything is, where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're gonna see more one click solutions, more SAS based solutions and solutions that hopefully prove faster time to value on, on all of these modern cloud platforms. >>Excellent. All right, Kurt Hasselbeck, thanks so much for coming on the Cube and previewing Data Citizens 22. Appreciate it. >>Thanks for having me, Dave. >>You're welcome. Right, and thank you for watching. Keep it right there for more coverage from the Cube. Welcome to the Cube's virtual Coverage of Data Citizens 2022. My name is Dave Valante and I'm here with Laura Sellers, who's the Chief Product Officer at Collibra, the host of Data Citizens. Laura, welcome. Good to see you. >>Thank you. Nice to be here. >>Yeah, your keynote at Data Citizens this year focused on, you know, your mission to drive ease of use and scale. Now when I think about historically fast access to the right data at the right time in a form that's really easily consumable, it's been kind of challenging, especially for business users. Can can you explain to our audience why this matters so much and what's actually different today in the data ecosystem to make this a reality? >>Yeah, definitely. So I think what we really need and what I hear from customers every single day is that we need a new approach to data management and our product teams. What inspired me to come to Calibra a little bit a over a year ago was really the fact that they're very focused on bringing trusted data to more users across more sources for more use cases. And so as we look at what we're announcing with these innovations of ease of use and scale, it's really about making teams more productive in getting started with and the ability to manage data across the entire organization. So we've been very focused on richer experiences, a broader ecosystem of partners, as well as a platform that delivers performance, scale and security that our users and teams need and demand. So as we look at, Oh, go ahead. >>I was gonna say, you know, when I look back at like the last 10 years, it was all about getting the technology to work and it was just so complicated. But, but please carry on. I'd love to hear more about this. >>Yeah, I, I really, you know, Collibra is a system of engagement for data and we really are working on bringing that entire system of engagement to life for everyone to leverage here and now. So what we're announcing from our ease of use side of the world is first our data marketplace. This is the ability for all users to discover and access data quickly and easily shop for it, if you will. The next thing that we're also introducing is the new homepage. It's really about the ability to drive adoption and have users find data more quickly. And then the two more areas of the ease of use side of the world is our world of usage analytics. And one of the big pushes and passions we have at Collibra is to help with this data driven culture that all companies are trying to create. And also helping with data literacy, with something like usage analytics, it's really about driving adoption of the CLE platform, understanding what's working, who's accessing it, what's not. And then finally we're also introducing what's called workflow designer. And we love our workflows at Libra, it's a big differentiator to be able to automate business processes. The designer is really about a way for more people to be able to create those workflows, collaborate on those workflow flows, as well as people to be able to easily interact with them. So a lot of exciting things when it comes to ease of use to make it easier for all users to find data. >>Y yes, there's definitely a lot to unpack there. I I, you know, you mentioned this idea of, of of, of shopping for the data. That's interesting to me. Why this analogy, metaphor or analogy, I always get those confused. I let's go with analogy. Why is it so important to data consumers? >>I think when you look at the world of data, and I talked about this system of engagement, it's really about making it more accessible to the masses. And what users are used to is a shopping experience like your Amazon, if you will. And so having a consumer grade experience where users can quickly go in and find the data, trust that data, understand where the data's coming from, and then be able to quickly access it, is the idea of being able to shop for it, just making it as simple as possible and really speeding the time to value for any of the business analysts, data analysts out there. >>Yeah, I think when you, you, you see a lot of discussion about rethinking data architectures, putting data in the hands of the users and business people, decentralized data and of course that's awesome. I love that. But of course then you have to have self-service infrastructure and you have to have governance. And those are really challenging. And I think so many organizations, they're facing adoption challenges, you know, when it comes to enabling teams generally, especially domain experts to adopt new data technologies, you know, like the, the tech comes fast and furious. You got all these open source projects and get really confusing. Of course it risks security, governance and all that good stuff. You got all this jargon. So where do you see, you know, the friction in adopting new data technologies? What's your point of view and how can organizations overcome these challenges? >>You're, you're dead on. There's so much technology and there's so much to stay on top of, which is part of the friction, right? It's just being able to stay ahead of, of and understand all the technologies that are coming. You also look at as there's so many more sources of data and people are migrating data to the cloud and they're migrating to new sources. Where the friction comes is really that ability to understand where the data came from, where it's moving to, and then also to be able to put the access controls on top of it. So people are only getting access to the data that they should be getting access to. So one of the other things we're announcing with, with all of the innovations that are coming is what we're doing around performance and scale. So with all of the data movement, with all of the data that's out there, the first thing we're launching in the world of performance and scale is our world of data quality. >>It's something that Collibra has been working on for the past year and a half, but we're launching the ability to have data quality in the cloud. So it's currently an on-premise offering, but we'll now be able to carry that over into the cloud for us to manage that way. We're also introducing the ability to push down data quality into Snowflake. So this is, again, one of those challenges is making sure that that data that you have is d is is high quality as you move forward. And so really another, we're just reducing friction. You already have Snowflake stood up. It's not another machine for you to manage, it's just push down capabilities into Snowflake to be able to track that quality. Another thing that we're launching with that is what we call Collibra Protect. And this is that ability for users to be able to ingest metadata, understand where the PII data is, and then set policies up on top of it. So very quickly be able to set policies and have them enforced at the data level. So anybody in the organization is only getting access to the data they should have access to. >>Here's Topica data quality is interesting. It's something that I've followed for a number of years. It used to be a back office function, you know, and really confined only to highly regulated industries like financial services and healthcare and government. You know, you look back over a decade ago, you didn't have this worry about personal information, g gdpr, and, you know, California Consumer Privacy Act all becomes, becomes so much important. The cloud is really changed things in terms of performance and scale and of course partnering for, for, with Snowflake it's all about sharing data and monetization, anything but a back office function. So it was kind of smart that you guys were early on and of course attracting them and as a, as an investor as well was very strong validation. What can you tell us about the nature of the relationship with Snowflake and specifically inter interested in sort of joint engineering or, and product innovation efforts, you know, beyond the standard go to market stuff? >>Definitely. So you mentioned there were a strategic investor in Calibra about a year ago. A little less than that I guess. We've been working with them though for over a year really tightly with their product and engineering teams to make sure that Collibra is adding real value. Our unified platform is touching pieces of our unified platform or touching all pieces of Snowflake. And when I say that, what I mean is we're first, you know, able to ingest data with Snowflake, which, which has always existed. We're able to profile and classify that data we're announcing with Calibra Protect this week that you're now able to create those policies on top of Snowflake and have them enforce. So again, people can get more value out of their snowflake more quickly as far as time to value with, with our policies for all business users to be able to create. >>We're also announcing Snowflake Lineage 2.0. So this is the ability to take stored procedures in Snowflake and understand the lineage of where did the data come from, how was it transformed with within Snowflake as well as the data quality. Pushdown, as I mentioned, data quality, you brought it up. It is a new, it is a, a big industry push and you know, one of the things I think Gartner mentioned is people are losing up to $15 million without having great data quality. So this push down capability for Snowflake really is again, a big ease of use push for us at Collibra of that ability to, to push it into snowflake, take advantage of the data, the data source, and the engine that already lives there and get the right and make sure you have the right quality. >>I mean, the nice thing about Snowflake, if you play in the Snowflake sandbox, you, you, you, you can get sort of a, you know, high degree of confidence that the data sharing can be done in a safe way. Bringing, you know, Collibra into the, into the story allows me to have that data quality and, and that governance that I, that I need. You know, we've said many times on the cube that one of the notable differences in cloud this decade versus last decade, I mean ob there are obvious differences just in terms of scale and scope, but it's shaping up to be about the strength of the ecosystems. That's really a hallmark of these big cloud players. I mean they're, it's a key factor for innovating, accelerating product delivery, filling gaps in, in the hyperscale offerings cuz you got more stack, you know, mature stack capabilities and you know, it creates this flywheel momentum as we often say. But, so my question is, how do you work with the hyperscalers? Like whether it's AWS or Google, whomever, and what do you see as your role and what's the Collibra sweet spot? >>Yeah, definitely. So, you know, one of the things I mentioned early on is the broader ecosystem of partners is what it's all about. And so we have that strong partnership with Snowflake. We also are doing more with Google around, you know, GCP and kbra protect there, but also tighter data plex integration. So similar to what you've seen with our strategic moves around Snowflake and, and really covering the broad ecosystem of what Collibra can do on top of that data source. We're extending that to the world of Google as well and the world of data plex. We also have great partners in SI's Infosys is somebody we spoke with at the conference who's done a lot of great work with Levi's as they're really important to help people with their whole data strategy and driving that data driven culture and, and Collibra being the core of it. >>Hi Laura, we're gonna, we're gonna end it there, but I wonder if you could kind of put a bow on, you know, this year, the event your, your perspectives. So just give us your closing thoughts. >>Yeah, definitely. So I, I wanna say this is one of the biggest releases Collibra's ever had. Definitely the biggest one since I've been with the company a little over a year. We have all these great new product innovations coming to really drive the ease of use to make data more valuable for users everywhere and, and companies everywhere. And so it's all about everybody being able to easily find, understand, and trust and get access to that data going forward. >>Well congratulations on all the pro progress. It was great to have you on the cube first time I believe, and really appreciate you, you taking the time with us. >>Yes, thank you for your time. >>You're very welcome. Okay, you're watching the coverage of Data Citizens 2022 on the cube, your leader in enterprise and emerging tech coverage. >>So data modernization oftentimes means moving some of your storage and computer to the cloud where you get the benefit of scale and security and so on. But ultimately it doesn't take away the silos that you have. We have more locations, more tools and more processes with which we try to get value from this data. To do that at scale in an organization, people involved in this process, they have to understand each other. So you need to unite those people across those tools, processes, and systems with a shared language. When I say customer, do you understand the same thing as you hearing customer? Are we counting them in the same way so that shared language unites us and that gives the opportunity for the organization as a whole to get the maximum value out of their data assets and then they can democratize data so everyone can properly use that shared language to find, understand, and trust the data asset that's available. >>And that's where Collibra comes in. We provide a centralized system of engagement that works across all of those locations and combines all of those different user types across the whole business. At Collibra, we say United by data and that also means that we're united by data with our customers. So here is some data about some of our customers. There was the case of an online do it yourself platform who grew their revenue almost three times from a marketing campaign that provided the right product in the right hands of the right people. In other case that comes to mind is from a financial services organization who saved over 800 K every year because they were able to reuse the same data in different kinds of reports and before there was spread out over different tools and processes and silos, and now the platform brought them together so they realized, oh, we're actually using the same data, let's find a way to make this more efficient. And the last example that comes to mind is that of a large home loan, home mortgage, mortgage loan provider where they have a very complex landscape, a very complex architecture legacy in the cloud, et cetera. And they're using our software, they're using our platform to unite all the people and those processes and tools to get a common view of data to manage their compliance at scale. >>Hey everyone, I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizens. Stan, it's great to have you back on the cube. >>Hey Lisa, nice to be. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation. It also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow gonna to be a data citizen, right? So you need to make sure that these people are aware of it. You need that. People have skills and competencies to do with data what necessary and that's on, all right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in dashboard to actually make that decision and take that action. Right? >>And once you have that why to the organization, that's when you have a good data culture. Now that's continuous effort for most organizations because they're always moving, somehow they're hiring new people and it has to be continuous effort because we've seen that on the hand. Organizations continue challenged their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefit. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example, and we did an IDC study earlier this year, quite interesting. I can recommend anyone to it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, ok, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this re reasons you're trying to bring both of those together and the ones that get data intelligence right, are successful and competitive. That's, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, the organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, laptops, what have you, you're not using those, right? Or you know, you're delivering them throughout organization, but not enabling your colleagues to actually do something with that asset. Same thing as through with data today, right? If you're not properly using the data asset and competitors are, they're gonna to get more advantage. So as to how you get this done, establish this. There's angles to look at, Lisa. So one angle is obviously the leadership whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? So I'm just gonna summarize it as a data leader for a second. >>So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can leadership in the organization and also the business value. And that's important. Cause those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You, I really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like s then the in place to really start upgrading that culture inch by inch if you'll, >>Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Calibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speaks here, are very excited. You know, we have Barb from m MIT speaking about data monetization. We have Dilla at the last minute. So really exciting agen agenda. Can't wait to get back out there essentially. So over the years at, we've doing this since two and eight, so a good years and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, if you, so everybody's wearing all sorts of hat at time. But over the years I've run, you know, presales that sales partnerships, product cetera. And as our company got a little bit biggish, we're now thousand two. Something like people in the company. >>I believe systems and processes become a lot important. So we said you CBRA isn't the size our customers we're getting there in of organization structure, process systems, et cetera. So we said it's really time for us to put our money where is and to our own data office, which is what we were seeing customers', organizations worldwide. And they organizations have HR units, they have a finance unit and over time they'll all have a department if you'll, that is responsible somehow for the data. So we said, ok, let's try to set an examples that other people can take away with it, right? Can take away from it. So we set up a data strategy, we started building data products, took care of the data infrastructure. That's sort of good stuff. And in doing all of that, ISA exactly as you said, we said, okay, we need to also use our product and our own practices and from that use, learn how we can make the product better, learn how we make, can make the practice better and share that learning with all the, and on, on the Monday mornings, we sometimes refer to eating our dog foods on Friday evenings. >>We referred to that drinking our own champagne. I like it. So we, we had a, we had the driver to do this. You know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should, this is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders, if you'll or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products can run, the data can flow and you know, the quality can be checked. >>And then we have a data intelligence or data governance builders where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the CBRA approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a map and started execution use of the use case. And a important ones are very simple. We them with our, our customers as well, people talking about the cata, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and privacy. So they have their process registry and they can see how the data flows. >>So that's a starting place and that turns into a marketplace so that if new analysts and data citizens join kbra, they immediately have a place to go to, to look at, see, ok, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? So they can immediately get access data. And another one that we is around trusted business. We're seeing that since, you know, self-service BI allowed everyone to make beautiful dashboards, you know, pie, pie charts. I always, my pet pee is the pie chart because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted this reporting. So we know if a, the dashboard, a data product essentially is built, we not that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either, Right. And that silver browser, right? Absolutely >>Decay. >>Exactly. Yes, >>Absolutely. Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with to your organization, but there's a few that we use that might be of interest. Use those pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Are the, is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data sciences and products. Are people using them? Are they getting value from it? >>Can we calculate that value in ay perspective, right? Yeah. So that we can to the rest of the business continue to say we're tracking all those numbers and those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or, or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so and so forth. So these are an set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in thousand 10 there may have been like 10 achieve data officers or something. Gartner has exact numbers on them, but then they grew, you know, industries and the number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data. So you'll see over the years that's gonna evolve more digital and more data products. So for next years, my, my prediction is it's all products because it's an immediate link between data and, and the essentially, right? Right. So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. I think there's gonna be a continued challenge for the chief officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? >>So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful and the ones who get that will the ones that do it on the basis of data monetization, right? Connecting value to the data and making that value clear to all the data citizens in the organization, right? And in that sense, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an asset. >>Absolutely. Because there's so much value that can be extracted. Organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful and being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the cube at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage. >>Okay, this concludes our coverage of Data Citizens 2022, brought to you by Collibra. Remember, all these videos are available on demand@thecube.net. And don't forget to check out silicon angle.com for all the news and wiki bod.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on the Cube, your leader in enterprise and emerging tech coverage. We'll see you soon.

okay we're back digging into trusted infrastructure with paris are good at he's a senior consultant for product marketing and storage at dell technologies pastor welcome to the cube good to see you great to be with you dave yeah coming from hyderabad awesome so i really appreciate you uh coming on the program let's start with talking about your point of view on what cyber security resilience means to to dell generally but storage specifically yeah so for something like storage you know we are talking about the data layer name and if you look at cyber security it's all about securing your data applications and infrastructure it has been a very mature field at the network and application layers and there are a lot of great technologies right from you know enabling zero trust uh advanced authentications uh identity management systems and so on and and in fact you know with the advent of you know the the use of artificial intelligence and machine learning really these detection tools for cyber securities have really evolved in the network and application spaces so for storage what it means is how can you bring them to the data layer right how can you bring you know the principles of zero trust to the data layer uh how can you leverage artificial intelligence and machine learning to look at you know access patterns and make intelligent decisions about maybe an indicator of a compromise and identify them ahead of time just like you know how it's happening and other of of applications and when it comes to cyber resilience it's it's basically a strategy which assumes that a threat is imminent and it's a good assumption with the severity and the frequency of the attacks that are happening and the question is how do we fortify the infrastructure in this rich infrastructure to withstand those attacks and have a plan a response plan where we can recover the data and make sure the business continuity is not affected so that's uh really cyber security and cyber resiliency at storage layer and of course there are technologies like you know network isolation um immutability and all these principles need to be applied at the storage level as well let me have a follow up on that if i may the intelligence that you talked about that ai and machine learning is that do you do you build that into the infrastructure or is that sort of a separate software module that that points at various you know infrastructure components how does that work both dave right at the data storage level we have come up with various data characteristics depending on the nature of data we developed a lot of signals to see what could be a good indicator of a compromise um and there are also additional applications like cloud iq is the best example which is like an infrastructure wide health monitoring system for dell infrastructure and now we have elevated that to include cyber security as well so these signals are being gathered at cloud iq level and other applications as well so that we can make those decisions about compromise and we can either cascade that intelligence and alert stream upstream for uh security teams um so that they can take actions in platforms like sign systems xtr systems and so on but when it comes to which layer the intelligence is it has to be at every layer where it makes sense where we have the information to make a decision and being closest to the data we have we are basically monitoring you know the various parallels data access who is accessing um are they crossing across any geo fencing is there any mass deletion that is happening or a mass encryption that is happening and we are able to uh detect uh those uh patterns and flag them as indicators of compromise and in allowing automated response manual control and so on for i.t teams yeah thank you for that explanation so at dell technologies world we were there in may it was one of the first you know live shows that that we did in the spring certainly one of the largest and i interviewed shannon champion and my huge takeaway from the storage side was the degree to which you guys uh emphasized security uh within the operating systems i mean really i mean power max more than half i think of the features were security related but also the rest of the portfolio so can you talk about the the security aspects of the dell storage portfolio specifically yeah yeah so when it comes to data security and broadly data availability right in the context of cyber resiliency um dell storage uh this you know these elements have been at the core of our um a core strength for the portfolio and a source of differentiation for the storage portfolio you know with almost decades of collective experience of building highly resilient architectures for mission critical data something like power max system which is the most secure storage platform for high-end enterprises um and now with the increased focus on cyber security we are extending those core technologies of high availability and adding modern detection systems modern data isolation techniques to offer a comprehensive solution to the customer so that they don't have to piece together multiple things to ensure data security or data resiliency but a well-designed and well-architected solution by design is uh delivered to them to ensure cyber protection at the data layer got it um you know we were talking earlier to steve kenniston and pete gear about this notion of dell trusted infrastructure how does storage fit into that as a component of that sort of overall you know theme yeah and you know and let me say this if you could adjust because a lot of people might be skeptical that i can actually have security and at the same time not constrict my organizational agility that's old you know not an or it's an and how do you actually do that if you could address both of those that would be great definitely so for dell trusted infrastructure cyber resiliency is a key component of that and just as i mentioned you know uh air gap isolation it really started with you know power protect cyber recovery you know that was the solution more than three years ago we launched and that was first in the industry which paved way to you know kind of data isolation being a core element of data management and you know for data infrastructure and since then we have implemented these technologies within different storage platforms as well so the customers have the flexibility depending on their data landscape they can approach they can do the right data isolation architecture right either natively from the storage platform or consolidate things into the backup platform and isolate from there and and the other key thing we focus in trusted infrastructure delta dell trusted infrastructure is you know the goal of simplifying security for the customers so one good example here is uh you know risk being able to respond to these cyber threats or indicators of compromise is one thing but an i.t security team may not be looking at the dashboard of the storage systems constantly right storage administration admins may be looking at it so how can we build this intelligence and provide this upstream platforms so that they have a single pane of glass to understand security landscape across applications across networks firewalls as well as storage infrastructure and and compute infrastructure so that's one of the key ways where how we are helping simplify the um kind of the ability to uh respond ability to detect and respond these threads uh in real time for security teams and you mentioned you know about zero trust and how it's a balance of you know not uh kind of restricting users or put heavy burden on you know multi-factor authentication and so on and this really starts with you know what we are doing is provide all the tools you know when it comes to advanced authentication uh supporting external identity management systems multi-factor authentication encryption all these things are intrinsically built into these platforms now the question is the customers are actually one of the key steps is to identify uh what are the most critical parts of their business or what are the applications uh that the most critical business operations depend on and similarly identify uh mission critical data where part of your response plan where it cannot be compromised where you need to have a way to recover once you do this identification then the level of security can be really determined uh by uh by the security teams by the infrastructure teams and you know another you know intelligence that gives a lot of flexibility for for even developers to do this is today we have apis um that so you can not only track these alerts at the data infrastructure level but you can use our apis to take concrete actions like blocking a certain user or increasing the level of authentication based on the threat level that has been perceived at the application layer or at the network layer so there is a lot of flexibility that is built into this by design so that depending on the criticality of the data criticality of the application number of users affected these decisions have to be made from time to time and it's as you mentioned it's it's a balance right and sometimes you know if if an organization had a recent attack you know the level of awareness is very high uh against cyber attacks so for a time you know these these settings may be a bit difficult to deal with but then it's a decision that has to be made by security teams as well got it so you're surfacing what may be hidden kpis that are being buried inside for instance the storage system through apis upstream into a dashboard so that somebody you know dig into the storage tunnel extract that data and then somehow you know populate that dashboard you're saying you're automating that that that workflow that's a great example and you may have others but is that the correct understanding absolutely and it's a two-way integration let's say a detector an attack has been detected at a completely different layer right in the application layer or at a firewall we can respond to those as well so it's a two-way integration we can cascade things up as well as uh respond to threats that have been detected elsewhere uh through the api that's great all right api for power skill is the best example for that uh excellent so thank you appreciate that give us the last word put a bow on this and and bring this segment home please absolutely so a dell uh storage portfolio um using advanced data isolation um with air gap having machine learning based algorithms to detect uh indicators of compromise and having ripple mechanisms um with granular snapshots being able to recover data and restore applications to maintain business continuity is what we deliver to customers uh and these are areas where a lot of innovation is happening a lot of product focus as well as you know if you look at the professional services all the way from engineering to professional services the way we build these systems the very we configure and architect these systems cyber security and protection is a key focus uh for all these activities and dell.com securities is where you can learn a lot about these initiatives that's great thank you you know at the recent uh reinforce uh event in in boston we heard a lot uh from aws about you know detent and response and devops and machine learning and some really cool stuff we heard a little bit about ransomware but i'm glad you brought up air gaps because we heard virtually nothing in the keynotes about air gaps that's an example of where you know this the cso has to pick up from where the cloud leaves off but as i was in front and so number one and number two we didn't hear a ton about how the cloud is making the life of the cso simpler and that's really my takeaway is is in part anyway your job and companies like dell so paris i really appreciate the insights thank you for coming on thecube thank you very much dave it's always great to be in these uh conversations all right keep it right there we'll be right back with rob emsley to talk about data protection strategies and what's in the dell portfolio you're watching the cube [Music] you

the cyber security landscape has changed dramatically over the past 24 to 36 months rapid cloud migration has created a new layer of security defense sure but that doesn't mean csos can relax in many respects it further complicates or at least changes the ciso's scope of responsibilities in particular the threat surface has expanded and that creates more seams and cisos have to make sure their teams pick up where the hyperscaler clouds leave off application developers have become a critical execution point for cyber assurance shift left is the kind of new buzz phrase for devs but organizations still have to shield right meaning the operational teams must continue to partner with secops to make sure infrastructure is resilient so it's no wonder that in etr's latest survey of nearly 1500 cios and it buyers that business technology executives cite security as their number one priority well ahead of other critical technology initiatives including collaboration software cloud computing and analytics rounding out the top four but budgets are under pressure and csos have to prioritize it's not like they have an open checkbook they have to contend with other key initiatives like those just mentioned to secure the funding and what about zero trust can you go out and buy xero trust or is it a framework a mindset in a series of best practices applied to create a security consciousness throughout the organization can you implement zero trust in other words if a machine or human is not explicitly allowed access then access is denied can you implement that policy without constricting organizational agility the question is what's the most practical way to apply that premise and what role does infrastructure play as the enforcer how does automation play in the equation the fact is that today's approach to cyber resilient type resilience can't be an either or it has to be an and conversation meaning you have to ensure data protection while at the same time advancing the mission of the organization with as little friction as possible and don't even talk to me about the edge that's really going to keep you up at night hello and welcome to the special cube presentation a blueprint for trusted infrastructure made possible by dell technologies in this program we explore the critical role that trusted infrastructure plays in cyber security strategies how organizations should think about the infrastructure side of the cyber security equation and how dell specifically approaches securing infrastructure for your business we'll dig into what it means to transform and evolve toward a modern security infrastructure that's both trusted and agile first up are pete gear and steve kenniston they're both senior cyber security consultants at dell technologies and they're going to talk about the company's philosophy and approach to trusted infrastructure and then we're going to speak to paris arcadi who's a senior consultant for storage at dell technologies to understand where and how storage plays in this trusted infrastructure world and then finally rob emsley who heads product marketing for data protection and cyber security he's going to take a deeper dive with rob into data protection and explain how it has become a critical component of a comprehensive cyber security strategy okay let's get started pete gear steve kenniston welcome to the cube thanks for coming into the marlboro studios today great to be here dave thanks dave good to see you great to see you guys pete start by talking about the security landscape you heard my little rap up front what are you seeing i thought you wrapped it up really well and you touched on all the key points right technology is ubiquitous today it's everywhere it's no longer confined to a monolithic data center it lives at the edge it lives in front of us it lives in our pockets and smartphones along with that is data and as you said organizations are managing sometimes 10 to 20 times the amount of data that they were just five years ago and along with that cyber crime has become a very profitable enterprise in fact it's been more than 10 years since uh the nsa chief actually called cyber crime the biggest transfer of wealth in history that was 10 years ago and we've seen nothing but accelerating cyber crime and really sophistication of how those attacks are perpetrated and so the new security landscape is really more of an evolution we're finally seeing security catch up with all of the technology adoption all the build out the work from home and work from anywhere that we've seen over the last couple of years we're finally seeing organizations and really it goes beyond the i t directors it's a board level discussion today security's become a board level discussion yeah i think that's true as well it's like it used to be the security was okay the secops team you're responsible for security now you've got the developers are involved the business lines are involved it's part of onboarding for most companies you know steve this concept of zero trust it was kind of a buzzword before the pandemic and i feel like i've often said it's now become a mandate but it's it's it's still fuzzy to a lot of people how do you guys think about zero trust what does it mean to you how does it fit yeah i thought again i thought your opening was fantastic in in this whole lead into to what is zero trust it had been a buzzword for a long time and now ever since the federal government came out with their implementation or or desire to drive zero trust a lot more people are taking a lot more seriously because i don't think they've seen the government do this but ultimately let's see ultimately it's just like you said right if if you don't have trust to those particular devices uh applications or data you can't get at it the question is and and you phrase it perfectly can you implement that as well as allow the business to be as agile as it needs to be in order to be competitive because we're seeing with your whole notion around devops and the ability to kind of build make deploy build make deploy right they still need that functionality but it also needs to be trusted it needs to be secure and things can't get away from you yeah so it's interesting we attended every uh reinforce since 2019 and the narrative there is hey everything in this in the cloud is great you know and this narrative around oh security is a big problem is you know doesn't help the industry the fact is that the big hyperscalers they're not strapped for talent but csos are they don't have the the capabilities to really apply all these best practices they're they're playing whack-a-mole so they look to companies like yours to take their r your r d and bake it into security products and solutions so what are the critical aspects of the so-called dell trusted infrastructure that we should be thinking about yeah well dell trusted infrastructure for us is a way for us to describe uh the the work that we do through design development and even delivery of our it system so dell trusted infrastructure includes our storage it includes our servers our networking our data protection our hyper converged everything that infrastructure always has been it's just that today customers consume that infrastructure at the edge as a service in a multi-cloud environment i mean i view the cloud as really a way for organizations to become more agile and to become more flexible and also to control costs i don't think organizations move to the cloud or move to a multi-cloud environment to enhance security so i don't see cloud computing as a panacea for security i see it as another attack surface and another uh aspect in front that organizations and and security organizations and departments have to manage it's part of their infrastructure today whether it's in their data center in a cloud or at the edge i mean i think it's a huge point because a lot of people think oh data's in the cloud i'm good it's like steve we've talked about oh why do i have to back up my data it's in the cloud well you might have to recover it someday so i don't know if you have anything to add to that or any additional thoughts on it no i mean i think i think like what pete was saying when it comes to when it comes to all these new vectors for attack surfaces you know people did choose the cloud in order to be more agile more flexible and all that did was open up to the csos who need to pay attention to now okay where can i possibly be attacked i need to be thinking about is that secure and part of the part of that is dell now also understands and thinks about as we're building solutions is it is it a trusted development life cycle so we have our own trusted development life cycle how many times in the past did you used to hear about vendors saying you got to patch your software because of this we think about what changes to our software and what implementations and what enhancements we deliver can actually cause from a security perspective and make sure we don't give up or or have security become a whole just in order to implement a feature we got to think about those things yeah and as pete alluded to our secure supply chain so all the way through knowing what you're going to get when you actually receive it is going to be secure and not be tampered with becomes vitally important and pete and i were talking earlier when you have tens of thousands of devices that need to be delivered whether it be storage or laptops or pcs or or whatever it is you want to be you want to know that that that those devices are can be trusted okay guys maybe pete you could talk about the how dell thinks about it's its framework and its philosophy of cyber security and then specifically what dell's advantages are relative to the competition yeah definitely dave thank you so we've talked a lot about dell as a technology provider but one thing dell also is is a partner in this larger ecosystem we realize that security whether it's a zero trust paradigm or any other kind of security environment is an ecosystem uh with a lot of different vendors so we look at three areas one is protecting data in systems we know that it starts with and ends with data that helps organizations combat threats across their entire infrastructure and what it means is dell's embedding security features consistently across our portfolios of storage servers networking the second is enhancing cyber resiliency over the last decade a lot of the funding and spending has been in protecting or trying to prevent cyber threats not necessarily in responding to and recovering from threats right we call that resiliency organizations need to build resiliency across their organization so not only can they withstand a threat but they can respond recover and continue with their operations and the third is overcoming security complexity security is hard it's more difficult because of the things we've talked about about distributed data distributed technology and and attack surfaces everywhere and so we're enabling organizations to scale confidently to continue their business but know that all all the i.t decisions that they're making um have these intrinsic security features and are built and delivered in a consistent security so those are kind of the three pillars maybe we could end on what you guys see as the key differentiators that people should know about that that dell brings to the table maybe each of you could take take a shot at that yeah i think first of all from from a holistic portfolio perspective right the uh secure supply chain and the secure development life cycle permeate through everything dell does when building things so we build things with security in mind all the way from as pete mentioned from from creation to delivery we want to make sure you have that that secure device or or asset that permeates everything from servers networking storage data protection through hyper converge through everything that to me is really a key asset because that means you can you understand when you receive something it's a trusted piece of your infrastructure i think the other core component to think about and pete mentioned as dell being a partner for making sure you can deliver these things is that even though those are that's part of our framework these pillars are our framework of how we want to deliver security it's also important to understand that we are partners and that you don't need to rip and replace but as you start to put in new components you can be you can be assured that the components that you're replacing as you're evolving as you're growing as you're moving to the cloud as you're moving to a more on-prem type services or whatever that your environment is secure i think those are two key things got it okay pete bring us home yeah i think one of one of the big advantages of dell is our scope and our scale right we're a large technology vendor that's been around for decades and we develop and sell almost every piece of technology we also know that organizations are might make different decisions and so we have a large services organization with a lot of experienced services people that can help customers along their security journey depending on whatever type of infrastructure or solutions that they're looking at the other thing we do is make it very easy to consume our technology whether that's traditional on-premise in a multi-cloud environment uh or as a service and so the best of breed technology can be consumed in any variety of fashion and know that you're getting that consistent secure infrastructure that dell provides well and dell's forgot the probably top supply chain not only in the tech business but probably any business and so you can actually take take your dog food and then and allow other billionaire champagne sorry allow other people to you know share share best practices with your with your customers all right guys thanks so much for coming thank you appreciate it okay keep it right there after this short break we'll be back to drill into the storage domain you're watching a blueprint for trusted infrastructure on the cube the leader in enterprise and emerging tech coverage be right back concern over cyber attacks is now the norm for organizations of all sizes the impact of these attacks can be operationally crippling expensive and have long-term ramifications organizations have accepted the reality of not if but when from boardrooms to i.t departments and are now moving to increase their cyber security preparedness they know that security transformation is foundational to digital transformation and while no one can do it alone dell technologies can help you fortify with modern security modern security is built on three pillars protect your data and systems by modernizing your security approach with intrinsic features and hardware and processes from a provider with a holistic presence across the entire it ecosystem enhance your cyber resiliency by understanding your current level of resiliency for defending your data and preparing for business continuity and availability in the face of attacks overcome security complexity by simplifying and automating your security operations to enable scale insights and extend resources through service partnerships from advanced capabilities that intelligently scale a holistic presence throughout it and decades as a leading global technology provider we'll stop at nothing to help keep you secure okay we're back digging into trusted infrastructure with paris sarcadi he's a senior consultant for product marketing and storage at dell technologies parasaur welcome to the cube good to see you great to be with you dave yeah coming from hyderabad awesome so i really appreciate you uh coming on the program let's start with talking about your point of view on what cyber security resilience means to to dell generally but storage specifically yeah so for something like storage you know we are talking about the data layer name and if you look at cyber security it's all about securing your data applications and infrastructure it has been a very mature field at the network and application layers and there are a lot of great technologies right from you know enabling zero trust advanced authentications uh identity management systems and so on and and in fact you know with the advent of you know the the use of artificial intelligence and machine learning really these detection tools for cyber securities have really evolved in the network and the application spaces so for storage what it means is how can you bring them to the data layer right how can you bring you know the principles of zero trust to the data layer uh how can you leverage artificial intelligence and machine learning to look at you know access patterns and make intelligent decisions about maybe an indicator of a compromise and identify them ahead of time just like you know how it's happening and other ways of applications and when it comes to cyber resilience it's it's basically a strategy which assumes that a threat is imminent and it's a good assumption with the severity of the frequency of the attacks that are happening and the question is how do we fortify the infrastructure in the switch infrastructure to withstand those attacks and have a plan a response plan where we can recover the data and make sure the business continuity is not affected so that's uh really cyber security and cyber resiliency and storage layer and of course there are technologies like you know network isolation immutability and all these principles need to be applied at the storage level as well let me have a follow up on that if i may the intelligence that you talked about that ai and machine learning is that do you do you build that into the infrastructure or is that sort of a separate software module that that points at various you know infrastructure components how does that work both dave right at the data storage level um we have come with various data characteristics depending on the nature of data we developed a lot of signals to see what could be a good indicator of a compromise um and there are also additional applications like cloud iq is the best example which is like an infrastructure wide health monitoring system for dell infrastructure and now we have elevated that to include cyber security as well so these signals are being gathered at cloud iq level and other applications as well so that we can make those decisions about compromise and we can either cascade that intelligence and alert stream upstream for uh security teams um so that they can take actions in platforms like sign systems xtr systems and so on but when it comes to which layer the intelligence is it has to be at every layer where it makes sense where we have the information to make a decision and being closest to the data we have we are basically monitoring you know the various parallels data access who is accessing um are they crossing across any geo fencing uh is there any mass deletion that is happening or a mass encryption that is happening and we are able to uh detect uh those uh patterns and flag them as indicators of compromise and in allowing automated response manual control and so on for it teams yeah thank you for that explanation so at dell technologies world we were there in may it was one of the first you know live shows that that we did in the spring certainly one of the largest and i interviewed shannon champion and a huge takeaway from the storage side was the degree to which you guys emphasized security uh within the operating systems i mean really i mean powermax more than half i think of the features were security related but also the rest of the portfolio so can you talk about the the security aspects of the dell storage portfolio specifically yeah yeah so when it comes to data security and broadly data availability right in the context of cyber resiliency dell storage this you know these elements have been at the core of our um a core strength for the portfolio and the source of differentiation for the storage portfolio you know with almost decades of collective experience of building highly resilient architectures for mission critical data something like power max system which is the most secure storage platform for high-end enterprises and now with the increased focus on cyber security we are extending those core technologies of high availability and adding modern detection systems modern data isolation techniques to offer a comprehensive solution to the customer so that they don't have to piece together multiple things to ensure data security or data resiliency but a well-designed and well-architected solution by design is delivered to them to ensure cyber protection at the data layer got it um you know we were talking earlier to steve kenniston and pete gear about this notion of dell trusted infrastructure how does storage fit into that as a component of that sort of overall you know theme yeah and you know and let me say this if you could adjust because a lot of people might be skeptical that i can actually have security and at the same time not constrict my organizational agility that's old you know not an ore it's an end how do you actually do that if you could address both of those that would be great definitely so for dell trusted infrastructure cyber resiliency is a key component of that and just as i mentioned you know uh air gap isolation it really started with you know power protect cyber recovery you know that was the solution more than three years ago we launched and that was first in the industry which paved way to you know kind of data isolation being a core element of data management and uh for data infrastructure and since then we have implemented these technologies within different storage platforms as well so that customers have the flexibility depending on their data landscape they can approach they can do the right data isolation architecture right either natively from the storage platform or consolidate things into the backup platform and isolate from there and and the other key thing we focus in trusted infrastructure dell infra dell trusted infrastructure is you know the goal of simplifying security for the customers so one good example here is uh you know being able to respond to these cyber threats or indicators of compromise is one thing but an i.t security team may not be looking at the dashboard of the storage systems constantly right storage administration admins may be looking at it so how can we build this intelligence and provide this upstream platforms so that they have a single pane of glass to understand security landscape across applications across networks firewalls as well as storage infrastructure and in compute infrastructure so that's one of the key ways where how we are helping simplify the um kind of the ability to uh respond ability to detect and respond these threads uh in real time for security teams and you mentioned you know about zero trust and how it's a balance of you know not uh kind of restricting users or put heavy burden on you know multi-factor authentication and so on and this really starts with you know what we're doing is provide all the tools you know when it comes to advanced authentication uh supporting external identity management systems multi-factor authentication encryption all these things are intrinsically built into these platforms now the question is the customers are actually one of the key steps is to identify uh what are the most critical parts of their business or what are the applications uh that the most critical business operations depend on and similarly identify uh mission critical data where part of your response plan where it cannot be compromised where you need to have a way to recover once you do this identification then the level of security can be really determined uh by uh by the security teams by the infrastructure teams and you know another you know intelligence that gives a lot of flexibility uh for for even developers to do this is today we have apis um that so you can not only track these alerts at the data infrastructure level but you can use our apis to take concrete actions like blocking a certain user or increasing the level of authentication based on the threat level that has been perceived at the application layer or at the network layer so there is a lot of flexibility that is built into this by design so that depending on the criticality of the data criticality of the application number of users affected these decisions have to be made from time to time and it's as you mentioned it's it's a balance right and sometimes you know if if an organization had a recent attack you know the level of awareness is very high against cyber attacks so for a time you know these these settings may be a bit difficult to deal with but then it's a decision that has to be made by security teams as well got it so you're surfacing what may be hidden kpis that are being buried inside for instance the storage system through apis upstream into a dashboard so that somebody could you know dig into the storage tunnel extract that data and then somehow you know populate that dashboard you're saying you're automating that that that workflow that's a great example and you may have others but is that the correct understanding absolutely and it's a two-way integration let's say a detector an attack has been detected at a completely different layer right in the application layer or at a firewall we can respond to those as well so it's a two-way integration we can cascade things up as well as respond to threats that have been detected elsewhere um uh through the api that's great all right hey api for power skill is the best example for that uh excellent so thank you appreciate that give us the last word put a bow on this and and bring this segment home please absolutely so a dell storage portfolio um using advanced data isolation um with air gap having machine learning based algorithms to detect uh indicators of compromise and having rigor mechanisms with granular snapshots being able to recover data and restore applications to maintain business continuity is what we deliver to customers uh and these are areas where a lot of innovation is happening a lot of product focus as well as you know if you look at the professional services all the way from engineering to professional services the way we build these systems the way we we configure and architect these systems um cyber security and protection is a key focus uh for all these activities and dell.com securities is where you can learn a lot about these initiatives that's great thank you you know at the recent uh reinforce uh event in in boston we heard a lot uh from aws about you know detent and response and devops and machine learning and some really cool stuff we heard a little bit about ransomware but i'm glad you brought up air gaps because we heard virtually nothing in the keynotes about air gaps that's an example of where you know this the cso has to pick up from where the cloud leaves off but that was in front and so number one and number two we didn't hear a ton about how the cloud is making the life of the cso simpler and that's really my takeaway is is in part anyway your job and companies like dell so paris i really appreciate the insights thank you for coming on thecube thank you very much dave it's always great to be in these uh conversations all right keep it right there we'll be right back with rob emsley to talk about data protection strategies and what's in the dell portfolio you're watching thecube data is the currency of the global economy it has value to your organization and cyber criminals in the age of ransomware attacks companies need secure and resilient it infrastructure to safeguard their data from aggressive cyber attacks [Music] as part of the dell technologies infrastructure portfolio powerstor and powermax combine storage innovation with advanced security that adheres to stringent government regulations and corporate compliance requirements security starts with multi-factor authentication enabling only authorized admins to access your system using assigned roles tamper-proof audit logs track system usage and changes so it admins can identify suspicious activity and act with snapshot policies you can quickly automate the protection and recovery process for your data powermax secure snapshots cannot be deleted by any user prior to the retention time expiration dell technologies also make sure your data at rest stays safe with power store and powermax data encryption protects your flash drive media from unauthorized access if it's removed from the data center while adhering to stringent fips 140-2 security requirements cloud iq brings together predictive analytics anomaly detection and machine learning with proactive policy-based security assessments monitoring and alerting the result intelligent insights that help you maintain the security health status of your storage environment and if a security breach does occur power protect cyber recovery isolates critical data identifies suspicious activity and accelerates data recovery using the automated data copy feature unchangeable data is duplicated in a secure digital vault then an operational air gap isolates the vault from the production and backup environments [Music] architected with security in mind dell emc power store and powermax provides storage innovation so your data is always available and always secure wherever and whenever you need it [Music] welcome back to a blueprint for trusted infrastructure we're here with rob emsley who's the director of product marketing for data protection and cyber security rob good to see a new role yeah good to be back dave good to see you yeah it's been a while since we chatted last and you know one of the changes in in my world is that i've expanded my responsibilities beyond data protection marketing to also focus on uh cyber security marketing specifically for our infrastructure solutions group so certainly that's you know something that really has driven us to you know to come and have this conversation with you today so data protection obviously has become an increasingly important component of the cyber security space i i don't think necessarily of you know traditional backup and recovery as security it's to me it's an adjacency i know some companies have said oh yeah now we're a security company they're kind of chasing the valuation for sure bubble um dell's interesting because you you have you know data protection in the form of backup and recovery and data management but you also have security you know direct security capability so you're sort of bringing those two worlds together and it sounds like your responsibility is to to connect those those dots is that right absolutely yeah i mean i think that uh the reality is is that security is a a multi-layer discipline um i think the the days of thinking that it's one uh or another um technology that you can use or process that you can use to make your organization secure uh are long gone i mean certainly um you actually correct if you think about the backup and recovery space i mean people have been doing that for years you know certainly backup and recovery is all about the recovery it's all about getting yourself back up and running when bad things happen and one of the realities unfortunately today is that one of the worst things that can happen is cyber attacks you know ransomware malware are all things that are top of mind for all organizations today and that's why you see a lot of technology and a lot of innovation going into the backup and recovery space because if you have a copy a good copy of your data then that is really the the first place you go to recover from a cyber attack and that's why it's so important the reality is is that unfortunately the cyber criminals keep on getting smarter i don't know how it happens but one of the things that is happening is that the days of them just going after your production data are no longer the only challenge that you have they go after your your backup data as well so over the last half a decade dell technologies with its backup and recovery portfolio has introduced the concept of isolated cyber recovery vaults and that is really the you know we've had many conversations about that over the years um and that's really a big tenant of what we do in the data protection portfolio so this idea of of cyber security resilience that definition is evolving what does it mean to you yeah i think the the analyst team over at gartner they wrote a very insightful paper called you will be hacked embrace the breach and the whole basis of this analysis is so much money has been spent on prevention is that what's out of balance is the amount of budget that companies have spent on cyber resilience and cyber resilience is based upon the premise that you will be hacked you have to embrace that fact and be ready and prepared to bring yourself back into business you know and that's really where cyber resiliency is very very different than cyber security and prevention you know and i think that balance of get your security disciplines well-funded get your defenses as good as you can get them but make sure that if the inevitable happens and you find yourself compromised that you have a great recovery plan and certainly a great recovery plan is really the basis of any good solid data protection backup and recovery uh philosophy so if i had to do a swot analysis we don't have to do the wot but let's focus on the s um what would you say are dell's strengths in this you know cyber security space as it relates to data protection um one is we've been doing it a long time you know we talk a lot about dell's data protection being proven and modern you know certainly the experience that we've had over literally three decades of providing enterprise scale data protection solutions to our customers has really allowed us to have a lot of insight into what works and what doesn't as i mentioned to you one of the unique differentiators of our solution is the cyber recovery vaulting solution that we introduced a little over five years ago five six years parapatek cyber recovery is something which has become a unique capability for customers to adopt uh on top of their investment in dell technologies data protection you know the the unique elements of our solution already threefold and it's we call them the three eyes it's isolation it's immutability and it's intelligence and the the isolation part is really so important because you need to reduce the attack surface of your good known copies of data you know you need to put it in a location that the bad actors can't get to it and that really is the the the the essence of a cyber recovery vault interestingly enough you're starting to see the market throw out that word um you know from many other places but really it comes down to having a real discipline that you don't allow the security of your cyber recovery vault to be compromised insofar as allowing it to be controlled from outside of the vault you know allowing it to be controlled by your backup application our cyber recovery vaulting technology is independent of the backup infrastructure it uses it but it controls its own security and that is so so important it's like having a vault that the only way to open it is from the inside you know and think about that if you think about you know volts in banks or volts in your home normally you have a keypad on the outside think of our cyber recovery vault as having its security controlled from inside of the vault so nobody can get in nothing can get in unless it's already in and if it's already in then it's trusted exactly yeah exactly yeah so isolation is the key and then you mentioned immutability is the second piece yeah so immutability is is also something which has been around for a long time people talk about uh backup immunoability or immutable backup copies so immutability is just the the the additional um technology that allows the data that's inside of the vault to be unchangeable you know but again that immutability you know your mileage varies you know when you look across the uh the different offers that are out there in the market especially in the backup industry you make a very valid point earlier that the backup vendors in the market seems to be security washing their marketing messages i mean everybody is leaning into the ever-present danger of cyber security not a bad thing but the reality is is that you have to have the technology to back it up you know quite literally yeah no pun intended and then actually pun intended now what about the intelligence piece of it uh that's that's ai ml where does that fit for sure so the intelligence piece is delivered by um a solution called cybersense and cybersense for us is what really gives you the confidence that what you have in your cyber recovery vault is a good clean copy of data so it's looking at the backup copies that get driven into the cyber vault and it's looking for anomalies so it's not looking for signatures of malware you know that's what your antivirus software does that's what your endpoint protection software does that's on the prevention side of the equation but what we're looking for is we're looking to ensure that the data that you need when all hell breaks loose is good and that when you get a request to restore and recover your business you go right let's go and do it and you don't have any concern that what you have in the vault has been compromised so cyber sense is really a unique analytic solution in the market based upon the fact that it isn't looking at cursory indicators of of um of of of malware infection or or ransomware introduction it's doing full content analytics you know looking at you know has the data um in any way changed has it suddenly become encrypted has it suddenly become different to how it was in the previous scan so that anomaly detection is very very different it's looking for um you know like different characteristics that really are an indicator that something is going on and of course if it sees it you immediately get flagged but the good news is is that you always have in the vault the previous copy of good known data which now becomes your restore point so we're talking to rob emsley about how data protection fits into what dell calls dti dell trusted infrastructure and and i want to come back rob to this notion of and not or because i think a lot of people are skeptical like how can i have great security and not introduce friction into my organization is that an automation play how does dell tackle that problem i mean i think a lot of it is across our infrastructure is is security has to be built in i mean intrinsic security within our servers within our storage devices uh within our elements of our backup infrastructure i mean security multi-factor authentication you know elements that make the overall infrastructure secure you know we have capabilities that you know allow us to identify whether or not configurations have changed you know we'll probably be talking about that a little bit more to you later in the segment but the the essence is is um security is not a bolt-on it has to be part of the overall infrastructure and that's so true um certainly in the data protection space give us the the bottom line on on how you see dell's key differentiators maybe you could talk about dell of course always talks about its portfolio but but why should customers you know lead in to dell in in this whole cyber resilience space um you know staying on the data protection space as i mentioned the the the work we've been doing um to introduce this cyber resiliency solution for data protection is in our opinion as good as it gets you know the you know you've spoken to a number of our of our best customers whether it be bob bender from founders federal or more recently at delton allergies world you spoke to tony bryson from the town of gilbert and these are customers that we've had for many years that have implemented cyber recovery vaults and at the end of the day they can now sleep at night you know that's really the the peace of mind that they have is that the insurance that a data protection from dell cyber recovery vault a parapatex cyber recovery solution gives them you know really allows them to you know just have the assurance that they don't have to pay a ransom if they have a an insider threat issue and you know all the way down to data deletion is they know that what's in the cyber recovery vault is good and ready for them to recover from great well rob congratulations on the new scope of responsibility i like how you know your organization is expanding as the threat surface is expanding as we said data protection becoming an adjacency to security not security in and of itself a key component of a comprehensive security strategy rob emsley thank you for coming back in the cube good to see you again you too dave thanks all right in a moment i'll be back to wrap up a blueprint for trusted infrastructure you're watching the cube every day it seems there's a new headline about the devastating financial impacts or trust that's lost due to ransomware or other sophisticated cyber attacks but with our help dell technologies customers are taking action by becoming more cyber resilient and deterring attacks so they can greet students daily with a smile they're ensuring that a range of essential government services remain available 24 7 to citizens wherever they're needed from swiftly dispatching public safety personnel or sending an inspector to sign off on a homeowner's dream to protecting restoring and sustaining our precious natural resources for future generations with ever-changing cyber attacks targeting organizations in every industry our cyber resiliency solutions are right on the money providing the security and controls you need we help customers protect and isolate critical data from ransomware and other cyber threats delivering the highest data integrity to keep your doors open and ensuring that hospitals and healthcare providers have access to the data they need so patients get life-saving treatment without fail if a cyber incident does occur our intelligence analytics and responsive team are in a class by themselves helping you reliably recover your data and applications so you can quickly get your organization back up and running with dell technologies behind you you can stay ahead of cybercrime safeguarding your business and your customers vital information learn more about how dell technology's cyber resiliency solutions can provide true peace of mind for you the adversary is highly capable motivated and well equipped and is not standing still your job is to partner with technology vendors and increase the cost of the bad guys getting to your data so that their roi is reduced and they go elsewhere the growing issues around cyber security will continue to drive forward thinking in cyber resilience we heard today that it is actually possible to achieve infrastructure security while at the same time minimizing friction to enable organizations to move quickly in their digital transformations a xero trust framework must include vendor r d and innovation that builds security designs it into infrastructure products and services from the start not as a bolt-on but as a fundamental ingredient of the cloud hybrid cloud private cloud to edge operational model the bottom line is if you can't trust your infrastructure your security posture is weakened remember this program is available on demand in its entirety at thecube.net and the individual interviews are also available and you can go to dell security solutions landing page for for more information go to dell.com security solutions that's dell.com security solutions this is dave vellante thecube thanks for watching a blueprint for trusted infrastructure made possible by dell we'll see you next time

[Music] okay we're back digging into trusted infrastructure with paris our godaddy he's a senior consultant for product marketing and storage at dell technologies parasite welcome to the cube good to see you great to be with you dave yeah coming from hyderabad awesome so i really appreciate you uh coming on the program let's start with talking about your point of view on what cyber security resilience means to to dell generally but storage specifically yeah so for something like storage you know we are talking about the data layer name and if you look at cyber security it's all about securing your data applications and infrastructure it has been a very mature field at the network and application layers and there are a lot of great technologies right from you know enabling zero trust uh advanced authentications uh identity management systems and so on and and in fact you know with the advent of you know the the use of artificial intelligence and machine learning really these detection tools for cyber securities have really evolved in the network and the application spaces so for storage what it means is how can you bring them to the data layer right how can you bring you know the principles of zero trust to the data layer how can you leverage artificial intelligence and machine learning to look at you know access patterns and make intelligent decisions about maybe an indicator of a compromise and identify them ahead of time just like you know how it's happening in other words of of applications and when it comes to cyber resilience it's it's basically a strategy which assumes that a threat is imminent and it's a good assumption with the severity and the frequency of the attacks that are happening and the question is how do we fortify the infrastructure in the switch infrastructure to withstand those attacks and have a plan a response plan where we can recover the data and make sure the business continuity is not affected so that's uh really cyber security and cyber resiliency and storage layer and of course there are technologies like you know um in network isolation um immutability and all these principles need to be applied at the storage level as well let me have a follow up on that if i may the intelligence that you talked about that ai and machine learning is that do you do you build that into the infrastructure or is that sort of a separate software module that that points at various you know infrastructure components how does that work both dave um right at the data storage level um we have come with various data characteristics depending on the nature of data we developed a lot of signals to see what could be a good indicator of a compromise um and there are also additional applications like cloud iq is the best example which is like an infrastructure-wide health monitoring system for dell infrastructure and now we have elevated that to include cyber security as well so these signals are being gathered at cloud iq level and other applications as well so that we can make those decisions about compromise and we can either cascade that intelligence and alert stream upstream for uh security teams um so that they can take actions in platforms like sign systems xtr systems and so on but when it comes to which layer the intelligence is it has to be at every layer where it makes sense where we have the information to make a decision and being closest to the data we have we are basically monitoring you know the various parallels data access who is accessing um are they crossing across any geo fencing is there any mass deletion that is happening or mass encryption that is happening and we are able to uh detect uh those uh patterns and flag them as indicators of compromise and in allowing automated response manual control and so on for iot teams yeah thank you for that explanation so at dell technologies world we were there in may it was one of the first you know live shows that that we did in the spring certainly one of the largest and i interviewed shannon champion and my huge takeaway from the storage side was the degree to which you guys uh emphasized security uh within the operating systems i mean really i mean powermax more than half i think of the features were security related but also the rest of the portfolio so can you talk about the the security aspects of the dell storage portfolio specifically yeah yeah so when it comes to data security and broadly data availability right in the context of cyber resiliency um dell storage uh this you know these elements have been at the core of our um a core strength for the portfolio and a source of differentiation for the storage portfolio you know with almost decades of collective experience of building highly resilient architectures for mission critical data something like power max system which is the most secure storage platform for high-end enterprises um and now with the increased focus on cyber security we are extending those core technologies of high availability and adding modern detection systems modern data isolation techniques to offer a comprehensive solution to the customer so that they don't have to piece together multiple things to ensure data security or data resiliency but a well-designed and well-architected solution by design is delivered to them to ensure cyber protection at the data layer got it um you know we were talking earlier to steve kenniston and pete gear about this notion of dell trusted infrastructure how does storage fit into that as a component of that sort of overall you know theme yeah and you know and let me say this if you could address because a lot of people might be skeptical that i can actually have security and at the same time not constrict my organizational agility that's old you know not an ore it's an end how do you actually do that if you could address both of those that would be great definitely so for dell trusted infrastructure cyber resiliency is a key component of that and just as i mentioned you know uh air gap isolation it really started with you know power protect cyber recovery you know that was the solution more than three years ago we launched and that was first in the industry which paved way to you know kind of data isolation being a core element of data management and uh for data infrastructure and since then we have implemented these technologies within different storage platforms as well so that customers have the flexibility depending on their data landscape they can approach they can do the right data isolation architecture right either natively from the storage platform or consolidate things into the backup platform and isolate from there and and the other key thing we focus in trusted infrastructure dell infra dell trusted infrastructure is you know the goal of simplifying security for the customers so one good example here is uh you know being able to respond to these cyber threats or indicators of compromise is one thing but an i.t security team may not be looking at the dashboard of the storage systems constantly right storage administration admins may be looking at it so how can we build this intelligence and provide this upstream platforms so that they have a single pane of glass to understand security landscape across applications across networks firewalls as well as storage infrastructure and and compute infrastructure so that's one of the key ways where how we are helping simplify the um kind of the ability to uh respond ability to detect and respond these threads uh in real time for security teams and you mentioned you know about zero trust and how it's a balance of you know not uh kind of restricting users or put heavy burden on you know multi-factor authentication and so on and this really starts with you know what we are doing is provide all the tools you know when it comes to advanced authentication uh supporting external identity management systems multi-factor authentication encryption all these things are intrinsically built into these platforms now the question is the customers are actually one of the key steps is to identify uh what are the most critical parts of their business or what are the applications uh that the most critical uh business operations depend on and similarly identify uh mission critical data where part of your response plan where it cannot be compromised where you need to have a way to recover once you do this identification then the level of security can be really determined uh by uh by the security teams by the infrastructure teams and you know another you know intelligence that gives a lot of flexibility uh for for even developers to do this is today we have apis um that so you can not only track these alerts at the data infrastructure level but you can use our apis to take concrete actions like blocking a certain user or increasing the level of authentication based on the threat level that has been perceived at the application layer or at the network layer so there is a lot of flexibility that is built into this by design so that depending on the criticality of the data criticality of the application number of users affected these decisions have to be made from time to time and it's as you mentioned it's it's a balance right and sometimes you know if if an organization had a recent attack you know the level of awareness is very high uh against cyber attacks so for a time you know these these settings may be a bit difficult to deal with but then it's a decision that has to be made by security teams as well got it so you're surfacing what may be hidden kpis that are buried inside for instance the storage system through apis upstream into a dashboard so that somebody could you know dig into the storage tunnel extract that data and then somehow you know populate that dashboard you're saying you're automating that that that workflow that's a great example and you may have others but is that the correct understanding absolutely and it's a two-way integration let's say a detector an attack has been detected at a completely different layer right in the application layer or at a firewall we can respond to those as well so it's a two-way integration we can cascade things up as well as uh respond to uh threats that have been detected elsewhere um through the api that's great all right api for power scale is the best example for that uh excellent so thank you appreciate that give us the last word put a bow on this and and bring this segment home please absolutely so a dell storage portfolio um using advanced data isolation with air gap having machine learning based algorithms to detect uh indicators of compromise and having rigor mechanisms with granular snapshots being able to recover data and restore applications to maintain business continuity is what we deliver to customers uh and these are areas where a lot of innovation is happening a lot of product focus as well as you know if you look at the professional services all the way from engineering to professional services the way we build these systems the way we we configure and architect these systems uh cyber security and protection uh is a key focus uh for all these activities and dell.com securities is where you can learn a lot about these initiatives that's great thank you you know at the recent uh reinforce uh event in in boston we heard a lot uh from aws about you know detent and response and devops and machine learning and some really cool stuff we heard a little bit about ransomware but i'm glad you brought up air gaps because we heard virtually nothing in the keynotes about air gaps that's an example of where you know this the cso has to pick up from where the cloud leaves off that was in front and so number one and number two we didn't hear a ton about how the cloud is making the life of the cso simpler and that's really my takeaway is is in part anyway your job and companies like dell so paris i really appreciate the insights thank you for coming on thecube thank you very much dave it's always great to be in these uh conversations all right keep it right there we'll be right back with rob emsley to talk about data protection strategies and what's in the dell portfolio you're watching the cube [Music] you

[Music] welcome to the great super cloud debate a power panel of three top technology industry analysts maribel lopez is here she's the founder and principal analyst at lopez research keith townsend is ceo and founder of the cto advisor and sanjeev mohan is principal at sanjmo super cloud is a term that we've used to describe the future of cloud architectures the idea is that super clouds are built on top of hyperscaler capex infrastructure and the idea is it goes beyond multi-cloud the premise being that multi-cloud is primarily a symptom of multi-vendor or m a or both and results in more stove we're going to talk about that super cloud's meant to connote a new architecture that leverages the underlying primitives of hyperscale clouds but hides and abstracts that complexity of each of their respective clouds and adds new value on top of that with services and a continuous experience a similar or identical experience across more than one cloud people may say hey that's multi-cloud we're going to talk about that as well so with that as brief background um i'd like to first welcome our painless guys thanks so much for coming on thecube it's great to see you all again great to be here thank you to be here so i'm going to start with maribel you know what i just described what's your reaction to that is it just like what like cloud is supposed to be is that really what multi-cloud is do you agree with the premise that multi-cloud has really been you know what like chuck whitten from dell calls it it's been multi-cloud by default i call it a symptom of multi-vendor what's your take on on what this is oh wow dave another term here we go right more more to define for people but okay the reality is i agree that it's time for something new something evolved right whether we call that super cloud or something else i you know i don't want to really debate the term but we need to move beyond where we are today in multi-cloud and into if we want to call it cloud 5 multi-cloud 2 whatever we want to call it i believe that we're at the next generation that we have to define what that next generation is but if you think about it we went from public to private to hybrid to multi and every time you have a discussion with somebody about cloud you spend 10 minutes defining what you're talking about so this doesn't seem any different to me so let's just go with super cloud for the moment and see where we go and you know if you're interested after everybody else makes their comments i got a few thoughts about what super cloud might mean as well yeah great so i and i agree with you when we like i said in a recent post you could call it cl cloud you know multi-cloud 2.0 but it's something different is happening and sanjeev i know you're not a you're not a big fan of buzz words either but i wonder if you could weigh in on this topic uh you mean by the way sanjeev is at the mit cdo iq conference a great conference uh in boston uh and so he's it's a public place so we're going to have i think you viewed his line when he's not speaking please go ahead yeah so you know i come from a pedigree of uh being an analyst of uh firms that love inventing new terms i am not a big fan of inventing new terms i feel that when we come up with a new term i spend all my time standing on a stage trying to define what it is it takes me away from trying to solve the problem so so i'm you know i find these terms to be uh words of convenience like for example big data you know big data to me may not mean anything but big data connotes some of this modern way of handling vast volumes of data that traditional systems could not handle so from that point of view i'm i'm completely okay with super cloud but just inventing a new term is what i have called in my previous sessions tyranny of jargons where we have just too many jargons and uh and they resonate with i.t people they do not resonate with the business people business people care about the problem they don't care about what we and i t called them yeah and i think this is a really important point that you make and by the way we're not trying to create a new industry category per se yeah we leave that to gartner that's why actually i like super cloud because nobody's going to use that no vendor's going to use the term super cloud it's just too buzzy so so but but but it brings up the point about practitioners and so keith i want to bring you in so the what we've talked about and i'll just sort of share some some thoughts on the problems that we see and and get keith get your practitioner view most clouds most companies use multiple clouds we all kind of agree on that i think and largely these clouds operate in silos and they have their own development environment their own operating environment different apis different primitives and the functionality of a particular cloud doesn't necessarily extend to other clouds so the problem is that increases friction for customers increases cost increases security risk and so there's this promise maribel multi-cloud 2.0 that's going to solve that problem so keith my question to you is is is that an accurate description of the problem that practitioners face today do what did i miss and i wonder if you could elaborate so i think we'll get into some of the detail later on why this is a problem specifically around technologies but if we think about it in the abstract most customers have their hands full dealing with one cloud like we'll you know through m a and such and you zoom in and you look at companies that have multiple clouds or multi-cloud from result of mma mna m a activity you'll see that most of that is in silos so organizationally the customer may have multiple clouds but sub orchid silos they're generally a single silo in a single cloud so as you think about being able to take advantage of of tooling across the multicloud of what dave you guys are calling the super cloud this becomes a serious problem it's just a skill problem it's too much capability uh across too many things that look completely different than another okay so dave can i pick up on that please i'd love i was gonna just go to you maribel please chime in here okay so if we think about what we're talking about with super cloud and what keith just mentioned remember when we went to see tcp ip and the whole idea was like how do we get computers to talk to each other in a more standardized way how do we get data to move in a more standardized way i think that the problem we have with multi-cloud right now is that we don't have that so i think that's sort of a ground level of getting us to your super cloud premise is that and and you know google's tried it with anthony's like everybody every hyperscaler has tried their like right one to run anywhere but that abstraction layer you talk about what whatever we want to call it is super necessary and it's sort of the foundation so if you really think about it we've spent like 15 years or so building out all the various components of cloud and now's the time to take it so that cloud is actually more of an operating model versus a place there's at least a base level of it that is vendor neutral and then to your point the value that's going to be built on top of that you know people been trying to commoditize the basic infrastructure for a while now and i think that's what you're seeing in your super cloud multi-cloud whatever you want to call it the infrastructure is the infrastructure and then what would have been traditionally that past layer and above is where we're going to start to see some real innovation but we still haven't gotten to that point where you can do visibility observability manageability across that really complex cloud stack that we have the reason i the reason i love that tcpip example hm is because it changed the industry and it had an ecosystem effect in sanjiv the the the example that i first example that i used was snowflake a company that you're very familiar with that is sort of hiding all that complexity and right and so we're not there yet but please chime in on this topic uh you gotta you gotta view it again uh after you building upon what maribel said you know to me uh this sounds like a multi-cloud operating system where uh you know you need that kind of a common uh set of primitives and layers because if you go in in the typical multi-cloud process you've got multiple identities and you can't have that you how can you govern if i'm if i have multiple identities i don't have observability i don't know what's going on across my different stacks so to me super cloud is that call it single pane of glass or or one way through which i'm unifying my experience my my technology interfaces my integration and uh and i as an end user don't even care which uh which cloud i'm in it makes no difference to me it makes a difference to the vendor the vendor may say this is coming from aws and this is coming from gcp or azure but to the end user it is a consistent experience with consistent id and and observability and governance so that to me makes it a big difference and so one of floyer's contribution conversation was in order to have a super cloud you got to have a super pass i'm like oh boy people are going to love that but the point being that that allows a consistent developer experience and to maribel's earlier point about tcp it explodes the ecosystem because the ecosystem can now write to that super pass if you will those apis so keith do you do do you buy that number one and number two do you see that industries financial services and healthcare are actually going to be on clouds or what we call super clouds so sanjeev hit on a really key aspect of this is identity let's make this real they you love talk about data collaboration i love senji's point on the business user kind of doesn't care if this is aws versus super cloud versus etc i was collaborating with the client and he wanted to send video file and the video file uh his organization's access control policy didn't allow him to upload or share the file from their preferred platform so he had to go out to another cloud provider and create yet another identity for that data on the cloud same data different identity a proper super cloud will enable me to simply say as a end user here's a set of data or data sets and i want to share a collaboration a collaborator and that requires cross identity across multiple clouds so even before we get to the past layer and the apis we have to solve the most basic problem which is data how do we stop data scientists from shipping snowballs to a location because we can't figure out the identity the we're duplicating the same data within the same cloud because we can't share identity across customer accounts or etc we we have to solve these basic thoughts before we get to supercloud otherwise we get to us a turtles all the way down thing so we'll get into snowflake and what snowflake can do but that's what happens when i want to share my snowflake data across multiple clouds to a different platform yeah you have to go inside the snowflake cloud which leads right so i would say to keith's question sanjeev snowflake i think is solving that problem but then he brings up the other problem which is what if i want to share share data outside the snowflake cloud so that gets to the point of visit open is it closed and so sanji chime in on the sort of snowflake example and in maribel i wonder if there are networking examples because that's that's keith's saying you got to fix the plumbing before you get these higher level abstractions but sanji first yeah so i so i actually want to go and talk a little bit about network but from a data and analytics point of view so i never built upon what what keith said so i i want to give an example let's say i am getting fantastic web logs i and i know who uh uh how much time they're spending on my web pages and which pages they're looking at so i have all of that now all of that is going into cloud a now it turns out that i use google analytics or maybe i use adobe's you know analytics uh suite now that is giving me the business view and i'm trying to do customer journey analytics and guess what i now have two separate identities two separate products two separate clouds if i and i as an id person no problem i can solve any problem by writing tons of code but why would i do that if i can have that super pass or a multi-cloud layout where i've got like a single way of looking at my network traffic my customer metrics and i can do my customer journey analytics it solves a huge problem and then i can share that data with my with my partners so they can see data about their products which is a combination of data from different uh clouds great thank you uh maribel please i think we're having a lord of the rings moment here with the run one room to rule them all concept and i'm not sure that anybody's actually incented to do that right so i think there's two levels of the stack i think in the basic we're talking a lot about we don't have the basic fundamentals of how do you move data authenticate data secure data do data lineage all that stuff across different clouds right we haven't even spoken right now i feel like we're really just talking about the public cloud venue and we haven't even pulled in the fact that people are doing hybrid cloud right so hybrid cloud you know then you're talking about you've got hardware vendors and you've got hyperscaler vendors and there's two or three different ways of doing things so i honestly think that something will emerge like if we think about where we are in technology today it's almost like we need back to that operating system that sanji was talking about like we need a next generation operating system like nobody wants to build the cloud mouse driver of the 21st century over and over again right we need something like that as a foundation layer but then on top of it you know there's obviously a lot of opportunity to build differentiation like when i think back on what happened with cloud amazon remained aws remained very powerful and popular because people invested in building things on amazon right they created a platform and it took a while for anybody else to catch up to that or to have that kind of presence and i still feel that way when i talk to companies but having said that i talked to retail the other day and they were like hey we spent a long time building an abstraction layer on top of the clouds so that our developers could basically write once and run anywhere but they were a massive global presence retailer that's not something that everybody can do so i think that we are still missing a gap i don't know if that exactly answers your question but i i do feel like we're kind of in this chicken and egg thing which comes first and nobody wants to necessarily invest in like oh well you know amazon has built a way to do this so we're all just going to do it the amazon way right it seems like that's not going to work either but i think you bring up a really important point which there is going to be no one ring to rule them all you're going to have you know vmware is going to solve its multi-cloud problem snowflake's going to do a very has a very specific you know purpose-built system for it itself databricks is going to do its thing and it's going to be you know more open source i would companies like aviatrix i would say cisco even is going to go out and solve this problem dell showed at uh at dell tech world a thing called uh project alpine which is basically storage across clouds they're going to be many super clouds we're going to get maybe super cloud stove pipes but but the point is however for a specific problem in a set of use cases they will be addressing those and solving incremental value so keith maybe we won't have that single cloud operating you know system but we'll have multiple ones what are your thoughts on that yeah we're definitely going to have multiple ones uh the there is no um there is no community large enough or influential enough to push a design take maribel's example of the mega retailer they've solved it but they're not going to that's that's competitive that's their competitive advantage they're not going to share that with the rest of us and open source that and force that upon the industry via just agreement from everyone else so we're not going to get uh the level of collaboration either originated by the cloud provider originated from user groups that solves this problem big for us we will get silos in which this problem is solved we'll get groups working together inside of maybe uh industry or subgroups within the industry to say that hey we're going to share or federate identity across our three or four or five or a dozen organizations we'll be able to share data we're going to solve that data problem but in the same individual organizations in another part of the super cloud problem are going to again just be silos i can't uh i can't run machine learning against my web assets for the community group that i run because that's not part of the working group that solved a different data science problem so yes we're going to have these uh bifurcations and forks within the super cloud the question is where is the focus for each individual organization where do i point my smart people and what problems they solve okay i want to throw out a premise and get you guys reaction to it because i think this again i go back to the maribel's tcpip example it changed the industry it opened up an ecosystem and to me this is what digital transformation is all about you've got now industry participants marc andreessen says every company is a software company you've now got industry participants and here's some examples it's not i wouldn't call them true super clouds yet but walmart's doing their hybrid thing with azure you got goldman sachs announced at the last reinvent and it's going to take its tools its software its data and which is on-prem and connect that to the aws cloud and actually deliver a service capital one we saw sanjiv at the snowflake summit is is taking their tooling and doing it now granted just within snowflake and aws but i fully expect them to expand that across other clouds these are industry examples capital one software is the name of the division that are now it's to the re reason why i don't get so worried that we're not solving the lord of the rings problem that maribel mentioned is because it opens up tremendous opportunities for companies we got like just under five minutes left i want to throw that out there and see what you guys think yeah i would just i want to build upon what maribel said i love what she said you're not going to build a mouse driver so if multi-cloud supercloud is a multi-cloud os the mouse driver would be identity or maybe it's data quality and to teach point that data quality is not going to come from a single vendor that is going to come from a different vendor whose job is to to harmonize data because there might be data might be for the same identity but it may be a different granularity level so you cannot just mix and match so you need to have some sort of like resolution and that is is an example of a driver for multi-cloud interesting okay so you know octa might be the identity cloud or z scaler might be the security cloud or calibre has its cloud etc any thoughts on that keith or maribel yeah so let's talk about where the practical challenges run into this we did some really great research that was sponsored by one of the large cloud providers in which we took all we looked at all the vmware cloud solutions when i say vmware cloud vmware has a lot of products across multi-cloud now in the rock broadcloud portfolio but we're talking about the og solution vmware vsphere it would seem like on paper if i put vmware vsphere in each cloud that is therefore a super cloud i think we would all agree to that in principle what we found in our research was that when we put hands on keyboard the differences of the clouds show themselves in the training gap and that skills gap between the clouds show themselves if i needed to expose less our favorite friend a friend a tc pip address to the public internet that is a different process on each one of the clouds that needs to be done on each one of the clouds and not abstracted in vmware vsphere so as we look at the nuance yes we can give the big controls but where the capital ones the uh jp morgan chase just spent two billion dollars on this type of capability where the spin effort is done is taking it from that 80 percent to that 90 95 experience and that's where the effort and money is spent on that last mile maribel we're out of time but please you know bring us home give us your closing thoughts hey i think we're still going to be working on what the multi-cloud thing is for a while and you know super cloud i think is a direction of the future of cloud computing but we got some real problems to solve around authentication uh identity data lineage data security so i think those are going to be sort of the tactical things that we're working on for the next couple years right guys always a pleasure having you on the cube i hope we see you around keith i understand you're you're bringing your airstream to vmworld or vmware explorer putting it on the on the floor i can't wait to see that and uh mrs cto advisor i'm sure we'll be uh by your side so looking forward to that hopefully sanjeev and maribel we'll see you uh on the circuit as well yes hope to see you there right looking forward to hopefully even doing some content with you guys at vmware explorer too awesome looking forward all right keep it right there for more content from super cloud 22 right back [Music] you

>>The cube presents, Dell technologies world brought to you by Dell. >>Welcome back to the cube. Lisa Martin and Dave Vale are live in Las Vegas. We are covering our third day of covering Dell technologies world 2022. The first live in-person event since 2019. It's been great to be here. We've had a lot of great conversations about all the announcements that Dell has made in the last couple of days. And we're gonna unpack a little bit more of that. Now. One of our alumni is back with us. Shannon champion joins us again, vice president product marketing at Dell technologies, and she's a company by Pete Robinson, the director of infrastructure engineering at Salesforce. Welcome. Thank >>You. >>So Shannon, you had a big announcement yesterday. I run a lot of new software innovations. Did >>You hear about that? I heard a little something >>About that. Unpack that for us. >>Yeah. Awesome. Yeah, it's so exciting to be here in person and have such a big moment across our storage portfolio, to see that on the big stage, the boom to announce major updates across power store, PowerMax and power flex all together, just a ton of innovation across the storage portfolio. And you probably also heard a ton of focus on our software driven innovation across those products, because our goal is really to deliver a continuously modern storage experience. That's what our customers are asking us for that cloud experience. Let's take the most Val get the most value from data no matter where it lives. That's on premises in the public clouds or at the edge. And that's what we, uh, unveil. That's what we're releasing. And that's what we're excited to talk about. >>Now, Pete, you, Salesforce is a long time Dell customer, but you're also its largest PowerMax customer. The biggest in the world. Tell us a little bit about what you guys are doing with PowerMax and your experience. >>Yeah, so, um, for Salesforce, trust is our number one value and that carries over into the infrastructure that we develop, we test and, and we roll out and Parex has been a key part of that. Um, we really like the, um, the technology in terms of availability, reliability, um, performance. And it, it has allowed us to, you know, continue to grow our customers, uh, continue needs for more and more data. >>So what was kind of eye popping to me was the emphasis on security. Not that you've not always emphasized security, but maybe Shannon, you could do a rundown of, yeah. Maybe not all the features, but give us the high level. And at Pete, I, I wonder how I, if you could comment on how, how you think about that as a practitioner, but please give us that. >>Sure. Yeah. So, you know, PowerMax has been leading for, uh, a long time in its space and we're continuing to lean into that and continue to lead in that space. And we're proud to say PowerMax is the world's most secure mission, critical storage platform. And the reason we can say that is because it really is designed for comprehensive cyber resiliency. It's designed with a zero trust security architecture. And in this particular release, there's 19 different security features really embedded in there. So I'm not gonna unpack all 19, but a couple, um, examples, right? So multifactor authentication also continuous ransomware anomaly detection, a leveraging cloud IQ, which is, uh, huge. Um, and last but not least, um, we have the industry's most granular cyber recovery at scale PowerMax can do up to 65 million imutable snapshots per array. So just, uh, and that's 30 times more than our next nearest competitor. So, you know, really when you're talking about recovery point objectives, power max can't be beat. >>So what does that mean to you, Pete? >>Uh, well, it's it's same thing that I was mentioning earlier about that's a trust factor. Uh, security is a big, a big part of that. You know, Salesforce invests heavily into the securing our customer data because it really is the, the core foundation of our success and our customers trust us with their data. And if we, if we were to fail at that, you know, we would lose that trust. And that's simply not, it's not an option. >>Let's talk about that trust for a minute. We know we've heard a lot about trust this week from Michael Dell. Talk to us about trust, your trust, Salesforce's trust and Dell technologies. You've been using them a long time, but cultural alignment yeah. Seems to be pretty spot on. >>I, I would agree. Um, you know, both companies have a customer first mentality, uh, you know, we, we succeed if the customer succeeds and we see that going back and forth in that partnership. So Dell is successful when Salesforce is successful and vice versa. So, um, when we've it's and it goes beyond just the initial, you know, the initial purchase of, of hardware or software, you know, how you operate it, how you manage it, um, how you continue to develop together. You know, our, you know, we work closely with the Dell engineering teams and we've, we've worked closely in development of the new, new PowerMax lines to where it's actually able to help us build our, our business. And, and again, you know, continue to help Dell in the process. So you've >>Got visibility on the new, a lot of these new features you're playing around with them. What I, I, I obviously started with security cuz that's on top of everybody's mind, but what are the things are important to you as a customer? And how do these features the new features kind of map into that? Maybe you could talk about your experience with the, I think you're in beta, maybe with these features. Maybe you could talk about that. >>Yeah. Um, probably the, the biggest thing that we're seeing right now, other than OB the obvious enhancements in hardware, which, which we love, uh, you know, better performance, better scalability, better, and a better density. Um, but also the, some of the software functionality that Dells starting to roll out, you know, we've, we've, we've uh, implemented cloud IQ for all of our PowerMax systems and it's the same thing. We continue to, um, find features that we would like. And we've actually, you know, worked closely with the cloud IQ team. And within a matter of weeks or months, those features are popping up in cloud IQ that we can then continue to, to develop and, and use. >>Yeah. I think trust goes both ways in our partnership, right? So, you know, Salesforce can trust Dell to deliver the, you know, the products they need to deliver their business outcomes, but we also have a relationship to where we can trust that Salesforce is gonna really help us develop the next generation product that's gonna, you know, really deliver the most value. Yeah. >>Can you share some business outcomes that you've achieved so far leveraging power max and how it's really enabled, maybe it's your organization's productivity perspective, but what are some of those outcomes that you've achieved so far? >>Um, there there's so many to, to, to choose from, but I would say the, probably the biggest thing that we've seen is a as we roll out new infrastructure, we have various generations that we deploy. Um, when we went to the new PowerMax, um, initially we were concerned about whether our storage infrastructure could keep up with the new compute, uh, systems that we were rolling out. And when we went through and began testing it, we came to realize that the, the performance improvements alone, that we were seeing were able to keep up with the compute demand, making that transition from the older VMAX platforms to the PMAX practically seamless and able to just deploy the new SKUs as, as they came out. >>Talk about the portfolio that you apply to PowerMax. I mean, it's the highest of the highest end mission critical the toughest workloads in the planet. Salesforce has made a lot of acquisitions. Yeah. Um, do you throw everything at PowerMax? Are you, are you selective? What's your strategy there? So >>It's, it's selective. In other words that there's no square peg that meets every need, um, you know, acquisitions take some time to, to ingest, um, you know, some run into cloud, some run in first, in, in first party. Um, but so we, we try to take a very, very intentional approach to where we deploy that technology. >>So 10 years ago, someone in your position, or maybe someone who works for you was probably do spent a lot of time managing lawns and tuning performance. And how has that changed? >>We don't do that. <laugh> we? >>We can, right. So what do you do with right. Talk, talk more double click on that. So how talk about how that transition occurred from really non-productive activities, managing storage boxes. Yeah. And, and where you are today, what are you doing with those resources? >>It, it, it all comes outta automation. Like, you know, the, you know, hardware is hardware to a point, um, but you reach a point where the, the manageability scale just goes exponential and, and we're way, well past that. And the only way we've been able to meet that, meet that need is to, to automate and really develop our operations, to be able to not just manage at a lung level or even at the system level, but manage at the data center level at the geographical, you know, location level and then being able to, to manage from there. >>Okay. Really stupid question. But I'm gonna ask it cause I wanna hear your answer. True. Why can't you just take a software defined storage platform and just run everything on that? Why do you need all these different platforms and why do you gotta spend all this money on PowerMax? Why, why can't you just do >>That? That's the million dollar question. Uh, I, I ask that all the time. <laugh>, um, I think software defined is it's on its way. Um, it's come a long way just in the last decade. Yeah. Um, but in terms of supporting what I consider mission critical, large scale, uh, applications, it's, it's not, it's just simply not on par just yet with what we do with PowerMax, for example. >>And that's exactly how we position it in our portfolio. Right? So PowerMax runs on 95% of the fortune 100 companies, top 20 healthcare companies, top 10 financial services companies in the world. So it's really mission critical high end has all of the enterprise level features and capabilities to really have that availability. That's so important to a lot of companies like Salesforce and, and Pete's right, you know, software define is on its way and it provides a lot of agility there. But at the end of the day for mission critical storage, it's all about PowerMax. >>I wonder if we're ever gonna get to, I mean, you, you, you, it was interesting answer cuz you kind of, I inferred from your that you're hopeful and even optimistic that someday will get to parody. But I wonder because you can't be just close enough. It's almost, you have to be. >>I think, I think the key answer to that is it's it's the software flying gets you halfway there. The other side of the coin is the application ecosystem has to change to be able to solve that other, other side of it. Cuz if you simply simply take an application that runs on a PowerMax and try to run it, just forklift it over to a software defined. You're not gonna have very much luck. >>Recovery has to be moved up to stack >>Operations recovery, the whole, whole whole works. >>Jenny, can you comment on how customers like Salesforce? Like what's your process for involving them in testing in roadmap and in that direction, strategic direction that you guys are going? Great >>Question. Sure. Yeah. So, you know, customer feedback is huge. You've heard it. I'm sure this is not new right product development and engineering. We love to hear from our customers. And there's multiple ways you heard about beta testing, which we're really fortunate that Salesforce can help us provide that feedback for our new releases. But we have user groups, we have forums. We, we hear directly from our sales teams, our, you know, our customers, aren't shy, they're willing to give us their feedback. And at the end of the day, we take that feedback and make sure that we're prioritizing the right things in our product management and engineering teams so that we're delivering the things that matter. Most first, >>We've heard a lot of that this week. So I would agree guys, thank you so much for joining Dave and me talking about Salesforce. What you doing with PowerMax? All the stuff that you announced yesterday, alone. Hopefully you get to go home and get a little bit of rest. >>Yes. >>I'm sure that there's, there's never a dull moment. Never. Can't wait guys. Great to have you. >>Thank you. You guys, >>For our guests on Dave Volante, I'm Lisa Martin and you're watching the queue. We are live day three of our coverage of Dell technologies world 2022, Dave and I will be right back with our final guest of the show.

>>Good morning, welcome to the cubes coverage of Qube con and cloud native con 21 live from Los Angeles. Lisa Martin, here with Dave Nicholson. David's great to be in person with other humans at this conference. Finally, I can't believe >>You're arms length away. It's unreal. >>I know, and they checked backs cards. So everybody's here is nice and safe. We're excited to welcome kingdom Barrett to the program, flux, maintainer and open source support engineer at we works. He came to him. Welcome to the program. >>Oh, thank you for having me on today. >>So let's talk about flux. This is a CNCF incubating project. I saw catalyze as adopt talk to us about flux and its evolution. >>Uh, so flex is, uh, uh, just got into its second version a while ago. We've been, uh, working on, um, uh, we're an incubating project and we're going towards graduation at this point. Um, flex has seen a great deal of adoption from, uh, infant cloud infrastructure vendors in particular, uh, like Microsoft and Amazon and VMware, all building products on, um, flux, uh, the latest version of flux. And, uh, we've heard, uh, from companies like Alibaba and state farm. We had a, uh, uh, conference, uh, at a co-hosted event earlier on Tuesday called get-ups con, uh, where we presented all about get ops, which is the technology, uh, guiding, uh, set of principles that underlies flux. And, uh, there are new adopters, um, all, all every day, including, uh, the department of defense, uh, who has a hundred thousand developers. Um, it's, it's, it's very successful project at this point, who are the >>Key users of flux flux? >>Excuse me. The key users of flux are, uh, probably, uh, application developers and infrastructure engineers, and platform support folks. So a pretty broad spectrum of people. >>And you've got some news at the event. >>Yeah, we actually, uh, we have a, uh, ecosystem event that's coming up, um, on October 20th, uh, it's free virtual event. Uh, folks can join us to hear from these companies. We have people from high level, uh, CTOs and GMs, uh, from companies like Microsoft, Amazon VMware, uh, we've worked D two IQ, um, that are, uh, going to be speaking, uh, about their, uh, products that you can buy from their cloud vendor, uh, that, uh, are based on flux. Uh, so, so that's a milestone for us. That's a major milestone. These are large vendors, um, major cloud vendors that have decided that they trust, uh, flux with their customers workloads. And it's, it's the way that they want to push get ups. Great >>Validation. Yeah. >>So give us an example, just digging in a little bit on flux and get ops. What are some of the things that flux either enforces or enables or validates? What, how would you describe the flux get ops relationship? >>So the first to get ops principles is declarative infrastructure and that's, uh, that's something that people who are using Kubernetes are already very familiar with. Um, flux has a basic itself, or, or I guess spawned, uh, maybe is a better way to say it. Uh, this, um, uh, whole get ops working group, that's just defined the principles. There's four of them in the formal definition. That's just been promoted to a 1.0 and, uh, the get ups working group, publish, publish this at, uh, open get-ups dot dev where you can read all four. And, um, it's great copy site. If you're not really familiar with get ops, you can, you can read all four, but, uh, the other, uh, the second one I would have mentioned is, uh, version storage is, is, uh, it's called get ups and get as a version store. So it's a good for, um, disaster recovery. >>Uh, and, uh, if you have an issue with a new release, if you're, uh, pushing changes frequently, that's, you know, more than likely you will have issues from time to time. Uh, you can roll back with, get ups because everything is version. Um, and, uh, you can do those releases rapidly because the deployment is automatic, um, and it's continuously reconciling. So those are the four principles of get ups. Uh, and they're, they're not exactly prescriptive. You don't have to adopt them all at once. You can pick and choose where you want to get started. Um, but that's what, uh, is underneath flux. >>How do you help customers pick and choose based on what are some of the key criteria that you would advise them on? >>We would advise them to try to follow all of those principles, because that's what you get out of the box with fluxes is a solution that does those things. But if there is one of those things that gets in a way, um, there's also the concept of a closed loop that is, um, sometimes debated as whether it should be part of the get ops principles or not. Um, that just means that, uh, when you use get-ups the only changes that go to your infrastructure are coming through get-ups. Uh, so you don't have someone coming in and using the back door. Um, it all goes through get, uh, w when you want to make a change to your cluster or your application, you push it to get the automation takes over from there and, um, and makes, uh, developers and platform engineers jobs a lot easier. And it makes it easier for them to collaborate with each other, >>Of course, productivity. You mentioned AWS, Microsoft, VMware, uh, all working with you to deliver, get ups to enterprise customers. Talk to me about some of the benefits in it for these big guys. I mean, that's great validation, but what's in it for AWS and VMware and Microsoft, for example, business outcome wise. >>Well, uh, one of the things that we've been promoting and since June is a flex has been, uh, uh, there's an API underneath, that's called the get ops toolkit. This is, uh, if you're building a platform for platforms like these cloud vendors are, um, we announced that fluxes APRs are officially stable. So that means that it's safe for them to build on top of, and they can, uh, go ahead and build things and not worry that we're going to pull the rug out from under them. So that's one of the major vendors, uh, one of the major, uh, uh, vendor benefits and, um, uh, we've, we've also added a recent improvement, uh, uh, called service side apply that, uh, will improve performance. Uh, we reduced the number of, um, API calls, but also for, for, uh, users, it makes things a lot easier because they don't have to write explicitly health checks on everything. Uh, it's possible for them to say, we'd like to see everything is healthy, and it's a one-line addition, that's it? >>So, you know, there's been a lot of discussion from a lot of different angles of the subject of security, uh, in this space. Um, how does this, how does this dovetail with that? A lot of discussion specifically about software supply chain security. Now this is more in the operations space. How do, how do those come together? Do you have any thoughts on security? >>Well, flux is built for security first. Um, there are a lot of products out there that, uh, will shell out to other tools and, and that's a potential vulnerability and flux does not do that. Uh, we've recently undergone a security audit, which we're waiting for the results and the report over, but this is part of our progress towards the CNCF graduated status. Um, and, uh, we've, we've liked what we've seen and preliminary results. Uh, we've, we've prepared for the security audit on knowing that it was coming and, uh, uh, flexes, uh, uh, designed for security first. Uh, you're able to verify that the commits that you're applying to your cluster are signed and actually come from a valid author who is, uh, permitted to make changes to the cluster and, uh, get ops itself is, is this, uh, model of operations by poll requests. So, um, you, you have an opportunity to make sure that your changes are, uh, appropriately reviewed before they get applied. >>Got it. So you had a session at coupon this week. Talk to me a little bit about that. What were like the top three takeaways, and maybe even share with us some of the feedback that you got from the audience? >>Um, so, uh, the session was about Jenkins and get ups or Jenkins and flux. And the, um, the main idea is that when you use flux, flux is a tool for delivery. So you've heard maybe of CIC, D C I N C D are separate influx. We consider these as two separate jobs that should not cross over. And, uh, when, when, uh, you do that. So the talk is about Jenkins and flux. Jenkins is a very popular CII solution and the messages, uh, you don't have to abandon, if you've made a large infrastructure investment in a CII solution, you don't have to abandon your Jenkins or your GitHub actions or, or whatever other CII solution you're using to build and test images. Uh, you can take it with you and adopt get ups. >>Um, so there's compatibility there and, and usability familiarity for the audience, the users. Yeah. What was some of the feedback that they provided to you? Um, were they surprised by that? Happy about that? >>Well, and talk to us a little bit fast paced. Uh, we'll put it in the advanced CIC D track. I covered a lot of ground in that talk, and I hope to go back and cover things in a little bit smaller steps. Um, I tried to show as many of the features of Fluxus as I could. Uh, and, and so one of the feedback that I got was actually, it was a little bit difficult to follow up as, so I'm a new presenter. Um, this is my first year we've worked. I've never presented at CubeCon before. Um, I'm really glad I got the opportunity to be here. This is a great, uh, opportunity to collaborate with other open source teams. And, um, that's, that's, uh, that's the takeaway from me? No. >>So you've got to give a shout out to, uh, to weave works. Absolutely. You know, any, any organization that realizes the benefit of having its folks participating in the community, realizing that it, it helps the community, it helps you, it helps them, you know, that's, that's what we love about, about all of this. >>Yeah. We're, uh, we're really excited to grow adoption for, um, Kubernetes and get ops together. So, >>So I've asked a few people this over the last couple of days, where do you think we are in the peak Kubernetes curve? Are we still just at the very beginning stages of this, of this as a, as a movement? >>Um, certainly we're, um, it's, it's, uh, for, for people who are here at CubeCon, I think we see that, you know, uh, a lot of companies are very successful with Kubernetes, but, um, I come from a university, it, uh, background and I haven't seen a lot of adoption, uh, in, in large enterprise, um, more conservative enterprises, at least in, in my personal experience. And I think that, uh, there is a lot for those places to gain, um, through, through, uh, adopting Kubernetes and get ups together. I think get ops is, uh, we'll provide them with the opportunity to, uh, experience Kubernetes in the best way possible. >>We've seen such acceleration in the last 18, 19 months of digital transformation for companies to survive, to pivot during COVID to survive, doubt to thrive. Do you see that influencing the adoption of Kubernetes and maybe different industries getting more comfortable with leveraging it as a platform? >>Sure. Um, a lot of companies see it as a cost center. And so if you can make it easier or possible to do, uh, operations with fewer people in the loop, um, that, that makes it a cost benefit for a lot of people, but also you need to keep people in the loop. You need to keep the people that you have included and, and be transparent about what infrastructure choices and changes you're making. So, uh, that's one of the things that get ups really helps with >>At transparency is key. One more question for you. Can you share a little bit before we wrap here about the project roadmap and some of the things that are coming down the pike? Yeah. >>So I mentioned a graduation. That's the immediate goal that we're working towards? Uh, most directly, uh, we have, um, grown our, uh, number of integrations pretty significantly. We have an operator how entry in red hat, open shift there's operator hub, where you can go and click to install flux. And that's great. Um, and, uh, we looked forward to, uh, making flux more compatible with more of the tools that you find in the CNCF umbrella. Um, that's, that's what our roadmap is for >>Increasing that compatibility. And one more time mentioned the event, October 20th, I believe he said, let folks know where they can go and find it on the web. Yeah. >>If you're interested in the get ups days.com, it's the get-ups one-stop shop and it's, uh, vendors like AWS and Microsoft and VMware detour IQ. And we've worked, we've all built a flux based solutions, um, for, uh, that are available for sale right now. So if you're, uh, trying to use get-ups and you have one of these vendors as your cloud vendor, um, it seems like a natural fit to try the solution that's out of the box. Uh, but if you need convincing, you get Upstate's dot com, you can go find out more about the event and, uh, we'll hope to see you there. >>I get upstairs.com kingdom. Thank you. You're joining Dave and me on the program, talking to us about flux. Congratulations on its evolution. We look forward to hearing more great things as the years unfold. >>Thank you so much for having me on our pleasure >>For Dave Nicholson. I'm Lisa Martin. You're watching the kid live from Los Angeles at CubeCon cloud native con 21 stick around Dave and I, and we'll be right back with our next guest.

>> Welcome everybody to this cube conversation. My name is Dave Vellante and we're joined today by Richard Goodwin, who's the group director of IT at Ultraleap and Avishek Kumar, who manages Dell's Power Store, product line, he directs that product line along with several other lines for the company. Gentlemen, welcome to the cube. >> (Avishek) Hi Dave. >> (Richard) Hi >> (Dave) So Richard, Ultraleap, very cool company tracks hand movements, and so forth. Tell us about the company and the technology I'm really interested in how it's used. >> Yeah, we've had many product lines, obviously. We're very innovative, and the organization was spun up from a PhD, a number of PhD students who were the co-founders for Ultraleap, and initially with mid-air haptics, as you, as many people may have seen, but also hand tracking, mid-air touch, sense and feel. So, yeah, it's, it's, it's quite impressive what we have produced and the number of sectors and markets that we were in. And obviously to, to push us to where we are, we have relied upon lots of the Dao technology, both software and hardware. >> (Dave) And what's your role at the company? >> I'm the group IT director, I'm responsible for the IT and business platforms, all infrastructure, network, hardware, software, and also the transition of those platforms to ensure that we're scalable. And we are able to develop our software and hardware as rapidly as possible. >> (Dave) Awesome. Yeah, a lot of data behind that too I bet. Okay Avishek, you direct a number of products at Dell across the portfolio, Unity, Extreme IO, the SC series, and of course power vault. It's quite the portfolio that you look after. So let's get into the case study, if we can, a bit, Richard, maybe you could paint a picture of, of your environment, some of the key applications that you're supporting and maybe what your infrastructure looks like. Give us a high level view. >> Sure. So, pre Power Store, we had quite a disparate architecture, so a fairly significant split and siding on the side of the cloud, not as hybrid as we would like, and not, not as much as on-prem, as we would have liked, and hey, but that's changed quite significantly. So we now have a number of servers and storage and storage arrays that we have on, on-premise, and then we host ourselves. So we are moving quite rapidly, you know as a startup and then moving to a scale-up, we needed that, that scalability and that versatility, and also the whole OPEX versus CAPEX, and also not being driven by lots of SaaS products and architecture and infrastructure, where we needed to be in control because of our development cycles and our products, product development. >> (Dave) So wait, Okay, So, so, too much cloud. I'm hearing you wanted a little bit a dose of on-prem, explain that a little bit more, the cloud wasn't doing it for you in terms of your development cycle, your control. Can you double click on that? >> Yeah. Some of the, some of the control and you know, there's always a balance because there's certain elements of our development cycles and our engineering, software engineering, where we need a very high parallelism for some of the work that we're doing, which then, you know, the CAPEX investment makes things very, very challenging, not commercially the right thing to do. However, there are some of our information, some of IP, some of the secure things that we do, we also do not want upgrades as an example, or any advantages or certain types of server and spec that we need to be quite and unique and that needs to be within our control. >> (Dave) Got it, Okay. Thank you for that. Avishek, we're going to talk about Power Store today. So set it up, please, tell us about Power Store, what it is, you know, why it's important to this conversation. >> Sure. So Power Store is a product that we launched may of 2020, roughly a little bit more than a year now. And it's a brand new architecture that Dell technologies released. And at the end of the day, I'll talk about a few unique aspects of the product, but at the end of the day, where we start with, it's a storage platform, right? So where we see similar to what Richard is saying here, in terms of being able to consolidate the customer's environment, whether it is blog, file, WeVaults, physical, virtual environments, and, and it's, as I said, it's a brand new architecture where we leveraged pieces of existing products, where it made sense, we are using all the latest and greatest technologies delivering the best performance based data reduction. And where we see a lot of traction is the options that it brings to the table for our customers in terms of flexibility, whether they want to add capacity, compute, whether in fact, we have apps on the deployment model where customers can consolidate their compute as well on the static storage platform with needed. So a lot of innovation from a platform perspective itself, and it's not just about the platform itself, but what comes along with it, right? So we refer to it as an ecosystem, part of it, where we work with Ansible playbooks, CSI plugin, you name it, right. And it's the storage platform by itself, doesn't stand by itself in a customer's environment, there are other aspects of the infrastructure that it needs to integrate with as well. Right? So if they are using Ansible playbooks, we want to make sure the integration is there. >> (Dave) Got it. >> And last, but perhaps not the least is the intelligence built into the platform, right? So as we are building these capabilities into the product, there is intelligence built into the product, as well as outside the product where things like Cloud IQ, things like technologies built into power suit itself makes it that much easier for the customers to manage the infrastructure and go from there. >> (Dave) Thank you for that, So, Richard, what was the workload? So it actually, you started with the sort of a Greenfield on-prem. If I understand it correctly, what was the workload that you were sort of building around or workloads? >> So, we had a, a number of different applications. Some of which we cannot really talk about too much, but we had, we had a VxRail, we had a a smaller doubt array and we have lots of what we class as runners, Kubernetes cluster that we run and quite a few different VMs that run on our, on-prem server infrastructure and storage arrays and the issues that we began to hit because of the high IO, from some of our workloads, that we were hitting very high latency, which rapidly stopped, began to cause us issues, especially with some of our software engineering teams. And that is when we embarked upon a competitive RFP for Dell Power Store, Dell were already engaged from an end-user compute where they'd been selected as the end-user compute provider from a previous competitive RFP. And then we engaged them regarding the storage issue that we had and we engaged the, our account lead and count exec, and a number of solution architects were working with us to ensure that we have the optimal solution. Dell were selected over the competitors because of many reasons, you know, the new technology, the de-duplication, the compression, the data, overall data reduction, and the guarantee that also came, came with that, the four-to-one data reduction guarantee, which was significant to us because of their amounts of data that we hold. And we have, you know, as I've mentioned, we're pulling further, further data of ours back into our hosted environments, which will end up on the Power Store, especially with the de-duplication that we're now getting. We've actually hit nine-to-one, which is significant. We were expecting four-to-one, maybe five-to-one with some of the data types. And what was excellent that we were that confident that they did not even review our data types prior, and they were willing to stand by that guarantee of four-to-one. And we've excelled that, we've got significant different data types on, on that array, and we've hit nine-to-one and that's gradually grown over the last nine months, you know, we were kind of at the six then we moved to seven and now we're hitting nine-to-one ratio. >> (Dave) That's great. So you get a little free storage. That's interesting what you're saying, Richard, cause I just assumed that a company that guaranteed four-to-one is going to say okay, let us, let us inspect your workload first and then we'll do the deal. So Avishek, what's the tech behind that data reduction that you're able to, with such confidence, not have to pre inspect the workload in this case anyway. >> Yeah. So, it goes back to the technologies that goes behind the product, right? So, so we, we stand behind the technology and we want to make it simpler for our customers as well where, again we don't want to spend weeks looking at all the data, scanning all the data before giving the guarantee. So we stand behind the technology where we understand that as the data is coming in, we are always going to be de-duplicate it. We are always going to compress it. There is technology within the product where we are offloading some of that to the outside the CPU, so it is not impacting the performance that the applications are going to see. So a data reduction by itself is not good enough, performance by itself is not good enough. Both of them have to be together, right? So, and that's what Power Store brings to the table. >> (Dave) Thank you. So Richard, I'm interested. I mean, I remember the Power Store announcement of, sort of, saw it leading up to it. And one of the big thrusts from Dell was the way I phrase it is essentially trying to create a cloud like experience on-prem. So really focused on simplicity. So my question to you is, let's start with just the deployment. You know, how complicated was it to install? What was that process like? How many clicks, I mean, not that you have to tell me how many clicks, but you know, what I'm asking is, is how difficult was it to get from zero to, you know, up and running? >> Well, we actually stepped our very difficult challenge. We were in quite a difficult situation where we'd pretty much gone off the cliff in terms of our IOPS performance. So the RFP was quite rapid, and then we needed to get whoever which vendor was successful, we needed to get that deployed rather rapidly and on the floor in our data center and server rooms, which we did. And it was very very simplistic, within three weeks of placing the order, we had that array in our server rack and we'd begun the migration, it was very simple to set up. And the management of that array has been, we've seen say 40% reduction in terms of effort to be able to manage our storage because it is very self-contained, you know, even from a reporting perspective, the deployment, the migration was all very, very, very simplistic, and you know, we we've done some work recently where we had to also do some work on the array and some other migrations that we were doing and the resilience came, came to, came to the forefront of where the Juul architecture and no single point of failure enabled us to do some things that we needed to do quite rapidly because of the, the Juul norms and the resilience within, within the unit and within the Power Store itself was considerable where we, we kept performance up, it also prioritize any discreet rebuilds, keeps the incoming ingest rates high, and prioritizes the, you know, the workloads, which is really impressive, especially when we are moving so quickly with our technology. We don't really have much time to, you know, micromanage the estate. >> (Dave) Can you, can you just repeat what you said on the percent reduction? I think I heard you cut out there a little bit, a percent reduction on, on, on management, on, on, on the labor side. >> So our lead storage engineer is estimated around 40% less management. >> (Dave) Wow. Okay. So that's, that's good. So actually, I love this conversation because, you know, in the early days of automation, people like, ah, that's my job, provisioning LUNs. I'm really good at it, but I think people are realizing that it's actually not something that you want to be really good at. It's something that you want to eliminate. So, it now maybe it's that storage engineer got his or her nights and weekends back, but, but what do they do now when they get that extra time, what do you, what do you put them on? You know, no more strategic initiatives or, you know, other, other tech things on the to-do list. What's that like?. >> The last thing that, you know, any of my team, whether it's the storage leads or some of the infrastructure team that were also involved in engaged, cause you know, the organization, we have to be quite versatile as a team in our skillsets. We don't want to be doing those BAU mundane tasks. Even the storage engineer does not want to be allocating LUNs and allocating storage to physical servers, Vms, etc. We want all of that to be automated. And, you know, those engineers, they're working on some of the cutting edge things that we're trying to do with machine learning as an example, which is much more interesting. It's what they want to be doing. You know, that aides, the obvious things like retention, interest and personal development, we don't want to be, you know, that base IT infrastructure management, is not where any of the engineers wants to be. >> (Dave) In terms of the decision to go with Dell Power Store. I'm definitely hearing there was a relationship. There was an existing relationship with Dell. I'm sure that played into it. >> There were many things. So the relationship wasn't really part of this, even though I've mentioned the end-user compute in any sets or anything that we're procuring, we want best of breed, you know, best of sets. And that was done on, the cost is definitely a driver. The technology, you know, is a big trust to us, We're a tech company, new technology to us is also fascinating, not only our own, but also the storage guarantee, the simplicity, the resilience within, within the unit. Also the ability, which was key to us because of what we're trying to do with our hybrid model and bring, bring back repatriate some of the data as it were from the client. We needed that ability to, with ease, to be able to scale up and scale high, and the Power Store gave us that. >> (Dave) When you say cost, I want to dig into that price or you know, the price tag or the, the cost, I mean, when you do the business case. And I wonder if we could add a little color to that. >> (Richard) There's two elements to this, so they're not only the cost of the price tag, but then also cost of ownership and the comparisons that we were running against the other vendors, but also the comparisons that we were running from a CAPEX investment against OPEX and what we have in the cloud, and also the performance, performance that we get from the cloud and our cloud storage and the resilience within that. And then also the initial price tag, and then comparing the CapEx investments to the OPEX where all elements that were key to us making our decision. And I know that there has to be some credit taken by the Dell account team and that their relationship towards the final phrase of that RFP, you know, were key initially, not all, we were just looking for the best possible storage solution for Ultraleap. >> (Dave) And to determine that on your end, was that like a feature, because it's sometimes fuzzy what the business impact is going to be like that 40% you mentioned, or the data reduction at nine to one, when there's a promise of four to one, did you, what did you do? Did you kind of do a feature function analysis and sort of line that up and, and say, okay, I'm going to map that to our business processes our IT processes and try to predict what the impact would be. Is that how you did it? or did you take a different approach? >> (Richard) We did. So we did that, obviously between vendors usually expected an RFP, but then also mapping to how that would impact the business. And that is not an easy process to go through. And we've seen more gains even comparing one vendor to another, some of that because of the technology, the terminology is very very different and sometimes you have to bring that upper level and also gain a much more detailed understanding, which at times can be challenging, but we did a very like-for-like comparison and, and also lots of research, but you're quite right. The business analysis to what we needed. We had quite a good forecast and from summarized stock information data, and also our engineering and business and strategic roadmap, we were able to map those two together, not the easiest of experiences, not one that I want to repeat, but we, we got it. (Dave laughing) >> (Dave)Yeah, a little bit of art and science involved. Avishek, maybe you could talk about Power Store, what, you know, give us the commercial. What makes it different from other products in the market of things like cloud IQ? Maybe you could talk about that a little bit. >> Sure. So, so again, from a, it's music to my ears, when Richard talks about the ease of deployment and the management, because there is a lot of focus on that. But even as I said earlier, from a man technology perspective, a lot of goodness built-in, in terms of being able to consolidate a customer's environment, onto the platform. So that's more from a storage point of view that give the best performance, give the best data reduction, storage efficiencies. The second part, of course, the flexibility, the options that Power Store gives to the customers in terms of sort of desegregating the storage and the compute aspects of it. So if, as a customer, I want to start with different points in terms of what our customer requirements are today, but going forward as the requirements change from a compute capacity perspective, you can use a scale up and scale out capabilities, and then the intelligence built in, right? So, as you scale out your cluster, being able to move storage around right, as needed being able to do that non-disruptively. So instead of saying that Mr. Customer, your, your storage is going to you're at 90% capacity, being able to say that based on your historical trending, we expect you run out of capacity in six months, some small things like that, right? And of course, if the, the dial home, the support assist capabilities that enabled, cloud IQ brings a lot of intelligence to the table as well. In addition to that, as they mentioned earlier, there is apps on capability that gives another level of flexibility to the customers to integrate your storage infrastructure into a virtual environment, if the customer chooses to do that. And last but not the least, it's not just about the product, right? So it's about the programs that we have put around it, anytime upgrade is a big differentiator for us, where it's an investment protection program for customers, where if they want to have the peace of mind, in terms of three months, nine months, three years down the line, if we come out with new technologies, being able to be upgrade to that non-disruptively is a big part of it as well. It's a peace of mind for the customers that, yes I'm getting into the Power Store architecture today, but going forward, I'm protected from that point of view. So anytime upgrade, it's a new business program that we put around leveraging the architectural benefits of Power Store, whether your compute requirement, your storage requirements change, you're covered from that point of view. So again, a very quick overview of, of what Power Store is, why it is different. And again, that's where that comes from. >> (Dave) Thank you for that. Richard, are you actively using cloud IQ? Do you get the, what kind of value do you get from it? >> Not currently. However, we have, we have had plans to do that. The uptake and BCR, our internal Workload is not allowed us, to do that. But one of the other key reasons for selecting Power Store was the non-disruptive element, you know, with other SaaS products, other providers, and other issues that we have experienced. That was one, that was a key decision for us from a Power Store perspective. One of the other, you know, to go back to the conversation slightly, in terms of performance, we are getting, getting there. You know, there's a 400% speed of improvement of publishing. We've got an 80% faster code coverage. Our firmware builds a 1300% quicker than they were previously. and the time savings of the storage engineer and, you know, as a director of IT, I often asked for certain reports from, from the storage array, we're working at, for storage forecast, performance forecast, you know, when we're coming close to product releases, code drops that we're trying to manage, the reporting or the Power Store is impressive. Whereas previously my storage engineer would not be the, the most happiest of people when I would be trying to pull, you know, monthly and quarterly reports, et cetera. Whereas now it's, it's ease and we have live dashboards running and we can easily extract that information. >> (Dave) I love that because, you know, so often we talk about the 40% reduction in IT labor, which okay, that's cool. But then your CFO's going to say, yeah, but it's not like we're getting rid of people. We, you know, we're still spending that money and you're like, okay. You're now into soft dollars, but when you talk about 400%, 80%, 1300% of what you're talking about business impact and that's telephone numbers to a CFO. So I love those metrics. Thank you for sharing. >> Yeah. But what would, they obviously, it's sort of like dashboards when they visualize that they are very hard hitting, you know, the impact. You're quite right the CFO does chase down you know, the availability and the resource profile, however, we're on a huge upward trajectory. So having the right resilience and infrastructure in places is exactly what we need. And as I mentioned before, those engineers are all reallocated to much more interesting work and, you know, the areas that will actually drive our business forward. >> (Dave) Speaking of resilience, are you doing any replication? >> Not currently. However, we've actually got a meeting regarding this today with some of the enterprise and some of their storage specialists, in a couple of hours time, actually, because that is a very high on the agenda for us to be able to replicate and have a high availability cluster and another potentially Power Store need. >> (Dave) Okay. So I was going to ask you where you want to take this thing. I'm hearing, you're looking at cloud IQ, really try to exploit that. So you got some headroom here in terms of the value that you can get out of this platform to do replication, faster recovery, et cetera, maybe protect against, you know, events. Guys, Thanks so much for your time. Really appreciate your insights. >> (Richard) No problem. >> (Avishek) Thank you. >> And thank you for watching this cube conversation. This is Dave Vellante and we'll see you next time.

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 Special coverage sponsored by AWS Worldwide Public Sector >>Hi and welcome to the Q Virtual and our coverage of AWS reinvent 2020 with special coverage of the public sector. I'm your host, Rebecca >>Knight. >>Today we have two guests for our segment. We have Kevin McCallum Jr. He is the chief technology officer at Maximus. Thanks for joining us, Kevin, and we have way. And we have Steve Zimmerman, who is the vice president of consulting services at Insight. Thank you so much for coming on the show. Steve. >>Thank you for having us appreciate it. >>So I want to start by asking. You both have to tell us a little bit more about your company's. Kevin. Let's start with you. Tell us a little bit more about Maximus. >>Yes, Thanks for having me. Maximus is a 40 year old company. We partner with state, federal and local governments to provide communities with critical health and human service programs. We leverage extensive experience to develop high quality services and solutions that are cost effective and tailored to their unique needs. One of the things that we do is offer government's ability to programs rapidly and scalable so that we can focus on the automation and their operations. We do services from Medicare to Medicaid, Welford work, and we have comprehensive solutions. Help the government's run effectively and efficiently. >>Great, Steve, tell us a little bit about insight. >>Yeah, sure. Um, Insight is a Fortune 500 company, you know, in 2020 will roughly do you know, probably a plus billion dollars in revenue. Global company. You know, we have thousands of treaty GIC relationships, but I'd say we have probably a couple 100 partners. We focus on one of those key partners to us is a W s. Right. As we go to market, Azzawi start, you know, working with our customers around transformation, of which we're gonna talk a little bit about that today with Kevin as it relates, Thio incite public sector. It's >>a pretty sizable >>part of our business. You know, we'll do about $1.5 billion in revenue. We have 200 plus contract vehicles, will work out there over 500 plus teammates, and we're seeing that business grow quarter over quarter, 20% growth. So It's a big investment for us and really looking forward to hearing Kevin talk about Maximus, uh, to the team, because obviously it's a big lever for us for inside public sector to get the word out there about the great transformation work. What you do with our customers. >>That's a great segue. So let's go back to you, Kevin, and talk a little bit about Maximus. Cloud transformation. Why did you hire insight for help you with this? >>Yeah, A Z We started our journey. One of the things we realized is as we were moving to the cloud is the experience. We needed a trusted partner and we ran an RFP process looking for partners out there that have done it that have done major data center programs. You're moving large companies, you know, We're moving about 6000 workloads 160 plus applications. So it was not a light or easy project and insight fit that. Aziz, We went through the interview process. It became very clear that they have done this for Fortune 500 companies in the past and their experience is beneficial to helping us drive to the future and the other factors is we wanted to make sure that once we were done with the project, we had the experience internally that they helped us with Thio drive forward. >>So talking about the importance of a trusted partner, which is such a key component of digital transformation cloud journeys tell us a little bit about the the strategy tied to the data center transformation and why you chose AWS. >>Sure. So, as we started doing our research, we did analysis across all of the cloud providers who were out there. AWS is clear leader in the marketplace. Their technology is better aligned with what Maximus has as the underlying technologies were, ah, majority of Lennox Base. We also have windows. We have Oracle, which, with the AWS depth on breath of our offerings, tied better to what we had. The other thing we were looking to do is get rid of our monolithic off the shelf products and use mawr of the cloud based products that are out there. Amazon has a very deep, uh, native technology that allows you to replace your old services where you had to bolt on or purchase another product to something that is integrated and streamlined, you know, down Thio, how do you monitor your systems? How do you do logs things like that. And, you know, as we looked at the time frame, we had to deliver this. They had to be able to grow with us. So as we were building out, new infrastructure were able to build where previously internally. With data centers, you have to buy infrastructure. You wait for it to arrive, you install it. Amazon has it at the click of a ah button. So we're able Thio basically have environment stood up in a day rather than having to wait weeks for it. So and the last thing was up time. So you know Amazon. They're five nines plus in up time and most of our contracts or three nines or better requirements. We had to find a bender that had multiple availability zones and regions that allowed us to be flexible in how we deployed. >>So talking about the convenience and the ability to streamline, and also the need for flexibility in the covert era. Of course, the word hybrid work environments has taken on a new meaning. But I want to ask you about how you see the hybrid era in the long term affecting Maximus. >>Yeah. Since Maximus is a government contractor, we will always be in a hybrid, uh, set up. So some of our contracts are very restrictive, especially when you get into our S d. O. D. And some of those agencies you have a fed ramp requirement is right. Well, with some of the federal agencies. So some of those components about to stay internally So where we can force, uh, you know, moving to the cloud because of the flexibility we have to deploy, that is the right will go. Um, co vid has introduced a new complexity. When it started back in March, you know, Maximus had 30,000 or so employees, and we instantly were thrown into You gotta make those employees get those employees to work from home. So we used Amazon's workspace Thio push our employees to work from home, where, you know, some of the employees and some of our contracts are customer owned equipment. So we couldn't actually take that equipment home. So we had to move to a B y o d model on Amazon workspaces in order to get the users to work from home and the complexity that, with what Amazon has to offer, allowed us to quickly move over 25,000 employees on the Amazon workspaces and work from home and then keeping the data center migration moving in the middle of it has also been, ah, challenge. So we will, in our federal space, still have internal data centers. Integration points that Amazon offers with their inter connects is key toe. How we make it a seamless process because we may have a business unit has stuff sitting in the data center and at Amazon, and they have to look at the seamless package. >>Steve, I want to bring you in here a little bit into this conversation. Cloud transformation, digital transformation. These are These are difficult and huge undertaking in the best of times. How does this pandemic this health crisis emergency. How has that affected the way you help your clients the way you work with your clients? Collaborate, communicate, talk a little bit about the effect of Kobe on this on the >>eso I would. I'll answer the question in a couple different ways, so I would agree with Kevin because, you know, forget about what we do with our customers. You know, we had a pivot really quick to write all remote workforce. You know, I think about my team, you know, 1000 plus teammates. Everyone's 80% travel all gone like, um, and I write eso everybody working remote. Everybody work from their homes. And but the challenging part was working with our customers. And, you know, I look at you know, I looked at with Kevin. You know, I've never met Kevin in person, you know, frankly, and there's teammates have come on to our to the project and execute executing this program remotely, so it makes it that much harder working with the customer. Um, you know, doing more video chats. You know, our methodology is built to be all remote. We have a proprietary tool called snap start that allows to bail scan environments. All that things done. Remote migrations could be done remote. The hard part is when you have to go on site because there's this stuff you have to go on site for around physical inventory to look at the equipment, but it just makes it that much harder. You know, I think he taking advantage of these video tools like we're doing today. You know, I can't tell me how many Skype You know how many calls have been on with Kevin like this and with his peers and with his leadership. But communication is really important program like this because, you know, in a program like this, there will be problems, right? And there will be challenges and, you know, getting on a call on being I will look at Kevin face to face and see what his reaction is really key. But you gotta work that much harder. You gotta work that much harder now in the pandemic. You know, I have other projects right now leaving with this other projects that, frankly, we have sold all remote and we're doing it all remote. And what I'm seeing with the bidam IQ is an acceleration of digital transformation. So, other similar projects like we're doing with Kevin. We're doing for other large fortune 500 companies because it's an acceleration of Hey, look, we gotta be old digital now, so it'll be interesting to see you know how the pandemic effects is long term because it is definitely accelerating out their digital transformation if you haven't done it, you're in trouble because it's gonna eat your company alive. >>Mhm. So, Kevin, he's talking. He talked a little bit about she talked a little bit about the importance of communication, particularly when work so many people are working from home. Um, talk a little bit of about other best practices that have emerged. Things that you have noticed. Things that you advice you would have to your peers. I mean, a Z we heard from Steve. If you're not there yet, you're in trouble. But for the for the people, for the executives out there who are watching this, What advice would you have for them? >>Yeah, I think that you know this this is brought to light. You know, there was always a view that you had to be in an office on a white board and actual actually functioning in that fashion. So, you know, before the pandemic, I was traveling three weeks a month on now, not traveling. I feel that I actually get more work done. I actually feel that I'm closer to the team just because we've introduced a lot of different digital channels. So now we have slack we have teams we do zoom. I require everybody to be on a on video, whereas previously before the pandemic you'd rarely have anybody on video. Um, and you've seen Ah, transformation is people pick up the phone a lot quicker than they did in the past. So it is, actually, I believe, brought the team closer together because now you know, everybody's on. Um, the downside of it is everybody's on all the time. So you've also had to have people step away from work because generally when they take PTO, they leave the office that go somewhere with their family. Now it's your kind of at home. There's not much to dio. You kinda have to force them to take the time off. One of the major factors that has has been interesting is we're doing this transformation in the middle of co vid with moving. All of our resource is the home. So we've we've had to take pauses, toe focus on getting everybody to work from home. Okay, now their work from home back to the project. And, you know, it's kind of a change the timeline a little bit, but in the end, you know we have some hard deadlines to meet. So it's been an interesting transition. You >>know, Kevin, um, I wanna agree with you two points is, uh you know, I think we're also getting not only your time, but also senior leadership, that I think, frankly, we never would have gotten, you know, I'm talking, you know, your peers and your leadership, Like I would fly for those meetings. I think about all the time that I've saved. But then again, it never ends, right? Never. It begins and never ends. And, you know, one of the things I'm concerned about is you know, the long term burnout factor for these folks because and depending on what state you're in, it never ends. You don't have anywhere to go, right. And you know, I think about teammates. I think you know, Kevin, I have talked about this related to our project like burdens and really thing right now for sure. 889 months into this thing. It's a real thing. Is people they have to focus on. Is is work sometimes. So it's a it's a concern for all of us is a project team is we start looking at the executing. This continue to execute this program for the next year. >>And it really highlights the importance of visionary leadership and a leader who cares who is empathetic, who is checking in with his or her team and making sure that the colleagues feel appreciated and cared for. I want you both to just give us look into your crystal ball is a little bit and talk about the where you see things 12, 24 months from now. Hopefully there will be a vaccine and we will return to somewhat of a of a new normal. Um, talk a little bit about where you see the Maximus transformation in two years. Absolutely. Yeah. Start with you. >>So s so you know, our cloud migration. We have some hard deadlines through next year, so we have a focus with insight to get that completed by September next year because our data center contracts are up and we've got to get out. You know, one of the the advantages of where we're headed is to move into more of a Dev ops model where you know you're able thio enable groups that have previously not been able to do work just do thio. The infrastructure was set up your now, enabling them to do deployments, get into production and have full stack ownership. That's really where our focus is. Is enablement of the teams that couldn't do the work previously because now you're in a different type of environment. Um, the other thing is being able thio be more agile. So as we move forward into the cloud journey, we as a company are consort contracts quicker. We are part of the, you know, contract tracing on unemployment insurance. We've done a lot of contracts with states that you know previously most of our contracts or anywhere from a 62 120 day startup. These contracts and contact tracing and covert projects. We've had to start them up in three days. That's having 500 employees online on workspaces on Genesis Cloud and fully functional, and it has been a challenge. But it also has introduced a a better way to do business because now we can we can move quicker for our customers and we can get contracts where they come and say, Hey, I need something in the next couple days. If you look further down the road. You know, it's taking the advantage of what Amazon has to offer, you know, moving from arm or monolithic programs like, you know, we sit on Oracle on Lenox today. You know, we could move into Aurora, which opens up the doors and floodgates, because then you manage, er a little differently. You manage your data a little differently. That's really where I think the the market's going and where we can actually transform our business. Even better, Thio, where we could be more flexible. We can start up quicker and, you know, be doom or things for our customers. >>The final word from you >>e I think it's gonna be a hybrid world, right? It's at least in the short term. And you know, we believe it's all about the workload and getting those workloads or applications, you know, in in the right spot, whether it be public or private and helping our customers with that journey, you know, just a pile on with Kevin talked about around Dev ops. Once you get a guy to get once you get all the stuff over there, you still got to manage it, Whether it's in a W. S or, you know, on Prem. You still gotta have a process to do that. So we see a lot of opportunity around the Modern I t operations and helping with that way. We want to continue to be a trusted partner. Thio Maximus. It's been a great relationship, but I want to thank Kevin and his his leadership team for trusting in us. And we look forward, Um, or more success with him in the future. >>Excellent. Thank you both so much. Kevin and Steve, thanks so much for coming on the Cube. >>Absolutely. Thank you. >>I'm your host, Rebecca. Night. Stay tuned. For more of the Cube virtual coverage of AWS reinvent with special coverage of the public sector.

>> Narrator: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Everyone welcome to this special CUBE conversation. I'm John Furrier, host of theCUBE here in our Palo Alto studios. During this time of the pandemic, we're doing a lot of remote interviews, supporting a lot of events. theCUBE virtual is our new brand because there's no events to go to, but we certainly want to talk to the best people and get the most important stories. And today I have a great segment with a world-class entrepreneur, Ajeet Singh co-founder and executive chairman of ThoughtSpot. And they've got an event coming up, which is going to be coming up in December 9th and 10th. But this interview is really about what it takes to be a world-class leader and what it takes to see the future and be a visionary, but then execute an opportunity because this is the time that we're in right now is there's a lot of change, data, technology, a sea change is happening and it's upon us and leadership around technology and how to capture opportunities is really what we need right now. And so Ajeet I want to thank you for coming on to theCUBE conversation. >> Thanks for having me, John. Pleasure to be here. >> For the folks watching, the startup that you've been doing for many, many years now, ThoughtSpot you're the co-founder executive chairman, but you also were involved in Nutanix as the co-founder of that company as well. You know, a little about unicorns and creating value and doing things early, but you're a visionary and you're a technologist and a leader. I want to go in and explore that because now more than ever, the role of data, the role of the truth is super important. And as the co-founder, your company is well positioned to do that. I mean, your tagline today on the website says insight is the speed of thought, but going back to the beginning, probably wasn't the tagline. It was probably maybe like we got to leverage data, take us through the vision initially when you founded the company in 2012. What was the thinking? What was on your mind? Take us through the journey. >> Yeah. So as an entrepreneur, I think visionary is a very big term. I don't know if I qualify for that or not, but what I'm really passionate about is identifying very large markets, with very, very big problems. And then going to the white board and from scratch, building a solution that is perfectly designed for the big problem that the market might be facing from scratch. And just an absolute honest way of approaching the problem and finding the best possible solution. So when we were starting ThoughtSpot, the market that we identified was analytics, analytics software. And the big problem that we saw was that while on one hand, companies were building very big data lakes, data warehouses, there was a lot of money being spent in capturing and storing data how that data was consumed by the end-users, the non-technical people, the sales, marketing, HR people, the doctors, the nurses, that process was not changing. That process was still stuck in old times where you have to ask an analyst to go and build a dashboard for you. And at the same time, we saw that in the consumer space, when anyone had a question they wanted to learn about something, they would just go to Google and ask that question. So we said, why can't analytics be as easy as Google? If I have a question, why do I have to wait for three weeks for some data experts to bring some insights to me for most simple questions, if I'm doing some very deep analysis, trying to come up with fraud algorithms, it's understood, you know, you need data expert. But if I'm just trying to understand how my business is doing, how my customers are doing, I shouldn't have to wait. And so that's how we identified the market and the problem. And then we build a solution that is designed for that non-technical user with a very design thinking UX first approach to make it super easy for anyone to ask that question. So that was the Genesis of the company. >> You know, I just love the thinking because you're solving a problem with a clean sheet piece of paper, you're looking at what can be done. And it's just, you can bring up Google because you know, you think about Google's motto was find what you're looking for. And they had a little gimmicky buttons, like I'm feeling lucky, which just took you to a random webpage at that time while everyone else was tryna build these walled gardens and this structural apparatus, Google wanted you in and out with your results fast. And that mindset just never came over to the enterprise and with all that legacy structure and all the baggage associated with it. So I totally loved the vision, but I got to ask you, how did you get to beachhead? How did you get that first success milestone? When did you see results in your thinking? >> Yeah, so I mean, I believe that once you've identified a big market and a big problem, it comes down to the people. So I sort of went on a recruit recruiting mission and I recruited perhaps the best technology and business team that you can find in any enterprise segment, not only just analytics, some of the early engineers, my co-founder, he was at Google before that, Amit Prakash, before that he was at Microsoft working on Bing. So it took a lot of very deliberate effort to find the right kind of people who have a builder's mentality and are also deep experts in areas like search large-scale distributed systems. Very passionate about user experience. And then you start building the product, you know, it took us almost, I would say one and a half three years to get the initial working version of the product. And we were lucky enough to engage with some of the largest companies in the world, such as Walmart who are very interested in our solution because they were facing these kinds of problems. And we almost co-developed this technology with our early customers, focusing on ease of use, scale, security, governance, all of that, because it's one thing to have a concept where you want to make access to data as easy as Google, you have a certain interface people can type and get an answer. But when you are talking about enterprise data and enterprise needs, they are nowhere similar to what you have in consumer space. Consumer space is free for all, all the information is there you can crawl it and then you can access it. In enterprise, for you to take this idea of search, but make it production grid, make it real and not just a concept card. You need to invest a lot in building deep technology and then enabling security and scalability and all of that. So it took us almost , I would say a two and a half to three years to get to the initial version of the product and the problem we are solving and the area of technology search that we are working on. We brought it to the market. It's almost an infinite game. You know, you can keep making things easier and easier. And we've seen how Google has continued to evolve their search over time And it is still evolving. We just feel so lucky to be in this market, taking the direction that we have taken. >> Yeah. It's easy to talk a big game in this area because like you said, it's a hard technical problem because it'll structural data, whether it's schema databases or whatever, legacy baggage, but to make it easy, hard. And I like what you guys go with this, find the right information and put it in the right place, the right time. It's a really hard problem. And the beautiful thing is you guys are building a category while there's spend in the market that needs the problem today. So category creation with an existing market that needs it. So I got to ask you, if you could do me a favor and define for the audience, what is search-driven analytics? What does that mean from your standpoint? >> Yeah, what it means is for the end user, it looks like search but under the hood is driving large scale analytics. I like to say that our product looks like a search engine on the surface, but under the hood, it's a massive number crunching machine. So Search and AI driven analytics. There's two goals there. One, if the user has, any user and we're talking about non-technical users here, we're not talking about necessarily data experts, but if a user has a question, they should be able to get an answer instantly. They shouldn't have to wait. That is what we achieve with Search and with Spot IQ, our AI engine, we help surface insights where people may not even know that those are the questions they should be asking because data has become so complex. People often don't even know what question they should be asking. And we give them a pool that's very easy to use, but it helps surface insights to them. So there is both a pool model that we enabled through Search and a push model that we enable through Spot IQ. >> So I have to ask you that you guys are pioneering this segment you're in first. And sometimes when you're first, you have arrows in your back as you know, it's not all the beginners survive, they get competition copies, but you guys have had a lead. You had success. What's different today as you have competition coming in trying to say, "Oh, we got Search too." So what's different today with ThoughtSpot? How are you guys differentiated? >> Yeah. I mean, that's always a sign of success. If what you are trying to do, if others are saying we have it too, you have done something that is valuable. And that happens in all industry. I think the best example is Tesla. They were the first to look at this very well-known problem. I mean, we haven't had a very sort of unique take on the existence of the problem itself. Everybody knows that there is a problem with access to data, but the technology that we have built is so deep that it's very, very hard to really copy it and make it work in real world with Tesla in automotive industry in cars, there is obviously so many other companies that have launched battery powered cars, electric cars, but there is Tesla and there is all the other electric cars which are a bit of an afterthought, because if you want to build an analytics product, where Search is at the core, Search cannot be added on the top, Search has to be the core, and then you build around it. And that requires you to build a fundamental architecture from the ground up. And you can't take an existing BI product that is built for dash boarding and add a search bar. I have always said that adding a search bar in a UI is perhaps, you know, 10 to 20 lines of JavaScript code. Anyone can add it and there is so much open source stuff out there that you can just take it and plug it. And many people have tried to do that, but taking off the shelf, Search technology that is built for unstructured data and sticking it on to a product that is required to do analytics on enterprise data, that doesn't work. We built a search technology that understands enterprise data at a very deep level, so that when our customers take our product and bring it into their environment, they don't have to fundamentally change how they manage their data. Our goal is to add value to their existing enterprise data Cloud Data Warehouses and deliver this amazing Search experience where our Search engine is enable to understand what's in their data Lake, what's in their Cloud Data Warehouse. What are the schema, the tables, the joints, the cardinality, the data archive, the security requirements, all of things have to be understood by the technology for you to deliver the experience. So now that said, we pride ourselves in not resting on our laurels. You know, we have this sort of motto in the company. We say we are only 2% done. So we are on our own sort of a continuous journey of innovation. And we have been working on taking our Search technology to the next level. And that is something really powerful that we are going to unveil at our upcoming conference, Beyond, in December. And that is one to create even more distance between us and the competition. And it's all driven by what we have seen with our customers, how they're using our product or learnings what they like, what they don't like, where we see gaps and where we see opportunity to make it even easier to deliver value to our customers and our users. >> I think that's a really profound insight you just shared, because if you look at what you just said around thinking about Search as an embedded architectural foundational, you know, embedded in the architecture, that's different than bolting on a feature where you said Java code or some open source library. You know, we see in the security market, people bolted on security had huge problems. Now, all you hear is, "Oh, you got a big security in from the beginning." You actually have baked Search into everything from the beginning. And it's not just a utility, it's a mindset. And it's also a technology metadata data about data software, and all kinds of tech is involved. Am I getting that right? I mean, cause I think this is what I heard you say. It's like, you got to have the data. >> This is totally right. I mean, if I can use an analogy, there is Google search and obviously Yahoo also tried to bring their own search Yahoo search Yahoo actually, Yahoo versus Google is a perfect example or a perfect analogy to compare with ThoughtSpot versus other BI product Yahoo was built for predefined content consumption. You know, you had a homepage, somebody defined it. You could make some customizations. And there is predefined content you can consume it. Now, they also did add search, but that didn't really go so far. While Google said, we will vary from scratch ability to crawl all the data, ability to index all the data and then build a serving infrastructure that deliver this amazing performance and interactivity and relevance for the user. Relevance is where Google already shined. And you can't do those things until you think about the architecture from the ground up. >> Ajeet I'm looking forward to having more deep dive conversations on that one topic. But for the folks who might not be old enough, like me to remember Google back at that time, Yahoo was the best search engine and it was directory basically with a keyword search. It was trivial, technically speaking, but they got big. And then the portal wars came out, we got to have a portal. Google was very much not looked down as an innovator, but they had great technical chops and they just stayed the course. They had a mission to provide the best search engine to help users find what they're looking for. And they never wavered. And it was not fashionable about that time to your point. And then Yahoo was number one, then Google just became Google and the rest is history. So I really think that's super notable because companies face the same problem. What looks like fashionable tech today might not be the right one. I think that's... >> Yeah, and I totally agree. And I think a lot of times in our space, there's a lot of sort of hype around AI and machine learning. We as a company have tried to stay close to our customers and users and build things that will work for them. And a lot of stuff that we are doing, it has never been done before. So it's not to say that along the way, we don't have our own failures. We do have failures and we learn from them. >> Yeah. Yeah. Just don't make the same mistake twice. >> Yeah, I think if you have a process of learning quickly, improving quickly, those are the companies that will have a competitive advantage. In today's world, nobody gets it right the first time. If you're trying to do something fundamentally different, if you're copying somebody else, then you're too late already. >> I totally agree. >> If you do something new, it's about how fast you penetrate And that's... >> That's a great mindset. That's a great mindset. And I think that's worth capturing calling out, but I got to ask you because what's first of all, distinguished history and I love your mindset and just solving problems, big problems. All great. I want to ask you something about the industry and where you guys were in 2012 alright when you started the company, you were literally in what I call the before Cloud phase. Cause it was before Cloud companies and then during Cloud companies and then after Cloud, you know, Amazon clearly took advantage of that for a lot of startups. So right around 2012 through 2016, I'd call that the Amazon is growing up years. How did the Cloud impact your thinking around the product and how you guys were executing because you were right on that wave. You were probably in the sweet spot of your development. >> Yeah. >> Pre business planning. You were in the pre-business planning mode, incomes, Amazon. I'm sure you're probably using Amazon cause your starters and all start up sort of use Amazon at first, but I just think about, do we all have found premise with a data center? How did that impact you guys? And how does that change today? >> Certainly. Yeah it's been fascinating to see how the world is evolving how enterprises have also really evolved in depth, thinking on how they leverage the cloud infrastructure now. In the Cloud, there is the compute and storage infrastructure. And then you have a Cloud Data Warehouse, the analytics stack in the Cloud. That's becoming more popular now with a company like Google, having BigQuery and then Snowflake really amazing concepts and things like that. So when we started, we looked at where our customers are , where is their data. And what kind of infrastructure is available to us at the time there wasn't enough compute to drive the search engine that we wanted to build. There were also not any significant Cloud Data Warehousing at the time, but our engineering team our co-founders, they came from companies like Google, where building a Cloud based architecture and elastic architecture, service oriented architecture is in their DNA. So we architected the product to run on infrastructure that is very elastic that can be run practically anywhere. But our initial customers and applies the Global 2000. They had their data on-prem. So we had started more with on-prem as a go-to-market strategy. and then about four and a half years ago, once cloud infrastructure I'm talking about the compute infrastructure started to become more mature, we certified our software, to run on all three clouds So today we have more than 75 to 80% of our customers already running our software in the Cloud. And as now, because we connect to our primary data sources, our Cloud Data Warehouses, Cloud Data Lakes. Now with Snowflake and BigQuery and Synapse and Redshift, we have enough of our customers who have deployed Cloud Data Warehouses. So we are also able to directly integrate with them. And that's why we launched our own hosted SaaS Offering about a month ago. So I would say our journey in this area has been sort of similar to companies like Splunk or Elastic, which started with a software model initially deployed more on-prem, but then evolved with the customers to the Cloud. So we have a lot of focus and momentum and lot of our customers, as they're moving their data to the Cloud, they're asking us as well to be in the Cloud and provide a hosted offering. And that is what we have built for the last one year. And we launched it a month ago. >> It's nice to be on the right side of history. I got to say, when you're on the way to be there. And that also makes integrations easy too. I love the Cloud play. Let's get to the final segment here. I want to get your thoughts on your customers, your advice. There's a huge untapped opportunity for companies when it comes to data, a lot of them are realizing that the pandemic is highlighting a lot of areas where they have to go faster and then to go to Cloud, they're going to build modern apps more data's coming in than ever before. Where are these untapped opportunities for customers to take advantage of the data? And what's your opinion on where they should look and what they should do? >> Yeah, I really think that the pandemics has shown for the first, the value of data to society at large, there is probably more than a billion people in the world that have seen a chart for the first time in their life. Everybody is being... and COVID has done some magic. But everybody was looking at charts of infection and so on and so forth. So there is a lot more broad awareness of what data can do in improving our society at large for the businesses of course, in the last six, seven months, you heard it enough from lot of leaders that digital transformation is accelerating. Everybody is realizing that the way to interact in the world is becoming more and more digital expecting your customers to come to your branch to do banking is not really an option. And people are also seeing how all the SaaS companies and SaaS businesses, digital businesses, they have really taken off. So if a company like Zoom can suddenly have a a hundred, $150 billion valuation, because you are able to do everything remote, all the enterprises are looking to really touch their customers and partners in a lot more digital way than they could do before. And definitely COVID has also really created this almost, you know, pool buckets of organization. There is lot of companies that have tremendously benefited from it. And there a lot of companies that have been poorly affected, really in a difficult place. And I think both of them for the first category, they are looking at how do I maintain this revenue even after COVID, because one of this thing, you know, hopefully early next year we have a vaccine and things can start to look better again sometime next year. But we have learned so much. We have attracted so many new customers, how do we retain and grow them further? And that means I need to invest more and more in my technology. Now, companies that are not doing well, they really want to figure out how to become more operationally efficient. And they are really under pressure to get more value from there and both categories, improving your revenue, retaining customers. You need to understand the customer behavior. You need to understand which products they are buying at a fine grain level, not with the law of averages, not by looking at a dashboard and saying our average customer likes this kind of product. That one doesn't really work. You have to offer people personalized services and that personalization is just not possible at scale, without really using data on the front lines. You can't have just manager sitting in their office, looking at dashboards and charts and saying these are the kinds of campaigns I need to run because my average customer seems to like these kinds of offers. I need to really empower my sales people, my individual frontline workers, who are interfacing with the customer to be able to make customized offers of services and products to them. And that is possible on the data. So we see a really, a lot more focus in getting value from data, delivering value quickly and digital transformation broadly but definitely leveraging data in businesses. There is tremendous acceleration that is happening and, you know, next five years, it's all going to be about being able to monetize data on the front lines when you are interfacing with your customers and partners >> Ajeet, that's great insight. And I really appreciate what you're saying. And you know, I wrote a blog post in 2007. I said, data will be the new development kit. Back then we used to call development kits, software user development. >> John, you are the real visionary. It took me until 2012 to be able to do this. >> Well, it wasn't clear, but you saw other data was going to have to be programmed be part of the programming. And I think, what you're getting at here is so profound because we're living 2020 people can see the value of data at the right time. It changes the conversations, it changes what's going on in the real time communications of our world with real-time access to information, whether that's machine to machine or machine to human, having data in the right place, changes the context. >> Yap. >> And that is a true, not a tech thing, that's just life, right? I think this year, I think we're going to look back and say, this was the year that everyone realized that real time communications, real-time society needs real time data. And I think it's going to be more important than ever. So it's a really big problem and important one. And thank you for sharing that. >> Yeah. And actually you bring up a very good point programming, developing big data. Data as a development kit. We are also going to announce a new product at Beyond, which will be about bringing ThoughtSpot everywhere, where a lot of business users are in their business applications. And by using ThoughtSpot product, using our full experience, they can obviously do enterprise wide analytics and look at all the data. But if they're looking for insights and nuggets, and they want to ask questions in their business workflows. We are also launching a product capability that will allow software developers to inject data in their business applications and enable and empower their own business users to be able to ask any questions that they might have without having to go to yet another BI product. >> It's data as code. I mean, you almost think about like software metaphors, where's the compiler? Where's the source code? Where's the data code? You start to get into this new mindset of thinking about data as code, because you got to have data about the data. Is it clean data, dirty data? Is it real time? Is it useful? There's a lot of intelligence needed to manage this. This is like a pretty big deal. And it's fairly new in the sense in the science side. Yeah, machine learning has been around for a while and you know, there's tracks for that. But thinking of this way as an operating system mindset, it's not just being a data geek. You know what I'm saying? So I think you're on the right track Ajeet. I really appreciate your thoughts here. Thank you. >> Thank you John. >> Okay. This is a cube conversation. Unpacking the data. The data is the future. We're living in a real-time world and in real-time data can change the outcomes of all kinds of contexts. And with truth, you need data and Ajeet Singh co-founder executive chairman of ThoughtSpot shares his thoughts here in theCUBE. I'm John furrier. Thanks for watching. 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>> Announcer: From around the globe, it's theCube with digital coverage of MIT, Chief Data Officer and Information Quality Symposium brought to you by Silicon Angle Media. >> Hi, I'm Stu Miniman and this is the seventh year of theCubes coverage of the MIT, Chief Data Officer and Information Quality Symposium. We love getting to talk to these chief data officers and the people in this ecosystem, the importance of data, driving data-driven cultures, and really happy to welcome to the program, first time guests Eileen Vitrine, Eileen is the Chief Data Officer for the United States Air Force, Eileen, thank you so much for joining us. >> Thank you Stu really excited about being here today. >> All right, so the United States Air Force, I believe had it first CDO office in 2017, you were put in the CDO role in June of 2018. If you could, bring us back, give us how that was formed inside the Air force and how you came to be in that role. >> Well, Stu I like to say that we are a startup organization and a really mature organization, so it's really about culture change and it began by bringing a group of amazing citizen airman reservists back to the Air Force to bring their skills from industry and bring them into the Air Force. So, I like to say that we're a total force because we have active and reservists working with civilians on a daily basis and one of the first things we did in June was we stood up a data lab, that's based in the Jones building on Andrews Air Force Base. And there, we actually take small use cases that have enterprise focus, and we really try to dig deep to try to drive data insights, to inform senior leaders across the department on really important, what I would call enterprise focused challenges, it's pretty exciting. >> Yeah, it's been fascinating when we've dug into this ecosystem, of course while the data itself is very sensitive and I'm sure for the Air Force, there are some very highest level of security, the practices that are done as to how to leverage data, the line between public and private blurs, because you have people that have come from industry that go into government and people that are from government that have leveraged their experiences there. So, if you could give us a little bit of your background and what it is that your charter has been and what you're looking to build out, as you mentioned that culture of change. >> Well, I like to say I began my data leadership journey as an active duty soldier in the army, and I was originally a transportation officer, today we would use the title condition based maintenance, but back then, it was really about running the numbers so that I could optimize my truck fleet on the road each and every day, so that my soldiers were driving safely. Data has always been part of my leadership journey and so I like to say that one of our challenges is really to make sure that data is part of every airmans core DNA, so that they're using the right data at the right level to drive insights, whether it's tactical, operational or strategic. And so it's really about empowering each and every airman, which I think is pretty exciting. >> There's so many pieces of that data, you talk about data quality, there's obviously the data life cycle. I know your presentation that you're given here at the CDO, IQ talks about the data platform that your team has built, could you explain that? What are the key tenants and what maybe differentiates it from what other organizations might have done? >> So, when we first took the challenge to build our data lab, we really wanted to really come up. Our goal was to have a cross domain solution where we could solve data problems at the appropriate classification level. And so we built the VAULT data platform, VAULT stands for visible, accessible, understandable, linked, and trustworthy. And if you look at the DOD data strategy, they will also add the tenants of interoperability and secure. So, the first steps that we have really focused on is making data visible and accessible to airmen, to empower them, to drive insights from available data to solve their problems. So, it's really about that data empowerment, we like to use the hashtag built by airmen because it's really about each and every airman being part of the solution. And I think it's really an exciting time to be in the Air Force because any airman can solve a really hard challenge and it can very quickly wrap it up rapidly, escalate up with great velocity to senior leadership, to be an enterprise solution. >> Is there some basic training that goes on from a data standpoint? For any of those that have lived in data, oftentimes you can get lost in numbers, you have to have context, you need to understand how do I separate good from bad data, or when is data still valid? So, how does someone in the Air Force get some of that beta data competency? >> Well, we have taken a multitenant approach because each and every airman has different needs. So, we have quite a few pathfinders across the Air Force today, to help what I call, upscale our total force. And so I developed a partnership with the Air Force Institute of Technology and they now have a online graduate level data science certificate program. So, individuals studying at AFIT or remotely have the opportunity to really focus on building up their data touchpoints. Just recently, we have been working on a pathfinder to allow our data officers to get their ICCP Federal Data Sector Governance Certificate Program. So, we've been running what I would call short boot camps to prep data officers to be ready for that. And I think the one that I'm most excited about is that this year, this fall, new cadets at the U.S Air Force Academy will be able to have an undergraduate degree in data science and so it's not about a one prong approach, it's about having short courses as well as academe solutions to up skill our total force moving forward. >> Well, information absolutely is such an important differentiator(laughs) in general business and absolutely the military aspects are there. You mentioned the DOD talks about interoperability in their platform, can you speak a little bit to how you make sure that data is secure? Yet, I'm sure there's opportunities for other organizations, for there to be collaboration between them. >> Well, I like to say, that we don't fight alone. So, I work on a daily basis with my peers, Tom Cecila at the Department of Navy and Greg Garcia at the Department of Army, as well as Mr. David Berg in the DOD level. It's really important that we have an integrated approach moving forward and in the DOD we partner with our security experts, so it's not about us doing security individually, it's really about, in the Air Force we use a term called digital air force, and it's about optimizing and building a trusted partnership with our CIO colleagues, as well as our chief management colleagues because it's really about that trusted partnership to make sure that we're working collaboratively across the enterprise and whatever we do in the department, we also have to reach across our services so that we're all working together. >> Eileen, I'm curious if there's been much impact from the global pandemic. When I talk to enterprise companies, that they had to rapidly make sure that while they needed to protect data, when it was in their four walls and maybe for VPN, now everyone is accessing data, much more work from home and the like. I have to imagine some of those security measures you've already taken, but have there anything along those lines or anything else that this shift in where people are, and a little bit more dispersed has impacted your work? >> Well, the story that I like to say is, that this has given us velocity. So, prior to COVID, we built our VAULT data platform as a multitenancy platform that is also cross-domain solution, so it allows people to develop and do their problem solving in an appropriate classification level. And it allows us to connect or pushup if we need to into higher classification levels. The other thing that it has helped us really work smart because we do as much as we can in that unclassified environment and then using our cloud based solution in our gateways, it allows us to bring people in at a very scheduled component so that we maximize, or we optimize their time on site. And so I really think that it's really given us great velocity because it has really allowed people to work on the right problem set, on the right class of patient level at a specific time. And plus the other pieces, we look at what we're doing is that the problem set that we've had has really allowed people to become more data focused. I think that it's personal for folks moving forward, so it has increased understanding in terms of the need for data insights, as we move forward to drive decision making. It's not that data makes the decision, but it's using the insight to make the decision. >> And one of the interesting conversations we've been having about how to get to those data insights is the use of things like machine learning, artificial intelligence, anything you can share about, how you're looking at that journey, where you are along that discovery. >> Well, I love to say that in order to do AI and machine learning, you have to have great volumes of high quality data. And so really step one was visible, accessible data, but we in the Department of the Air Force stood up an accelerator at MIT. And so we have a group of amazing airmen that are actually working with MIT on a daily basis to solve some of those, what I would call opportunities for us to move forward. My office collaborates with them on a consistent basis, because they're doing additional use cases in that academic environment, which I'm pretty excited about because I think it gives us access to some of the smartest minds. >> All right, Eileen also I understand it's your first year doing the event. Unfortunately, we don't get, all come together in Cambridge, walking those hallways and being able to listen to some of those conversations and follow up is something we've very much enjoyed over the years. What excites you about being interact with your peers and participating in the event this year? >> Well, I really think it's about helping each other leverage the amazing lessons learned. I think that if we look collaboratively, both across industry and in the federal sector, there have been amazing lessons learned and it gives us a great forum for us to really share and leverage those lessons learned as we move forward so that we're not hitting the reboot button, but we actually are starting faster. So, it comes back to the velocity component, it all helps us go faster and at a higher quality level and I think that's really exciting. >> So, final question I have for you, we've talked for years about digital transformation, we've really said that having that data strategy and that culture of leveraging data is one of the most critical pieces of having gone through that transformation. For people that are maybe early on their journey, any advice that you'd give them, having worked through a couple of years of this and the experience you've had with your peers. >> I think that the first thing is that you have to really start with a blank slate and really look at the art of the possible. Don't think about what you've always done, think about where you want to go because there are many different paths to get there. And if you look at what the target goal is, it's really about making sure that you do that backward tracking to get to that goal. And the other piece that I tell my colleagues is celebrate the wins. My team of airmen, they are amazing, it's an honor to serve them and the reality is that they are doing great things and sometimes you want more. And it's really important to celebrate the victories because it's a very long journey and we keep moving the goalposts because we're always striving for excellence. >> Absolutely, it is always a journey that we're on, it's not about the destination. Eileen, thank you so much for sharing all that you've learned and glad you could participate. >> Thank you, STU, I appreciate being included today. Have a great day. >> Thanks and thank you for watching theCube. I'm Stu Miniman stay tuned for more from the MIT, CDO IQ event. (lively upbeat music)

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation [Music] hi I'm Stu manna man and welcome to a special cube conversation normally the first week of May we would be at Dell technologies world but that event has been moved to the fall but one of the major announcements from the event are going forward joining me to talk about powering up the mid-range of storage is Caitlin Gordon she is the vice president of marketing at Dell technologies Caitlin you thanks so much for joining thank you so much for having me Stu it's great to be here all right so Caitlin the last couple of years at a dtw different segments of the market as I said it's been powered up as the marketing messaging usually you've got some good t-shirts you've got a lot the labs and demos so tell us about the important announcement that you're sharing with today yeah I mean unfortunately the show is not going on but the product is still launching it actually is already started chipping and we are excited that we're still at be able to announce it this week our store is really probably the most exciting product they've ever gotten to help bring to market and all those demos and labs that you've talked about we're gonna have them all they're all going to be digital this year as well and it's really important for us as a business because it really changes what we're able to do for our customers you know we love speeds and feeds and storage but power store is so much more than that We certainly have designed it to meet the needs of all the workloads lock and file providing performance and efficiency but even more importantly what we built with this platform is something that will help our customers change the way that they're running their data centers and maybe most importantly can adapt with them as their businesses evolve yeah it's so important Caitlin I'm glad you talked about that you know you know the storage industry you know IP in general we can really get wonky and dig down to the speeds and feeds and yeah we want to understand you know how does nvm me and sports class memory and all that thing fit into but I want you to talk about you know what is that customer requirement that you're solving for in the age of AI and cloud you know what are the customers looking for what are those things that your cell for that maybe you know previous generations you go back to like the Unity ie this weren't on the table for discussion yeah I think one of the most interesting thing that's happened for us in the past few years in our conversations with customers is we do have the speeds and feeds the end-to-end nvme and octane and all that wonderful goodness but what they're really helped they're really asking for help on is how do they move towards this vision of having a truly autonomous data center how do they move to a fully self-service model so that all of their infrastructure can be treated like code and that you can automate all of those storage workflows picking out all of the additional costs and time and probably most importantly risk of manual tasks how do we have infrastructure that can be a more intelligent and helped them make more proactive and intelligent decisions that's one part of the equation the other piece is what we've heard loud and clear and this is now true more than ever before that infrastructure investments not only need to make sense for what the needs are today but also need to have the flexibility to adapt with businesses as they're going through this rapid and unpredictable transformation so that they can ensure that there are infrastructure investments today don't become technical debt tomorrow so that ability to have infrastructure that can adapt and evolve that the business is so important to our customers yes so Caitlin how is that done you know traditionally store do you think about it you know I buy a box like why did no way I write it off over 30 number years so what's different about you know the the service is and I'm guessing there's some financial pieces that make you know power store and the rest of the power family different than what I would have bought traditionally from buying a storage array yeah really the whole dynamic changes and it starts really foundationally with the flexible architecture so the product itself is built with the flexible architecture the ability the fact that it's a container based architecture were able to innovate on a container basis which makes our data services across the portfolio more consist enables us to innovate faster it also means that all of our innovation will be delivered to customers in a non disruptive way whether that's a hardware upgrade or a software upgrade all of that will happen without impacting the business that's really the flexible and adaptable architecture but when you look at the deployment that's an even bigger conversation how can we help and deliver infrastructure that gives you a solution that can support a small footprint at the edge collapse that infrastructure at the edge help with data center modernization connect into cloud and the last piece you're just touching on is that consumption more and more and then that's accelerated over the past month or so the ability to consume this as a service it's such an important part of what we're doing here in power stores available all of our Dell technologies on-demand offerings flex on-demand to give you that ability to really consume an infrastructure and an object model really interesting you talked about you know underneath the covers you know containerized architecture you know I think back the previous generations when you know EMC moved on to an intel-based architecture you know there's things where you say there's a major change in the code bases a major change in the architecture and from a customer standpoint they shouldn't have to think about it but I know there's so much work that goes through to make sure that things are rock-solid that it's still gonna provide you know X nines of capability and make sure that you can run your business on it helped us understand a little bit about you know how you know you said a lot of things have changed but we're still talking about things that you know you're running you know our business is on or you know mid-race customers for small enterprises midsize enterprise you know but what's what's still the same I guess is what I'm asking for today's storage compared to what we were looking at that yeah and if you look at it I mean the architecture itself is built as an architecture can pick conserve the broadest set of needs or the biggest set of our customer base so foundationally it supports all physical databases and applications we've got we've all support it's got performance that's really incredible compared to our previous lead mid range all flash solutions seven times faster three times better response times the efficiency of course is critical the ability to support that in a really small footprint with always-on inline data reduction four to one guaranteed the architecture not only scales up of course as a storage appliance but also can independently scale compute so they have the ability to scale up in an appliance and scale out into a cluster and of course you can't resist the buzzwords that's important and an nvme of course the ability to support nvme based flash drives or SEM and it's specifically actually the dual ported octane drive for persistent storage so when you look at it it truly is a best-in-class all flash mid-range storage array but it also does a lot more and that's part of the fun dynamic of what we've built okay so you know we talked about scaling up and scaling out you know of course you know we look at Bay's world two things that are critically important to customers it's my data and my applications obviously you know strong legacy at Dell EMC looking at the data you touched a little bit about the applications but you know tell me more how does this fit for you know my latest cloud native type environments you know how do applications fit into this environment yeah and it's really builds on what we're starting to talk about with that container based architecture so the fact that his container based is interesting and good for us because we can innovate faster it's even more important for customers and we can deliver that to them faster and more consistently what's more interesting is what we can then do for their workloads and their applications because we have this brand-new modular software operating system of course we can deploy that as a standard bare metal on purpose-built hardware or storage appliance what's even more interesting and what's really different about what we can do with our store is we can also abstract that storage OS from the underlying hardware onboard VMware ESXi and run both the storage operating system and applications natively on the appliance so able to collapse the compute and storage layers into a single piece of infrastructure and run a handful of specialized applications on that one appliance which really is game-changing in the data center at the edge to change the way that you can run and consolidate your operations okay yeah if you say specialize to applications so let let's build onion a little bit on that you know I think back obviously you know Dell has a very strong position in hyper-converged infrastructure which is scaling you know compute and storage and doing that an entire environment I remember there were a lot of efforts to say well with a virtualized environment maybe I hate storage and I can put applications on it that was there was use case with Isilon and to say you know I've got a lot of general-purpose compute if I have some excess capacity maybe I can do that it wasn't something that I heard used a lot so what sort of applications and how do kind of compare and contrast this with other things like like HDI yeah and this is power stores apps on capability and really what it's built for is these kind of two classes of applications the first is infrastructure apps so think of these as any type of application that the infrastructure team themselves is is leveraging and wants to simplify their operations antivirus data protection things like that the other category would be what we call data intensive so a data intensive application really is more storage intensive right either has a high demand for capacity and a small demand for compute or is one of these more latency sensitive applications real-time analytics is a good example things like blink and spark the response time is really King and when we look at that in comparison to what HCI is we have been and we are in a great position right with the xrail has been leading the hyper-converged market and we know that our customers are deploying that alongside three-tier architecture and what you look at what we've done with our store what we already have with rail they're highly complementary what we've done in HCI is we've taken storage and brought it into compute what we've done with power store we've taken storage and we brought compute into it and it really solves four different is optimized for different challenges and we really think complementing those in the data center next to each other is going to be an increasingly common deployment model to have the right architecture or the right workloads and then you have VMware consistent operations across the top so you have that consistent operations within your data center whoo edge and also to the cloud all right so end-to-end portfolio is what you're saying there's options for the different applications what one of the big challenges for storage people always is you know I always used to joke it's the four-letter word its migration so customers you know there there are very few Greenfield deployments out there so the existing Dell customers people out there that have been doing things in previous ways how do they get to power store and you know once they're on power Spore what does that mean for you know future you know growth expansion you know migration discussions yeah and I've heard this before right forklifts are not a friendly thing and the good news is with power store it is truly the end of data migration we've built with power store is an architecture that enables you to non-disruptive Li upgrade the controllers when new generations come out you can destructively operate those keep all the capacity in place and don't have any an impact to your business we also know the customers need to get data to powers for now getting to the 2 power store is going to be really really seamless we have invested significantly and a number of different migration options for our portfolio and for third-party to get data to our score and what seamless means could be different to different customers that can be non disruptive it could be agent lists it also could be host based we'll have all of those solutions from day one to enable that transition that happened as seamlessly as possible and on a customer's own time we've actually optimized this to the point where we now enable you to move data from an existing platform to our store in less than 10 players okay that that's great Kaitlyn so you know III remember back when Mendell first finished the acquisition of EMC one of the things we heard loud and clear with Jeff Clarke is a simplification of the portfolio it's something we've heard throughout the ranks remember talking to Jeff Boudreau about hinting at what was happening at the in the mid-range so what does this mean for existing mid-range lines and tell us about what we expect to see as this transition rolls out yeah absolutely so power store is absolutely our lead mid-range all-flash offering we continue to have unity XD is our lead hybrid mid-range solution and we have at end of life any of our other existing mid-range platforms what we know above anything else is that transformation and transitions in the data center and on storage race takes time and the important thing for us is that we enable our customers to do that on their own time and as seamlessly as possible so we have not announced a new end of life when we do we're going to have a long service life and we've built all of these different migration tools to help support that transition so it's going to be very easy for our customers to do that move on their own time and it still enables us to deliver on what we've promised you which is a simplified portfolio great Kaitlyn last thing I want to ask you is what's challenging for people is number one they've got kind of the skill set and the rules that they have today so there needs to be you know an easy migration to go from what they have to the new on the other hand also sometimes it you you want to take a clean sheet of paper and say boy if you could just start over and do it this way it's going to make your life so much easier so tell us how you're balancing that and how you can help both that you know you're your install base as well as you know new people coming in that might not have been traditional storage industry yeah I think the reality is that they're the specialized skill as a storage administrator isn't is something that will not be a growing skill set and we need to help our customers certainly support an operating model that does work like a storage array but does so in a way that is extraordinarily simple and has a lot of intelligence built in so first and foremost this is a storage platform and has really been designed who have the most seamless and simple operating experience from an element manager with our store manager for a storage admin but at the same time we know that for a variety of reasons a lot of customers have a single team that managed their infrastructure and is really moving into more of a cloud operating model and for that we've built in all of the integrations and tools with vmware whether it's Fiero vmware cloud foundation to really help vmware administrator also be able to operate the system as well excellent so it's just on that also how do things like analytics fit into the entire monitoring discussion help us understand how that fits in with some of the rest of the Dell portfolio yeah that's exactly where I was going to go over the last piece of this is why would I Q is something that's really important is Prateek for us cloud IQ of course comes with power so it comes with all of our storage offerings today we're officially announcing it coming across our infrastructure portfolio as well and that's really game-changing for customers in a number of different ways first is it really helps produce risk in the environment because it shows you a health scare or for your data center and if it has an issue it will quickly help you pinpoint that and troubleshoot it before it ever actually becomes a problem that impacts your business you're gonna help you predict your future user needs things like predictive analytics built into cloud IQ help you do capacity forecasting and planning so that you can see exactly when you're going to get to those thresholds of 80 90 100 percent capacity and remedy that board impacts the business and with it now coming across the entire infrastructure portfolio the value it can bring is outside of just storage alone but to the entire data center and one of the biggest things our customers and partners have loved about Cloud IQ is the trusted advisor feature that allows these are our reps or partner to have the ability to be part of that cloud IQ experience he read into from a mobile application or from a web browser have that remote monitoring of the environment and add that human intelligence to the machine intelligence really manage that data center and help our customers stay on top of problems and stay ahead of them before they impact the business well Kaitlyn congratulations the whole power store team we understand a lot of hard work goes into building this and really look forward to by the time we get to Delta technology's world in the fall talking to customers that are using thanks so much for joining us and look forward to talking with you again thanks - great to see you all right be sure to check out the cube dotnet for all the upcoming events that we're doing right now of course a hundred percent remote I'm sue minimun and thank you for watching the Q [Music]

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Welcome to the cubes coverage here in Moscone in San Francisco for RSA copper's 2020. I'm John hosted the cube and you know, cyber security is the hottest thing. Transforming businesses and you know, old. It has to transform into not only playing defense but playing off fence and understand the threats, how to organize around it. And that's really been a big part of this new next generation architecture operations and just mindset. We've got a great guest here to share his perspective. Luke Wilson, who's the vice president, intelligence for four IQ hot startup but also former FBI counter terrorism of right other DOD state department. Uh, tons of experience on both sides. Now on the commercial side. Luke, thanks for coming on. Thanks for having me. So obviously your background gives you a unique perspective and you know, I've been in uh, in the commercial side, I haven't done any government service like you have, but I can tell you it in the enterprise it's been boring. >>Oh yeah. He has storage, provisioning, storage, business servers, cloud comes in, it gets exciting. Yeah. Startups are doing cloud native lot more robust scale and you starting to see the new applications with that, the security perimeter is gone. It's now a huge surface area. So the enterprise has to get more FBI like or more smarter around how they organize, how they hire. Yeah. This is your, this is your world. Yes, it is. What's your take on this? What's it, what's your view of the industry right now? Well, I think right now what you're seeing is this change from, uh, you know, I hate to be cliche about it, but for years we've been playing whack-a-mole against the bad guys. I've see Matt, you know, uh, at my time at the FBI and various government, different agencies there, um, we're starting to see a shift of alright, we want, they want to know, okay, how is this happening to them? >>So it's just not the, the, what's happened. It's like who's behind it. And you know, in today's, in today's, uh, arena with the, you know, with cyber security, you have to start figuring out what entity is behind these attacks, uh, what they're going after. So you can start protecting that, but then also using that information, that intelligence from there, sharing it with other business sectors and then also turn in that big backend side so you can have some kind of preventive maintenance as well. I mean, you've got a lot going on. There used to be a nice little neat little industry in a box security by some software. You've got the servers, you have firewalls, all that nice stuff. Now you're talking about elaboration. Operating models are changing. A whole new dimension and open source has given a, an ability to cloak, whether it's nation States can now be operating under stealth mode. >>Oh yeah. You have all kinds of new dynamics. What is, what does the company do? You know, how do people solve this? There, there is no one answer or that, you know, it's got, it's gonna take a community, uh, the community of protectors and, uh, groups that want to help solve these issues. Uh, you know, and law enforcement, we always say, you know, it's a, it's a cat and mouse game. We catch up to them and then they change a little, you know, maybe a little bit here and there and then we catch up to him again and, uh, we're just gonna keep playing that game. But you know, uh, businesses, commercial businesses are starting to get into that, into that mode as well of, Hey, just because I defeated something today doesn't mean it's going to be right back at my door tomorrow. You know, you and I saw each other last night at the general Alexander's, uh, talk, uh, and he's always been all about offense, defense and understanding visibility and signals. >>Um, you know, there's a lot to do there. Um, you got to know where things are coming from. There's a lot of shared responsibility, but shared work, right? It's like, yes, we want, there's a lot of redundancy going on in security now. Oh yeah. And within and without pumping. So the collaboration, you mentioned the big part, how do you see that evolving that you work with the FBI counterterrorism, you kind of see how this kind of thinking renders itself. How does that work in a commercial world? How do you see that evolving? Well, you have certain cyber centers that are built for that kind of model, uh, for, uh, helping, you know, commercial, uh, industries, uh, deal with that threat. You know, there's no, uh, one tool, one company that can protect itself from a nation state attack. Uh, we've seen that, you know, so, uh, the best thing that's happening right now is people are starting to understand in order to get the entire, um, I would say the topology of the attack, that's that that's affecting you. >>You're going to have to share this information. You're going to have to learn from other groups. Uh, law enforcement, intelligence agencies are sharing. Um, and, you know, it's quite frankly, it's, it's, we're kind of late in the game of sharing, which the criminals have been doing this now for years, you know, sharing that information and understanding who to attack them, when to attack. Yeah. And they've been been winning. So I gotta ask you, as someone who's been in the industry now, and I'm book both sides, you look at RSA this year, um, besides the headline of the coronavirus who's got a backdrop to all of this, there's still a huge show here and, and the trends are changing. It seems to be the scene game, whack a mole on steroids, but now you've got cloud. What's new out there that, that's getting you excited? What do you think people should be paying attention to? >>Why? I think what people should be paying attention to is now a lot of the, I would say the products and the tools that are coming out are actually being developed by people who are practitioners have been in that space and understand what it takes in order to defeat, uh, the, the types of criminals that you're facing every day. Um, you know, I, I see a lot of products, uh, getting into the, the hoop, you know, and for me, I think that's a very, uh, a very strong point now that you can't just keep saying, I closed this court and that court in this sport and we're good. No, they're just gonna change little thing and come right back in. Um, so I see a lot of tools or act or identification or identification time attribution, um, people are trying to get to the who in this space now in order to turn that back around for prevention as well. >>So something where normally this is, you know, an FBI, uh, uh, you know, a federal government, uh, uh, agency trying to figure out the who, a lot of the tools and, and some of the, uh, you know, the data today is helping out with that for private industry. So that are great point gradient site by the way. I love that. I love that angle on that. What about meal time? Because now real time is a big one and people are overworked. It's a pile of threat detection out there. Like, Hey, there's some stuff happening in another company. So people are buying feeds. I get it right now. You need a data processing perspective. You've got to get the data. How does that, how do you see that whole challenge become an opportunity? Well, you know, uh, we're a data driven society now, right? So everything has data connected to it. >>Um, you know, and, and you're getting that amount of data stream float into your commercial entity. You know, first of all, it needs to be automated. You're going to have, you know, a lot, a lot of data to sift and sort through to understand what's actually happening here. So I think the, the, you know, that that live feed going real time is very helpful, but also content, uh, you know, put some context context behind that and having and having that, that information fully digested so you can understand what's the threat, how's it coming at you. And then using that for prevention. Super exciting time. I want to get into your experience and how that translates into maybe your advice for people that are kinda kind of waking up from lack of multiple, kind of being more of a kind of a versatile athlete, if you will, athletes, cyber athletes. >>Um, but I gotta ask you about, um, the idea of threats that are coming in that you seen in the FBI that enterprises should be paying attention. Because I'll give you an example. I'll say, Luke, I'm good. My it department covering this for years. I don't really have anything that's valuable, right? So I'm good. I got my patches done, so I don't really need to buy anything from you or I'm good, right? Not everyone's saying that, but that can be the mentality at different spectrum of, all right, so what do, what do you say to that? Well, you know, besides, I'm an idiot, you know, we see that a lot and I think, um, you have to, that, that's a very big naive approach about it. Um, you know, you also have to start thinking about, are you good with your insider threat? Are you good with your third party risks, you know, threats. >>Um, so there's so many things going down the line. When you look at what it takes for, let's say a large financial institution to run, would it take for a large, uh, company like an Uber or Lyft to run? Um, you know, there's, there's threats there and if you're saying you don't have any threats and you're, you're, you're OK, then uh, you know, I would say that's a, that's another, it's being polite, being polite. What you're saying is, no, you're not. Okay. Well, I mean, cause if, think about it, if you're just running a main small little manufacturing operation, I don't have any IP, but your operations is your IP. You might be exposed for ransomware or some, you know what I'm saying? There's always disruption. This has been kind of an interesting, there's a mindset. It's not just what you think you have. There's a holistic view. >>What's your take on the reaction to that? Yeah. It isn't the holistic view. You have to take that approach. You've seen what's happening nowadays, especially within the ransomware. Uh, you know, it's, it may come from a third party that basically didn't secure their systems, but they knew exactly what they went with, the cyber criminal, exactly what they were doing because they solely wanted to attack you and they knew the weakest link was three steps down from you. And so that's exactly where they went to. You know, I love these conversations and not, you know, a lot. I'm a Patriot and I love to help our country. I do my best. I don't really serve in the government, but one of the things I feel strongly about and people know I rant about this all the time when I'm on the cube is that digital war is happening and I really believe that, you know, our, we're a free society. >>You can't lock every door in this country. You've got borders, physical borders, so digital borders or if we're open society, you can't really be defensive all the time. Yeah. So if someone does strike us, our answers especially been counter strike back with a vengeance. Exactly. Which is how the deterrent is. But digitally, where's that line? I mean if you drop chips in Manhattan, you know you're, we're a tapping attack. What's the digital drawing in your opinion? Because this is something that Noah's talking about, but it's kind of paper cuts is that there's a line of knowing is are we being attacked? It's the who. What's your view on this? I know it's a new emerging area. Yeah. Aye. Aye. Aye. I seem to I think a little bit on both sides here. I want to do something back, but I don't think I'm most special, especially commercial businesses. >>Understand what that means. Actually find some attribution and then say, you know, it is this entity or this country that's doing that and it's kind of a slippery slope when you start getting out of that cutting edge societal issue. Because I mean the government has a military to protect me, right? But if I'm a cyber company, I going to build my own military digital military. Now what are we talking about here? I mean, it's interesting. It's, it's again, that's why I start seeing a lot. If you look at the place, you know around here you start looking at some of these tools, they are offensive weapons. When you look at them, these are weapons to understand, well not weapons, but tools to understand who and you already know what happened. And so now you get the who and the why, right? Yeah. You can't really strike back. >>But what you could do is turn that back inward and say, okay, I'm going to start preventing this stuff. Yeah. Right. But then also, Hey, I can go to the, you know, the FBI and say, here's a nice neat packet of information on what happened to me and who we believe it to be. And that's where that conversation starts to happen. And I'm really excited by the digital twin and the simulation environments where you can start having flex, you can flex scenarios to do, use some of this scenario based planning so you can protect and plan for scenarios which is reacting to it. Yeah. Yeah. The digital training space, when he got there, you know, and it just like you stated earlier, right? You know, the, the, the United States military goes out here and trains for certain scenarios all the time. Companies have to start doing that because that's what's happening to them. >>You know, they're, you're right on the money. I love the insight. Thanks for sharing. Greetings. I love that you got to get the reps and you got to do the operations. You got to nail that. So just give a quick plug before IQ. Thanks for sharing your awesome insight. What do you guys do and what are you guys all about? What's your value proposition? Great. Yeah, we're, we're identity intelligence company. Oh, what that means is that we have tools and products that's going to allow our clients get to that who, you know, uh, and we also have tools that allow them to get to the what as well. So we're on both sides of a, of the fence there. Um, we're trying to get left of boom, what they call it. Um, but our data and our intelligence allows us clients to find the bad guy. >>A very simple, we have some AI and machine learning built into there where it's almost like a click of a button, I can expand and figure out who these individuals are and understand their TTPs. And what we want to do is make automation of these different types of tools easier and faster for the clients to use. So you want to bring intelligence into their visibility space or data space or, yes, I actionable intelligence. Yeah. So basically in their, into their digital space of understanding, you know, their attack surface, understanding what problems that they're having. And then we have, um, you know, like I said, a lot of tools and, and, and, and, and, um, it's, I would call it tell who calls you out, who's the customer, who's the buyer, the IOC show? Is it, uh, uh, off-gas? What's the, who's buying your stuff? So mainly what we're into a lot of, um, cyber fraud, fusion centers, just like that. >>Law enforcement intelligence agencies. Um, I would say, you know, I, I know for a fact that I wouldn't use this, you know, if I had this tool and the FBI. Um, and, and, and a lot of, you know, if you have a large digital footprint, uh, we have cryptocurrency companies using this as well. Um, you know, you're, you're seeing some, some, some pretty bad guys attacking your systems, trying to defraud you. Our product helps you out with that. Right. Luke, great conversation. Thanks for coming on. Appreciate RSA coverage. Taking the show. What's the hot thing at the show? What's your favorite moment here? What's, what's the big story here at RSA? I w I would say, uh, for me it's this, uh, sit in the one, uh, Ashton Martin sit now, you know, every year there's something different. You know, I go to these Bitcoin conferences and I see they usually have Lamborghinis out for it. And now I think this is happening. So yeah, I don't know if we're trending in that direction now. Get in that car and we're gonna erase away. Great. Luke Wilson, VP of intelligence before I Q a here inside the cube, the cube coverage show our say I'm John furrier. Thanks for watching.

>>From our studios in the heart of Silicon Valley. Palo Alto, California myth is a cute conversation. >>Hello and welcome to the cube studios in Palo Alto, California. For another cube conversation. We go in depth with thought leaders driving innovation across the tech industry. I'm your host, Peter Burris. It's a well known fact of life at this point in time. We're going to the cloud in some manner, way, shape or form. Every business that intends to undertake a digital transformation is going to find themselves in a situation where they are using cloud resources to build new classes of applications and accelerate their opportunities to create new markets that are more profitable. What folks haven't fully internalized yet though is what it means to govern those activities. What does it mean to use data that is in the cloud in a compliant and reliable way? What does it mean to allow rapid innovation while at the same time ensuring that our businesses are not compromised by new classes of risk, new classes of compliance issues as a result of making certain liberties, uh, with how we handle governance. So that's what we're going to talk about today and we've got a great conversation for you. Toby Knapp is a co founder and CTO of day two IQ and Charlie Betts is the principal analyst at Forrester. Toby. Charlie, welcome to the cube theater. All right, so Charlie, I'm going to start with you. I kind of outline the overall nature of the problem, but let's get it very specific. What is the problem that enterprises face today as they try to accelerate their use of technology in a way that doesn't compromise the risk and compliance concerns? >>Well, we are hearing the same story over and over again. Peter, uh, companies are starting on the cloud native journey and perhaps a dev ops journey. You know, there's some similarities there. You know, one leads to the other in many cases and they S they do a proof of concept and they do a pilot and they like the results. But both of those efforts had what from monopoly, we would call it a get out of jail free card. You know, they had a pass to bypass certain regulatory or governance or compliance controls. Now they want to scale it. They want to roll it out across the enterprise and you can't give every team a get out of jail free card. >>Well, let me dig into this because is it that the speed with which we're trying to create new things, is that the key issue? Is it that the new technologies like Coobernetti's lend themselves to new style that doesn't necessarily bring good governance along with it? What is, what are those factors that are driving this problem? >>I think the central factor, Peter, is the movement from stage gated governance to governance of continuous flow. We could unpack this in various ways, but really if you look at so many governance models and people ship them to us and we comb through them and it's getting, you know, doing a lot of out lately, what we see is over and over again, this idea that delivery pauses experts come in from their perspective with a checklist they go through, they check the delivery against the checklist, and then the Greenlight is given to move on. And this is how we've run digital systems for a long time now. But now we're moving towards continuous flow, continuous iteration, >>agile, agile, DevOps, >>dev ops, all the rest. And these methods are well suited to be supported by architectures like Coobernetti's. And there are certain things you can do with automation that are very beneficial in cloud native systems, but you're up against, you know, decades of policy that assume this older model is based on older guidance like ITIL and PIM, Bach and, and COBIT and all the rest. COBIT 2019 is still based on a plan build run model, >>which is not, is not necessarily a bad thing in the grand scheme of things, but it doesn't fit into a month long sprint. >>It doesn't fit. And more and more what we're seeing when I say stage Gates are going away, what we're seeing is that the life cycle becomes internalized to the team. You still plan, build, run. But it's not something that you can put controls >>on at the high level. And so the solution seems to be is that we need to be able to foster this kind of speedy acceleration that encourages the use of agile, uh, leads to a dev ops orientation. And somehow fold good solid governance practices right into the mix. What do you think the, let's take a look at 2025, what's it going to look like? And uh, even if we're not ready for it yet? >>Well, I think you were going to govern a lot more at the level of the outcome. You're going to govern what not how as much, but there are a lot of things that still are essential and just basic solid good practice such as not having 15 different ways or a hundred different ways to configure major pieces of infrastructure. You know, there's a, in the, some of the reports, uh, the state of DevOps report that came out, there was a, uh, a note in there or a finding in there that it was best to let the developers have a lot of choice. And I understand that developer autonomy is very important, but every time a development team chooses a new technology or a new way to configure an ex, an existing technology, that's an expansion of attack surface. And I'm very concerned about that, especially as we see things like Equifax with the, uh, the struts exploit, you know, we, we have to keep our environment secure, well patched up to date. And if you only have one or two ways that things are configured, that means your staff are more likely to do the right thing as opposed to, you know, infinite levels of variation, you know, on a hundred different ways of configuring. Coobernetti's >>well, presumably we don't want the infinite levels of variation to be revealed at the business level and not down at the infrastructure level. I think one of the things that folks mean or folks aren't intending or hope to be able to do with digital business you're alluding to this is creating a digital asset, a software based asset because ultimately it's going to be more integratable, but you lose the opportunity to integrate those things if you're increasing the transaction costs by introducing a plethora of discordant governance models. Is that what you're seeing as well, Toby? >>Absolutely. And I think, uh, you know, some aspects of cloud native that make this problem a lot bigger is actually, you know, cloud native encourages sort of a self service model for infrastructure. And also we're seeing our shift, um, off, uh, power and decision making towards developers, right? So you have developers introducing a lot of these new stacks, often in a very, you know, sort of bottoms up, um, organic way. So very quickly and enterprise finds themselves with, you know, 10, 15 different ways to provision infrastructure to provision communities, clusters. Um, and often, you know, the teams that are in charge of governance aren't even aware of these things, right? Yes. So, uh, I think it starts actually with that and you know, how can we find, uh, this balance of giving developers the flexibility they want, uh, you know, having them leverage the benefits of cloud native, but at the same time making the folks that are in charge of governance, uh, aware of what's going on in, in their enterprise, uh, making them aware of the different stacks that are provisioned. Uh, and then finding the right balance between that flexibility and enforcing governance. Uh, there's ways to do that. Um, you know, there what we see a lot is, is, uh, waste, uh, people building one stack on cloud provider, a different stack on cloud provider B, a third stack, you know, at the edge or in their data center. And so when it comes to patching, security issues, upgrading versions, you know, you, you're doing three, five times the, the amount of work. >>Well, let me ask you a question because we can see that the problem is this explosion in innovation at the digital level, uh, that is running into this, uh, the, the stricture of historical practices. And as a result, people are in running governance. What is it, I mean, if I think about this, it sounds to me like the developer tooling is getting better, faster than the governance tooling. Where are we in the marketplace in terms of thinking about technologies that can improve the productivity on the governance side so that we can bring governance models to the developers so they don't have to make decisions at that level? >>Right. I think where we are in the market is, um, so obviously cloud native and Kubernetes specifically has seen rapid adoption Indiana price, right? And I think, um, you know, the governance and tools are just now catching up. Right? Right. Um, so the typical journey we see is, uh, you know, folks try out Kubernetes, they try out cloud native technologies to have a very good first experience. It's easy. And so they kind of, uh, you know, forget some of the best practices that we've learned over the years for how to secure a production stack, how to make it upgradable, maintainable, how to govern workloads and versions, um, because they'll still, schools just simply didn't exist. Uh, so far we're now seeing these tools emerge. Um, and, and really it's the same approaches that have worked for us in the past for, for running these types of infrastructure. It's, um, you're having a central pane of class for visibility. What versions am I running? Uh, you know, first being aware of what's out there and then you'll centralizing management of these, of these stacks. Um, how do I, you know, lifecycle manage my, my Kubernetes clusters and all the related technologies. Those are the tools that are just now showing up in the market, >>but it's also got to be, I presume that, uh, a degree of, uh, presuming that the tooling itself does bring forward good governance practices into a modern world. If I got that right. >>Yeah, absolutely. I think this is one of the key things that the updated INO team, uh, the infrastructure and operations and our, our view is that these become platform teams. So we've maybe relieved the INO term behind we go with the platform teams. This is one thing that they should be doing is creating reference implementations. You know, the, you know, here's your hello world stack and it's perfectly compliant. Go solve your business problem and leave the undifferentiated heavy lifting to us. You know, and this is I think, uh, going should be a welcome message. Uh, assuming that the stack is providing all the services that the developer expects. >>Well it certainly suggests that there is a reasonable and rational separation of duties and function within a business. So the people that are close to the business of building the function that the business needs are out there doing it. Meanwhile, we've got infrastructure developers that are capable of building a platform that serves as multitude of purposes with the specificity required for each workload and in compliance with the overall organization. >>There's a key message that I want to reinforce with the audience as we think about the future of INO. I, we've been thinking a lot about it at Forester. What is the future of the traditional INO organization? If I say infrastructure that implies application and I'm talking about a stack that doesn't go away, you know, there will always be a stack, a layered architecture. What is being challenged is, when I say operations, that implies dev and I'm talking now about a life cycle. That's what's merging together. And so well, the life cycle becomes something that is held internally within your feature or component team and is no longer a suitable topic of governance. Absolutely. In terms of the layered infrastructure, this is where we, it's still a thing, you know, because yes, we will platform teams, component teams, feature teams facing the business or the end user. >>Well, it's all back to the idea that a resource is a reasonably well bound, but nonetheless with the appropriate separation, uh, of, of function that delivers some business outcome. And that's gonna include both infrastructure at a software level, an application at a software level. So look, we, you spent a lot of time talking to customers about these issues when they come back to you. Uh, where are you seeing successes most obviously and why? >>Yeah, so where we see successes is where, um, you know, organizations, um, figure out a way to give developers what they want, which is in the cloud native spaces. Every development team wants to own their own communities cluster. They want to, it is their sandbox. They want to install their own applications on there. They don't want to talk to different team when they install applications. So how can you give them that while at the same time enforcing the standards that you need to, right? How do you make sure those clusters follow a certain blueprint that have the right access control rules? Um, you know, sensitive information like, like credentials are distributed in the right way. The right versions of workloads are available. Organizations that figure out how to do that, uh, they are successful at this. So the government from a central place, they have um, you know, essential pane of glass. >>Um, you know, like our product commander where they essentially set up blueprints for teams. Um, each individual team can have their own cluster. It gets provisioned with this blueprint. And then from the central place I can say, all right, here is what my production clusters should look like. Right? Here are the secrets that should be available. Here are the access control rules that need to be set. And so you find the right balance that way, right? You can enforce your governance standards while at the same time giving developers their individual clusters that development their staging of production clusters. >>And here's the options and what is an edible option and what is not. Right. Yeah. So it seems to me as if I, I mentioned this earlier, if I think about digital business, it's the opportunity to not only turn process, we're increasingly digitized process, but the real promise also is to then find ways of bringing these things together, integrate the business in response to new opportunities or new, uh, competitive factors or regulatory factors, whatever else it might be, and literally reconfigure the business quickly. That has to be more difficult if we have a wide array of, of governance models and operational principles. Trolley is, you think about customer success, uh, what does it mean for the future to be able to foster innovation with governance so that the whole thing can come together when it needs to come together? >>Well, I think that we need to move to governing again, as I said earlier, governing >>what not. How uh, >>I believe that, uh, you know, teams should be, should be making certain promises and there's a whole idea of the theory that's out there. A guy named Mark Burgess who is, you know, well known in certain certain infrastructure as code circles. So what are the promises that the team makes within the larger construct of the team of teams and is that team being accountable to those promises? And I think this is the basis of some of the new operating models we're seeing like Holacracy and teal. I think we're in very early days of looking at this. But you know, yeah, you will be held accountable for you know, objectives and key results. But how you get there, you have more degrees of freedom and yet at an infrastructure level, this is also bounded by the fact that if this is a solved problem, if this is not interesting to the business, you shouldn't be burning brain power on solving it. You know, and maybe it was interesting, you know, a couple of years ago and there was a need to explore new technologies, but really the effort should be spent solving the customer's problems. Charlie Betts, principal analyst at Forrester, Toby not co founder and CTO of D to IQ. Thanks very much for being on the cube. Thank you. Thank you, Peter, and thank you for joining us for another cube conversation. Once again, I'm Peter Burris. See you next time..