>>from around the globe. It's the Cube >>with digital coverage of VM World 2020 brought to you by VM Ware and its ecosystem partners. Hello and welcome back to the VM World 2020 Virtual coverage with the Cube Virtual I'm John for day. Volonte your hosts our 11th year covering VM. We'll get a great guest Greg Lavender, SBP and the CTO of VM. Where, uh, welcome to the Cube. Virtual for VM World 2020 Virtual Great. Thanks for coming on. >>Privileged to be here. Thank you. >>Um, really. You know, one of the things Dave and I were commenting with Pat on just in general start 11th year covering VM world. Uh, a little difference not face to face. But it's always been a technical conference. Always a lot of technical innovation. Project Monterey's out there. It's pretty nerdy, but it's a it's called the catnip of the future. Right? People get excited by it, right? So there's really ah lot of awareness to it because it kinda it smells like a systems overhaul. It smells like an operating system. Feels like a, you know, a lot of moving parts that are, quite frankly, what distributed computing geeks and software geeks love to hear about and to end distributed software intelligence with new kinds of hardware innovations from and video and whatnot. Where's that innovation coming from? Can you share your thoughts on this direction? >>Yeah, I think first I should say this isn't like, you know, something that just, you know, we decided to do, you know, six months ago, actually, in the office of C T 04 years ago, we actually had a project. Um, you know, future looking project to get our core hyper visor technology running on arm processors and that incubated in the office of the CTO for three years. And then last December, move the engineering team that had done that research and advanced development work in the office of the CTO over to our cloud platforms business unit, you know, and smart Knicks, you know, kind of converged with that. And so we were already, you know, well along the innovation path there, and it's really now about building the partnerships we have with smart nick vendors and driving this technology out to the benefit of our customers who don't want to leverage it. >>You get >>Greg, I want if you could clarify something for me on that. So Pat talked about Monterey, a complete re architect ing of the i o Stack. And he talked about it affecting in video. Uh, intel, melon, ox and Sandoz part of that when he talks about the Iot stack, you know, specifically what are we talking about there? >>So you know any any computing server in the data center, you know, in a cola facility or even even in the cloud, you know? Ah, large portion of the, you know CPU resource is, and even some memory resource is can get consumed by just processing. You know, the high volumes of Iot that's going out, you know, storage devices, you know, communicating between the different parts of multi tiered applications. And so there's there's a there's an overhead that that gets consumed in the course server CPU, even if its multi core multi socket. And so by offloading that a lot of that I owe work onto the arm core and taking advantage of the of the hardware offloads there in the smart Knicks, you can You can offload that processing and free up even as much as 30% of the CPU of a server, multi socket, multicourse server, and give that back to the application so that the application gets the benefit of that extra compute and memory resource is >>So what about a single sort of low cost flash tear to avoid the complexities of tearing? Is that part of the equation? >>Well, you know, you can you can, um you know, much storage now is network attached. And so you could if it's all flash storage, you know, using something like envy me fabric over over Ethernet, you can essentially build large scale storage networks more efficiently, you know more cheaply and take advantage of that offload processing, uh, to begin to reduce the Iot Leighton. See, that's required taxes. That network attached storage and not just storage. But, you know, other devices, you know, that you can use you could better network attached. So disaggregated architectures is term. >>Uh, is that a yes? Or is that a stay tuned? >>Yeah, Yeah, yeah, yeah, yes. I mean the storage. You know, more efficient use of different classes of storage and storage. Tearing is definitely a prime use case there. >>Yeah, great. Thank you. Thanks for that. John, >>How could people think about the edge now? Because one of the things that's in this end to end is the edge. Pat brought it up multi cloud and edge or two areas that are extending off cloud and hybrid. What should people think about the innovation equation around those things? Is that these offload techniques? What specifically in the systems architecture? Er, do you guys see as the key keys there? >>So so, you know, edges very diversified, heterogeneous place, Uh, in the architectures of multi cloud services. So one thing we do know is, you know, workload. I would like to say workload follows data, and a lot of the data will be analyzed, the process at the edge. So the more that you can accelerate that data processing at the edge and apply some machine learning referencing at the edge were almost certainly gonna have kubernetes everywhere, including the edge. So I think you're seeing a convergence of the hardware architectures er the kubernetes control plane and services and machine learning workloads. You know, traveling to the edge where the where the data is going to be processed and actions could be taken autonomously at the edge. So I think we're in this convergence point in the industry where all that comes together. >>How important do you >>do you see that? Okay, John, >>how important is the intelligence piece? Because again, the potatoes at the edge. How do you guys see the data architecture being built out there? >>Um, well, again, it's depending on the other. The thick edge of the thin edge. You know, you're gonna have different, different types of data, and and again, a lot of the the inference thing that could happen at the edges. Going to, I think, for mawr, you know, again to take action at the edges, opposed to calling home to a cloud, you know, to decide what to do. So, depending on, you know, the computational power and the problem with its video processing or monitoring, you know, sensors, Aaron, oil. Well, the kind of interesting that will happen at the edge will will be dependent on that data type and what kind of decisions you want to make. So I think data will be moving, you know, from the edge to the cloud for historical analytics and maybe transitional training mechanisms. But, you know, the five G is gonna play heavily into this is well right for the network connectivity. So we read This unique point is often occurs in the industry every few years of all these technology innovations converging to open up an entirely new platform in a new way of computing that happens at the edge, not just in your data center at the cloud. >>So, Greg, you did a fairly major stint at a large bank. What would something you mentioned? You know, like an oil rig. But what would something like these changes mean for a new industry like banking or financial? Uh, will it have an impact there and put on your customer hat for a minute and take us through that >>e? You know, eight machines, you know, branches, chaos. You know, there's all make banks always been a very distributed computing platform. And so, you know, people want to deliver mawr user experience, services, more video services. You know all these things at the edge to interact positively with the customer without using the people in the loop. And so the banking industry has already gone through the SD when, and I want transformation to deliver the bandwidth more capably to the edge. And I just think that they'll just now be able to deliver Mawr Edge services that happened can happen more autonomously at the edge is opposed that having the hairpin home run everything back to the data center. >>Awesome. Well, Pat talks about the modern platform, the modern companies. Greg, I wanna ask you because we're seeing with Kovar, there's to use cases, you know, the people who don't have a tailwind, Um, companies that are, you know, not doing well because there's no business that you have there modernizing their business while they have some downtime. Other ones have a tailwind. They have a modern app that that takes advantage, this covert situation. So that brings up this idea of what is a modern app look like? Because now, if you're talking about a distributed architecture, some of things you're mentioning around inference, data edge. People are starting to think about these modern naps, and they are changing the game for the business. Now you have vertical industries. You mentioned oil and gas, you got financial services. It used to be you had industry solution. It worked like that and was siloed. Now you have a little bit of a different architectures. If we believe that we're looking up, not down. Does it matter by industry? How should people think about a modern application, how they move faster? Can you share your insights into into some of this conceptual? What is a modern approach and does it doesn't matter by vertical or industry. >>Yes, I mean, certainly over the course of my career, I mean, there's there's a massive diversity of applications. And of course, you know, the explosion of mobile and edge computing is just another sort of sort of use cases that will put demands on the infrastructure in the architecture and the networking. So a modern, a modern app I mean, we historically built sort of these monolithic app. So we sort of built these sort of three tier apse with, you know, sort of the client side, the middleware side. The database back in is the system of record. I mean, this is even being more disaggregated in terms of, you know, the the consumer edges both not just web here, but mobile tear. And, you know, we'll see what emerges out of that. The one thing for sure that is that, um they're becoming less monolithic and mawr a conglomeration of sass and other services that are being brought together, whether it's from the cloud services or whether it's s, you know, SBS delivering, you know, bring your own software. Um, and they're becoming more distributed because people need operated higher degrees of scale. There's a limit to Virgil vertical scaling, so you have to go to horizontal scaling, which is what the cloud is really good at. So I think all these things were driving a whole new set of technologies like next generation AP gateways. Message Busses, service mesh. We're announcing Tanzi's service message being world. Um, you know, this is just allowing allowing that application to be disaggregated and then integrated with other APS assassin services that allow you to get faster time to market. So speed of delivery is everything. So modern C I. C d. Modern software, technology and ability to deploy and run that workload anywhere at the edge of the core in the data center in the cloud. >>So when you do in your re architecture like this, Greg, I mean you've seen over the course of history in our industry you've seen so many companies have hit a wall and in VM, whereas it's just amazing engineering culture. How are you able toe, you know, change the engine mid flight here and avoid like, serious technical debt. And I mean, it took, you know, you said started four years ago, but can you give us a peek inside? You know, that sort of transformation and how you're pulling that off? >>Well, I mean, we're providing were delivered the platform and, you know, spring Buddhas a key, you know, technology that's used widely across the industry already, which is what we've got is part of our pivotal acquisition. And so what we're just trying to do is just keep keep delivering the technology and the platform that allows people to go faster with quality security and safety and resiliency. That's what we do really well at VM ware. So I think you're seeing more people building these APS Cloud native is opposed to, you know, taking an existing legacy app In trying to re factor it, they might do what it called e think somebody's called two speed architectures. Take the user front, end the consumer front in, and put that cloud native in the cloud. But the back end system of record still runs in the private cloud in a highly resilient you know, backed up disaster recovered way. So you're having, I think, brand new cloud native APS we're seeing. And then you're seeing people very carefully because there's a cost to it of looking at How do I basically modernized the front end but maintain the reliability of the scalability of security and the reliability of that sort of system of record back in? So either way, it's it's winning for the companies because they could do faster delivery to their businesses and their clients and their partners. But you have to have the resiliency and reliability that were known for for running those mission critical workloads, >>right? So the scenario is that back end stays on premise on the last earnings call, I think, Pat said, or somebody said that, that I think I just they said on Prem or maybe the man hybrid 30 to 40% cheaper, then doing it in the cloud. I presume they were talking about those kind of back end systems that you know you don't wanna migrate. Can you add some color that again from your customer perspective That the economics? >>Yeah. You know, um, somebody asked me one time what's really a cloud. Greg and I said, automation, automation, automation you can take you can take You can take your current environments and highly automate the release. Lifecycle management develop more agile software delivery methods. And so therefore, you could you could get sort of cloud benefits, you know, from your existing applications by just highly optimizing them and, you know, on the cost of goods and services. And then again, the hybrid cloud model just gives customers more choice, which is okay. I want to reduce the number of data centers I have, but I need to maintain reliability, scalability, etcetera. Take advantage of, you know, the hybrid cloud that we offer. But you'll still run things. Cloud natives. I think you're seeing this true multi cloud technology and paradigm, you know, grow out as people have these choices. And then the question is okay. If you have those choices, how do you maintain security? How do you maintain reliability? How do you maintain up time yet be able to move quickly. And so I think there's different speeds in which those platforms will evolve. And our goal is to give you the ability to basically make those choices and and optimize for economics as well as technical. You know, capability. >>Great. I want to ask you a question with Cove it we're seeing and we've been reporting the Cube virtual evolve because we used to be it at events, but we're not there anymore. But the as everyone has realized with cove it it's exposed some projects that you might not want to double down on or highlighted some gaps in architecture. Er, I mean, certainly who would have forecast of the disruption of 100% work from home VP and provisioning to access and access management security, and it really is exposed. What kind of who's where in the journey, Right in digital transformation. So I gotta ask you, what's the most important story or thing to pay attention, Thio as the smart money and smart customers go, Hey, you know what? I'm gonna double down on that. I'm gonna kill that project or sunset. That or I'm not gonna re factor that I'm gonna contain Arise it and there's probably there's a lot of that going on. In our conversations with customers, they're like it's pretty obvious. It's critical path. It's like we stay in business. We build a modern app, but I'm doubling down. I'm transitioning. It's a whole nother ballgame. What >>is >>the most important thing that you see that people should pay attention to around maintaining an innovation and coming out on the other side? >>Yeah, well, I think I think it just generally goes to the whole thesis of software defined. I mean, you know the idea of taking an appliance physical, You know, you have to order the hardware, get it on your loading dock, install in your data center. You know, go configure it, mapping into the rest of your environment. You know, whereas or you could just spend up new, softer instances of load balancers, firewalls, etcetera. So I think you know what's What's really helped in the covert era is the maturity of software to find everything. Compute storage, networking. Lan really allowed customers and many of our customers toe, you know, rapidly make that pivot. And so you know what? It's the you know, the workspace, the remote workspace. You gotta secure it. That's a key part of it, and you've got to give it. You know, you gotta have the scalability back in your data centers or, if you don't have it, be able to run those virtual desktops you know, in the cloud. And I think so. This ability again to take your current environment and, more importantly, your operating model, which, you know the technology could be agile and fast. But if you're operating models not agile, you know you can't executed Well, One of the best comments I heard from a customer CEO was, you know, for six months we debated, you know, the virtual networking architecture and how to deploy the virtual network. And, you know, when covet hit. We made the decision that did it all in one week. So the question the CEO asked now is like Well, why do we Why do we have to operate in that six month model going forward? Let's operate in the one week model going forward. E. I think that that z yeah, that's e think that's the big That's a big inflection point is the operating model has to be agile. We got all kinds of agile technology and choices I mentioned it's like, How do you make your organization agile to take advantage of those technological offerings? That's really what I've been doing the last six months, helping our customers achieve. >>I think that's a key point worth calling out and doubling down on day because, you know, whether you talk about our q Q virtual, our operating model has changed and we're doing new things. But it's not bad. It's actually beneficial. We could talk to more people. This idea of virtual ization. I mean pun intended virtual izing workforces face to face interactions air now remote. This is a software defined operating business. This is the rial innovation. I think this is the exposure. As companies wake up and going. Why didn't we do that before? Reminds me of the old mainframe days. Days? You know, why do we have that mainframe? Because they're still clutching and grabbing onto it. They got a transition. So this is the new the new reality. >>We were joking earlier that you know it ain't broke, don't fix it. And all of a sudden Covic broke everything. And so you know, virtualization becomes a fundamental component of of of how you respond. But and I wonder if Greg you could talk about the security. Peace? How how that fits in. You know everybody you know, the bromide, of course, is security can't be a bolt on. It's gotta be designed in from the start, Pat Gelsinger said years ago in the Cube. Security is a do over. You guys have purchased many different security components you've built in. Security comes. So how should we think about? And how are you thinking about designing insecurity across that entire stack without really bolting in, You know, pieces, whether it's carbon, carbon, black or other acquisitions that you've made? >>Yeah, I mean, I think that's that's the key. Inflection point we're in is an industry. I mean, getting back to my banking experience, I was responsible for cybersecurity, engineering the platforms that we engineered and deployed across the bank globally. And the challenge, the challenge. You know, that's I had, you know, 150 plus security products, and you go to bed at night wondering what? Which one did I forget to deploy or what did I get that gap? Do you think you think you're safe by the sheer number, but when you really boil down to it is like, you know, because you have to sort of like both all this stuff together to create a secure environment, you know, on a global level. And so really, our philosophy of VM where is Okay? Well, let's kind of break that model. That's what we call it intrinsic security, which is just, you know, we have the hyper visor. If you're running, the hyper visor is running on most of the service in your data center. If we have your if you have our network virtualization, we see all the traffic going between all those hyper visors and out to the cloud as well hybrid cloud or public cloud with our NSX technology. And then, you know, then you sort of bring into that the load balancers and the software to find firewalls. And pretty soon you have realized Okay, look, we have we have most of the estate. Therefore we could see everything and bring some intelligent machine learning to that and get proactive as opposed to reactive. Because our whole model now is we. All this technology and some alert pops and we get reactive. How about proactively telling me that something nasty is going on. >>I need to ask you a >>question. May be remediated. Sorry, John. It may be remediated at some point anyway. Bring in some machine intelligence tow. So instead of like you said, getting an alert actually tells me what what happened and how it was fixed, you know? Or at least recommending what I should dio, right? >>Yeah. I mean, part of the problem in the historic architectures is it was all these little silos. You know, every business unit had its own sort of technology. And Aziz, you make things virtualized. You you sort of do the virtual networking. The virtual stories of virtual compute all the software. You know, all of a sudden you have you have a different platform, you have lots of standardization. Therefore you don't have your operating model simplifies right and amount of and then it's about just collecting all the data and then making sense of the data. So you're not overwhelming the human's capacity to respond to it. And so I think that's really the fundamental thing we're all trying to get to. But the surface area is enlarged outside the data centers we've discussed out to the edge, whatever the edges, you know, into the cloud hybrid or public. So now you've got this big surface area where you've gotta have all that telemetry and all that visibility again, Back to getting proactive. So you got to do it in Band is opposed out of band. >>Great. I want to ask you a question on cyber security. We have an event on October 4th, the virtual event that Cuba is hosting with Cal Poly around this space and cybersecurity, symposiums, intersection of space and cyber. I noticed VM Ware recently announced last month that the United States Space Force has committed to the Tan Xue platform for for Continuous Dev ops operation for agility. I interviewed Lieutenant General John Thompson, Space Force, and we talked about that. He said quote, it's hard to do break fix in space. Uh, illustrating, really? Just can't send someone to swap out something in space. Not yet, at least. So they're looking at software defined as a key operating reality. Okay, so again, talk about the edge of space Isas edges. You're gonna get it. Need to be completely mad and talk about payloads and data. This >>is kind >>of interesting data point because you have security issues because space is gonna be contested and congested as an edge device. So it's actually the government's interested in that. But fundamentally, the death hops problem that you're you guys are involved in This >>is a >>reality. It's kind of connects this reality idea of operating models based in reality have to be software. What's >>your name? Yeah. I mean, I think the term we use now is def sec ops because you can't just do Dev ops. You have to have the security component in there, So, uh, yeah, the interesting. You know, like, there's a lot of interesting things happen just in fundamental networking, right? I mean, you know, the StarLink, you know, satellites at Testa. His launched Elon musk has launched and, you know, bringing sort of, you know, higher band with laurel agency to those. Yeah, we'll call it near space the and then again, just opens up all new opportunities for what we can dio. And so, Yeah, I think that's the software that the whole the whole saw for development ecosystem again, back to this idea. I think of three things. You gotta have speed. You gotta have scale and you gotta have security. And so that's really the emerging platform, whether it's a terrestrial or in near space, Uh, that's giving us the opportunity, Thio Do new architectures create service measures of services, some terrestrial, some some you know, far remote. And as you bring these new application architectures and system platform architectures together with all the underlying hardware and networking innovations that are occurring, you mentioned flash. But even getting into pmm persistent memory, right? So this this is so much happening that is converging. What's exciting to me about being a TV? Where is the CTO and we partner with all the hardware vendors? We partner with all the system providers, like in video and others. You know, the smart nick vendors. And then we get to come up with software architectures that sort of bring that together holistically and give people a platform. We can run your workloads to get work done wherever you need to land those workloads. And that's really the excitement about >>the candy store. And yet you've got problems hard problems to work on to solve. I mean, this really brings the whole project moderate, full circle because we think about space and networks and all these things you're talking about, You need to have smart everything. I mean, isn't that software? It's a complete tie into the Monterey. >>Yeah, yeah, yeah, Exactly. You're right. It's not just it's not just connecting everything and pushing data around its than having the intelligence to do it efficiently, economically, insecurely. And that's you know. So I see that you don't want to over hype machine learning. I did not to use the term AI, but use the machine learning technologies, you know, properly trained with the proper data sets, you know, and then the proper algorithms. You know that you can then a employee, you know, at the edge small edge, thick edge, you know, in the data center at the cloud is really Then you give the visibility so that we get to that proactive world I was talking about. >>Yeah, great stuff, Greg. Great insight, great conversation. Looking forward to talking mawr Tech with you. Obviously you are in the right spot was in the center of all the action across the board final point. If you could just close it out for us. What is the most important story at VM World 2020 this year. >>Um, well, I think you know, I like to say that I have the best job. I think you know that I've had in my career. I've had some great ones is you know, we get to be disruptive innovators, and we have a culture of perpetual innovation and really being world for us, Aly employees and all the people that work together to put it together is we get to showcase. You know, some of that obviously have more up our sleeves for the future. But, you know, being world is are, you know, coming coming out out show of the latest set of innovations and technologies. So there's going to be so much I have, ah, vision and innovation. Keynote kickoff, right. Do some lightning demos. And actually, I talk about work we're doing in sustainability, and we're putting a micro grid on our campus in Palo Alto and partnership with City of Palo Alto so that when the wildfires come through or there is power outages, you know we're in oasis of power generating capacity with our solar in our batteries. And so the city of Palo Alto could take their emergency command vehicles and plug into our batteries when the power is out in Palo Alto and operate city services and city emergency services. So we're not just innovating, you know, in cortex we're innovating to become a more, you know, sustainable company and provide sustainable, you know, carbon neutral technology for our customers to adopt. And I think that's an area we wanna talk about me. We talk about it next time, but I think you know our innovations. We're gonna basically help change the world with regard to climate as well. >>Let's definitely do that. Let's follow up for another in depth conversation on the societal impact. Of course, VM Ware VM Ware's VM World's 2020 is virtual is a ton of sessions. There's a Cloud City portion. Check out the 60 solution demos. Of course, they ask the expert, Greg, you're in there with Joe Beta Raghu, all the experts, um, engage and check it out. Thank you so much for the insight here on the Cube. Virtual. Thanks for coming on. >>Appreciate the opportunity. Great conversation and good questions. >>Great stuff. Thank you very much. Innovation that vm where it's the heart of their missions always has been, but they're doing well on the business side, Dave. Okay. The cube coverage. They're not there in person. Virtual. I'm John for day. Volonte. Thanks for watching.

[Music] [Applause] hi I'm Peter Burris and welcome again to another cube conversation from our wonderful studios here in Palo Alto California great conversation today branching out into the world of data governance a lot of things going on in the industry around data and what does it mean for digital business and how do we treat data increasingly as an asset and that obviously raises a lot of questions about how we govern those assets improve their value share them appropriately at the same time privatizing and make sure that they are corrupted and to have this conversation we've got two great guests first off we've got Kelly O'Neil who's the CEO of first San Francisco partners is an information management consultancy here in the Bay Area and Saatchi on sangani welcome back to the cube CEO of relation welcome so let's get started I kind of said in the preamble that this notion of data governance becomes especially acute especially important because we're now trying to treat data as an asset so we're not governing the resources to manage data we're actually trying to govern data itself utilizing resources so Sachin why don't we start with you what does data governance mean from a tool and process standpoint and then Kelly on rescue and let's go deeper into that process part >> yeah I mean I think so there's lots of different definitions of data governance that a wide variety of experts have put out and I'm not sure that I want to sort of put a new definition in the debate very generically it's a set of processes that institutions use to manage the data that's at their disposal and if you think about that generically in terms of where the problem is broadly stated how do I manage my information and in the consumption and the production and the storage of that information you know that is a super hard problem to deal with when you have you know hundreds of thousands of data sources potentially millions of different data sets and thousands of people who are constantly consuming that information and limited resources and so the process of data governance now in a world to your point where every business is trying to become a digital business and where the monetization of data is a huge part of that business is the fundamental problem right how do we have people discover the data how do we have people understand the data that they're seeing how do we have people trust the data that they're seeing that is the consort of province of data governance and that is what people are coming to realize but >> we do have tooling now that is specifically being built including elation which is a great catalog for performing some of these or to facilitate some of these governance activities so there's a enough of a standard set of definitions that we actually can put tooling in place which means now we can really liberate the power and the talent of people to appropriately govern data and use data so Kelly what are you doing with your clients to help them take the tools for data governance and turn it into ideally a strategic capability that really drives the digital business forward yeah >> absolutely so as a services organization we really focus on ensuring that the people in the process are in place so that they can take advantage of the technology right so you've got accountability around who has who's responsible to ensure the data is of a certain sort of quality or a certain sort of standard as well as who has the ability to access that data and use that data and I think one of the things that sahteen brought up is there's just this onslaught of data that's coming in so if you think about that as a construct it's entirely overwhelming there's too much data to be able to say this person owns this data field this person defines that data field it has to be much more organic it has to be much more shared and tools much more communal yeah and so it really is this concept of how do we have a certain level of trust in the data and what does trust mean to the organization to take advantage of that data and to use it as an asset and to use it in business context and so our services help organizations to see what that means to them to right-size that investment in the sense of how much effort do we put towards this and then also how do we make sure that those tools are used that they're adopted and that they're embedded into work processes that it's not a standalone repository that never gets used >> you know we had Aaron Cal bond not too long ago to talk about trust check and I know that's one of the things that's bringing you together is this notion of a communal approach to putting to imbuing data with trust so let's talk a bit about trust check and in particular how your companies are working together to accelerate the prop the processes that you so accurately described what starts at 10 when we start with you let's trust checking and what does it mean for you yeah so trust check is a very simple it's a very simple capability although very complicated to implement the idea behind trust check is that as and when somebody's communing consuming data whether that's in a Salesforce dashboard or in a tableau report or conversely even inside of elation that immediately as they're consuming that information they're presented with context around that data talking about the appropriateness of that data for the use that they particularly have now that could be about timeliness of the data that could be about the availability of the data that could be about the quality of the data that could be about you know the privacy regulations or the security surrounding that data there are lots of reasons why one might not trust the data but often that information is off to the side right and often that information is in a place where the consumer of the data has no awareness that the policy even exists much less where to go get it that information and so what trust check is saying look this notion of governance has to actually be actionable and immediate and available in order for it to be valuable to the person that's using the information yeah and you might say that also that it might be trusted in this context but not in other context as well so how does that inform well how does that facilitate how does that accelerate implementing these processes to make sure that communities of data in an evidence-based world are better able to apply data use data and share information about that data with each other yeah absolutely so it provides a number one just automation right so fundamentally that's a value add it means that it's more available it's more shared it's faster and that can make the governance organization more relevant to the business so that the data is actually used in a more appropriate and higher-value way so first things Automation and then the second thing is that as we start to automate there's this concept of kind of learning and expanding and so being able to leverage a tool within a services practice and phonology it means that we can kind of start within one area and to leverage that learning and extend and extend and extend because fundamentally data is pervasive right it's everywhere and which makes governance really intimidating and hard so that idea of focusing learning doing something well and being agile right and growing over time a tool really helps you to do that because it is a place where people can get focused for that learning and then repeat rinse and repeat rinse and repeat so it many respects it is a reflection of manifestation of some of these good processes absolutely the you guys obviously have an enormous amount of knowledge about data Government's about the tool infer data to government's about where this all goes but ultimately a lot of your customers are still very much in the formative stages of putting this in place so how are other than just having them license elations toolkit how are you coming together to put in place services or training or something else to help diffuse your knowledge I just want to come back to one point that you mentioned is I think I think there's been a shift in the tooling market okay so I wouldn't say that the tooling has not that there's never been any tooling to deal with the problem of data governance in fact I think there's been lots of tooling that hasn't worked particularly very well so so let me put some context on that so when I say tooling as I said kind of upfront to my mind it's tooling for the resources that handle the data not tooling for the data yeah but keep going if I'm wrong I want to hear well know I think even tooling for the resources that handle the data has largely been the province of either there is a category of software that one would traditionally described in the realm of data stewardship and data governance and broadly speaking it allows you to create forms and to administer workflows with those forms right so you know there and so that is a highly unauthorized and so what a traditional you know governance implementing regime might include would be the development of policies and the enactment of those policies through a set of people who have to vary manually check the data at their disposal it is generally speaking disconnected from the data right when you have small sets of data when you have limited quantities of data that could be a perfectly fine solution when you have a very small set of policies that you need to interact or interact with because you have to have a set of goals that are maybe regulatory in nature that is an okay thing to go do when you have petabytes of data across hundreds of thousands of data sets it's an impossible thing to go do right and so I think that that sort of inundation that Kelly was referring to is is is you know born out of this massive volume of data coming up where the traditional methods just just don't work right so your tanks are you talking about such an essentially that were that we're adding that metadata directly to the data itself and creating trusted objects that the organization can use and apply as assets wherever so that is exactly a solution and the analogy that I think will then inform you know most of the people who are sort of listening us today to us today would be the sort of shift from Yahoo to Google right so if you think about Yahoo Yahoo relied upon every single webmaster tagging every single webpage to make sure that the search engine knew which webpages to go look up right that required a whole bunch of trust in your webmasters first of all some of whom were bad actors right you may not have those in the stewardship regime regime inside of a enterprise but you could right people have their own perspectives and it also required for people to have enough knowledge to tag things right so you'd have to know what to tag and that a tag would have to be right for anybody who's developed a folder system you know that those folder systems are constantly changing right and so then Google comes along and says look if we just watch what people are doing with this information and we know what people are linking to then we can say hey what what's more valuable what's more useful by watching the behaviors right and I think that's the sort of shift of a Bottoms Up approach which is different from sort of that top-down declarative approach that's come in the technology for governance and fortunately and and I think that's what people have to understand which is that the problems always been there but what's happened is the volumes and the relevance and the timely the information have just been so critical that now we have to change the way we do things and not what we're working together on it's mercury it's it's it's it has scale issues but also the annoying technology has gotten to the point where we can actually do more automated discovery about how people are using things which means you have to change the process and the people great so let's let's come back to that question what are you guys doing together to ensure that you can in fact diffuse this knowledge and diffuse these insights into organizations faster so they can pick up on some of these changes better yeah so so for San Francisco is taking some of our methodologies and ensuring that they are right size and fit for the elation suite of products especially the trust checks suite of products and so what we're starting with is the data acquisition process and that's important because the supply chain for data is what has become inordinately complex it's no longer primarily internally created data most data is actually acquired and so if we start with that ingestion process and the data acquisition process that's a huge value both to the customers that are using it as well as to the mutual organizations right so right focusing on that as a as a case and then we'll move on to the concept of information stewardship itself so stewardship across the supply chain not just the data acquisition supply chain so we are adapting our methodologies to be specific and unique to alation to help their existing customer base and obviously potentially new customers together yeah so an a great example of that I was just talking to a chief dead officer of a very large financial institution in North America you know this individual was contending with the problem of making good data available to there and you know and business audience for analytical purposes right to solve exactly this problem he said we acquire companies all the time we're acquiring companies constantly and we're getting all of this data in and I have to figure out what this data is and do I already have this data in-house do I have systems that store this sort of data do I have systems that duplicate the data but incorrectly and are there multiple of these sets of data inside the company that I'm acquiring because they've got data duplication just like we do and how do we figure all of that out right so this would be a perfect example where the data acquisition problem is critical to solve in the process of being able to create available useful government data right and so this would be a perfect example for you know the two of our companies to be able to work together because we don't speak to the implementation and the process we speak to the technical capability of simply providing the inventory so that somebody can then figure out what to do with that information but there are practices that are probably going to do better or will generate greater value out of the elation toolkit than others would absolutely yeah and so in many respects we're looking into companies like yours to help correct or define what those practices are defuse them more broadly through C package consulting and through really good partnership that you guys have been working on yeah because I mean you know you know I mean I you know I think Larry Ellison is a controversial character right right but you know I'll quietly say that I worked at Oracle at one point in time what one of the things that Larry one of the things that Larry said is you know people when they buy software are constantly asking the question of how do I figure out how to take my existing business process and fit it on top of the software that exists out there and he's like no that's exactly wrong what people should be doing is figuring out what should my business process be given the capability that I've got right and so we now have a new capability and we're we're enabling people to have more or less super powers relative to what they would have had to do by hunting and pecking through every data set and tagging it manually right and what you know Kellyanne for San Francisco are bringing to the table is the ability to have a new process that would allow them to do that at scale and faster so that's where we see per sighted excellence so in a date of first world data governance becomes more important to thought leaders helping to make that happen Saachi and sigani CEO of elation Kelly O'Neil for San Francisco partners thanks very much for being on the queue thank you Peter thank you and once again this has been a cute conversation from our Palo Alto studios thank you very much for watching until next time [Music] you