>>Welcome back to the cubes, continuous coverage of AWS storage day. We're in beautiful downtown Seattle in the great Northwest. My name is Dave Vellante and we're going to talk about file systems. File systems are really tricky and making those file systems elastic is even harder. They've got a long history of serving a variety of use cases as with me as Duncan Lennox. Who's the general manager of Amazon elastic file system. Dunkin. Good to see you again, Dave. Good to see you. So tell me more around the specifically, uh, Amazon's elastic file system EFS you, you know, broad file portfolio, but, but let's narrow in on that. What do we need to know? >>Yeah, well, Amazon elastic file system or EFS as we call it is our simple serverless set and forget elastic file system service. So what we mean by that is we deliver something that's extremely simple for customers to use. There's not a lot of knobs and levers. They need to turn or pull to make it work or manage it on an ongoing basis. The serverless part of it is there's absolutely no infrastructure for customers to manage. We handled that entirely for them. The elastic part then is the file system automatically grows and shrinks as they add and delete data. So they never have to provision storage or risk running out of storage and they pay only for the storage they're actually using. >>What are the sort of use cases and workloads that you see EFS supporting? >>Yeah. Yeah. It has to support a broad set of customer workloads. So it's everything from, you know, serial, highly latency, sensitive applications that customers might be running on-prem today and want to move to the AWS cloud up to massively parallel scale-out workloads that they have as well. >>So. Okay. Are there any industry patterns that you see around that? Are there other industries that sort of lean in more or is it more across the board? We >>See it across the board, although I'd have to say that we see a lot of adoption within compliance and regulated industries. And a lot of that is because of not only our simplicity, but the high levels of availability and durability that we bring to the file system as well. The data is designed for 11 nines of durability. So essentially you don't need to be worrying about your anything happening into your data. And it's a regional service meaning that your file system is available from all availability zones in a particular region for high availability. >>So as part of storage data, we, we saw some, some new tiering announcements. W w w what can you tell us about those >>Super excited to be announcing EFS intelligent tiering? And this is a capability that we're bringing to EFS that allows customers to automatically get the best of both worlds and get cost optimization for their workloads and how it works is the customer can select, uh, using our lifecycle management capability, a policy for how long they want their data to remain active in one of our active storage classes, seven days, for example, or 30 days. And what we do is we automatically monitor every access to every file they have. And if we see no access to a file for their policy period, like seven days or 30 days, we automatically and transparently move that file to one of our cost optimized, optimized storage classes. So they can save up to 92% on their storage costs. Um, one of the really cool things about intelligent tiering then is if that data ever becomes active again and their workload or their application, or their users need to access it, it's automatically moved back to a performance optimized storage class, and this is all completely transparent to their applications and users. >>So, so how, how does that work? Are you using some kind of machine intelligence to sort of monitor things and just learn over time? And like, what if I policy, what if I don't get it quite right? Or maybe I have some quarter end or maybe twice a year, you know, I need access to that. Can you, can the system help me figure >>That out? Yeah. The beauty of it is you don't need to know how your application or workload is accessing the file system or worry about those access patterns changing. So we'll take care of monitoring every access to every file and move the file either to the cost optimized storage class or back to the performance optimized class as needed by your application. >>And then optimized storage classes is again, selected by the system. I don't have to >>It that's right. It's completely transparent. So we will take care of that for you. So you'll set the policy by which you want active data to be moved to the infrequent access cost optimized storage class, like 30 or seven days. And then you can set a policy that says if that data is ever touched again, to move it back to the performance optimized storage class. So that's then all happened automatically by the service on our side. You don't need to do anything >>It's, it's it's serverless, which means what I don't have to provision any, any compute infrastructure. >>That's right. What you get is an end point, the ability to Mount your file system using NFS, or you can also manage your file system from any of our compute services in AWS. So not only directly on an instance, but also from our serverless compute models like AWS Lambda and far gays, and from our container services like ECS and EKS, and all of the infrastructure is completely managed by us. You don't see it, you don't need to worry about it. We scale it automatically for you. >>What was the catalyst for all this? I mean, you know, you got to tell me it's customers, but maybe you could give me some, some insight and add some, some color. Like, what would you decoded sort of what the customers were saying? Did you get inputs from a lot of different places, you know, and you had to put that together and shape it. Uh, tell us, uh, take us inside that sort of how you came to where you are >>Today. Well, you know, I guess at the end of the day, when you think about storage and particularly file system storage, customers always want more performance and they want lower costs. So we're constantly optimizing on both of those dimensions. How can we find a way to deliver more value and lower cost to customers, but also meet the performance needs that their workloads have. And what we found in talking to customers, particularly the customers that EFS targets, they are application administrators, their dev ops practitioners, their data scientists, they have a job they want to do. They're not typically storage specialists. They don't want to have know or learn a lot about the bowels of storage architecture, and how to optimize for what their applications need. They want to focus on solving the business problems. They're focused on whatever those are >>You meaning, for instance. So you took tiering is obvious. You're tiering to lower cost storage, serverless. I'm not provisioning, you know, servers, myself, the system I'm just paying for what I use. The elasticity is a factor. So I'm not having to over provision. And I think I'm hearing, I don't have to spend my time turning knobs. You've talked about that before, because I don't know how much time is spent, you know, tuning systems, but it's gotta be at least 15 to 20% of the storage admins time. You're eliminating that as well. Is that what you mean by sort of cost optimum? Absolutely. >>So we're, we're providing the scale of capacity of performance that customer applications need as they needed without the customer needing to know exactly how to configure the service, to get what they need. We're dealing with changing workloads and changing access patterns. And we're optimizing their storage costs. As at the same time, >>When you guys step back, you get to the whiteboard out, say, okay, what's the north star that you're working because you know, you set the north star. You don't want to keep revisiting that, right? This is we're moving in this direction. How do we get there might change, but what's your north star? Where do you see the future? >>Yeah, it's really all about delivering simple file system storage that just works. And that sounds really easy, but there's a lot of nuance and complexity behind it, but customers don't want to have to worry about how it works. They just need it to work. And we, our goal is to deliver that for a super broad cross section of applications so that customers don't need to worry about how they performance tune or how they cost optimize. We deliver that value for them. >>Yeah. So I'm going to actually follow up on that because I feel like, you know, when you listen to Werner Vogels talk, he gives takes you inside. It's a plumbing sometimes. So what is the, what is that because you're right. That it, it sounds simple, but it's not. And as I said up front file systems, getting that right is really, really challenging. So technically what's the challenges, is it doing this at scale? And, and, and, and, and, and having some, a consistent experience for customers, there's >>Always a challenge to doing what we do at scale. I mean, the elasticity is something that we provide to our customers, but ultimately we have to take their data as bits and put them into Adams at some point. So we're managing infrastructure on the backend to support that. And we also have to do that in a way that delivers something that's cost-effective for customers. So there's a balance and a natural tension there between things like elasticity and simplicity, performance, cost, availability, and durability, and getting that balance right. And being able to cover the maximum cross section of all those things. So for the widest set of workloads, we see that as our job and we're delivering value, and we're doing that >>For our customers. Then of course, it was a big part of that. And of course, when we talk about, you know, the taking away the, the need for tuning, but, but you got to get it right. I mean, you, you, you can't, you can't optimize for every single use case. Right. But you can give great granularity to allow those use cases to be supported. And that seems to be sort of the balancing act that you guys so >>Well, absolutely. It's focused on being a general purpose file system. That's going to work for a broad cross section of, of applications and workloads. >>Right. Right. And that's, that's what customers want. You know, generally speaking, you go after that, that metal Dunkin, I'll give you the last word. >>I just encourage people to come and try out EFS it's as simple as a single click in our console to create a file system and get started. So come give it a, try the >>Button Duncan. Thanks so much for coming back to the cube. It's great to see you again. Thanks, Dave. All right. And keep it right there for more great content from AWS storage day from Seattle.

>>From around the globe, but it's the cube presenting active DQ, intelligent automation for data quality brought to you by IO Tahoe. >>Now we're going to look at the role automation plays in mobilizing your data on snowflake. Let's welcome. And Duncan Turnbull who's partner sales engineer at snowflake and AIG Vihara is back CEO of IO. Tahoe is going to share his insight. Gentlemen. Welcome. >>Thank you, David. Good to have you back. Yeah, it's great to have you back >>A J uh, and it's really good to CIO Tao expanding the ecosystem so important. Um, now of course bringing snowflake and it looks like you're really starting to build momentum. I mean, there's progress that we've seen every month, month by month, over the past 12, 14 months, your seed investors, they gotta be happy. >>They are all that happy. And then I can see that we run into a nice phase of expansion here and new customers signing up. And now you're ready to go out and raise that next round of funding. I think, um, maybe think of a slight snowflake five years ago. So we're definitely on track with that. A lot of interest from investors and, um, we're right now trying to focus in on those investors that can partner with us, understand AI data and, and automation. >>So personally, I mean, you've managed a number of early stage VC funds. I think four of them, uh, you've taken several comp, uh, software companies through many funding rounds and growth and all the way to exit. So, you know how it works, you have to get product market fit, you know, you gotta make sure you get your KPIs, right. And you gotta hire the right salespeople, but, but what's different this time around, >>Uh, well, you know, the fundamentals that you mentioned though, those are never change. And, um, what we can say, what I can say that's different, that's shifted, uh, this time around is three things. One in that they used to be this kind of choice of, do we go open source or do we go proprietary? Um, now that has turned into, um, a nice hybrid model where we've really keyed into, um, you know, red hat doing something similar with Santos. And the idea here is that there is a core capability of technology that independence a platform, but it's the ability to then build an ecosystem around that made a pervade community. And that community may include customers, uh, technology partners, other tech vendors, and enabling the platform adoption so that all of those folks in that community can build and contribute, um, while still maintaining the core architecture and platform integrity, uh, at the core of it. >>And that's one thing that's changed was fitting a lot of that type of software company, um, emerge into that model, which is different from five years ago. Um, and then leveraging the cloud, um, every cloud snowflake cloud being one of them here in order to make use of what customers, uh, and customers and enterprise software are moving towards. Uh, every CIO is now in some configuration of a hybrid. Um, it is state whether those cloud multi-cloud on prem. That's just the reality. The other piece is in dealing with the CIO is legacy. So the past 15, 20 years they've purchased many different platforms, technologies, and some of those are still established and still, how do you, um, enable that CIO to make purchase while still preserving and in some cases building on and extending the, the legacy, um, material technology. So they've invested their people's time and training and financial investment into solving a problem, customer pain point, uh, with technology, but, uh, never goes out of fashion >>That never changes. You have to focus like a laser on that. And of course, uh, speaking of companies who are focused on solving problems, don't can turn bill from snowflake. You guys have really done a great job and really brilliantly addressing pain points, particularly around data warehousing, simplified that you're providing this new capability around data sharing, uh, really quite amazing. Um, Dunkin AAJ talks about data quality and customer pain points, uh, in, in enterprise. It, why is data quality been such a problem historically? >>Oh, sorry. One of the biggest challenges that's really affected by it in the past is that because to address everyone's need for using data, they've evolved all these kinds of different places to store all these different silos or data marts or all this kind of clarification of places where data lives and all of those end up with slightly different schedules to bringing data in and out. They end up with slightly different rules for transforming that data and formatting it and getting it ready and slightly different quality checks for making use of it. And this then becomes like a big problem in that these different teams are then going to have slightly different or even radically different ounces to the same kinds of questions, which makes it very hard for teams to work together, uh, on their different data problems that exist inside the business, depending on which of these silos they end up looking at and what you can do. If you have a single kind of scalable system for putting all of your data into it, you can kind of sidestep along to this complexity and you can address the data quality issues in a, in a single and a single way. >>Now, of course, we're seeing this huge trend in the market towards robotic process automation, RPA, that adoption is accelerating. Uh, you see, in UI paths, I IPO, you know, 35 plus billion dollars, uh, valuation, you know, snowflake like numbers, nice cops there for sure. Uh, agent you've coined the phrase data RPA, what is that in simple terms? >>Yeah, I mean, it was born out of, uh, seeing how in our ecosystem concern community developers and customers, uh, general business users for wanting to adopt and deploy a tar hose technology. And we could see that, um, I mean, there's not monkeying out PA we're not trying to automate that piece, but wherever there is a process that was tied into some form of a manual overhead with handovers and so on. Um, that process is something that we were able to automate with, with our ties technology and, and the deployment of AI and machine learning technologies specifically to those data processes almost as a precursor to getting into financial automation that, um, that's really where we're seeing the momentum pick up, especially in the last six months. And we've kept it really simple with snowflake. We've kind of stepped back and said, well, you know, the resource that a snowflake can leverage here is, is the metadata. So how could we turn snowflake into that repository of being the data catalog? And by the way, if you're a CIO looking to purchase a data catalog tool stop, there's no need to, um, working with snowflake, we've enable that intelligence to be gathered automatically and to be put, to use within snowflake. So reducing that manual effort, and I'm putting that data to work. And, um, and that's where we've packaged this with, uh, AI machine learning specific to those data tasks. Um, and it made sense that's, what's resonated with, with our customers. >>You know, what's interesting here, just a quick aside, as you know, I've been watching snowflake now for awhile and, and you know, of course the, the competitors come out and maybe criticize why they don't have this feature. They don't have that feature. And it's snowflake seems to have an answer. And the answer oftentimes is, well, its ecosystem ecosystem is going to bring that because we have a platform that's so easy to work with though. So I'm interested Duncan in what kind of collaborations you are enabling with high quality data. And of course, you know, your data sharing capability. >>Yeah. So I think, uh, you know, the ability to work on, on datasets, isn't just limited to inside the business itself or even between different business units. And we were kind of discussing maybe with their silos. Therefore, when looking at this idea of collaboration, we have these where we want to be >>Able to exploit data to the greatest degree possible, but we need to maintain the security, the safety, the privacy, and governance of that data. It could be quite valuable. It could be quite personal depending on the application involved. One of these novel applications that we see between organizations of data sharing is this idea of data clean rooms. And these data clean rooms are safe, collaborative spaces, which allow multiple companies or even divisions inside a company where they have particular, uh, privacy requirements to bring two or more data sets together for analysis. But without having to actually share the whole unprotected data set with each other, and this lets you to, you know, when you do this inside of snowflake, you can collaborate using standard tool sets. You can use all of our SQL ecosystem. You can use all of the data science ecosystem that works with snowflake. >>You can use all of the BI ecosystem that works with snowflake, but you can do that in a way that keeps the confidentiality that needs to be presented inside the data intact. And you can only really do these kinds of, uh, collaborations, especially across organization, but even inside large enterprises, when you have good reliable data to work with, otherwise your analysis just isn't going to really work properly. A good example of this is one of our large gaming customers. Who's an advertiser. They were able to build targeting ads to acquire customers and measure the campaign impact in revenue, but they were able to keep their data safe and secure while doing that while working with advertising partners, uh, the business impact of that was they're able to get a lifted 20 to 25% in campaign effectiveness through better targeting and actually, uh, pull through into that of a reduction in customer acquisition costs because they just didn't have to spend as much on the forms of media that weren't working for them. >>So, ha I wonder, I mean, you know, with, with the way public policy shaping out, you know, obviously GDPR started it in the States, you know, California, consumer privacy act, and people are sort of taking the best of those. And, and, and there's a lot of differentiation, but what are you seeing just in terms of, you know, the government's really driving this, this move to privacy, >>Um, government public sector, we're seeing a huge wake up an activity and, uh, across the whole piece that, um, part of it has been data privacy. Um, the other part of it is being more joined up and more digital rather than paper or form based. Um, we've all got stories of waiting in line, holding a form, taking that form to the front of the line and handing it over a desk. Now government and public sector is really looking to transform their services into being online, to show self service. Um, and that whole shift is then driving the need to, um, emulate a lot of what the commercial sector is doing, um, to automate their processes and to unlock the data from silos to put through into those, uh, those processes. Um, and another thing I can say about this is they, the need for data quality is as a Dunkin mentions underpins all of these processes, government pharmaceuticals, utilities, banking, insurance, the ability for a chief marketing officer to drive a, a loyalty campaign. >>They, the ability for a CFO to reconcile accounts at the end of the month. So do a, a, uh, a quick, accurate financial close. Um, also the, the ability of a customer operations to make sure that the customer has the right details about themselves in the right, uh, application that they can sell. So from all of that is underpinned by data and is effective or not based on the quality of that data. So whilst we're mobilizing data to snowflake cloud, the ability to then drive analytics, prediction, business processes off that cloud, um, succeeds or fails on the quality of that data. >>I mean it, and, you know, I would say, I mean, it really is table stakes. If you don't trust the data, you're not gonna use the data. The problem is it always takes so long to get to the data quality. There's all these endless debates about it. So we've been doing a fair amount of work and thinking around this idea of decentralized data, data by its very nature is decentralized, but the fault domains of traditional big data is that everything is just monolithic and the organizations monolithic technology's monolithic, the roles are very, you know, hyper specialized. And so you're hearing a lot more these days about this notion of a data fabric or what calls a data mesh. Uh, and we've kind of been leaning in to that and the ability to, to connect various data capabilities, whether it's a data warehouse or a data hub or a data Lake that those assets are discoverable, they're shareable through API APIs and they're governed on a federated basis. And you're using now bringing in a machine intelligence to improve data quality. You know, I wonder Duncan, if you could talk a little bit about Snowflake's approach to this topic. >>Sure. So I'd say that, you know, making use of all of your data, is there a key kind of driver behind these ideas that they can mesh into the data fabrics? And the idea is that you want to bring together not just your kind of strategic data, but also your legacy data and everything that you have inside the enterprise. I think I'd also like to kind of expand upon what a lot of people view as all of the data. And I think that a lot of people kind of miss that there's this whole other world of data they could be having access to, which is things like data from their business partners, their customers, their suppliers, and even stuff that's more in the public domain, whether that's, you know, demographic data or geographic or all these kinds of other types of data sources. And what I'd say to some extent is that the data cloud really facilitates the ability to share and gain access to this both kind of between organizations inside organizations. >>And you don't have to, you know, make lots of copies of the data and kind of worry about the storage and this federated, um, you know, idea of governance and all these things that it's quite complex to kind of manage this. Uh, you know, the snowflake approach really enables you to share data with your ecosystem all the world, without any latency with full control over what's shared without having to introduce new complexities or having complex attractions with APIs or software integration. The simple approach that we provide allows a relentless focus on creating the right data product to meet the challenges facing your business today. >>So, Andrea, the key here is to don't get to talking about it in my mind. Anyway, my cake takeaway is to simplicity. If you can take the complexity out of the equation, we're going to get more adoption. It really is that simple. >>Yeah, absolutely. Do you think that that whole journey, maybe five, six years ago, the adoption of data lakes was, was a stepping stone. Uh, however, the Achilles heel there was, you know, the complexity that it shifted towards consuming that data from a data Lake where there were many, many sets of data, um, to, to be able to cure rate and to, um, to consume, uh, whereas actually, you know, the simplicity of being able to go to the data that you need to do your role, whether you're in tax compliance or in customer services is, is key. And, you know, listen for snowflake by auto. One thing we know for sure is that our customers are super small and they're very capable. They're they're data savvy and know, want to use whichever tool and embrace whichever, um, cloud platform that is gonna reduce the barriers to solving. What's complex about that data, simplifying that and using, um, good old fashioned SQL, um, to access data and to build products from it to exploit that data. So, um, simplicity is, is key to it to allow people to, to, to make use of that data. And CIO is recognize that >>So Duncan, the cloud obviously brought in this notion of dev ops, um, and new methodologies and things like agile that brought that's brought in the notion of data ops, which is a very hot topic right now. Um, basically dev ops applies to data about how D how does snowflake think about this? How do you facilitate that methodology? >>Yeah, sorry. I agree with you absolutely. That they drops takes these ideas of agile development of >>Agile delivery and of the kind of dev ops world that we've seen just rise and rise, and it applies them to the data pipeline, which is somewhere where it kind of traditionally hasn't happened. And it's the same kinds of messages as we see in the development world, it's about delivering faster development, having better repeatability and really getting towards that dream of the data-driven enterprise, you know, where you can answer people's data questions, they can make better business decisions. And we have some really great architectural advantages that allow us to do things like allow cloning of data sets without having to copy them, allows us to do things like time travel so we can see what data looked like at some point in the past. And this lets you kind of set up both your own kind of little data playpen as a clone without really having to copy all of that data. >>So it's quick and easy, and you can also, again, with our separation of storage and compute, you can provision your own virtual warehouse for dev usage. So you're not interfering with anything to do with people's production usage of this data. So the, these ideas, the scalability, it just makes it easy to make changes, test them, see what the effect of those changes are. And we've actually seen this. You were talking a lot about partner ecosystems earlier. Uh, the partner ecosystem has taken these ideas that are inside snowflake and they've extended them. They've integrated them with, uh, dev ops and data ops tooling. So things like version control and get an infrastructure automation and things like Terraform. And they've kind of built that out into more of a data ops products that, that you can, you can make yourself so we can see there's a huge impact of, of these ideas coming into the data world. >>We think we're really well-placed to take advantage to them. The partner ecosystem is doing a great job with doing that. And it really allows us to kind of change that operating model for data so that we don't have as much emphasis on like hierarchy and change windows and all these kinds of things that are maybe use as a lot of fashioned. And we kind of taking the shift from this batch data integration into, you know, streaming continuous data pipelines in the cloud. And this kind of gets you away from like a once a week or once a month change window, if you're really unlucky to, you know, pushing changes, uh, in a much more rapid fashion as the needs of the business change. >>I mean, those hierarchical organizational structures, uh, w when we apply those to begin to that, what it actually creates the silos. So if you're going to be a silo Buster, which aji look at you guys in silo busters, you've got to put data in the hands of the domain experts, the business people, they know what data they want, if they have to go through and beg and borrow for a new data sets, et cetera. And so that's where automation becomes so key. And frankly, the technology should be an implementation detail, not the dictating factor. I wonder if you could comment on this. >>Yeah, absolutely. I think, um, making the, the technologies more accessible to the general business users >>Or those specialists business teams that, um, that's the key to unlocking is it is interesting to see is as people move from organization to organization where they've had those experiences operating in a hierarchical sense, I want to break free from that and, um, or have been exposed to, um, automation, continuous workflows, um, change is continuous in it. It's continuous in business, the market's continuously changing. So having that flow across the organization of work, using key components, such as get hub, similar to what you drive process Terraform to build in, um, code into the process, um, and automation and with a high Tahoe leveraging all the metadata from across those fragmented sources is, is, is good to say how those things are coming together. And watching people move from organization to organization say, Hey, okay, I've got a new start. I've got my first hundred days to impress my, my new manager. >>Uh, what kind of an impact can I, um, bring to this? And quite often we're seeing that as, you know, let me take away the good learnings from how to do it, or how not to do it from my previous role. And this is an opportunity for me to, to bring in automation. And I'll give you an example, David, you know, recently started working with a, a client in financial services. Who's an asset manager, uh, managing financial assets. They've grown over the course of the last 10 years through M and a, and each of those acquisitions have bought with it tactical data. It's saying instead of data of multiple CRM systems now multiple databases, multiple bespoke in-house created applications. And when the new CIO came in and had a look at those well, you know, yes, I want to mobilize my data. Yes, I need to modernize my data state because my CEO is now looking at these crypto assets that are on the horizon and the new funds that are emerging that around digital assets and crypto assets. >>But in order to get to that where absolutely data underpins and is the core asset, um, cleaning up that, that legacy situation mobilizing the relevant data into the Safelite cloud platform, um, is where we're giving time back, you know, that is now taking a few weeks, whereas that transitioned to mobilize that data, start with that, that new clean slate to build upon a new business as a, a digital crypto asset manager, as well as the legacy, traditional financial assets, bonds stocks, and fixed income assets, you name it, uh, is where we're starting to see a lot of innovation. >>Yeah. Tons of innovation. I love the crypto examples and FTS are exploding and, you know, let's face it, traditional banks are getting disrupted. Uh, and so I also love this notion of data RPA. I, especially because I've done a lot of work in the RPA space. And, and I want to, what I would observe is that the, the early days of RPA, I call it paving the cow path, taking existing processes and applying scripts, get letting software robots, you know, do its thing. And that was good because it reduced, you know, mundane tasks, but really where it's evolved is a much broader automation agenda. People are discovering new, new ways to completely transform their processes. And I see a similar, uh, analogy for data, the data operating model. So I'm wonder whenever you think about that, how a customer really gets started bringing this to their ecosystem, their data life cycles. >>Sure. Yeah. So step one is always the same is figuring out for the CIO, the chief data officer, what data do I have, um, and that's increasingly something that they want towards a mate, so we can help them there and, and do that automated data discovery, whether that is documents in the file, share backup archive in a relational data store, in a mainframe really quickly hydrating that and bringing that intelligence, the forefront of, of what do I have, and then it's the next step of, well, okay. Now I want to continually monitor and curate that intelligence with the platform that I've chosen. Let's say snowflake, um, in order such that I can then build applications on top of that platform to serve my, my internal, external customer needs and the automation around classifying data reconciliation across different fragmented data silos, building that in those insights into snowflake. >>Um, as you say, a little later on where we're talking about data quality, active DQ, allowing us to reconcile data from different sources, as well as look at the integrity of that data. Um, so they can go on to remediation, you know, I, I wanna, um, harness and leverage, um, techniques around traditional RPA. Um, but to get to that stage, I need to fix the data. So remediating publishing the data in snowflake, uh, allowing analysis to be formed performance snowflake. Th those are the key steps that we see and just shrinking that timeline into weeks, giving the organization that time back means they're spending more time on their customer and solving their customer's problem, which is where we want them to be. >>This is the brilliance of snowflake actually, you know, Duncan is, I've talked to him, then what does your view about this and your other co-founders and it's really that focus on simplicity. So, I mean, that's, you, you picked a good company to join my opinion. So, um, I wonder if you could, you know, talk about some of the industry sectors that are, again, going to gain the most from, from data RPA, I mean, traditional RPA, if I can use that term, you know, a lot of it was back office, a lot of, you know, financial w what are the practical applications where data RPA is going to impact, you know, businesses and, and the outcomes that we can expect. >>Yes, sir. So our drive is, is really to, to make that, um, business general user's experience of RPA simpler and, and using no code to do that, uh, where they've also chosen snowflake to build that their cloud platform. They've got the combination then of using a relatively simple script scripting techniques, such as SQL, uh, without no code approach. And the, the answer to your question is whichever sector is looking to mobilize their data. Uh, it seems like a cop-out, but to give you some specific examples, David, um, in banking where, uh, customers are looking to modernize their banking systems and enable better customer experience through, through applications and digital apps. That's where we're, we're seeing a lot of traction, uh, and this approach to, to pay RPA to data, um, health care, where there's a huge amount of work to do to standardize data sets across providers, payers, patients, uh, and it's an ongoing, um, process there for, for retail, um, helping to, to build that immersive customer experience. >>So recommending next best actions, um, providing an experience that is going to drive loyalty and retention, that's, that's dependent on understanding what that customer's needs intent, uh, being out to provide them with the content or the outfit at that point in time, or all data dependent utilities is another one great overlap there with, with snowflake where, you know, helping utilities, telecoms energy, water providers to build services on that data. And this is where the ecosystem just continues to, to expand. If we, if we're helping our customers turn their data into services for, for their ecosystem, that's, that's exciting. And they were more so exciting than insurance, which we always used to, um, think back to, uh, when insurance used to be very dull and mundane, actually, that's where we're seeing a huge amounts of innovation to create new flexible products that are priced to the day to the situation and, and risk models being adaptive when the data changes, uh, on, on events or circumstances. So across all those sectors that they're all mobilizing that data, they're all moving in some way, shape or form to a, a multi-cloud, um, set up with their it. And I think with, with snowflake and without Tahoe, being able to accelerate that and make that journey simple and as complex is, uh, is why we found such a good partner here. >>All right. Thanks for that. And then thank you guys. Both. We gotta leave it there. Uh, really appreciate Duncan you coming on and Aja best of luck with the fundraising. >>We'll keep you posted. Thanks, David. All right. Great. >>Okay. Now let's take a look at a short video. That's going to help you understand how to reduce the steps around your data ops. Let's watch.

>> Announcer: From around the globe. It's the cube presenting active DQ, intelligent automation for data quality brought to you by Io Tahoe. (indistinct) >> Got it? all right if everybody is ready we'll opening on Dave in five, four, three. Now we're going to look at the role automation plays in mobilizing your data on snowflake. Let's welcome. And Duncan Turnbull who's partner sales engineer at snowflake, Ajay Vohora is back CEO of IO. Tahoe he's going to share his insight. Gentlemen. Welcome. >> Thank you, David good to be back. >> Yes it's great to have you back Ajay and it's really good to see Io Tahoe expanding the ecosystem so important now of course bringing snowflake in, it looks like you're really starting to build momentum. I mean, there's progress that we've seen every month month by month, over the past 12, 14 months. Your seed investors, they got to be happy. >> They are they're happy and they can see that we're running into a nice phase of expansion here new customers signing up, and now we're ready to go out and raise that next round of funding. Maybe think of us like Snowflake five years ago. So we're definitely on track with that. A lot of interest from investors and right now trying to focus in on those investors that can partner with us and understand AI data and an automation. >> Well, so personally, I mean you've managed a number of early stage VC funds. I think four of them. You've taken several comm software companies through many funding rounds and growth and all the way to exit. So you know how it works. You have to get product market fit, you got to make sure you get your KPIs, right. And you got to hire the right salespeople, but what's different this time around? >> Well, you know, the fundamentals that you mentioned those that never change. What I can see that's different that's shifted this time around is three things. One in that they used to be this kind of choice of do we go open source or do we go proprietary? Now that has turned into a nice hybrid model where we've really keyed into RedHat doing something similar with Centos. And the idea here is that there is a core capability of technology that underpins a platform, but it's the ability to then build an ecosystem around that made up of a community. And that community may include customers, technology partners, other tech vendors and enabling the platform adoption so that all of those folks in that community can build and contribute whilst still maintaining the core architecture and platform integrity at the core of it. And that's one thing that's changed. We're seeing a lot of that type of software company emerge into that model, which is different from five years ago. And then leveraging the Cloud, every Cloud, Snowflake Cloud being one of them here. In order to make use of what customers end customers in enterprise software are moving towards. Every CIO is now in some configuration of a hybrid. IT is state whether that is Cloud, multi-Cloud, on-prem. That's just the reality. The other piece is in dealing with the CIO, his legacy. So the past 15, 20 years I've purchased many different platforms, technologies, and some of those are still established and still (indistinct) How do you enable that CIO to make purchase whilst still preserving and in some cases building on and extending the legacy material technology. So they've invested their people's time and training and financial investment into. Yeah, of course solving a problem, customer pain point with technology that never goes out in a fashion >> That never changes. You have to focus like a laser on that. And of course, speaking of companies who are focused on solving problems, Duncan Turnbull from Snowflake. You guys have really done a great job and really brilliantly addressing pain points particularly around data warehousing, simplified that you're providing this new capability around data sharing really quite amazing. Duncan, Ajay talks about data quality and customer pain points in enterprise IT. Why is data quality been such a problem historically? >> So one of the biggest challenges that's really affected that in the past is that because to address everyone's needs for using data, they've evolved all these kinds of different places to store it, all these different silos or data marts or all this kind of pluralfiation of places where data lives and all of those end up with slightly different schedules for bringing data in and out, they end up with slightly different rules for transforming that data and formatting it and getting it ready and slightly different quality checks for making use of it. And this then becomes like a big problem in that these different teams are then going to have slightly different or even radically different ounces to the same kinds of questions, which makes it very hard for teams to work together on their different data problems that exist inside the business, depending on which of these silos they end up looking at. And what you can do. If you have a single kind of scalable system for putting all of your data, into it, you can kind of side step along this complexity and you can address the data quality issues in a single way. >> Now, of course, we're seeing this huge trend in the market towards robotic process automation, RPA that adoption is accelerating. You see in UI paths, IPO, 35 plus billion dollars, valuation, Snowflake like numbers, nice comms there for sure. Ajay you've coined the phrase data RPA what is that in simple terms? >> Yeah I mean, it was born out of seeing how in our ecosystem (indistinct) community developers and customers general business users for wanting to adopt and deploy Io Tahoe's technology. And we could see that. I mean, there's not marketing out here we're not trying to automate that piece but wherever there is a process that was tied into some form of a manual overhead with handovers. And so on, that process is something that we were able to automate with Io Tahoe's technology and the employment of AI and machine learning technologies specifically to those data processes, almost as a precursor to getting into marketing automation or financial information automation. That's really where we're seeing the momentum pick up especially in the last six months. And we've kept it really simple with snowflake. We've kind of stepped back and said, well, the resource that a Snowflake can leverage here is the metadata. So how could we turn Snowflake into that repository of being the data catalog? And by the way, if you're a CIO looking to purchase the data catalog tool, stop there's no need to. Working with Snowflake we've enabled that intelligence to be gathered automatically and to be put to use within snowflake. So reducing that manual effort and I'm putting that data to work. And that's where we've packaged this with our AI machine learning specific to those data tasks. And it made sense that's what's resonated with our customers. >> You know, what's interesting here just a quick aside, as you know I've been watching snowflake now for awhile and of course the competitors come out and maybe criticize, "Why they don't have this feature. They don't have that feature." And snowflake seems to have an answer. And the answer oftentimes is, well ecosystem, ecosystem is going to bring that because we have a platform that's so easy to work with. So I'm interested Duncan in what kind of collaborations you are enabling with high quality data. And of course, your data sharing capability. >> Yeah so I think the ability to work on datasets isn't just limited to inside the business itself or even between different business units you're kind of discussing maybe with those silos before. When looking at this idea of collaboration. We have these challenges where we want to be able to exploit data to the greatest degree possible, but we need to maintain the security, the safety, the privacy, and governance of that data. It could be quite valuable. It could be quite personal depending on the application involved. One of these novel applications that we see between organizations of data sharing is this idea of data clean rooms. And these data clean rooms are safe, collaborative spaces which allow multiple companies or even divisions inside a company where they have particular privacy requirements to bring two or more data sets together, for analysis. But without having to actually share the whole unprotected data set with each other. And this lets you to you know, when you do this inside of Snowflake you can collaborate using standard tool sets. You can use all of our SQL ecosystem. You can use all of the data science ecosystem that works with Snowflake. You can use all of the BI ecosystem that works with snowflake. But you can do that in a way that keeps the confidentiality that needs to be presented inside the data intact. And you can only really do these kinds of collaborations especially across organization but even inside large enterprises, when you have good reliable data to work with, otherwise your analysis just isn't going to really work properly. A good example of this is one of our large gaming customers. Who's an appetizer. They were able to build targeted ads to acquire customers and measure the campaign impact in revenue but they were able to keep their data safe and secure while doing that while working with advertising partners. The business impact of that was they're able to get a lift of 20 to 25% in campaign effectiveness through better targeting and actually pull through into that of a reduction in customer acquisition costs because they just didn't have to spend as much on the forms of media that weren't working for them. >> So, Ajay I wonder, I mean with the way public policy is shaping out, you know, obviously GDPR started it in the States, California consumer privacy Act, and people are sort of taking the best of those. And there's a lot of differentiation but what are you seeing just in terms of governments really driving this move to privacy. >> Government, public sector, we're seeing a huge wake up an activity and across (indistinct), part of it has been data privacy. The other part of it is being more joined up and more digital rather than paper or form based. We've all got, so there's a waiting in the line, holding a form, taking that form to the front of the line and handing it over a desk. Now government and public sector is really looking to transform their services into being online (indistinct) self service. And that whole shift is then driving the need to emulate a lot of what the commercial sector is doing to automate their processes and to unlock the data from silos to put through into those processes. And another thing that I can say about this is the need for data quality is as Duncan mentions underpins all of these processes government, pharmaceuticals, utilities, banking, insurance. The ability for a chief marketing officer to drive a a loyalty campaign, the ability for a CFO to reconcile accounts at the end of the month to do a quick accurate financial close. Also the ability of a customer operations to make sure that the customer has the right details about themselves in the right application that they can sell. So from all of that is underpinned by data and is effective or not based on the quality of that data. So whilst we're mobilizing data to the Snowflake Cloud the ability to then drive analytics, prediction, business processes of that Cloud succeeds or fails on the quality of that data. >> I mean it really is table stakes. If you don't trust the data you're not going to use the data. The problem is it always takes so long to get to the data quality. There's all these endless debates about it. So we've been doing a fair amount of work and thinking around this idea of decentralized data. Data by its very nature is decentralized but the fault domains of traditional big data is that everything is just monolithic. And the organizations monolithic that technology's monolithic, the roles are very, you know, hyper specialized. And so you're hearing a lot more these days about this notion of a data fabric or what Jimit Devani calls a data mesh and we've kind of been leaning into that and the ability to connect various data capabilities whether it's a data, warehouse or a data hub or a data lake, that those assets are discoverable, they're shareable through API APIs and they're governed on a federated basis. And you're using now bringing in a machine intelligence to improve data quality. You know, I wonder Duncan, if you could talk a little bit about Snowflake's approach to this topic >> Sure so I'd say that making use of all of your data is the key kind of driver behind these ideas of beta meshes or beta fabrics? And the idea is that you want to bring together not just your kind of strategic data but also your legacy data and everything that you have inside the enterprise. I think I'd also like to kind of expand upon what a lot of people view as all of the data. And I think that a lot of people kind of miss that there's this whole other world of data they could be having access to, which is things like data from their business partners, their customers, their suppliers, and even stuff that's, more in the public domain, whether that's, you know demographic data or geographic or all these kinds of other types of data sources. And what I'd say to some extent is that the data Cloud really facilitates the ability to share and gain access to this both kind of, between organizations, inside organizations. And you don't have to, make lots of copies of the data and kind of worry about the storage and this federated, idea of governance and all these things that it's quite complex to kind of manage. The snowflake approach really enables you to share data with your ecosystem or the world without any latency with full control over what's shared without having to introduce new complexities or having complex interactions with APIs or software integration. The simple approach that we provide allows a relentless focus on creating the right data product to meet the challenges facing your business today. >> So Ajay, the key here is Duncan's talking about it my mind and in my cake takeaway is to simplicity. If you can take the complexity out of the equation you're going to get more adoption. It really is that simple. >> Yeah, absolutely. I think that, that whole journey, maybe five, six years ago the adoption of data lakes was a stepping stone. However, the Achilles heel there was the complexity that it shifted towards consuming that data from a data lake where there were many, many sets of data to be able to cure rate and to consume. Whereas actually, the simplicity of being able to go to the data that you need to do your role, whether you're in tax compliance or in customer services is key. And listen for snowflake by Io Tahoe. One thing we know for sure is that our customers are super smart and they're very capable. They're data savvy and they'll want to use whichever tool and embrace whichever Cloud platform that is going to reduce the barriers to solving what's complex about that data, simplifying that and using good old fashioned SQL to access data and to build products from it to exploit that data. So simplicity is key to it to allow people to make use of that data and CIO is recognize that. >> So Duncan, the Cloud obviously brought in this notion of DevOps and new methodologies and things like agile that's brought in the notion of DataOps which is a very hot topic right now basically DevOps applies to data about how does Snowflake think about this? How do you facilitate that methodology? >> So I agree with you absolutely that DataOps takes these ideas of agile development or agile delivery and have the kind of DevOps world that we've seen just rise and rise. And it applies them to the data pipeline, which is somewhere where it kind of traditionally hasn't happened. And it's the same kinds of messages. As we see in the development world it's about delivering faster development having better repeatability and really getting towards that dream of the data-driven enterprise, where you can answer people's data questions they can make better business decisions. And we have some really great architectural advantages that allow us to do things like allow cloning of data sets without having to copy them, allows us to do things like time travel so we can see what the data looked like at some point in the past. And this lets you kind of set up both your own kind of little data playpen as a clone without really having to copy all of that data so it's quick and easy. And you can also, again with our separation of storage and compute, you can provision your own virtual warehouse for dev usage. So you're not interfering with anything to do with people's production usage of this data. So these ideas, the scalability, it just makes it easy to make changes, test them, see what the effect of those changes are. And we've actually seen this, that you were talking a lot about partner ecosystems earlier. The partner ecosystem has taken these ideas that are inside Snowflake and they've extended them. They've integrated them with DevOps and DataOps tooling. So things like version control and get an infrastructure automation and things like Terraform. And they've kind of built that out into more of a DataOps products that you can make use of. So we can see there's a huge impact of these ideas coming into the data world. We think we're really well-placed to take advantage to them. The partner ecosystem is doing a great job with doing that. And it really allows us to kind of change that operating model for data so that we don't have as much emphasis on like hierarchy and change windows and all these kinds of things that are maybe viewed as a lot as fashioned. And we kind of taken the shift from this batch stage of integration into streaming continuous data pipelines in the Cloud. And this kind of gets you away from like a once a week or once a month change window if you're really unlucky to pushing changes in a much more rapid fashion as the needs of the business change. >> I mean those hierarchical organizational structures when we apply those to begin to that it actually creates the silos. So if you're going to be a silo buster, which Ajay I look at you guys in silo busters, you've got to put data in the hands of the domain experts, the business people, they know what data they want, if they have to go through and beg and borrow for a new data sets cetera. And so that's where automation becomes so key. And frankly the technology should be an implementation detail not the dictating factor. I wonder if you could comment on this. >> Yeah, absolutely. I think making the technologies more accessible to the general business users or those specialists business teams that's the key to unlocking. So it is interesting to see is as people move from organization to organization where they've had those experiences operating in a hierarchical sense, I want to break free from that. And we've been exposed to automation. Continuous workflows change is continuous in IT. It's continuous in business. The market's continuously changing. So having that flow across the organization of work, using key components, such as GitHub and similar towards your drive process, Terraform to build in, code into the process and automation and with Io Tahoe, leveraging all the metadata from across those fragmented sources is good to see how those things are coming together. And watching people move from organization to organization say, "Hey okay, I've got a new start. I've got my first hundred days to impress my new manager. What kind of an impact can I bring to this?" And quite often we're seeing that as, let me take away the good learnings from how to do it or how not to do it from my previous role. And this is an opportunity for me to bring in automation. And I'll give you an example, David, recently started working with a client in financial services. Who's an asset manager, managing financial assets. They've grown over the course of the last 10 years through M&A and each of those acquisitions have bought with its technical debt, it's own set of data, that multiple CRM systems now multiple databases, multiple bespoke in-house created applications. And when the new CIO came in and had a look at those he thought well, yes I want to mobilize my data. Yes, I need to modernize my data state because my CEO is now looking at these crypto assets that are on the horizon and the new funds that are emerging that's around digital assets and crypto assets. But in order to get to that where absolutely data underpins that and is the core asset cleaning up that that legacy situation mobilizing the relevant data into the Snowflake Cloud platform is where we're giving time back. You know, that is now taking a few weeks whereas that transitioned to mobilize that data start with that new clean slate to build upon a new business as a digital crypto asset manager as well as the legacy, traditional financial assets, bonds, stocks, and fixed income assets, you name it is where we're starting to see a lot of innovation. >> Tons of innovation. I love the crypto examples, NFTs are exploding and let's face it. Traditional banks are getting disrupted. And so I also love this notion of data RPA. Especially because Ajay I've done a lot of work in the RPA space. And what I would observe is that the early days of RPA, I call it paving the cow path, taking existing processes and applying scripts, letting software robots do its thing. And that was good because it reduced mundane tasks, but really where it's evolved is a much broader automation agenda. People are discovering new ways to completely transform their processes. And I see a similar analogy for the data operating model. So I'm wonder what do you think about that and how a customer really gets started bringing this to their ecosystem, their data life cycles. >> Sure. Yeah. Step one is always the same. It's figuring out for the CIO, the chief data officer, what data do I have? And that's increasingly something that they want to automate, so we can help them there and do that automated data discovery whether that is documents in the file share backup archive in a relational data store in a mainframe really quickly hydrating that and bringing that intelligence the forefront of what do I have, and then it's the next step of, well, okay now I want to continually monitor and curate that intelligence with the platform that I've chosen let's say Snowflake. In order such that I can then build applications on top of that platform to serve my internal external customer needs. and the automation around classifying data, reconciliation across different fragmented data silos building that in those insights into Snowflake. As you say, a little later on where we're talking about data quality, active DQ, allowing us to reconcile data from different sources as well as look at the integrity of that data. So then go on to remediation. I want to harness and leverage techniques around traditional RPA but to get to that stage, I need to fix the data. So remediating publishing the data in Snowflake, allowing analysis to be formed, performed in Snowflake but those are the key steps that we see and just shrinking that timeline into weeks, giving the organization that time back means they're spending more time on their customer and solving their customer's problem which is where we want them to be. >> Well, I think this is the brilliance of Snowflake actually, you know, Duncan I've talked to Benoit Dageville about this and your other co-founders and it's really that focus on simplicity. So I mean, that's you picked a good company to join in my opinion. So I wonder Ajay, if you could talk about some of the industry sectors that again are going to gain the most from data RPA, I mean traditional RPA, if I can use that term, a lot of it was back office, a lot of financial, what are the practical applications where data RPA is going to impact businesses and the outcomes that we can expect. >> Yes, so our drive is really to make that business general user's experience of RPA simpler and using no code to do that where they've also chosen Snowflake to build their Cloud platform. They've got the combination then of using a relatively simple scripting techniques such as SQL without no code approach. And the answer to your question is whichever sector is looking to mobilize their data. It seems like a cop-out but to give you some specific examples, David now in banking, where our customers are looking to modernize their banking systems and enable better customer experience through applications and digital apps, that's where we're seeing a lot of traction in this approach to pay RPA to data. And health care where there's a huge amount of work to do to standardize data sets across providers, payers, patients and it's an ongoing process there. For retail helping to to build that immersive customer experience. So recommending next best actions. Providing an experience that is going to drive loyalty and retention, that's dependent on understanding what that customer's needs, intent are, being able to provide them with the content or the offer at that point in time or all data dependent utilities. There's another one great overlap there with Snowflake where helping utilities telecoms, energy, water providers to build services on that data. And this is where the ecosystem just continues to expand. If we're helping our customers turn their data into services for their ecosystem, that's exciting. Again, they were more so exciting than insurance which it always used to think back to, when insurance used to be very dull and mundane, actually that's where we're seeing a huge amounts of innovation to create new flexible products that are priced to the day to the situation and risk models being adaptive when the data changes on events or circumstances. So across all those sectors that they're all mobilizing their data, they're all moving in some way but for sure form to a multi-Cloud setup with their IT. And I think with Snowflake and with Io Tahoe being able to accelerate that and make that journey simple and less complex is why we've found such a good partner here. >> All right. Thanks for that. And thank you guys both. We got to leave it there really appreciate Duncan you coming on and Ajay best of luck with the fundraising. >> We'll keep you posted. Thanks, David. >> All right. Great. >> Okay. Now let's take a look at a short video. That's going to help you understand how to reduce the steps around your DataOps let's watch. (upbeat music)

[Music] hi everybody this is David on tape with the Cuban welcome to Boston we're covering storage here at Amazon storage day and we're looking at all the innovations and the expansion of Amazon's pretty vast storage portfolio Duncan Lennox is here is the director of product management for Amazon DFS Duncan good to see it's great to be here so what is so EF s stands for elastic file system what is Amazon EFS that's right EFS is our NFS based filesystem service designed to make it super easy for customers to get up and running with the file system in the cloud so should we think of this as kind of on-prem file services just stuck into the cloud or is it more than that it's more than that but it's definitely designed to enable that we wanted to make it really easy for customers to take the on pram applications that they have today that depend on a file system and move those into the cloud when you look at the macro trends particularly as it relates to file services what are you seeing what a customer's telling you well the first thing that we see is that it's still very early in the move to the cloud the vast majority of workloads are still running on Prem and customers need easy ways to move those thousands of applications they might have into the cloud without having to necessarily rewrite them to take advantage of cloud native services and that's a key thing that we built EFS for to make it easy to just pick up the application and drop it into the cloud without the application even needing to know that it's now running in the cloud okay so that's transparent to the to the to the application and the workload and it absolutely is we built it deliberately using NFS so that the application wouldn't even need to know that it's now running in the cloud and we also built it to be elastic and simple for the same reason so customers don't have to worry about provisioning the storage they need it just works NFS is hard making making NFS simple and elastic is not a trivial engineering task is it it hadn't been done until we did it a lot of people said it couldn't be done how could you make something that truly was elastic in the cloud but still support that NFS but we've been able to do that for tens of thousands of customers successfully and and what's the real challenge there is it to maintain that performance and the recoverability from a technical standpoint an engineering standpoint what's yes sir it's all of the above people expect a certain level of performance whether that's latency throughput and I ops that their application is dependent on but they also want to be able to take advantage of that pay-as-you-go cloud model that AWS created back with s3 13 years ago so that elasticity that we offer to customers means they don't have to worry about capex they don't have to plan for exactly how much storage they need to provision the file system grows and shrinks as they add and remove data they pay only for what they're using and we handle all the heavy lifting for them to make that happen this this opens up a huge new set of workloads for your customers doesn't it it absolutely does and a big part of what we see is customers wanting to go on that journey through the cloud so initially there starting with lifting and shifting those applications as we talked about it but as they mature they want to be able to take advantage of newer technologies like containerization and ultimately even service all right let's talk about EFS ia infrequently access files is really what it's designed for tell us more about it right so one of the things that we heard a lot from our customers of course is can you make it cheaper we love it but we'd like to use more of it and what we discovered is that we could develop this infrequent access storage class and how it works is you turn on a capability we call lifecycle management and it's completely automated after that so we know from industry analysts and from talking to customers that the majority of data perhaps as much as 80% goes pretty cold after about a month and it's rarely touched again so we developed the infrequent access storage class to take advantage of that so once you enable it which is a single click in the console or one API call you pick a policy 14 days 30 days and we monitor the readwrite IO to every file individually and once a file hasn't been read from or written to in that policy period say 30 days we automatically and transparently move it to the infrequent access storage class which is 92% cheaper than our standard storage class it's only two and a half cents in our u.s. East one region as opposed to 30 cents for our standard storage class two and a half cents per per gigabyte per gigabyte month we've done about four customers that were particularly excited about is that it remains active file system data so we move your files to the infrequent access storage class but it does not appear to move in the file system so for your applications and your users it's the same file in the same directory so they don't even need to be aware of the fact that it's now on the infrequent access storage class you just get a bill that's 92 percent cheaper for storage for that file like that ok and it's and it's simple to set up you said it's one click and then I set my policy and I can go back and change my that's exactly right we have multiple policies available you can change it later you can turn off lifecycle management if you decide you no longer need it later so how do you see customers taking advantage of this what do you expect the adoption to be like and what are you hearing from them well what we heard from customers was that they like to keep larger workloads in their file systems but because the data tends to go cold and isn't frequently accessed it didn't make economic sense to say to keep large amounts of data in our standard storage class but there's advantages to them in their businesses for example we've got customers who are doing genomic sequencing and for them to have a larger set of data always available to their applications but not costing them as much as it was allows them to get more results faster as one example you obviously see that yeah what we're what we're trying to do all the time is help our customers be able to focus less on the infrastructure and the heavy lifting and more on being able to innovate faster for their customer so Duncan Duncan some of the sort of fundamental capabilities of EFS include high availability and durability tell us more about that yeah when we were developing EFS we heard a lot from customers that they really wanted higher levels of durability and availability than they typically been able to have on Prem it's super expensive and complex to build high availability and high durability solutions so we've baked that in as a standard part of EFS so when a file is written to an EFS file system and that acknowledgement is received back by the client at that point the data is already spread across three availability zones for both availability and durability what that means is not only are you extremely unlikely to ever lose any data if one of those AZ's goes down or becomes unavailable for some reason to your application you continue to have full read/write access to your file system from the other two available zones so traditionally this would be a very expensive proposition it was sort of on Prem and multiple data centers maybe talk about how it's different in the clouds yeah it's complex to build there's a lot of moving parts involved in it because in our case with three availability zones you were talking about three physically distinct data centers high-speed networking between those and actually moving the data so that it's written not just to one but to all three and we handled that all transparently under the hood in EFS it's all included in our standard storage to your cost as well so it's not something that customers have to worry about more either a complexity or a cost point of view it's so so very very I guess low RPO and an RTO and my essentially zero if you will between the three availability zones because once your client gets that acknowledgement back it's already durably written to the three availability zones all right we'll give you last word just in the world of file services what should we be paying attention to what kinds of things are you really trying to achieve I think it's helping people do more for less faster so there's always more we can do and helping them take advantage of all the services AWS has to offer spoken like a true Amazonian Duncan thanks so much for coming on the queue for thank you good all right and thank you for watching everybody be back from storage day in Boston you watching the cute

>> Live (lively music) from Las Vegas it's the Cube covering the AWS Accenture Executive Summit. Brought to you by Accenture. >> Welcome back everyone to The Cube's live coverage of the AWS Executive Summit I'm your host Rebecca Knight. We have two guests for this segment we have Chad Duncan, Managing Director of Financial Services Technology Advisory Cloud Lead North America at Accenture, it's quite a long title. (laughs) And Jim Good, Senior Director Product and Portfolio Delivery at Capital One. Thank you both so much for coming on the show. >> Thanks for having us. >> Thank you. >> So we're talking today about Capital One's migration to the Cloud, but Jim, let's start out with Capital One the bank and why moving to the Cloud was a business imperative for you. >> Essentially, as we look at Capital One, we have national reach and in credit cards, people are very familiar with that, but we also wanted national reach in banking services too. And the approach we're using is not to go the old fashioned way, bricks and mortar, but it's to actually go more into the way people like to interact with their financial services partners and that's through mobile devices. And the only way to really get the kind of innovation you need, and to get the features to customers that they want on a regular basis is to be a very nimble, and use strategies like DevOps, et cetera. And the Cloud really puts us in the position to do that. By the dynamic provisioning of infrastructure, all the different things that our Agile practices can take advantage of so that we can regularly deliver new features to customers that they want. >> So, Agile delivery, you mentioned Agile. What is it about Capital One's culture in terms of it's approach to innovation that sort of enables that? >> Well we've adopted Agile a number of years ago and this is something where we'd like to really empower teams to work with the business to deliver these features on a recurring basis, regular releases. That's ingrained in our culture. I don't think we'd be able to actually do this Cloud migration without that structure because the teams themselves are doing the work. The teams themselves now have control over the infrastructure. No more centralized group doing all the work for them. It's really distributed to the teams. And so that's really become what's expected of our teams that they can actually deploy when they need to and actually build as needed. Again, without the Cloud, without the AWS services that we're using, we simply would not be able to realize that and the teams could not innovate the way that they are. >> Chad, in terms of you, you've been working with Capital One for a few years now on this migration. What would you say about this company and about how it's migration has gone? >> Their innovation strategy right? They want to be innovative, you heard Jim talk a little bit about that just now, and how they go to market for their customers. How they create new service offerings for their customers. Be their new cafes. Right? They don't have typical branches. You walk into a cafe, you can get a cup of coffee, yes there's financial advisors in there, but that's not the main focus it's not walking into a traditional branch bank. So taking that, if you think about that theme across all of their different product sets, and being able to very quickly and iteratively roll out new products to the market, and services that customers are desiring and really kind of being a disruptor in the industry. Frankly, is the approach that they're taking. >> And is Accenture says, we are living in this age of epic disruption so >> Epic disruption. >> (laughing) Exactly. So Jim, one of the challenges in the migrating legacy platforms is this lack of megadata metadata, I'm sorry. (laughs) Megadata. >> There's megadata. >> There is megadata. >> (laughing) I think we need the aid of the U.S. house bans to talk about that. >> The mega needs meta. (all laughing) >> But this lack of metadata, so how do you overcome that obstacle? >> Well it's been one of the more challenging things that we face. We have a lot of legacy systems that we're kind of unwinding and migrating to the cloud. We're building new platforms for those new services of those. There's been a lot of rolling up the sleeves work just to understand what all this is the old fashioned way. But, what we're really able to do now because as we move things to the Cloud as we move new applications to the Cloud, we're able to use information that's now available to us that was not available to us before. VPC Flow Logs for example, from Amazon, allow us to know what are the connections between all these different services, and we've been able to use some of their tools and other tools that we've developed internally to start to visualize this in a much better way. Would not have been able to do that in our legacy setup. And so this is something that now we're actually using to aid the migrations, to understand how things connect in a much better way. And really, looking forward, we're in a much better place and we now know what we have, and we're able to track it very well. >> So Chad, Capital One is making it sound like it is pretty easy, (laughing) but we know that moving to the Cloud is actually really hard for so many financial institutions. Why has Capital One been able to succeed at a time when so many other banks are really struggling to do this? >> Yeah, I think about it in a couple of ways. They're not afraid to lead and innovate and fail fast, right? So you get out there, you talked about an MVP, and how you would stand up a new surface offering, or one of the applications in the cloud, right? Go ahead and do that, get some momentum, get people excited about the progress that's being made. That's one thing. And really understanding that security shouldn't be an issue, right? There's ways to secure your data in the Cloud. You can run core banking in the Cloud, Capital One's doing that, right? So, there's things like that that some other institutions sort of have analysis paralysis and they're like, "Well I don't know if I can secure my data, "I don't know if I can get the throughput that I need." The data latency may be an issue for banking and really bring the right architects to the table and do that. Capital one did a great job from the beginning of getting their people trained and certified in the Cloud technologies. A lot, mostly with AWS, right? Frankly. And really making that a culture of their organization. They don't consider themselves a financial services institution really. They consider themselves a technology company. >> Yep. >> And that's the culture. When you walk into a Capital One building, not a bank ... >> A Pete's cafe. (laughs) Right? Yeah. >> People center. >> The center, yes right, and headquarters building. You feel like you're walking through a technology company. You don't feel like you're in a bank. And setting that culture and that expectation with all of the Capital One associates I think is a huge key to your success and how you guys were able to get everybody on board. >> Yes. >> You had your CEO your CIO all talking about we're moving to Cloud. We're going to close our data centers. We're going to be all-in in public Cloud and that's the marching orders. And that's the drum beat, right? And you kind of feel that when you're there. >> And also from our inception, we've been a test and learn company and culture. That is what we have built Capital One on is finding out what customers really want, responding to that and iterating, and iterating, and iterating in different offerings. And it's no different with how we've approached our migration to the Cloud. We're going to set the minimum viable product as far as outcomes are concerned. We're going to test and learn, test and learn, test and learn. We learn from those, it's the fail fast kind of mentality, and we learn from some of those failures and adjust. And it's been, again, it really does fit our culture very well historically. >> And that's how, because there are so many trade-offs involved when you're thinking about these things. And is that how you sort of stick with the minimum viable product? This test and learn ethos? >> Well the test and learn is a way to get there. The minimum viable product is like this is our goal let's kind of be focused there so we can get to that. It takes some discipline to be able to say no there's shiny objects over here and over here, but if we go that way it's going to take us a little bit off track. So we spend a lot of time discussing what is MVP for the migration, for an application, whatever it might be, and sticking to that and making sure we stay true to that. So we have regular reviews at a team level, at a program level, to make sure we're staying the course and driving toward that. >> And that's critical. So many of our customers think they have to have it all thought out, all planned out, the entire strategy, all of the different dependencies mapped out, how we're going to develop this in the Cloud and they never get anywhere. Because you can't absorb all of that at once. So you start small, you gain, you iterate, and you go from there. >> When you're talking about getting inside the brains of customers and figuring out what they want and then delivering that, when we think about the bank of the future Capital One has this digital first strategy, what do you envision? For how people will interact with their financial services institution? >> Well I have four kids and they're all in their 20s and so I observe them a lot and I learn from them a lot and I can see what people want to do. They want to use their mobile devices. That's what they want to be able to do. They want to have access to their information at their fingertips, when they want it. The cafes Chad mentioned are kind of our big step toward, it's an educational offering more than anything else. Like here's how you can do that, here's the things you can do with this. It's not a sales oriented thing, it's an educational oriented thing so people can understand what tools they have available, understand what products we have available to help them, and then go about their lives the way they want. >> Great. What are some of the most exciting applications coming down the pipeline in terms of this new way of banking that Capital One is showing us? >> Do you want to take this one? >> We've actually built our primary customer servicing application that our customers use every day native in the Cloud. And we're continuing to iterate on that so I think you don't have to look much further than our mobile app to see what we're super excited about and what we already offer to folks. And again, that's been enabled by our migration to the Cloud so it's going to continue to iterate, we continue to learn from our customers what they want, what new features they want, we continue to build those out. >> Great. >> And even from a call center perspective you guys are using Amazon connect, right? >> Yes we are. >> To man your call centers and that has enabled a different way to interact with the customer. You have more data at your fingertips. You're learning some of the patterns from your customer calls in a way that you've not been able to do that in the past. So enabling some of that data is also been effective and kind of servicing those accounts and having that very good interaction with your customer. >> Great. Chad, Jim, thank you so much for coming on the show it was really fun. >> Thank you. >> Thank you. Thanks. >> I'm Rebecca Knight, we will have more of the Cube's live coverage of the AWS Executive Summit coming up in just a little bit. (lively music)

>> [Announcer] From San Francisco, it's theCUBE covering OSIsoft PIWORLD 2018, brought to you by OSIsoft. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE, we're in downtown San Francisco at the OSIsoft PIWorld 2018. They've been doing it for like 28 years, it's amazing. We've never been here before, it's our first time and really these guys are all about OT, operational transactions. We talk about IoT and industrial IoT, they're doing it here. They're doing it for real and they've been doing it for decades so we're excited to have our next two guests. Tyler Duncan, he's a Technologist from Dell, Tyler, great to see you. >> Hi, thank you. >> He's joined by Ed Watson, the global account manager for channels for Osisoft. Or OSIsoft, excuse me. >> Glad to be here. Thanks, Jeff. >> I assume Dell's one of your accounts. >> Dell is one of my accounts as well as Nokia so-- >> Oh, very good. >> So there's a big nexus there. >> Yep, and we're looking forward to Dell Technology World next week, I think. >> Next week, yeah. >> I think it's the first Dell Technology not Dell EMC World with-- >> That's right. >> I don't know how many people are going to be there, 50,000 or something? >> There'll be a lot. >> There'll be a lot. (laughs) But that's all right, but we're here today... >> Yeah. >> And we're talking about industrial IoT and really what OSIsoft's been doing for a number of years, but what's interesting to me is from the IT side, we kind of look at industrial IoT as just kind of getting here and it's still kind of a new opportunity and looking at things like 5G and looking at things like IPE, ya know, all these sensors are now going to have IP connections on them. So, there's a whole new opportunity to marry the IT and the OT together. The nasty thing is we want to move it out of those clean pristine data centers and get it out to the edge of the nasty oil fields and the nasty wind turbine fields and crazy turbines and these things, so, Edge, what's special about the Edge? What are you guys doing to take care of the special things on the Edge? >> Well, a couple things, I think being out there in the nasty environments is where the money is. So, trying to collect data from the remote assets that really aren't connected right now. In terms of the Edge, you have a variety of small gateways that you can collect the data but what we see now is a move toward more compute at the Edge and that's where Dell comes in. >> Yeah, so I'm part of Dell's Extreme Scale and Structure Group, ESI, and specifically I'm part of our modular data center team. What that means is that for us we are helping to deploy compute out at the Edge and also at the core, but the challenges at the Edge is, you mentioned the kind of the dirty area, well, we can actually change that environment so that's it's not a dirty environment anymore. It's a different set of challenges. It may be more that it's remote, it's lights out, I don't have people there to maintain it, things like that, so it's not necessarily that it's dirty or ruggedized or that's it's high temperature or extreme environments, it just may be remote. >> Right, there's always this kind of balance in terms of, I assume it's all application specific as to what can you process there, what do you have to send back to process, there's always this nasty thing called latency and the speed of the light that just gets in the way all the time. So, how are you redesigning systems? How are you thinking about how much computing store do you put out on the Edge? How do you break up that you send back to central processing? How much do you have to keep? You know we all want to keep everything, it's probably a little bit more practical if you're keepin' it back in the data center versus you're tryin' to store it at the Edge. So how are you looking at some of these factors in designing these solutions? >> [Ed] Well, Jeff, those are good points. And where OSIsoft PI comes in, for the modular data center is to collect all the power cooling and IT data, aggregate it, send to the Cloud what needs to be sent to the Cloud, but enable Dell and their customers to make decisions right there on the Edge. So, if you're using modular data center or Telecom for cell towers or autonomous vehicles for AR VR, what we provide for Dell is a way to manage those modular data centers and when you're talking geographically dispersed modular data centers, it can be a real challenge. >> Yeah, and I think to add to that, there's, when we start lookin' at the Edge and the data that's there, I look at it as kind of two different purposes. There's one of why is that compute there in the first place. We're not defining that, we're just trying to enable our customers to be able to deploy compute however they need. Now when we start looking at our control system and the software monitoring analytics, absolutely. And what we are doing is we want to make sure that when we are capturing that data, we are capturing the right amount of data, but we're also creating the right tools and hooks in place in order to be able to update those data models as time goes on. >> [Jeff] Right. >> So, that we don't have worry about if we got it right on day one. It's updateable and we know that the right solution for one customer and the right data is not necessarily the right data for the next customer. >> [Jeff] Right. >> So we're not going to make the assumptions that we have it all figured out. We're just trying to design the solution so that it's flexible enough to allow customers to do whatever they need to do. >> I'm just curious in terms of, it's obviously important enough to give you guys your own name, Extreme Scale. What is Extreme Scale? 'Cause you said it isn't necessarily because it's dirty data and hardened and kind of environmentally. What makes an Extreme Scale opportunity for you that maybe some of your cohorts will bring you guys into an opportunity? >> Yeah so I think for the Extreme Scale part of it is, it is just doing the right engineering effort, provide the right solution for a customer. As opposed to something that is more of a product base that is bought off of dell.com. >> [Jeff] Okay. >> Everything we do is solution based and so it's listening to the customer, what their challenges are and trying to, again, provide that right solution. There are probably different levels of what's the right level of customization based off of how much that customer is buying. And sometimes that is adding things, sometimes it's taking things away, sometimes it's the remote location or sometimes it's a traditional data center. So our scrimpt scale infrastructure encompasses a lot of different verticals-- >> And are most of solutions that you develop kind of very customer specific or is there, you kind of come up with a solution that's more of an industry specific versus a customer specific? >> Yeah, we do, I would say everything we do is very customer specific. That's what our branch of Dell does. That said, as we start looking at more of the, what we're calling the Edge. I think ther6e are things that have to have a little more of a blend of that kind of product analysis, or that look from a product side. I'm no longer know that I'm deploying 40 megawatts in a particular location on the map, instead I'm deploying 10,000 locations all over the world and I need a solution that works in all of those. It has to be a little more product based in some of those, but still customized for our customers. >> And Jeff, we talked a little bit about scale. It's one thing to have scale in a data center. It's another thing to have scale across the globe. And, this is where PI excels, in that ability to manage that scale. >> Right, and then how exciting is it for you guys? You've been at it awhile, but it's not that long that we've had things like at Dupe and we've had things like Flink and we've had things like Spark, and kind of these new age applications for streaming data. But, you guys were extracting value from these systems and making course corrections 30 years ago. So how are some of these new technologies impacting your guys' ability to deliver value to your customers? >> Well I think the ecosystem itself is very good, because it allows customers to collect data in a way that they want to. Our ability to enable our customers to take data out of PI and put it into the Dupe, or put it into a data lake or an SAP HANA really adds significant value in today's ecosystem. >> It's pretty interesting, because I look around the room at all your sponsors, a lot of familiar names, a lot of new names as well, but in our world in the IT space that we cover, it's funny we've never been here before, we cover a lot of big shows like at Dell Technology World, so you guys have been doing your thing, has an ecosystem always been important for OSIsoft? It's very, very important for all the tech companies we cover, has it always been important for you? Or is it a relatively new development? >> I think it's always been important. I think it's more so now. No one company can do it all. We provide the data infrastructure and then allow our partners and clients to build solutions on top of it. And I think that's what sustains us through the years. >> Final thoughts on what's going on here today and over the last couple of days. Any surprises, hall chatter that you can share that you weren't expecting or really validates what's going on in this space. A lot of activity going on, I love all the signs over the building. This is the infrastructure that makes the rest of the world go whether it's power, transportation, what do we have behind us? Distribution, I mean it's really pretty phenomenal the industries you guys cover. >> Yeah and you know a lot of the sessions are videotaped so you can see Tyler from last year when he gave a presentation. This year Ebay, PayPal are giving presentations. And it's just a very exciting time in the data center industry. >> And I'll say on our side maybe not as much of a surprise, but also hearing the kind of the customer feedback on things that Dell and OSIsoft have partnered together and we work together on things like a Redfish connector in order to be able to, from an agnostic standpoint, be able to pull data from any server that's out there, regardless of brand, we're full support of that. But, to be able to do that in an automatic way that with their connector so that whenever I go and search for my range of IP addresses, it finds all the devices, brings all that data in, organizes it, and makes it ready for me to be able to use. That's a big thing and that's... They've been doing connectors for a while, but that's a new thing as far as being able to bring that and do that for servers. That, if I have 100,000 servers, I can't manually go get all those and bring them in. >> Right, right. >> So, being able to do that in an automatic way is a great enablement for the Edge. >> Yeah, it's a really refreshing kind of point of view. We usually look at it from the other side, from IT really starting to get together with the OT. Coming at it from the OT side where you have such an established customer base, such an established history and solution set and then again marrying that back to the IT and some of the newer things that are happening and that's exciting times. >> Yeah, absolutely. >> Yeah. >> Well thanks for spending a few minutes with us. And congratulations on the success of the show. >> Thank you. >> Thank you. >> Alright, he's Tyler, he's Ed, I'm Jeff. You're watching theCUBE from downtown San Francisco at OSIsoft PI WORLD 2018, thanks for watching. (light techno music)

>> Narrator: Live from Chicago, Illinois, it's theCUBE, covering VeeamOn 2018. Brought to you my Veeam. >> Welcome back to Chicago everybody. You're watching theCUBE, the leader in live tech coverage, and we are covering VeeamOn 2018, #VeaamOn. My name is Dave Vellante, and I'm here with my cohost Stuart Miniman, Duncan Epping is here, Chief Technologist, Storage and Availability at VMWare and the world's number one blogger in virtualization, Yellow Bricks, yellow-bricks.com. Duncan, thanks very much coming to theCUBE. Good to see you. >> No problem, my pleasure, it's been a while. I actually hoped to be on the show probably six, seven, eight years ago, I don't know how long it is, but I've watched many episodes. So it's great to be part of it. >> Well great, Duncan one of the biggest problems is you're so busy, every year at VM World you were totally booked up, so no thanks so much we're so glad we could do this. >> So Stu and I remember the peer insight we did many many years ago back when we had Boonyon on recently, and he was talking about when VMWare sort of created virtualization, it pushed the bottle neck around. It created a lot of stress on the storage systems. And WMWare for years dealt with that through API integration and the like and very well sort of covered. But I wonder if you could take us through your perspectives of the journey of storage at VMWare and generally, or specifically, and virtualization generally. >> Yeah, it's a good question. I think everyone that has been part of the community has faced all of the different challenges from a storage perspective. I mean, Stu, you now what kind of problem EMC had when VMWare first started doing virtualization. And I think the key reasons for these were fairly straightforward. When we started virtualization and we started leveraging shared storage systems, those shared storage systems were never designed with virtualization in the back of their minds. They were designed for physical workloads, maybe one or two machines connected to it, you know in larger volume it may be 10 or 15, but not 10 or 15 physical hosts with hundred of virtual machines. So we started noticing is that from a performance perspective systems were lagging, we were doing all sorts of things to the storage systems that they weren't expecting, virtual machine snapshots. They were seeing IO patterns that they had never seen before. Instead of sequential IO we had a lot of random IOs so we had to start doing different things from a storage perspective so as you said, we started with APIs, we had the vSPhere APIs for IO filtering, we have the Divi APIs, the array integration, so that we can offload some of the functionality, but of course on top of that what we started doing within VMWare is we started exploring what we could do smarter from a storage point from our stance. So not just looking at how we can help the ecosystem, but also what we can do from our perspective, so there were two main efforts over the past couple of years. The first one is virtual volumes. It has taken a while before the adoption ramped up. I think part of that is mainly because a lot of our customer base was still on vSphere 5.5. Now that we're starting to see broader adoption of vSphere 6.0 and actually 6.5 and 6.7, we're starting to see the adoption of stuff like virtual volumes go up as well. That is also due to the fact that our partners like Pure Storage, Nimble, HP with 3PAR has been pushing or have been pushing VVols tremendously. So they've done a great job, and we're starting to see a lot of customers adopting VVols, and that way we're getting around some of the limitations that we have from a traditional storage perspective. >> Explain that, what are customers telling you about the benefits that they're getting out of VVols and VVol and VVol adoption? >> Well, there's two main things. It kind of depends on what kind of problems you're facing, but a lot of customers come to us with management issues and scalability issues. From a scalability perspective we have larger customers that literally have thousands of volumes. If you look at an E6 cluster today you're limited in terms of the numbers of volumes you can connect to a cluster. So that's one thing. As soon as they start moving to VVols now they're not managing those individual volumes anymore but they're managing the storage system as a whole, and they start creating policies, and that's where the management aspect comes into play. So it becomes a lot easier to manage, because instead of having thousands of volumes to select from, they don't normally have to look at a spreadsheet, for instance, to figure out where to place a virtual machine, now they simply make a policy and the policy engine will figure out where to place that virtual machine. >> Dave: It sounds like cloud. >> It actually is, you know, the cloud version of, cloudified version of storage I would say. But it brings a lot of benefits. And the funny thing is that we've been talking about policies and policy engines for a long time, even in the cloud, but try to come up with one cloud that actually has a decent policy engine. Hardly anyone has that today. From a storage perspective I think storage policy based management framework that VMWare has is quite unique. Well now we're starting to see that popping up in other areas, and that's the strange thing about it. >> Always back to the software mainframe Stu. >> Yeah, and Duncan one of the things we've really seen, a transition for, it took us about a decade to try and fix storage in a virtualized environment, and today most things are built either understanding virtualization, or at least that's part of the puzzle, and then of course VVols led us into was the ability for vSANs. Help us kind of transition that threshold as to how that's just kind of a given underneath for vSAN and other solutions like it. >> Yeah, if you look at vSAN it has been around for a while. The beta was in 2013, as you guys know. We have a large adoption, at least we saw a large increase over the last couple of years, I would say the last two years. You guys have spoken with Yangbing before, so you know about the business side of vSAN, I'm not going to cover that, but if you look at it from a technology perspective we stared developing this 2008, 2009, that's when we started thinking about what we could do different from a storage perspective. There were already some companies doing something in the hyperverge space and we figured we could do something significantly different than they were doing. They had a storage solution that sat on top of the hypervisor, we own the hypervisor so we can create something that sits within the hypervisor, and that's when we started looking at including these different technologies, so we started looking in how can we introduce things like deduplication and compression? What can we do with for ROBO solutions? Can we do something like stretch clustering in an easy way? There are a lot of stretch cluster solutions out there, but if you look at a stretch clustering solution today it typically takes weeks to implement that. If you look at something like vSAN, it was our aim to actually to be able to deploy something like that from a storage perspective within hours instead of weeks, right? And we've been able to achieve that, and it has been a huge undertaking, but I think it's fair to say that it has been rather successful. >> All right, Duncan, help connect the dots to where we are here at VeeamOn. It's funny, I think Veeam started out heavily in virtualization, still heavily involved in virtualization, they've got a v in the beginning of their name. When I hear the keynote this morning, a lot of hyper, reminded me of before we had, before hyperconverge fully took over, VMWare tried to call it a hypervisor converge system around VMWare, so talk to us a little bit about data protection, the Veeam relationship and how that fits into things like vSAN and vSphere? >> Yeah I think, I talk to a lot of customers as a Chief Technologist, it's part of my role to talk to customers and have discussions about what's on top of their mind. Data protection is always one of those things that comes up. I would say it's always in the top three. Whenever you talk to a CIO, a CTO, protection of the data, availability of data, resiliency, reliability, it's fairly important. Veeam of course, for us, is a great partner. Primarily because of the simplicity of the features and the products that they offer. Whenever I talk to a customer and they explain how difficult it is to manage their backup and recovery solutions I always point them to a partner like Veeam simply because it's going to make their life a lot easier if you ask me. And I can see that Veeam is slowly transitioning. As you mentioned, the v is in front of the name. The v is in front of our name as well, but we know that it's not, the whole world isn't just VMWare and the whole world isn't just virtual. There's a lot of other different solutions out there, and actually Veeam's looking at other revenue streams as well. I would argue, though, if you're looking at something like the edge space which I think that more or less exploring at looking at things like IoT, there's going to be some form of virtualization within that, whether that's VMWare based or another solution of course is going to be the question. That is something that we'll need to figure out in the upcoming years, but I think there's a big opportunity out there. If you ask me, the keynote was really interesting. I kind of missed the end of details. I'm hoping that the closing keynote is going to give some more details on what they will be doing in the IoT space, how they see their solution evolving from that point of view because it's a market that's still being developed, but that's definitely going to be interesting. >> So Duncan it's interesting to hear you say that when you talk to customers data protection is in the top three, even amongst CIOs. It used to not be that way. Data protection was always a bolt on, it was an afterthought, it was kind of one size fits all. What's changed? >> Well I think the importance of the data has changed. If you look over the last 10 years whenever you talk to any company out there that has lost any significant amount of data they understand what the value was of the data that they were hosting. I think the big difference over the past 10 years is in the past we had applications like email, maybe some file services and that's it. But now everything revolves around applications, and that's also the shift that I'm seeing in the industry. Also from an IT perspective, right? In the past, over the past decade I think everyone has been focused on the infrastructure layer. If you look at something like VBlock, very much infrastructure focused. If you look at something like hyperconverged solutions, very much infrastructure focused. But now whenever we talk to customers, customers are more and more interested in what we can do for the application layer. What kind of benefits do we have for Exchange, for Oracle, for SAP, you name it? I think that's also a big change that's happening in the industry right now. One of the things from a technical perspective, and there may be others, but when VMWare really became prominent it was wonderful but we were reducing the number of physical resources, and the one workload that took a lot of physical resources was backup, and then sort of Veeam swept in and took advantage of that sea change. What's the technical constraint now when you think about things like multi cloud and SaaS and IoT, data's much more distributed, it's out of the control necessarily of a single platform. So from a technicals perspective, what's the big challenge and sort of the gate to architectures today? >> Well as you said, the distribution of data is the big challenge as it stands right now from a technical perspective. I think the biggest challenge that most of the players in this space, and not just Veeam, some other players as well, will have is trying to figure out how to control and manage their data. Other platforms are facing similar challenges. And no one really has solved this problem yet. We're starting to see some players in this space that have solutions that sit out in Azure, that sit out in Google Cloud, but it's a very challenging solution, and I think if you ask me, and this is something that I've said internally as well, the company that is capable of managing and owning the data is the company that's probably going to be most successful in the cloud war that's now happening. I think that's the most critical aspect. Workloads can move around, but data is very difficult to move around and own as well. >> Duncan one of the discontinuities we see in the marketplace that you mentioned earlier, wondering if you can talk to, in the enterprise in the data center, how do we get them to get to that next version? Comfortable with it, it's stable, it works. I look at the cloud, I'm running Microsoft Azure or AWS I'm running the version that they want. How do we help close that gap? Because from a security standpoint, from a features standpoint, we need to move there, but you know it seems to be just one of the greatest disconnects we see between kind of my data center and somebody else's cloud. >> That is a great question. I think we had a lot of challenges in the past. I think it's fair to say with vSphere 5.0 it was a great release, 5.5 among great releases. But the challenges that we have from an upgrade perspective was typically V centered and all of the components connected to it. It's not just the vSphere platform but if you look at the vSphere platform, the challenges that we had were all of the components integrating with it, whether that's something like vROps, VRA's, or VREalize Automation, but it could also be something like Evermar or maybe Veeam. So there were so many different components we had to take into account. So what we started doing within VMWare was simplifying the architecture from a vSPhere perspective. If you look at vSAN for instance, it used to be a solution where we had multiple functions spread out across different virtual machines. I'm now trying to bring that back into a single virtual machine again. Actually dumbing it down, making it easier to upgrade. So that is something that is actively happening within VMWare, and it is something that we started with 6.0, and that's also the reason why we see the adoption from 6.0 to 6.5 and 6.5 to 6.7, is at a must faster pace than 5, in the 5 code stream, so 5 to 5.1, for instance, took a lot longer for a lot of customers or 5.1 to 6.0, took extremely long for a lot of customers. It's the key reason is complexity from our infrastructure stand. While we're changing that, we're evolving that in the upcoming years. >> Duncan it's the last question here, but as the technologist, things that you're looking at that are exciting to you, that you know, get your juices flowing? >> Yeah, that's an interesting one because it's something that I've been thinking about recently. I've been doing vSphere for the last, well wasn't even called vSphere back then, but I've been doing this for the last 12 years, virtualization. Thirteen years maybe something like that. At least as a consultant and then as a technologist and technical marketing, but recently I'm starting to look more and more at the edge space. For computing, IoT, I think that's a really interesting space, especially because there isn't really significant market. Well, there is a significant market out there, but there isn't really one player out there that really stands out. No one has really figured out what customers would like to do with it and how our customers are going to use it. So the edge computing space and IoT's a really interesting thing and especially because of the distributed aspect is one of the things that I've been always been passionate about, vSphere clusters, which is a distributed mechanism. So distributed computing is definitely something that has my interest. >> All right if you care about virtualization, VMWare, follow the yellow brick road, yellow-bricks.com. Duncan, thanks very much for coming on theCUBE. >> Thanks for having me guys. >> You're welcome. All right, keep it right there buddy. We'll be back with our next guest. You're watching theCUBE live from Chicago, VeeamOn 2018. We'll be right back. (techno music)

>> Announcer: From San Francisco, it's theCUBE covering OSIsoft PIWORLD 2018, brought to you by OSIsoft. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE, we're in downtown San Francisco at the OSIsoft PIWorld 2018. They've been doing it for like 28 years, it's amazing. We've never been here before, it's our first time and really these guys are all about OT, operational transactions. We talk about IoT and industrial IoT, they're doing it here. They're doing it for real and they've been doing it for decades so we're excited to have our next two guests. Tyler Duncan, he's a Technologist from Dell, Tyler, great to see you. >> Hi, thank you. >> He's joined by Ed Watson, the global account manager for channels for Osisoft. Or OSIsoft, excuse me. >> Glad to be here. Thanks, Jeff. >> I assume Dell's one of your accounts. >> Dell is one of my accounts as well as Nokia so-- >> Oh, very good. >> So there's a big nexus there. >> Yep, and we're looking forward to Dell Technology World next week, I think. >> Next week, yeah. >> I think it's the first Dell Technology not Dell EMC World with-- >> That's right. >> I don't know how many people are going to be there, 50,000 or something? >> There'll be a lot. >> There'll be a lot. (laughs) But that's all right, but we're here today... >> Yeah. >> And we're talking about industrial IoT and really what OSIsoft's been doing for a number of years, but what's interesting to me is from the IT side, we kind of look at industrial IoT as just kind of getting here and it's still kind of a new opportunity and looking at things like 5G and looking at things like IPE, ya know, all these sensors are now going to have IP connections on them. So, there's a whole new opportunity to marry the IT and the OT together. The nasty thing is we want to move it out of those clean pristine data centers and get it out to the edge of the nasty oil fields and the nasty wind turbine fields and crazy turbines and these things, so, Edge, what's special about the Edge? What are you guys doing to take care of the special things on the Edge? >> Well, a couple things, I think being out there in the nasty environments is where the money is. So, trying to collect data from the remote assets that really aren't connected right now. In terms of the Edge, you have a variety of small gateways that you can collect the data but what we see now is a move toward more compute at the Edge and that's where Dell comes in. >> Yeah, so I'm part of Dell's Extreme Scale and Structure Group, ESI, and specifically I'm part of our modular data center team. What that means is that for us we are helping to deploy compute out at the Edge and also at the core, but the challenges at the Edge is, you mentioned the kind of the dirty area, well, we can actually change that environment so that's it's not a dirty environment anymore. It's a different set of challenges. It may be more that it's remote, it's lights out, I don't have people there to maintain it, things like that, so it's not necessarily that it's dirty or ruggedized or that's it's high temperature or extreme environments, it just may be remote. >> Right, there's always this kind of balance in terms of, I assume it's all application specific as to what can you process there, what do you have to send back to process, there's always this nasty thing called latency and the speed of the light that just gets in the way all the time. So, how are you redesigning systems? How are you thinking about how much computing store do you put out on the Edge? How do you break up that you send back to central processing? How much do you have to keep? You know we all want to keep everything, it's probably a little bit more practical if you're keepin' it back in the data center versus you're tryin' to store it at the Edge. So how are you looking at some of these factors in designing these solutions? >> Ed: Well, Jeff, those are good points. And where OSIsoft PI comes in, for the modular data center is to collect all the power cooling and IT data, aggregate it, send to the Cloud what needs to be sent to the Cloud, but enable Dell and their customers to make decisions right there on the Edge. So, if you're using modular data center or Telecom for cell towers or autonomous vehicles for AR VR, what we provide for Dell is a way to manage those modular data centers and when you're talking geographically dispersed modular data centers, it can be a real challenge. >> Yeah, and I think to add to that, there's, when we start lookin' at the Edge and the data that's there, I look at it as kind of two different purposes. There's one of why is that compute there in the first place. We're not defining that, we're just trying to enable our customers to be able to deploy compute however they need. Now when we start looking at our control system and the software monitoring analytics, absolutely. And what we are doing is we want to make sure that when we are capturing that data, we are capturing the right amount of data, but we're also creating the right tools and hooks in place in order to be able to update those data models as time goes on. >> Jeff: Right. >> So, that we don't have worry about if we got it right on day one. It's updateable and we know that the right solution for one customer and the right data is not necessarily the right data for the next customer. >> Jeff: Right. >> So we're not going to make the assumptions that we have it all figured out. We're just trying to design the solution so that it's flexible enough to allow customers to do whatever they need to do. >> I'm just curious in terms of, it's obviously important enough to give you guys your own name, Extreme Scale. What is Extreme Scale? 'Cause you said it isn't necessarily because it's dirty data and hardened and kind of environmentally. What makes an Extreme Scale opportunity for you that maybe some of your cohorts will bring you guys into an opportunity? >> Yeah so I think for the Extreme Scale part of it is, it is just doing the right engineering effort, provide the right solution for a customer. As opposed to something that is more of a product base that is bought off of dell.com. >> Jeff: Okay. >> Everything we do is solution based and so it's listening to the customer, what their challenges are and trying to, again, provide that right solution. There are probably different levels of what's the right level of customization based off of how much that customer is buying. And sometimes that is adding things, sometimes it's taking things away, sometimes it's the remote location or sometimes it's a traditional data center. So our scrimpt scale infrastructure encompasses a lot of different verticals-- >> And are most of solutions that you develop kind of very customer specific or is there, you kind of come up with a solution that's more of an industry specific versus a customer specific? >> Yeah, we do, I would say everything we do is very customer specific. That's what our branch of Dell does. That said, as we start looking at more of the, what we're calling the Edge. I think ther6e are things that have to have a little more of a blend of that kind of product analysis, or that look from a product side. I'm no longer know that I'm deploying 40 megawatts in a particular location on the map, instead I'm deploying 10,000 locations all over the world and I need a solution that works in all of those. It has to be a little more product based in some of those, but still customized for our customers. >> And Jeff, we talked a little bit about scale. It's one thing to have scale in a data center. It's another thing to have scale across the globe. And, this is where PI excels, in that ability to manage that scale. >> Right, and then how exciting is it for you guys? You've been at it awhile, but it's not that long that we've had things like at Dupe and we've had things like Flink and we've had things like Spark, and kind of these new age applications for streaming data. But, you guys were extracting value from these systems and making course corrections 30 years ago. So how are some of these new technologies impacting your guys' ability to deliver value to your customers? >> Well I think the ecosystem itself is very good, because it allows customers to collect data in a way that they want to. Our ability to enable our customers to take data out of PI and put it into the Dupe, or put it into a data lake or an SAP HANA really adds significant value in today's ecosystem. >> It's pretty interesting, because I look around the room at all your sponsors, a lot of familiar names, a lot of new names as well, but in our world in the IT space that we cover, it's funny we've never been here before, we cover a lot of big shows like at Dell Technology World, so you guys have been doing your thing, has an ecosystem always been important for OSIsoft? It's very, very important for all the tech companies we cover, has it always been important for you? Or is it a relatively new development? >> I think it's always been important. I think it's more so now. No one company can do it all. We provide the data infrastructure and then allow our partners and clients to build solutions on top of it. And I think that's what sustains us through the years. >> Final thoughts on what's going on here today and over the last couple of days. Any surprises, hall chatter that you can share that you weren't expecting or really validates what's going on in this space. A lot of activity going on, I love all the signs over the building. This is the infrastructure that makes the rest of the world go whether it's power, transportation, what do we have behind us? Distribution, I mean it's really pretty phenomenal the industries you guys cover. >> Yeah and you know a lot of the sessions are videotaped so you can see Tyler from last year when he gave a presentation. This year Ebay, PayPal are giving presentations. And it's just a very exciting time in the data center industry. >> And I'll say on our side maybe not as much of a surprise, but also hearing the kind of the customer feedback on things that Dell and OSIsoft have partnered together and we work together on things like a Redfish connector in order to be able to, from an agnostic standpoint, be able to pull data from any server that's out there, regardless of brand, we're full support of that. But, to be able to do that in an automatic way that with their connector so that whenever I go and search for my range of IP addresses, it finds all the devices, brings all that data in, organizes it, and makes it ready for me to be able to use. That's a big thing and that's... They've been doing connectors for a while, but that's a new thing as far as being able to bring that and do that for servers. That, if I have 100,000 servers, I can't manually go get all those and bring them in. >> Right, right. >> So, being able to do that in an automatic way is a great enablement for the Edge. >> Yeah, it's a really refreshing kind of point of view. We usually look at it from the other side, from IT really starting to get together with the OT. Coming at it from the OT side where you have such an established customer base, such an established history and solution set and then again marrying that back to the IT and some of the newer things that are happening and that's exciting times. >> Yeah, absolutely. >> Yeah. >> Well thanks for spending a few minutes with us. And congratulations on the success of the show. >> Thank you. >> Thank you. >> Alright, he's Tyler, he's Ed, I'm Jeff. You're watching theCUBE from downtown San Francisco at OSIsoft PI WORLD 2018, thanks for watching. (light techno music)

>> Announcer: Live from the Javits Center in New York City, it's theCUBE. Covering Inforum 2017. Brought to you buy Infor. >> Welcome back to Inforum 2017 everybody. This is theCUBE, the leader in live tech coverage. Duncan Angove is here, the President of Infor and a Cube alum. Good to see you again Duncan. >> Hey, afternoon guys. >> So it's all coming together right? When we first met you guys down in New Orleans, we were sort of unpacking, trying to squint through what the strategy is. Now we call it the layer cake, we were talking about off camera, really starting to be cohesive. But set up sort of what's been going on at Infor. How are you feeling? What the vibe is like? >> Yeah it's been an amazing journey over the last six years. And, um, you know, all the investments we put in products, as you know, we said to you guys way back then, we've always put products at the center. Our belief is that if you put innovation and dramatic amounts of investment in the core product, everything else ends up taking care of itself. And we put our money where our mouth was. You know, we're a private company, so we can be fairly aggressive on the level of investment we put into R&D and it's increased double digit every single year. And I think the results you've seen over the last two years, in terms of our financials is that, you know the market's voting in a way that we're growing double digits dramatically faster than our peers. So that feels pretty good. >> So Jim is, I know, dying to get into the AI piece, but lets work our way up that sort of strategy layer cake with an individual had a lot to do with that. So you know, you guys started with the decision of Micro-verticals and you know the interesting thing to us is you're starting to see some of the big SI's join in. And I always joke, that they love to eat at the trough. But you took a lot of the food away by doing that last mile. >> Yeah. >> But now you're seeing them come in, why is that? >> You know I think the whole industry is evolving. And the roles that different and the valor that different companies in that ecosystem play, whether it's an enterprise software vendor or it's a systems integrator. Everything's changing. I mean, The Cloud was a big part of that. That took away tasks that you would sometimes see a systems integrator doing. As larger companies started to build more completely integrated suites, that took away the notion that you need a systems integrator to plug all those pieces together. And then the last piece for us was all of the modifications that were done to those suites of software to cover off gaps in industry functionality or gaps in localizations for a country, should be done inside the software. And you can only do that if you have a deep focus, by industry on going super, super deep at a rapid rate on covering out what we call these last malfeatures. So that means that the role of the systems integrators shifted. I mean they've obviously pivoted more recently into a digital realm. They've all acquired digital agencies. And having to adapt to this world where you have these suites of software that run in The Cloud that don't need as much integration or as much customization. So we were there you know five, six years ago. They weren't quite there. It was still part of this symbiotic relationship with other large vendors. And I think now, you know, the reason for the first time we've got guys like Accenture, and Deloitte, and Capgemini, and Grant Thornton here, is that they see that. And their business model's evolved. And you know those guys obviously like to be where they can win business and like to build practices around companies they see winning business. So the results we've seen and the growth we've seen over the last two to three years, obviously that's something they want a piece of. So I think it's going to work out. >> Alright so Jim, you're going to have to bear with me a second 'cause I want to keep going up the stack. So the second big milestone decision was AWS. >> Duncan: Yeah. >> And we all understand the benefits of AWS. But there's two sides to that cone and one is, when you show your architectural diagram, there's a lot of AWS in there. There's S3, there's DynamoDB, I think I saw Kinesis in there. I'm sure there's some Ec2 and other things. And it just allows you to focus on what you do best. At the same time, you're getting an increasingly complex data pipeline and ensuring end-to-end performance has to be technically, a real challenge for you. So, I wanted to ask you about that and see if you could comment and how you're managing that. >> Yeah so, I mean obviously, we were one of the first guys to actually go all in on Amazon as a Cloud delivery platform. And obviously others now have followed. But we're still one of their top five ISV's on there. The only company that Amazon reps actually get compensated on. And it's a two way relationship right? We're not just using them as a Cloud delivery partner. We're also using some of their components. You know you talked about some of their data storage components. We're also leverage them for AI which we'll get into in a second. But it's a two way relationship. You know, they run our asset management facility for all of their data centers globally. We do all the design and manufacturing of their drones and robots. We're partnered with them on the logistic side. So it's a deep two way relationship. But to get to your question on just sort of the volume and the integration. We work in integrations with staggering volumes right? I mean, retail, you're dealing with billions and billions of data points. And we'll probably get into that in a second you know. The whole asset management space, is one of the fastest growing applications we have. Driven by cycle dynamics of IoT and explosion in device data and all of that. So we've had for a very, very long time, had to figure out an efficient way to move large amounts of data that can be highly chatty. And do it in an efficient way. And sometimes it's less about the pipes in moving it around, it's how you ingest that data into the right technology from a data storage perspective. Ingest it and then turn it into insights that can power analytics or feed back into our applications to drive execution. Whether it's us predicting maintenance failure on a pump and then feeding that back into asset management to create a work order and schedule an engineer on it. Right? >> That's not a trivial calculus. Okay, now we're starting to get into Jim's wheelhouse, which is, you call it, I think you call it the "Age of Network Intelligence". And that's the GT Nexus acquisition. >> Yeah. >> To us it's all about the data. I think you said 18 years of transaction history there. So, talk about that layer and then we'll really get into the data the burst piece and then of course the AI. >> Yeah, so there were two parts to why we called it "The Age of Network Intelligence". And it's not often that technology or an idea comes along in human history that actually bends the curve of progress right? And I think that we said it on stage, the steam engine was one of those and it lead to the combustion engine, it lead to electricity and it lead to the internet and the mobile phone and it all kind of went. Of course it was invented by a British man, an Englishman you know? That doesn't happen very often right? Where it does that. And our belief is that the rise of networks, coupled with the rise of artificial intelligence, those two things together will have the same impact on society and mankind. And it's bigger than Infor and bigger than enterprise software, it's going to change everything. And it's not going to do it in a linear way. It's going to be exponential. So the network part of that for us, from an Infor perspective was, yes it was about the commerce network, which was GT Nexus, and the belief that almost every process you have inside an enterprise at some point has to leave the enterprise. You have to work with someone else, a supplier or a customer. But ERP's in general, were designed to automate everything inside the four walls. So our belief was that you should extend that and encompass an entire network. And that's obviously what the GT Nexus guys spent 18 years building was this idea of this logistics network and this network where you can actually conduct trade and commerce. They do over 500 billion dollars a year on that network. And we believe, and we've announced this as network CloudSuites, that those two worlds will blur. Right? That ultimately, CloudSuites will run completely nakedly on the network. And that gives you some very, very interesting information models and the parallel we always give is like a Linkedin or a Facebook. On Linkedin, there's one version of the application. Right? There's one information model where everyone's contact information is. Everyone's details about who they are is stored. It's not stored in all these disparate systems that need to be synchronized constantly. Right? It's all in one. And that's the power of GT Nexus and the commerce network, is that we have this one information model for the entire supply chain. And now, when you move the CloudSuite on top of that, it's like this one plus one is five. It's a very, very powerful idea. >> Alright Jim, chime in here, because you and I both excited about the burst when we dug into that a little bit. >> Yes. >> Quite impressed actually. Not lightweight vis, you know? It's not all sort of BI. >> Well the next generation of analytics, decision support analytics that infuse and inform and optimize transactions. In a distributed value chain. And so for the burst is a fairly strong team, you've got Brad Peters who was on the keynote yesterday, and of course did the pre-briefing for the analyst community the day before. I think it's really exciting, the Coleman strategy is really an ongoing initiative of course. First of all, on the competitive front, all of your top competitors in this very, I call it a war of attrition in ERP. SAP, Oracle and Microsoft have all made major investments on going in AI across their portfolios. With a specific focus on informing and infusing their respective ERP offerings. But what I conceived from what Infor's announced with the Coleman strategy, is that yours is far more comprehensive in terms of taking it across your entire portfolio, in a fairly accelerated fashion. I mean, you've already begun to incorporate, Coleman's already embedded in several of your vertical applications. First question I have for you Duncan, as I was looking through all the discussions around Coleman, when will this process be complete in terms of, "Colemanizing", is my term? "Colemanizing" the entire CloudSuite and of course network CloudSuite portfolio. That's a huge portfolio. And it's like you got fresh funding, a lot of it, from Koch industries. To what extent can, at what point in the next year or two, can most Infor customers have the confidence that their cloud applications are "Colemanized"? And then when will, if ever, Coleman AI technology be made available to those customers who are using your premises based software packages? >> So yeah, we could spend a long time talking about this. The thing about Coleman and RAI and machine learning capabilities is that we've been at work on it for a while. And you know we created the dynamic science labs. Our team of 65 Ph.D.'s based up in M.I.T. got over three and a half four years ago. And our differentiation versus all the other guys you mentioned is that, two things, one, we bring a very application-centric view of it. We're not trying to build a horizontal, generic, machine learning platform. In the same way that we- >> Yeah you're not IBM with Watson, all that stuff. >> Yeah, no, no. Or even Auricle. >> Jim: Understood. >> Or Microsoft. >> Jim: Nobody expects you to be. >> No, you know, and we've always been the guys that have worked for the Open Source community. Even when you look at like, we're the first guys to provide a completely open source stack underneath our technology with postscripts. We don't have a dog in the hunt like most of the other guys do. Right? So we tap in to the innovation that happens in the Open Source community. And when you look at all the real innovation that's happening in machine learning, it's happening in the Open Source Community. >> Jim: Yes. >> It's not happening with the old legacy, you know, ERP guys. >> Jim: Pencer, Flow and Spark and all that stuff. >> Yeah, Google, Apple, the GAFA. >> Yeah. >> Right? Google, Apple, Facebook, those are the guys that are doing it. And the academic community is light years ahead on top of that of what these other guys will do. So that's what we tap into right? >> Are you tapping into partners like AWS? 'Cause they've obviously, >> Duncan: Absolutely >> got a huge portfolio of AI. >> Yeah, so we. >> Give us a sense whether you're going to be licensing or co-developing Coleman technologies with them going forward. >> Yeah so we obviously we have NDA's with them, we're deeply inside their development organization in terms of working on things. You know, our science is obviously presented to them around ideas we think they need to go. I mean, we're a customer of their AI frameup to machine learning and we're testing it at scale with specific use cases in industries, right? So we can give them a lot of insights around where it needs to go and problems we're trying to solve. But we do that across a number of different organizations and we've got lots and lots of academic collaborations that happen on around all of the best universities that are pushing on this. We've even received funding from DAPA in certain cases around things that we're trying to solve for. You know quietly we've made some machine-learning acquisitions over the last five, six years. That have obviously brought this capability into it. But the point is we're going to leverage the innovation that happens around these frameworks. And then our job is understanding the industries we're in and that we're an applications company, is to bring it to life in these applications in a seamless way, that solves a very specific problem in an industry, in a powerful and unique way. You know on stage I talked about this idea of bringing this AI first mindset to how we go about doing it. >> So it's important, if I can interject. This is very important. This is Infor IP, the serious R&D that's gone into this. It's innovation. 'Cause you know what your competitors are going to say. They're going to deposition and say, oh, it's Alexa on steroids. But it's not. It's substantial IP and really leveraging a lot of the open source technologies that are out there. >> Yeah. So you know, I talked about there were four components to Coleman, right? And the first part of it was, we can leverage machine-learning services to make the CloudSuites conversational. So they can chat, and talk, and see, and hear, and all of that. And yeah, some of those are going to use the technology that sits behind Alexa. And it's available in AWS's Alexa as you guys know. But that's only really a small part of what we're doing. There are some places where we are looking at using computer vision. For example, automated inspection of car rental returns, is one area. We're using it for quality management pilot at a company that normally has humans inspect something on a production line. That kind of computer-vision, that's not Alexa, right? It's you know, I gave the example of image recognition. Some of it can leverage AWS's framework there. But again, we're always going to look for the best platform and framework out there to solve the specific problem that we're trying to solve. But we don't do it just for the sake of it. We do it with a focus to begin with, with an industry. Like, where's a really big problem we can solve? Or where is there a process that happens inside an application today that if you brought an AI first mindset to it, it's revolutionary. And we use this phrase, "the AI is the UI". And we've got some pretty good analogies there that can help bring it to life. >> And I like your approach for presenting your AI strategy, in terms of the value it delivers your customers, to business. You know, there's this specter out there in the culture that AI's going to automate everybody out of a job. Automation's very much a big part of your strategy but you expressed it well. Automating out those repetitive functions so that human beings, you can augment the productivity of human beings, free them up for more value-added activities and then augment those capabilities through conversational chat box. And so forth, and so on. Provide you know, in-application, in process, in context, decision support with recommendations and all that. I think that's the exact right way to pitch it. One of the things that we focus on and work on in terms of application development, disciplines that are totally fundamental to this new paradigm. Recommendation engines, recommender systems, in line to all application. It's happening, I mean, Coleman, that really in many ways, Coleman will be the silent, well not so silent, but it'll be the recommendation engine embedded inside all of your offerings at some point. At least in terms of the strategy you laid out. >> Yeah, no, absolutely right I mean. It's not just about, we all get hung up on machine-learning and deep learning 'cause it's the sexy part of AI, right? But there's a lot more. I mean, AI, all the way back, you can go all the way back to Socrates and the father of logic right? I mean, some of the things you can do is just based on very complex rules and logic. And what used to be called process automation right? And then it extends all the way to deep learning and neural networks and so on. So one of the things that Coleman also does, is it unifies a lot of this technology. Things that you would normally do for prediction or optimization, and optimization normally is the province of operations research guys right? Which again it's a completely different field. So it unifies all of that into one consistent platform that has all of that capability into it. And then it exposes it in a consistent way through our API architecture. So same thing with bots. People always think chat bots are separate. Well that too is unified inside Coleman. So it's a cohesive platform but again, industry focused. >> What's your point of view on developers? And how do you approach the development community and what's your strategy there? >> Yeah, I mean, it's critical right? So we've always, I mean, hired an incredible number of application engineers every year. I think the first 12 months we were here, we hired 1800 right? 'Cause you know, that's kind of what we do. So we believe hugely in smarts. And it sounds kind of obvious, but experience can be learned, smarts is portable. And we have a lot of programs in place with universities. We call it the Education Alliance Program. And I think we have up to 32 different universities around the world where we're actually influencing curriculum, and actually bringing students right out of there. Using internships during the year and then actually bringing them into our development organization. So we've got a whole pipeline there. I mean that's critical that we have access to those. >> And what about outside your four walls, or virtual walls have been four? Is there a strategy to specifically pursue external developers and open up a PAZ layer? >> Yeah we do. >> Or provide an STK for Coleman for example, for developers. >> Yeah so we did, as part of our Infor Operating Service update. Which is, you know, the name for our unified technology platform. We did announce Mongoose platform was a service. Our Mongoose pass. >> Host: Oh Mongoose, sure. >> So that now is being delivered as a platform with a service for application development. And it's used in two ways. It's used for us to build new applications. It's a very mobile-first type development framework too. And obviously Hook and Loop had a huge influence in how that ships. The neat thing about it, is that it ships with plumbing into ION API, plumbing into our security layer. So customers will use it because it leverages our security model. It's easy to access everything else. But it's also used by our Hook and Loop digital team. So those guys are going off and they're building completely differentiated curated apps for customers. And again, they're using Mongoose. So I think between ION API's and between all the things you get in the Infor Operating Service, and Mongoose, we've got a pretty good story around extensibility and application development. As it relates to an STK for Coleman, we're just working through that now. Again, our number one focus is to build those things into the applications. It's a feature. The way most companies have approached optimization and machine learning historically, is it's a discrete app that you have to license. And it's off to the side and you integrate it in. We don't think that's the right way of doing it. Machine-learning and artificial intelligence, is a platform. It's an enabler. And it fuses and changes every part of the CloudSuite. And we've got a great example on how you can rethink demand forecasting, demand planning. Every, regardless of the industry we serve, everyone has to predict demand right? It's the basis for almost every other decision that happens in the enterprise. And, how much to make, how many nurses to put on staff, all of that, every industry, that prediction of demand. And the thinking there really hasn't changed in 20, 30 years. It really hasn't. And some of that's just because of the constraints with technology. Storage, compute, all of that. Well with the access we have to the elastic super-computing now and the advancements in sort of machine-learning and AI, you can radically rethink all of that, and take what we call and "AI First" approach, which is what we've done with building our brand new demand prediction platform. So the example we gave is, you think about when early music players came along on the internet right? The focus was all around building a gorgeous experience for how to build a playlist. It was drag and drop, I could do it on a phone, I could share it with people and it showed pictures of the album art. But it was all around the usability of making that playlist better. Then guys like Spotify and Pandora came around and it took an AI First approach to it. And the machine builds your playlist. There is no UI. AI is the UI. And it can recommend music I never knew I would've liked. And the way it does that, comes back to the data. Which is why I'm going to circle back to Infor here in a second. Is that, it breaks a song down into hundreds if not thousands of attributes about that song. Sometimes it's done by a human, sometimes it's even done by machine listening algorithms. Then you have something that crawls the web, finds music reviews online, and further augments it with more and more attributes. Then you layer on top of that, user listening activity, thumbs up, thumbs down, play, pause, skip, share, purchase. And you find, at that attribute level, the very lowest level, the true demand drivers of a song. And that's what's powering it right? Just like you see with Netflix for movies and so on. Imagine bringing that same thought process into how you predict demand for items, that you've never promoted before. Never changed the price before. Never put in this store before. Never seen before. >> The cold start problem in billing recommendation areas. >> Exactly right, so, that's what we mean by AI First. It's not about just taking traditional demand planning approaches and making it look sexier and putting it on an iPad right? Rethink it. >> Well it's been awesome to watch. We are out of time. >> Yeah, we're out of time. >> Been awesome to watch the evolution, >> We could go on and on with this yeah. >> of Infor as it's really becoming a data company. And we love having executives like you on. >> Yeah >> You know, super articulate. You got technical chops. Congratulations on the last six years. >> Thanks. >> The sort of quasi-exit you guys had. >> Great show, amazing turnout. >> And look forward to watching the next six to 10. So thanks very much for coming out. >> Brilliant, thank you guys. Alright thank you. >> Alright keep it right there everybody, we'll be back with our next guest, this is Inforum 2017 and this is theCUBE. We'll be right back. (digital music)

>>from the bellagio Hotel >>in Las Vegas. >>It's the >>cube covering >>Ui Path forward. >>Four brought to >>you by Ui Path. >>Welcome back to Las Vegas. The cube is here. We've been here for two days covering Ui Path Forward for lisa martin here with David Monty. We've talked about automation and many industries. Now this segment is going to focus on automation and healthcare. We've got two guests joining us Jim Petrosea Cto of Blue Cross, Blue Shield and Gadget. Dhaliwal. The global C. I. O. Industry lead at you. I pass guys welcome to the program. Thank you. So let's start unpacking from the CTO level and the ceo level the agenda for automation. Jim let's start with you. What does that look like >>for us. It's actually pretty strategic and part of as we think about digital and what digital transformation means, it actually plays a pretty key role. Um There are a lot of processes that can be very manual within a big organization like Blue cross and Blue shield and to be able to streamline that and take away kind of what I would call the mundane work. Right? The the you know, going through a spreadsheet and then typing it into the screen, there are a lot of processes like that that are legacy. But what if you could take that away um and actually create a better work experience for the people that work there right? And and focus on higher value type uh type things and it's really key. And it really It goes down to our our business folks right? There are a lot of things we can drive with automation. We started a program um in 2019. Um that's been quite successful. We now have 250 box, we measure what we call annualized efficiency gains. So how much efficiency are we getting by these bots? So the bots are doing um this repetitive work that people would do. Um And what we're finding is, you know, we've got about $11 million in any wise efficiency gain through the process and we're just getting started. Um But we're all we're not stopping there too though, we're enabling citizen developers. So we're saying, hey business, if you want to automate, you know, parts of your job, we're gonna help you do that. So we've got about 60 people that were training. Um We run bad Ethan's where they come together and they actually create bots uh And it's really really creating some some impact and buzz in our business >>anywhere from your lens, where does automation fit within the C. I. O. S. Agenda? And how do you work together in unison with the C. T. O. To help roll this out across the enterprise? >>Yeah, no, definitely. And in fact as a part of introduction, I can actually share that. How I'm wearing a Ceo had within your path since I'm just joining join path and I'm actually now helping a client ceos in their automation strategy but I was a deputy ceo in my prior role at L. A. County where actually I ran the automation strategy. So if we look at from our organization perspective B complex as L. A County which is such a Federated organization. From a Ceo perspective, the way we look at the strategy is it's always driven by the business goals of the city or a county and we typically drive into three different areas. One is how we can transform our operational processes so that we can save the tax dollars. It's all about doing more with the less dollars. And then second is about how we can transform our residents experience because end of the day it is all about how we can improve the quality of life for our residents. So we've got 10 million people for L. A. County, the largest populous county in us. So it was an uphill task to serve that such a diverse population need and that the third area is about how to transform the new business models because as we are moving away from a government centric approach to the residents centric approach, you really need to come up with a new digital solutions. And Ceo is in the center of all these three elements when you look at it. So it's a very appear to us to keep keep improving your efficiency and then at a time keep adding the new digital solutions and that's where automation strategy is kind of a horizontal strategy which enables all these components. So what I hear from >>that is alignment with the business. Yeah. Right. Change management. Absolutely. That's like really fundamental and then see IOS this this agent of transformation uh you can see or she has a horizontal purview across the organization now now jim the cto role is the automation at blue cross blue shield lead by you or you there to make sure the technology plugs into your enterprise architecture. What's your shoulder? >>You know? Uh my my role is really to drive uh what I'll call technology enabled business change. Right. So I actually uh started our our automation journey uh at hc sc and I did that by partnering with our business. Um There was actually a lot of buzz around automation and there were actually some small pockets of it, none of it was enterprise scale. Um Right. And we really wanted to go big in this and and working with the business sponsors, they saw value in it. Um and we've you know, we've generated um a lot of uh efficiency, better quality of work because of it but but I very closely had a partner with our business, we have a committee that is lead of business folks that I facilitate. So I view my role as an enabler, um we have to communicate the change management pieces is huge. Uh the education just having a common vernacular on what is automation mean, Right, because everybody interpreted it differently um and then being able to do it at an enterprise scale is quite challenging. Um You know, I I really enjoyed um one of the key notes, I don't know if you had a chance to see shankar by Duncan from the hidden brain, right? But he talked a lot about the brain aspect and how do you get people to change? And and that's a large part of it. There's a lot about technology, but there's really a lot about being a change agent um and and really working very closely with your business, >>how does one measure? I'm hearing a lot time saved. Our saved. How does one measure that and quantify the dollar impact, which by the way, I'm on record as saying the soft dollars are way bigger. And but when you're talking to the, you know, the bottom line CFO and it's all about, you know, the cash flow, whatever is, how do you measure that? >>I can take it. So we, what we do is as we define these use cases right? We we go through an actual structure product process where we we gather them. Um we then rate them and we actually prioritize them based on those that are going to have the greatest impact. Um and we can tell based on, you know, what is the manual effort today. So we understand there are X number of people that do this X number of days and we think this body can take that some load off of them. Right? Um So we we go in with the business case. Um And then the Ui Path platform actually allows us to measure well, how much is that pot running? Right. So we can actually sit there and say, well we wanted that thing to run 10 hours a day and it did and it's generated this kind of efficiency because otherwise the human would have had to do that work. >>So the business case is kind of redeploying >>human. It really is is really maximizing human capital and make and and you know really using because the bots do repetitive stuff really well. They don't do higher level thinking and and we don't view it as replacing people, we view it as augmenting and actually making them more efficient and more effective at what, how do you get the dollars out of that? Well, a couple of ways. Right. And so one of the things we've we've done is we we create and measure the efficiency our business users and financed by the way is one of our bigger ones. And the CFO is one of the sponsors of the program, um can decide how to reinvest it in a lot of cases it is actually cost avoidance as we grow, literally being able to grow without adding staff. I mean that's very measurable. Um in some cases it is actually taking, you know cost out um in in certain cases, but a lot of times that's just through attrition, right? You don't back fill positions, you let it happen naturally. Um and and then there's just things that happen to your business that you have to respond to give you a great example, state of texas, um passes what's the equivalent of the no surprise attack. But they did it there before the federal government did it. Um but it requires a lot of processes to be put in place, because now you have providers and payers having to deal with disputes, right? It actually generates a boatload of work. And we thought there might be, you know, 5000 of these in the first year, where there were 21,000 in the first year. And so far this year we're doubling that amount, right. We were able to use automation to respond to that without having to add a bunch of stuff. If we had to add staff for that, it would have literally been, you know, maybe hundreds of people, right? And but now, you know, there's, you can clearly put a value on it and it's millions of dollars a year, that we would have otherwise had to expect. >>The reason I'm harping on this lease is because I've been through a lot of cycles, as you know, and after the dot com boom, the the cost avoidance meant not writing the check to the software company, right? And that's what nick Carr wrote this, i. T matter. And then, and then, you know, post the financial crisis, we've entered uh a decade plus of awareness on the impact of technology. And I wonder if it's, I think this, I think this the cycle is changing I think. And I wonder if you have an opinion here where people, I think organizations are going to look at Technology completely different than they did like in the early 2000s when it was just easy to cut. >>No, I think the other point I will add to it. I agree with the gym. So we typically look at our away but it doesn't always have to be the cost. Right? If you look from the outcomes of the value, there are other measures also right? If you look at the how automation was able to help in the Covid generate. It was never about costs at that time. It was about a human lives. So you always may not be able to quantify it what you look at. Okay. What how are we maximizing the value or what kind of situations where we are and where we may not even have a human power to do that work. And we are running against the time. It could be the compliance needs. I'll give example of our covid use case which was pretty big success uh within L. A. County we deployed bots for the covid contact tracing program. So we were actually interviewing all the people who were testing positive so that we actually can keep track of them and then bring back that data within our HR so that our criminologists actually can look at the trends and see how we are doing as a county as compared to other counties and nationally. And we were in the peak, we were interviewing about 5000 people a day And we had to process that data manually into our nature and we deployed 15 members to do that. And they were doing like about 600 interviews a day. So every day we had a backlog of 2500 interviews. So it is not about a cost saving or a dollar value here because nobody planned for these unplanned events and now we don't have a time and money to find more data entry operators and parts were able to actually clear up all the backlog. So the value which we were able to bring it is way beyond the cost element. >>I I believe that 100% and I've been fighting this battle for a long time and it's easier to fight now because we're in this economic cycle even despite the pandemic, but I think it can be quantified. I honestly believe it can be tied to the income statement or in the case of a public sector, it could be tied to the budget and the mission how that budget supports the mission of the company. But I really believe it. And and I've always said that those soft factors are dwarf the cost savings, but sometimes, you know, sometimes the CFO doesn't listen, you know, because he or she has to cut. I think automation could change that >>for public sector. We look at how we can do more about it. So it's because we don't look at bottom line, it's about the tax dollars, we have limited dollars, but how we can maximize the value which we are giving to residents, it is not about a profit for us. We look at the different lens when it comes to the commercial >>Side, it's similar for us. So as a as a health care pair, because we're a mutual right? Our members and we have 17 million of them are really the folks that own the company and we're very purpose driven. Our our purpose is to do everything in our power to stand by members in sickness and in health. So how do you get the highest quality, cost effective health care for them? So if automation allows you to be more effective and actually keep that cost down, that means you can cover more people and provide higher quality care to our members. So that's really the driver for mission driven, >>I was gonna ask you as a member as one of your 17 million members, what are some of the ways in which automation is benefiting me? >>Um you know, a number of different ways. First off, you know, um it lowers our administrative costs, right? So that means we can actually lower our rights as as we go out and and and work with folks? That's probably the the the the bottom line impact, but we're also automating processes uh to to make it easier for the member. Right? Uh the example I used earlier was the equivalent of no surprises. Right. How do we take the member out of the middle of this dispute between, you know, out of network providers and the payer and just make it go away. Right, and we take care of it. Um but that that creates potentially administrative burden on our side, but we want to keep their costs down and we do it efficiently using it. So there's a number of use cases that we've we've done across, you know, different parts of our business. We automate a lot of our customer service, right? When you call um there's bots in the background that are helping that that agent do their job. And what that means is you're on the show, you're on the phone a lot shorter of a period of time. And that agent can be more concise and more accurate in answering your question. >>So your employee experience is dramatically improved, as is the member experience? >>Yes, they go hand in hand. They do go hand, unhappy members means unhappy employees, 100% >>mentioned scale before, you said you can't scale in this particular, the departmental pockets. Talk about scale a little bit. I'm curious as to how important cloud is to scale. Is it not matter. Can you scale without cloud? What are the other dimensions of scale? >>Well, you know, especially with my CTO had, we're we're pushing very heavily to cloud. We view ourselves as a cloud first. We want to do things in a cloud versus our own data centers, partially because of the scale that it gives us. But because we're healthcare, we have to do it very securely. So. We are very meticulous about guarding our data, how we encrypt information um, not only in our data center but in the cloud and controlling the keys and having all the controls in place. You know, the C. So and I are probably the best friends right now in the company because we have to do it together and you have to take that that security mind set up front. Right cloud first. Put security first with it. Um, so we're moving what we can to the cloud because we think it's just going to give us better scale as we grow and better economics overall, >>Any thoughts on that? I think a similar thoughts but if we look from L. A. county because of the sheer volume itself because the data which we are talking about. We had 40 departments within the county. Each department is serving a different business purpose for the resident beit voting or B justice or being social services and all and the amount of data which we are generating for 10 million residents and the amount of duplicate asi which it comes out because it's a very government centering model. You have a different systems and they may not be talking to each other. The amount of diplomacy and identity delicacy which we are creating and as we are enabling the interoperability between these functions to give us seamless experience keeping security in mind so fully agree on that because the end of the day we have to ensure that customer guarantee but it's a sheer volume that as and when we are adding these data sets and the patient's data as well as the residents data and now we have started adding a machine data because we have deployed so many IOT solutions so the data which is coming from those machines, the logs and all its exponential so that's where the scale comes into picture and how we can ensure that we are future ready for the upscale which we need and that's where cloud ability definitely helps a lot. >>What do you mean by future ready? >>So if you look at from a future smart city or a smart community perspective, imagine when machines are everywhere machines and IOT solutions are deployed, beat even healthcare, your bad information, you're even patient information, everything is interconnected and amount of data which is getting generated in that your automobile they're going to start talking to entertainment or we have to potentially track a single resident might be going same person going to the justice or maybe same person might be having a mental health issues, A same person might be looking for a social services, how we're going to connect those dots and what all systems they are touching. So all that interconnections needs to happen. So that exponential increase of data is a future readiness, which I'm talking about. Are we future ready from a technology perspective? Are we future ready from the other ecosystem perspective and how and how we're gonna manage those situations? Uh, so those are the things which we >>look at it and it's a it's a multiplier to, right? We all have this influx of information and you need to figure out what to do with it. Right. This is where artificial intelligence, machine learning is so important. But you also have interoperability standards that are coming. So now we're we have this massive data that each of our organizations have. But now you have interoperability which is a good thing for the member saying now I need to be able to share that data. Yeah, I wanted to ask you about >>that because a lot of changes in health care, um, are meaningful use. You have to show that to get paid but the standards weren't mature. Right? And so now that's changing what role does automation play in facilitating those standards. >>So, you know, we're big, big supporters of the fire standard that's out there um to in order to be able to support the standards and and create a P. I. S. And and pull together the information. What what will happen sometimes in the background is there's actually um artificial intelligence, machine learning models that create algorithms right? The output of that though often has to be active. Now a person can do something with that information or a vodka. Right? So when you start taking the ideal of artificial intelligence and now you have a robotic process that can use that to pull together the information and assimilated in a way to make it higher quality. But now it's available. It's kind of in the background. You don't see it but it's there helping. >>What are some of the things that you see? I know we're out of time but I just have a couple more questions. Some of the things that you see here we are you I path forward for we're in person. This is a bold company that's growing very quickly. Some of the announcements that were made, what are what are some of your reaction to that? And how do you see it helping move blue crush blue shield forward even >>faster. Well you know a lot of the announcements in terms of some of the features that that they've added around their robotics processing are great right? The fact that they're in the cloud and and some of the capabilities and and and better ability to to support that the process mining is key. Right. In order for abouts to be effective, you have to understand your process and you just don't want to necessarily automate the bad practices. Right? So you want to take a look at those processes to figure out how you can automate things smartly. Um and some of their capabilities around that are very interesting. We're going to explore that quite a bit but but I think they're the ambition here is beyond robotics. Right. It's actually creating um you know, applications that actually are using bots in the background which is very intriguing and has a lot of potential potentially to drive even more digital transformation. This can really affect all of our workers and allow us to take digital solutions out to the market a lot faster >>and to see what was going to ask you, you are here for four weeks at UI Path, you got to meet a lot of your colleagues, which is great. But what about this company attracted you to leave your former role and come over here to the technology vendor side. >>Well, I think I was able to achieve the similar role within L. A. County, able to establish the automation practice and achieve the maturity, able to stand up things and I feel that this is the same practitioner activity which I can actually take it back to the other clients ceos because of one thing which I really like about your hypothesis. RP is just a small component of it. I really want to change that mindset that we have to start looking ui path as an end to end full automation enterprise solution and it is not only the business automation, it's the idea automation and it's a plus combination and whether we are developing a new industry solutions with our partners to help the different industry segments and we actually helping Ceo in the center of it because Ceo is the one who is driving the automation, enabling the business automation and actually managing the automation ceo and the governess. So CEO is in left and center of it and my role is to ensure that I actually help those Ceos to make successful and get that maturity and you will path as a platform is giving that ability of length and breath and that's what is really fascinating me and I'm really looking forward that how that spectrum is changing that we are getting matured in a process mining area and how we are expanding our horizons to look at the whole automation suit, not just the R. P. Product and that's something which I'm really looking forward and seeing that how we're going to continue expanding other magic quadrants and we're actually going to give the seamless experience so the client doesn't have to worry about okay for this, I have to pick this and further, I have to pick something else >>that's seamless experience is absolutely table stakes these days. Guys, we're out of time. But thank you so much for joining. David me, talking about automation and health care. Your recommendations for best practices, how to go about doing that and and the change management piece. That's a critical piece. We appreciate your time. >>Thanks for having. Thank >>you. Our pleasure for day Volonte. I'm lisa martin live in las Vegas. The cubes coverage of you a path forward for continues next. Mhm. Mhm mm.

>> Narrator: From around the globe, it's theCUBE with digital coverage of PegaWorld iNspire, brought to you by Pegasystems. >> Hi everybody, this is Dave Vellante and welcome to theCUBE's coverage of PegaWorld iNspire 2020. And now that the dust has settled on the event, we wanted to have a little postmortem power panel, and I'm really excited to have three great guests here today. Adrian Swinscoe is a customer service and experience advisor and the best-selling author of a couple of books: "How to Wow" and "Punk CX." Adrian great to see you, thanks for coming on. >> Hey Dave. >> And Shelly Kramer's a principal, analyst, and a founding partner at Futurum Research, CUBE alum. Shelly, good to see you. >> Hi, great to see you too. >> And finally, Don Schuerman who is the CTO of Pegasystems and one of the people that was really highlighting the keynotes. Don, thanks for your time, appreciate you coming on. >> Great to be here. >> Guys, let's start with some of the takeaways from the event, and if you don't mind I'm going to set it up. I had some, I had many many notes. But I'll take a cue from Alan's keynote, where he talked about three things: rethinking the customer engagement, that whole experience, that as a service, I'm going to say that certainly the second part of last decade came to the front and center and we think is going to continue in spades. And then new tech, we heard about that. Don we're going to ask you to chime in on that. Modern software, microservices, we've got machine intelligence now. And then I thought there were some really good customer examples. We heard from Siemens, we heard from the CIO and head of digital at Aflac, the Bank of Australia. So, some really good customer examples. But Shelly, let me start with you. What were your big takeaways of PegaWorld iNspire 2020, the virtual edition? >> You know, what I love is a focus, and we have talked a lot about that here at Futurum Research, but what I love is the thinking that what really is important now is to think about rethinking and kind of tearing things apart. Especially when we're in a time, we're in difficult economic times, and so instead of focusing on rebuilding and relaunching as quickly as possible, I think that now's the time to really focus on reexamining what is it that our customers want? How is it that we can best serve them? And really sort of start from ground zero and examine our thinking. And I think that's really at the heart of digital transformation, and I think that both in this virtual event and in some interviews I was lucky enough to do in advance with some of the Pega senior team, that was really a key focus, is really thinking about how we can re-architect things, how we can do things in ways that are more efficient, that impact people more effectively, that impact the bottom line more effectively. And to me that's really exciting. >> So Adrian, CX is obviously your wheelhouse. A lot of the conversation at PegaWorld iNspire was of course about customer experience, customer service. How do you think the content went? What were some of the highlights for you? And maybe, what would you have liked to hear more of? >> Well I think, thanks Dave, I actually really enjoyed it. I actually kind of thought was, first of all I should say that I've been to a bunch of virtual summits and I thought this was one of the best ones I've done in terms of its pace and its interactivity. I love the fact that Don was bouncing around the screen, kind of showing us around the menu and things. I thought that was great. But the things that I thought really stood out for me was this idea of the context around accelerating digital transformation. And that's very contextual, it's almost being forced upon us. But then this idea of also the center-out thinking and the Process Fabric. Because it really reminded me of, and Don you can maybe correct me if I'm wrong here, is taking a systems-thinking approach to delivering the right outcomes for customers. Because it's always struck me that there's a contradiction at the heart of the rhetoric around customer-centricity where people say they want to do the right things by customers but then they force them down this channel-centric or process-centric way of thinking. And so actually I thought it was really refreshing to hear about this center-out and Process Fabric platform that Pega's building. And I thought it's really exciting because it felt like actually we're going to start to take a more systemic look and take to delivering great service and great experience. So I thought that was really great. Those were my big headlines out of the summit. >> So Don, one of the-- >> Adrian I think-- >> Go ahead, please. >> Yeah, I think the whole idea, you know, and Alan referred to center-out as a business architecture, and I think that's really an important concept because this is really about the intersection of that business goal. How do I truly become customer-centric? And then how do I actually make my technology do it? And it's really important for that to work where you put your business logic in the technology. If you continue to do it in the sort of channel-centric way or really data-centric, system-centric way that historically has been the approach, I don't think you can build a sustainable platform for great customer engagement. So I think that idea of a business architecture that you clued in on a little bit is really central to how we've been thinking about this. >> Let's stay on that for a second. But first of all, I just want to mention, you guys did a good job of not just trying to take a physical event and plug in into virtual. So congratulations on that. The virtual clicker toss, and you know, you were having some fun eating your eggs. I mean that was, that's great. And the Dropkick Murphys couldn't be live, but you guys still leveraged that, so well done. One of the better ones that I've seen. But I want to stay on your point there. Alan talked about some of the mistakes that are made, and one of the questions I have for you guys is, what is the state of customer experience today, and why the divergence between great, and good, and pretty crappy? And Alan talked about, well, people try to impose business process top-down, or they try to infuse logic in the database bottom-up. You really got to do that middle-out. So, Don I want to come back to you. Let's explore that a little bit. What do you really mean by middle-out? Where am I putting the actual business logic? >> Yeah, I think this is important, right. And I think that a lot of time we have experiences as customers. And I had one of these recently with a cable provider, where I spent a bunch of time on their website chatting with a chatbot of some kind, that then flipped me over to a human. When the chatbot flipped me to the human, the human didn't know what I was doing with the chatbot. And that human eventually told me I had to call somebody. So I picked up the phone, I made the phone call. And that person didn't know what I was doing on chat with the human or with the chatbot. So every time there's a customer, I'm restarting. I'm reexplaining where I am. And that to me is a direct result of that kind of channel-centric thinking, where all of my business logic ends up embedded in, "Well hey, we're going to build a cool chatbot. "And now we're going to build a cool chat system. "And by the way, "we're going to keep our contact centers running." But I'm not thinking holistically about the customer experience. And that's why we think this center-out approach is so important, because I want to go below the channel. And I want to think about that customer journey. What's the outcome I'm trying to get to? In the case of my interaction, I was just trying to increase my bandwidth so that I could do events like this, right? What's that outcome that I'm trying to get to and how do I get the customer to that outcome in a way that's as efficient for the business and as easy for the customer as possible regardless of what channel they're on. And I think that's a little bit of a new way of thinking. And again, it means thinking not just about the customer goal, but having an opinion, whether you are a business leader or an IT person, about where that logic belongs in your architecture. >> So, Adrian. Don just described the sort of bot and human experience, which mimics a lot of the human experience that we've all touched in the past. So, but the customer journey that Don talked about isn't necessarily one journey. There's multiple journeys. So what's your take on how organizations can do better with that kind of service. >> Well I think you're absolutely right, Dave. I mean, actually during the summer I was talking, I was listening to Paul Greenberg talk about the future of customer service. And Paul said something that I think was really straightforward but really insightful. He said, "Look, organizations think about customer journeys "but customers don't think about journeys "in the way that organizations do. "They think discontinuously." So it's like, "I'm going to go to channel one, "and then channel three, and then channel four, "and then channel five, and then back to channel two. "And then back to channel five again." And they expect those conversations to be picked up across those different channels. And so I think what we've got to do is develop, as Don said, build an architecture that is, that works around trying to support the different journeys but allows that flexibility and that adaptability for customers to jump around and to have one of those continuous but disconnected conversations. But it's up to us to try and connect them all, to deliver the service and experience that the customers actually want. >> Now Shelly, a lot of the customer experience actually starts with the employees, and employees don't like when the customer is yelling at them saying, "I just answered all those questions. "Why do I have to answer them again?" So you've, at your firm, you guys have written a lot about this, you've thought a lot about it, you have some data I know you shared on theCUBE one time that 80% of employees are disengaged. And so, that affects the customer experience, doesn't it? >> Yeah it does, you know. And I think that when I'm listening to Don's explanation about his cable company, I'm having flashbacks to what feels like hundreds of my own experiences. And you're just thinking, "This does not have to be this complicated!" You know, ten years ago that same thing that Don just described happened with phone calls. You know, you called one person and they passed you off to somebody else, and they passed you off to somebody else, and you were equally as frustrated as a customer. Now what's happening a lot of times is that we're plugging technology in, like a chat bot, that's supposed to make things better but we're not developing a system and processes throughout our organization, and also change management, what do I want to say, programs within the organization and so we're kind of forgetting all of those things. So what's happening is that we're still having customers having those same experiences that are a decade old, and technology is part of the mix. And it really shouldn't be that way. And so, one thing that I really enjoyed, speaking about employees, was listening to Rich Gilbert from Aflac. And he was talking about when you're moving from legacy processes to new ones, you have to plan for and invest in change management. And we talk about this all the time here at Futurum, you know technology alone is never the answer. It's technology plus people. And so you have to invest in people, you have to invest in their training in order to be able to support and manage change and to drive change. And I think one really important part of that equation is also listening to your employees and getting their feedback, and making them part of the process. Because when they are truly on your front lines, dealing with customers, many times dealing with stressed, upset, frustrated customers, you know, they have a lot of insights. And sometimes we don't bring them into those conversations, certainly early enough in the process to help, to let them help guide us in terms of the solutions and the processes that we put in place. I think that's really important. >> Yeah, a lot of-- >> Shelly, I think-- >> If I may, a lot of the frustration with some employees sometimes is those processes change, and they're unknown going into it. We saw that with COVID, Don. And so, your thoughts on this? >> Yeah, I mean, I think the environment employees are working in is changing rapidly. We've got a customer, a large telecommunications company in the UK where their customer service requests are now being handled by about 4,000 employees pulled from their marketing department working distributed because that's the world that we're in. And the thing I was going to say in response to Shelly is, Alan mentioned in his keynote this idea of design thinking. And one of the reasons why I think that's so important is that it's actually about giving the people on the front lines a voice. It's a format for engaging the employees who actually know the day-to-day experiences of the customers, the day-to-day experiences of a customer service agent, and pulling them into the solution. How do we develop the systems, how do we rethink our processing, how does that need to plug into the various channels that we have? And that's why a lot of our focus is not just on the customer service technology, but the underlying low code platform that allows us to build those processes and those chunks of the customer journey. We often refer to them as "microjourneys" that lead to a specific outcome. And if you're using a low code based platform, something that allows anybody to come in and define that process, you can actually pull employees from the front lines and put them directly on your project teams. And all of a sudden you get better engagement but you also get this incredible insight flowing into what you're doing because you're talking to the people who live this day in and day out. >> Well and when you have-- >> So let's stay on this for a second, if we can. Shelly, go ahead please. >> Sure. When you have a chance to talk with those people, to talk with those front line employees who are having an opportunity to work with low code, no code, they get so excited about it and their jobs are completely, the way they think about their jobs and their contribution to the company, and their contribution to the customer, and the customer experience, is just so wonderful to see. And it's such an easy thing to do, so I think that that's really a critical part of the equation as it relates to success with these programs. >> Yeah, staying close to the customer-- >> Can I jump in? >> Yeah, please Adrian. >> Can I jump in on that a little, a second. I think Shelly, you're absolutely right. I think that it's a really simple thing. You talk about engagement. And one of the key parts of engagement, it seems to me, is that, is giving people a voice and making them feel important and feel heard. And so to go and ask for their opinion and to help them get involved and make a difference to the work that they do, the outcomes that their customers receive, and the overall productivity and efficiency, can only have a positive impact. And it's almost like, it feels self-evident that you'd do that but unfortunately it's not very common. >> Right. It does feel self-evident. But we miss on that front a lot. >> So I want to ask, I'm going to come back to, we talked about people process, we'll come back to that. But I want to talk about the tech. You guys announced, the big announcement was the Pega Process Fabric. You talked about that, Don, as a platform for digital platforms. You've got all these cool microservices and dynamic APIs and being able to compose on the fly, so some pretty cool stuff there. I wonder, with the virtual event, you know, with the physical event you've got the hallway traffic, you talk to people and you get face-to-face reactions. Were you able to get your kind of real-time reactions to the announcement? What was that like? Share with us please. >> Yeah, so, we got well over 1,000 questions in during the event and a lot of them were either about Process Fabric or comments about it. So I think people are definitely excited about this. And when you strip away all of the buzzwords around microservices and cloud, et cetera, I think what we're really getting at here is that work is going to be increasingly more distributed. We are living proof of that right now, the four of us all coming here from different studios. But work is going to be distributed for a bunch of reasons. Because people are more distributed, because organizations increasingly are building customer journeys that aren't just inside their walls, but are connected to the partners and their ecosystem. I'm a bank but I may, as part of my mortgage process, connect somebody up to a home insurer. And all of a sudden the home buying process goes beyond my four walls. And then finally, as you get all of these employees engaged with building their low code apps and being citizen developers, you want to let the 1,000 flowers to bloom but you also need a way to connect that all back together. And Process Fabric is about putting the technology in place to allow us to take these distributed bits of work that we need to do and weave them together into experiences that are coherent for a customer and easy for an employee to navigate. Because I think it's going to be really really important that we do that. And even as we take our systems and break them up into microservices, well customers don't interact with microservices. Customers interact with journeys, with experiences, with the processes you lay out, and making sure we can connect that up together into something that feels easy for the customer and the employee, and gets them to that result they want quickly, that's what the vision of Process Fabric is all about. >> You know, it strikes me, I'm checking my notes here. You guys talked about a couple of examples. One was, I think you talked about the car as sort of a mobility experience, maybe, you know, it makes me wonder with all this AI and autonomous vehicle stuff going on, at what point is owning and driving your own vehicle really going to be not the norm anymore? But you talked about this totally transformed, sorry to use that word, but experience around autos. And certainly financial services is maybe a little bit more near-term. But I wonder Shelly, Futurum, you know, you guys look ahead, how far can we actually go with AI in this realm? >> Well, I think we can go pretty far and I think it'll happen pretty fast. And I think that we're seeing that already in terms of what happened when we had the Coronavirus COVID-19, and of course we're still navigating through that, is that all of a sudden things that we talked about doing, or thought about doing, or planned doing, you know later on in this year or 2021, we had to do all of those things immediately. And so again, it is kind of like ripping the Bandaid off. And we're finding that AI plays a tremendously important role in relieving the workload on the frontline workers, and being able to integrate empathy into decision making. And you know, I go back to, I remember when you all first rolled out the empathy part of your platform, Don, and just watching a demo on that of how you can slide this empathy meter to be warmer, and see in true dollars and cents over time the impact of treating your customers with more empathy, what that delivers to a company. And I think that AI that continues to build and learn and again, what we're having right now, is we're having this gigantic volume of needs, of conversation, of all these transactions that need to happen at once, and great volumes make for better outcomes as it relates to artificial intelligence and how learning can happen more quickly over time. So I think that it's, we're definitely going to see more use of AI more rapidly than we might've seen it before, and I don't think that's going to slow down, at all. Certainly, I mean there's no reason for it to slow down. The benefits are tremendous. The benefits are tremendous, and let me step back and say, following a conversation with Rob Walker on responsible AI, that's a whole different ball of wax. And I think that's something that Pega has really embraced and planted a flag in. So I think that we'll see great things ahead with AI, and I think that we'll see the Pega team really leading as it relates to ethical AI. And I think that's tremendously important as well. >> Well that's the other side of the coin, you know. I asked how far can we go and I guess you're alluding to how far should we go. But Adrian, we also heard about agility and empathy. I mean, I want an empathic service provider. Are agility and empathy related to customer service, and how so? >> Well, David, I think that's a great question. I think that, you talk about agility and talk about empathy, and I think the thing is, what we probably know from our own experience is that being empathetic is sometimes going to be really hard. And it takes time, and it takes practice to actually get better at it. It's almost like a new habit. Some people are naturally better at it than others. But you know, organizationally, I talk about that we need to almost build, almost like an empathetic musculature at an organizational level if we're going to achieve this. And it can be aided by technology, but we, when we develop new muscles it takes time. And sometimes you go through a bit of pain in doing that. So I think that's where the agility comes in, is that we have to test and learn and try new things, be willing to get things wrong and then correct, and then kind of move on. And then learn from these kind of things. And so I think the agility and empathy, it does go hand in hand and it's something that will drive growth and increasing empathetic interactions as we go forward. But I think it's also, just to build on Shelly's point, I think you're absolutely right that Pega has been leading the way in this sort of dimension, in terms of its T-switch and its empathetic advisor. But now the ethical AI testing or the ethical bias testing adds a dimension to that to make sure it's not just about all horsepower, but being able to make sure that you can steer your car. To use your analogy. >> So AI's coming whether we like it or not. Right, Shelly? Go ahead. >> It is. One real quick real world example here is, you know, okay so we have this time when a lot of consumers are furloughed. Out of work. Stressed about finances. And we have a lot of Pega's customers are in the financial services space. Some of the systems that they've established, they've developed over time, the processes they've developed over time is, "Oh, I'm talking with Shelly Kramer and she has a "blah-blah-blah account here. "And this would be a great time to sell her on "this additional service," or whatever. And when you can, so that was our process yesterday. But when you're working with an empathic mindset and you are also needing to be incredibly agile because of current circumstances and situations, your technology, the platform that you're using, can allow you to go, "Okay I'm dealing "with a really stressed customer. "This is not the best time "to offer any additional services." Instead what we need to ask is this series of questions: "How can we help?" Or, "Here are some options." Or whatever. And I think that it's little tweaks like that that can help you in the customer service realm be more agile, be more empathetic, and really deliver an amazing customer experience as a result. And that's the technology. >> If I could just add to that. Alan mentioned in his keynote a specific example, which is Commonwealth Bank of Australia. And they were able, multiple times this year, once during the Australian wildfires and then again in response to the COVID crisis, to completely shift and turn on a dime how they interacted with their customer, and to move from a prioritization of maybe selling things to a prioritization of responding to a customer need. And maybe offering payment deferrals or assistance to a customer. But back to what we were talking about earlier, that agility only happened because they didn't have the logic for that embedded in all their channels. They had it centralized. They had it in a common brain that allowed them to make that change in one place and instantly propagate it to all of the 18 different channels in which they touch their customer. And so, being able to have agility and that empathy, to my mind, is explicitly tied to that concept of a center-out business architecture that Alan was talking about. >> Oh, absolutely. >> And, you know, this leads to discussion about automation, and again, how far can we go, how far should we go? Don, you've been interviewed many many times, like any tech executive, about the impact of AI on jobs. And, you know, the typical response of course is, "No, we want augmentation." But the reality is, machines have always replaced humans it's just, now it's the first time in terms of cognitive function. So it's a little different for us this time around. But it's clear, as I said, AI is coming whether we like it or not. Automation is very clearly on the top of people's minds. So how do you guys see the evolution of automation, the injection of automation into applications, the ubiquity of automations coming in this next decade? Shelly, let's start with you. >> You know, I was thinking you were going to ask Don that question so I'm just listening and listening. (laughing) >> Okay, well we can go with Don, that's-- >> No I'm happy to answer it. It's fine, it just wasn't what I expected. You know, we are really immersed in the automation space. So I very much see the concerns that people on the front line have, that automation is going to replace them. And the reality of it is, if a job that someone does can be automated, it will be automated. It makes sense. It makes good business sense to do that. And I think that what we are looking at from a business agility standpoint, from a business resilience standpoint, from a business survival standpoint, is really how can we deliver most effectively to serve the needs of our customers. Period. And how we can do that quickly and efficiently and without frustration and in a way that is cost effective. All of those things play into what makes a successful business today, as well as what keeps employees, I'm sorry, as well as what keeps customers served, loyal, staying around. I think that we live in a time where customer loyalty is fleeting. And so I think that smart businesses have to look at how do we deepen the relationships that we have with customers? How can we use automation to do that? And the thing about it, you know, I'll go back to the example that Don gave about his cable company that all of us have lived through. It's just like, "Oh my gosh. "There's got to be a better way." So compare that to, and I'm sure all of us can think of an experience where you had to deal with a customer service situation in some way or another, and it was the most awesome thing ever. And you walked away from it and you just went, "Oh my gosh. I know I was talking to a bot here or there." Or, "I know I was doing this, but that solved my problem. "I can't believe it was so easy! "I can't believe it was so easy! "I can't wait to buy something from this company again!" You know what I'm saying? And that's really, I think, the role that automation can play. Is that it can really help deepen existing relationships with our customers, and help us serve them better. And it can also help our employees do things that are more interesting and that are more relevant to the business. And I think that that's important too. So, yes, jobs will go. Yes, automation will slide into places where we've done things manually and repetitive processes before, but I think that's a good thing. >> So, we've got to end it shortly here but I'll give you guys each a last opportunity to chime in. And Adrian, I want to start with you. I invoked the T-word before, transformation, a kind of tongue-in-cheek joking because I know it's not your favorite word. But it is the industry's favorite word. Thinking ahead for the future, we've talked about AI, we've talked about automation, people, process and tech. What do you see as the future state of customer experience, this mix of human and machine? What do we have to look forward to? >> So I think that, first of all, let me tackle the transformation thing. I mean, I remember talking about this with Duncan Macdonald who is the CIO across at UPC, which is one of Pega's customers, on my podcast there the other week. And he talked about, he's the cosponsor of a three year digital transformation program. But then he appended the description of that by saying it's a transformation program that will never end. That's the thing that I think about, because actually, if you think about what we're talking about here, we're not transforming to anything in particular, you know. It's not like going from here to there. And actually, the thing that I think we need to start thinking about is, rather than transformation we actually need to think about an evolution. And adopting an evolutionary state. And we talked about being responsive. We talked about being adaptable. We talked about being agile. We talk about testing and learning and all these different sort of things, that's evolutionary, right? It's not transformational, it's evolutionary. If you think about Charles Darwin and the theory of the species, that's an evolutionary process. And there's a quote, as you've mentioned I authored this book called "Punk CX," there's a quote that I use in the book which is taken from a Bad Religion song called "No Control" and it's called, "There is no vestige of a beginning, "and no prospect of an end." And that quote comes from a 1788 book by James Hutton, which was one of the first treaties on geology, and what he found through all these studies was actually, the formation of the earth and its continuous formation, there is no vestige of a beginning, no prospect of an end. It's a continuous process. And I think that's what we've got to embrace is that actually change is constant. And as Alan says, you have to build for change and be ready for change. And have the right sort of culture, the right sort of business architecture, the right sort of technology to enable that. Because the world is getting faster and it is getting more competitive. This is probably not the last crisis that we will face. And so, like in most evolutionary things, it wasn't the fittest and the strongest that survived, it was the ones that were most adaptable that survived. And I think that's the kind of thing I want to land on, is actually how, it's the ones that kind of grasp that, grasp that whole concept are the ones that are going to succeed out of this. And, what they will do will be... We can't even imagine what they're going to do right now. >> And, thank you. And Shelly, it's not only responding to, as Adrian was saying, to crisis, but it's also being in a position to very rapidly take advantage of opportunities and that capability is going to be important. You guys are futurists, it's in the name. Your thoughts? >> Well I think that, you know, Adrian's comments were incredibly salient, as always. And I think that-- >> Thank you. >> The thing that this particular crisis that we are navigating through today has in many ways been bad, but in other ways, I think it's been incredibly good. Because it has forced us, in a way that we really haven't had to deal with before, to act quickly, to think quickly, to rethink and to embrace change. Oh, we've got to work from home! Oh, we've got 20 people that need to work from home, we have 20,000 people that need to work from home. What technology do we need? How do we take care of our customers? All of these things we've had to figure out in overdrive. And humans, generally speaking, aren't great at change. But what we are forced to do as a result of this pandemic is change. And rethink everything. And I think that, you know, the point about transformation not being a beginning and an end, we are never, ever, ever done. It is evolutionary and I think that as we look to the future and to one of your comments, we are going faster with more exciting technology solutions out there, with people who are incredibly smart, and so I think that it's exciting and I think that all we are going to see is more and more and more change, and I think it will be a time of great resilience, and we'll see some businesses survive and thrive, and we'll see other businesses not survive. But that's been our norm as well, so I think it's really, I think we have some things to thank this pandemic for. Which is kind of weird, but I also try to be fairly optimistic. But I do, I think we've learned a lot and I think we've seen some really amazing exciting things from businesses who have done this. >> Well thanks for sharing that silver lining, Shelly. And then, Don, I'm going to ask you to bring us to the finish line. And I'm going to close my final question to you, or pose it. You guys had the wrecking ball, and I've certainly observed, when it comes to things like digital transformations, or whatever you want to call it, that there was real complacency, and you showed that cartoon with the wrecking ball saying, "Ehh not in my life, not on my watch. "We're doing fine." Well, this pandemic has clearly changed people's thinking, automation is really top of mind now at executive. So you guys are in a good spot from that standpoint. But your final thoughts, please? >> Yeah, I mean, I want to concur with what Adrian and Shelly said and if I can drop another rock quote in there. This one is from Bob Dylan. And Dylan famously said, "The times they are a changing." But the quote that I keep on my wall is one that he tossed off during an interview where he said, "I accept chaos. "I'm not sure if it accepts me." But I think digital transformation looks a lot less like that butterfly emerging from a cocoon to go off happy to smell the flowers, and looks much more like accepting that we are in a world of constant and unpredictable change. And I think one of the things that the COVID crisis has done is sort of snapped us awake to that world. I was talking to the CIO of a large media company who is one of our customers, and he brought up the fact, you know, like Croom said, "We're all agile now. "I've been talking about five years, "trying to get this company to operate in an agile way, "and all of a sudden we had to do it. "We had no choice, we had to respond, "we had to try new things, we had to fail fast." And my hope is, as we think about what customer engagement and automation and business efficiency looks like in the future, we keep that mindset of trying new things and continuously adapting. Evolving. At the end of the day, our company's brand promise is, "Build for change." And we chose that because we think that that's what organizations, the one thing they can design for. They can design for a future that will continue to change. And if you put the right architecture in place, if you take that center-out mindset, you can support those immediate needs, but set yourself up for a future of continuous change and continuous evolution and adaptation. >> Well guys, I'll quote somebody less famous. Jeff Frick, who said, "The answer to every question "lives somewhere in a CUBE interview." and you guys have given us a lot of answers. I really appreciate your time. I hope that next year at PegaWorld iNspire we can see each other face-to-face and do some live interviews. But really appreciate the insights and all your good work. Thank you. >> Thank you. >> Absolutely. >> And thank you for watching everybody, this is Dave Vellante and our coverage of PegaWorld iNspire 2020. Be right back, right after this short break. (lighthearted music)

(electric upbeat music) >> Live from Washington D.C. It's theCUBE. Covering Inforum DC 2018. Brought to you by Infor. >> Well welcome back here on theCUBE along with Dave Vallante I'm John Walls as we wrap up our coverage here at Inforum 18, Washington D.C. Nations capital. Again just saying which we are between Capital Hill and the White House here. And just on top of the show floor Dave had a chance to check out the goings on down. So good feeling here. Good vibe on the floor. Good feeling on the Keynote stage. I know tomorrow, good lineup as well but just your thoughts as we wind up here on day one. Well I think Charles Phillips is an awesome host. I mean first of all he looks great up there. He's tall. He's thin. He's got has this awesome suit on. I mean the guy is just dressed impeccably. Add to that his mind. I mean he's a very clear thinker, a clear strategist. He's able to articulate the value, the strategy that Infor has and has had for quite some time and the value that it brings to customers. So I really like listening to him. He's not a hype machine. Unlike, you know, so many in this industry who are incredibly successful, Larry Ellison, Marc Benioff you know others you know love to hype what they do. Charles throws a little, few little jokes in there but very low key as we heard this morning. And it seems to be working. I mean as a private company they can write their own narrative. Alright if this were a public company people would be hammering them on the debt. They'd be knocking them on the top-line growth. Cause the Income Statement, you know, from a growth stand point is not exploding but the SAS pieces of the business are. So but you know Wall street, they would be picking at this scabs. So as a private company, they're not subject to the 90-day shot clock. And so as a result they can write their own narrative which I think is incredibly important for this company right now because they have a large installed base of customers that they're trying to move to their new platform. Move, migrate you know, those are scary words for customers. And so the competition, this is why. Why is Oracle coming at Infor so much? Two reasons there may be others. But number one. Infor is hurting Oracle. They're taking share away and Oracle you know, think that they should have 100% market share. Same with SAP. The second is that it sees an opportunity to fight back you know the best, the best defense is a good offense. And so they're trying to go after those customers that Infor's trying to woe to their new platform. And any time you moving it's an opportunity. You know we saw this with big acquisitions like Dell and EMC. You know EMC took their eye off the ball, others came in allowed a company like NetApp to come back. So you see that certainly HP, when it was splitting up, got distracted so you see that and so now what's key about sessions like this, events like this, is it allows Infor to stay relevant. To put a relevance story in front of its customers. So what is that story? It's got a platform. It's got a full stack. It's investing in R and D. It's innovating with technologies like AI. It's building organic innovation. And it's bringing in inorganic through acquisition. Things like Birst for modern BI and injecting that throughout its application portfolio. It's got a full-suite. It was interesting somebody said we had to make a bet, do we go full-suite >> Or best-of-breed. >> Or do we go best-of-breed. >> Right. >> I would argue by going micro-vertical they can claim both. It's very hard to be both best-of-breed and both full-suite. I mean I would agree if you just want to do one thing, you're probably going to do that one thing better than anybody else. And so I'll grant you that. But I think that the balancing act is how do you stay like best-of-breed or near best-of-breed with that full-suite? And I think Infor's found the answer with micro-verticals. And bringing in technologies like AI. Was very impressed with all the robotic process automation talk this morning. That's going to be a huge business it's already. I mean it's growing like crazy. So if I'm an Infor customer and I'm an old Legacy customer I'm thinking: "Wow these guys are really making "some interesting investments." "Yeah I got to spend, "and I got to maybe migrate "but if I don't I'm going to get digitally transformed "by somebody else." And they didn't actually put a lot of scare tactics in there but maybe that's something they should, might want to add in, is some examples of customers that are, that have been left behind. But maybe that's bromide in the industry today. But I think that, that relevance message came through load and strong and I think it's critical for this company. >> I think interesting just to start with the Keynotes, and then we heard it throughout the various guest that we had here on the program today was that it's a compony that really knows who it is. At least that's the feeling I get. Knows where it's going. So it inspires a lot of confidence, right. He does, Charles does. The company does. And they're just kind, they're just real comfortable in their own skin for one. And two, they're committed to other principles outside of business. I'm talking about the diversity and inclusion. That's just not flab, that's really who they are. That's their DNA. I think there's an appealing aspect there too. >> Yeah and so. And then we heard a lot, you know, the Coke industries investment, two and a half billion. I said two billion earlier it's two and a half billion. That money didn't show up in the Balance Sheet, okay. So again. You get to write your own narrative as a private company. So there's still three hundred and thirty-eight million on the Balance Sheet you know, still quite a bit of debts. So again, Wall Street would be picking at that but doesn't even come up, at this event. Customers aren't really asking those questions. They want to see a company that's viable. This company is clearly viable. They have thrown off a lot of cash that's why private equity and organizations like Coke Industries are interested in them. Because it's cashflow positive, they see a lot of, you know, financial upside for this company. So that's kind if cool. They other things is Hook & Loop the Design firm that Infor bought you know, several years ago we heard how that's evolving and becoming a fundamental part of, not just design but product development. I think that's pretty impressive. Many companies are doing that now. These guys got in first and so they're a little bit ahead of the game. I think they're, they're innovating in a way that I think has ripple effects for customers. I mean the customer experience. You hear a lot about diversity at this company, I mean this is not to me lip service. >> Right. >> You know Charles is really serious about this stuff. And he's got the platform to do it and he's investing in it. And so, you know, you see a lot of substantive examples. And I think that will pay off. It will pay dividends. The Four Horsemen now have been sort of evolving. There's a succession planning with the Four Horsemen, right. Because Stephan and Duncan have, have moved on. You know they've left the company or at least they're not front and center anymore. They're LinkedIn still says they're working with Infor so they're somehow affiliated. But they don't have operating roles. It's clear. But Charles and Pam still do. And so you're seeing an evolution there. We're going to ask the head of HR tomorrow about that. We heard from, you know Martine, back to the diversity. Corey Tollefson talking retail. You know again, Micro industry. You know, we know, he didn't mention it, but you know guys like Macy's, Safeway, these are decent sized customers of Infor. We're seeing the partner ecosystem grow. We had Capgemini on today. Grant Thornton is out there. You know Deloitte and others that. >> Accenture is out here I think. >> Accenture's out here, yeah. So that's, that's important. Again I think, I think Coke Industries helped nudge some people in there. "Like Hey, we just made a big investment." "We're a big client of yours." >> Didn't hurt. >> "You're going to pay attention." (laughing) >> "And find some opportunities." Probably said: "Look it's got to be subsidize, "It's got to be a win-win but we want you to look in earnest." And I think others have. I've heard that there's been multi-million dollar deals that these guys have have catalyzed. Kevin Curry from Public Sector, a critical space for Infor, he has almost a thousand customers here and Amazon has a huge presence in Public Sector and they're drafting off of that. And then of course we ended with Raul from AWS which was fun interview. AWS is obviously winning in so many different fronts. Big partnerships with guys like VMware. Obviously number one in Cloud, others I guess if you add up all the revenue are number one. But really Amazon's number one in cloud. >> That's right. >> We know they're tops. Because they're in a. For their serve market, which is infrastructure as a service, they're by far the leader and they started the whole thing. Tomorrow we got Charles Phillips coming on. We got Pam Murphy the two, what I consider founders of Infor. They weren't right, but they were the founders of, the new co-founders of the new Infor if you will. And some customers coming on. So really excited to be here. >> Big day, look forward to it. >> Yeah. >> And we, unfortunately I can't share this with you at home but Venus Williams on the Keynote stage tomorrow. Looking forward to that. Talking about the human potential. Shackles going to be here. Had a last minute cancellation so they've Venus Williams in and talk about really thematically, very consistent to her life story with what Infor is talking about here this week. And we're glad to have the opportunity to be here with you throughout the week, and the show. So that's it for day one here at Inforum 18. From Dave Vallante, I'm John Walls, thanks for joining us here on theCUBE and we'll see you back here tomorrow from Washington D.C. (electric upbeat music)

>> Live from Washington DC, it's theCUBE. Covering Inforum DC 2018. Brought to you by Infor. >> Well, welcome to the nation's capital, a rain soaked Washington DC. We're here for Inforum 18, Dave Vellante, John Walls We're in the Walter Washington Convention Center. The fourth time, theCUBE has been at an Infor show and getting bigger and better than ever, David. >> That's right John. This is, let's see, the first one was in New Orleans several years ago. Then Infor skipped a year, and then did Javits couple years in a row. That's sort of the headquarters of where Infor is, very close to the Javits Center. And Charles Phillips, of course, lives in New York City. And this year they decided to come to the nation's capital. I mean, Infor is an interesting company. About $3billion in revenue, essentially it is a private equity roll up. From Golden Gate and others, that really the roots of it are in Lawson Softwares. Some of you may remember Lawson Softwares, the enterprise software company. And then Charles Phillips came on, and of course he was the architect of Oracle's M and A. Probably spent $30 plus billion for Larry Ellison, remaking Oracle. Completely transforming Oracle, brought some of that expertise to Infor in this private equity play, this roll up. And then bought many, many software companies, rolled them up together and really started to compete, using a different model. So, Infor's sort of expertise, if you will is around so called Micro verticals, so they cover a lot of different industries, hospitality industries, they got also manufacturing, ERP, >> Retail financial >> Retail financial, health care, and then they also have horizontal applications like Human Capital management. Their differentiation, is several fold. One major point is they go after what they call the last mile. So they call this micro verticals. So the last mile functionality that would normally have to be customized, Infor does that work for you. Now, the advantage of that is two fold. One is you don't have to do a bunch of custom mods all that hard work is done. The second is, another part of the differentiation is cloud. So they chose, several years ago to go with AWS cloud to put their SaaS on the cloud. Charles Phillips said 'hey when we were an on-prem software company, we didn't manage our own servers for our customers. Or manage customer servers, we didn't do that. So why would we do it in the cloud? We don't want to compete with Google and Microsoft and Amazon in terms of scale, so were going to put our software on the Amazon cloud.' So that's another point of differentiation, the reason that is so important in the context of custom mods, is if you're rolling out new upgrades on a periodic basis, and you hear this a lot from Servicenow customers, for example another cloud software company. You can't do custom mods and then take advantage of the new releases. Because you're going to be way behind. Okay, so you have to have that hard work done so that you can avoid those custom modification. And that is something Infor has been very proud of. So as I say, $3billion company. Last year they took a $2billion investment from Koch industries. Now that investment, largely went to recapitalising the company, the private equity guys probably took some money off the table as did the four, what I call the four horsemen. They were the four, sort of new founders of Infor including Charles Phillips, Pam Murphey who is still there and then two others Duncan Angove and Stephan who have left the company, so they have got some succession planning now. We saw a different, two new faces up on stage Soma and we're going to have some other folks on that we'll introduce you to. But so, now we're entering a new phase and it's the phase of what Charles Phillip's coined 'Human Potentials'. So big focus this year on human capital management, we heard that. Big focus on AI, they talked a lot about robotic process automation. I just had a meeting, last night at the airport in DCA with the head of marketing at an RPA company, UiPath, they are smoking hot, they just raised 225 million they have gone from 2 million to 200 million over night. And that space is exploding, it was interesting to hear Charles Phillips talk a lot today about Robotic process automation, RPA. Which is essentially software >> Break that down for me. >> So RPA is software robots and software robots are used to automate mundane tasks. Having machines do very specific tasks and you are seeing this a lot in financial services and a lot of back office automation. It's not physical robots moving around, it's basically software based processes that machines can do. Repetitive processes, that machines can do better. Machines don't get tired, so they can do these repetitive tasks, take that away those mundane tasks away from humans. You heard a lot of conversation about that today. You also heard a little competitive fire. So Oracle is now taking ads out against Infor, we've seen that. All the cabs here, many of the cabs have Oracle branding on them. So Oracle is paying attention to Infor. >> And they're right down the road here too, by the way. You know, I mean, Western Virginia not far so this is their backyard. >> Well congratulations Infor, Oracle is paying attention to you that means, must mean you're hurting them We've seen this before with others, I mean we certainly saw it, you know in past days with IBM, we see it extensively with Workday. We've seen some kind of, tit for tat with SalesForce, even though SalesForce is one of Oracles largest customers. So that's been kind of fun, fun to watch. And now Infor, so Infor clearly is doing some damage, to the traditional guys. Oracle, SAP, Workday maybe not so much Workday is growing like crazy, but Infor claims it is growing SaaS revenue 50% faster than Oracle's SaaS revenue. It's growing double the rate of SAP, and growing as fast almost as Workday, is kind of what it claims. And so, this whole enterprise resource planning, HCM, vertical market software, horizontal software the market is always been hot. It's a huge, huge market. Many, many, tens of billions, it's probably a hundred billion dollar TAM. And the big, big whales are of course Oracle and SAP, and then of course, SalesForce and you've seen the emergence of companies like ServiceNow which has quite a bit of different strategy but with Oracle, with Infor's sort of Oracle heritage a lot of people in the company came from Oracle so they know where the skeletons are buried they know how to compete, they have relationships with the customers. And they're offering some differentiation, as they say with those Micro verticals, the last mile, and the pure cloud model. Now, if you look at the income statement you'll see the SaaS portion of the business only represents about 25% of the revenues but remember, that's a ratable model. So you're only recognizing revenue as you're, as the months go on, so you're billing sort of monthly if you will, or recognizing monthly. And so, as a result that skews and dampens the effects of the SaaS software, I think from a booking stand point is probably much higher, proportion of bookings I would guess closer to 50% as they said they took $2billion last year from Koch industries. That $2billion dollars didn't really hit the balance sheets, they get about $330million on the balance sheet. And they've a lot of debt, because they you know did you know, it was a private equity you know leverage deal. They did a lot of acquisitions, so they've probably got about $5.7billions of what they call net debt, which presumably is debt after cash. So I would guess close to $6billion in debt. They're a quasi, they're not a public company they're a private company, but they act in many ways like a public company, I would suspect within the next couple of years here, if this kind of growth continues that you'll see an IPO, from Infor. Although, presumably Koch industries, we heard Koch on stage today, they said they've made $15billion in investments in technology companies. $2billion, this has to be one of their largest. And, but that's patient capital. They get the benefit of the cash flow, they can probably take dividends if they want to do that. And if they're smart, and they invest and they can take market share from Oracle and SAP and others, and gain share in the market space, they can do an IPO. They're revenues are $3billion, their valuation, they implied a valuation based on the Koch industries investment is $15billion. So if they can take that $15billion to $30billion 20 to 30 billion, there's going to be a nice return. >> You know I thought, what's interesting about Koch too they talked about this, it's certainly as you talked about 2billion right. They put the money in, but they're also, it's a symbiotic relationship, in that that Koch is using it's organization as a test lab. For a lot of products and services, that Infor is producing. And allowing them to refine that under the Koch umbrella before they take it out to the market place. So that's pretty true, I feel like seems to makes sense. You have a company that has 60,000 world wide employees, you're in dozens of countries, you've a chance to let them take their products to scale, in maybe a somewhat more friendlier, controlled environment before you take it out to the marketplace. That seems to make a lot of sense. >> Yeah, we heard the CIO of Koch industries today and I talked to him last year, and we were talking about some of the technical debt that they had, again going back to those custom modifications that I was talking about earlier. They were in this terrible virtuous cycle almost a negative virtuous cycle where they had so many custom mods that they couldn't make changes. So the applications were becoming voxalised, so they were becoming non competitive and that is the last thing that a line of business wants to hear, is 'hey we can't make the changes, right IT says no, we can't touch the code, it's working or changes take too long. They take months or sometimes years, to get to a major release and so as a result Koch was looking for ways to simplify its application portfolio and its application infrastructure. The other thing that Koch industries has brought is, you might notice on the show floor here, you see Accenture, you see Deloitte, you're seeing Grant Thornton, now these guys weren't really going after, or going hard after the Infor base before. I think, a company like Koch industries does a lot of business with these SIs and so I think Koch has introduced the SIs to the Infor opportunity and maybe nudged them a little bit and say 'hey as a big you know supplier to us, we're a big customer of yours we want you to pay attention to that opportunity and in earnest go look at ways to partner with Infor. And that's happened, my intelligence suggests there are many multi million dollar deals that are being capitalized by these big SIs and they do a ton of business with SAP and Oracle. So that's another positive in the tail wind that Koch industries, I think it's brought to the table. >> Alright, you mention human potential which is the real overarching theme of the show here this week. Again, we're here in Washington DC. I was just listening to Van Jones from CNN. One of their anchors and political contributor talking about that as his personal mantra but certainly that intersects with what Infor is talking about in terms of unlocking human potential and using technology to do that. Share a little light from Charles Phillip's perspective the key note address that he gave, in terms of how do they view human potential and unlocking it with the use of their services? >> Well we're going to have Charles Phillip's on so we'll certainly ask him that but Charles Phillip's is a guy with a lot of potential. And that he is realizing that potential >> Lot of track record too >> Exactly, this is an individual with a military background, he became I don't know if you know the story but he became a highly successful Wall Street analyst. He wrote the seminal piece in the 90s that said the software industry, is too many software players and is going to consolidate. Larry Ellison, prior to reading that used to denigrate competitors for writing cheques not code. Meaning, his competitors were acquiring companies instead of innovating. Well then, he went on a spending spree probably 30, 35 million dollars in acquisitions orchestrated by Charles Phillips. And they totally remade Oracle starting with a soft hostile takeover. And then now you see Oracle, obviously this Saas powerhouse with many many companies that were bought in. Charles Phillips left Oracle, became the CEO of Infor and we heard today, architected an entirely new strategy with a stack, they call this thing the Stack. I'll just go through this briefly, I wrote about it last year, in the WikiBon blog. They've got the Infor platform, the Infor OS and then it goes all the way up to AI, the last mile software, the cloud. They have this thing called GT nexus, which is a supply chain network and that where their IoT play fits. Then they bought a company last year called Birst, to do BI and analytics, and then on top of that is Coleman. So they've got this stack that they are basically infusing into their applications, and I will answer your question. Essentially what they want to do is, use automation and artificial intelligence to essentially coach people, worker, as they're doing their jobs. So we heard today, that there are more openings than there are unemployed >> Employees, yeah. >> And productivity is going down. So Infor, Charles Phillips wants to attack that problem through software and automation. How do you do that? Well, if you could use artificial intelligence to monitor people's KPIs, they didn't use those terms but that is essentially what they are doing. And then provide feedback on outcomes, 'hey you could have done it differently. You could have done it more quickly. The outcome could have been better if.' Also, analyzing other factors like the relationship for example, using data to analyze the relationship between say tenure or were you recently promoted or turn over on the productivity of for instance stores, retail stores for example. And so, you're seeing an infusion of AI and software and automation in to the entire application portfolio to unlock the human potential. That's one part of it, the other part of it is Charles Phillips is big on diversity, big on women in business, and so that's another angle that I am sure we are going to hear more about this week. >> I thought it was interesting too any time a show comes to Washington there is a reason. And it's generally federal sector based, policy based. There's a regulatory undertone of some kind. And it was addressed somewhat on the key note stage here this morning. But the idea, the notion was that federal regulation and federal mandates, whatever, can't keep up the pace. They just can't, and it really is up to the tech sector because it works on a much different time frame, right? I mean, changes are made by the minute, whereas policy gets shaped by the year. You know, up on the hill here, not far about 3 miles 2 miles from here. So, the tech sector's responsibility in that regard in terms of being more diverse, of having more inclusivity, of looking at environmental considerations. All these things, and of unleashing human potential. And not at making a government do that. Not letting a regulation do that. That certainly plays in the Infor's thinking as well, I would think? >> Yes, so first of all we were down here at the AWS public sector event in June. And there were ten thousand people here. So AWS has a huge presence here. Infor and AWS are big time partners. And remember the CIA was the first deal, the first cloud deal, that AWS did, they won. IBM contested it, the judge eviscerated IBM in his ruling. Basically saying they were gaming the system. They were purposely misinterpreting the RFP. Amazon won hands down, it was a huge victory for Amazon. Forced IBM to go out and capitulate and purchase Softlayer for $2billion. I believe that only helps a company like Infor who has decided to be all public cloud, with AWS and drafting off AWS' deep ties to various government agencies, in the GovCloud. So for instance, AWS was first with fedramp. First with a lot of different certifications and security hurdles. And so Infor can just draft off of that. The CIA, again a big account, we heard the CIA talk in June about how security on the worst day of cloud is better than its client server applications on their best day. And so, I suspect Infor is doing business with the CIA although that's not come out publicly. But I would think that there is an advantage Infor has because of that AWS relationship. And that makes DC all the much more important for them. Well, we are at Inforum 18, we have a full 2 days of scheduling for you. Great guest coming up here on theCUBE. I am with Dave Vellante, I'm John Walls We'll continue here on theCUBE live from DC right after this break.

>> Announcer: Live from Chicago, Illinois it's the CUBE, covering Veeamon 2018. Brought to you by Veeam. >> We're back in Chicago, Veeamon 2018, you're watching the CUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. My name is Dave Vellante and I'm here with my co-host Stu Miniman. Day one of our two day coverage of Veeamon, On our second year. Vaughn Stewart is here who is the vice president of Technology at Pure Storage, Cube alum, good friend. Great to see you man. >> Good to see you Dave, Stu. >> Dave: Thanks so much for coming on. >> Vaughn: Great to be back. >> So Pure, you know, I remember when you joined Pure and you were like, "Dave, this is going to be the rocket ship of a lifetime." it's turned out to be the case. First company since NetApp to hit a billion dollars in the storage business. It's like independent storage companies are back. >> Yeah. (laughs) >> So give us the update, what's happening at Pure? >> So fantastic year. Wrapped up end of January, right. So first independent storage company to hit a billion dollars. Actually, we're kind of on the cusp of maybe being the the fastest infrastructure company, if not the fastest tied with being the fastest to hit a billion dollars. So the growth rates been great, the products, obviously, have been off the charts. Whether you're looking at it from an analyst's perspective, you know, the gardener reports, the IDC market scape, so if you look at from the customers perspective with the NPS scores, right. Just crushing in terms of the products, the customers stating that we're not overstating the capabilities, and we make some pretty bold statements. But when you kind of boil it back to where we're at now, I think our focus is helping customers adopt a data centric architecture as a part of their IT or data center modernization plans, right. This is, we've kind of gone through this phase of like virtualizing everything, now everything's in the cloud and now we're starting to mature a little bit and we're always looking at this tsunami of data that's being created and it's more around, where's your data going to reside? Because there's going to be some gravity around it and bring the compute to where the data should reside. And so our products and our strategy is to help customers again, this data-centric architecture, adopt new technologies that are going to help them radically shift how they operate, changing the cost of operations, changing the complexity to either let an existing storage team scale to a larger capacity per full-time, you know, FTE or to allow actually the application teams or the private cloud teams to just manage their infrastructure stack, right. We're seeing we're seeing kind of growth in both areas. I think beyond that, our technology with our evergreen storage as a subscription model has also been able to be transformative for Enterprise about how do they acquire, refresh, and introduce new technologies within the storage space. And so it's been pretty exciting. >> So let's talk about some of that. I remember, I've I've been around a long time Stu, as you know, so Al Shughart, the legend, once told me when I was just a pup trying to understand the business. He said, "Dave, the storage business is simple. The customers want it to be dirt cheap, rock solid, and lightning fast." >> Vaughn: Yeah. >> This is the days of spinning discs, which we're kind of dirt cheap, but they really weren't that rock solid and they really weren't that lightning fast. So you guys actually delivered on that promise but you added some other things. Simplicity, the business model of reduced friction. You mentioned Evergreen, so it's not, obviously, not just about flash, where we say, "oh, flash, Pure storage flash, we have flash too." It's so much more than that. The way you positioned it just now the company in terms of data centricity. And, as they say, the business model innovations have really worked well for you. You've been able to stay ahead of the competition. I wonder if you could comment. >> Sure. So I, for your audience, I think it's important to maybe back up a bit. Pure was born in in the the wave of a number of all flash arrays. >> Dave: Yeah. Right? And a fair amount of them were acquired by large existing storage vendors. And I think now that the dust has settled a bit, you know, we were kind of the phoenixes that rose through those ashes, if you will, within the storage space and I think, really, the key driver there was, it wasn't about performance. Flash makes everything faster. >> Dave: Right. It was about a combination of the business model, the operational simplicity, but also, what I would call, the Tier One Feature Sets, right. You had to deliver on six nines of greater availability. You had to have all the data management capabilities to plug into a large partner ecosystem like veeam, which, you know, we're at Veeam live and that was kind of what I would call Act one of Pure, which was, you know, flash ray based, you know, storage for your traditional enterprise apps. Last year we introduced flash blade, right. This was a radically different architecture. It was to scale out a scale out blade-based storage platform that scaled capacity and performance linearly. And the adoption in that space has been this next-generation apps, which... Are just..the sets are growing, you know, out of control and beyond what we would have ever expected with an Enterprise app. So whether it's AI, machine learning, deep learning, analytics, or this new use case we're seeing, which is rapid data recovery. The flash blade, because of the combination of its low latency and massive parallel throughput, has really been a big growth vector for us and it's kind of act two, if you will, of Pure Storage. >> Dave: Go ahead Stu. >> Yeah, Vaughn I'd love to hear more your thoughts on, kind of, an application proliferation. so I think back, you know, you and I lived through that wave of virtualization. While I love virtualization, one of the challenges I had with it was I could take my old application that was probably already too long in the tooth and stick it in a VM and then keep it for another five to ten years because it didn't care about the hardware, their OS, and all that standpoint. Today, talk about cloud native apps, talk about IOT and analytics and all of these micro services and everything like that. It's a huge impact on infrastructure and how we build things. It brings up to speed how we bridge from, kind of, the old world and the new world. >> Yeah, I'm glad that you asked this question. I wish you would be coming to our conference next week - >> Stu: Well, Dave will be there. >> because we'll have a session discussing this and it'll include an internal case study. And so that's all the details I can give right now. For a long time I think a lot of IT vendors, particularly, those who made hardware products, try to position this on-prem versus the cloud, right. and it was really the wrong mindset. Cloud is just one more deployment model for an organization to look at. The question that I think organizations have is, what fits where? And I think, to your point, if you're looking to build a new application or re-platform an existing, what you have today versus in the past was, you had a contained set of APIs and interfaces to work with, right. If you were building on, say, you know, a database vendor's enterprise business suite that was the tools that you got to use. Today you look at what's available, an open source or in the public cloud space, and you get to build a massively disaggregated application that's comprised of functions and and microservices, right. And it gets to leverage these notions of scaling on demand and being being very elastic. What I would share with you and what we discussed with customers is, your development team will want to go as fast as they can and leverage all these new tools and they're iterating very quickly, and the cloud is an ideal platform for that. But you need to plan and look forward to, around what's the the volume of data that you may be dealing with? What's the access requirements of that data over time? And where's it going to be a better position? Should it sit in the cloud? Should it sit on Prem? Should it sit in a private to public cloud hybrid type of architecture model and leverage, say, the compute and all the software agility within the cloud and yet still have stewardship over your data and not have to deal with with maybe unforeseen things like charges per, you know, API call or egress charges things of that nature. >> And Edge as the whole, >> And so I'm grossly simplifying a lot this. but these are the conversations that you get within the enterprise, which is where the sweet spot is. These are real considerations that that they have right there past the is cloud secure or, you know? They're past the data sovereignty type of concerns. They're more around how is this going to scale long-term because, for example, I'll give you an example. So we rolled out meta, which is our AI as part of our support for our products. This all getting ahead of the customers and predicting faults, getting them... This is what helps us achieve greater than six nines availability across the entire fleet for the last two and a half years, right. It's, it's getting ahead of the problems. When we work on looking at some of the AI that we create around meta and we want to test it, we have to download a year's worth of phone home data from the cloud. That takes 45 days to download today and it's not going to get any faster as the install base gets larger, right. And so those are challenges that you have to look at and say, maybe I started in the cloud but maybe I need to look at something in a hybrid model because it's going to impact my business agility. And so these are conversations that we can have and our architects have with customers based on whatever their criteria or forecast look like. >> So just about a year ago Scott Dietzen stepped down as CEO, brought in Charlie - >> Vaughn: Yeah >> new leader. It was kind of, kind of interesting, it was right on the heels of Frank Slootman doing something similar. Frank Slootman just stepped down as chairman and so how's the new leadership going? What, what has Charlie brought? I can't wait to interview him next week on the CUBE but give us your take as somebody who's been an industry observer and, obviously, a long-time Pure employee. >> So ,so a great question. So just for the audience to know, so Dietzen is still with us, right. He stepped down from being the CEO and is now the chairman of the board. and I owe a large gratitude of debt to Scott. Scott brought me into Pure and I'm always encouraged when, you know, every now and then you get that that direct email from him, you know, you know, keep, you know, keep being a thorn in someone's side and push this forward. That was a little self-serving, so I apologize. But what I like about Charlie is, and, and understand I was, I was with Ned F for 13 years, right. And so we did this large growth cycle, not as early as with Pure, but going through a lot of the same growth pains and and whatnot that we have today. But we did all that growth under Worman Joven before they changed over. What was nice about Scott is, he told me on day one that he didn't know how far he would take Pure but it was apparent to him that he had taken it as far as he could, he would find his, his, his heir and obviously Charlie was the choice. And what Charlie's brought in has been a lot of structure, right. The formation of business units, a lot of accountability, a lot of, what I would say, that maturation phase from startup, right. That's kind of grown to the, to the the maximum output of your current organizational structures, to looking forward into a structure that that is going to allow us to scale better over time, right. Continue to grow as well as.. I think Charlie be the first to tell ya, you know, Pure's on a trajectory to hit two billion dollars and can do that on inertia in the current products, right. Charlie's focus or one of Charlie's focuses over the last handful of months is, is, what are we going to become two years from now and what investments do we need to start making in the near term to get prepared for two years from now? >> So I, I brought up Frank Slootman who's in the service now because I know, I know Frank and Scott were close, right? There's some board action going on there over the years, they're part of the Silicon Valley mafia with the Mai Bucherii. But but I, and we can joke about that but there's a there's a culture of succession that has really taken hold in in certain parts of the valley and, and again, very similar to what we saw as service now, where was the new guy was brought in to take them to the next level. And the existing CEO, you know, mature enough, you know, maybe, maybe worked so hard for all these years too, maybe felt like they need a little break. but still mature enough to say, okay, I know my limitations and I want to bring somebody else in. So it's been sort of this new thing and I want to tie it back to something we were talking to before on the CUBE. I mean, you guys hit escape velocity. When you look back at the sort of the virtualization craze with Three Par and Isilon, Data Domain, Compelling. Yeah, they kind of hit a billion-dollar status you know, they hit unicorn, but they never hit billion dollar revenue. And, and so now, and then the other thing you talked about was some of the bigger players decided to buy up flash companies. >> Vaughn: Yeah. >> And they said, you know, rather than pay 2.5 billion dollars for a data domain or Three Par, we'll spend a billion dollars or, in some cases, hundreds of millions of dollars and then we'll organically grow that internally. Did it work? Yeah, maybe yeah, you know. Maybe some of it, maybe not. But, but you guys stayed the course and are now on track to do two billion. >> Vaughn: Yeah >> So here's my question, long-winded sort of narrative babble, sorry about that. I used to question Worman Joven all the time Tucci, even. Can you stay independent? Right? That was the big question. You know, because Converged is coming. But now it looks like being an independent is actually in vogue. Best-of-breed is actually still a viable business model. >> So obviously I'm not in on the inside of whatever the board decisions may be. >> Yeah, but you're an observer who know this business. We're kind of talking about Vaughn the prognosticator, analyst, if you will. >> What I think is different today, and Stu and I were talking about this because we ran into each other over in the corner with Duncan. You know, the emergence of all the flash vendors and them getting acquired and really what's happened by and large is just the same old products just got flash injected into them and, you know, got, you know, the the vendors hope to get another decade out of them. But okay, they're faster, but it doesn't fundamentally change your business model or your operations and sometimes that's a good thing, right. For some customers, right, their change averse. >> Right, they don't want that disruption. >> Yeah. For us, right, we're trying to usher in now this this next wave of shared accelerated storage and it's a disaggregated model, right. Start to look up it at what, you know, in a commercial sense, if you will. What are the enter.. what are the the hyper scalars, you know, delivering, you know? They're not running data direct attached storage. They're not doing HCI, right? They've got pools of compute and pools of storage and it's either disk and cold or it's flash flash and hot and, you know, they've got network and it's all over Ethernet, so it's greatly simplified. We're trying to help our customers with, with that type of architecture. Whether they're looking at simplifying their private cloud or extending the private cloud to the public cloud, or what's even more interesting, as they look at like their data pipelines, you know, a lot of, you know.. There's, there's AI and analytics in every organization of every size. They may or may not sit inside the IT department but they tend to follow that model of eighths and software. So I'm just going to do it on DAS and I'm going to build this siloed cluster. And, you know, it must be cheap regardless of whatever the efficiency I get out of it. And what we're trying to help large organizations look at is data pipelines and flow and the flexibility that you gain by separating compute from storage and not having to worry about the performance issues or constraints of disk-based systems from a decade ago because technologies like flash and now with non-volatile memory Express and non-volatile memory expressed over fabrics, right. You're getting direct memory to memory communications from the servers to the storage. So you're getting all the benefits of pooling and sharing your storage with all the benefits of it without a local bus in terms of speed and performance. And so it can change, particularly, a large volume of data. You can change your agility. >> So that that is certainly a tailwind for you but it was a tailwind for a lot of companies and you have the product. Let's assume best product just for sake of argument. I'm sure you would agree. But best product doesn't always win, right? So what I'm hearing is there was business model innovation. >> Vaughn: Yeah. >> Obviously very strong go to market. You guys knew where all the skeletons were buried with all the reps that you guys hired. But there were other factors involved in your ascendancy, which maybe is independent of the structure of the industry because the industry structure is changing. It's going from, you know, now remote cloud services into these digital, this digital matrix and somehow you have to fit into that digital matrix and participate in that. >> Yeah, it's.. I think you brought up two points,\. So I think if you if you're going to be a start-up, to be successful, it's not just technology. You've hit the head on the nail there. Pure had.. the technology had to deliver, Pure had that. The business model was innovative, the marketing was off the hook, right? For a start-up, you know, we were punching above our weight but you also have sales, have sales force execution and, you know, you never know what you get when you walk into a start-up. But you've got to.. If you don't hit on all four of those dimensions then you don't achieve escape velocity. In terms of shifting from startup to, you know, becoming mainstream. Not only did we achieve a billion dollars last year, we were cashflow positive for the year and we were profitable for Q4, right? So that puts a lot of wind in ourselves as we go forward. You know, with, at the end of last year, a half a billion dollars in the bank and now a billion dollars in the bank. You know, for us to go you know figure out what we're going to grow and go into. I think moving forward and being independent, I think we'll see, right? I think there's always a tick-tock in our industry, right? Things are distributed, they're centralized, their distributed, I want one throat to choke, I want best-of-breed. I think with all the distributed apps and all the analytics platforms that are going to start to become more important than what we're used to in the X83 space. I think best-of-breed is starting to rise up right now and so I think the runway for Pure to stay independent is there. Don't get me wrong, we're going to have to do our works with plugging into clouds, right? And all those those ecosystems because customers want a transparent experience. But we'll be sharing some news on that, I think next week. >> Well and excited to here that. The cartel will continue to suck up startups, no question about it. But, you know, we love companies like Pure, put Nutanix in that mix and it was sad to us to see all their run of the virtualization comers, they just disappeared. Because if it's just the cartel building new products, you're not going to have the level of innovation that you get with VC funded startups in the valley. you just, you're just not. >> Well, in the US you're seeing, I mean, you're, in the US you're seeing VC investment starting to diversify a bit, right? >> Dave: Yeah >> Colorado's getting hot, the Boston area is, it has been there for a while but it's getting hot. >> IOT and security. >> And, you know, that's been the great thing about, you know, about IT in the US, right, is we've been an innovative landscape. I think the barrier has probably forced some innovators out based on just the cost of living. So, you know, who knows what the mix will look like a decade from now, but yeah, we're still going to be Silicon Valley centric for the near-term. >> So I love talking you because we can have these conversations. We were joking off-camera, we could go for 90 minutes, which we easily could. We got to, we got to go soon but let's talk about Veeam, relationship with Veeam. You guys are kind of birds of a feather in a lot of ways but, but take us through that. >> Yeah, so the opportunity to partner with Veeam was a no-brainer. There were synergies there, right? Pure and Veeam both trying to just disrupt legacy markets, doing it through simplicity, right? Riding the wave of, you know, virtualization as a primary business focus but not exclusive. our Net Promoter scores with both companies are off the charts, right. Customers love it and, you know, we're multiples higher than any of our competitors. And so bringing the technologies together were real simple. So last month we announced, four or five weeks ago we announced and released a new set of solutions and integrations. It was comprised around three areas of benefit, right? Accelerating backups, increasing the speed at which you could recover data, and adding a new level of agility within your ecosystem. So delivering those three value props were based on us supporting their Universal API adapters. So now that they can offload some of the backup process to array-based snapshots and that preserves the performance, makes the window collapse faster. That's where when production data sits on the flash array. We've also certified putting the flash blade behind the Veeam servers as a backup data repository and the benefits of that from a backup window are faster data ingestion times across your real estate. Obviously, smaller footprint, lower cost within the data center. The bigger impact on both of these is on rapid data recovery. So with Veeam, through their explorer integrations, you can pull files, disks, VMs, applications, right out of the array snapshots. If the array is still online but someone's just munched the data, if the array is no longer there and you need to pull from the flash blade, flash blade gives them a capability that they never had with disk, which is they can start because, you know, how Veeam recovers, right? They actually start the data services and recover them from the backup repository and then live migrate it back to the production environment. With the live, with the back and the data repository being all flash, now they can bring up a significant, if not all of your data back online and then trickle restore it back to the production data sets. We had a customer with a large distributed database that was on a more traditional disk backup system that was really focused on ingest, right? Make the backup window not so much focused on the restore times. It took them in excess of 36 hours to put back their database and this was the mission critical database to the organization. We've come in and replaced that. 36 hours is now 30 minutes. So is all flashes as repository for your backup for everyone? Maybe not for every organization but we're seeing a big growth ramp on that in the enterprise. The last piece that we've brought to market together in integrations is, integrating with their data labs. That's their environment to be able to on-demand create, test, and DEV infrastructures for you and that pairs really well with all flash arrays and snapshots because it's instantaneous, consumes no new storage, and our automatic QOS preserves that, preserves the resources for the production environment from the lab. And so those are our three areas: accelerate backups, rapid restores, and give you some agility with your test DEV. >> Okay and the agility in the ecosystem is oftentimes underappreciated, right? >> I'm amazed at the customers that I.. Large enterprise customers, right? Revenues in the tens of billions of dollars that you still meet with today, where they've half staffs that their job is to restore, you know, an Oracle database to an Oracle developer and that's all the guy does 40, guy or gal, does 40 hours a week, it's amazing. >> Right, Vaughn, great to see you again. >> Dave, awesome. >> Thanks so much for coming to the CUBE. We'll see you next week Pure Accelerate at San Francisco. We're there Wednesday, I believe, we're broadcasting. So look for all the things that Vaughn teased. He showed a little leg on some stuff, so we'll be covering that next week. We're back here tomorrow. Stu and I will be kicking off at 9:30 with Peter MacKay, so don't miss that. We're out for today, Veeamon 2018 the CUBE. See you tomorrow (electronic music)

>> Announcer: From Gillette Stadium in Foxborough, Massachusetts, it's theCube! Covering VTUG Winter Warmer 2018, presented by Silicon Angle. >> Hi I'm Stu Miniman and this is the VTUG Winter Warmer 2018. Happy to welcome to the program a regular here at the VTUG, but no longer a local, so Chris Colotti who's currently the Field CTO at Tintri, great to see you Chris. >> You too Stu, it's been a while. >> And love the attire. >> I know, I think every time I come and do a presentation, I have a Patriots jersey on of some kind. >> Absolutely, I mean there's a few things we know you for, so you love your virtualization, you love your Patriots, and there's usually some workout thing, so are we going to get some fitness tips (mumbles)? >> Not today, actually you don't want to know what I did the other day with a buddy of mine, so you'll see me hobbling around because it was not a good leg day (laughs). >> Okay, so we'll be getting, I always like to hear, I just had a user on of what they weren't like in the industry, so you'll give us the what not to do to make sure that you can keep your fitness goals. >> Yeah, don't hook up with a buddy who has a lot of sandbags in his truck that likes to work out with them. >> So Chris, for those of our audience that haven't been to the event, and give us just a little bit about your background, what you're doing these days. >> Yeah, so I mean VTUG's, man this has been around forever, I think. >> 12 years now. >> 12 years the Harneys have been doing this, and I've been, I think I've been a part of it for a better part of the last decade or so. One being a Patriot's fan, two being a virtualization person, and where I kind of grew my career from sort of being a Sys Admin to where I am now, I just think this is one of the better events because it's all technology, right? I mean we run into people that it's not just virtualization, you got AWS now, you got people of all walks of life that comes to this and honestly, I think you can't beat the venue, right? I mean especially, how many times have we been here where they cover the windows? If the windows are covered, it's a good year. That's what we say. >> As a matter fact, this is the fifth year we've had theCube, and every year the Patriots are still in the playoffs, working towards the Super Bowl, and they're one step away again. >> I think the worst year for me, was I actually had the center stage keynote one year, and they told me while I was presenting they were actually on the field practicing, and it was all I could to not just stop talking and say I'll be right back (laughs). >> As you said, better part of a decade you've been here, you were working for VMWare, when this was a VMUG, but you've been involved, tell us just what you're doing these days for work. >> Yeah, so I left VMWare and moved over to Tintri, which is I'll flash the word partner, I came over there, actually I came over as a cloud evangelist kind of person, and that shifted a little bit, and while that was around how to use our APIs and things like that for automation and private cloud, now there's actually three Field CTOs, I'm one of 'em, and I spend most of my time really talking to customers, doing events, doing roadmap presentations, where were going, what we're doing, I still spend my fair share on the road doing the shows and stuff, VMworld. >> You just threw in a bunch of things there, talk cloud, API, storage, what are you hearing from customers these days? What are they getting right? What are they struggling with, and what are they looking for? >> Yeah it's funny, so for a long time I was a cloud guy, right? I mean I did VCloud Air, I launched VCloud Air DR, and I think what I heard coming over to Tintri is good, folks are still struggling with that whole, "What do I put in the cloud? "What don't I put in the cloud? "Do I bring everything back?" We've got a lot of customers that have brought stuff back on premises, I think a lot of customers are just still struggling with that concept, I mean one of the first presentations I did, probably I think, here it was back in 2010, right around that timeframe, when VCloud Air, or VCloud Director was launched, Chris had me, Harney had me come down and do VCloud Director, and it was deer in the headlights, you know? It was so bleeding edge for VMWare at that point to have this cloud product and this automation stuff, and then fast forward to today, you know eight years later, I still think people are struggling with that. They're just not sure how to deal with it, right? And operationally, I think people come and really figure out it's not about cloud so much as automation, we've got to simplify the way we do things, we got to automate more. We've got to take day to day operations and do something different with 'em. >> Yeah, I mean a line we've used often is cloud is not a destination, it's an operations model. >> Yeah, for sure. Unfortunately I think there's a lot of people that still think it's a destination, the old To the Cloud ads, remember those? >> Microsoft, absolutely, there's lots of jokes on that. Yeah, you gave an interesting keynote this morning, I actually had one of the users that came on our program earlier, and she was like, "I really enjoyed that." So Luigi Danakos, a friend of ours and you, tell me a little more about IT in careers, because we know the only thing that is consistent is that things are going to change, so give our audience a little bit of taste of what you talked about. >> So yeah, it was actually interesting, so we came up with the idea because I've come to these and done technical presentations all the time, but inevitably I always get somebody, or a couple people come up to you and say, "How did you get where you are? "How did you evolve?" And people who know my story, what's interesting about mine is I went to school for architectural engineering, I actually have a degree in architectural engineering, drawing blueprints and designing houses, and they always look at me and say, "How did you "get to here? "You were a System Admin, and I'm a Sys Admin, "and how do I grow my career?" So Luigi and figured why don't we sort of take a little bit of that history 'cause now we're kind of, I hate to say we're the old guys on the porch these days, but back in the day, we were younger, we were faster, as you go forward, how do you stay relevant? And that's what we wanted to kind of talk about, so we talk a concept from an author by the name of John C Maxwell and we kind of took one of his books and we kind of cobbled it down to five different aspects and we just talked about what to think about, how to move, not just always knowing the technology, where do you want to go? What do you want to do? And how to get there, not just to sit and say, "Well it's never going to happen for me." You have to make something out of it yourself, and I think the response was pretty good, it was different, it was the first one in the morning, but it wasn't getting hit at 9:00 a.m. with technicals, it was really just us telling our stories around how we got to where we were going, and one of the big parts about Luigi was having just been let go from HP and now he's done some interviews and I thought it was really great 'cause he came right out and said, "Y'know what? "I'm going to just do my own thing. "I've just decided there's never a good time "to start your own company, so why not do it now?" And that was after he went through four or five interviews, so hopefully it resonated with some people. For me, it's always gotten harder to learn. I think as we get older, I made the joke in the session, I lost my phone first thing this morning. Literally, couldn't remember where I put it, dropped it, I called my best friend, Chris Boyd, who's one of the other CTOs and I said have you seen it? Because I'm going to send the, I was going to have him run around the west side with the buzzer going off, the Find my iPhone to go find this, I can't remember what I did yesterday, so learning gets harder. >> Yeah, well learning's harder, the bar's not that high to kind of get into new stuff. When I walk around the show, two things struck me. Number one is the vendors, every single one of them are hiring SEs, and they can't find enough good quality people, and it's more about the people, then it is, you can train them up. And secondly, some of these new spaces, talk about like the cloud space, if you get your Associate's on like AWS? Like people will call you immediately, and there's so much opportunity out there, we both had lots of friends. There's changes in consolidations in the industry, and therefore there's people that hey, it's time for a change, so-- >> Well I never thought I would work for a storage company. Well I worked for VMWare which was acquired EMC years ago, but we still never, as VMWare employees, we didn't work for a storage company. >> VMWare's a software company. >> We were a software company, and I still actually look at Tintri as a software company, yes we sell an appliance, but the crux of what Tintri does really is the software of the OS itself and that's what makes it different. So yeah, and I mean I've had to learn more about storage then I knew before, and I was telling a guy at the show, one of the things that Luigi and I talk to people, always said just learn something new every day, just as small and as silly as it was, and we've told different stories, and a guy asked me, "So what's the last thing "you learned, technology-wise, outside of storage?" I said I actually learned containers because of my home media server environment. I had to go out and learn Docker because I wanted to run some stuff and I didn't want to stand it up, I just wanted to figure out how containers work, so now Tim Gabett and I, we're on the phone back and forth, alright how'd you get that container run? And what'd you do for the storage, and how'd you deal with this? But that to me is what keeps your brain a little bit sharp, I mean I don't do puzzles and things like that, but those stupid side projects we all do because we're technologists I think help. >> Yeah, and you never know when those side projects and passions could turn into an opportunity from careers standpoint? >> Yeah, yeah, yeah. >> Alright Chris, you've been coming to this event quite a long time, as we said, give us the what's changed and what's stayed the same from your standpoint? >> Aw man, that's a tough one because I think a lot of stuff has essentially stayed the same in the realm of networking and storage, I think there's always a new player, but I look back at the last, I'll probably get myself in trouble here, but what was the last big innovative thing in the IT space when I was a System Admin, and I go back to those easy things, like I remember when I did my first VMotion, and it was like how does that work? And I used to have conversations, and I do that today with engineers, and I say what are we innovating? What are we doing to change the game? And to me, and again this is all my personal opinion, I suppose I'll preface it with that because for most people that know me know I have a pretty strong opinion on stuff, but I think that's the tough part is how do we move forward? How do we evolve to the next, really big, innovative thing that just blows people's minds? And I think AWS definitely did that a little bit when it really started to go mainstream and people realized it was a real thing, it wasn't a book store anymore, they had this other stuff, and we go through these cycles, right? But I think in the standard IT space, I'm still trying to figure out outside of those, what's the next really cool thing that we're going to see from the different vendors? And who's innovating and who's just sort of maintaining? >> Yeah, absolutely, well I can tell you that people here are excited, there's a lot to learn about keynotes this morning, I mean everything from what's happening in the automation space, developers, not a ton of developers at a show like this, but definitely lots of opportunity there, you talked the AWS presentation, he's like, "I'm live-coding and showing you Lambda stuff." Most of the people here aren't quite ready for some serverless world-- >> That was like me doing VCloud Director presentations (laughs). >> And things like that, I remember three years ago, it was like the AWS 101, everybody was like, "Oh my gosh, "this cloud thing sounds really amazing." So it takes some time, we've heard about it. I remember back when I heard about VMotion when it was in development, and still one of those things where you look back at your career and like wow, that was an amazing, it was that magic technology. >> It was almost those conversation, where were you when you did your first VMotion, right (laughs)? >> As a matter of fact, Duncan actually did a blog post about that, "Where you heard about it?" And I pulled in (mumbles) into the thread because I was lucky enough to go to a conference and moderate a session where he explained down to Kernel Zero how it worked, and it was interesting-- >> How he actually did what he did. >> You know what they say, "Any technology that is significantly difficult "to explain might as well be magic." So you're right, interesting stuff to see where innovation's going in the industry, I think most people I know are pretty excited, there's so much going on there, there's no shortage of new things to learn, we just need to reach out and take those opportunities, and I love your advice to keep learning something every day. >> As small as it is, I told these guys this morning that one of my biggest learning experiences was when we moved, I had to learn how to drive a motor home, a house, and deal with stuff that I've never done, right? But it's all learning. I challenged them today to just whether you're going to the sessions or you're just walking around where the vendors are, just understand what those people do and take that away and internalize it and see how you can use it. >> Well Chris, I'm glad to see you're still a true blue Patriots fan there-- >> The tattoo is still real (laughs). >> You haven't picked up the Southern drawl just yet. >> No it's funny, my wife said I pick it up a little bit when I'm around our neighbors, and then when I come back up here, I can really turn on the Boston accent if I tried but (laughs). >> Well, you all come back for lots more coverage here from VTUG Winter Warmer 2018. I'm Stu Miniman, this is theCube. (exciting electronic music)