>> From theCUBE's studios in Palo Alto, in Boston, connecting with all leaders all around the world. This is a CUBE Conversation. >> Hello, everyone, this is Dave Vellante and welcome. We're going to do a little preview of ThoughtSpot Beyond, and we're going to look at the intersection of cloud, data, search and analytics. For a decade, we've been collecting all this information and tapping data sources for many, many different places. Now we're at the point where we can very cost-effectively and quickly put data into the hands of many orders of magnitude, more users so the data can inform opinions and ultimately actions. With me is Sudheesh Nair, who's the CEO of ThoughtSpot. Sudheesh, it's always a pleasure to have you on theCUBE. Thanks for coming on. >> Absolutely, my pleasure, Dave. Thanks for having me. >> You know it's ironic that we start this decade with so much disruption to our lives. It's forced us to become digital businesses really overnight. I wonder if you could talk about the role of data as it relates to our digital lives? >> I think the idea that data somehow directly impacts our lives sometimes can be farfetched. That is because we don't really talk about it in the right way. Data can be this archaic mountain of things that people don't really connect with. What we should really be talking about is what data does, the byproduct, the end product of data, which is the signal that we get out of the mountain of data, the insight that we derive from it and the action, the bespoke actions that makes our lives possible in this new world that we are all living in. If you really do a good job of talking about what data does for you or the by-product of what the data does for you, I think people will understand that we are incredibly connected, incredibly dependent on the signals that we derive from the data that we are giving out to the world that we are operating in today. >> We had a fire ready and aim because the speed at which we've had to adapt as we've never seen this before. I'm wondering if you could share with us what you're seeing. What kind of challenges this creates for organizations, specifically in terms of being able to leverage their data assets? >> See, I think if you think of the last eight, nine months, sometimes in our industry, it is easy to sort of look at this as an opportunity, more of an opportunistic way of looking at how can I sell more data driven things when the world is sort of falling apart. You walk on a downtown, you see all these restaurants closed, parking lots empty. My sort of less than in the last eight, nine months is to be more outside-in as opposed to inside-out. That is, why are we doing this, is now more important than what we are doing. In that context, my biggest lesson that I've learned is that the thing that stand in the way of delivering value for customers almost always is not technology, not product and not even quality of data. A lot of data people will say it is the data quality that is holding me back from doing. It is lack of courage, lack of vision, lack of ability to sort of empathize with your customers and truly see what can we do to make their lives better, where data driven insights might be a part of it. I really believe that organizations that are differentiating by providing better services where they use data to do that are clearly coming out ahead as we are looking at the end of this global pandemic. >> It's interesting what you're saying about data quality, because I agree with you. I actually think it's access to data because as a business user, I can look at data, ask a couple of questions and say, I can get pretty close to the truth. If you think about organizations generally, but specifically business users, they've been clamoring for more fast style access to data and really the time is now for them to realize this vision. I wonder if you could share with us what's happening in ThoughtSpot business in the past month, 'cause that's what you're all about, is that easy, fast access to data. >> I always talk about the decision making pipeline. I know one end, you have the data that customers are happy to give. However, it's a two way street. They are saying, look, I'll give you my data, in return I want you to do two things. Number one, make sure it is safe and protected. Number two, you are using that data to deliver a bespoke experiences for me, bespoke services for me. That is I'm giving you the data so you will get to know me and treat me as an individual, as a person with the likes and dislikes that are different from someone else's. If you don't do that, you're breaking that contract. When I think of this continuum of data to insight to knowledge to action, action is where the users benefit. I sort of sometimes worry that the chasm that exists between the people who can speak the data, the SQL, the data, warehouse people who have usually the answers and not necessarily have the questions because questions are usually coming from the business users. Our sort of purpose in life as a company in the world has been simple. That is let us break that barrier. Let's move that silos and then unify so that people with questions can get answers. People who know the business can get the answer from the data without any tax on their curiosity. It is easier said than done, but it is a journey. I strongly believe that pushing the ability to inquire and get insights from the data all the way to the front line, where business users interact with their customers, the businesses customers, the consumers, the clients, if you don't do that properly, there is no way to keep up with the velocity of change that the world is throwing at your business. >> So speaking of the data sources, one of the data sources I sometimes look at it, you look at the stock market, it is funny. The last month Pfizer announces they got a very highly successful trial and the stock market goes up 800 points. You sort of look at that and say, that's a data point. I recently released a number of pieces on cloud and its impact. After that you saw up on a cloud stocks, everybody panicked, sell tech. Even though written cloud's not immune to COVID, it's clear from our data that cloud migration has been very much accelerated since the pandemic hit and I don't really see that changing. I wonder if you could talk about the ways in which you see cloud changing, how organizations operate and really what's missing when it comes to getting the most out of their cloud investments, specifically around analytics. >> It is like any other function. Data analytics is not different in what the cloud does for the customers. I used to always talk about the world of computing, the world of technology as a race against commoditization. Imagine that it's a ocean that is warming and there's an iceberg that is floating on it. As the ocean warms the iceberg is melting and if you want to survive, you've got to keep going up the mountain, the iceberg mountain. In this example, the commoditization of technology is the ocean. Anything that you think is unique, anything that you think is proprietary, it's going to get commoditized. The reason why that's happening is because people want to go up the value chain. That's the iceberg, that's the mountain. If you use that metaphor, what you will see here is that people want to go up the value that the data analytics deliver as opposed to how cool or how differentiated the process of delivering value is. Let me explain that. Imagine that you are producing a lot of content, I am pretty sure that you have ways to sort of collect the data on how it is making an impact. That is how many people watched it, how many of them were young versus old versus Salesforce engineering versus marketing versus... You can slice and dice the data. That is where today's data analytics stops. Now, imagine if you can take it to the next level, that is what impact is it having on my consumers? Are they able to get better jobs, for example, because of a technology that you talked about or theCUBE's ability to sort of democratize access, the way sometimes you take complex technology and simplify it. Is that making easier for some execs to catch up with the speed with which technology is changing? In turn, which makes their business model agile. Our thesis is that when we stop data analytics at the noise level, the data level, the insight level, we are only doing half the job. We need to go all the way through that value chain, climb all the way up in that iceberg and think for the customer. What am I doing for the customer? There are recent examples of our banks, largest of large banks, where they had inherent bias when it comes to how they were giving loans to minorities and people of color, or the people who have an accent on the phone, they're actually calling on customer support. These sort of things are not an AI problem or a BI problem, these are human problems. By breaking the barrier between business users and their consumers, where data become an inherent part of deficient making, you can make tangible difference in the world. I think that is what we are trying to do. I know it sounds somewhat naive and utopian, but I do think this is possible if you really approach it outside-in. >> And outside-in thinking is critical. I want to pick up on something you said about kind of moving up the value chain. We've watched over the last decade, sort of the SASification of many industries. You guys recently announced ThoughtSpot Cloud, which was your first SAS offering. Tell us, how's it going? What's the uptake like, the adoption? What are customers telling you about what it's doing for their business? >> Again, this is the same outside-in story. It is relatively new, it's only been a month. The interest is pretty high and we have closed a handful of customers. I don't want to claim victory yet, but the signs have been very positive and it does not surprise me because it aligns with that story that I talked about growing up the value chain. Traditionally, when we deployed ThoughtSpot, we deployed in the customer's VPC, their own cloud or in the data center. The problem is when you are doing that, they are responsible for integrating the data, connecting the data, prepping the data, managing it. There's a lot of work that goes with it. But ThoughtSpot I would ask you, is it possible for us to do as much for the customer with TS Cloud, ThoughtSpot Cloud? That is you just go to ThoughtSpot Cloud and connect to your SAS data warehouse services that you may have, but there's Snowflake or Redshift or in a DBQ, Google BigQuery, or a Microsoft synapse and then get going immediately. To give you an idea, a typical ThoughtSpot deployment used to take around four to five months, now it is taking around 35 minutes. That's what ThoughtSpot Cloud does for our customers. If it happens in 35 minutes, their business of delivering value to their clients is happening that much faster. >> Everything shifts to actually getting insights as opposed to setting stuff up. One of the other things to do that I've been reporting on. I've said in the last decade, we kind of moved from really a product centric world to one that's more platform centric, particularly with cloud and SAS. The latest research that we've been doing shows that ecosystems, we think are going to power the next wave of innovation. I wonder what your view is of that premise and how you're thinking about ecosystems as a lever of growth. >> This word platform is one of the most abused word in our industry because people like to say, don't say product, say solution, and then say, don't say solution use platform. In reality, a platform is useless if people are not standing on. If you're standing on a railway platform, nobody's there, watch the point? The same thing applies to business, our business as to when it comes to platform. A platform is only a real platform if there are other players making money of what you have built. If you build a platform, all it does is a bunch of API. Nobody's consuming, it's not useful. In that context, we have long ways to go, we have really long ways to go. I do think one of sort of... I wouldn't say mistake, but one of the oversights that our sport had was not delivering on the vision of platform. That it is easy to make for others to come together and do commerce on ThoughtSpot. Most importantly, make sure that it is not just easy but when customers come to them, that one plus one is like 10 or 11, as opposed to one plus one equal two. That is something that we have to remedy. At the Beyond Conference, next month on December 9th, you will see us make some interesting announcements around this thing. It is one of my favorite sort of projects because once we do that very well, you will see that it becomes a platform. Think of Stripe, think of Square. These are platforms because it made their customers' lives easier, but at the same time, multiple companies could come together to deliver joint solutions where the sum is much bigger than equals of the parts. That is a vision that ThoughtSpot needs to really deliver on and Beyond will be a stock. >> I mean, the power of many versus the resources of one and this is well understood over time and now we're seeing it really applied to our industry. Sudheesh, a lot of the analytics that we produce today are the result of humans clicking and typing and interacting with systems. That's obviously going to continue to grow, but you think about things like IOT, the build-out of 5G, it brings this whole new dimension of machine to machine communications and tons of new data. Much of the data out there is analog, today, it's being increasingly become digital. How are you thinking about these trends in terms of the impact on your company and your customers? >> I think if anyone asks me, what does ThoughtSpot do for the data analytics world? My answer is very simple. We have introduced a new interface to access structure data that can be used by anybody, search that is driven by AI, that's an AI driven search. That core idea is about scale, but more importantly, rate of change. That's where the new inventions around 5G where the bottlenecks are being removed at IoT and mobile. I mean, we want to put mobile as well. So you have mobile devices, IOT devices, very big pipe, and then cloud on the backend where processing and storing is cheap. Now if you think of that, it is a 12 lane super highway, all the way to the end user, all the way to the end device, to the mothership. When you have that much speed and when you remove everything, you have to think about the asset, the artifacts that you build out of that kind of a data stream. That's where the old way of looking at dashboards will die. It's not a question of if or when it is dying. What we need is now to make sure that at that speed, when the data is changing much faster than ever before, you have new way to deliver insight to the people who can act on it, which is business users. If you think of it, there used to be cases where companies used to make supply chain decisions for the year. Now, supply chain decisions are made monthly because you don't know what next month will look like with COVID. When you have annual decisions become monthly decisions, monthly decisions become weekly decisions, weekly decisions became minute by minute decisions sometimes like placing social media sentiment changes, things like that, there is no way that you can depend on a Monday morning report or a Monday morning meeting, and then send out, here is what you need to do, action items to the front end. Everyone should have the pulse on where the business is, which is where the data is going to help them. However, human experience is so critical. You don't want to remove human experience. That's why as we deliver more and more on 5G and IoT, making the data as it is changing and then delivering those signals that insights directly to business users in the frontline is going to be like the de facto way businesses will operate. I think we are just beginning that journey in terms of what is possible. >> Well, it reminds me of when we were kids, the coaches would tell us, go to where you think the ball is going to be, find opportunities for that open space, not to where it is today. That's the notion of whether it's soccer or basketball, or of course, hockey skate to the puck is obviously a famous term. So how do you stay ahead of that disruption curve in a space like analytics? What are the innovation opportunities that organizations should be tapping today and beyond? >> I was thinking about this a lot myself, which is the important thing is to be ready to unlearn. I know it is a simple thing but it was one of the most difficult things because as you grow up in the organizations, as you become an exec, as you gain more experience, we actually calcify our knowledge. That's a problem, because things are changing. There are new way to do things, new opportunities. Being open to unlearning is going to be more critical than learning new things sometimes. That will require humility. I won't say it's a go learn AI, or go learn a new language or Python or coding. Those things might be necessary, but having that mentality of willing to unlearn and then having the courage to make some difficult decisions. If you do those two things, I think this is an exciting role. And if you're not, you're going to go the wayside of a lot of industries have been going. >> That's great advice. I mean, we saw that a lot coming into the pandemic. There was a lot of complacency around digital and of course there isn't anymore. Sudheesh, thanks so much for joining me in this CUBE Conversation. It's always great to talk to you. >> Thank you for taking the time, I appreciate it. >> My pleasure. Thank you for watching, everybody. This is Dave Vellante for theCUBE, will see you next time. (bright upbeat music)

>> Narrator: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Everyone welcome to this special CUBE conversation. I'm John Furrier, host of theCUBE here in our Palo Alto studios. During this time of the pandemic, we're doing a lot of remote interviews, supporting a lot of events. theCUBE virtual is our new brand because there's no events to go to, but we certainly want to talk to the best people and get the most important stories. And today I have a great segment with a world-class entrepreneur, Ajeet Singh co-founder and executive chairman of ThoughtSpot. And they've got an event coming up, which is going to be coming up in December 9th and 10th. But this interview is really about what it takes to be a world-class leader and what it takes to see the future and be a visionary, but then execute an opportunity because this is the time that we're in right now is there's a lot of change, data, technology, a sea change is happening and it's upon us and leadership around technology and how to capture opportunities is really what we need right now. And so Ajeet I want to thank you for coming on to theCUBE conversation. >> Thanks for having me, John. Pleasure to be here. >> For the folks watching, the startup that you've been doing for many, many years now, ThoughtSpot you're the co-founder executive chairman, but you also were involved in Nutanix as the co-founder of that company as well. You know, a little about unicorns and creating value and doing things early, but you're a visionary and you're a technologist and a leader. I want to go in and explore that because now more than ever, the role of data, the role of the truth is super important. And as the co-founder, your company is well positioned to do that. I mean, your tagline today on the website says insight is the speed of thought, but going back to the beginning, probably wasn't the tagline. It was probably maybe like we got to leverage data, take us through the vision initially when you founded the company in 2012. What was the thinking? What was on your mind? Take us through the journey. >> Yeah. So as an entrepreneur, I think visionary is a very big term. I don't know if I qualify for that or not, but what I'm really passionate about is identifying very large markets, with very, very big problems. And then going to the white board and from scratch, building a solution that is perfectly designed for the big problem that the market might be facing from scratch. And just an absolute honest way of approaching the problem and finding the best possible solution. So when we were starting ThoughtSpot, the market that we identified was analytics, analytics software. And the big problem that we saw was that while on one hand, companies were building very big data lakes, data warehouses, there was a lot of money being spent in capturing and storing data how that data was consumed by the end-users, the non-technical people, the sales, marketing, HR people, the doctors, the nurses, that process was not changing. That process was still stuck in old times where you have to ask an analyst to go and build a dashboard for you. And at the same time, we saw that in the consumer space, when anyone had a question they wanted to learn about something, they would just go to Google and ask that question. So we said, why can't analytics be as easy as Google? If I have a question, why do I have to wait for three weeks for some data experts to bring some insights to me for most simple questions, if I'm doing some very deep analysis, trying to come up with fraud algorithms, it's understood, you know, you need data expert. But if I'm just trying to understand how my business is doing, how my customers are doing, I shouldn't have to wait. And so that's how we identified the market and the problem. And then we build a solution that is designed for that non-technical user with a very design thinking UX first approach to make it super easy for anyone to ask that question. So that was the Genesis of the company. >> You know, I just love the thinking because you're solving a problem with a clean sheet piece of paper, you're looking at what can be done. And it's just, you can bring up Google because you know, you think about Google's motto was find what you're looking for. And they had a little gimmicky buttons, like I'm feeling lucky, which just took you to a random webpage at that time while everyone else was tryna build these walled gardens and this structural apparatus, Google wanted you in and out with your results fast. And that mindset just never came over to the enterprise and with all that legacy structure and all the baggage associated with it. So I totally loved the vision, but I got to ask you, how did you get to beachhead? How did you get that first success milestone? When did you see results in your thinking? >> Yeah, so I mean, I believe that once you've identified a big market and a big problem, it comes down to the people. So I sort of went on a recruit recruiting mission and I recruited perhaps the best technology and business team that you can find in any enterprise segment, not only just analytics, some of the early engineers, my co-founder, he was at Google before that, Amit Prakash, before that he was at Microsoft working on Bing. So it took a lot of very deliberate effort to find the right kind of people who have a builder's mentality and are also deep experts in areas like search large-scale distributed systems. Very passionate about user experience. And then you start building the product, you know, it took us almost, I would say one and a half three years to get the initial working version of the product. And we were lucky enough to engage with some of the largest companies in the world, such as Walmart who are very interested in our solution because they were facing these kinds of problems. And we almost co-developed this technology with our early customers, focusing on ease of use, scale, security, governance, all of that, because it's one thing to have a concept where you want to make access to data as easy as Google, you have a certain interface people can type and get an answer. But when you are talking about enterprise data and enterprise needs, they are nowhere similar to what you have in consumer space. Consumer space is free for all, all the information is there you can crawl it and then you can access it. In enterprise, for you to take this idea of search, but make it production grid, make it real and not just a concept card. You need to invest a lot in building deep technology and then enabling security and scalability and all of that. So it took us almost , I would say a two and a half to three years to get to the initial version of the product and the problem we are solving and the area of technology search that we are working on. We brought it to the market. It's almost an infinite game. You know, you can keep making things easier and easier. And we've seen how Google has continued to evolve their search over time And it is still evolving. We just feel so lucky to be in this market, taking the direction that we have taken. >> Yeah. It's easy to talk a big game in this area because like you said, it's a hard technical problem because it'll structural data, whether it's schema databases or whatever, legacy baggage, but to make it easy, hard. And I like what you guys go with this, find the right information and put it in the right place, the right time. It's a really hard problem. And the beautiful thing is you guys are building a category while there's spend in the market that needs the problem today. So category creation with an existing market that needs it. So I got to ask you, if you could do me a favor and define for the audience, what is search-driven analytics? What does that mean from your standpoint? >> Yeah, what it means is for the end user, it looks like search but under the hood is driving large scale analytics. I like to say that our product looks like a search engine on the surface, but under the hood, it's a massive number crunching machine. So Search and AI driven analytics. There's two goals there. One, if the user has, any user and we're talking about non-technical users here, we're not talking about necessarily data experts, but if a user has a question, they should be able to get an answer instantly. They shouldn't have to wait. That is what we achieve with Search and with Spot IQ, our AI engine, we help surface insights where people may not even know that those are the questions they should be asking because data has become so complex. People often don't even know what question they should be asking. And we give them a pool that's very easy to use, but it helps surface insights to them. So there is both a pool model that we enabled through Search and a push model that we enable through Spot IQ. >> So I have to ask you that you guys are pioneering this segment you're in first. And sometimes when you're first, you have arrows in your back as you know, it's not all the beginners survive, they get competition copies, but you guys have had a lead. You had success. What's different today as you have competition coming in trying to say, "Oh, we got Search too." So what's different today with ThoughtSpot? How are you guys differentiated? >> Yeah. I mean, that's always a sign of success. If what you are trying to do, if others are saying we have it too, you have done something that is valuable. And that happens in all industry. I think the best example is Tesla. They were the first to look at this very well-known problem. I mean, we haven't had a very sort of unique take on the existence of the problem itself. Everybody knows that there is a problem with access to data, but the technology that we have built is so deep that it's very, very hard to really copy it and make it work in real world with Tesla in automotive industry in cars, there is obviously so many other companies that have launched battery powered cars, electric cars, but there is Tesla and there is all the other electric cars which are a bit of an afterthought, because if you want to build an analytics product, where Search is at the core, Search cannot be added on the top, Search has to be the core, and then you build around it. And that requires you to build a fundamental architecture from the ground up. And you can't take an existing BI product that is built for dash boarding and add a search bar. I have always said that adding a search bar in a UI is perhaps, you know, 10 to 20 lines of JavaScript code. Anyone can add it and there is so much open source stuff out there that you can just take it and plug it. And many people have tried to do that, but taking off the shelf, Search technology that is built for unstructured data and sticking it on to a product that is required to do analytics on enterprise data, that doesn't work. We built a search technology that understands enterprise data at a very deep level, so that when our customers take our product and bring it into their environment, they don't have to fundamentally change how they manage their data. Our goal is to add value to their existing enterprise data Cloud Data Warehouses and deliver this amazing Search experience where our Search engine is enable to understand what's in their data Lake, what's in their Cloud Data Warehouse. What are the schema, the tables, the joints, the cardinality, the data archive, the security requirements, all of things have to be understood by the technology for you to deliver the experience. So now that said, we pride ourselves in not resting on our laurels. You know, we have this sort of motto in the company. We say we are only 2% done. So we are on our own sort of a continuous journey of innovation. And we have been working on taking our Search technology to the next level. And that is something really powerful that we are going to unveil at our upcoming conference, Beyond, in December. And that is one to create even more distance between us and the competition. And it's all driven by what we have seen with our customers, how they're using our product or learnings what they like, what they don't like, where we see gaps and where we see opportunity to make it even easier to deliver value to our customers and our users. >> I think that's a really profound insight you just shared, because if you look at what you just said around thinking about Search as an embedded architectural foundational, you know, embedded in the architecture, that's different than bolting on a feature where you said Java code or some open source library. You know, we see in the security market, people bolted on security had huge problems. Now, all you hear is, "Oh, you got a big security in from the beginning." You actually have baked Search into everything from the beginning. And it's not just a utility, it's a mindset. And it's also a technology metadata data about data software, and all kinds of tech is involved. Am I getting that right? I mean, cause I think this is what I heard you say. It's like, you got to have the data. >> This is totally right. I mean, if I can use an analogy, there is Google search and obviously Yahoo also tried to bring their own search Yahoo search Yahoo actually, Yahoo versus Google is a perfect example or a perfect analogy to compare with ThoughtSpot versus other BI product Yahoo was built for predefined content consumption. You know, you had a homepage, somebody defined it. You could make some customizations. And there is predefined content you can consume it. Now, they also did add search, but that didn't really go so far. While Google said, we will vary from scratch ability to crawl all the data, ability to index all the data and then build a serving infrastructure that deliver this amazing performance and interactivity and relevance for the user. Relevance is where Google already shined. And you can't do those things until you think about the architecture from the ground up. >> Ajeet I'm looking forward to having more deep dive conversations on that one topic. But for the folks who might not be old enough, like me to remember Google back at that time, Yahoo was the best search engine and it was directory basically with a keyword search. It was trivial, technically speaking, but they got big. And then the portal wars came out, we got to have a portal. Google was very much not looked down as an innovator, but they had great technical chops and they just stayed the course. They had a mission to provide the best search engine to help users find what they're looking for. And they never wavered. And it was not fashionable about that time to your point. And then Yahoo was number one, then Google just became Google and the rest is history. So I really think that's super notable because companies face the same problem. What looks like fashionable tech today might not be the right one. I think that's... >> Yeah, and I totally agree. And I think a lot of times in our space, there's a lot of sort of hype around AI and machine learning. We as a company have tried to stay close to our customers and users and build things that will work for them. And a lot of stuff that we are doing, it has never been done before. So it's not to say that along the way, we don't have our own failures. We do have failures and we learn from them. >> Yeah. Yeah. Just don't make the same mistake twice. >> Yeah, I think if you have a process of learning quickly, improving quickly, those are the companies that will have a competitive advantage. In today's world, nobody gets it right the first time. If you're trying to do something fundamentally different, if you're copying somebody else, then you're too late already. >> I totally agree. >> If you do something new, it's about how fast you penetrate And that's... >> That's a great mindset. That's a great mindset. And I think that's worth capturing calling out, but I got to ask you because what's first of all, distinguished history and I love your mindset and just solving problems, big problems. All great. I want to ask you something about the industry and where you guys were in 2012 alright when you started the company, you were literally in what I call the before Cloud phase. Cause it was before Cloud companies and then during Cloud companies and then after Cloud, you know, Amazon clearly took advantage of that for a lot of startups. So right around 2012 through 2016, I'd call that the Amazon is growing up years. How did the Cloud impact your thinking around the product and how you guys were executing because you were right on that wave. You were probably in the sweet spot of your development. >> Yeah. >> Pre business planning. You were in the pre-business planning mode, incomes, Amazon. I'm sure you're probably using Amazon cause your starters and all start up sort of use Amazon at first, but I just think about, do we all have found premise with a data center? How did that impact you guys? And how does that change today? >> Certainly. Yeah it's been fascinating to see how the world is evolving how enterprises have also really evolved in depth, thinking on how they leverage the cloud infrastructure now. In the Cloud, there is the compute and storage infrastructure. And then you have a Cloud Data Warehouse, the analytics stack in the Cloud. That's becoming more popular now with a company like Google, having BigQuery and then Snowflake really amazing concepts and things like that. So when we started, we looked at where our customers are , where is their data. And what kind of infrastructure is available to us at the time there wasn't enough compute to drive the search engine that we wanted to build. There were also not any significant Cloud Data Warehousing at the time, but our engineering team our co-founders, they came from companies like Google, where building a Cloud based architecture and elastic architecture, service oriented architecture is in their DNA. So we architected the product to run on infrastructure that is very elastic that can be run practically anywhere. But our initial customers and applies the Global 2000. They had their data on-prem. So we had started more with on-prem as a go-to-market strategy. and then about four and a half years ago, once cloud infrastructure I'm talking about the compute infrastructure started to become more mature, we certified our software, to run on all three clouds So today we have more than 75 to 80% of our customers already running our software in the Cloud. And as now, because we connect to our primary data sources, our Cloud Data Warehouses, Cloud Data Lakes. Now with Snowflake and BigQuery and Synapse and Redshift, we have enough of our customers who have deployed Cloud Data Warehouses. So we are also able to directly integrate with them. And that's why we launched our own hosted SaaS Offering about a month ago. So I would say our journey in this area has been sort of similar to companies like Splunk or Elastic, which started with a software model initially deployed more on-prem, but then evolved with the customers to the Cloud. So we have a lot of focus and momentum and lot of our customers, as they're moving their data to the Cloud, they're asking us as well to be in the Cloud and provide a hosted offering. And that is what we have built for the last one year. And we launched it a month ago. >> It's nice to be on the right side of history. I got to say, when you're on the way to be there. And that also makes integrations easy too. I love the Cloud play. Let's get to the final segment here. I want to get your thoughts on your customers, your advice. There's a huge untapped opportunity for companies when it comes to data, a lot of them are realizing that the pandemic is highlighting a lot of areas where they have to go faster and then to go to Cloud, they're going to build modern apps more data's coming in than ever before. Where are these untapped opportunities for customers to take advantage of the data? And what's your opinion on where they should look and what they should do? >> Yeah, I really think that the pandemics has shown for the first, the value of data to society at large, there is probably more than a billion people in the world that have seen a chart for the first time in their life. Everybody is being... and COVID has done some magic. But everybody was looking at charts of infection and so on and so forth. So there is a lot more broad awareness of what data can do in improving our society at large for the businesses of course, in the last six, seven months, you heard it enough from lot of leaders that digital transformation is accelerating. Everybody is realizing that the way to interact in the world is becoming more and more digital expecting your customers to come to your branch to do banking is not really an option. And people are also seeing how all the SaaS companies and SaaS businesses, digital businesses, they have really taken off. So if a company like Zoom can suddenly have a a hundred, $150 billion valuation, because you are able to do everything remote, all the enterprises are looking to really touch their customers and partners in a lot more digital way than they could do before. And definitely COVID has also really created this almost, you know, pool buckets of organization. There is lot of companies that have tremendously benefited from it. And there a lot of companies that have been poorly affected, really in a difficult place. And I think both of them for the first category, they are looking at how do I maintain this revenue even after COVID, because one of this thing, you know, hopefully early next year we have a vaccine and things can start to look better again sometime next year. But we have learned so much. We have attracted so many new customers, how do we retain and grow them further? And that means I need to invest more and more in my technology. Now, companies that are not doing well, they really want to figure out how to become more operationally efficient. And they are really under pressure to get more value from there and both categories, improving your revenue, retaining customers. You need to understand the customer behavior. You need to understand which products they are buying at a fine grain level, not with the law of averages, not by looking at a dashboard and saying our average customer likes this kind of product. That one doesn't really work. You have to offer people personalized services and that personalization is just not possible at scale, without really using data on the front lines. You can't have just manager sitting in their office, looking at dashboards and charts and saying these are the kinds of campaigns I need to run because my average customer seems to like these kinds of offers. I need to really empower my sales people, my individual frontline workers, who are interfacing with the customer to be able to make customized offers of services and products to them. And that is possible on the data. So we see a really, a lot more focus in getting value from data, delivering value quickly and digital transformation broadly but definitely leveraging data in businesses. There is tremendous acceleration that is happening and, you know, next five years, it's all going to be about being able to monetize data on the front lines when you are interfacing with your customers and partners >> Ajeet, that's great insight. And I really appreciate what you're saying. And you know, I wrote a blog post in 2007. I said, data will be the new development kit. Back then we used to call development kits, software user development. >> John, you are the real visionary. It took me until 2012 to be able to do this. >> Well, it wasn't clear, but you saw other data was going to have to be programmed be part of the programming. And I think, what you're getting at here is so profound because we're living 2020 people can see the value of data at the right time. It changes the conversations, it changes what's going on in the real time communications of our world with real-time access to information, whether that's machine to machine or machine to human, having data in the right place, changes the context. >> Yap. >> And that is a true, not a tech thing, that's just life, right? I think this year, I think we're going to look back and say, this was the year that everyone realized that real time communications, real-time society needs real time data. And I think it's going to be more important than ever. So it's a really big problem and important one. And thank you for sharing that. >> Yeah. And actually you bring up a very good point programming, developing big data. Data as a development kit. We are also going to announce a new product at Beyond, which will be about bringing ThoughtSpot everywhere, where a lot of business users are in their business applications. And by using ThoughtSpot product, using our full experience, they can obviously do enterprise wide analytics and look at all the data. But if they're looking for insights and nuggets, and they want to ask questions in their business workflows. We are also launching a product capability that will allow software developers to inject data in their business applications and enable and empower their own business users to be able to ask any questions that they might have without having to go to yet another BI product. >> It's data as code. I mean, you almost think about like software metaphors, where's the compiler? Where's the source code? Where's the data code? You start to get into this new mindset of thinking about data as code, because you got to have data about the data. Is it clean data, dirty data? Is it real time? Is it useful? There's a lot of intelligence needed to manage this. This is like a pretty big deal. And it's fairly new in the sense in the science side. Yeah, machine learning has been around for a while and you know, there's tracks for that. But thinking of this way as an operating system mindset, it's not just being a data geek. You know what I'm saying? So I think you're on the right track Ajeet. I really appreciate your thoughts here. Thank you. >> Thank you John. >> Okay. This is a cube conversation. Unpacking the data. The data is the future. We're living in a real-time world and in real-time data can change the outcomes of all kinds of contexts. And with truth, you need data and Ajeet Singh co-founder executive chairman of ThoughtSpot shares his thoughts here in theCUBE. I'm John furrier. Thanks for watching. (soft upbeat music)

from the cube studios in palo alto in boston connecting with thought leaders all around the world this is a cube conversation welcome to the cube lisa martin here i'm having the opportunity to speak with one of dell technologies customers joining me from all the way down under in melbourne australia is kevin pritchard the head of it and business systems from janna investment advisors hi kevin nice to have you on the program thanks lisa a pleasure to be here so tell us about jonah investments who you guys are what you do all the types of data that you're dealing with jana is uh an asset consultant uh we consult to what we call in australia the superannuation industry which is the equivalent of your 401 k our clients are the actual funds themselves the pension funds we advise on both the accumulation and then the pension stage of those to those funds we have under advice across all our clients approximately 500 billion aud so that's a significant responsibility our decisions our research our recommendations probably affects between two to three out of five australians retirement outcomes all right so business critical data kevin i imagine there's compliance requirements not just in australia but if you're doing business with any clients in the americas or in uh europe primarily our markets australia but the regulatory overlays that we and our clients face into are significant and growing the superannuation sector in australia is now at around three trillion dollars it's a significant amount of money i think it's the second or third largest in the world um don't quote me on that but it's a significant amount of money so let's talk about data as a business critical asset and also from a brand reputation perspective talk to me about your it environment how you were managing data before and what some of the challenges were that you wanted to resolve i've been with jana for 14 years and in that time the demands and the complexity of our environment have increased we have to address a growing accumulation of business critical data our data forms our ip it's the core of our advice and it's not just what we're doing today it's what we've done five years ago 10 years ago it has to be there for ready reference it's a critical business asset i like how you said it's really your data is really your ip so talk to me about your it environment before on-prem cloud virtualize what does that landscape look like so we run a a data center we have a it's it's a more economical footprint but nevertheless it's the core of what we do as a business on a day-to-day some data we can't put in the cloud the regulatory overlays really don't permit it and privacy and you know we can better protect in a data center uh we we occupy a space in a dedicated space in a tier 4 data center in australia but that said we are increasingly moving into cloud now the cloud is super important to us it's but it's not easy to migrate into people just say oh let's just go to the cloud you really do have to think about things you have to think about how it's implemented you have to think about data security uh they're very good the cloud providers but it's all care no responsibility it ultimately comes back to you but the the nexus between cloud and on-prem is something that you have to think about and if i'm thinking about backup and dr and i can think of it from a number of perspectives you know it's not just backing up in case we've got failure of hardware but it's about cyber security it's about protection from things like air gapping ensuring um you know that your backups are actually aware of the malware for example uh we've we've had incidents uh and i'm sure the u.s had as well in australia where organizations have found six months down the track that their backups have been compromised we can't afford to do that our regulators our clients i myself have to give assurances to our clients that we're resilient that we're meeting the increasingly stringent benchmarks in your case study i was reading about uh really jonah was on a quest to become more data driven and also it sounded to me like the board was heavily invested and had a vested interest in data protection talk to me about how dell technologies is helping you meet some of those goals becoming more data driven and enabling you to ensure to your cfo et cetera the board that our data is secure yeah as i was saying [Music] at the beginning of this journey i would have thought back up how hard can it be right you you take a backup it's a tape it's a disc you put it into a secure repository something somewhere offside you have a problem you phone someone up they bring it take back and you restore those days have gone and when you really look into it it's a very specialist area how do you back up data especially the size of the data that we have how do you restore it in a timely manner how do you protect it against as i'm saying compromise you need to test it you need easy ways to test it it's complex now when i looked at this problem three years ago i think well okay we're no longer part of a big bank um we've got to stand on our own feet what's the best solution do you research the market um i i've worked with dell for a long time and they're in the mix in the end dell offered the best solution and they showed that they had the understanding of my environment and more broadly where industry is going so that data protection mix of products between the the visibility the dashboards and what happens in the cloud in terms of testing your workloads that are up there because testing is something that my board really really insists upon we have a an annual testing program it runs the full 12 months where we're testing various aspects of uh recovery so talk to me about you're talking about the complexity of a person in the beginning i thought back up in recovery how how difficult can that be you talked about the complexity though and as we talked about with with probably i would say increasing scrutiny from a regulations perspective aboard the cfo how did dell technologies how did power protect actually help you simplify because i actually saw a quote from you in your case study about it being easy help us understand how that was possible yeah you've always got to be careful using the word easy but let's take that perspective from what it would be if it wasn't easy so our prior solution was essentially relying on the dis backup multi-volume disk backup that was stored by a suitable company now i was looking at the dell uh the power protect data protect dashboard the other day and i was surprised we have 27 terabytes of data stored in the cloud which is sent up there daily i get a report card each day it's all green thankfully i can see that on average you know the change the delta of what the data we store on particular servers is on average around seven to ten percent a day those statistics are really important and uh and the deduplication compression ratios you know 97 98 are outstanding um that is really helpful so the point i was trying to make in my previous comments is that visibility is very important that's where it gets easy because i don't have to rely on an expert who's sitting over there he may be in or out telling me what's the status of where we are in day-to-day backup it's it's a critical part of bau it's a pretty critical part of data protection and our clients are greatly comforted by it absolutely when you were describing your previous environment i thought wow one of the things you probably you couldn't have had is complete visibility let alone maybe even good visibility so now with the dell uh power protect series can you look through like a single pane of glass management and see all the backups on file servers virtual machines all of that iep that you talked about that's core to the business uh the short answer is yes now there was another part of our previous setup where we used you what would be classical we had a warm site and we would replicate data one of the problems with that is i didn't know if replication was occurring i didn't know if you know if i if i had had a and we haven't but if we had a ransomware attack then it infects the server and it actually it replicates to your secondary side there was no air gap air gap your backup protected these old solutions of running a you know for an organization outside the the expanding the maintenance required to run a secondary side are just too much one of the things that sounds like you now have is confidence that what you're protecting with dell is in fact protected it's secure and you talked about ransomware a second ago and now in the age of kobe i read the other day that there's a ransomware attack happens every 11 seconds phishing is getting more personal and more sophisticated so that's a big challenge now that sounds like you've got a pretty resilient infrastructure that i i'm going to speak for you gives you the confidence that you're in a pretty good situation with respect to ensuring that that data is indeed safe i have a great deal more confidence and i'm being cautious and cynical i'm you'd never want to say 100. all right because the backup gods will frown upon you but i'm now more confident i can provide my c-suite i can provide the board with a ready snapshot view of where we stand are there any issues um not just cost effectiveness but the visibility of what's going on and look i i was absolutely surprised that an organization outside had 27 terabytes of data that's a lot of data for someone outside and that's important because really at the end of the day this boils down to brand reputation the ability to guarantee to the regulators your clients that all of the data that you talked about it's a lot for a company of your size is indeed secure and protected and that you can as you said you have pretty strong confidence i agree with you saying 100 is always one of those challenging kind of areas to be in but but i think from from a business outcomes perspective this isn't just about protecting the data that's sitting on file servers and virtual machines this is protecting and helping to reinforce the reputation of the brand of janna yes reputation our reputation is so important and we need to ensure to to guarantee to our clients that we stand head and shoulders above i've had funds come to me we we do our uh audits they've come in they've looked at our processes procedures you are miles ahead of us you put us to shame what's your advice to those folks who are coming in saying what you're doing kevin is putting us to shame you say here's how i would advise you to modernize your environment what's your advice well backup is no longer in d i's just look at the bcp and the dr thing it's no longer just about anticipating a hardware failure hub is very reliable but it can still fail network failure malware and malware is increasingly something we have to protect again that your your database is must be insured so you've got to think about it what's the best strategy and that and so you start with those primary objectives standing vms up in the cloud is you know you've got to understand cloud environments so seek good advice really research and and go for the solution that really offers hide the complexity if you can because at least if you guys make sure you can have someone over there that does all the the cloud stuff someone over there that knows all the hardware and then they can all get into a room and we can but most companies now are looking for that single pane of glass and you if you plan right and size your requirements then you you'll be okay in that respect and and it is an endorsement to dell [Music] um implementation phase well they're very good through the through the investigation phase their proposals were very very sound the um the costings the financial benefits were all laid out for me i was able to take a very firm recommendation to my board and we were able to secure that funding and then the implementation kevin that's great advice do do your due diligence and i'm sure now in this very dynamic different world that you're in you're in a much better position than you would have been had this not been able to be moved forward under your leadership we thank you so much for joining us on thecube today and sharing the successes that you're having at janna pleasure for kevin pritchard i'm lisa martin you're watching the cube

from the cube studios in palo alto in boston connecting with thought leaders all around the world this is a cube conversation [Music] welcome to this cube conversation lisa martin here with one of dell technologies customers what a great time to be talking about a candy company clifton dorsey joins me the vp at world corporation clifton welcome to the cube all right thank you i appreciate being here so i know royal corporation does more than candy but you know here we are approaching the holidays and and i think all of us could just use a feel-good story about candy but i know you do more tell our audience a little bit more about where else from a corporation standpoint sure war el corporation has been in family and it's a family-owned business for 50-plus years we're a co-packer co-manufacturer so you won't really see a world candy bar out there but we really help bring to life a lot of innovative ideas around the candy and the good for you products for a lot of our partners so talk to us about you're obviously working with dell technologies give us uh an insight into your data center operations your it environment before the solution that we're going to be talking about what was that like physical on-prem cloud sure well our data center kind of falls right in line with the same time of year as a horror story when i first came here and got on board a lot of outdated equipment despair and equipment separated our backups were they were few and far between um the the equipment was so old that some of it wasn't even supported anymore we had antiquated systems but the biggest thing is the confidence level you have zero confidence that your system stay running your backup it was an everyday occurrence just to try to get a reliable backup for just a piece of the data let alone all of our um all of our data and information that we had that confidence factor is table stakes and especially now it's it's if a company can't have confidence that their data is secure and protected that's you know folks that can't might not be around tomorrow but talk to me a little bit about from a workload's perspective what were you protecting vm's erp systems give us a slice of that data in terms of its impact in the business sure and you're correct you know having that that confidence level in the systems is what you need our sql databases are in there our erp system's in there our file servers and at the time even our email server was in there so any one of those goes down it's a business impact you know you have to look at what can't you do when that happens on our manufacturing floor we're collecting a lot of data coming back off the floor for all of our folks and purchasing and procurement and our run times to make sure that we're hitting our our dates on time so even our shipping and receiving team needs to know how the floor is running to know if we're going to hit those ship dates and when to schedule the truck so it literally all correlates and all comes together and i imagine also not just does that involve every aspect of world's business internally but relationships with the partners that you are helping fulfill right that's correct because we're making their product if they can't have a product on the shelves that impacts them you know so we really have to do everything that we can to make sure our systems are up make sure everything is running and really fulfill their order and get it out there so you can have that product yeah that's why often we talk about data protection and brand reputation go hand in hand so talk to me when you came into world you must have seen nowhere to go but up talk to me about some of the things that you said we have got to for example aging physical infrastructure we've got to replace that we obviously have to be able to have reliable data protection because we have to have the confidence that we can enable our teams and uh our partners but what were some of the things that you said all right let me kind of get a phased approach here what are we gonna change and why are we gonna do it with dell technologies sure so looking at our business continuity plan you don't have a good dr so you have to start looking backwards of where do you start so we have zero backups our data's not protected we have zero confidence in it we go back a little farther our systems aren't really there for us to back up so it really started at the appliance level in our server level to get rid of all of the old information get a new subset of servers in so we have a new vxrail environment in it integrates great with the integrated appliance ties directly into it so we have backups we have everyday backups we have fast and speedy backups then we can offload those to an off site so we now truly have a full business continuity plan and a dr disaster recovery situation that's critical because i was reading your case study and where there was no dr before talk to me about the ability to to leverage the clouds of now with what you've implemented uh and the power protect series you've now got the ability to from a dr perspective i just want to understand that especially here we are you know towards the end of 2020 when there's been such a shift to remote operations what's that cloud benefit like from a dr standpoint it's been great um you know we were old tape backups so someone had to be here to switch out the old tapes you know and hope that how do we get them off site who's taking them home what vault are they living in you know with the remote aspect all of that worry goes away everything is offloaded everything goes into a cloud if there is a situation we just work through our cloud environment we can reinstate business literally a click of a switch yeah i was looking at some of your statistics and it looks like about a 6x reduction in your backup windows and a huge reduction in your physical footprint the data center also imagine more green tell us a little bit about it from that perspective sure yeah a couple points should hit there i mean our deduplication and compression rates are higher than what we're expected by far so that's been a great spot as far as we don't need as much physical storage to hold all of that well with that we were able to take our racks we had three server racks we went down to half of one server rack so your heating and air conditioning your heating and cooling cost comes down your power cost comes down all of that soft cost that stretches around this environment really has a benefit for us i'm also thinking too in this time of everything shifting and data protection becoming business critical your team's productivity won we talked about um the the backup big reduction in backup windows but your team must be must be much more productive and also i imagine from confidence from a reputation standpoint your executives or senior management probably now has the confidence because you have the confidence that the data is secure yeah lisa that's true and even down to our user level when i first got here i mean our users were complaining about not being able to print a word document i mean not being able to print a document that's that's fundamental stuff started diving into it and our systems are just old disparate and weren't configured the best so our team's really been able to revamp all of that redo all of that and the confidence level around the organization has just really improved and it's great to see we now have a lot more time to work on tomorrow than living in the trenches of today which everyone needs right now since this it's pivot after pivot after pivot i'm curious how long ago did you come in like how many years ago did you find this antiquated system yeah i've been here a little over two years now okay so fairly recently what were some of the things that you think world was stuck in was it cultural was it operational what was it that you helped influence in terms of we have to make a change now sure one of the things for me is one of the old phrases i think is the worst phrase is well because we've always done it that way you know so getting a fresh line and a fresh look on something was able to really help out the innovation that dell brings to the table falls in line with the innovation that we bring for candy so let's look at what they have let's look at how they tie together but we have to do a full forklift of our infrastructure in our data center you want to look at the integrated systems and you know how you get that best performance not the best bang for the buck when it comes to the budget because if they're unbudgeted dollars you really got to get every dollar to stretch farther and looking at the vxrail with the integrated appliance and with the cdra to offload to you know a cloud site it was a perfect package it was the perfect pairing for what we needed but going from you talk about you know we've always done it this way and you're right we hear that a lot and it's well why you can do it so much differently can you imagine if they were still doing it that way in the era of covid but thinking about this big switch from um a big physical um footprint to going to hyper converged infrastructure how was that transition that you helped drive how did it shift the culture at world because i imagine it 50 year old company in leicester right yeah i believe it did i believe it helped everyone kind of just look at everything and say just because it works to get us here is it going to work with get us to tomorrow so everybody really started looking at different situations and different things when we sat down with our users we changed the entire desktop experience you know we have new laptops we have new operating systems we have the way things are working better so it really changed the culture through and through so you know when you go to work you want systems to work when you come in the last thing you want to deal with is oh is a computer is going to be down do i have to call it today so getting that scalability was great but getting that reliance from the user in from the keyboard the whole way back to your edge was a huge win for us and let's look at your team now having more time to be innovative especially i'm curious what you've been able to do the last six to seven months that you now have this reliable infrastructure data secure internally people can print things they can check their emails without having to bother i.t what are some of the new maybe strategic areas that you've been able to get involved in because you have the time to focus on them we're really getting involved with more of the plant all the equipment on the floor trying to collect that data and correlate all that data coming off the floor and now we're able to have a little fun of how do we get the data on the floor real-time collection back into the system and how can we have technology help drive that innovation on the floor when our r d department comes to us about we have a new product that needs to run where do we run it i'm now able to work with the manufacturing manager and say that type of product runs best on this machine and here's the data to support that that's really the fun of what we can do for tomorrow so does this now enable you to become data-driven whereas before maybe not so much yeah i agree yes very much so and it's good data it's not hypothetical data that someone put on a piece of paper and thought through it's really good data that we can correlate and collect and that's critical especially right now as everybody wants everything real time and the consumer demand is changes every industry and i think it's probably going to be a pretty big demand still this year for candy i know uh that sounds pretty good right about now i'd love to get your advice for men and women in your position coming into maybe a legacy business that has an antiquated infrastructure how do you recommend how do you advise that they go about approaching leadership and their teams to do a complete transformation i think it starts with a good partner you've got to have a good partner and able to put things in order i like to call it one hand to high five you have to have that good partner to fall back on you build a good solid solution and then you look at your budget can do but it's all about the culture if you can find out where your culture is suffering because people are upset when they come in because something doesn't work what's the root cause of that how do you get that out of play you know work with your folks i always say i want people to drive in happy i want people to drive home happy how do we make sure that is and i know it sounds weird coming from vit guy but you have a huge impact so when you can look at everyday experience of sitting down coming into your office and sitting down at your technology and it works it's just one level of stress that we no longer have i said it's a huge level of stress that you don't have and i think that's that's an important point that you bring up you want people to come in happy and leave happy but you also really challenge them to get out of your comfort zone just because we've always done it this way doesn't mean we should still should and actually if we do there might be a competitor right behind us that's ready to come in and take over this is a competitive differentiator and especially in the time of this dynamic environment in which we live the status quo the comfort zone probably going to be a factor in determining i think the winners of tomorrow do you agree with that i do agree with that and what we actually found is when we asked people to kind of think outside of their box and step back a minute we found that they were doing something as a as a band-aid well i have to now do it this way and it just became status quo when we pulled that band-aid off we kept going back kept going back kept going back found out you're doing something because it wasn't fixed four processes ago let's fix that now it's not even a thing you know so it just leverages them more time to think more outside of the box so how do i better this situation and they can really look at everything they do how do i make it better down to how the orders come in how we process the orders to even how we ship them out and how we package them up in the truck well when you were talking about band-aids like band-aid on band-aid on band-aid i just think inherently complexity yes so talk to me in the last question here as we wrap up here from a from a simplification perspective how has dell technologies helped transform and simplify the environment i don't know that i have the word i've been thinking for that how is that because it's been so monumental that they've done for us i mean down to we've been able to revamp our data center and i know that that sounds odd well it's just a vxrail it's just it's not it's being able to simplify all of the stuff we had down into 5u of rackspace allowed us to clean up our data center clean up that complexity everything's running inside of there we no longer have you know a tape drive sitting somewhere else we now have more man hours and the soft cost we have more man hours to do a lot more of the tomorrow world so the complexity we can at our own level of complexity when we want for security or anything else but we're not we don't have a whole spider web of stuff going on that we have to work through just to see where we need to start and that's really as you said what's the word it's transformative but it sounds to me like what you're doing as a leader yourself and with dell technologies is really enabling the organization or has enabled it to get out of its comfort zone embrace modernizing take out complexity where it's not needed and focus on business outcomes which at the end of the day is the most important thing it is and you know we have our own research and development team here for you know what's the next candy you're going to see on the market we have our own innovation team i challenged every one of the departments that i work with to think the same thing what's next in your world how can you re-innovate what you have what what haven't we thought of um you know and the old thing is no idea is a bad idea let's put it on the table let's bet vetted out let's see if it works but then also working with the other departments the other departments are now able to collaborate well i didn't know that you needed that yep that's the data i need oh that's easy here you go and it has really streamlined processes from from start to finish that collaboration is essential will clifton thanks for sharing what you're doing with dell technologies the um the new dp series great work there we look forward to hearing more of what's to come from world well i do appreciate thank you so much for your time lisa and the dell team um the appliances and everything has been great for us so we appreciate everything dell's done thank you excellent i know you have that confidence because you talked about it all right guys for clifton dorsey i'm lisa martin you're watching this cube [Music] conversation

from the cube studios in palo alto in boston connecting with thought leaders all around the world this is a cube conversation hi lisa martin with the cube here covering some news from dell technologies i'm pleased to welcome one of its customers liam furlong the i.t manager from revelation software liam great to see you today thanks lisa it's fantastic to be with you and we're socially distant california you're down in australia i know it's early morning for you but we're pleased to be chatting with you so give me and our audience an overview of revelation software who are you and what do you do yeah sure revelation software is a software development company no surprises there and our primary product is a tool called revtrack and for all those sap users out there we help you get your changes navigated safely through the wide landscapes and the open seas of your sap environment so we're all about change management and delivering certainty in what is really rapidly changing landscapes uh in the it world so customers can go to you for all of their challenges with all their sap data and sort of offload that basically i mean that sounds lovely i'm sure many of them would take that so talk to me about your itune manager talking about your i.t environment i know you're highly virtualized just give us an overview of what your data environment looks like we um like a lot of software companies we give our development teams a lot of freedom and so over the years a lot has definitely built into our environment we have hundreds of vms and even more sap landscapes we are committed to our customers to provide a lot of previous version compatibility both in our product but also in sap we support more of sap's old versions than they do we just want to make sure that everyone is able to do their job and focus on what they're trying to do rather than worrying about you know do i have to upgrade am i going to be forced ahead uh in you know especially in a change management landscape and so we have a lot of history a lot of old environments and we manage that by using a lot of on-prem we have local data centers like everyone i guess but also we've got a great multi-cloud environment now and it helps us to really uh provide an excellent environment for our teams to develop in the way that they want to support our customers uh in an efficient way but also without us having to over commit to hardware and so on so you have highly virtualized environment about 150 vms nearly 500 sap landscapes so big administration of overhead talk to me about how you were protecting your data i'm assuming vms maybe some sap databases and servers how are you protecting that before using dell's new integrative approach yeah we uh used a targeted appliance uh style i guess we built up what we thought was the right solution we had a lot of legacy thinking really but uh tools we used a lot of scripts previously we used the veeam platform and that presented an ever increasing set of challenges as you can imagine with s s3 s4 hana rolling along the environment just had to change our backup load was increasing our backup windows weren't getting any larger and our backup targets weren't getting any larger so we really needed to ask some hard questions about what we were doing and whether it was working for us we had absolutely no cloud integration our off-site copies were completely inadequate and so as an i-team manager who is um the guy at the end of the road when it comes to rpo and rto and uh certainty of restorability i was not sleeping well it's fair to say well and that's something that obviously you you look to a company like dell technologies to help with sleep as a sleep aid but you guys i saw that after 20 years you were testing and a hosted version of your rev track insights product and needed cloud dr and you kind of talked about meeting customer slas and i was reading your case study and there was some big challenges there with respect to the sla front yeah definitely um i guess uh actually we were really fortunate to have started a conversation with dell even before we were bringing our cloud platform online we knew we were going to need to be able to address cloud dr it was on the horizon for us and so being able to talk with a vendor that had everything wrapped in uh the idea of an integrated appliance was really quite foreign to me the um the the thought that i could trust dell technologies to actually do this better than me i made that that sounds a bit uh arrogant but the truth is you know i knew my environment and they didn't but what was really stand out for us in the process is dell knew that too and they climbed into our environment and worked really hard they really actually wanted to understand well what were our challenges and what were our loads what was our environment really like and then work with us on a strong solution and i was amazed it felt really like the cavalry had arrived and they knew exactly what they were doing and then they worked overtime to help us find a great solution and it has been a fantastic solution not only solving the challenges we faced at that time of deployment but knowing what was on the horizon going into the cloud and having a sas platform uh we were future-proofed in a way that i was hopeful about but now that we're using it in that way i'm confident and every day i know that it's working properly for us that confidence is absolutely critical but you use the term that we hear so often in technology future proof talk to me about when you hear that as an i.t manager what does that mean to you and how is dell tech with the integrated approach delivering that yeah i think um i mean if i'm just being honest uh i generally dismiss that when i hear anyone say that they're future-proofed because no one knows what's coming i mean here we are living this year outright and uh we we knew 2020 was going to be a big year but not in the ways that it has been uh i think that even though we wanted to believe that this backup tool would cover us we weren't sure uh what it has meant is there are two real standout things one there's a suite of functionality and in the integrated appliance which we didn't need then but it was standing by and it was easy to turn on it wasn't like oh and now you'll have to pay this extra fee or now you'll have to deploy these extra tools it was all ready to go and so they've brought their years of experience and forecasting and built in a bunch of functions which you're not going to need and no one is going to need all of the tools out of the box but over time you can deploy it and the other really big one for us is all of the extra storage that we might need as our backup requirements grow shipped in the box which is a huge cost to the vendor um but it's just sitting there ready for us to consume as we need which is absolutely fantastic for me i don't need to take our backup system offline to upgrade i don't need to consume more rack space i don't need to use more power it's already doing everything it needs to and it's just about rolling forward easily as we move forward as a company so walk us through what the environment looks like now we mentioned 150 vms a big sap landscape give us a picture of the technologies and what dell is helping to protect in your environment yeah so um dell dell covers everything the the integrated appliance we're using um actually it meets all of our needs uh i'm a paranoid and in my job so we have extra bits and pieces kicking around but the power protect device is our go-to we know that it's going to be there it's going to be online it's going to have covered everything from our on-prem so we use a vmware environment locally and we're backing up all of those vms every night about 54 terabytes of data and we knock that out in about a 90 minute window which is absolutely fantastic so that backs up to local and then it ships up to our cloud environment so we've got our offsite covered in that same night then we've also got environment i guess using the amazon example we have a multi-cloud so we've got things in a couple of different cloud providers but to use amazon as an example we have production systems running up there we have our sas environment running up there and we capture that also with our power protect device and bring everything back down and so now we've got that covered as well and so no matter what our problem is i've just got one place to go to to say i need to restore this and i need to do it fast and we can get that done uh straight away it's fantastic and that's what i've been hearing i've spoken with a number of folks already including the vp of product marketing caitlin gordon and we're hearing a lot of that one-stop shop sort of description for the integrated appliance i'm wondering if you could give us a compare and contrast uh power protect the integrated appliance as you said and described the benefits that you've already achieved versus the targeted approach with theme that you had before yeah sure um what we came from was only being able to back up mission critical systems nightly and everything else had to be backed up weekly to achieve our backup windows even still monday morning was uh was a nerve wracking a few hours while the weekend back up kind of crawled through and finished and people are like oh systems are a bit slow this morning like oh yeah we're looking at that you know um we came from that to getting as i said earlier everything done every night which is a complete transformation for us it means that we don't need to worry about we used to have to supplement our veeam backup with scripts because we could get the scripted backup done uh much faster and so we would go oh we'll restore with veeam and then we'll lay a script over the top to recover everything up to last night but now um it's just all uh covered through that one appliance um again in our cloud environments we use the local tools to provide a local backup and that's great to have previously that was mission critical we had to have that working and we had to have our technicians up to speed with four or five different uh tool sets but now they it's great that they are aware of those tools but really it's just about understanding uh one application in regards to a targeted solution you end up having really all these building blocks that only one person really knows how they all string together but now not only do our whole team understand how it works together but it's one phone number to find a whole group of people who know how it works together and they can help us you know from upgrades deployments restores anything we need if i'm on leave then i know that someone else from deltek can step in and cover me for any of their questions it might normally bubble up to my level um one of my favorite numbers i'm sorry i feel like i'm ranting but one of my favorite numbers is you know we came from using a different hardware vendor's san and we were getting compression maybe of three to six times uh on data we get compression from a month view of 150 to 200 times and if we expand that out to an annual view we get compression rates of 300 times on our data which means instead of having literally 15 ru of storage we have two u of storage uh the cost per terabyte is down by hundreds of dollars it it makes me look really good and i haven't had to do anything all i did was just go yep you guys do it you guys deploy your solution so it's been those are huge deduplication numbers i know caitlin gordon shared with me on average 65 to 1 but you you basically at least double that and in terms of of making you look good that's something that's actually quite important in terms of i.t and the business uh making sure that what you can deliver to the business is the confidence and you and your team that their data is protected can you share a little bit about maybe the i.t business relations and how this technology has helped them just have that confidence yeah definitely um i mean as you say every part of the business sees a different thing our development team are paying attention to very different things to our accounting team these numbers definitely help me to make friends in both teams as a it manager if the backups do their job properly if this all works no one notices if this goes wrong i break the business so the stakes are pretty high with backup but even though that's true and we know that's true committing a big financial investment is still hard it's still a moment where you hold your breath and ask was it worth it but now that we've been able to show the numbers to our executive teams and they can see how much money they're saving how much money we would normally be reinvesting at this point but we can now make that available for other projects we can put that into further development we can put that into improving our sas platform that really works for us as a business we want to serve our customers better we don't want to waste our time and money on stuff that affects just our day-to-day we want to be really focused where our people are and with what they care about so by putting money back in the pockets uh that's a big win and by making our uh infrastructure teams more free their time is freer because they're not spending you know we do restores every week pardon me every week because those restores now run more smoothly and they are faster and there's less hunting around to try and find the backup that actually worked then that means our infrastructure teams are free to also now do other upgrades to work alongside say our developers they want to be running the current versions of the atlassian suite not you know a version from a year ago but we've got more time to do that work now it makes a big difference well that workforce productivity that you're alluding to it can be hugely impactful across the business it's not just that now you know you've got one solution one phone number to call if there's issues you've got more time back to be more innovative more strategic and so do the rest of the folks on your team so the business overall that workforce productivity can really be very widespread in a good way absolutely and it's well felt i think you know one of the things that it's really hard to put a dollar value on but it is really key is people don't like doing rework and backup recovery feels like reworking like i've been here before and so by mitigating particularly this aspect of our roles our teams are happier they generally are enjoying their work more because they're as i say they've got more time to work on things that are energizing and rewarding and across the business people feel better as well there are a lot of complications in anyone's job but certainly from the direction that hardware and storage and backup is being uh concerned we've taken away a big stress for me for example it's important that we test our dr scenario obviously everyone says that but now we can actually do it and now we can actually do a full dr production outage and go okay great let's shut it down and see what happens and we were able to do that a couple of times a year we don't have to pay for a cold dc or a warm dc in the wings we can recover to the cloud we our dr site is vmware cloud on amazon so we can spin it up and do the whole dr scenario our dr is engaged within about three hours from a full building loss and not only is that great peace of mind but also again it puts great data into the hands of my cio he's able to present on business continuity issues to the executive team and show that we're actually caring about the business and caring about the things that people do worry about and again makes people look good which is uh which is always helpful it is absolutely as you said it's really you know if you can't restore the data you're kind of stuck so now i know why you look so rested because you you have the solution you're sleeping better at night liam has been such a pleasure talking to you great work and we look forward to hearing more great stories to come from revelation software thanks so much lisa it's been a wonderful time per liam furlong i'm lisa martin you're watching the cube you

>> Narrator: From the CUBE Studios in Palo Alto, in Boston, connecting with thought leaders all around the world, this is a cube conversation. >> Hi, Lisa Martin here with Caitlin Gordon, the VP of product marketing for Dell technologies, Caitlin, welcome back to the CUBE, we're excited to see you again. >> Caitlyn: I'm very excited to be here again. >> So data protection in the news what's going on? >> Yeah, it's been a busy year, we had obviously our Power Protect DD appliance launch last year. And then this year we've had announcements on the software side. We had announcements at VMworld, some more at Dell Technologies World. And now today we're announcing even more which is the new Power Protect the DP series appliances the new integrated appliances. And it's really exciting. So we now have our Power Protect DD, the next generation of data domain, and we have our power protect DP appliances integrated appliances. And that's all about combining both protection storage, protects and software in a single converge, all in one offering. That's really popular with our customers today, because of the simplicity the ability to really modernize your data protection in a very simple way, get up really up and running quickly. And in fact, it's really the fastest growing part of the backup appliance market. >> Yeah, I have read that the integrated appliances our market is growing twice as fast as the targeted market. So give us a picture of what customers can expect from the new DP series. >> Yeah, it's not that dissimilar to actually our DD series from last year, which is there's four models in the new DP series. And it's really all about getting better performance, better efficiency. We've got new hardware, assisted compression, denser drives, and all that gives us the ability to get faster backups faster recovery, In fact, you get 38% faster up backups, 45% faster recovery, more logical capacity, 30% more logical capacity, 65 to one deduplication which is just incredible and 60,000 IOPS for instant access. So really ups the game, both in performance and efficiency. >> Those are big numbers. You mentioned the DD launch last year, contrast it with what you're announcing now. What's the significance of the DP series? >> This is exciting for us because it does a couple of things. It expands our power protect appliance family, with the new DP series of integrated appliances. But at the same time, we're also announcing other important Power Protect enhancements on the software side. Power Protect data manager which we've been enhancing and continuing to talk about all year also has some new improvements the ability to deploy it in Azure and AWS gov cloud for in-cloud protection. The enhancements that we've done with VMware that we talked about, not that long ago at VM world about being able to integrate with based policy management really automating and simplifying VMware protection. And it's really all about kuberetes, right? And the ability to support kubernetes as well. So not only is this an exciting appliance launch for us but it's also the marketing of yet even more enhancements on the Power Protect data manager side and all that together, it means that with Power Protect, you really have a one-stop shop for all of your data protection needs no matter where the data lives, no matter what SLA, whether it's a physical virtual appliance, whether it's target or integrated, you've all got them in the Power Protect family now. >> Excellent. All right. Last question for you Caitlin, we know Dell technologies is focused on three big waves, it's cloud VMware and cyber recovery. Anything else you want to add here? >> Cyber resiliency, cyber recovery Ransomware has really risen to the top of the list. Unfortunately for many organizations and Power Protect cyber recovery is really an important enhancement that we also have with this announcement today. We've had this offering in market for a couple years with the exciting new enhancement here. So it is the first cyber recovery solution endorsed by sheltered Harbor. And if you're not familiar with Power Protect cyber recovery it provides an automated air gaped solution for data isolation, and then cyber sense provides the analytics and the forensics for discovering, diagnosing, and remediating those attacks. So it's really all about ransomware protecting from, recovering from those attacks, which unfortunately have become all too common for our customers today. >> Excellent news Caitlin. Thanks for sharing. What's new congratulations to you and the Dell team. >> Thank you so much, Lisa, >> For Caitlin Gordon, I'm Lisa Martin. You're watching the cube. (outro music)

our Studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hey welcome back they're ready Jeff Rick here with the cube we're in our Palo Alto studios today to have a conversation with a really exciting company they've actually been around for a while but they've raised a ton of money and they're doing some really important work in the world in which we live today which is a lot different than the world was when they started in 2010 so we're excited to welcome to the studio he's been here on before Mohit ladee is the CEO and co-founder of Thousand Eyes mode great to see you great to see you as well as pretty to be here yeah welcome back but for people that didn't see the last video or not that familiar with Thousand Eyes tell them a little bit kind of would a thousand eyes all about absolutely so in today's world the cloud is your new data center the Internet is your new network and SAS is your new application stack and thousand eyes is built to be the the only thing that can really help you see across all three of these like it's your own private environment I love that I love that kind of setup and framing because those are the big three things and as you said all those things have moved from inside your control to outside of your control so in 2010 is that was that division I mean when you guys started the company UCLA I guess a while ago now what was that the trend what did you see what yes what kind of started it so it's really interesting right so our background as a founding company with two founders we did our PhD at UCLA in computer science and focused on internet and we were fascinated by the internet because it was just this complex system that nobody understood but we knew even then that it would meaningfully change our lives not just as consumers but even as enterprise companies so we had this belief that it's going to be the backbone of the modern enterprise and nobody quite understood how it worked because everyone was focused on your own data center your own network and so our entire vision at that point was we want people to feel the power of seeing the internet like your network that's sort of where we started and then as we started to expand on that vision it was clear to us that the Internet is what brings companies together what brings the cloud closer to the enterprise what brings the SAS applications closer to the enterprise right so we expanded into into cloud and SAS as well so when you had that vision you know people had remote offices and they would set up they would you know set up tunnels and peer-to-peer and all kinds of stuff why did you think that it was gonna go to that next step in terms of the internet you know just kind of the public Internet being that core infrastructure yes we were at the at the very early stages of this journey to cloud right and at the same time you had companies like Salesforce you had office 365 they were starting to just make it so much easier for companies to deploy a CRM you don't have to stand up these massive servers anymore its cloud-based so it was clear to us that that was gonna be the new stack and we knew that you had to build a fundamentally different technology to be able to operate in that stack and it's not just about visibility it's about making use of collective information as well because you're going from a private environment with your own data center your own private network your own application stack to something that's sitting in the cloud which is a shared environment going over the Internet which is the same network that carries cat videos that your kids watch it's carrying production traffic now for your core applications and so you need a different technology stack and you need to really sort of benefit from this notion of collective intelligence of knowing what everybody sees together as one view so I'm here I think I think Salesforce was such an important company in terms of getting enterprises to trust a SAS application for really core function which just sales right I think that was a significant moment in moving the dial was there a killer app for you guys that was you know for your customers the one where they finally said wait you know we need a different level of his ability to something that we rely on that's coming to us through an outside service so it's interesting right when we started the company we had a lot of advisors that said hey your position should be you're gonna help enterprises enforce SLA with Salesforce and we actually took a different position because what we realized was Salesforce did all the right stuff on their data centers but the internet could mess things up or enterprise companies that were not ready to move to cloud didn't have the right architectures would have some bottlenecks in their own environment because they are backhauling traffic from their London office to New York and then exiting from New York they're going back to London so all this stuff right so we took the position of really presenting thousand eyes as a way to get transparency into this ecosystem and we we believe that if we take this position if we want to help both sides not just the enterprise companies we want to help sales force we want to have enterprise companies and just really present it as a means of finding a common truth of what is actually going on it works so much better right so there wasn't really sort of one killer application but we found that anything that was real-time so if you think about video based applications or any sort of real-time communications based so the web access of the world they were just very sensitive to network conditions and internet conditions same with things that are moving a lot of data back and forth so these applications like Salesforce office 365 WebEx they just are demanding applications on the infrastructure and even if they're done great if the infrastructure doesn't it doesn't give you a great experience right and and and you guys made a really interesting insight too it's an it's an all your literature it's it's a really a core piece of what you're about and you know when you owned it you could diagnose it and hopefully you could fix it or call somebody else to fix it but when you don't own it it's a very different game and as you guys talked about it's really about finding the evidence or everyone's not pointing fingers back in and forth a to validate where the actual problem is and then to also help those people fix the problem that you don't have direct control of so it's a very different you know kind of requirement to get things fixed when they have to get fixed yeah and the first aspect of that is visibility so as an example right you generally don't have a problem going from one part of your house to another part of your house because you own the whole place you know exactly what sits between the two rooms that you're trying to get to you don't you don't have run into surprises but when you're going from let's say Palo Alto to San Francisco and you have two options you can take the 101 or 280 you need to know what you expect to see before you get on one of those options right and so the Internet is very similar you have these environments that you have no idea what to expect and if you don't see that with the right level of granularity that you would in your own environments you would make decisions that you have you know you have no control over right the visibility is really important but it's giving that lens like making it feel like a google maps of the internet that gives you the power to look at these environments like it's your private network that's the hard part right and then so what you guys have done as I understand is you've deployed sensors basically all over the Internet all at an important pops yeah an important public clouds and important enterprises etc so that you now have a view of what's going on it I can have that view inside my enterprise by leveraging your infrastructure is that accurate correct and so this is where the notion of being able to set up this sort of data collection environment is really difficult and so we have created all of this over years so enterprise companies consumer companies they can leverage this infrastructure to get instant results so there's zero implementation what right but the key to that is also understanding the internet itself and so this is where a research background comes in play because we studied we did years of research on actually modeling the internet so we know what strategic locations to put these probes that to give good coverage we know how to fill the gaps and so it's not just a numbers game it's how you deploy them where you deploy them and knowing that connectivity we've created this massive infrastructure now that can give you eyes on the internet and we leverage all of their data together so if let's say hypothetically you know AT&T has an issue that same issue is impacting multiple customers through all our different measurements so it's like ways if you're using ways to get from point A to point B if Waze was just used by your family members and nobody else it would give you completely useless information values in that collective insight right and then now you also will start to be able to until every jamel and AI and you know having all that data and apply just more machine learning to it to even better get out in front of problems I imagine as much as as is to be able to identify it so that's a really interesting point right so the first thing we have to tackle is making a complex data set really accessible and so we have a lot of focus into essentially getting insights out of it using techniques that are smarter than the brute-force techniques to get insights out and then present it in manners that it's accessible and digestible and then as we look into the next stages we're going to bring more and more things like learning and so on to take it even further right it's funny the accessible and digestible piece I've just had a presentation the other day and there was a woman from a CSO at a big bank and she talked about you know the problem of false positives and in in early days I mean their biggest issues was just too much data coming in from too many sensors and and too many false positives to basically bury people so I didn't have time to actually service the things that are a priority so you know a nice presentation of a whole lot of data that's a big difference to make it actual it is absolutely true and now that the example I'll give you is oftentimes when you think about companies that operate with a strong network core like we do they are in the weeds right which is important but what is really important is tying that intelligence to business impact and so the entire product portfolio we've built it's all about business impact user experience and then going into connecting the dots or the network side so we've seen some really interesting events and as much as we know the internet every day I wake up and I see something that surprises me right we've had customers that have done migrations to cloud that have gone horribly wrong right so we the latest when I was troubleshooting with the customer was where we saw they migrated from there on from data center to Amazon and the user experience was 10x worse than what it was on their own data the app once they moved to Amazon okay and what had happened there was the whole migration to Amazon included the smart sort of CDN where they were fronting your traffic at local sites but the traffic was going all over the place so from if a user was in London instead of going to the London instance of Amazon they were going to Atlanta they were going to Los Angeles and so the whole migration created a worse user experience and you don't have that lens because you don't see that in a net portion of that right that's what we like we caught it instantly and we were able to showcase that hey this is actually a really bad migration and it's not that Amazon is bad it's just it's been implemented incorrectly right so ya fix these things and those are all configurations all Connecticut which is so very easy all the issues you hear about with with Amazon often go back to miss configuration miss settings suboptimal leaving something open so to have that visibility makes a huge impact and it's more challenging because you're trying to configure different components of this environment right so you have a cloud component you have the internet component your own network you have your own firewalls and you used to have this closed environment now it's hybrid it involves multiple parties multiple skill sets so a lot of things can really go wrong yeah I think I think you guys you guys crystallize very cleanly is kind of the inside out and outside in approach both you know a as as a service consumer yep right I'm using Salesforce I'm using maybe s3 I'm using these things that I need and I want to focus on that and I want to have a good experience I want my people to be able to get on their Salesforce account and book business but but don't forget the other way right because as people are experiencing my service that might be connecting through and aggregating many other services along the way you know I got to make sure my customer experience is big and you guys kind of separate those two things out and really make sure people are focusing on both of them correct and it's the same technology but you can use that for your production services which are revenue generating or you can use that for your employee productivity the the visibility that you provide is is across a common stack but on the production side for example because of the way the internet works right your job is not just to ensure a great performance in user experience your job is also to make sure that people are actually reaching your site and so we've seen several instances where because of the way internet works somebody else could announce that their google.com and they could suck a bunch of traffic from the Internet and this happens quite routinely in the notion of what is now known as DP hijacks or sometimes DNS hijacks and the the one that I remember very well is when there was the small ISP in Nigeria that announced the identity of the address block for Google and that was picked up by China Telecom which was picked up by a Russian telco and now you have Russia China and Nigeria in the path for traffic to Google which is actually not even going to Google's right those kinds of things are very possible because of the way the internet how fast those things kind of rise up and then get identified and then get shut off is this hours days weeks in this kind of example so it really depends because if you are let's say you were Google in this situation right you're not seeing a denial of service attack T or data centers in fact you're just not seeing traffic running it because somebody else is taking it away right it's like identity theft right like I somebody takes your identity you wouldn't get a mail in your inbox saying hey your identity has been taken back so I see you have to find it some other way and usually it's the signal by the time you realize that your identity has been stolen you have a nightmare ahead of you all right so you've got some specific news a great great conversation you know it's super insightful to talk people that are in the weeds of how all the stuff works but today you have a new a new announcement some new and new offering so tell us about what's going on so we have a couple of announcements today and coming back to this notion of the cloud being a new data center the internet your new network right two things were announcing today is one we're announcing our second version of the cloud then benchmark performance comparison and what this is about is really helping people understand the nuances the performance difference is the architecture differences between Amazon Google ad your IBM cloud and Alibaba cloud so as you make decisions you actually understand what is the right solution for me from a performance architecture standpoint so that's one it's a fascinating report we found some really interesting findings that surprised us as well and so we're releasing that we're also touching on the internet component by releasing a new product which we call as Internet insights and that is giving you the power to actually look at the internet more holistically like you own the entire internet so that is really something we're all excited about because it's the first time that somebody can actually see the Internet see all these connections see what is going on between major service providers and feel like you completely owned the environment so are people using information like that to dynamically you know kind of reroute the way that they handle their traffic or is it more just kind of a general health you know kind of health overview you know how much of it do I have control over how much should I have control over and how much of I just need to know what's going on so yeah so in just me great question so the the best way I can answer that is what I heard CIO say in a CIO forum we were presenting it where they were a customer it's a large financial services customer and somebody asked the CIO what was the value of thousand I wasn't the way he explained it which was really fascinating was phase one of thousand eyes when we started using it was getting rid of technical debt because we would keep identifying issues which we could fix but we could fix the underlying root cause so it doesn't happen again and that just cleared the technical debt that we had made our environment much better and then we started to optimize the environments to just get better get more proactive so that's a good way to think about it when you think about our customers most of the times they're trying to just not have their hair on fire right that's the first step right once we can help them with that then they go on to tuning optimising and so on but knowing what is going on is really important for example if you're providing a.com service like cube the cube comm right it's its life and you're providing it from your data center here you have two up streams like AT&T and Verizon and Verizon is having issues you can turn off that connection and read all your customers back live having a full experience if you know that's the issues right right the remediation is actually quite quite a few times it's very straight forward if you know what you are trying to solve right so do you think on the internet insights this is going to be used just more for better remediation or do you think it's it's kind of a step forward and getting a little bit more proactive and a little bit more prescriptive and getting out ahead of the issues or or can you because these things are kind of ephemeral and come and go so I think it's all of the about right so one the things that the internet insights will help you is with planning because as you expand into new geo so if you're a company that's launching a service in a new market right that immediately gives you a landscape of who do you connect with where do you host right now you can actually visualize the entire network how do you reach your customer base the best right so that's the planning aspect and if you plan right you would actually reduce a lot of the trouble that you see so we had this customer of ours that was deploying Estevan software-defined man in there a she offices and they used thousand eyes to evaluate two different ISPs that they were looking at one of them had this massive time-of-day congestion so every time every day at nine o'clock the latency would get doubled because of congestion it's common in Asia the other did not have time of day congestion and with that view they could implement the entire Estevan on the ice pea that actually worked well for them so planning is important part of this and then the other aspect of this is the thing that folks often don't realize is internet is not static it's constantly changing so you know AT&T may connect to where I is in this way it connects it differently it connects to somebody else and so having that live map as you're troubleshooting customer experience issues so let's say you have customers from China that are having a ton of issues all of a sudden or you see a drop of traffic from China now you can relate that information of where these customers are coming from with our view of the health of the Chinese internet and which specific ISPs are having issues so that's the kind of information merger that simply doesn't happen today right promote is a fascinating discussion and we could go on and on and on but unfortunately do not have all day but I really like what you guys are doing the other thing I just want to close on which which I thought was really interesting is you know a lot of talked about digital transformation we always talk about digital transformation everybody wants a digital transfer eyes it but you really boiled it down into really three create three critical places that you guys play the digital experience in terms of what what the customers experience you know getting to cloud everybody wants to get to cloud so one can argue how much and what percentage but everybody's going to cloud and then as you said in this last example the modern when as you connect all these remote sites and you guys have a play in all of those places so whatever you thought about in 2010 that worked out pretty well thank you and we had a really strong vision but kudos to the team that we have in place that has stretched it and really made the most out of that so excited good job and thanks for for stopping by sharing the story thank you for hosting always fun to be here absolutely all right well he's mo and I'm Jeff you're watching the cube when our Palo Alto studio is having a cube conversation thanks for watching we'll see you next time [Music]

>> Announcer: From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello, and welcome to theCUBE studios, in Palo Alto, California for another CUBE conversation where we go in depth with though leaders driving innovation across tech industry. I'm your host, Peter Burris. The whole concept of self service analytics has been with us decades in the tech industry. Sometimes its been successful, most times it hasn't been. But we're making great progress and have over the last few years as the technologies matures, as the software becomes more potent, but very importantly as the users of analytics become that much more familiar with what's possible and that much more wanting of what they could be doing. But this notion of self service analytics requires some new invention, some new innovation. What are they? How's that going to play out? Well, we're going to have a great conversation today with Stephanie McReynolds, she's Senior Vice President of Marketing, at Alation. Stephanie, thanks again for being on theCUBE. >> Thanks for inviting me, it's great to be back. >> So, tell us a little, give us an update on Alation. >> So as you know, Alation was one of the first companies to bring a data catalog to the market. And that market category has now been cemented and defined depending on the industry analyst you talk to. There could be 40 or 50 vendors now who are providing data catalogs to the market. So this has become one of the hot technologies to include in a modern analytics stacks. Particularly, we're seeing a lot of demand as companies move from on premise deployments into the cloud. Not only are they thinking about how do we migrate our systems, our infrastructure into the cloud but with data cataloging more importantly, how do we migrate our users to the cloud? How do we get self-service users to understand where to go to find data, how to understand it, how to trust it, what re-use can we do of it's existing assets so we're not just exploding the amount of processing we're doing in the cloud. So that's been very exciting, it's helped us grow our business. We've now seen four straight years of triple digit revenue growth which is amazing for a high growth company like us. >> Sure. >> We also have over 150 different organizations in production with a data catalog as part of their modern analytics stack. And many of those organizations are moving into the thousands of users. So eBay was probably our first customer to move into the, you know, over a thousand weekly logins they're now up to about 4,000 weekly logins through Alation. But now we have customers like Boeing and General Electric and Pfizer and we just closed a deal with US Air Force. So we're starting to see all sorts of different industries and all sorts of different users from the analytics specialist in your organization, like a data scientist or a data engineer, all the way out to maybe a product manager or someone who doesn't really think of them as an analytics expert using Alation either directly or sometimes through one of our partnerships with folks like Tableau or Microstrategy or Power BI. >> So, if we think about this notion of self- service analytics, Stephanie, and again it's Alation has been a leader in defining this overall category, we think in terms of an individual who has some need for data but is, most importantly, has questions they think data can answer and now they're out looking for data. Take us through that process. They need to know where the data is, they need to know what it is, they need to know how to use it, and they need to know what to do if they make a mistake. How is that, how are the data catalogs, like Alation, serving that, and what's new? >> Yeah, so as consumers, this world of data cataloging is very similar if you go back to the introduction of the internet. >> Sure. >> How did you find a webpage in the 90's? Pretty difficult, you had to know the exact URL to go to in most cases, to find a webpage. And then a Yahoo was introduced, and Yahoo did a whole bunch of manual curation of those pages so that you could search for a page and find it. >> So Yahoo was like a big catalog. >> It was like a big catalog, an inventory of what was out there. So the original data catalogs, you could argue, were what we would call from an technical perspective, a metadata repository. No business user wants to use a metadata repository but it created an inventory of what are all the data assets that we have in the organizations and what's the description of those data assets. The meta- data. So metadata repositories were kind of the original catalogs. The big breakthrough for data catalogs was: How do we become the Google of finding data in the organization? So rather than manually curating everything that's out there and providing an in- user inferant with an answer, how could we use machine learning and AI to look at patterns of usage- what people are clicking on, in terms of data assets- surface those as data recommendations to any end user whether they're an analytics specialist or they're just a self- service analytics user. And so that has been the real break through of this new category called data cataloging. And so most folks are accessing a data catalog through a search interface or maybe they're writing a SQL query and there's SQL recommendations that are being provided by the catalog-- >> Or using a tool that utilizes SQL >> Or using a tool that utilizes SQL, and for most people in a- most employees in a large enterprise when you get those thousands of users, they're using some other tool like Tableau or Microstrategy or, you know, a variety of different data visualization providers or data science tools to actually access that data. So a big part of our strategy at Alation has been, how do we surface this data recommendation engine in those third party products. And then if you think about it, once you're surfacing that information and providing some value to those end users, the next thing you want to do is make sure that they're using that data accurately. And that's a non- trivial problem to solve, because analytics and data is complicated. >> Right >> And metadata is extremely complicated-- >> And metadata is-- because often it's written in a language that's arcane and done to be precise from a data standpoint, that's not easily consumable or easily accessible by your average human being. >> Right, so a label, for example, on a table in a data base might be cust_seg_257, what does that mean? >> It means we can process it really quickly in the system. >> Yeah, but as-- >> But it's useless to a human being-- >> As a marketing manager, right? I'm like, hey, I want to do some customer segmentation analysis and I want to find out if people who live in California might behave differently if I provide them an offer than people that live in Massachusetts, it's not intuitive to say, oh yeah, that's in customer_seg_ so what data catalogs are doing is they're thinking about that marketing manager, they're thinking about that peer business user and helping make that translation between business terminology, "Hey I want to run some customer segmentation analysis for the West" with the technical, physical model, that underlies the data in that data base which is customer_seg_257 is the table you need to access to get the answer to that question. So as organizations start to adapt more self- service analytics, it's important that we're managing not just the data itself and this translation from technical metadata to business metadata, but there's another layer that's becoming even more important as organizations embrace self- service analytics. And that's how is this data actually being processed? What is the logic that is being used to traverse different data sets that end users now have access to. So if I take gender information in one table and I have information on income on another table, and I have some private information that identifies those two customers as the same in those two tables, in some use tables I can join that data, if I'm doing marketing campaigns, I likely can join that data. >> Sure. >> If I'm running a loan approval process here in the United States, I cannot join that data. >> That's a legal limitation, that's not a technical issue-- >> That's a legal, federal, government issue. Right? And so here's where there's a discussion, in folks that are knowledgeable about data and data management, there's a discussion of how do we govern this data? But I think by saying how we govern this data, we're kind of covering up what's actually going on, because you don't have govern that data so much as you have to govern the analysis. How is this joined, how are we combining these two data sets? If I just govern the data for accuracy, I might not know the usage scenario which is someone wants to combine these two things which makes it's illegal. Separately, it's fine, combined, it's illegal. So now we need to think about, how do we govern the analytics themselves, the logic that is being used. And that gets kind of complicated, right? For a marketing manager to understand the difference between those things on the surface is doesn't really make sense. It only makes sense when the context of that government regulation is shared and explained and in the course of your workflow and dragging and dropping in a Tableau report, you might not remember that, right? >> That's right, and the derivative output that you create that other people might then be able to use because it's back in the data catalog, doesn't explicitly note, often, that this data was generated as a combination of a join that might not be in compliance with any number of different rules. >> Right, so about a year and a half ago, we introduced a new feature in our data catalog called Trust Check. >> Yeah, I really like this. This is a really interesting thing. >> And that was meant to be a way where we could alert end users to these issues- hey, you're trying to run the same analytic and that's not allowed. We're going to give you a warning, we're not going to let you run that query, we're going to stop you in your place. So that was a way in the workflow of someone while they're typing a SQL statement or while they're dragging and dropping in Tableau to surface that up. Now, some of the vendors we work with, like Tableau, have doubled down on this concept of how do they integrate with an enterprise data catalog to make this even easier. So at Tableau conference last week, they introduced a new metadata API, they introduced a Tableau catalog, and the opportunity for these type of alerts to be pushed into the Tableau catalog as well as directly into reports and worksheets and dashboards that end users are using. >> Let me make sure I got this. So it means that you can put a lot of the compliance rules inside Alation and have a metadata API so that Alation effectively is governing the utilization of data inside the Tableau catalog. >> That's right. So think about the integration with Tableau is this communication mechanism to surface up these policies that are stored centrally in your data catalog. And so this is important, this notion of a central place of reference. We used to talk about data catalogs just as a central place of reference for where all your data assets lie in the organizations, and we have some automated ways to crawl those sources and create a centralized inventory. What we've added in our new release, which is coming out here shortly, is the ability to centralize all your policies in that catalog as well as the pointers to your data in that catalog. So you have a single source of reference for how this data needs to be governed, as well as a single source of reference for how this data is used in the organization. >> So does that mean, ultimately, that someone could try to do something, trust check and say, no you can't, but this new capability will say, and here's why or here's what you do. >> Exactly. >> A descriptive step that says let me explain why you can't do it. >> That's right. Let me not just stop your query and tell you no, let me give you the details as to why this query isn't a good query and what you might be able to do to modify that query should you still want to run it. And so all of that context is available for any end user to be able to become more aware of what is the system doing, and why is recommending. And on the flip side, in the world before we had something like Trust Check, the only opportunity for an IT Team to stop those queries was just to stop them without explanation or to try to publish manuals and ask people to run tests, like the DMV, so that they memorized all those rules of governance. >> Yeah, self- service, but if there's a problem you have to call us. >> That's right. That's right. So what we're trying to do is trying to make the work of those governance teams, those IT Teams, much easier by scaling them. Because we all know the volume of data that's being created, the volume of analysis that's being created is far greater than any individual can come up with, so we're trying to scale those precious data expert resources-- >> Digitize them-- >> Yeah, exactly. >> It's a digital transformation of how we acquire data necessary-- >> And then-- >> for data transformation. >> make it super transparent for the end user as to why they're being told yes or no so that we remove this friction that's existed between business and IT when trying to perform analytics. >> But I want to build a little bit on one of the things I thought I heard you say, and that is that the idea that this new feature, this new capability will actually prescribe an alternative, logical way for you to get your information that might be in compliance. Have I got that right? >> Yeah, that's right. Because what we also have in the catalog is a workflow that allows individuals called Stewards, analytics Stewards to be able to make recommendations and certifications. So if there's a policy that says though shall not use the data in this way, the Stewards can then say, but here's an alternative mechanism, here's an alternative method, and by the way, not only are we making this as a recommendation but this is certified for success. We know that our best analysts have already tried this out, or we know that this complies with government regulation. And so this is a more active way, then, for the two parties to collaborate together in a distributed way, that's asynchronous, and so it's easy for everyone no matter what hour of the day they're working or where they're globally located. And it helps progress analytics throughout the organization. >> Oh and more importantly, it increases the likelihood that someone who is told you now have self- service capability doesn't find themselves abandoning it the first time that somebody says no, because we've seen that over and over with a lot of these query tools, right? That somebody says, oh wow, look at this new capability until the screen, you know, metaphorically, goes dark. >> Right, until it becomes too complicated-- >> That's right-- >> and then you're like, oh I guess I wasn't really trained on this. >> And then they walk away. And it doesn't get adopted. >> Right. >> And this is a way, it's very human centered way to bring that self- service analyst into the system and be a full participant in how you generate value out of it. >> And help them along. So you know, the ultimate goal that we have as an organization, is help organizations become our customers, become data literate populations. And you can only become data literate if you get comfortable working with the date and it's not a black box to you. So the more transparency that we can create through our policy center, through documenting the data for end users, and making it more easy for them to access, the better. And so, in the next version of the Alation product, not only have we implemented features for analytic Stewards to use, to certify these different assets, to log their policies, to ensure that they can document those policies fully with examples and use cases, but we're also bringing to market a professional services offering from our own team that says look, given that we've now worked with about 20% of our installed base, and observed how they roll out Stewardship initiatives and how they assign Stewards and how they manage this process, and how they manage incentives, we've done a lot of thinking about what are some of the best practices for having a strong analytics Stewardship practice if you're a self- service analytics oriented organization. And so our professional services team is now available to help organizations roll out this type of initiative, make it successful, and have that be supported with product. So the psychological incentives of how you get one of these programs really healthy is important. >> Look, you guys have always been very focused on ensuring that your customers were able to adopt valued proposition, not just buy the valued proposition. >> Right. >> Stephanie McReynolds, Senior Vice President of Marketing Relation, once again, thanks for being on theCUBE. >> Thanks for having me. >> And thank you for joining us for another CUBE conversation. I'm Peter Burris. See you next time.

(upbeat music) >> Announcer: From our studios in the heart of Silicon Valley, Palo Alto, California, This is a Cube Conversation. >> Hello and welcome to theCUBE studios in Palo Alto, California for another Cube Conversation. Where we go in depth with thought leaders driving innovation across the tech industry. I'm your host, Peter Burris. Michael Segal is the product manager, or Area Vice President of Strategic Alliances in NetScout Systems. Michael, we are sitting here in theCUBE studios in Palo Alto in November of 2019, re:Invent 2019 is right around the corner. NetScout and AWS are looking to do some interesting things. Why don't you give us an update of what's happening. >> Yeah, just very brief introduction of what NetScout actually does. So, NetScout assures service, performance and security for the largest enterprises and service providers in the world. We do it for something we refer to as visibility without borders by providing actionable intelligence necessary to very quickly identify the root cause of either performance or security issues. So with that, NetScout, partnering very closely with AWS. We are an advanced technology partner, which is the highest tier for ISVs of partnership. This enables us to partner with AWS on a wide range of activities including technology alignment with road map and participating in different launch activities of new functionality from AWS. It enables us to have go-to market activities together, focusing on key campaigns that are relevant for both AWS and NetScout. And it enables us also to collaborate on sales initiatives. So, with this wide range of activities, what we can offer is a win-win-win situation for our customers, for AWS, and for NetScout. So, from customers' perspective, beyond the fact that NetScout offering is available in AWS marketplace, now this visibility without borders that I mentioned, helps our customers to navigate through their digital transformation journey and migrate to AWS more effectively. From AWS perspective, the win is their resources are now consumed by the largest enterprises in the world, so it accelerates the consumption of compute, storage, networking, database resources in AWS. And for NetScout, this is strategically important because now NetScout becoming a strategic partner to our large enterprise customers as they navigate their digital transformation journey. So that's why it's really important for us to collaborate very, very efficiently with AWS. It's important to our customers, and it's important to AWS. >> And you're going to be at re:Invent. You're actually going to be speaking, as I understand. What are you going to be talking about? >> So we are going to be talking about best practices of migrating to AWS. NetScout also is a platinum sponsor for the re:Invent show. This demonstrates our commitment to AWS, and the fact that we want to collaborate and partner with them very, very efficiently. And beyond that also, NetScout partnered with AWS on the launch of what is referred to as Amazon VPC traffic mirroring. And, this functionality enables us to acquire traffic data and packet data very efficiently in AWS. And it's part of the technology aligns that we have with AWS and demonstrates how we utilize these technology aligns to extend NetScout visibility without borders to AWS cloud. >> There's no reason to make AWS cloud a border. >> Michael Segal: Exactly. >> Michael Segal, NetScout Systems. Thanks very much for being on theCUBE. >> Thank you for having me. >> And, once again we'd like to thank you for joining us for another Cube Conversation. Until next time. (upbeat music)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host still minimun hi and welcome to a special cube conversation here in our Boston area studio I'm Stu minimun and we're getting towards the end of 2019 where we've had a bevy of cloud conferences I've - I've attended Microsoft ignite cube con cloud native con and the big the Super Bowl for industry AWS reinvent is right on the horizon and happy to talk about some of the data protection items related to cloud welcoming back to our program RIA a touch Barrett who is the vice president of marketing in the data protection group at Dell EMC Fria great to see you great to see you Stu nice to be back alright so RIA you know obviously cloud has had such a huge impact on our entire industry you know transforming what's happening there bring us inside how some of those trends are really impacting your organization in your customers yeah definitely I think one of the things that no one would be surprised about is that organizations today are managing seven times the data that they were managing just two years ago so last year in 2018 there was a study done by Vanson Bourne and analyst firm it's called the global data protection index study where they surveyed over 2,200 IT decision-makers and they asked specifically about their data protection challenges one interesting data point is more than 76 percent of the surveyed had placed some sort of data disruption in the last 12 month the preceding 12 months before the survey and 30 close to 30 percent are twenty seven to be exact had lost data costing upwards of millions based on that disruption so before you even get into some of the market trends that's complicating protection I think a lot of customers are still very challenged with their data protection just in any regular environment now the challenge are on data protection and even more broadly data management because again there's the 80/20 rule a lot of your data is actually in the tertiary secondary copies of your data it's getting more complex so a couple of big trends that you and I talk about all the time data growth we kind of talked about that data distribution data is more distributed than ever you have it across multiple clouds you have data hungry technologies like artificial intelligence and machine learning that's basically generating data volumes that's unprecedented and that will be generating data volumes that are unprecedented and obvious and some of these technologies are actually also fueling data growth at the edge so I think that I saw a number or I think Michael Dell was talking about how the data at the edge is actually going to surpass data in all of the clouds combined in the near future then you have application transformation so that's where cloud really comes in a lot of our customers are speeding their time to market and their exchanges and interactions with their customers by really transforming their application development and using cloud native you know application deployment to really fuel how they're how they're developing apps and that's requiring new ways of data protection then you bring into effect all the regulatory rules there's one coming up very shortly I think in January so you have increasing governmental regulations you have increasing privacy laws and and mandates so again data protection is getting into this area where you would say it's in the eye of the storm yeah so many challenges what we've really loved to document over the last few years is the opportunity around data your business is creating new business value creating new lines of business and really extracting information use the word information even you know we've really defined is what defines a company that has successfully gone through digital transformation is it as data that is driving decisions and companies there so you've talked to a lot of customers you've got some survey data or you bring us inside you know what are some of those leading-edge customers what differentiates kind of the leaders and ones that become winners in this world compared to before data was at the center of what they were doing absolutely three the power of three again I think the the companies that are really doing things well or have seem to have a handle around their ever-changing data protection needs are doing have three things in common I think the first thing is pretty evident and you talk to it just now Stu they value data they see data as capital so the amount of attention they give to data is really significantly different than a lot of the other companies so they really ranked when they talked about how they see data as the most important capital you know one of the most important capitals in their in their environment they looked at productivity apps as a significant area of importance they looked at AI machine learning business intelligence and analytics as some of the most critical applications including the new cloud native applications they are gaining significant importance in the eyes of these companies so first and foremost they really value data and they want to make sure that they are protecting it in a way that really meets what they need to the second thing that's really interesting that they're doing is they're investing in a single vendor for all of their data protection needs again this is based on the global data protection index study of the 2,200 IT decision makers and GDP I found that companies that are using at least two vendors are 35 percent more likely to experience some sort of disruption and when they talk about disruption they talked about downtime ransomware and they talked about data loss as the number most frequently cited disruptions in their environment and multiple vendor solutions really really lead to increased complexity there's just more touch points disparate management tools especially when you're in a recovery type situation it just adds a lot of complexity to it including service and support experience that you're going to get from multiple vendors so again investing in a single solution across a very diverse portfolio of application deployment choices physical virtual multi-cloud including extent to cloud use cases as well as cloud native protection really makes sense from core to edge to cloud and I think it will increase decrease the complexity as well as minimize the downtime associated with any type of disruption so that's the second trend so we talked about they value data the second one was that they really have investing in a single partner in their data protection solutions the other one is that they prioritize the third one they have some fundamental needs that they prioritize for their multi cloud so they prioritize scale efficiency as well as ease of management for their multi cloud data protection needs so while cloud computing gives us a lot of flexibility agility it can also bring with it complexity unknown costs and increased risk if not managed appropriately and if this extends to your data protection environment so you need data protection solutions that basically can manage that are easy to scale easy to deploy and deliver efficiency and resiliency across this multi cloud environment so those are the three things that are really doing differently still all right yes so many so many things that customers need to think about now living in that multi cloud world cloud native infiltrating the application environment so as we look forward to 2020 here what are those new requirements so you know what a customers need to really think about when they're they're shaping the future of building their environments yeah that's that's a great question and all of the new requirements start with the fundamentals if you don't have the fundamentals and your requirements will fall short and if anything the fundamentals are becoming more and more critical so we already talked about what those companies that are doing well really do differently so they value scale efficiency performance and when they look at those environments they look at it across a distributed deployment model so you're talking about global scale performance at a global level you know if efficiency across the cloud as well as the cloud resources that you're utilizing so if when you talk about efficiency and performance and scale it takes on a brand-new meaning in the new set of requirements and then there's some real new new requirements so for protection we're seeing protection for cloud native applications so we were at kubernetes and we had our kubernetes cube con and we were showcasing our container data protection kubernetes container data protection so we're doing a tech preview of that that got really well received because a lot of companies are struggling with how they're going to be protecting containers and then you have protection for modern apps SAS based applications MongoDB cloud era type applications that now need protection so it used to be a wide range of different applications now there's new modern apps that need the same level of protection and they have new requirements one of the last ones is again protection of traditional because you're going to still have a big traditional deployment and cloud native applications at what we're calling global scale so what does global scale mean it means you have visibility and reporting to ensure protection across health compliance efficiency across core edge and multi cloud right those are going to be some of the new requirements and then data reuse is another one that we see coming up more and more so there's so much investment in making sure your data is protected and companies want to actually get additional value out of their protection data and they want to drive that value through innovation through being able to leverage that data for app dev and test analytics type work so really they want to be able to do that on their secondary and tertiary copies so that's another set new set of requirements that we're seeing so it starts with the fundamentals and then you need to be able to scale and drive these new requirements yeah absolutely in many ways some of these requirements echo what we had in the past you know go back 20 years ago was spreading a crawl you know mainframe UNIX and Linux and Windows and now it's multi cloud and SAS and hybrid environments so really exciting stuff you know your team you know just give us a look for 2020 you know you know seeing Dell EMC show up not only at of course Dell technology's world but you know cube Colin and reinvent and some of these cloud shows yeah yes more and more Dell to be announced I'll tech cloud last year so it's a big focus for the company what we're doing in partnership with VMware so there's a lot of exciting things that are happening and data protection is really becoming critical to all of these conversations so it's going to be a very exciting year I think it's going to be a defining year for us next year and you're gonna see innovation like you've never seen before from Dell EMC all right exciting stuff definitely so much opportunity innovation happen in the clouds Rhea thank you so much for the updates looking forward to seeing the team with lots of you know over 50,000 of everybody's friends in Las Vegas for AWS thank you thanks for having us - all right be sure to check out the cube net for all of the AWS reinvent content as well as all the other shows we've done this year and look forward to 2020 also I'm Stu minimun thanks for watching the Q

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host Stu minimun hi and welcome to a special cube conversation here in our Boston area studio I am Stu minimun and we're digging in with Dell EMC on data protection in the multi cloud where era happy to join welcome to the program first time guest Nelson Nelson Hsu who is the director of solutions marketing with Dell EMC Nelson great to see you great to be here thank you sir all right so you and I were both at Q con plus cloud native con with about 12,000 of our friends in the open-source community down in San Diego California you know when you bring us in first it's probably not the first place that people think of when they think of Delhi MC so explain a little bit what the team was doing the announcements there and what you're seeing at the show sure no I appreciate that it was a first time for for Dell technologies it was kind of our coming-out party if you all went into the cloud native realm we've got a tremendous amount of momentum especially OCR on kubernetes between what we've done in the data protection space with our power protect software for kubernetes we've done in our storage room in the work that we've done around container storage interfaces so a lot of that was coming out in introducing that to the Keuka and cognitive count attendees I think it was a really good timing though yeah Elson we've been watching you know the role the developers the discussion of DevOps of course is central what's happening not only at cube con but many of the cloud shows there I know at VMworld you know you see what's happening on with the VMware code team so explain how a kind of the the Dell technologies cloud partnership with vm or how about all that all pulls together for activities that the your organization's doing with that within the DevOps well you know you you know they were right they're right it's all about DevOps it's about the developers it's about the the new world of bringing cloud native applications and driving them into the production environment I think that you know we heard that at vmworld with pack L singer and we're his his pillars of you know build run protect connect are key aspects so you know if you look at that man component protect falls right into that area right because with the growth of data as we're seeing it today the need to manage that in the cloud native realm becomes even more prevalent and important you know we've seen DevOps mature over the last couple years where you see you know we had 8,000 people in Seattle right now we had 12,500 of your best friends and just gonna go out right I'm sure you saw that yeah absolutely huge growth there and I'm glad you brought up to protect thing because when I think about developers we want to reduce the friction for developers to be able to build their apps you think about DevOps is you know keeping agility going but you know where is the data and how do I make sure that you know we know when we go to a cloud world we still need to things about security we still need to think about data management and data protection there so explain for audience how that protect piece fits into the DevOps world well you know for first we should clarify a little bit right because like over the last two years everything's been about security within containers right and that's great because you're protecting the applications and people are worried about about penetration there and and it's been fantastic and I think that today specifically around the aspect of securing the application and now securing the infrastructure is key you know storage has become a very very relevant topic whether it's like persistent volumes taking center stage right when it comes to claim a vApps movie into production because it's about protecting those mission critical workloads and as you just stated you have your applications but at the end of the day your data right is really at the capital right and that's what you really need to focus on it becomes greater and greater importance when you have that holistic discussion about DevOps right and so now we have the aspect of the kubernetes administrator meets the IT administrator all right and having to be able to protect through this application transformation that's being driven by cloud native complexity and that you know tradition was disaggregated from the infrastructure but now as you mature and you look at those production and mission-critical environments you really have to pay attention to how am I going to protect my data the edge to core to cloud and in that cloud native world yeah definitely is one of those areas we found at the conference for many it's a steep learning curve to try to understand you know kubernetes all these cloud native architectures if you come in there with the traditional infrastructure role I was actually something we were discussed more a couple of years ago was they've some of the basic blocking and tackling of networking and storage inside of a container environment but now a lot of discussion is around that application development and therefore we need to make sure that we're having not only the app dev but the infrastructure team all understanding how everything goes together and you know protection of course a critical piece there oh absolutely and and you know if we look at all the different projects that are underway under C and C F I mean it's fantastic right I mean there's so much momentum everyone's now also looking at that infrastructure right I mean last year was all about the surface mesh right so I think that we're at that inflection point and now it's going to be a lot about the storage and protecting that storage if you look at Project Valero right so project Valero wasn't as an open source project under C and C F right being driven by the work that was done by the the you know the the the active form enormous hefty oh right so I got Joe Bereta right you got Greg Milwaukee and the work that they done in the starter house arc well now WMC in specificity of the data protection team is working and contributing hand in hand with the vmware team on velaro and i think you'll see that resonate through the future of tansu and pacific as we go forward great let's connect the dots now between what we're doing is the CMC F cube con show and now we've got AWS reinvented coming up so Amazon might now let us use the word multi-cloud that that context there but absolutely that was the conversation at many of the other shows this year is you know hybrid cloud multi-cloud how customers get their arms around all these environments so you know help us understand how this story that we were just talking about for cloud native environment fits into the broader kind of public cloud discussion oh absolutely so you I think one of the key aspects to that is around consistency right so being able from a data protection perspective be able to protect all that valuable data that you have whether it's in premises where it's in cloud with its multi cloud or hybrid and you want to be able to protect that holistically using the same capability you have from your premises base into or out of or within cloud all right so I want to be able to within AWS be able to protect my data from region to region right so we've got a great offering for VMware cloud on AWS it allows you to protect into and within the cloud itself so you can protect in and extend out to the cloud yeah definitely probably one of the most interesting partnerships I think the industry's been watching the last two years is you know VMware and AWS now you know the dominant virtualization you know in your data center environment and you know the leader in public clouds so looking forward to hearing some proof points at the conference and he gives a little bit of hint as to what we'll be seeing in hearing about at the show well I think you'll hear a lot about that consistency with regards to you know observability orchestration automation automation becomes so key that you take your workflows for data protection from premises to the cloud and having that consistency I think you'll also see some pretty pretty significant numbers coming forth with regards to how much data is being protected in in AWS ok definitely looking forward to that always love looking forward to the customers all right Nelson I want to give you the last word what else should we be looking for your team kind of end of 2019 it going into 2020 well you know I think it all starts with cloud and multi clock all right that's our core focus that's what we're driven to I think you'll see innovation especially in the cloud native space that we have I think you will see further innovation in in the in the cybersecurity in the cyber recovery space around data protection so I think those are really key elements that that you'll see more from yeah absolutely super important discussions around data around security and everything there Nelson thank you so much for joining us here in the cube sue thank you all right be sure to check out silicon angle for exclusive content leading up to and after AWS reinvent of course and check out the cube net if you're not at the table if you are at the show come to the center of the show floor at the Venetian inside the Sands Convention Center you can find myself Dave Volante John Ferrier and our whole team there for three days water wall coverage for our last big show of the year and I'm Stu minimun thank you for watching the Q

our Studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hello and welcome to the cube studios in Palo Alto California for another cube conversation where we go in-depth with thought leaders driving innovation across the tech industry I'm your host Peter Burris almost everybody's heard of the term black hat and white hat and it constitutes groups of individuals that are either attacking or defending security challenges it's been an arms race for the past 10 20 30 years as the world has become more digital and an arms race that many of us are concern that black hats appear to have the upper hand but there's new developments in technology and new classes of tooling that are actually racing to the aid of white hats and could very well upset that equilibrium in favor of the white hats to have that conversation about the Ascension of the white hats we're joined by Derek manky who's chief security insights and global threat alliances lead at Ford Annette dereck thanks for joining us for another cube conversation it's always a pleasure speaking yeah all right Derrick let's start what's going on afforda labs at four Dannette so 2019 we've seen a ton of development a lot pretty much on track with our predictions when we talked last year obviously a big increase in volume thanks offense of automation we're also seeing low volume attacks that are disrupting big business models I'm talking about targeted ransom attacks right you know criminals that are able to get into networks caused millions of dollars of damages thanks to critical revenue streams being out usually in the public sector we've seen a lot of this we've seen a rise in sophistication the adversary's are not slowing down AET s advanced evasion techniques are on the rise and so you know to do this and for the guard loves to be able to track this and map this we're not just relying on blogs anymore and you know 40 50 page white papers so we're actually looking at that playbooks now mapping the adversary's understanding their tools techniques procedures how they're operating why they're operating who are they hitting on and what what might be their next move so that's a big development on the intelligence sides here all right so I mentioned upfront this notion that the white hats may be ascending I'm implying a prediction here tell us a little bit about what we see on the horizon for that concept of the white hats ascending and specifically why is there reason to be optimistic yeah so as it's it's it's been gloomy for you for decades like he said and for many reasons right and I think those reasons there are no secrets I mean cyber criminals and black hats have always been able to move very you know with with agility right I'm sorry crime has no borders it's often a slap on the wrist that they get they can do a million things are on they don't care there's no ethics and quite frankly no no rules by right on the white hand side we've always had rules binding us we've had to we've had to take due care and we've had to move methodically which slows us down so a lot of that comes in place because of frameworks because of technology as well having to move um after it's in able to it with frameworks so specifically with you know making corrective action and things like that so those are the challenges that we face against but you know like thinking ahead to to 2020 particularly with the use of artificial intelligence everybody talks about AI you know it's it's impacted our daily lives but when it comes to cybersecurity on the white hat side um you know a proper AI and machine learning model it takes time you think it can take you years in fact in our case in our experience about four to five years before we can actually roll it out to production but the good news is that we have been investing and when I say we I'm just talking to the industry in general and wait we've been investing into this technology because quite frankly we've had to it takes a lot of data it takes a lot of smart minds a lot of investment a lot of processing power and that foundation has now been set over the last five years if we look at the blackcats it's not the case and why because they've been enjoying living off the land on a low-hanging truth path of least resistance because they've been able to so one of the things that's changing that equilibrium then is the availability of AI as you said it could take four or five years to get to a point we've actually got useful AI is it can have an impact I guess that means that we've been working on these things for four or five years what's the state of the art with AI as it pertains to security and are we seeing different phases of development start to emerge as we gain more experience with these technologies yeah absolutely and it's quite exciting right ai isn't this universal brain that's that's always good the world's problems that everyone thinks it might right it's very specific it relies on machine learning models each machine learning model is very specific to its task right I mean you know voice learning technology versus autonomous vehicle driving versus cybersecurity it's very different when it comes to the swimming purposes so so in essence the way I look at it you know there's three generations of AI we have generation 1 which was the past generation 2 which is a current where we are now and the generation 3 is where we're going so generation 1 was pretty simple right it was just a central processing lyrtle of machine learning model that'll take in data they'll correlate that data and then take action based off of it some simple inputs simple output right generation to where we're currently sitting is more advances looking at pattern recognition more advanced inputs are distributed models where we have the you know sensor is lying around networks I'm talking about even IOT devices security appliances and so forth but still report up to this centralized brain that's learning and acting on things but where things get really interesting moving forward in 2020 gets into this third generation where you have especially you know moving towards about computer sorry I'm computing where you have localized learning notes that are actually processing and learning so you can think of them as these mini brains instead of having this monolithic centralized brain you have individual learning modes individual brains doing their own machine learning that are actually connected to each other learning from each other speaking to each other it's a very powerful model we actually refer to this as federated machine learning in our industry so we've been first phase we simply use statistics to correlate events take action yeah now we're doing exceptions pattern recognition or exceptions and building patterns and in the future we're going to be able to further distribute at that so that increasingly the AI is going to work with other AI so that the aggregate this federated aggregate gets better I got that right yeah absolutely and what's the advantage of that a couple of things I'm it's very similar to the human immune system right I mean if you have you know if I were to cut my finger on my hand what's gonna happen well localized white blood cells get localized not nothing from a foreign entity or further away in my body are gonna come to the rescue and start healing right it's the same idea it's because it's interconnected within the nervous system it's the same idea of this federated machine learning right if security appliance is to detect a threat locally on-site its able to alert other security appliances so that they can actually take action on this and learn from that as well so connected machine learning models it means that that you know by properly implementing these these AI this federated AI machine learning models in an organization that that system is able to actually in an auto you may pick up what that threat is be able to act on that threat which means it's able to respond to these threats quicker shut them down to the point where it can be you know virtually instantaneous right before you know that the damage is done and bleeding starts happening so the common time safe common baseline is constantly getting better even as we're giving opportunities for local local managers to perform the work in response to local conditions so that takes us to the next notion of we've got this federated a la a I on the horizon how are people how is the role of people security professionals going to change what kind of recipes are they going to follow to ensure that they are working in a maximally productive way with these new capabilities these new federated capabilities especially as we think about the introduction of 5g and greater density of devices and faster speeds and lower latencies yeah so you know that the the the the world of cyber computer cyber security has always been incredibly complex so we're trying to simplify that and that's where again this this federated machine learning comes into place particularly with playbooks so you know if we look at 2019 and where we're going in 2020 we've put a lot of a lot of groundwork quite frankly into pioneering the work of playbooks right so when I say playbooks I'm talking about adversary's playbook knowing the offense knowing the tools techniques procedures the way that these cybercrime operations are moving right and the black hats are moving the more that we can understand that the more we can predict their next move and that centralized language right once you know that offense we can start to create automated Blue Team playbook so defensive play books that a human that that's a security technology can automatically integrate and respond to it but to getting back to your question we can actually create human readable sea cecil guides that can actually say look there's a threat here's why it's a problem here's here here are the gaps in your security that we've identified if you're some recommended course of action as my deity right so that's that's where the humans and the machines are really going to be worked working together and and quite frankly moving speed being able to do that a machine level but also being being able to simplify a complex landscape that is where we can actually gain traction right that this is part of that ascendancy of the white hat because because it's it's allowing us to move in a more agile nature it's an it's allowing us to gain ground against heat actors and quite frankly it allows us to start disrupting their business model right it's more resilient Network in the future this leads to the whole notion of self-healing networks as well that quite frankly just makes it a big pain it disrupts your business model it forces them to go back to the drawing board - well it also seems as though when we start talking about 5g that the speeds as I said the speeds the dentin see the reduced latency the the potential for a bad thing to propagate very quickly demands that we have a more consistent coherent response at both the Machine level but also at the people level we 5g into this conversation what's what will be the impact of 5g on how these playbooks and AI start to come together over the next few years yeah it's it's it's it's gonna be very impactful it's gonna take a couple of years and we're just at the dawn of 5g right now but if you think of 5g you're talking about a lot more volume essentially as we move to the future we're entering into the age of five G and edge computing and 5g and edge computing is gonna start eating the cloud in a sense that more of that processing power that was in the cloud is starting to shift now towards edge computing right this is that on-premises so it is gonna allow models like I was talking about federated machine learning models at first from the the white hats point of view which I again I think we are in the driver's seat and in a better you know more advantageous position here because we have more experience again like I said we've been doing this for years where the black hats quite frankly haven't yes they're toying with it but not to the same level at scale that we have but you know you know it's I'm always a realist this isn't a completely rosy picture I mean there it is optimistic that we are able to get this upper hand it has to be done right but if we think about the weaponization of 5g that's also very large problem right last year we're talking about sworn networks right the idea of sworn networks is a whole bunch of devices that can connect to each other share intelligence and then act to do something like a large-scale DDoS attack that's absolutely in the in the realm of possibility when it comes to the weaponization of 5g as well so one of the things I guess the last question I want to ask you is you noted that these play books incorporate the human element in ways that are uniquely human so having C so readable recipes for how people have to respond does that also elevate the conversation with the business and does allows us to do a better job of understanding risk pricing risk and appropriately investing to manage and assure the business against risk in the right way absolutely absolutely it does yeah yeah because the more you know about going back to the playbook some more you know about the office and their tools you know you the more you know about how much of a danger it is what sort of targets they're after right I mean if they're just going trying to look to to to collect a little bit of information on you know to do some reconnaissance that first phase attack might not cause a lot of damage but if this group is knowing to go in hit hard steal intellectual property shut down critical business streams to do s that in the past we know and we've seen has caused four or five million dollars from one you know from one breach that's a very good way to start classifying risk so yeah I mean it's all about really understanding the picture first on the offense and that's exactly what these automated playbook guides are going to be doing on the on the on the blue team and again not only from a CSE suite perspective certainly that on the human level but the nice thing about the play books is because we've done the research the threat hunting and understood this you know from a machine level it's also able to put a lot of those automated let's say day-to-day decisions making security operation center is so I'm talking about like sect DevOps much more efficient to so he's talking about more density at the edge amongst these devices I also want to bring back one last thought here and that is you said that historically some of the black hats have been able to act with a degree of impunity they haven't necessarily been hit hard there a lot of slapping on the wrist as I think you said talk about how the playbooks and AI is going to allow them to more appropriately share data with others that can help both now but also in some of the forensics and the the enforcement side namely the the legal and policing world how are we going to share the responsibility or how is that going to change over the next few years to incorporate some of the folks that actually can then turn a defense into a legal attack illumination this is what I call it right so again if we look at the current state we've made great strides great progress you know working with law enforcement so we've set up public private sector relationships we need to do that have security experts working with law enforcement law enforcement working on there and to train process prosecutors to understand cybercrime and so forth that foundation has been set but it's still slow-moving you know there's only a limited amount of playbooks right now it takes a lot of work to unearth and and and do to really move the needle what we need to do again like we're talking about is to integrate artificial intelligence with playbooks the more that we understand about groups the more that we do this threat illumination the more we have cover about them the more we know about them and by doing that we can start to form predictive models right basically I always say old habits die hard so you know if an attacker goes in hits a network and they're successful following a certain sequence of patterns they're likely going to follow that say that's that same sequence on their next victim or their next target so the more that we understand about that the more that we can forecast eight from a mitigation standpoint but the also by the same token the more correlation we're doing on these playbooks the more machine learning we're doing on this playbooks the more we were able to do attribution and attribution is the Holy Grail it's always been the toughest thing to do when it comes to research but by combining the framework that we're using with playbooks and AI machine learning it's a very very powerful recipe and that's that's what we need to get right and move forward in the right direction Derrick McKey ordinance chief of security insights and threat alliances thanks again for being on the cube it's a pleasure anytime happy to talk and I want to thank you for joining us for another cube conversation I'm Peter Burris see you next time [Music]

our Studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hello and welcome to the cube studios in Palo Alto California for another cube conversation where we go in-depth with thought leaders driving innovation across the tech industry I'm your host Peter Burris almost everybody's heard of the term black hat and white hat and it constitutes groups of individuals that are either attacking or defending security challenges it's been an arms race for the past 10 20 30 years as the world has become more digital and an arms race that many of us are concern that black hats appear to have the upper hand but there's new developments in technology and new classes of tooling that are actually racing to the aid of white hats and could very well upset that equilibrium in favor of the white hats to have that conversation about the Ascension of the white hats we're joined by Derek manky who's chief security insights and global threat alliances lead at Ford Annette dereck thanks for joining us for another cube conversation it's always a pleasure speaking yeah all right Derrick let's start what's going on afforda labs at four Dannette so 2019 we've seen a ton of development a lot pretty much on track with our predictions when we talked last year obviously a big increase in volume thanks offense of automation we're also seeing low volume attacks that are disrupting big business models I'm talking about targeted ransom attacks right you know criminals that are able to get into networks caused millions of dollars of damages thanks to critical revenue streams being out usually in the public sector we've seen a lot of this we've seen a rise in sophistication the adversary's are not slowing down AET s advanced evasion techniques are on the rise and so you know to do this and for the guard loves to be able to track this and map this we're not just relying on blogs anymore and you know 40 50 page white papers so we're actually looking at that playbooks now mapping the adversary's understanding their tools techniques procedures how they're operating why they're operating who are they hitting on and what what might be their next move so that's a big development on the intelligence sides here all right so I mentioned upfront this notion that the white hats may be ascending I'm implying a prediction here tell us a little bit about what we see on the horizon for that concept of the white hats ascending and specifically why is there reason to be optimistic yeah so as it's it's it's been gloomy for you for decades like he said and for many reasons right and I think those reasons there are no secrets I mean cyber criminals and black hats have always been able to move very you know with with agility right I'm sorry crime has no borders it's often a slap on the wrist that they get they can do a million things are on they don't care there's no ethics and quite frankly no no rules by right on the white hand side we've always had rules binding us we've had to we've had to take due care and we've had to move methodically which slows us down so a lot of that comes in place because of frameworks because of technology as well having to move um after it's in able to it with frameworks so specifically with you know making corrective action and things like that so those are the challenges that we face against but you know like thinking ahead to to 2020 particularly with the use of artificial intelligence everybody talks about AI you know it's it's impacted our daily lives but when it comes to cybersecurity on the white hat side um you know a proper AI and machine learning model it takes time you think it can take you years in fact in our case in our experience about four to five years before we can actually roll it out to production but the good news is that we have been investing and when I say we I'm just talking to the industry in general and wait we've been investing into this technology because quite frankly we've had to it takes a lot of data it takes a lot of smart minds a lot of investment a lot of processing power and that foundation has now been set over the last five years if we look at the blackcats it's not the case and why because they've been enjoying living off the land on a low-hanging truth path of least resistance because they've been able to so one of the things that's changing that equilibrium then is the availability of AI as you said it could take four or five years to get to a point we've actually got useful AI is it can have an impact I guess that means that we've been working on these things for four or five years what's the state of the art with AI as it pertains to security and are we seeing different phases of development start to emerge as we gain more experience with these technologies yeah absolutely and it's quite exciting right ai isn't this universal brain that's that's always good the world's problems that everyone thinks it might right it's very specific it relies on machine learning models each machine learning model is very specific to its task right I mean you know voice learning technology versus autonomous vehicle driving versus cybersecurity it's very different when it comes to the swimming purposes so so in essence the way I look at it you know there's three generations of AI we have generation 1 which was the past generation 2 which is a current where we are now and the generation 3 is where we're going so generation 1 was pretty simple right it was just a central processing lyrtle of machine learning model that'll take in data they'll correlate that data and then take action based off of it some simple inputs simple output right generation to where we're currently sitting is more advances looking at pattern recognition more advanced inputs are distributed models where we have the you know sensor is lying around networks I'm talking about even IOT devices security appliances and so forth but still report up to this centralized brain that's learning and acting on things but where things get really interesting moving forward in 2020 gets into this third generation where you have especially you know moving towards about computer sorry I'm computing where you have localized learning notes that are actually processing and learning so you can think of them as these mini brains instead of having this monolithic centralized brain you have individual learning modes individual brains doing their own machine learning that are actually connected to each other learning from each other speaking to each other it's a very powerful model we actually refer to this as federated machine learning in our industry so we've been first phase we simply use statistics to correlate events take action yeah now we're doing exceptions pattern recognition or exceptions and building patterns and in the future we're going to be able to further distribute at that so that increasingly the AI is going to work with other AI so that the aggregate this federated aggregate gets better I got that right yeah absolutely and what's the advantage of that a couple of things I'm it's very similar to the human immune system right I mean if you have you know if I were to cut my finger on my hand what's gonna happen well localized white blood cells get localized not nothing from a foreign entity or further away in my body are gonna come to the rescue and start healing right it's the same idea it's because it's interconnected within the nervous system it's the same idea of this federated machine learning right if security appliance is to detect a threat locally on-site its able to alert other security appliances so that they can actually take action on this and learn from that as well so connected machine learning models it means that that you know by properly implementing these these AI this federated AI machine learning models in an organization that that system is able to actually in an auto you may pick up what that threat is be able to act on that threat which means it's able to respond to these threats quicker shut them down to the point where it can be you know virtually instantaneous right before you know that the damage is done and bleeding starts happening so the common time safe common baseline is constantly getting better even as we're giving opportunities for local local managers to perform the work in response to local conditions so that takes us to the next notion of we've got this federated a la a I on the horizon how are people how is the role of people security professionals going to change what kind of recipes are they going to follow to ensure that they are working in a maximally productive way with these new capabilities these new federated capabilities especially as we think about the introduction of 5g and greater density of devices and faster speeds and lower latencies yeah so you know that the the the the world of cyber computer cyber security has always been incredibly complex so we're trying to simplify that and that's where again this this federated machine learning comes into place particularly with playbooks so you know if we look at 2019 and where we're going in 2020 we've put a lot of a lot of groundwork quite frankly into pioneering the work of playbooks right so when I say playbooks I'm talking about adversary's playbook knowing the offense knowing the tools techniques procedures the way that these cybercrime operations are moving right and the black hats are moving the more that we can understand that the more we can predict their next move and that centralized language right once you know that offense we can start to create automated Blue Team playbook so defensive play books that a human that that's a security technology can automatically integrate and respond to it but to getting back to your question we can actually create human readable sea cecil guides that can actually say look there's a threat here's why it's a problem here's here here are the gaps in your security that we've identified if you're some recommended course of action as my deity right so that's that's where the humans and the machines are really going to be worked working together and and quite frankly moving speed being able to do that a machine level but also being being able to simplify a complex landscape that is where we can actually gain traction right that this is part of that ascendancy of the white hat because because it's it's allowing us to move in a more agile nature it's an it's allowing us to gain ground against heat actors and quite frankly it allows us to start disrupting their business model right it's more resilient Network in the future this leads to the whole notion of self-healing networks as well that quite frankly just makes it a big pain it disrupts your business model it forces them to go back to the drawing board - well it also seems as though when we start talking about 5g that the speeds as I said the speeds the dentin see the reduced latency the the potential for a bad thing to propagate very quickly demands that we have a more consistent coherent response at both the Machine level but also at the people level we 5g into this conversation what's what will be the impact of 5g on how these playbooks and AI start to come together over the next few years yeah it's it's it's it's gonna be very impactful it's gonna take a couple of years and we're just at the dawn of 5g right now but if you think of 5g you're talking about a lot more volume essentially as we move to the future we're entering into the age of five G and edge computing and 5g and edge computing is gonna start eating the cloud in a sense that more of that processing power that was in the cloud is starting to shift now towards edge computing right this is that on-premises so it is gonna allow models like I was talking about federated machine learning models at first from the the white hats point of view which I again I think we are in the driver's seat and in a better you know more advantageous position here because we have more experience again like I said we've been doing this for years where the black hats quite frankly haven't yes they're toying with it but not to the same level at scale that we have but you know you know it's I'm always a realist this isn't a completely rosy picture I mean there it is optimistic that we are able to get this upper hand it has to be done right but if we think about the weaponization of 5g that's also very large problem right last year we're talking about sworn networks right the idea of sworn networks is a whole bunch of devices that can connect to each other share intelligence and then act to do something like a large-scale DDoS attack that's absolutely in the in the realm of possibility when it comes to the weaponization of 5g as well so one of the things I guess the last question I want to ask you is you noted that these play books incorporate the human element in ways that are uniquely human so having C so readable recipes for how people have to respond does that also elevate the conversation with the business and does allows us to do a better job of understanding risk pricing risk and appropriately investing to manage and assure the business against risk in the right way absolutely absolutely it does yeah yeah because the more you know about going back to the playbook some more you know about the office and their tools you know you the more you know about how much of a danger it is what sort of targets they're after right I mean if they're just going trying to look to to to collect a little bit of information on you know to do some reconnaissance that first phase attack might not cause a lot of damage but if this group is knowing to go in hit hard steal intellectual property shut down critical business streams to do s that in the past we know and we've seen has caused four or five million dollars from one you know from one breach that's a very good way to start classifying risk so yeah I mean it's all about really understanding the picture first on the offense and that's exactly what these automated playbook guides are going to be doing on the on the on the blue team and again not only from a CSE suite perspective certainly that on the human level but the nice thing about the play books is because we've done the research the threat hunting and understood this you know from a machine level it's also able to put a lot of those automated let's say day-to-day decisions making security operation center is so I'm talking about like sect DevOps much more efficient to so he's talking about more density at the edge amongst these devices I also want to bring back one last thought here and that is you said that historically some of the black hats have been able to act with a degree of impunity they haven't necessarily been hit hard there a lot of slapping on the wrist as I think you said talk about how the playbooks and AI is going to allow them to more appropriately share data with others that can help both now but also in some of the forensics and the the enforcement side namely the the legal and policing world how are we going to share the responsibility or how is that going to change over the next few years to incorporate some of the folks that actually can then turn a defense into a legal attack illumination this is what I call it right so again if we look at the current state we've made great strides great progress you know working with law enforcement so we've set up public private sector relationships we need to do that have security experts working with law enforcement law enforcement working on there and to train process prosecutors to understand cybercrime and so forth that foundation has been set but it's still slow-moving you know there's only a limited amount of playbooks right now it takes a lot of work to unearth and and and do to really move the needle what we need to do again like we're talking about is to integrate artificial intelligence with playbooks the more that we understand about groups the more that we do this threat illumination the more we have cover about them the more we know about them and by doing that we can start to form predictive models right basically I always say old habits die hard so you know if an attacker goes in hits a network and they're successful following a certain sequence of patterns they're likely going to follow that say that's that same sequence on their next victim or their next target so the more that we understand about that the more that we can forecast eight from a mitigation standpoint but the also by the same token the more correlation we're doing on these playbooks the more machine learning we're doing on this playbooks the more we were able to do attribution and attribution is the Holy Grail it's always been the toughest thing to do when it comes to research but by combining the framework that we're using with playbooks and AI machine learning it's a very very powerful recipe and that's that's what we need to get right and move forward in the right direction Derrick McKey ordinance chief of security insights and threat alliances thanks again for being on the cube it's a pleasure anytime happy to talk and I want to thank you for joining us for another cube conversation I'm Peter Burris see you next time [Music]

(upbeat music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. >> Hello and welcome to the CUBE studio in Palo Alto, California for another CUBE Conversation. Where we go in-depth with thought leaders driving innovation across the tech industry. I'm your host, Peter Burris. Every business wants Cloud, every business wants digital transformation, but the challenge is, what do you do with the data? How do you ensure that your data is set up so that you can take greater advantage of it, create more classes of business options in a digital world, while at the same time having the flexibility, the agility that you need from a storage and infrastructure standpoint to not constrain the business as it tries to move forward. It's a big topic that a lot of customers are facing. To have that conversation, we are joined by Matt Kixmoeller, who is the Vice President of Strategy at Pure Storage. Matt, welcome back to the CUBE. >> Thanks, Peter. >> So lets dispense with the necessaries. Update from Pure. >> It's a fun time at Pure, we just hit our tenth birthday, and we're fresh off the heels of our Accelerate Conference down in Austin, where we had a lot of good product news and talked a lot about what the next decade's going to be all about. >> So, one of the things you mentioned down in Austin was the notion of the modern data experience. I want to really highlight that notion of experience because that's kind of the intersection with the Cloud experience. So, talk a little bit about how the experience word in modern data and cloud is coming together. >> Absolutely, so ya know the Cloud has forever changed IT's expectation of how tech needs to work, and I think the most archaic layer in a lot of ways right now is storage, and so we've done a lot within our platform to modernize for Cloud, link to the Cloud, deliver an all flash experience, but more interesting perhaps is also just reacting to the changing nature of how customers want to use storage and procure storage. >> And that means that they don't want to buy in advance of their needs. >> I think the key thing is as a service on demand right? And, ya know it's interesting when you consider both the usage and consumption as well as the purchase pattern, right? Um, if you think about the usage and consumption, it's all about on demand and automation, and perhaps one of the best examples I can give you is the transformation around containers. Um, ya know, we see all of our call home data from our customers, and how they use the arrays obviously, and your typical array has just a handful of management operations per day, where someone changes something, provision, storage, you name it. If you look at our container environment, ya know we have a tool called PSO, Pure Service Orchestrator that orchestrates our storage as part of a container environment, and a PSO based array does thousands of these operations a day. And so, it's very obvious that if you're having to deal with the fluidity of the container Cloud, there's no way you're going to have a human admin sitting there, clicking yes, yes, yes, or doing anything like that type of provision storage. You have to plumb for automation from the beginning. >> So that's a great example of the experience necessarily must be different, where you can't use a manual approach of doing things, you have to use more of an automated approach, so as you start to consider these issues, how is that informing the evolution of the modern data experience at Pure? >> I think it's an automated first world, and you have to really prepare yourself for plumbing everything for automation for APIs, for orchestration, as opposed to thinking about processes manually. Um, we've also seen as a vendor, it's changed how people want to consume, and you know, the concepts of more Opex-based on-demand consumption are also coming to storage, and so, last year, we introduced, um, ya know one of the first models in the industry in this regard that we called, at the time, ES2, and we broadened that and launched it again this year at Accelerate, expanding it to the entire Pure Business, and called it Pure as a service. >> So, what we now have is we now have, at least, from Pure, the option to think about how I'm going to match my storage consumption with my storage spend, which is especially important in a world where, by some aspect, storage or data is growing in volumes, from a volume perspective, at 35, 40% per anum. You don't want to have to buy four years of data out because you're growing that fast, and use it today. So as you think about this, what does Pure do next with the marriage of the Cloud experience and the modern date experience? >> Well, I think a key thing, particularly around this consumption world, is to give people flexibility between On-Prem and Cloud. Ya know, we did a lot in the show to announce news around how we're linking our On-Prem offerings with the Cloud with our Cloud Block Store offering to allow workloads to move back and forth, but what if I own On-Prem storage and I want to use the Cloud. And so another thing we did as part of Pure as a service is allow for that subscription to go either direction. You might be a customer that subscribes to 100 terabytes of Pure On-Prem, and then tomorrow you get the edict that says lets move half that to the Cloud. No problem, you can move 50 terabytes to the Cloud and not pay us another dime. The next day, you want to move back. You can do that again as well, and so we've thought about how we can really evolve those procurement processes such that they are just as agile and just as flexible as a Cloud model. >> Matt Kixmoeller, Pure Storage, thanks again for being on the CUBE. >> Thank you, Peter. >> And thank you for joining us for another CUBE conversation. I'm Peter Burris. See you next time. (upbeat music)

(funky music) >> Announcer: From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE Conversation. >> Hello, and welcome to theCUBE Studios in Palo Alto, California for another CUBE Conversation, where we go in depth with thought leaders driving innovation across the tech industry. I'm your host, Donald Klein. Today, we're here to talk about digital transformation, and the challenges many enterprises face in helping employees adopt the new applications that drive their business. To have that conversation, we're joined by Vara Kumar, CTO and co-founder of Whatfix . Vara, welcome to the show. >> Thanks, thanks Don for inviting me to the show. >> Great, so looking forward to this. Tell us a little bit about Whatfix, what you guys do and a little bit of the history here. >> Sure. Whatfix is a digital adoption platform. So essentially it overlays on top of applications and makes employees to use applications faster and better. So, we are five years old company, so we have offices in four different countries, and we have 500 customers, and 60 Fortune 500 users, including companies like Amazon, UPS, Facebook, Microsoft, Western Union, Western Digital. The users are a variety of applications like CRMs, VRPs, SCMs. >> Great, fantastic customer base, that's really good. So when you say you're a digital adoption platform that kind of provides an overlay, what specifically you're talking about? You're talking about notifications inside of an application? Tell us a little more about that. >> Sure, sure. So Whatfix helps employees through all their journey in their applications. As they onboard to the applications for the first time, Whatfix welcomes them and holds them to the application. So we provide these, what we call as flows, so these are step-by-step guidance to the users for using the applications and processes and not only within the application, Whatfix guides the users across applications that the employee is faced with, so for example-- >> So cross-application workflows, that kind of thing. >> That's correct, that's correct. For example Anaconda executive, so they have to manage opportunities in the CRM, and then to create a code they have to go to the CPQ and then to submit a purchase order, probably they will have to go to a digital workplace to maintain the code and proceed to the contract. So Whatfix can guide the users through all this and that process. >> Great, so it's not just about the challenges of learning about one particular application, it's actually learning an entire workflow that might stretch across multiple applications. >> That's accurate. >> Some sort of end to end process that gets very complex because you're moving from one interface to the next. >> That's accurate, that's accurate. >> And I guess another challenge would be that, many, in a large enterprise, right, many of the applications that come from the well-known vendors get highly customized for that particular business environment is that correct? >> That's completely true Don, so, Salesforce instance of UPS looks very different from Salesforce instance of Western Union because it's completely customized to the organization business workflows and the nature of their business. So this customization also brings in lot more adoption challenges because even though I'm an account executive who has seen Salesforce in my past experience it looks very different from my current job. So that's more challenging for the enterprises to train their employees and make them use. >> Great, understood, okay, very good. So the problem that you guys are really trying to solve is around this challenge of getting employees to adopt the new applications as part of their overall digital transformation journey, is that right? >> That's true, it's not only new applications now with the so much of cloud movement. So the applications are actually getting updated more faster as you must have heard so much about as well being used in the enterprises for the IT rollouts and IT deployments. That means changes are constant so because you are reinventing your business process as you're learning. So now employees, actually, it impacts more the employee experience because every update employees have to be on top of those. So Whatfix can help them with these updates and making sure that employees are self-served. >> Understood, okay, very good. So now, this has become really such a widespread problem across many of these large enterprises that it's now become quite a mature category of software solutions, is that right? >> That's accurate, Gartner called this category as digital adoption solutions, DAS. >> Digital adoption solutions, okay DAS. >> That's correct, and then they coined this term only a quarter back, and they published reports, in terms of seller productivity and how it will influence the digital workplace, and such kind of things. >> Great, okay, great. So this category now is becoming more widespread, and people really see these types of solutions as being key to enabling digital transformation in the enterprise, right? >> That's accurate. >> Okay great, so then what are the trends that are driving this problem, what is it that's making this such a problem area that companies really need to focus on dedicated solutions to solving? >> Yeah, so one primary is the cloud migration. Yes, more and more the companies, wants to move to the cloud, for example you no longer hear CRM being on-prem, so people are using all the cloud CRMs. So the migration to the cloud, and then the digital, overall the digital transformation of these business practices to suit this cloud migration, that'll also, it's all putting pressure on employee experience. So impacting and making sure that employees are getting used to these new applications and the constant rollouts. >> Got it, got it, okay. So with all this happening, right, more and more applications moving to the cloud, the applications themselves are evolving much faster, the interfaces are changing, and then moreover they're getting more complex, because they're getting more interconnected, right? And so you have this step by step kind of work flow that helps people navigate all of these integrated applications to actually perform a single workflow. >> That's accurate, that's accurate and at the same time given that Whatfix is on top of these applications we are learning a lot about the user, this particular user and what they are doing, what they are good at, what they're not good at, this is helping us to make our content more personalized to the users, just like Google, you search for the same keyword, I search for the same thing, we both see different results. Because it's personalizing to our taste and our knowledge and expertise. So that's exactly it's getting into. And it's not only guidance, we are also helping users to be more productive by automating certain steps. Let's say you do a certain activity every day, then Whatfix can do that automatically for you so that you're becoming more and more faster in your job. >> Interesting, that's interesting. So it's not only helping provide guidance for people moving through these applications but it's actually collecting data about how users are interfacing with it, right, and then delivering a more kind of personalized experience in terms of the guidance that it offers. >> Accurate, accurate, that's accurate. >> Great, so that's really kind of, I guess that would really be the main kind of area of innovation I would imagine for a system like this, right, the ability to capture data about how users are interfacing with the application and then provide recommendations on how to do it better. >> Yes, that's definitely one of the area there's several reasons why customers choose us. We believe in the concept called adoption everywhere, so that adoption everywhere, that means employee need not be on the application all the time, they may want to interact with the application when they're outside of the application. So be, maybe you're on the wiki, you're looking for something then you wanted interface with application, so Whatfix is present across all touchpoints wherever the employee may decide and guide them to the application and help them use the application. And second, we are very easy to deploy and maintain, so we invested heavily on this, because we realize that we don't have to, we shouldn't be providing a platform which is technically more complex for the business guys to create these kind of process flows, we kept them very low tech, and our authoring environment is very easy for them to use and maintain. And then we are, we are very open in terms of how our API is just like Salesforce, which is very open in terms of integrations because we do understand that enterprises are, wants more of interconnected applications so, our allowed APIs are open and we work well with the enterprise ecosystem. And our customer success is highly regarded, so we are best among in the software vendors in terms of the highest customer satisfaction. And we care a lot about real user privacy and security so we don't really collect PII information for the recommendations and personalizations as I spoke about. >> Okay, very good. And so then the, tell us a little bit more about which kind of applications are you guys finding, which categories of applications really kind of benefit most from this kind of guided, walkthrough capability? >> Sure, so the applications are widespread so but more commonly people use us on CRMs, ERPs, and SCMs, and digital workplaces. These are the kind of applications where customers commonly use us on. >> Okay, so ERP and CRM would be the kind of core, would you say? >> Yeah, CRM, ERP and SCM. So these will be the core I would say. And, it's not only the applications that the customers are purchasing from outside, but Whatfix can work on any application that is internally built, any applications that are their IT team is customizing, Whatfix can work on those. >> Great so, bespoke applications developed internally inside companies are equally suitable for this, as are the the packaged applications they might be customizing for their business processes. >> That's correct. >> Okay, that's great. So I just, on the kind of conclude here, let's talk a little bit about maybe some of the customer success stories, that you guys have had. And I'm not asking you to necessarily name names, but maybe talk about some of the areas where you've seen some real value creation from implementing a system like this. >> Sure, sure, our customers have seen that our onboarding time of employees into the applications have reduced one third, because of using Whatfix, because now employees are learning in the flow of work, you no longer have to train them to use the applications, and we've also seen that organizations telling that their content creation times and their amount of planning preparation time has reduced 85%, because of our easy to use authoring environment, and easy to maintain authoring environment. And we've also seen organizations have reduced internal support tickets by 60%. Yeah, so we have also seen that the overall productivity of the employees increased by 35% because they're able to find things and be able to self serve, and do more faster in the applications. >> Got it, so the old days of sitting down and sort of expecting the employees to read the user manual page by page, right, before they dive in, is kind of gone now right? >> It's gone. >> What people want to see is they want to get into the application and then they want to be able to be guided through what they need to do to solve their particular problem. And they want it done in real time. >> That's true, that's right Don. >> And even better they have that whole guide through maybe customized to their particular problem. >> That's accurate Don, that's the digital option solutions for you. >> Great, well that sounds like a fantastic solution, understand the role it plays fantastic, I think you guys are doing great work. So, want to maybe just kind of touch on this last point, where do you see this kind of industry going in the future? This is fantastic innovation but how do you see this trending as digital transformation becomes more widespread? >> Yeah, sure. So adoption as the problem statement more and more organizations understand, and more and more software vendors understand today, we are at Dreamforce now, so if you see the number of sessions around adoption is phenomenal. So, when the Gartner called out that only six to 7% of our enterprises have adopted to the solutions like Whatfix, so there has to be more awareness, some people, enterprises understand that adoption is a problem, but they are not aware that there are solutions that exist to tackle that problem. So we see that's going to be the future for us as we go forward, having more and more enterprises adopt these kind of solutions. >> Great, okay, well if you happen to be at Dreamforce, folks, stop by and talk to Whatfix. So, Vara Kumar thank you for coming on TheCUBE. So thanks for joining us for another CUBE Conversation, I'm Donald Klein and we'll see you next time. (funky music)

(upbeat jazz music) [Woman] - From our Studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello and welcome to theCUBE Studios in Palo Alto, California, for another CUBE conversation, where we go in depth with thought leaders driving innovation across tech industry. I'm your host Peter Burris. Almost everybody's heard of the term black-hat and white-hat. And it constitutes groups of individuals that are either attacking or defending security challenges. It's been an arms race for the past 10, 20, 30 years as the worlds become more digital. And an arms race that many of us are concerned that black-hats appear to have the upper hand. But there's new developments in technology and new classes of tooling that are actually racing to the aid of white-hats and could very well upset that equilibrium in favor of the white-hats. To have that conversation about the ascension of the white-hats, we're joined by Derek Manky, who's the Chief Security Insights & Global Threat Alliances lead at Fortinet. Derek, thanks for joining us for another CUBE conversation. >> It's always a pleasure speaking with you. [Peter] - All right. [Derek] - Happy to be here. >> Derek, let's start, what's going on at FortiLabs at Fortinet? >> So 2019, we've seen a ton of development, a lot pretty much on track with our predictions when we talked last year. Obviously a big increase in volume, thanks to offensive automation. We're also seeing low volume attacks that are disrupting big business models. I'm talking about targeted ransom attacks, right. But, you know, criminals that are able to get into networks, cause millions of dollars of damages thanks to critical revenue streams being held. Usually in the public sector we've seen a lot of this. We've seen a rise in sophistication's, the adversaries are not slowing down. AET's, the mass evasion techniques are on the rise. And so, you know, to do this on FortiGaurd Labs, to be able to track this and map this, we're not just relying on logs anymore and, you know, 40, 50 page white papers. So, we're actually looking at that playbooks now, mapping the adversaries, understanding their tools, techniques, procedures, how they're operating, why they're operating, who are they hitting and what might be their next moves. So that's a bit development on the intelligence side too. >> All right, so imagine a front this notion that the white-hats might be ascending. I'm implying a prediction here. Tell us a little bit about what we see on the horizon for that concept of the white-hats ascending and specifically, why is a reason to be optimistic? >> Yeah, so it's been gloomy for decades like you said. And for many reasons, right, and I think those reasons are no secrets. I mean, cyber criminals and black-hats have always been able to move very, you know, with agility right. Cyber crime has no borders. It's often a slap on the wrist that they get. They can do a million things wrong, they don't care, there's no ethics and quite frankly no rules binding them right. On the white-hand side, we've always had rules binding us, we've had to take due care and we've had to move methodically, which slows us down. So, a lot of that comes in place because of frameworks, because of technology as well, having to move after it's enabled to with frameworks, specifically with making corrective action and things like that. So, those are the challenges that we faced against. But you know like, thinking ahead to 2020, particularly with the use of artificial intelligence, everybody talks about AI, it's impacted our daily lives, but when it comes to cyber security, on the white-hat side a proctor AI and machine learning model takes times. It can take years. In fact in our case, our experience, about four to five years before we can actually roll it out to production. But the good news is, that we have been investing, and when I say we, I'm just talking to the industry in general and white-hat, we've been investing into this technology because quite frankly we've had to. It takes a lot of data, it takes a lot of smart minds, a lot of investment, a lot of processing power and that foundation has now been set over the last five years. If we look at the black-hats, it's not the case. And why? Because they've been enjoying living off the land on low hanging fruit. Path of least resistance because they have been able to. >> So, what are the things that's changing that, equilibrium then, is the availability of AI and as you said, it could take four, five years to get to a point where we've actually got useful AI that can have an impact. I guess that means that we've been working on these things for four, five years. What's the state of the art with AI as it pertains to security, and are we seeing different phases of development start to emerge as we gain more experience with these technologies? >> Yeah, absolutely. And it's quite exciting right. AI isn't this universal brain that solves the worlds problems that everyone thinks it might be right. It's very specific, it relies on machine learning models. Each machine learning model is very specific to it's task right, I mean, you know, voice learning technology versus autonomous vehicle jobbing versus cyber security, is very different when it comes to these learning purposes. So, in essence the way I look at it, you know, there's three generations of AI. We have generation one, which was the past. Generation two, which is the current, where we are now and the generation three is where we're going. So, generation one was pretty simple right. It was just a central processing alert machine learning model that will take in data, correlate that data and then take action based off of it. Some simple inputs, simple output right. Generation two where we're currently sitting is more advanced. It's looking at pattern recognition, more advanced inputs, distributed models where we have sensors lying around networks. I'm talking about even IoT devices, security appliances and so forth, that still record up to this centralized brain that's learning it and acting on things. But where things get really interesting moving forward in 2020 gets into this third generation where you have especially moving towards cloud computer, sorry, edge computing, is where you have localized learning nodes that are actually processing and learning. So you can think of them as these mini brains. Instead of having this monolithic centralized brain, you have individual learner nodes, individual brains doing their own machine learning that are actually connected to each other, learning from each other, speaking to each other. It's a very powerful model. We actually refer to this as federated machine learning in our industry. >> So we've been, first phase we simply used statistics to correlate events, take action, now we're doing acceptions, pattern recognition, or acceptions and building patterns, and in the future we're going to be able to further distribute that so that increasingly the AI is going to work with other AI so that the aggregate, this federated aggregate gets better, have I got that right? >> Yeah absolutely. And what's the advantage of that? A couple of things. It's very similar to the human immune system right. If you have, if I were to cut my finger on my hand, what's going to happen? Well, localized white blood cells, localized, nothing from a foreign entity or further away in my body, are going to come to the rescue and start healing that right. It's the same, it's because it's interconnected within the nervous system. It's the same idea of this federated machine learning model right. If a security appliance is to detect a threat locally on site, it's able to alert other security appliances so that they can actually take action on this and learn from that as well. So connected machine learning models. So it means that by properly implementing these AI, this federated AI machine earning models in an organization, that that system is able to actually in a auto-immune way be able to pick up what that threat is and be able to act on that threat, which means it's able to respond to these threat quicker or shut them down to the point where it can be you know, virtually instantaneous right, before the damage is done and bleeding starts happening. >> So the common baseline is continuously getting better even as we're giving opportunities for local managers to perform the work in response to local conditions. So that takes us to the next notion of, we've got this federated AI on the horizon, how are people, how is the world of people, security professionals going to change? What kind of recipes are they going to follow to insure that they are working in a maximally productive way with these new capabilities, these new federated capabilities, especially as we think about the introduction of 5G and greater density of devices and faster speeds in the relatancies? >> Yeah so, you know the world of cyber computer, cyber security has always been incredibly complex. So we're trying to simplify that and that's where again, this federated machine learning comes into place, particularly with playbooks, so if we look at 2019 and where we're going in 2020, we've put a lot of groundwork quite frankly and so pioneering the work of playbooks right. So when I say playbooks I'm talking about adversary playbooks, knowing the offense, knowing the tools, techniques, procedures, the way that these cyber crime operations are moving right and the black-hats are moving. The more that we can understand that, the more we can predict their next move and that centralized language right, once you know that offense, we can start to create automated blue team playbooks, so defensive playbooks. That security technology can automatically integrate and respond to it, but getting back to you question, we can actually create human readable CECO guides that can actually say, "Look, there's a threat," "here's why it's a problem," "here are the gaps in your security that we've identified," "here's some recommended course of action as an idea too." Right, so that's where the humans and the machines are really going to be working together and quite frankly moving at speed, being able to that at machine level but also being able to simplify a complex landscape, that is where we can actually gain traction right. This is part of that ascendancy of the white-hat because it's allowing us to move in a more agile nature, it's allowing us to gain ground against the attackers and quite frankly, it allows us to start disrupting their business model more right. It's a more resilient network. In the future this leads to the whole notion of self-healing that works as well that quite frankly just makes it a big pain, it disrupts your business model, it forces them to go back to the drawing board too. >> Well, it also seems as though, when we start talking about 5G, that the speeds, as I said the speeds, the dentancy, the reduced latency, the potential for a bad thing to propagate very quickly, demands that we have a more consistent, coherent response, at both the the machine level but also the people level. We 5G into this conversation. What's, what will be the impact to 5G on how these playbooks and AI start to come together over the next few years? >> Yeah, it's going to be very impactful. It is going to take a couple of years and we're just at the dawn of 5G right now. But if you think of 5G, your talking about a lot more volume, essentially as we move to the future, we're entering into the age of 5G and edge computing. And 5G and edge computing is going to start eating the cloud in a sense that more of that processing power that was in the cloud is starting to shift now towards edge computing right. This is at on Premis.it So, A; it is going to allow models like I was talking about, federated machine learning models and from the white-hats point of view, which again I think we are in the driver seat and a better, more advantageous position here, because we are more experienced again like I said, we've been doing this for years with black-hats quite frankly haven't. Yes, they're toying with it, but not in the same level and skill as we have. But, you know, (chuckles) I'm always a realist. This isn't a completely realsy picture, I mean, it is optimistic that we are able to get this upper hand. It has to be done right. But if we think about the weaponisation of 5G, that's also a very large problem right. Last year we're talking about swarm networks right, the idea of swarm networks is a whole bunch of devices that can connect to each other, share intelligence and then act to do something like a large scale DDoS attack. That's absolutely in the realm of possibility when it comes to the weaponisation of 5G as well. >> So one of the things, I guess the last question I want to ask you is, is you noted that these playbooks incorporate the human element in ways that are uniquely human. So, having CECO readable recipes for how people have to respond, does that also elevate the conversation with the business and does, allows us to do a better job of understanding risk, pricing risk and appropriately investing to manage and assure the business against risk in the right way? >> Absolutely. Absolutely it does, yeah. Yeah, because the more you know about going back to the playbooks, the more you know about the offense and their tools, the more you know about how much of a danger it is, what sort of targets they're after right. I mean if they're just going trying to look to collect a bit of information on, you know, to do some reconnaissance, that first phase attack might not cause a lot of damage, but if this group is known to go in, hit hard, steal intellectual property, shut down critical business streams through DoS, that in the past we know and we've seen has caused four, five million dollars from one breach, that's a very good way to start classifying risk. So yeah, I mean, it's all about really understanding the picture first on the offensive, and that's exactly what these automated playbook guides are going to be doing on the blue team and again, not only from a CoC perspective, certainly that on the human level, but the nice thing about the playbooks is because we've done the research, the threat hunting and understood this, you know from a machine level it's also able to put a lot of those automated, let's say day-to-day decisions, making security operation centers, so I'm talking about like SecDevOps, much more efficient too. >> So we've talked about more density at the edge amongst these devices, I also want to bring back one last thought here and that is, you said that historically some of the black-hats have been able to access with a degree of impunity, they have necessarily been hit hard, there's been a lot of slapping on the wrist as I think you said. Talk about how the playbooks and AI is going to allow us to more appropriately share data with others that can help both now but also in some of the forensics and the enforcement side, namely the legal and policing world. How are we going to share the responsibility, how is that going to change over the next few years to incorporate some of the folks that actually can then turn a defense into a legal attack? >> Threat elimination is what I call it right. So again, if we look at the current state, we've made great strides, great progress, you know, working with law enforcement, so we've set up public private sector relationships, we need to do that, have security experts working with law enforcement, law enforcements working on their end to train prosecutors to understand cyber crime and so forth. That foundation has been set, but it's still slow moving. You know, there's only a limited amount of playbooks right now. It takes a lot of work to unearth and do, to really move the needle, what we need to do, again like we're talking about, is to integrate a artificial intelligence with playbooks. The more that we understand about groups, the more that we do the threat illumination, the more that we uncover about them, the more we know about them, and by doing that we can start to form predictive models right. Based, I always say old habits die hard. So you know, if an attacker goes in, hits a network and their successful following a certain sequence of patterns, they're likely going to follow that same sequence on their next victim or their next target. So the more that we understand about that, the more that we can forecast A; from a mitigation standpoint, but the, also by the same token, the more correlation we're doing on these playbooks, the more machine learning we're doing on these playbooks, the more we're able to do attribution and attribution is the holy grail, it's always been the toughest thing to do when it comes to research. But by combing the framework that we're using with playbooks, and AI machine learning, it's a very very powerful recipe and that's what we need to get right and forward in the right direction. >> Derek Manky, Fortinet's Chief of Security Insights & Threat Alliances, thanks again for being on theCUBE. >> It's a pleasure. Anytime. Happy to talk. >> And I want to thank you for joining us for another CUBE conversation. I'm Peter Burris, see you next time. (upbeat jazz music) >> Yeah I thought it was pretty good. [Man] - That was great. [Derek] - Yeah, yeah.