(upbeat music) >> Hello, everyone, welcome to theCUBE. I'm John Furrier, the host of theCUBE in Palo Alto, California. Also it's SiliconANGLE News. Got two great guests here to talk about AI, the impact of the future of the internet, the applications, the people. Amr Awadallah, the founder and CEO, Ed Alban is the CEO of Vectara, a new startup that emerged out of the original Cloudera, I would say, 'cause Amr's known, famous for the Cloudera founding, which was really the beginning of the big data movement. And now as AI goes mainstream, there's so much to talk about, so much to go on. And plus the new company is one of the, now what I call the wave, this next big wave, I call it the fifth wave in the industry. You know, you had PCs, you had the internet, you had mobile. This generative AI thing is real. And you're starting to see startups come out in droves. Amr obviously was founder of Cloudera, Big Data, and now Vectara. And Ed Albanese, you guys have a new company. Welcome to the show. >> Thank you. It's great to be here. >> So great to see you. Now the story is theCUBE started in the Cloudera office. Thanks to you, and your friendly entrepreneurship views that you have. We got to know each other over the years. But Cloudera had Hadoop, which was the beginning of what I call the big data wave, which then became what we now call data lakes, data oceans, and data infrastructure that's developed from that. It's almost interesting to look back 12 plus years, and see that what AI is doing now, right now, is opening up the eyes to the mainstream, and the application's almost mind blowing. You know, Sati Natel called it the Mosaic Moment, didn't say Netscape, he built Netscape (laughing) but called it the Mosaic Moment. You're seeing companies in startups, kind of the alpha geeks running here, because this is the new frontier, and there's real meat on the bone, in terms of like things to do. Why? Why is this happening now? What's is the confluence of the forces happening, that are making this happen? >> Yeah, I mean if you go back to the Cloudera days, with big data, and so on, that was more about data processing. Like how can we process data, so we can extract numbers from it, and do reporting, and maybe take some actions, like this is a fraud transaction, or this is not. And in the meanwhile, many of the researchers working in the neural network, and deep neural network space, were trying to focus on data understanding, like how can I understand the data, and learn from it, so I can take actual actions, based on the data directly, just like a human does. And we were only good at doing that at the level of somebody who was five years old, or seven years old, all the way until about 2013. And starting in 2013, which is only 10 years ago, a number of key innovations started taking place, and each one added on. It was no major innovation that just took place. It was a couple of really incremental ones, but they added on top of each other, in a very exponentially additive way, that led to, by the end of 2019, we now have models, deep neural network models, that can read and understand human text just like we do. Right? And they can reason about it, and argue with you, and explain it to you. And I think that's what is unlocking this whole new wave of innovation that we're seeing right now. So data understanding would be the essence of it. >> So it's not a Big Bang kind of theory, it's been evolving over time, and I think that the tipping point has been the advancements and other things. I mean look at cloud computing, and look how fast it just crept up on AWS. I mean AWS you back three, five years ago, I was talking to Swami yesterday, and their big news about AI, expanding the Hugging Face's relationship with AWS. And just three, five years ago, there wasn't a model training models out there. But as compute comes out, and you got more horsepower,, these large language models, these foundational models, they're flexible, they're not monolithic silos, they're interacting. There's a whole new, almost fusion of data happening. Do you see that? I mean is that part of this? >> Of course, of course. I mean this wave is building on all the previous waves. We wouldn't be at this point if we did not have hardware that can scale, in a very efficient way. We wouldn't be at this point, if we don't have data that we're collecting about everything we do, that we're able to process in this way. So this, this movement, this motion, this phase we're in, absolutely builds on the shoulders of all the previous phases. For some of the observers from the outside, when they see chatGPT for the first time, for them was like, "Oh my god, this just happened overnight." Like it didn't happen overnight. (laughing) GPT itself, like GPT3, which is what chatGPT is based on, was released a year ahead of chatGPT, and many of us were seeing the power it can provide, and what it can do. I don't know if Ed agrees with that. >> Yeah, Ed? >> I do. Although I would acknowledge that the possibilities now, because of what we've hit from a maturity standpoint, have just opened up in an incredible way, that just wasn't tenable even three years ago. And that's what makes it, it's true that it developed incrementally, in the same way that, you know, the possibilities of a mobile handheld device, you know, in 2006 were there, but when the iPhone came out, the possibilities just exploded. And that's the moment we're in. >> Well, I've had many conversations over the past couple months around this area with chatGPT. John Markoff told me the other day, that he calls it, "The five dollar toy," because it's not that big of a deal, in context to what AI's doing behind the scenes, and all the work that's done on ethics, that's happened over the years, but it has woken up the mainstream, so everyone immediately jumps to ethics. "Does it work? "It's not factual," And everyone who's inside the industry is like, "This is amazing." 'Cause you have two schools of thought there. One's like, people that think this is now the beginning of next gen, this is now we're here, this ain't your grandfather's chatbot, okay?" With NLP, it's got reasoning, it's got other things. >> I'm in that camp for sure. >> Yeah. Well I mean, everyone who knows what's going on is in that camp. And as the naysayers start to get through this, and they go, "Wow, it's not just plagiarizing homework, "it's helping me be better. "Like it could rewrite my memo, "bring the lead to the top." It's so the format of the user interface is interesting, but it's still a data-driven app. >> Absolutely. >> So where does it go from here? 'Cause I'm not even calling this the first ending. This is like pregame, in my opinion. What do you guys see this going, in terms of scratching the surface to what happens next? >> I mean, I'll start with, I just don't see how an application is going to look the same in the next three years. Who's going to want to input data manually, in a form field? Who is going to want, or expect, to have to put in some text in a search box, and then read through 15 different possibilities, and try to figure out which one of them actually most closely resembles the question they asked? You know, I don't see that happening. Who's going to start with an absolute blank sheet of paper, and expect no help? That is not how an application will work in the next three years, and it's going to fundamentally change how people interact and spend time with opening any element on their mobile phone, or on their computer, to get something done. >> Yes. I agree with that. Like every single application, over the next five years, will be rewritten, to fit within this model. So imagine an HR application, I don't want to name companies, but imagine an HR application, and you go into application and you clicking on buttons, because you want to take two weeks of vacation, and menus, and clicking here and there, reasons and managers, versus just telling the system, "I'm taking two weeks of vacation, going to Las Vegas," book it, done. >> Yeah. >> And the system just does it for you. If you weren't completing in your input, in your description, for what you want, then the system asks you back, "Did you mean this? "Did you mean that? "Were you trying to also do this as well?" >> Yeah. >> "What was the reason?" And that will fit it for you, and just do it for you. So I think the user interface that we have with apps, is going to change to be very similar to the user interface that we have with each other. And that's why all these apps will need to evolve. >> I know we don't have a lot of time, 'cause you guys are very busy, but I want to definitely have multiple segments with you guys, on this topic, because there's so much to talk about. There's a lot of parallels going on here. I was talking again with Swami who runs all the AI database at AWS, and I asked him, I go, "This feels a lot like the original AWS. "You don't have to provision a data center." A lot of this heavy lifting on the back end, is these large language models, with these foundational models. So the bottleneck in the past, was the energy, and cost to actually do it. Now you're seeing it being stood up faster. So there's definitely going to be a tsunami of apps. I would see that clearly. What is it? We don't know yet. But also people who are going to leverage the fact that I can get started building value. So I see a startup boom coming, and I see an application tsunami of refactoring things. >> Yes. >> So the replatforming is already kind of happening. >> Yes, >> OpenAI, chatGPT, whatever. So that's going to be a developer environment. I mean if Amazon turns this into an API, or a Microsoft, what you guys are doing. >> We're turning it into API as well. That's part of what we're doing as well, yes. >> This is why this is exciting. Amr, you've lived the big data dream, and and we used to talk, if you didn't have a big data problem, if you weren't full of data, you weren't really getting it. Now people have all the data, and they got to stand this up. >> Yeah. >> So the analogy is again, the mobile, I like the mobile movement, and using mobile as an analogy, most companies were not building for a mobile environment, right? They were just building for the web, and legacy way of doing apps. And as soon as the user expectations shifted, that my expectation now, I need to be able to do my job on this small screen, on the mobile device with a touchscreen. Everybody had to invest in re-architecting, and re-implementing every single app, to fit within that model, and that model of interaction. And we are seeing the exact same thing happen now. And one of the core things we're focused on at Vectara, is how to simplify that for organizations, because a lot of them are overwhelmed by large language models, and ML. >> They don't have the staff. >> Yeah, yeah, yeah. They're understaffed, they don't have the skills. >> But they got developers, they've got DevOps, right? >> Yes. >> So they have the DevSecOps going on. >> Exactly, yes. >> So our goal is to simplify it enough for them that they can start leveraging this technology effectively, within their applications. >> Ed, you're the COO of the company, obviously a startup. You guys are growing. You got great backup, and good team. You've also done a lot of business development, and technical business development in this area. If you look at the landscape right now, and I agree the apps are coming, every company I talk to, that has that jet chatGPT of, you know, epiphany, "Oh my God, look how cool this is. "Like magic." Like okay, it's code, settle down. >> Mm hmm. >> But everyone I talk to is using it in a very horizontal way. I talk to a very senior person, very tech alpha geek, very senior person in the industry, technically. they're using it for log data, they're using it for configuration of routers. And in other areas, they're using it for, every vertical has a use case. So this is horizontally scalable from a use case standpoint. When you hear horizontally scalable, first thing I chose in my mind is cloud, right? >> Mm hmm. >> So cloud, and scalability that way. And the data is very specialized. So now you have this vertical specialization, horizontally scalable, everyone will be refactoring. What do you see, and what are you seeing from customers, that you talk to, and prospects? >> Yeah, I mean put yourself in the shoes of an application developer, who is actually trying to make their application a bit more like magic. And to have that soon-to-be, honestly, expected experience. They've got to think about things like performance, and how efficiently that they can actually execute a query, or a question. They've got to think about cost. Generative isn't cheap, like the inference of it. And so you've got to be thoughtful about how and when you take advantage of it, you can't use it as a, you know, everything looks like a nail, and I've got a hammer, and I'm going to hit everything with it, because that will be wasteful. Developers also need to think about how they're going to take advantage of, but not lose their own data. So there has to be some controls around what they feed into the large language model, if anything. Like, should they fine tune a large language model with their own data? Can they keep it logically separated, but still take advantage of the powers of a large language model? And they've also got to take advantage, and be aware of the fact that when data is generated, that it is a different class of data. It might not fully be their own. >> Yeah. >> And it may not even be fully verified. And so when the logical cycle starts, of someone making a request, the relationship between that request, and the output, those things have to be stored safely, logically, and identified as such. >> Yeah. >> And taken advantage of in an ongoing fashion. So these are mega problems, each one of them independently, that, you know, you can think of it as middleware companies need to take advantage of, and think about, to help the next wave of application development be logical, sensible, and effective. It's not just calling some raw API on the cloud, like openAI, and then just, you know, you get your answer and you're done, because that is a very brute force approach. >> Well also I will point, first of all, I agree with your statement about the apps experience, that's going to be expected, form filling. Great point. The interesting about chatGPT. >> Sorry, it's not just form filling, it's any action you would like to take. >> Yeah. >> Instead of clicking, and dragging, and dropping, and doing it on a menu, or on a touch screen, you just say it, and it's and it happens perfectly. >> Yeah. It's a different interface. And that's why I love that UIUX experiences, that's the people falling out of their chair moment with chatGPT, right? But a lot of the things with chatGPT, if you feed it right, it works great. If you feed it wrong and it goes off the rails, it goes off the rails big. >> Yes, yes. >> So the the Bing catastrophes. >> Yeah. >> And that's an example of garbage in, garbage out, classic old school kind of comp-side phrase that we all use. >> Yep. >> Yes. >> This is about data in injection, right? It reminds me the old SQL days, if you had to, if you can sling some SQL, you were a magician, you know, to get the right answer, it's pretty much there. So you got to feed the AI. >> You do, Some people call this, the early word to describe this as prompt engineering. You know, old school, you know, search, or, you know, engagement with data would be, I'm going to, I have a question or I have a query. New school is, I have, I have to issue it a prompt, because I'm trying to get, you know, an action or a reaction, from the system. And the active engineering, there are a lot of different ways you could do it, all the way from, you know, raw, just I'm going to send you whatever I'm thinking. >> Yeah. >> And you get the unintended outcomes, to more constrained, where I'm going to just use my own data, and I'm going to constrain the initial inputs, the data I already know that's first party, and I trust, to, you know, hyper constrain, where the application is actually, it's looking for certain elements to respond to. >> It's interesting Amr, this is why I love this, because one we are in the media, we're recording this video now, we'll stream it. But we got all your linguistics, we're talking. >> Yes. >> This is data. >> Yep. >> So the data quality becomes now the new intellectual property, because, if you have that prompt source data, it makes data or content, in our case, the original content, intellectual property. >> Absolutely. >> Because that's the value. And that's where you see chatGPT fall down, is because they're trying to scroll the web, and people think it's search. It's not necessarily search, it's giving you something that you wanted. It is a lot of that, I remember in Cloudera, you said, "Ask the right questions." Remember that phrase you guys had, that slogan? >> Mm hmm. And that's prompt engineering. So that's exactly, that's the reinvention of "Ask the right question," is prompt engineering is, if you don't give these models the question in the right way, and very few people know how to frame it in the right way with the right context, then you will get garbage out. Right? That is the garbage in, garbage out. But if you specify the question correctly, and you provide with it the metadata that constrain what that question is going to be acted upon or answered upon, then you'll get much better answers. And that's exactly what we solved Vectara. >> Okay. So before we get into the last couple minutes we have left, I want to make sure we get a plug in for the opportunity, and the profile of Vectara, your new company. Can you guys both share with me what you think the current situation is? So for the folks who are now having those moments of, "Ah, AI's bullshit," or, "It's not real, it's a lot of stuff," from, "Oh my god, this is magic," to, "Okay, this is the future." >> Yes. >> What would you say to that person, if you're at a cocktail party, or in the elevator say, "Calm down, this is the first inning." How do you explain the dynamics going on right now, to someone who's either in the industry, but not in the ropes? How would you explain like, what this wave's about? How would you describe it, and how would you prepare them for how to change their life around this? >> Yeah, so I'll go first and then I'll let Ed go. Efficiency, efficiency is the description. So we figured that a way to be a lot more efficient, a way where you can write a lot more emails, create way more content, create way more presentations. Developers can develop 10 times faster than they normally would. And that is very similar to what happened during the Industrial Revolution. I always like to look at examples from the past, to read what will happen now, and what will happen in the future. So during the Industrial Revolution, it was about efficiency with our hands, right? So I had to make a piece of cloth, like this piece of cloth for this shirt I'm wearing. Our ancestors, they had to spend month taking the cotton, making it into threads, taking the threads, making them into pieces of cloth, and then cutting it. And now a machine makes it just like that, right? And the ancestors now turned from the people that do the thing, to manage the machines that do the thing. And I think the same thing is going to happen now, is our efficiency will be multiplied extremely, as human beings, and we'll be able to do a lot more. And many of us will be able to do things they couldn't do before. So another great example I always like to use is the example of Google Maps, and GPS. Very few of us knew how to drive a car from one location to another, and read a map, and get there correctly. But once that efficiency of an AI, by the way, behind these things is very, very complex AI, that figures out how to do that for us. All of us now became amazing navigators that can go from any point to any point. So that's kind of how I look at the future. >> And that's a great real example of impact. Ed, your take on how you would talk to a friend, or colleague, or anyone who asks like, "How do I make sense of the current situation? "Is it real? "What's in it for me, and what do I do?" I mean every company's rethinking their business right now, around this. What would you say to them? >> You know, I usually like to show, rather than describe. And so, you know, the other day I just got access, I've been using an application for a long time, called Notion, and it's super popular. There's like 30 or 40 million users. And the new version of Notion came out, which has AI embedded within it. And it's AI that allows you primarily to create. So if you could break down the world of AI into find and create, for a minute, just kind of logically separate those two things, find is certainly going to be massively impacted in our experiences as consumers on, you know, Google and Bing, and I can't believe I just said the word Bing in the same sentence as Google, but that's what's happening now (all laughing), because it's a good example of change. >> Yes. >> But also inside the business. But on the crate side, you know, Notion is a wiki product, where you try to, you know, note down things that you are thinking about, or you want to share and memorialize. But sometimes you do need help to get it down fast. And just in the first day of using this new product, like my experience has really fundamentally changed. And I think that anybody who would, you know, anybody say for example, that is using an existing app, I would show them, open up the app. Now imagine the possibility of getting a starting point right off the bat, in five seconds of, instead of having to whole cloth draft this thing, imagine getting a starting point then you can modify and edit, or just dispose of and retry again. And that's the potential for me. I can't imagine a scenario where, in a few years from now, I'm going to be satisfied if I don't have a little bit of help, in the same way that I don't manually spell check every email that I send. I automatically spell check it. I love when I'm getting type ahead support inside of Google, or anything. Doesn't mean I always take it, or when texting. >> That's efficiency too. I mean the cloud was about developers getting stuff up quick. >> Exactly. >> All that heavy lifting is there for you, so you don't have to do it. >> Right? >> And you get to the value faster. >> Exactly. I mean, if history taught us one thing, it's, you have to always embrace efficiency, and if you don't fast enough, you will fall behind. Again, looking at the industrial revolution, the companies that embraced the industrial revolution, they became the leaders in the world, and the ones who did not, they all like. >> Well the AI thing that we got to watch out for, is watching how it goes off the rails. If it doesn't have the right prompt engineering, or data architecture, infrastructure. >> Yes. >> It's a big part. So this comes back down to your startup, real quick, I know we got a couple minutes left. Talk about the company, the motivation, and we'll do a deeper dive on on the company. But what's the motivation? What are you targeting for the market, business model? The tech, let's go. >> Actually, I would like Ed to go first. Go ahead. >> Sure, I mean, we're a developer-first, API-first platform. So the product is oriented around allowing developers who may not be superstars, in being able to either leverage, or choose, or select their own large language models for appropriate use cases. But they that want to be able to instantly add the power of large language models into their application set. We started with search, because we think it's going to be one of the first places that people try to take advantage of large language models, to help find information within an application context. And we've built our own large language models, focused on making it very efficient, and elegant, to find information more quickly. So what a developer can do is, within minutes, go up, register for an account, and get access to a set of APIs, that allow them to send data, to be converted into a format that's easy to understand for large language models, vectors. And then secondarily, they can issue queries, ask questions. And they can ask them very, the questions that can be asked, are very natural language questions. So we're talking about long form sentences, you know, drill down types of questions, and they can get answers that either come back in depending upon the form factor of the user interface, in list form, or summarized form, where summarized equals the opportunity to kind of see a condensed, singular answer. >> All right. I have a. >> Oh okay, go ahead, you go. >> I was just going to say, I'm going to be a customer for you, because I want, my dream was to have a hologram of theCUBE host, me and Dave, and have questions be generated in the metaverse. So you know. (all laughing) >> There'll be no longer any guests here. They'll all be talking to you guys. >> Give a couple bullets, I'll spit out 10 good questions. Publish a story. This brings the automation, I'm sorry to interrupt you. >> No, no. No, no, I was just going to follow on on the same. So another way to look at exactly what Ed described is, we want to offer you chatGPT for your own data, right? So imagine taking all of the recordings of all of the interviews you have done, and having all of the content of that being ingested by a system, where you can now have a conversation with your own data and say, "Oh, last time when I met Amr, "which video games did we talk about? "Which movie or book did we use as an analogy "for how we should be embracing data science, "and big data, which is moneyball," I know you use moneyball all the time. And you start having that conversation. So, now the data doesn't become a passive asset that you just have in your organization. No. It's an active participant that's sitting with you, on the table, helping you make decisions. >> One of my favorite things to do with customers, is to go to their site or application, and show them me using it. So for example, one of the customers I talked to was one of the biggest property management companies in the world, that lets people go and rent homes, and houses, and things like that. And you know, I went and I showed them me searching through reviews, looking for information, and trying different words, and trying to find out like, you know, is this place quiet? Is it comfortable? And then I put all the same data into our platform, and I showed them the world of difference you can have when you start asking that question wholeheartedly, and getting real information that doesn't have anything to do with the words you asked, but is really focused on the meaning. You know, when I asked like, "Is it quiet?" You know, answers would come back like, "The wind whispered through the trees peacefully," and you know, it's like nothing to do with quiet in the literal word sense, but in the meaning sense, everything to do with it. And that that was magical even for them, to see that. >> Well you guys are the front end of this big wave. Congratulations on the startup, Amr. I know you guys got great pedigree in big data, and you've got a great team, and congratulations. Vectara is the name of the company, check 'em out. Again, the startup boom is coming. This will be one of the major waves, generative AI is here. I think we'll look back, and it will be pointed out as a major inflection point in the industry. >> Absolutely. >> There's not a lot of hype behind that. People are are seeing it, experts are. So it's going to be fun, thanks for watching. >> Thanks John. (soft music)

(upbeat music) (air whooshing) >> Hi everybody. John Walls here continuing our Cube Conversations here focusing on NETSCOUT today and the drawing problem of ransomware. Obviously very much in the news these days for the couple of high profile cases. It is certainly an increasing challenge, but by no means a new phenomenon at all. With us to talk about this is Roland Dobbins who is the principal engineer of NETSCOUT's A-CERT team. And Ronald and good to see you today, sir. Thanks for joining us. >> Good to see you as well. And Richard Hummel who's Threat Intelligence research lead for the A-CERT Team. And Richard, thank you for being with us as well here on the Cube. >> Absolutely John, thanks for having us. >> Yeah, let's just jump right in here. Ransomware, obviously we're all well aware of a couple of high profile cases, as I alluded to. Let's talk about first, the magnitude and scale of the problem, as it currently exists. And Roland, I'm going to let you just set the table for us here. Let's talk about ransomware, where it was maybe four or five years ago, and then the challenge has become today? >> Actually, John, if you don't mind I'd really like to hand that one to my colleague, Richard because >> By all means, so Richard- he's really has an in-depth background there if that's okay. >> Richard, jump in on that. >> Absolutely. Yeah. And so (clears throat) I'll handle all the ransomware stuff, namely because I've been doing this for going on seven years now of looking specifically at ransomware. I started this right around the time I joined Eyesight Partners, you know leading premier provider of threat intelligence who was acquired by FireEye and now Mandiat, and now even a conglomerate that just acquired Mandia. So there's been a series of acquisitions here but the reality is this threat intelligence has been pervasive across all of these. And you can see that over time that value hasn't diminished. And you can see that by all of these acquisitions. that are like that's a really good example to show how valuable this is because everybody wants it. And the reality is back then I started tracking ransomware specifically looking at a lot of the CryptoLocker variance, things like CryptoWall, and TorrentLocker, and TeslaCrypt. And there's any number I could go on and on and on about all these different variations, and how ransomware came to be, and what you know, adversaries were using it for. But the reality is ransomware has been around for a long, long time and probably three or four years ago. There was this lull in time where people are like, hey we've got these initiatives like no ransomware.org. We've got the, you know, local law enforcement backing in a bunch of different countries. There's this big huge international effort to basically get rid of ransomware. And it's going to% be a thing of the past. And we very clearly see that is not the case. And now with ransomware, you have an evolution over time. It used to be you would have different flavors of ransomware where sometimes it would encrypt your files first and then it would reach back to the command control. Sometimes it would reach back first to get keys and then it would encrypt. Sometimes the encryptions were breakable, sometimes the keys were stored locally, but a lot of them more recent variants of ransomware are very well done. They're very sophisticated. They will encrypt your files and the keys themselves are held by the adversary. And so there's no way to just decrypt it. You can't create a decryptor like a lot of these security companies do you would actually have to get that key from the adversary or you would have to restore your systems from a backup. And so the history of ransomware is very long and varied. And you know one of the core topics we want to discuss today is ransomware isn't by itself anymore. It used to be like ransomware was the name that incited fear but these guys have evolved over time. And now ransomware operators are doing kind of this triple extortion. Where they will encrypt your files, they've already gained access to that system. So then they will exfiltrate sensitive data and they will have that as kind of a hostage and say, look you're going to pay us for this ransomware to decrypt your files, to get those back. But I'll guess what? We also have your sensitive data that we're going to post online and sell and on underground forms unless you pay us additional money. But now we even have a third stage here. And this is kind of where Roland's going to come in and talk about this is we have DDoS extortion. That is surging In fact, we did a survey of enterprise internet service providers. And when we asked them what was their biggest concerns in 2020 and going into 2021 about threats, and obviously ransomware was number one but DDoS extortion was number two. And so you have this one, two bang the adversaries are using to be able to extort payment from victims. And this has been going on for a number of years with this kind of double extortion. And now this triple extortion, in fact going all the way back to the CryptoLocker days you would have banking malware, like Gameover Zeus where they would get on your system, they would do wire transfers from your bank accounts. There was steal files. And then as a last hurrah they would deploy ransomware and encrypt all your files. And so not only did they steal all your money from the bank. Now, they're going to say, you got to pay us to actually do decrypt your files. So this idea of kind of a double tap has been going on for a long time. And more recently around September of last year we started to see this DDoS aspect part of these operations. And so, yeah, that's kind of the history of what we're dealing with here. >> And so, and DDoS distributed denial service, Ronald let you pick up the ball at this point then. Now this evolution you will the triple threat, you know first you were talking about in encryption, in public exposure. And now this DDoS stage, this pillar of the malfeasance, if you will what kind of headaches is this causing in terms of from an engineering perspective from your side of the fence when you're looking at what your clients are dealing with when all of a sudden they have this entirely new plethora of challenges that are confronting them. >> Sure. So DDoS goes back a long ways. So it actually goes back to the late 80s and the early ARPANET. And then we started to see non-monetary DDoS extortion in the early 1990s. And we started to see monetary DDoS extortion that kicked off around 1997. So with any, criminals are very, very adaptive. And so when new technologies come online and new ways that they can potentially exploit it for their gain, they will do so in many cases using old modalities just simply transliterated into the new technology space. And that's what we see with (indistinct) extortion. DDOS attacks are attacks against availability. So the idea is to disrupt the access, (indistinct) access to applications, services, servers, data content, infrastructure, those different types of things. And DDoS attacks can be motivated by pretty much any motivation you can think of. But there is a hard core of DDoS extortionists that we've seen over the years. And this Richard indicated what we started to see is a convergence between these sets of criminal specialties. And so a few years ago, we actually were disassembling a piece of ransomware and it turned out that it had some very basic DDoS attack capabilities coded into it. It was obviously a prototype, it hadn't been finished, but this showed that these criminals in the ransomware space were thinking about getting into DDoS. And now they've developed this methodology where like Richard said, they, number one, they encrypt the files. Number two, they'll threaten to leak information. And then they will DDoS the public facing infrastructure of the organizations to try and put additional pressure on them to pay. And especially now during the pandemic with this wholesale shift to remote work. The attackers for the first time have the ability not only to disrupt the online operations which is bad enough, but they can actually interfere with the ordinary work day activities of the first-line workforce of organizations. And so this really makes it even more potent. And the ransomware itself is interesting as well because it uses exploits, social engineering, along with technological exploits to exploit the confidentiality and the integrity of data, and to restrict that stuff which actually turns into an attack against availability. So it's kind of really a different form of DDoS attack and coupled out with a real DDoS attack, and it can be very, very challenging. But one thing John that we've seen is that organizations if they have prepared to deal with a DDoS attack in form an architectural perspective, from an operational perspective. If they have done the things they need to do, to be able to maintain availability, even in the face of attack. There are about 80% of where they need to be to be to able to withstand a ransomware attack. Conversely, if organizations have been doing a good job and ensuring that their systems are secured and if they do get hit somehow with ransomware that they have the ability to maintain operations and communications and recover, they're about 80% of where they need to be to be able to successfully withstand DDoS attacks. And so it turns out that even though these threats are major threats and they are something that organizations need to be aware of, the good news is that a lot of the planning, and resources, and organizational changes that need to be made to face these threats are in fact very similar. >> Yeah, but (indistinct) mean the challenge is, it's hard work, right? It, there's an enormous amount of preparations got to go into this, and pre-planning, pre-thought, and that's what NETSCOUT is all about obviously is trying to get people onto that journey and getting into this examination of their services, and their networks, and... The fact that this can happen on multiple layers, right? It could be application, be protocols, transport, network, whatever, you know just multiple ways that these DDoS attacks can occur. What kind of I'd say well, challenges again does that present in the fact that it is, there are many doors, right? That these attacks can happen from or where these attacks can come from. So how do you then talk to your client base about approaching this kind of examination and these prophylactic measures that you're suggesting that have to be done in order to minimize the damage? >> It's really about business continuity. Now business continuity planning, we used to be called "disaster recovery planning", right? Is something that organizations are very familiar with. It often has executive sponsorship and a lot of planning has gone into it. The thing is DDoS attacks, which were attacks against availability are in fact a manmade disaster, right? And they interrupt the continuity of business. Same thing with the ransomware, and so from an architectural standpoint, from the standpoint of rolling out new products and services, resiliency and to attack, and the ability to maintain availability and continue with operations in the face of attack is really really key for any organization today which has any kind of significant online presence. And that's really just about all of them. And so from a planning standpoint, it's imperative from an architectural standpoint whether we're talking about things like network infrastructure, or DNS, or software applications. It's important from an operational standpoint. So one of the things that we see for example is that many organizations don't really have a good communications plan. They don't have a good internal communications plan nor do they have a good external communications plan for communicating during an event. And they don't even have really a plan for dealing with an event that is disruptive to business continuity and operations. And so that is really key. Technology is important, but the most important aspect of this is the human factor, understanding the business, understanding the types of risks to the business's ability to execute on its mission and then doing the things from a technological perspective, from an operational perspective, and from a communications perspective to maintain operations, and communications throughout an event and to be able to emerge on the other side of that agenda successfully. >> So Richard you're in threat intelligence, right? Risk assessments. And as you said, you've been around this block for quite some time now. In terms of, I guess getting people's attention that has been accomplished now with obviously some, with some of these high profile cases. But what about that kind of work that you're doing in terms of trying to communicate these very threats to your client base or to prospective clients in terms of identifying their real vulnerabilities within their networks and then having them seriously address these. I mean, what's the difference maybe in the mindset now, as opposed to where maybe that conversation was being had a few years ago? >> I think the biggest difference here is a matter of when and not if. It used to be, you could say, "Oh I'm never going to get hit by ransomware or I'm never going to get DDoS attacked." But that is no longer the case. Roland made a really good point that just about every single business in the world now relies on internet connectivity in order to operate their business. If they don't have that then they're not going to be able to connect with their consumers, their shoppers, if they're a retail, right? If you're a bank, then you have to communicate with your individuals having accounts. And I mean, I have not gone to a physical bank in probably six years. And so that just underscores how important it is to have this internet connectivity. Now, with that comes risk. Not only do you risk the DDoS attacks because you're publicly exposed in an adversary where you can actually find your internet space by doing some forensics, such as network scanning, being able to walk that back like a passive DNS but their historical records use things like showdown to figure out what kind of devices you're running. So there's any number of ways that you can do that. But at the same time you're also exposing yourself to these ransomware operators and really any kind of crime ware operator out there, because they're going to exploit you over the internet. We actually did a case study probably two years ago. Looking at brute forcing on networks and looking at exploitation attempts to figure out like what is the Delta? If you have an online internet presence are you going to get attacked? And the answer was very shocking to us. Yes, you're going to get attacked. And also it's going to be in less than five minutes, from the time a brand new IOT device goes online to the time it starts getting brute force attacked. And within 24 hours you're going to get exploitation attempts from known vulnerabilities or devices that haven't been patched and things like that. And so the reality is not if you're going to get attacked, it's when? And so understanding that is the nature of the threat landscape right now and having this kind of security awareness. Actually another good point that Roland just brought up was that human element. The human element is kind of the linchpin for any security organization. And as part of my master's I had wrote a dissertation about, and I named it as such my professor didn't really care for this, but I said, "The humans are the weakest link." Because in the security posture, that is essentially true. If you don't have the expertise on a team you're not going to be able to get things configured properly. If you don't have the expertise you're not going to be able to respond properly. If you have individuals that aren't concerned about security, now you're going to have a bunch of gaps. Not only that, social engineering is still the number one method that adversaries use to get into organizations and that manipulates the human element. And so having the security awareness in what we do here, on this cube interview, the threat reports, we publish, the blogs that we do, all the threads summaries, all of that goes hand-in-hand with educating the general public and having security awareness pushed out as much as possible to every single person we can. And that's really the key, this preparation, this awareness of what adversaries are doing in order to defend against them. >> So Roland in your mind and you've already walked us through a little bit of this about certain steps and measures. Do you think that could be taken safeguards basically, that everybody should have in the place? What is the optimal scenario from an engineering perspective in terms of trying to prevent these kinds of intrusions, these kinds of attacks in terms of what are those basic pieces, these fundamental pieces as you see it now, understanding as Richard just told us that it's matter of not if, but when? >> Right. So availability, redundancy these have to be core architectural principles whether we're talking about network infrastructure, whether we're talking about important ancillary supporting services like DNS in terms of personnel, in terms of remote access. All of these different elements and many many more have to be designed from the out. All the services in the applications whether they're used internally, whether they are part of service delivery that an organization is doing across the internet, publicly there has to be redundancy and resiliency. There has to be a defense plan in order to defend these assets in these organizations against attack. Whether it's DDoS attack or whether it's a containment plan to deal with a ransomware that potentially gets let loose inside the enterprise network, there has to be a plan to contain it, and deal with it, and restore from backup. These plans have to be continuously updated because IT is not static. There are always noose and nance and changes this organizations provision new services offer new products, move into new markets and new new sub-specializations. And so the plans have to be consistently updated and they have to be rehearsed. You can't have a plan that just exists as pixels on a phosphorous somewhere. The plan has to be executed because you're going to find that there's some scenario, some service, or application, or operational process that needs to be updated or that needs to be included in the plan. And this has to be done regularly. Another key point is that you have to have people who are very skilled and who have both depth and breadth of understanding. And either you bring those people into your organization or you reach out and get that expertise from organizations who do in fact have that kind of expertise on tap and available. >> Well, is, you both certainly exhibit the depth and the breadth to fight this issue(chuckles) I certainly appreciate the time, the insights, and the warning is quite clear. Be prepared, do the hard work upfront. It could save you a lot of headache on the backside. And it is a matter of when and not if, these days. Richard Roland, thanks for being with us here on the Cube >> Thank you so much. >> Thank you so much. It's a pleasure. >> All right, talking about the triple threat of extortion, cyber extortion these days, and DDoS, the distributed denial of service in the growing problem. It is, but there is a way that you can combat it. And you just learned about that (indistinct) NETSCOUT here on the Cube. (upbeat music)

(upbeat music) (air whooshing) >> Hi everybody. John Walls here continuing our Cube Conversations here focusing on NETSCOUT today and the drawing problem of ransomware. Obviously very much in the news these days for the couple of high profile cases. It is certainly an increasing challenge, but by no means a new phenomenon at all. With us to talk about this is Roland Dobbins who is the principal engineer of NETSCOUT's A-CERT team. And Ronald and good to see you today, sir. Thanks for joining us. >> Good to see you as well. And Richard Hummel who's Threat Intelligence research lead for the A-CERT Team. And Richard, thank you for being with us as well here on the Cube. >> Absolutely John, thanks for having us. >> Yeah, let's just jump right in here. Ransomware, obviously we're all well aware of a couple of high profile cases, as I alluded to. Let's talk about first, the magnitude and scale of the problem, as it currently exists. And Roland, I'm going to let you just set the table for us here. Let's talk about ransomware, where it was maybe four or five years ago, and then the challenge has become today? >> Actually, John, if you don't mind I'd really like to hand that one to my colleague, Richard because >> By all means, so Richard- he's really has an in-depth background there if that's okay. >> Richard, jump in on that. >> Absolutely. Yeah. And so (clears throat) I'll handle all the ransomware stuff, namely because I've been doing this for going on seven years now of looking specifically at ransomware. I started this right around the time I joined Eyesight Partners, you know leading premier provider of threat intelligence who was acquired by FireEye and now Mandiat, and now even a conglomerate that just acquired Mandia. So there's been a series of acquisitions here but the reality is this threat intelligence has been pervasive across all of these. And you can see that over time that value hasn't diminished. And you can see that by all of these acquisitions. that are like that's a really good example to show how valuable this is because everybody wants it. And the reality is back then I started tracking ransomware specifically looking at a lot of the CryptoLocker variance, things like CryptoWall, and TorrentLocker, and TeslaCrypt. And there's any number I could go on and on and on about all these different variations, and how ransomware came to be, and what you know, adversaries were using it for. But the reality is ransomware has been around for a long, long time and probably three or four years ago. There was this lull in time where people are like, hey we've got these initiatives like no ransomware.org. We've got the, you know, local law enforcement backing in a bunch of different countries. There's this big huge international effort to basically get rid of ransomware. And it's going to% be a thing of the past. And we very clearly see that is not the case. And now with ransomware, you have an evolution over time. It used to be you would have different flavors of ransomware where sometimes it would encrypt your files first and then it would reach back to the command control. Sometimes it would reach back first to get keys and then it would encrypt. Sometimes the encryptions were breakable, sometimes the keys were stored locally, but a lot of them more recent variants of ransomware are very well done. They're very sophisticated. They will encrypt your files and the keys themselves are held by the adversary. And so there's no way to just decrypt it. You can't create a decryptor like a lot of these security companies do you would actually have to get that key from the adversary or you would have to restore your systems from a backup. And so the history of ransomware is very long and varied. And you know one of the core topics we want to discuss today is ransomware isn't by itself anymore. It used to be like ransomware was the name that incited fear but these guys have evolved over time. And now ransomware operators are doing kind of this triple extortion. Where they will encrypt your files, they've already gained access to that system. So then they will exfiltrate sensitive data and they will have that as kind of a hostage and say, look you're going to pay us for this ransomware to decrypt your files, to get those back. But I'll guess what? We also have your sensitive data that we're going to post online and sell and on underground forms unless you pay us additional money. But now we even have a third stage here. And this is kind of where Roland's going to come in and talk about this is we have DDoS extortion. That is surging In fact, we did a survey of enterprise internet service providers. And when we asked them what was their biggest concerns in 2020 and going into 2021 about threats, and obviously ransomware was number one but DDoS extortion was number two. And so you have this one, two bang the adversaries are using to be able to extort payment from victims. And this has been going on for a number of years with this kind of double extortion. And now this triple extortion, in fact going all the way back to the CryptoLocker days you would have banking malware, like Gameover Zeus where they would get on your system, they would do wire transfers from your bank accounts. There was steal files. And then as a last hurrah they would deploy ransomware and encrypt all your files. And so not only did they steal all your money from the bank. Now, they're going to say, you got to pay us to actually do decrypt your files. So this idea of kind of a double tap has been going on for a long time. And more recently around September of last year we started to see this DDoS aspect part of these operations. And so, yeah, that's kind of the history of what we're dealing with here. >> And so, and DDoS distributed denial service, Ronald let you pick up the ball at this point then. Now this evolution you will the triple threat, you know first you were talking about in encryption, in public exposure. And now this DDoS stage, this pillar of the malfeasance, if you will what kind of headaches is this causing in terms of from an engineering perspective from your side of the fence when you're looking at what your clients are dealing with when all of a sudden they have this entirely new plethora of challenges that are confronting them. >> Sure. So DDoS goes back a long ways. So it actually goes back to the late 80s and the early ARPANET. And then we started to see non-monetary DDoS extortion in the early 1990s. And we started to see monetary DDoS extortion that kicked off around 1997. So with any, criminals are very, very adaptive. And so when new technologies come online and new ways that they can potentially exploit it for their gain, they will do so in many cases using old modalities just simply transliterated into the new technology space. And that's what we see with (indistinct) extortion. DDOS attacks are attacks against availability. So the idea is to disrupt the access, (indistinct) access to applications, services, servers, data content, infrastructure, those different types of things. And DDoS attacks can be motivated by pretty much any motivation you can think of. But there is a hard core of DDoS extortionists that we've seen over the years. And this Richard indicated what we started to see is a convergence between these sets of criminal specialties. And so a few years ago, we actually were disassembling a piece of ransomware and it turned out that it had some very basic DDoS attack capabilities coded into it. It was obviously a prototype, it hadn't been finished, but this showed that these criminals in the ransomware space were thinking about getting into DDoS. And now they've developed this methodology where like Richard said, they, number one, they encrypt the files. Number two, they'll threatened to leak information. And then they will DDoS the public facing infrastructure of the organizations to try and put additional pressure on them to pay. And especially now during the pandemic with this wholesale shift to remote work. The attackers for the first time have the ability not only to disrupt the online operations which is bad enough, but they can actually interfere with the ordinary work day activities of the first-line workforce of organizations. And so this really makes it even more potent. And the ransomware itself is interesting as well because it uses exploits (indistinct), social engineering, along with technological exploits to exploit the confidentiality and the integrity of data, and to restrict that stuff which actually turns into an attack against availability. So it's kind of really a different form of DDoS attack and coupled out with a real DDoS attack, and it can be very, very challenging. But one thing John that we've seen is that organizations if they have prepared to deal with a DDoS attack in form an architectural perspective, from an operational perspective. If they have done the things they need to do, to be able to maintain availability, even in the face of attack. There are about 80% of where they need to be to be to able to withstand a ransomware attack. Conversely, if organizations have been doing a good job and ensuring that their systems are secured and if they do get hit somehow with ransomware that they have the ability to maintain operations and communications and recover, they're about 80% of where they need to be to be able to successfully withstand DDoS attacks. And so it turns out that even though these threats are major threats and they are something that organizations need to be aware of, the good news is that a lot of the planning, and resources, and organizational changes that need to be made to face these threats are in fact very similar. >> Yeah, but (indistinct) mean the challenge is, it's hard work, right? It, there's an enormous amount of preparations got to go into this, and pre-planning, pre-thought, and that's what NETSCOUT is all about obviously is trying to get people onto that journey and getting into this examination of their services, and their networks, and... The fact that this can happen on multiple layers, right? It could be application, be protocols, transport, network, whatever, you know just multiple ways that these DDoS attacks can occur. What kind of I'd say well, challenges again does that present in the fact that it is, there are many doors, right? That these attacks can happen from or where these attacks can come from. So how do you then talk to your client base about approaching this kind of examination and these prophylactic measures that you're suggesting that have to be done in order to minimize the damage? >> It's really about business continuity. Now business continuity planning, we used to be called "disaster recovery planning", right? Is something that organizations are very familiar with. It often has executive sponsorship and a lot of planning has gone into it. The thing is DDoS attacks, which were attacks against availability are in fact a manmade disaster, right? And they interrupt the continuity of business. Same thing with the ransomware, and so from an architectural standpoint, from the standpoint of rolling out new products and services, resiliency and to attack, and the ability to maintain availability and continue with operations in the face of attack is really really key for any organization today which has any kind of significant online presence. And that's really just about all of them. And so from a planning standpoint, it's imperative from an architectural standpoint whether we're talking about things like network infrastructure, or DNS, or software applications. It's important from an operational standpoint. So one of the things that we see for example is that many organizations don't really have a good communications plan. They don't have a good internal communications plan nor do they have a good external communications plan for communicating during an event. And they don't even have really a plan for dealing with an event that is disruptive to business continuity and operations. And so that is really key. Technology is important, but the most important aspect of this is the human factor, understanding the business, understanding the types of risks to the business's ability to execute on its mission and then doing the things from a technological perspective, from an operational perspective, and from a communications perspective to maintain operations, and communications throughout an event and to be able to emerge on the other side of that agenda successfully. >> So Richard you're in threat intelligence, right? Risk assessments. And as you said, you've been around this block for quite some time now. In terms of, I guess getting people's attention that has been accomplished now with obviously some, with some of these high profile cases. But what about that kind of work that you're doing in terms of trying to communicate these very threats to your client base or to prospective clients in terms of identifying their real vulnerabilities within their networks and then having them seriously address these. I mean, what's the difference maybe in the mindset now, as opposed to where maybe that conversation was being had a few years ago? >> I think the biggest difference here is a matter of when and not if. It used to be, you could say, "Oh I'm never going to get hit by ransomware or I'm never going to get DDoS attacked." But that is no longer the case. Roland made a really good point that just about every single business in the world now relies on internet connectivity in order to operate their business. If they don't have that then they're not going to be able to connect with their consumers, their shoppers, if they're a retail, right? If you're a bank, then you have to communicate with your individuals having accounts. And I mean, I have not gone to a physical bank in probably six years. And so that just underscores how important it is to have this internet connectivity. Now, with that comes risk. Not only do you risk the DDoS attacks because you're publicly exposed in an adversary where you can actually find your internet space by doing some forensics, such as network scanning, being able to walk that back like a passive DNS but their historical records use things like showdown to figure out what kind of devices you're running. So there's any number of ways that you can do that. But at the same time you're also exposing yourself to these ransomware operators and really any kind of crime ware operator out there, because they're going to exploit you over the internet. We actually did a case study probably two years ago. Looking at brute forcing on networks and looking at exploitation attempts to figure out like what is the Delta? If you have an online internet presence are you going to get attacked? And the answer was very shocking to us. Yes, you're going to get attacked. And also it's going to be in less than five minutes, from the time a brand new IOT device goes online to the time it starts getting brute force attacked. And within 24 hours you're going to get exploitation attempts from known vulnerabilities or devices that haven't been patched and things like that. And so the reality is not if you're going to get attacked, it's when? And so understanding that is the nature of the threat landscape right now and having this kind of security awareness. Actually another good point that Roland just brought up was that human element. The human element is kind of the linchpin for any security organization. And as part of my master's I had wrote a dissertation about, and I named it as such my professor didn't really care for this, but I said, "The humans are the weakest link." Because in the security posture, that is essentially true. If you don't have the expertise on a team you're not going to be able to get things configured properly. If you don't have the expertise you're not going to be able to respond properly. If you have individuals that aren't concerned about security, now you're going to have a bunch of gaps. Not only that, social engineering is still the number one method that adversaries use to get into organizations and that manipulates the human element. And so having the security awareness in what we do here, on this cube interview, the threat reports, we publish, the blogs that we do, all the threads summaries, all of that goes hand-in-hand with educating the general public and having security awareness pushed out as much as possible to every single person we can. And that's really the key, this preparation, this awareness of what adversaries are doing in order to defend against them. >> So Roland in your mind and you've already walked us through a little bit of this about certain steps and measures. Do you think that could be taken safeguards basically, that everybody should have in the place? What is the optimal scenario from an engineering perspective in terms of trying to prevent these kinds of intrusions, these kinds of attacks in terms of what are those basic pieces, these fundamental pieces as you see it now, understanding as Richard just told us that it's matter of not if, but when? >> Right. So availability, redundancy these have to be core architectural principles whether we're talking about network infrastructure, whether we're talking about important ancillary supporting services like DNS in terms of personnel, in terms of remote access. All of these different elements and many many more have to be designed from the out. All the services in the applications whether they're used internally, whether they are part of service delivery that an organization is doing across the internet, publicly there has to be redundancy and resiliency. There has to be a defense plan in order to defend these assets in these organizations against attack. Whether it's DDoS attack or whether it's a containment plan to deal with a ransomware that potentially gets let loose inside the enterprise network, there has to be a plan to contain it, and deal with it, and restore from backup. These plans have to be continuously updated because IT is not static. There are always noose and nance and changes this organizations provision new services offer new products, move into new markets and new new sub-specializations. And so the plans have to be consistently updated and they have to be rehearsed. You can't have a plan that just exists as pixels on a phosphorous somewhere. The plan has to be executed because you're going to find that there's some scenario, some service, or application, or operational process that needs to be updated or that needs to be included in the plan. And this has to be done regularly. Another key point is that you have to have people who are very skilled and who have both depth and breadth of understanding. And either you bring those people into your organization or you reach out and get that expertise from organizations who do in fact have that kind of expertise on tap and available. >> Well, is, you both certainly exhibit the depth and the breadth to fight this issue(chuckles) I certainly appreciate the time, the insights, and the warning is quite clear. Be prepared, do the hard work upfront. It could save you a lot of headache on the backside. And it is a matter of when and not if, these days. Richard Roland, thanks for being with us here on the Cube >> Thank you so much. >> Thank you so much. It's a pleasure. >> All right, talking about the triple threat of extortion, cyber extortion these days, and DDoS, the distributed denial of service in the growing problem. It is, but there is a way that you can combat it. And you just learned about that (indistinct) NETSCOUT here on the Cube. (upbeat music)

>>president >>so called big data promised to usher in a new era of innovation where companies competed on the basis of insights and agile decision making. There's little question that social media giants, search leaders and e commerce companies benefited. They had the engineering shops and the execution capabilities to take troves of data and turned them into piles of money. But many organizations were not as successful. They invested heavily in data architecture is tooling and hyper specialized experts to build out their data pipelines. Yet they still struggle today to truly realize they're busy. Did data in their lakes is plentiful but actionable insights aren't so much chaos. Search is a cloud based startup that wants to change this dynamic with a new approach designed to simplify and accelerate time to insights and dramatically lower cost and with us to discuss his company and its vision for the future is cuba Lem Ed Walsh had great to see you. Thanks for coming back in the cube. >>I always love to be here. Thank you very much. It's always a warm welcome. Thank you. >>Alright, so give us the update. You guys have had some big funding rounds, You're making real progress on the tech, taking it to market what's new with chaos surgery. >>Sure. Actually even a lot of good exciting things happen. In fact just this month we need some, you know, obviously announced some pretty exciting things. So we unveiled what we consider the industry first multi model data late platform that we allow you to take your data in S three. In fact, if you want to show the image you can, but basically we allow you to put your data in S three and then what we do is we activate that data and what we do is a full index of the data and makes it available through open a P. I. S. And the key thing about that is it allows your end users to use the tools are using today. So simply put your data in your cloud option charge, think Amazon S three and glacier think of all the different data. Is that a natural act? And then we do the hard work. And the key thing is to get one unified delic but it's a multi mode model access so we expose api like the elastic search aPI So you can do things like search or using cabana do log analytics but you can also do things like sequel, use Tableau looker or bring relational concepts into cabana. Things like joins in the data back end. But it allows you also to machine learning which is early next year. But what you get is that with that because of a data lake philosophy, we're not making new transformations without all the data movement. People typically land data in S. Three and we're on the shoulders of giants with us three. Um There's not a better more cost effective platform. More resilient. There's not a better queuing system out there and it's gonna cost curve that you can't beat. But basically so people store a lot of data in S. Three. Um But what their um But basically what you have to do is you E. T. L. Out to other locations. What we do is allow you to literally keep it in place. We index in place. We write our hot index to rewrite index, allow you to go after that but published an open aPI S. But what we avoid is the GTL process. So what our index does is look at the data and does full scheme of discovery normalization, were able to give sample sets. And then the refinery allows you to advance transformations using code. Think about using sequel or using rejects to change that data pull the dead apartheid things but use role based access to give that to the end user. But it's in a format that their tools understand cabana will use the elasticsearch ap or using elasticsearch calls but also sequel and go directly after data by doing that. You get a data lake but you haven't had to take the three weeks to three months to transform your data. Everyone else makes you. And you talk about the failure. The idea that Alex was put your data there in a very scalable resilient environment. Don't do transformation. It was too hard to structure for databases and data. Where else is put it there? We'll show you how value out Largely un delivered. But we're that last mile. We do exactly that. Just put it in s. three and we activated and activate it with a piece that the tools of your analysts use today or what they want to use in the future. That is what's so powerful. So basically we're on the shoulders of giants with street, put it there and we light it up and that's really the last mile. But it's this multi model but it's also this lack of transformation. We can do all the transformation that's all to virtually and available immediately. You're not doing extended GTL projects with big teams moving around a lot of data in the enterprise. In fact, most time they land and that's three and they move it somewhere and they move it again. What we're saying is now just leave in place well index and make it available. >>So the reason that it was interesting, so the reason they want to move in the S three was the original object storage cloud. It was, it was a cheap bucket. Okay. But it's become much more than that when you talk to customers like, hey, I have all this data in this three. I want to do something with it. I want to apply machine intelligence. I want to search it. I want to do all these things, but you're right. I have to move it. Oftentimes to do that. So that's a huge value. Now can I, are you available in the AWS marketplace yet? >>You know, in fact that was the other announcement to talk about. So our solution is one person available AWS marketplace, which is great for clients because they've been burned down their credits with amazon. >>Yeah, that's that super great news there. Now let's talk a little bit more about data. Like you know, the old joke of the tongue in cheek was data lakes become data swamps. You sort of know, see no schema on, right. Oh great. I can put everything into the lake and then it's like, okay, what? Um, so maybe double click on that a little bit and provide a little bit more details to your, your vision there and your philosophy. >>So if you could put things that data can get after it with your own tools on elastic or search, of course you do that. If you don't have to go through that. But everyone thinks it's a status quo. Everyone is using, you know, everyone has to put it in some sort of schema in a database before they can get access to what everyone does. They move it some place to do it. Now. They're using 1970s and maybe 1980s technology. And they're saying, I'm gonna put it in this database, it works on the cloud and you can go after it. But you have to do all the same pain of transformation, which is what takes human. We use time, cost and complexity. It takes time to do that to do a transformation for an user. It takes a lot of time. But it also takes a teams time to do it with dBS and data scientists to do exactly that. And it's not one thing going on. So it takes three weeks to three months in enterprise. It's a cost complexity. But all these pipelines for every data request, you're trying to give them their own data set. It ends up being data puddles all over this. It might be in your data lake, but it's all separated. Hard to govern. Hard to manage. What we do is we stop that. What we do is we index in place. Your dad is already necessary. Typically retailing it out. You can continue doing that. We really are just one more use of the data. We do read only access. We do not change that data and you give us a place in. You're going to write our index. It's a full rewrite index. Once we did that that allows you with the refinery to make that we just we activate that data. It will immediately fully index was performant from cabana. So you no longer have to take your data and move it and do a pipeline into elasticsearch which becomes kind of brittle at scale. You have the scale of S. Three but use the exact same tools you do today. And what we find for like log analytics is it's a slightly different use case for large analytics or value prop than Be I or what we're doing with private companies but the logs were saving clients 50 to 80% on the hard dollars a day in the month. They're going from very limited data sets to unlimited data sets. Whatever they want to keep an S. Three and glacier. But also they're getting away from the brittle data layer which is the loosen environment which any of the data layers hold you back because it takes time to put it there. But more importantly It becomes brittle at scale where you don't have any of that scale issue when using S. three. Is your dad like. So what what >>are the big use cases Ed you mentioned log analytics? Maybe you can talk about that. And are there any others that are sort of forming in the marketplace? Any patterns that you see >>Because of the multi model we can do a lot of different use cases but we always work with clients on high R. O. I use cases why the Big Bang theory of Due dad like and put everything in it. It's just proven not to work right? So what we're focusing first use cases, log analytics, why as by way with everything had a tipping point, right? People were buying model, save money here, invested here. It went quickly to no, no we're going cloud native and we have to and then on top of it it was how do we efficiently innovate? So they got the tipping point happens, everyone's going cloud native. Once you go cloud native, the amount of machine generated data that you have that comes from the environment dramatically. It just explodes. You're not managing hundreds or thousands or maybe 10,000 endpoints, you're dealing with millions or billions and also you need this insight to get inside out. So logs become one of the things you can't keep up with it. I think I mentioned uh we went to a group of end users, it was only 60 enterprise clients but we asked him what's your capture rate on logs And they said what do you want it to be 80%, actually 78 said listen we want eight captured 80 200 of our logs. That would be the ideal not everything but we need most of it. And then the same group, what are you doing? Well 82 had less than 50%. They just can't keep up with it and every everything including elastic and Splunk. They work harder to the process to narrow and keep less and less data. Why? Because they can't handle the scale, we just say landed there don't transform will make it all available to you. So for log analytics, especially with cloud native, you need this type of technology and you need to stop, it's like uh it feels so good when you stop hitting your head against the wall. Right? This detail process that this type of scale just doesn't work. So that's exactly we're delivering the second use case uh and that's with using elastic KPI but also using sequel to go after the same data representation. And we come out with machine learning. You can also do anomaly detection on the same data representation. So for a log uh analytic use case series devops setups. It's a huge value problem now the same platform because it has sequel exposed. You can do just what we use the term is agile B. I people are using you think about look or tableau power bi I uh metabolic. I think of all these toolsets that people want to give and uh and use your business or coming back to the centralized team every single week asking for new datasets. And they have to be set up like a data set. They have to do an e tail process that give access to that data where because of the way just landed in the bucket. If you have access to that with role based access, I can literally get you access that with your tool set, let's say Tableau looker. You know um these different data sets literally in five minutes and now you're off and running and if you want a new dataset they give another virtual and you're off and running. But with full governance so we can use to be in B I either had self service or centralized. Self service is kind of out of control, but we can move fast and the centralized team is it takes me months but at least I'm in control. We allow you do both fully governed but self service. Right. I got to >>have lower. I gotta excel. All right. And it's like and that's the trade off on each of the pieces of the triangle. Right. >>And they make it easy, we'll just put in a data source and you're done. But the problem is you have to E T L the data source. And that's what takes the three weeks to three months in enterprise and we do it virtually in five minutes. So now the third is actually think about um it's kind of a combination of the two. Think about uh you love the beers and diaper stories. So you know, think about early days of terror data where they look at sales out data for business and they were able to look at all the sales out data, large relational environment, look at it, they crunch all these numbers and they figured out by different location of products and the start of they sell more sticker things and they came up with an analogy which everyone talked about beers and diapers. If you put it together, you sell more from why? Because afternoon for anyone that has kids, you picked up diapers and you might want to grab a beer of your home with the kids. But that analogy 30 years ago, it's now well we're what's the shelf space now for approximate company? You know it is the website, it's actually what's the data coming from there. It's actually the app logs and you're not capturing them because you can't in these environments or you're capturing the data. But everyone's telling, you know, you've got to do an E. T. L. Process to keep less data. You've got to select, you got to be very specific because it's going to kill your budget. You can't do that with elastic or Splunk, you gotta keep less data and you don't even know what the questions are gonna ask with us, Bring all the app logs just land in S. three or glacier which is the most it's really shoulders of giants right? There's not a better platform cost effectively security resilience or through but to think about what you can stream and the it's the best queuing platform I've ever seen in the industry just landed there. And it's also very cost effective. We also compress the data. So by doing that now you match that up with actually relatively small amount of relational data and now you have the vaccine being data. But instead it's like this users using that use case and our top users are always, they start with this one then they use that feature and that feature. Hey, we just did new pricing is affecting these clients and that clients by doing this. We get that. But you need that data and people aren't able to capture it with the current platforms. A data lake. As long as you can make it available. Hot is a way to do it. And that's what we're doing. But we're unique in that. Other people are making GTL IT and put it in a in 19 seventies and 19 eighties data format called a schema. And we avoided that because we basically make S three a hot and elected. >>So okay. So I gotta I want to, I want to land on that for a second because I think sometimes people get confused. I know I do sometimes without chaos or it's like sometimes don't know where to put you. I'm like okay observe ability that seems to be a hot space. You know of course log analytics as part of that B. I. Agile B. I. You called it but there's players like elastic search their star burst. There's data, dogs, data bricks. Dream EOS Snowflake. I mean where do you fit where what's the category and how do you differentiate from players like that? >>Yeah. So we went about it fundamentally different than everyone else. Six years ago. Um Tom hazel and his band of merry men and women came up and designed it from scratch. They may basically yesterday they purposely built make s free hot analytic environment with open A. P. I. S. By doing that. They kind of changed the game so we deliver upon the true promises. Just put it there and I'll give you access to it. No one else does that. Everyone else makes you move the data and put it in schema of some format to get to it. And they try to put so if you look at elasticsearch, why are we going after? Like it just happens to be an easy logs are overwhelming. You once you go to cloud native, you can't afford to put it in a loose seen the elk stack. L is for loosen its inverted index. Start small. Great. But once you now grow it's now not one server. Five servers, 15 servers, you lose a server, you're down for three days because you have to rebuild the whole thing. It becomes brittle at scale and expensive. So you trade off I'm going to keep less or keep less either from retention or data. So basically by doing that so elastic we're not we have no elastic on that covers but we allow you to well index the data in S. Tree and you can access it directly through a cabana interface or an open search interface. Api >>out it's just a P. >>It's open A P. I. S. It's And by doing that you've avoided a whole bunch of time cost, complexity, time of your team to do it. But also the time to results the delays of doing that cost. It's crazy. We're saving 50-80 hard dollars while giving you unlimited retention where you were dramatically limited before us. And as a managed service you have to manage that Kind of Clunky. Not when it starts small, when it starts small, it's great once at scale. That's a terrible environment to manage the scale. That's why you end up with not one elasticsearch cluster, dozens. I just talked to someone yesterday had 125 elasticsearch clusters because of the scale. So anyway, that's where elastic we're not a Mhm. If you're using elastic it scale and you're having problems with the retired off of cost time in the, in the scale, we become a natural fit and you don't change what your end users do. >>So the thing, you know, they had people here, this will go, wow, that sounds so simple. Why doesn't everybody do this? The reason is it's not easy. You said tom and his merry band. This is really hard core tech. Um and it's and it's it's not trivial what you've built. Let's talk about your secret sauce. >>Yeah. So it is a patented technology. So if you look at our, you know, component for architecture is basically a large part of the 90% of value add is actually S. Three, I gotta give S three full kudos. They built a platform that we're on shoulders of giants. Um But what we did is we purpose built to make an object storage a hot alec database. So we have an index, like a database. Um And we basically the data you bring a refinery to be able to do all the advanced type of transformation but all virtually done because we're not changing the source of record, we're changing the virtual views And then a fabric allows you to manage and be fully elastic. So if we have a big queries because we have multiple clients with multiple use cases, each multiple petabytes, we're spending up 1800 different nodes after a particular environment. But even with all that we're saving them 58%. But it's really the patented technology to do this, it took us six years by the way, that's what it takes to come up with this. I come upon it, I knew the founder, I've known tom tom a stable for a while and uh you know his first thing was he figured out the math and the math worked out. Its deep tech, it's hard tech. But the key thing about it is we've been in market now for two years, multiple use cases in production at scale. Um Now what you do is roadmap, we're adding a P. I. So now we have elasticsearch natural proofpoint. Now you're adding sequel allows you open up new markets. But the idea for the person dealing with, you know, so we believe we deliver on the true promise of Data Lakes and the promise of Data lakes was put it there, don't focus on transferring. It's just too hard. I'll get insights out and that's exactly what we do. But we're the only ones that do that everyone else makes you E. T. L. At places. And that's the innovation of the index in the refinery that allows the index in place and give virtual views in place at scale. Um And then the open api is to be honest, uh I think that's a game. Give me an open api let me go after it. I don't know what tool I'm gonna use next week every time we go into account they're not a looker shop or Tableau Sharp or quick site shop there, all of them and they're just trying to keep up with the businesses. Um and then the ability to have role based access where actually can give, hey, get them their own bucket, give them their own refinery. As long as they have access to the data, they can go to their own manipulation ends up being >>just, >>that's the true promise of data lakes. Once we come out with machine learning next year, now you're gonna rip through the same embassy and the way we structured the data matrices. It's a natural fit for things like tensorflow pytorch, but that's, that's gonna be next year just because it's a different persona. But the underlining architecture has been built, what we're doing is trying to use case that time. So we worked, our clients say it's not a big bang. Let's nail a use case that works well. Great R. O. I great business value for a particular business unit and let's move to the next. And that's how I think it's gonna be really. That's what if you think about gardener talks about, if you think about what really got successful in data, where else in the past? That's exactly it wasn't the big bang, it was, let's go and nail it for particular users. And that's what we're doing now because it's multi model, there's a bunch of different use cases, but even then we're focusing on these core things that are really hard to do with other relational only environments. Yeah, I >>can see why you're still because you know, you haven't been well, you and I have talked about the api economy for forever and then you've been in the storage world so long. You know what a nightmare is to move data. We gotta, we gotta jump. But I want to ask you, I want to be clear on this. So you are your cloud cloud Native talked to frank's Lukman maybe a year ago and I asked him about on prem and he's like, no, we're never doing the halfway house. We are cloud all the >>way. I think >>you're, I think you have a similar answer. What what's your plan on Hybrid? >>Okay. We get, there's nothing about technology, we can't go on, but we are 100 cloud native or only in the public cloud. We believe that's a trend line. Everyone agrees with us, we're sticking there. That's for the opportunity. And if you can run analytics, There's nothing better than getting to the public cloud like Amazon and he was actually, that were 100 cloud native. Uh, we love S three and what would be a better place to put this is put the next three and we just let you light it up and then I guess if I'm gonna add the commercial and buy it through amazon marketplace, which we love that business model with amazon. It's >>great. Ed thanks so much for coming back in the cube and participating in the startup showcase. Love having you and best of luck. Really exciting. >>Hey, thanks again, appreciate it. >>All right, thank you for watching everybody. This is Dave Volonte for the cube. Keep it right there.

[Music] welcome back to red hat summit 2021 my name is dave vellante and you're watching the cube where we go out to the events and extract the signal from the noise of course virtually in this case and i'm pleased to welcome victor carumpus who is the senior vice president of digital banking at bank mandiri coming in from jakarta welcome to the cube victor great to see you hi dave great to see you and great to be invited here thank you yeah you're very welcome i i wonder if you could just give us an overview of the bank maybe talk a little bit about your strategy your customers you know what the what the focus is of your company and what your role is there okay uh maybe i'm i'll give a short overview about bang mandir itself so bang money is a state-owned enterprise owned by the government but we also public company currently we already have a very big distribution channel in so uh you know indonesia is an island country it's very huge country so we are we are representing all over indonesia from province of aceh and i'm up to profits of papua and we have about 2600 branches all over indonesia and about uh 15 000 atms all over indonesia so bangladesh itself is focused on a lot of segment customers like indonesia from the corporate side small medium enterprise and also retail banking now uh we are we are currently focused in turning ourselves to become having to have more digital capability and currently in our uh current situations actually it is very good uh about 95 percent of our transactions is already coming from the electronic channel so it's only about five percent that coming from the branches but we know that this is still a journey uh and we are building more digital capability and features and functions on our digital channels to our customer got it um okay and so your your your digital journey kind of coincides i guess in a way with your your your container uh adoption journey uh i think that started a few years ago um and so maybe you could talk a little bit about that i i mean in thinking about modernizing your application portfolio obviously containers been around forever but they weren't packaged in a way that could actually be easily you know utilized and now you're seeing people in i.t roles like yourself really leaning in maybe you could talk about some of the technology considerations that impacted that desire to actually leverage containers i think uh first it's about the scalability because with a monolithic architecture it's kind of difficult to scale up for only specific features by doing container microservices we have options to scale up in a very fast way because one of the features is auto scaling on the container architectures uh one monitor is a very focused on the transaction banking so you might say bangladesh is supporting the economy of the country because in a in any given time in bangladesh we we're running about four thousand transactions per seconds that's a huge transactions number and have having said that uh our channel like i told you already running about 95 percent of the transactions so scalability is always important for us because especially like like now is the the in indonesia is a festive month it's a ramadan month where muslim is actually doing fasting but at the same time actually there's a lot of needs and people do a lot of transactions and on this kind of festive seasons the transition can be increased up to 40 or 50 suddenly and that's kind of things always happen in bangladesh and we must be ready and we must have a scalability on demand now containerization is enabling us to do that other thing is about flexibility because on the old days actually when we want to set up a new environment it's very difficult and takes a lot of time and that's affecting the time to market our products by doing the containerizations and putting it on a ci cd continuous integration called the development plan platform we are we call devsecops platform that kind of things becoming automatic because we set up the devsecos platform and the third one is the consistency actually so by by doing the contact investigations we can put the the apis on our back-end apis in the container itself and actually it's deliverable environment and a consistent experience to our customer because for example we promise our customer that every transaction should be finished within two seconds from their mobile banking up to our hosts and back forward to their mobile banking is only two seconds so that kind of thing is driving us to move to the current technology which we're using containerization and micro services great okay so 4 000 transactions per second you can't can't do that on erc20 ethereum for all you crypto fans out there that's that's pretty high volume uh and if i understand it correctly victor your role is really to envision this digital environment and then ultimately make it happen from a technology standpoint is that correct that's product that's got it yeah so okay so you now have a number of of product lines and teams you're using the same container platform maybe you could share with our audience some of the best practices and learnings that that you've taken away on this journey so i think first of all we can reuse a lot of components by doing this containerization platform is different when we still use the monolithic platform like the application server of java application server uh by using containerization actually uh be providing like a service banking as a service so whenever we build a new channel for example the first one we built a new service for example like a fun transfer service but when we create another channel for example a corporate banking electronic channel or we create another uh let's say wealth management channel whatever we already built before can be reusable instantly by using this technology so uh if i might say that actually there is a lot of best practices coming by using this platform and my team get a lot of benefit in terms of faster development time and also they can deliver the product and service in a high quality manner minimize the number of errors as well you know there's a lot of choices out there obviously i wonder if you could share what led you to the choice of red hat and open shift okay so first of all before we choose the platform actually we also comparing ourselves with the with the fintechs and also with the big tech in indonesia as well so we see we see that actually they already start using kubernetes and uh their platform is quite stable and even they can support about 90 to 100 million of customers without any issues at all so when we see this uh we choose a lot of we learn about a lot of platform and we finally choose opencv because we think that openshift and we we already do our research openshift is quite stable and for banks like us that have for having 4500 transaction per seconds stability is number one uh availability is also number one now uh having said that after doing our research we choose openshift and we implemented openshift in our environment because we promise our customers to provide 99.95 percent uh availability can i just i'm sorry to interrupt you victor can you just repeat that you cut out a little bit so you you said you you promised your customers to deliver and then you cut out a little bit can you just repeat what you just said there okay so we're giving a promise to our to our customer providing a 99.95 availability so this is the starting point of our channel sure in the efficiency we have efficient also to providing four nines which is 99.99 but i mean the starting point is 99.95 and because we have that the demand that requirement that's one of the reason we choose the openshift and red hat as our technology stack platform got it okay and so i have a question um what was it like in terms of just the skills and the adoption uh for your developers uh was it was it a big gap to go from where you were to you know where you are today did you have to what kind of training did you have to do did you have to do any sort of outsourcing to accelerate that maybe you could describe that how you close that skills gap so definitely in the beginning is quite challenging because although they are using modern languages like jaffa or kotlin but uh to understand the concept and to design correctly yes we we did a lot of training to them uh it takes a it takes me about three months to give them the proper training uh in terms of building the right uh microservices platform and also to building modular architecture in terms of the customer channel because this will be the fundamental when you build it correctly in the beginning and actually at the later point you will enjoy the benefit so the first three months actually is training and doing research and development and doing a lot of trial and errors but after the three months actually we already have the right technology stack have the right models and our devsecops is already working then actually after that the speed is very fast because uh it sprints uh we do agile way of working the agiles dlc it's only one month so every one month we already have new features coming in so that's what we call a huge transformation a digital transformation inside of our bank it's three months actually not bad i mean i would i would have thought on average it's going to take five or six months to get people up to speed so three months is pretty good and i'm also inferring that you weren't just paving the cow path you weren't just saying okay let's take our traditional and then you know re refactor it to digital you had to re-envision what digital looked like because the digital is different uh than the traditional uh so so that's actually pretty good uh ramp rate i wonder if you could just go ahead and comment if you could because when you say about uh revamp so actually it's not on the id side not only but also the business side we implement new way as well so actually if clearly they're implementing a new model so they're using a design thinking and also a co-creation model where now when we building a product so we're not writing the old product in a new way no we totally building it from from scratch and involving our key customer and our stakeholder when we're building this product so actually we implementing new models what we call design thinking and also uh co-creation with our customer so that's actually changing the face of the customer electronic channel a lot and and actually when we when we want to to deploy we invite our customer to test it first we call it like usability testing if they like it we continue to design if they they don't like it they give us a feedback how they would like it to be changed and and that's we appreciate our customer feedback because customers experience is everything now yeah so so the product can be accepted if the experience on that product is really making customer uh solving their problem solving the customer problem and making them enjoying uh doing transactions in our mobile banking product i think this is a really important point for people to understand so you weren't just paving the cow path i call it you're taking the old and and just trying to refactor it and make it exactly turn it into digital you had to really think about the business the business processes the dependencies the customer experience and then bring it back um what have been some of the business outcomes of this initiative and maybe you could we then after that we can get into some of the the future plans so so the outcome uh i think this journey uh since last year uh not last year actually since no october 2019 we already started the journey uh what took us by surprise is actually the pandemic uh suddenly the first three months when we have the pandemic of coffee we are being forced to close a lot of branches for temporary because we want to avoid the pandemic situations and that time actually the the demand using our digital channel is increasing a lot but because we already prepared actually we get the benefit one of the thing is uh the business benefit is relating so during the pandemic nobody can come to the branch and mostly the account opening actually happening online so uh we even got about 9000 account opening per day which is something that we are not imagining before so uh the benefit is very clear by using this this technology actually enabling us to provide digital capability for our customer and enabling us to open more accounts we see ourselves can grow even not linear but exponentially grow by using this platform uh talking about that indonesia is a is a huge country with we have about 200 250 million populations and actually there's still a lot of people is not having a bank account at all now by doing this actually we open opportunity doing financial inclusion for those people that need a banking account now they can reach us by using the digital platform as well yeah that's an awesome story and it goes back to the to the reason the real motivator for for moving to kubernetes and containers was scale uh and and you know it's you obviously started your digital journey prior to the pandemic but a lot of customers and i'm sure you as well were were forced to speed up a portion anyway of the digital component uh because of the pandemic like you said you couldn't people couldn't walk into the branches so but now you've got some more time to think about that journey you've had a lot of learnings 2020 was like a petri dish of experimentation but but in real time having to serve customers what's the future look like for the bank's technology journey okay so basically we uh we are not stopping only on the retail side yeah uh we want to redefine our customer journey also on the wholesale side and also on the small medium enterprise there is still a lot of things that need to be done uh and required by the customer actually so uh on the on the on the sme side we want to give them easier access uh for uh financing their businesses i think when we are back to the new normal uh the business need to have funding for for starting their business again so building an sme platform for them will will help a lot and will help the country as well on the retail side actually like i told you uh we are focusing on the more financial inclusion because uh i give you example right uh from the 230 million of indonesians uh populations i think by today maybe it's only about 50 million customers that already have a banking account so there is still a lot of people that need an access faster and cheaper and more efficient way for doing banking transactions so that's this also will become our focus and the last part is actually corporate what we see now a lot of the corporate require us to open uh api connectivity doing open banking with them the government actually the central bank supporting it supporting all the banks they are trying to create an api playbooks now and then they create they want to create an api standard for all the core all the use corporate also can connect it to the bank directly using api so this is also our focus because it will help the country economy when the economy costs the transaction costs getting more efficient getting more cheaper and there's a lot of transaction can be supported by our bank as well so i think i think that's the the future that we are imagining and i'm really hope that the pandemi will be finished and we come back to the to the new normal and we can support more transactions for this country yeah you're here to that i call it the new abnormal but so this is this is a great story everybody loves to talk about disruption we do as well and but people think oh it's out with out with the old in with the new and it's not like that this is a great story victor of uh of an established incumbent that is modernizing its its applications and its digital experience and of course the incumbent has the advantage of it's a real business it has customers that has a data it has experiences it and if it can modernize its infrastructure and and it's in its application portfolio it actually has an advantage because it's got way more features way more data way more customers and more resources so victor thanks so much for coming on thecube i really appreciate you sharing your story thank you dave thank you for inviting me thank you that was our pleasure and thank you for watching red hat summit 21 this is thecube you

>>from around the globe. It's the Cube with digital coverage of biz ops Manifesto unveiled. Brought to you by Biz Ops Coalition. Hey, Welcome back, everybody. Jeffrey here with the Cube. We're coming to you from our Palo Alto studios. And welcome back to this event. Is the biz Opps Manifesto unveiling? So the biz Opps manifesto and the biz Opps coalition have been around for a little while, But today's the big day. That's kind of the big public unveiling are excited to have some of the foundational people that put their put their name on the dotted line, if you will, to support this initiative to talk about why that initiative is so important. And so the next guest, we're excited to have his doctor, Mick Kirsten. He is the founder and CEO of Task Top. Make great to see you coming in from Vancouver, Canada, I think. Right. >>Yes. Great to be here, Jeff. Thank you. Absolutely. >>I hope your air is a little better out there. I know you had some of the worst air of all of us a couple a couple of weeks back, so hopefully things air, uh, getting a little better. And we get those fires under control? >>Yeah, Things have cleared up now, so yeah, it's good. It's good to be close to the U. S. And it's gonna have the Arabic clean as well. >>Absolutely. So let's let's jump into it. So you you've just been an innovation guy forever Starting way back in the day and Xerox Park. I was so excited to do an event at Xerox Park for the first time last year. I mean that that to me represents along with Bell Labs and and some other, you know, kind of foundational innovation and technology centers. That's got to be one of the greatest one. So I just wonder if you could share some perspective of getting your start there at Xerox Parc. You know, some of the lessons you learn and what you've been ableto kind of carry forward from those days. >>Yeah, I was fortunate. Joined Xerox Park in the computer science lab there at a very early point in my career, and to be working on open source programming languages. So back then, and the computer science lab where some of the inventions around programming around software development names such as Object of programming and ah, lot of what we had around really modern programming levels construct. Those were the teams that had the fortune of working with and really our goal waas. And of course, there's a Z. You know, this, uh, there's just this DNA of innovation and excitement and innovation in the water. And really, it was the model that was all about changing the way that we work was looking at for how we could make it 10 times easier to write. Code like this is back in 99 we were looking at new ways of expressing especially business concerns, especially ways of enabling people who are who want to innovate for their business, to express those concerns in code and make that 10 times easier than what that would take. So we created a new open source programming language, and we saw some benefits, but not quite quite what we expected. I then went and actually joined Charles Stephanie that former chief actor Microsoft, who is responsible for I actually got a Microsoft word as a out of Xerox Parc and into Microsoft and into the hands of Bill Gates and the company I was behind the whole office suite and his vision and the one I was trying to execute with working for him was to, you know, make Power point like a programming language, make everything completely visual. And I realized none of this was really working, that there was something else fundamentally wrong that programming languages or new ways of building software like Let's try to do with Charles around intentional programming. That was not enough. >>That was not enough. So you know, the agile movement got started about 20 years ago, and we've seen the rise of Dev ops and really this kind of embracing of of, of sprints And, you know, getting away from M. R. D s and P. R. D s and these massive definitions of what we're gonna build and long billed cycles to this iterative process. And that's been going on for a little while. So what was still wrong? What was still missing? Why the Biz Ops Coalition? Why the biz ops manifesto? >>Yeah, so I basically think we nailed some of the things that the programming language levels of teams can have. Effective languages deployed softened the club easily now right and at the kind of process and collaboration and planning level agile two decades decades ago was formed. We were adopting all the all the teams I was involved with on. It's really become a solved problem. So agile tools, agile teams actually of planning are now very mature and the whole challenges when organizations try to scale that. And so what I realized is that the way that Agile was scaling across teams and really scaling from the Technology Party organization to the business was just completely flawed. The agile teams had one set of doing things. One set of metrics, one set of tools and the way that the business was working was planning was investing in technology was just completely disconnected and using a a whole different set of measures. It's pretty interesting because I think it's >>pretty clear from the software development teams in terms of what they're trying to deliver, because they've got a feature set right and they've got bugs and it's easy. It's easy to see what they deliver, but it sounds like what you're really honing in on is is disconnect on the business side in terms of, you know, is it the right investment you know. Are we getting the right business? R o I on this investment? Was that the right feature? Should we be building another feature or shall we building a completely different products? That so it sounds like it's really a core piece of this is to get the right measurement tools, the right measurement data sets so that you can make the right decisions in terms of what you're investing, you know, limited resource is you can't Nobody has unlimited resources and ultimately have to decide what to do, which means you're also deciding what not to dio. It sounds like that's a really big piece of this of this whole effort. >>Yeah, Jeff, that's exactly it. Which is the way that the adult measures their own way of working is very different from the way that you measure business outcomes. The business outcomes are in terms of how happy your customers are. Are you innovating fast enough to keep up with the pace of, ah, rapidly changing economy, rapidly changing market and those are those are all around the customer. And so what? I learned on this long journey of supporting many organizations transformations and having them trying to apply those principles vigilant develops that those are not enough. Those measures technical practices, those measures, technical excellence of bringing code to the market. They don't actually measure business outcomes. And so I realized that really was much more around having these entwined flow metrics that are customer centric and business centric and market centric where we needed to go. So I want to shift gears >>a little bit and talk about your book because you're also a best selling author project a product, and and you you brought up this concept in your book called The Flow Framework. And it's really interesting to me because I know, you know, flow on one hand is kind of a workflow in the process flow, and you know that's how things get done and and embrace the flow. On the other hand, you know, everyone now in a little higher level, existential way is trying to get into the flow right into the workflow and, you know not be interrupted and get into a state where you're kind of your highest productivity, you know, kind of your highest comfort. Which floor you talking about in your book, or is it a little bit of both. >>That's a great question, is it's not what I gotta ask very often, cause me, it's It's absolutely both. So the thing that we want to get that we've learned how toe and, uh, master individual flow, that there's this beautiful book by me Holly teachings mentality. There's a beautiful Ted talk about him as well, about how we can take control of our own flow. So my question with the book with project surprise, How can we bring that to entire teams and really entire organizations? How come we have everyone contributing to a customer outcome? And this is really what if you go to the bazaar manifesto? It says, I focus on Out comes on using data to drive, whether we're delivering those outcomes rather than a focus on proxy metrics such as How quickly did we implement this feature? And now it's really how much value did the customs of the future and how quickly did we learn? And how quickly did you use that data to drive to that next outcome? Really, that with companies like Netflix on, like Amazon, have mastered, how do we get that every large organization, every idea, organization and make everyone be a softer innovator. So it's to bring that on the concept of flow to these entering value streams. And the fascinating thing is, we've actually seen the data. We've been able to study a lot of value streams. We see when flow increases, when organizations deliver value to a customer faster developers actually become more happy. So things like that implying that promotes course rise. And we've got empirical data for this. So that beautiful thing to me is that we've actually been able thio, combine these two things and and see the results in the data that you increased flow to the customer, your development or more happy. I >>love it. I love it, right, because we're all more. We're all happier when we're in the flow and we're all more productive winner in the flow. So I that is a great melding of two concepts. But let's jump into the into the manifesto itself a little bit. And you know, I love that you know, that took this approach really of having kind of four key values, and he gets 12 key principles and I just want to read a couple these values because when you read them, it sounds pretty brain dead, right? Of course. Right. Of course, you should focus on business outcomes. Of course, you should have trust and collaboration. Of course, you should have data based decision making processes and not just intuition or, you know, whoever is the loudest person in the room on toe, learn and respond and pivot. But >>what's the >>value of actually just putting them on a piece of paper? Because again, this is not this. These are all good positive things, right? When when somebody reads these to you or tells you these or sticks it on the wall? Of course. But unfortunately, of course, isn't always enough. >>No, I think what's happened is some of these core principles originally from the agile manifested two decades ago. The whole Dev ops movement of the last decade off flow feedback and continue learning has been key. But a lot of organizations, especially the ones undergoing transformations, have actually gone a very different way, right? The way that they measure value in technology innovation is through costs For many organizations, the way that they actually are looking at at their moving to cloud is actually is a reduction in costs, whereas the right way of looking at moving the cloud is how much more quickly can we get to the value to the customer? How quickly can we learn from that? And how could quickly can we drive the next business outcome? So, really, the key thing is to move away from those old ways of doing things that funding projects and call centers to actually funding and investing in outcomes and measuring outcomes through these flow metrics, which in the end are your fast feedback for how quickly you're innovating for your customer. So these things do seem, you know, very obvious when you look at them. But the key thing is what you need to stop doing. To focus on these, you need to actually have accurate real time data off how much value your phone to the customer every week, every month, every quarter. And if you don't have that, your decisions are not given on data. If you don't know what your bottle like, it's. And this is something that in the decades of manufacturing car manufacturers, other manufacturers master. They always know where the bottom back in their production processes you ask, uh, random. See, I all want a global 500 company where the bottleneck is, and you won't get it there. Answer. Because there's not that level of understanding. So have to actually follow these principles. You need to know exactly where you follow like is because that's what's making your developers miserable and frustrated on having them context, which on thrash So it. The approach here is important, and we have to stop doing these other things right. >>There's so much. They're a pack. I love it, you know, especially the cloud conversation, because so many people look at it wrong as a cost saving device as opposed to an innovation driver, and they get stuck, they get stuck in the literal. And, you know, I think the same thing always about Moore's law, right? You know, there's a lot of interesting riel tech around Moore's law and the increasing power of microprocessors. But the real power, I think in Moore's laws, is the attitudinal change in terms of working in a world where you know that you've got all this power and what will you build and design? E think it's funny to your your comment on the flow in the bottleneck, right? Because because we know manufacturing assumes you fix one bottleneck. You move to your next one, right, You always move to your next point of failure. So if you're not fixing those things, you know you're not. You're not increasing that speed down the line unless you can identify where that bottleneck is, or no matter how Maney improvements you make to the rest of the process, it's still going to get hung up on that one spot. >>That's exactly, and you also make it sound so simple. But again, if you don't have the data driven visibility of where the bottleneck is. And but these bottlenecks are just as you said, if it's just lack, um, all right, so we need to understand is the bottleneck, because our security use air taking too long and stopping us from getting like the customer. If it's that automate that process and then you move on to the next bottleneck, which might actually be that deploy yourself through the clouds is taking too long. But if you don't take that approach of going flow first rather than again the sort of way cost production first you have taken approach of customer centric city, and you only focus on optimizing cost. Your costs will increase and your flow will slow down. And this is just one, these fascinating things. Whereas if you focus on getting back to the customer and reducing your cycles on getting value your flow time from six months to two weeks or 21 week or two event as we see with tech giants, you actually could both lower your costs and get much more value. Of course, get that learning going. So I think I've I've seen all these cloud deployments and modernizations happen that delivered almost no value because there was such a big ball next up front in the process. And actually the hosting and the AP testing was not even possible with all of those inefficiencies. So that's why going flow first rather than costs. First, there are projects versus Sochi. >>I love that and and and and it begs, repeating to that right within a subscription economy. You know you're on the hook to deliver value every single month because they're paying you every single month. So if you're not on top of how you delivering value, you're going to get sideways because it's not like, you know, they pay a big down payment and a small maintenance fee every month. But once you're in a subscription relationship, you know you have to constantly be delivering value and upgrading that value because you're constantly taking money from the customers. It's it's such a different kind of relationship, that kind of the classic, you know, Big Bang with the maintenance agreement on the back end really important. >>Yeah, and I think in terms of industry ship, that's it. That's what catalyzed this industry shift is in this SAS that subscription economy. If you're not delivering more and more value to your customers, someone else's and they're winning the business, not you. So one way we know is that divide their customers with great user experiences. Well, that really is based on how many features you delivered or how much. How about how many quality improvements or scaler performance improvements you delivered? So the problem is, and this is what the business manifesto was was the forefront of touch on is, if you can't measure how much value delivered to a customer, what are you measuring? You just back again measuring costs, and that's not a measure of value. So we have to shift quickly away from measuring costs to measuring value to survive in in the subscription economy. Mick, >>we could go for days and days and days. I want to shift gears a little bit into data and and a data driven, um, decision making a data driven organization. Because right day has been talked about for a long time. The huge big data mean with with Hadoop over over several years and data warehouses and data lakes and data, oceans and data swamps and you go on and on, it's not that easy to do right. And at the same time, the proliferation of data is growing exponentially were just around the corner from from I, O. T and five G. So now the accumulation of data at machine scale again this is gonna overwhelm, and one of the really interesting principles that I wanted to call out and get your take right is today's organizations generate mawr data than humans can process. So informed decisions must be augmented by machine learning and artificial intelligence. I wonder if you can again, you've got some great historical perspective reflect on how hard it is to get the right data to get the data in the right context and then to deliver to the decision makers and then trust the decision makers to actually make the data and move that down. You know, it's kind of this democratization process into more and more people and more and more frontline jobs, making more and more of these little decisions every day. >>Yeah, and Jeff, I think the front part of what you said are where the promises of big data have completely fallen on their face into these swamps. As you mentioned, because if you don't have the data and the right format, you can connect, collected that the right way, you're not. Model it that way the right way. You can't use human or machine learning on it effectively. And there have been the number of data, warehouses and a typical enterprise organization, and the sheer investment is tremendous. But the amount of intelligence being extracted from those is a very big problem. So the key thing that I've known this is that if you can model your value streams so you actually understand how you're innovating, how you're measuring the delivery value and how long that takes. What is your time to value through these metrics? Like for the time you can actually use both. You know the intelligence that you've got around the table and push that balance as it the assay, far as you can to the organization. But you can actually start using that those models to understand, find patterns and detect bottlenecks that might be surprising, Right? Well, you can detect interesting bottle next one you shift to work from home. We detected all sorts of interesting bottlenecks in our own organization that we're not intuitive to me that had to do with more senior people being overloaded and creating bottlenecks where they didn't exist. Whereas we thought we were actually organization. That was very good at working from home because of our open source route. So the data is highly complex. Software Valley streams are extremely complicated, and the only way to really get the proper analysts and data is to model it properly and then to leverage these machine learning and AI techniques that we have. But that front, part of what you said, is where organizations are just extremely immature in what I've seen, where they've got data from all the tools, but not modeled in the right way. >>Well, all right, so before I let you go, you know? So you get a business leader he buys in. He reads the manifesto. He signs on the dotted line. He says, Mick, how do I get started? I want to be more aligned with With the development teams, you know, I'm in a very competitive space. We need to be putting out new software features and engage with our customers. I want to be more data driven. How do I get started? Well, you know, what's the biggest inhibitor for most people to get started and get some early winds, which we know is always the key to success in any kind of a new initiative, >>right? So I think you can reach out to us through the website. Uh, on the is a manifesto, but the key thing is just it's exactly what you said, Jeff. It's to get started and get the key wins. So take a probably value stream. That's mission critical. It could be your new mobile Web experiences, or or part of your cloud modernization platform where your analysts pipeline. But take that and actually apply these principles to it and measure the entire inflow of value. Make sure you have a volumetric that everyone is on the same page on, right. The people on the development teams that people in leadership all the way up to the CEO and one of the where I encourage you to start is actually that enter and flow time, right? That is the number one metric. That is how you measure whether you're getting the benefit of your cloud modernization. That is the one metric that even Cockcroft when people I respect tremendously put in his cloud for CEOs Metric 11 way to measure innovation. So basically, take these principles, deployed them on one product value stream measure into and flow time on. Then you'll actually you well on your path to transforming and to applying the concepts of agile and develops all the way to the business to the way in your operating model. >>Well, Mick, really great tips, really fun to catch up. I look forward to a time when we can actually sit across the table and and get into this, because I just I just love the perspective. And, you know, you're very fortunate to have that foundational, that foundational base coming from Xerox parc. And it's, you know, it's a very magical place with a magical history. So the to incorporate that and to continue to spread that wealth, you know, good for you through the book and through your company. So thanks for sharing your insight with us today. >>Thanks so much for having me, Jeff. Absolutely. >>Alright. And go to the biz ops manifesto dot org's Read it. Check it out. If you want to sign it, sign it. They'd love to have you do it. Stay with us for continuing coverage of the unveiling of the business manifesto on the Cube. I'm Jeffrey. Thanks for watching. See you next time.

>>from around the globe. It's the Cube covering >>space and cybersecurity. Symposium 2020 hosted by Cal Poly >>Over On Welcome to this Special virtual conference. The Space and Cybersecurity Symposium 2020 put on by Cal Poly with support from the Cube. I'm John for your host and master of ceremonies. Got a great topic today in this session. Really? The intersection of space and cybersecurity. This topic and this conversation is the cybersecurity workforce development through public and private partnerships. And we've got a great lineup. We have Jeff Armstrong's the president of California Polytechnic State University, also known as Cal Poly Jeffrey. Thanks for jumping on and Bang. Go ahead. The second director of C four s R Division. And he's joining us from the office of the Under Secretary of Defense for the acquisition Sustainment Department of Defense, D O D. And, of course, Steve Jake's executive director, founder, National Security Space Association and managing partner at Bello's. Gentlemen, thank you for joining me for this session. We got an hour conversation. Thanks for coming on. >>Thank you. >>So we got a virtual event here. We've got an hour, have a great conversation and love for you guys do? In opening statement on how you see the development through public and private partnerships around cybersecurity in space, Jeff will start with you. >>Well, thanks very much, John. It's great to be on with all of you. Uh, on behalf Cal Poly Welcome, everyone. Educating the workforce of tomorrow is our mission to Cal Poly. Whether that means traditional undergraduates, master students are increasingly mid career professionals looking toe up, skill or re skill. Our signature pedagogy is learn by doing, which means that our graduates arrive at employers ready Day one with practical skills and experience. We have long thought of ourselves is lucky to be on California's beautiful central Coast. But in recent years, as we have developed closer relationships with Vandenberg Air Force Base, hopefully the future permanent headquarters of the United States Space Command with Vandenberg and other regional partners, we have discovered that our location is even more advantages than we thought. We're just 50 miles away from Vandenberg, a little closer than u C. Santa Barbara, and the base represents the southern border of what we have come to think of as the central coast region. Cal Poly and Vandenberg Air force base have partner to support regional economic development to encourage the development of a commercial spaceport toe advocate for the space Command headquarters coming to Vandenberg and other ventures. These partnerships have been possible because because both parties stand to benefit Vandenberg by securing new streams of revenue, workforce and local supply chain and Cal Poly by helping to grow local jobs for graduates, internship opportunities for students, and research and entrepreneurship opportunities for faculty and staff. Crucially, what's good for Vandenberg Air Force Base and for Cal Poly is also good for the Central Coast and the US, creating new head of household jobs, infrastructure and opportunity. Our goal is that these new jobs bring more diversity and sustainability for the region. This regional economic development has taken on a life of its own, spawning a new nonprofit called Reach, which coordinates development efforts from Vandenberg Air Force Base in the South to camp to Camp Roberts in the North. Another factor that is facilitated our relationship with Vandenberg Air Force Base is that we have some of the same friends. For example, Northrop Grumman has has long been an important defense contractor, an important partner to Cal poly funding scholarships and facilities that have allowed us to stay current with technology in it to attract highly qualified students for whom Cal Poly's costs would otherwise be prohibitive. For almost 20 years north of grimness funded scholarships for Cal Poly students this year, their funding 64 scholarships, some directly in our College of Engineering and most through our Cal Poly Scholars program, Cal Poly Scholars, a support both incoming freshman is transfer students. These air especially important because it allows us to provide additional support and opportunities to a group of students who are mostly first generation, low income and underrepresented and who otherwise might not choose to attend Cal Poly. They also allow us to recruit from partner high schools with large populations of underrepresented minority students, including the Fortune High School in Elk Grove, which we developed a deep and lasting connection. We know that the best work is done by balanced teams that include multiple and diverse perspectives. These scholarships help us achieve that goal, and I'm sure you know Northrop Grumman was recently awarded a very large contract to modernized the U. S. I. C B M Armory with some of the work being done at Vandenberg Air Force Base, thus supporting the local economy and protecting protecting our efforts in space requires partnerships in the digital realm. How Polly is partnered with many private companies, such as AWS. Our partnerships with Amazon Web services has enabled us to train our students with next generation cloud engineering skills, in part through our jointly created digital transformation hub. Another partnership example is among Cal Poly's California Cybersecurity Institute, College of Engineering and the California National Guard. This partnership is focused on preparing a cyber ready workforce by providing faculty and students with a hands on research and learning environment, side by side with military, law enforcement professionals and cyber experts. We also have a long standing partnership with PG and E, most recently focused on workforce development and redevelopment. Many of our graduates do indeed go on to careers in aerospace and defense industry as a rough approximation. More than 4500 Cal Poly graduates list aerospace and defense as their employment sector on linked in, and it's not just our engineers and computer sciences. When I was speaking to our fellow Panelists not too long ago, >>are >>speaking to bang, we learned that Rachel sins, one of our liberal arts arts majors, is working in his office. So shout out to you, Rachel. And then finally, of course, some of our graduates sword extraordinary heights such as Commander Victor Glover, who will be heading to the International space station later this year as I close. All of which is to say that we're deeply committed the workforce, development and redevelopment that we understand the value of public private partnerships and that were eager to find new ways in which to benefit everyone from this further cooperation. So we're committed to the region, the state in the nation and our past efforts in space, cybersecurity and links to our partners at as I indicated, aerospace industry and governmental partners provides a unique position for us to move forward in the interface of space and cybersecurity. Thank you so much, John. >>President, I'm sure thank you very much for the comments and congratulations to Cal Poly for being on the forefront of innovation and really taking a unique progressive. You and wanna tip your hat to you guys over there. Thank you very much for those comments. Appreciate it. Bahng. Department of Defense. Exciting you gotta defend the nation spaces Global. Your opening statement. >>Yes, sir. Thanks, John. Appreciate that day. Thank you, everybody. I'm honored to be this panel along with President Armstrong, Cal Poly in my long longtime friend and colleague Steve Jakes of the National Security Space Association, to discuss a very important topic of cybersecurity workforce development, as President Armstrong alluded to, I'll tell you both of these organizations, Cal Poly and the N S. A have done and continue to do an exceptional job at finding talent, recruiting them in training current and future leaders and technical professionals that we vitally need for our nation's growing space programs. A swell Asare collective National security Earlier today, during Session three high, along with my colleague Chris Hansen discussed space, cyber Security and how the space domain is changing the landscape of future conflicts. I discussed the rapid emergence of commercial space with the proliferations of hundreds, if not thousands, of satellites providing a variety of services, including communications allowing for global Internet connectivity. S one example within the O. D. We continue to look at how we can leverage this opportunity. I'll tell you one of the enabling technologies eyes the use of small satellites, which are inherently cheaper and perhaps more flexible than the traditional bigger systems that we have historically used unemployed for the U. D. Certainly not lost on Me is the fact that Cal Poly Pioneer Cube SATs 2020 some years ago, and they set the standard for the use of these systems today. So they saw the valiant benefit gained way ahead of everybody else, it seems, and Cal Poly's focus on training and education is commendable. I especially impressed by the efforts of another of Steve's I colleague, current CEO Mr Bill Britain, with his high energy push to attract the next generation of innovators. Uh, earlier this year, I had planned on participating in this year's Cyber Innovation Challenge. In June works Cal Poly host California Mill and high school students and challenge them with situations to test their cyber knowledge. I tell you, I wish I had that kind of opportunity when I was a kid. Unfortunately, the pandemic change the plan. Why I truly look forward. Thio feature events such as these Thio participating. Now I want to recognize my good friend Steve Jakes, whom I've known for perhaps too long of a time here over two decades or so, who was in acknowledge space expert and personally, I truly applaud him for having the foresight of years back to form the National Security Space Association to help the entire space enterprise navigate through not only technology but Polly policy issues and challenges and paved the way for operational izing space. Space is our newest horrifying domain. That's not a secret anymore. Uh, and while it is a unique area, it shares a lot of common traits with the other domains such as land, air and sea, obviously all of strategically important to the defense of the United States. In conflict they will need to be. They will all be contested and therefore they all need to be defended. One domain alone will not win future conflicts in a joint operation. We must succeed. All to defending space is critical as critical is defending our other operational domains. Funny space is no longer the sanctuary available only to the government. Increasingly, as I discussed in the previous session, commercial space is taking the lead a lot of different areas, including R and D, A so called new space, so cyber security threat is even more demanding and even more challenging. Three US considers and federal access to and freedom to operate in space vital to advancing security, economic prosperity, prosperity and scientific knowledge of the country. That's making cyberspace an inseparable component. America's financial, social government and political life. We stood up US Space force ah, year ago or so as the newest military service is like the other services. Its mission is to organize, train and equip space forces in order to protect us and allied interest in space and to provide space capabilities to the joint force. Imagine combining that US space force with the U. S. Cyber Command to unify the direction of space and cyberspace operation strengthened U D capabilities and integrate and bolster d o d cyber experience. Now, of course, to enable all of this requires had trained and professional cadre of cyber security experts, combining a good mix of policy as well as high technical skill set much like we're seeing in stem, we need to attract more people to this growing field. Now the D. O. D. Is recognized the importance of the cybersecurity workforce, and we have implemented policies to encourage his growth Back in 2013 the deputy secretary of defense signed the D. O d cyberspace workforce strategy to create a comprehensive, well equipped cyber security team to respond to national security concerns. Now this strategy also created a program that encourages collaboration between the D. O. D and private sector employees. We call this the Cyber Information Technology Exchange program or site up. It's an exchange programs, which is very interesting, in which a private sector employees can naturally work for the D. O. D. In a cyber security position that spans across multiple mission critical areas are important to the d. O. D. A key responsibility of cybersecurity community is military leaders on the related threats and cyber security actions we need to have to defeat these threats. We talk about rapid that position, agile business processes and practices to speed up innovation. Likewise, cybersecurity must keep up with this challenge to cyber security. Needs to be right there with the challenges and changes, and this requires exceptional personnel. We need to attract talent investing the people now to grow a robust cybersecurity, workforce, streets, future. I look forward to the panel discussion, John. Thank you. >>Thank you so much bomb for those comments and you know, new challenges and new opportunities and new possibilities and free freedom Operating space. Critical. Thank you for those comments. Looking forward. Toa chatting further. Steve Jakes, executive director of N. S. S. A Europe opening statement. >>Thank you, John. And echoing bangs thanks to Cal Poly for pulling these this important event together and frankly, for allowing the National Security Space Association be a part of it. Likewise, we on behalf the association delighted and honored Thio be on this panel with President Armstrong along with my friend and colleague Bonneau Glue Mahad Something for you all to know about Bomb. He spent the 1st 20 years of his career in the Air Force doing space programs. He then went into industry for several years and then came back into government to serve. Very few people do that. So bang on behalf of the space community, we thank you for your long life long devotion to service to our nation. We really appreciate that and I also echo a bang shot out to that guy Bill Britain, who has been a long time co conspirator of ours for a long time and you're doing great work there in the cyber program at Cal Poly Bill, keep it up. But professor arms trying to keep a close eye on him. Uh, I would like to offer a little extra context to the great comments made by by President Armstrong and bahng. Uh, in our view, the timing of this conference really could not be any better. Um, we all recently reflected again on that tragic 9 11 surprise attack on our homeland. And it's an appropriate time, we think, to take pause while the percentage of you in the audience here weren't even born or babies then For the most of us, it still feels like yesterday. And moreover, a tragedy like 9 11 has taught us a lot to include to be more vigilant, always keep our collective eyes and ears open to include those quote eyes and ears from space, making sure nothing like this ever happens again. So this conference is a key aspect. Protecting our nation requires we work in a cybersecurity environment at all times. But, you know, the fascinating thing about space systems is we can't see him. No, sir, We see Space launches man there's nothing more invigorating than that. But after launch, they become invisible. So what are they really doing up there? What are they doing to enable our quality of life in the United States and in the world? Well, to illustrate, I'd like to paraphrase elements of an article in Forbes magazine by Bonds and my good friend Chuck Beans. Chuck. It's a space guy, actually had Bonds job a fuse in the Pentagon. He is now chairman and chief strategy officer at York Space Systems, and in his spare time he's chairman of the small satellites. Chuck speaks in words that everyone can understand. So I'd like to give you some of his words out of his article. Uh, they're afraid somewhat. So these are Chuck's words. Let's talk about average Joe and playing Jane. Before heading to the airport for a business trip to New York City, Joe checks the weather forecast informed by Noah's weather satellites to see what pack for the trip. He then calls an uber that space app. Everybody uses it matches riders with drivers via GPS to take into the airport, So Joe has lunch of the airport. Unbeknownst to him, his organic lunch is made with the help of precision farming made possible through optimized irrigation and fertilization, with remote spectral sensing coming from space and GPS on the plane, the pilot navigates around weather, aided by GPS and nose weather satellites. And Joe makes his meeting on time to join his New York colleagues in a video call with a key customer in Singapore made possible by telecommunication satellites. Around to his next meeting, Joe receives notice changing the location of the meeting to another to the other side of town. So he calmly tells Syria to adjust the destination, and his satellite guided Google maps redirects him to the new location. That evening, Joe watches the news broadcast via satellite. The report details a meeting among world leaders discussing the developing crisis in Syria. As it turns out, various forms of quote remotely sensed. Information collected from satellites indicate that yet another band, chemical weapon, may have been used on its own people. Before going to bed, Joe decides to call his parents and congratulate them for their wedding anniversary as they cruise across the Atlantic, made possible again by communications satellites and Joe's parents can enjoy the call without even wondering how it happened the next morning. Back home, Joe's wife, Jane, is involved in a car accident. Her vehicle skids off the road. She's knocked unconscious, but because of her satellite equipped on star system, the crash is detected immediately and first responders show up on the scene. In time, Joe receives the news books. An early trip home sends flowers to his wife as he orders another uber to the airport. Over that 24 hours, Joe and Jane used space system applications for nearly every part of their day. Imagine the consequences if at any point they were somehow denied these services, whether they be by natural causes or a foreign hostility. And each of these satellite applications used in this case were initially developed for military purposes and continue to be, but also have remarkable application on our way of life. Just many people just don't know that. So, ladies and gentlemen, now you know, thanks to chuck beans, well, the United States has a proud heritage being the world's leading space faring nation, dating back to the Eisenhower and Kennedy years. Today we have mature and robust systems operating from space, providing overhead reconnaissance to quote, wash and listen, provide missile warning, communications, positioning, navigation and timing from our GPS system. Much of what you heard in Lieutenant General J. T. Thompson earlier speech. These systems are not only integral to our national security, but also our also to our quality of life is Chuck told us. We simply no longer could live without these systems as a nation and for that matter, as a world. But over the years, adversary like adversaries like China, Russia and other countries have come to realize the value of space systems and are aggressively playing ketchup while also pursuing capabilities that will challenge our systems. As many of you know, in 2000 and seven, China demonstrated it's a set system by actually shooting down is one of its own satellites and has been aggressively developing counter space systems to disrupt hours. So in a heavily congested space environment, our systems are now being contested like never before and will continue to bay well as Bond mentioned, the United States has responded to these changing threats. In addition to adding ways to protect our system, the administration and in Congress recently created the United States Space Force and the operational you United States Space Command, the latter of which you heard President Armstrong and other Californians hope is going to be located. Vandenberg Air Force Base Combined with our intelligence community today, we have focused military and civilian leadership now in space. And that's a very, very good thing. Commence, really. On the industry side, we did create the National Security Space Association devoted solely to supporting the national security Space Enterprise. We're based here in the D C area, but we have arms and legs across the country, and we are loaded with extraordinary talent. In scores of Forman, former government executives, So S s a is joined at the hip with our government customers to serve and to support. We're busy with a multitude of activities underway ranging from a number of thought provoking policy. Papers are recurring space time Webcast supporting Congress's Space Power Caucus and other main serious efforts. Check us out at NSS. A space dot org's One of our strategic priorities in central to today's events is to actively promote and nurture the workforce development. Just like cow calling. We will work with our U. S. Government customers, industry leaders and academia to attract and recruit students to join the space world, whether in government or industry and two assistant mentoring and training as their careers. Progress on that point, we're delighted. Be delighted to be working with Cal Poly as we hopefully will undertake a new pilot program with him very soon. So students stay tuned something I can tell you Space is really cool. While our nation's satellite systems are technical and complex, our nation's government and industry work force is highly diverse, with a combination of engineers, physicists, method and mathematicians, but also with a large non technical expertise as well. Think about how government gets things thes systems designed, manufactured, launching into orbit and operating. They do this via contracts with our aerospace industry, requiring talents across the board from cost estimating cost analysis, budgeting, procurement, legal and many other support. Tasker Integral to the mission. Many thousands of people work in the space workforce tens of billions of dollars every year. This is really cool stuff, no matter what your education background, a great career to be part of. When summary as bang had mentioned Aziz, well, there is a great deal of exciting challenges ahead we will see a new renaissance in space in the years ahead, and in some cases it's already begun. Billionaires like Jeff Bezos, Elon Musk, Sir Richard Richard Branson are in the game, stimulating new ideas in business models, other private investors and start up companies. Space companies are now coming in from all angles. The exponential advancement of technology and microelectronics now allows the potential for a plethora of small SAT systems to possibly replace older satellites the size of a Greyhound bus. It's getting better by the day and central to this conference, cybersecurity is paramount to our nation's critical infrastructure in space. So once again, thanks very much, and I look forward to the further conversation. >>Steve, thank you very much. Space is cool. It's relevant. But it's important, as you pointed out, and you're awesome story about how it impacts our life every day. So I really appreciate that great story. I'm glad you took the time Thio share that you forgot the part about the drone coming over in the crime scene and, you know, mapping it out for you. But that would add that to the story later. Great stuff. My first question is let's get into the conversations because I think this is super important. President Armstrong like you to talk about some of the points that was teased out by Bang and Steve. One in particular is the comment around how military research was important in developing all these capabilities, which is impacting all of our lives. Through that story. It was the military research that has enabled a generation and generation of value for consumers. This is kind of this workforce conversation. There are opportunities now with with research and grants, and this is, ah, funding of innovation that it's highly accelerate. It's happening very quickly. Can you comment on how research and the partnerships to get that funding into the universities is critical? >>Yeah, I really appreciate that And appreciate the comments of my colleagues on it really boils down to me to partnerships, public private partnerships. You mentioned Northrop Grumman, but we have partnerships with Lockie Martin, Boeing, Raytheon Space six JPL, also member of organization called Business Higher Education Forum, which brings together university presidents and CEOs of companies. There's been focused on cybersecurity and data science, and I hope that we can spill into cybersecurity in space but those partnerships in the past have really brought a lot forward at Cal Poly Aziz mentioned we've been involved with Cube set. Uh, we've have some secure work and we want to plan to do more of that in the future. Uh, those partnerships are essential not only for getting the r and d done, but also the students, the faculty, whether masters or undergraduate, can be involved with that work. Uh, they get that real life experience, whether it's on campus or virtually now during Covic or at the location with the partner, whether it may be governmental or our industry. Uh, and then they're even better equipped, uh, to hit the ground running. And of course, we'd love to see even more of our students graduate with clearance so that they could do some of that a secure work as well. So these partnerships are absolutely critical, and it's also in the context of trying to bring the best and the brightest and all demographics of California and the US into this field, uh, to really be successful. So these partnerships are essential, and our goal is to grow them just like I know other colleagues and C. S u and the U C are planning to dio, >>you know, just as my age I've seen I grew up in the eighties, in college and during that systems generation and that the generation before me, they really kind of pioneered the space that spawned the computer revolution. I mean, you look at these key inflection points in our lives. They were really funded through these kinds of real deep research. Bond talk about that because, you know, we're living in an age of cloud. And Bezos was mentioned. Elon Musk. Sir Richard Branson. You got new ideas coming in from the outside. You have an accelerated clock now on terms of the innovation cycles, and so you got to react differently. You guys have programs to go outside >>of >>the Defense Department. How important is this? Because the workforce that air in schools and our folks re skilling are out there and you've been on both sides of the table. So share your thoughts. >>No, thanks, John. Thanks for the opportunity responded. And that's what you hit on the notes back in the eighties, R and D in space especially, was dominated by my government funding. Uh, contracts and so on. But things have changed. As Steve pointed out, A lot of these commercial entities funded by billionaires are coming out of the woodwork funding R and D. So they're taking the lead. So what we can do within the deal, the in government is truly take advantage of the work they've done on. Uh, since they're they're, you know, paving the way to new new approaches and new way of doing things. And I think we can We could certainly learn from that. And leverage off of that saves us money from an R and D standpoint while benefiting from from the product that they deliver, you know, within the O D Talking about workforce development Way have prioritized we have policies now to attract and retain talent. We need I I had the folks do some research and and looks like from a cybersecurity workforce standpoint. A recent study done, I think, last year in 2019 found that the cybersecurity workforce gap in the U. S. Is nearing half a million people, even though it is a growing industry. So the pipeline needs to be strengthened off getting people through, you know, starting young and through college, like assess a professor Armstrong indicated, because we're gonna need them to be in place. Uh, you know, in a period of about maybe a decade or so, Uh, on top of that, of course, is the continuing issue we have with the gap with with stamps students, we can't afford not to have expertise in place to support all the things we're doing within the with the not only deal with the but the commercial side as well. Thank you. >>How's the gap? Get? Get filled. I mean, this is the this is again. You got cybersecurity. I mean, with space. It's a whole another kind of surface area, if you will, in early surface area. But it is. It is an I o t. Device if you think about it. But it does have the same challenges. That's kind of current and and progressive with cybersecurity. Where's the gap Get filled, Steve Or President Armstrong? I mean, how do you solve the problem and address this gap in the workforce? What is some solutions and what approaches do we need to put in place? >>Steve, go ahead. I'll follow up. >>Okay. Thanks. I'll let you correct. May, uh, it's a really good question, and it's the way I would. The way I would approach it is to focus on it holistically and to acknowledge it up front. And it comes with our teaching, etcetera across the board and from from an industry perspective, I mean, we see it. We've gotta have secure systems with everything we do and promoting this and getting students at early ages and mentoring them and throwing internships at them. Eyes is so paramount to the whole the whole cycle, and and that's kind of and it really takes focused attention. And we continue to use the word focus from an NSS, a perspective. We know the challenges that are out there. There are such talented people in the workforce on the government side, but not nearly enough of them. And likewise on industry side. We could use Maura's well, but when you get down to it, you know we can connect dots. You know that the the aspect That's a Professor Armstrong talked about earlier toe where you continue to work partnerships as much as you possibly can. We hope to be a part of that. That network at that ecosystem the will of taking common objectives and working together to kind of make these things happen and to bring the power not just of one or two companies, but our our entire membership to help out >>President >>Trump. Yeah, I would. I would also add it again. It's back to partnerships that I talked about earlier. One of our partners is high schools and schools fortune Margaret Fortune, who worked in a couple of, uh, administrations in California across party lines and education. Their fifth graders all visit Cal Poly and visit our learned by doing lab and you, you've got to get students interested in stem at a early age. We also need the partnerships, the scholarships, the financial aid so the students can graduate with minimal to no debt to really hit the ground running. And that's exacerbated and really stress. Now, with this covert induced recession, California supports higher education at a higher rate than most states in the nation. But that is that has dropped this year or reasons. We all understand, uh, due to Kobe, and so our partnerships, our creativity on making sure that we help those that need the most help financially uh, that's really key, because the gaps air huge eyes. My colleagues indicated, you know, half of half a million jobs and you need to look at the the students that are in the pipeline. We've got to enhance that. Uh, it's the in the placement rates are amazing. Once the students get to a place like Cal Poly or some of our other amazing CSU and UC campuses, uh, placement rates are like 94%. >>Many of our >>engineers, they have jobs lined up a year before they graduate. So it's just gonna take key partnerships working together. Uh, and that continued partnership with government, local, of course, our state of CSU on partners like we have here today, both Stephen Bang So partnerships the thing >>e could add, you know, the collaboration with universities one that we, uh, put a lot of emphasis, and it may not be well known fact, but as an example of national security agencies, uh, National Centers of Academic Excellence in Cyber, the Fast works with over 270 colleges and universities across the United States to educate its 45 future cyber first responders as an example, so that Zatz vibrant and healthy and something that we ought Teoh Teik, banjo >>off. Well, I got the brain trust here on this topic. I want to get your thoughts on this one point. I'd like to define what is a public private partnership because the theme that's coming out of the symposium is the script has been flipped. It's a modern error. Things air accelerated get you got security. So you get all these things kind of happen is a modern approach and you're seeing a digital transformation play out all over the world in business. Andi in the public sector. So >>what is what >>is a modern public private partnership? What does it look like today? Because people are learning differently, Covert has pointed out, which was that we're seeing right now. How people the progressions of knowledge and learning truth. It's all changing. How do you guys view the modern version of public private partnership and some some examples and improve points? Can you can you guys share that? We'll start with the Professor Armstrong. >>Yeah. A zai indicated earlier. We've had on guy could give other examples, but Northup Grumman, uh, they helped us with cyber lab. Many years ago. That is maintained, uh, directly the software, the connection outside its its own unit so that students can learn the hack, they can learn to penetrate defenses, and I know that that has already had some considerations of space. But that's a benefit to both parties. So a good public private partnership has benefits to both entities. Uh, in the common factor for universities with a lot of these partnerships is the is the talent, the talent that is, that is needed, what we've been working on for years of the, you know, that undergraduate or master's or PhD programs. But now it's also spilling into Skilling and re Skilling. As you know, Jobs. Uh, you know, folks were in jobs today that didn't exist two years, three years, five years ago. But it also spills into other aspects that can expand even mawr. We're very fortunate. We have land, there's opportunities. We have one tech part project. We're expanding our tech park. I think we'll see opportunities for that, and it'll it'll be adjusted thio, due to the virtual world that we're all learning more and more about it, which we were in before Cove it. But I also think that that person to person is going to be important. Um, I wanna make sure that I'm driving across the bridge. Or or that that satellites being launched by the engineer that's had at least some in person training, uh, to do that and that experience, especially as a first time freshman coming on a campus, getting that experience expanding and as adult. And we're gonna need those public private partnerships in order to continue to fund those at a level that is at the excellence we need for these stem and engineering fields. >>It's interesting People in technology can work together in these partnerships in a new way. Bank Steve Reaction Thio the modern version of what a public, successful private partnership looks like. >>If I could jump in John, I think, you know, historically, Dodi's has have had, ah, high bar thio, uh, to overcome, if you will, in terms of getting rapid pulling in your company. This is the fault, if you will and not rely heavily in are the usual suspects of vendors and like and I think the deal is done a good job over the last couple of years off trying to reduce the burden on working with us. You know, the Air Force. I think they're pioneering this idea around pitch days where companies come in, do a two hour pitch and immediately notified of a wooden award without having to wait a long time. Thio get feedback on on the quality of the product and so on. So I think we're trying to do our best. Thio strengthen that partnership with companies outside the main group of people that we typically use. >>Steve, any reaction? Comment to add? >>Yeah, I would add a couple of these air. Very excellent thoughts. Uh, it zits about taking a little gamble by coming out of your comfort zone. You know, the world that Bond and Bond lives in and I used to live in in the past has been quite structured. It's really about we know what the threat is. We need to go fix it, will design it says we go make it happen, we'll fly it. Um, life is so much more complicated than that. And so it's it's really to me. I mean, you take you take an example of the pitch days of bond talks about I think I think taking a gamble by attempting to just do a lot of pilot programs, uh, work the trust factor between government folks and the industry folks in academia. Because we are all in this together in a lot of ways, for example. I mean, we just sent the paper to the White House of their requests about, you know, what would we do from a workforce development perspective? And we hope Thio embellish on this over time once the the initiative matures. But we have a piece of it, for example, is the thing we call clear for success getting back Thio Uh, President Armstrong's comments at the collegiate level. You know, high, high, high quality folks are in high demand. So why don't we put together a program they grabbed kids in their their underclass years identifies folks that are interested in doing something like this. Get them scholarships. Um, um, I have a job waiting for them that their contract ID for before they graduate, and when they graduate, they walk with S C I clearance. We believe that could be done so, and that's an example of ways in which the public private partnerships can happen to where you now have a talented kid ready to go on Day one. We think those kind of things can happen. It just gets back down to being focused on specific initiatives, give them giving them a chance and run as many pilot programs as you can like these days. >>That's a great point, E. President. >>I just want to jump in and echo both the bank and Steve's comments. But Steve, that you know your point of, you know, our graduates. We consider them ready Day one. Well, they need to be ready Day one and ready to go secure. We totally support that and and love to follow up offline with you on that. That's that's exciting, uh, and needed very much needed mawr of it. Some of it's happening, but way certainly have been thinking a lot about that and making some plans, >>and that's a great example of good Segway. My next question. This kind of reimagining sees work flows, eyes kind of breaking down the old the old way and bringing in kind of a new way accelerated all kind of new things. There are creative ways to address this workforce issue, and this is the next topic. How can we employ new creative solutions? Because, let's face it, you know, it's not the days of get your engineering degree and and go interview for a job and then get slotted in and get the intern. You know the programs you get you particularly through the system. This is this is multiple disciplines. Cybersecurity points at that. You could be smart and math and have, ah, degree in anthropology and even the best cyber talents on the planet. So this is a new new world. What are some creative approaches that >>you know, we're >>in the workforce >>is quite good, John. One of the things I think that za challenge to us is you know, we got somehow we got me working for with the government, sexy, right? The part of the challenge we have is attracting the right right level of skill sets and personnel. But, you know, we're competing oftentimes with the commercial side, the gaming industry as examples of a big deal. And those are the same talents. We need to support a lot of programs we have in the U. D. So somehow we have to do a better job to Steve's point off, making the work within the U. D within the government something that they would be interested early on. So I tracked him early. I kind of talked about Cal Poly's, uh, challenge program that they were gonna have in June inviting high school kid. We're excited about the whole idea of space and cyber security, and so on those air something. So I think we have to do it. Continue to do what were the course the next several years. >>Awesome. Any other creative approaches that you guys see working or might be on idea, or just a kind of stoked the ideation out their internship. So obviously internships are known, but like there's gotta be new ways. >>I think you can take what Steve was talking about earlier getting students in high school, uh, and aligning them sometimes. Uh, that intern first internship, not just between the freshman sophomore year, but before they inter cal poly per se. And they're they're involved s So I think that's, uh, absolutely key. Getting them involved many other ways. Um, we have an example of of up Skilling a redeveloped work redevelopment here in the Central Coast. PG and e Diablo nuclear plant as going to decommission in around 2020 24. And so we have a ongoing partnership toe work on reposition those employees for for the future. So that's, you know, engineering and beyond. Uh, but think about that just in the manner that you were talking about. So the up skilling and re Skilling uh, on I think that's where you know, we were talking about that Purdue University. Other California universities have been dealing with online programs before cove it and now with co vid uh, so many more faculty or were pushed into that area. There's going to be much more going and talk about workforce development and up Skilling and Re Skilling The amount of training and education of our faculty across the country, uh, in in virtual, uh, and delivery has been huge. So there's always a silver linings in the cloud. >>I want to get your guys thoughts on one final question as we in the in the segment. And we've seen on the commercial side with cloud computing on these highly accelerated environments where you know, SAS business model subscription. That's on the business side. But >>one of The >>things that's clear in this trend is technology, and people work together and technology augments the people components. So I'd love to get your thoughts as we look at the world now we're living in co vid um, Cal Poly. You guys have remote learning Right now. It's a infancy. It's a whole new disruption, if you will, but also an opportunity to enable new ways to collaborate, Right? So if you look at people and technology, can you guys share your view and vision on how communities can be developed? How these digital technologies and people can work together faster to get to the truth or make a discovery higher to build the workforce? These air opportunities? How do you guys view this new digital transformation? >>Well, I think there's there's a huge opportunities and just what we're doing with this symposium. We're filming this on one day, and it's going to stream live, and then the three of us, the four of us, can participate and chat with participants while it's going on. That's amazing. And I appreciate you, John, you bringing that to this this symposium, I think there's more and more that we can do from a Cal poly perspective with our pedagogy. So you know, linked to learn by doing in person will always be important to us. But we see virtual. We see partnerships like this can expand and enhance our ability and minimize the in person time, decrease the time to degree enhanced graduation rate, eliminate opportunity gaps or students that don't have the same advantages. S so I think the technological aspect of this is tremendous. Then on the up Skilling and Re Skilling, where employees air all over, they can be reached virtually then maybe they come to a location or really advanced technology allows them to get hands on virtually, or they come to that location and get it in a hybrid format. Eso I'm I'm very excited about the future and what we can do, and it's gonna be different with every university with every partnership. It's one. Size does not fit all. >>It's so many possibilities. Bond. I could almost imagine a social network that has a verified, you know, secure clearance. I can jump in, have a little cloak of secrecy and collaborate with the d o. D. Possibly in the future. But >>these are the >>kind of kind of crazy ideas that are needed. Are your thoughts on this whole digital transformation cross policy? >>I think technology is gonna be revolutionary here, John. You know, we're focusing lately on what we call digital engineering to quicken the pace off, delivering capability to warfighter. As an example, I think a I machine language all that's gonna have a major play and how we operate in the future. We're embracing five G technologies writing ability Thio zero latency or I o t More automation off the supply chain. That sort of thing, I think, uh, the future ahead of us is is very encouraging. Thing is gonna do a lot for for national defense on certainly the security of the country. >>Steve, your final thoughts. Space systems are systems, and they're connected to other systems that are connected to people. Your thoughts on this digital transformation opportunity >>Such a great question in such a fun, great challenge ahead of us. Um echoing are my colleague's sentiments. I would add to it. You know, a lot of this has I think we should do some focusing on campaigning so that people can feel comfortable to include the Congress to do things a little bit differently. Um, you know, we're not attuned to doing things fast. Uh, but the dramatic You know, the way technology is just going like crazy right now. I think it ties back Thio hoping Thio, convince some of our senior leaders on what I call both sides of the Potomac River that it's worth taking these gamble. We do need to take some of these things very way. And I'm very confident, confident and excited and comfortable. They're just gonna be a great time ahead and all for the better. >>You know, e talk about D. C. Because I'm not a lawyer, and I'm not a political person, but I always say less lawyers, more techies in Congress and Senate. So I was getting job when I say that. Sorry. Presidential. Go ahead. >>Yeah, I know. Just one other point. Uh, and and Steve's alluded to this in bonded as well. I mean, we've got to be less risk averse in these partnerships. That doesn't mean reckless, but we have to be less risk averse. And I would also I have a zoo. You talk about technology. I have to reflect on something that happened in, uh, you both talked a bit about Bill Britton and his impact on Cal Poly and what we're doing. But we were faced a few years ago of replacing a traditional data a data warehouse, data storage data center, and we partner with a W S. And thank goodness we had that in progress on it enhanced our bandwidth on our campus before Cove. It hit on with this partnership with the digital transformation hub. So there is a great example where, uh, we we had that going. That's not something we could have started. Oh, covitz hit. Let's flip that switch. And so we have to be proactive on. We also have thio not be risk averse and do some things differently. Eyes that that is really salvage the experience for for students. Right now, as things are flowing, well, we only have about 12% of our courses in person. Uh, those essential courses, uh, and just grateful for those partnerships that have talked about today. >>Yeah, and it's a shining example of how being agile, continuous operations, these air themes that expand into space and the next workforce needs to be built. Gentlemen, thank you. very much for sharing your insights. I know. Bang, You're gonna go into the defense side of space and your other sessions. Thank you, gentlemen, for your time for great session. Appreciate it. >>Thank you. Thank you. >>Thank you. >>Thank you. Thank you. Thank you all. >>I'm John Furry with the Cube here in Palo Alto, California Covering and hosting with Cal Poly The Space and Cybersecurity Symposium 2020. Thanks for watching.

>>thank you very much for this opportunity to talk about Stamp with a bio design program, which is entrepreneurship education for the medical devices. My name is Julia Key Can. Oh, I am Japanese. I have seen the United States since two doesn't want on the more than half of my life after graduating from medical school is in the United States. I hope I can contribute to make them be reached between Japan that you were saying right I did the research in the period of medical devices with a patient all over the world today is my batteries met their country finished medication stamp of the city. Yeah, North Korea academia, but also a wrong. We in the industry sectors sometimes tried to generate new product which can generate revenue from their own research outward, it is explained by three steps. The first one is the debut river, which is the harbor Wrong research output to the idea which can be product eventually. That they are hard, though, is the best body, which is a hot Arboria. From idea to commercial for the other one is that we see which is a harder to make a martial hold up to become a big are revenue generating products for the academia that passed the heart is a critical on the essential to make a research output to the idea. Yeah, they're two different kind of squash for the developing process in the health care innovation, Why's bio and by all the farmer under the other one is medical device regarding the disciplining method is maybe in mechanical engineering. Electrical engineering on the medical under surgical by Obama is mainly chemical engineering, computer science, biology and genetics. However, very important difference off these to be the innovation process. Medic is suitable on these digital innovation and by Obama, is suitable discovery process needs. Yeah, in general transformation of medical research between the aroma academia output to the commercial product in the medical field is called bench to bed. It means from basically such to critical applications. But it is your bio on the path. Yeah, translation. Medical research for medical devices is better. Bench on back to bed, which means quicker Amit needs to bench on back to Greek application. The difference off the process is the same as the difference off the commercialization. Yeah, our goal is to innovate the newer devices for patient over the war. Yeah, yeah, there are two process to do innovation. One is technology push type of innovation. The other one is news, full type of innovation. Ignore the push stop Innovation is coming from research laboratory. It is suitable for the farm on the bios. Happy type of innovation. New, useful or used driven type of type of innovation is suitable for medical devices. Either Take this topic of innovation or useful type of innovation. It is important to have Mini's. We should think about what? It's waas Yeah, in 2001 stop for the Cube, API has started to stop with Bio Design program, which is on entrepreneurship education for medical devices. Our mission is educated on empowering helps technology, no based innovators on the reading, the transition to a barrier to remain a big innovation ecosystem. Our vision is to be a global leader in advancing Hearst technology innovation to improve lives everywhere. There are three steps in our process. Off innovation, identify invent on England. Yeah, yeah. The most important step is the cluster, which is I didn't buy. I didn't buy a well characterized needs is the Vienna off a grating vision. Most of the value off medical device development is due to Iraq Obina unmet needs. So we focused in this gated by creates the most are the mosque to find on the Civic on appropriate. Yeah, our barrels on the student Hickory World in March, disparate 19 that ideally include individual, which are background in many thing engineering on business. Yeah, how to find our needs. Small team will go to the hospital or clinic or environment to offer them the healthcare providers with naive eyes. The team focused. You look to keep all the um, it needs not technology. This method is senior CTO. It's a rocket car approach which can be applied all that design, thinking the team will generate at least 200 needs from economic needs. Next stick to identify Pace is to select the best. Amit Knees were used for different aspect, which can about it the nominees. These background current existing solutions market size on the stakeholders. Once we pick up ur madness from 200 nominees, they can move to the invention pates. Finally, they can't be the solution many people tend to invent on at the beginning base without carefree evaluating its unmet knees to result in a better tend to pouring love. Their whole idea, even amid NIS, is not what this is. Why most of the medical device innovation fail due to the lack off unmet needs. To avoid this Peter Hall, our approach is identify good needs. First on invention is the sex to generate the idea wrong. Unmet knees. We will use seven Rules off race Tony B B zero before judgment encourage wild ideas built on the ideas off. Others. Go Conte. One conversation time. Stay focused on the topic. The brainstorming is like association game. Somebody's idea can stimulate the others ideas. After generating many ideas, the next step is sleeping of idea whether use five different Dustin to embody the ideas. Intellectual property regulatory. Remember National Business Model on technology How, after this election step, we can have the best solution with system it needs, and finally team will go to the implementation pace. This place is more business oriented mothers. The strategy off business implementations on the business planning. Yeah, yeah, students want more than 50 starting up are spinning off from by design program. Let me show one example This is a case of just reputations. If patient your chest pain, most of that patient go to family doctor and trust. The first are probably Dr before the patient to General Securities. General Card, obviously for the patient Director, Geologist, Director, API geologist will make a reservation. Horta uses it. Test patient will come to the clinic people for devices in machine on his chest. Well, what? Two days? Right? That patient will visit clinic to put all the whole decency After a few days off. Analysis patient Come back to Dr to hear the result Each step in his money to pay. This is a minute, Knees. This is a rough sketch off the solutions. The product name is die. A patch on it can save about $620. Part maybe outpatient right here. >>Yeah, yeah. Life is stressful. We all depend on our heart with life source of our incredible machine. The body, however, sometimes are hard Need to check up. Perhaps you felt dizzy heart racing or know someone who has had a serious heart problem The old fashioned monitors that used to get from most doctors or bulky And you can't wear them exercising or in the shower. If appropriate for you, sudden life will provide you the eye rhythm. Zero patch to buy five inch band aid like patch would. You can apply to your chest in the comfort of your own home or in the gym. It will monitor your heart rate for up to 14 days. You never have to come into a doctor's office as you mail back. Patched us shortly after you were receiving. Easy to understand report of your heart activity, along with recommendations from a heart specialists to understand the next steps in your heart. Health sudden life bringing heart monitoring to you. >>This is from the TV broadcasting become Ah, this is a core value we can stamping on his breast. He has a connotation of the decent died. Now the company names Iris is in the public market cap off. This company is more than six billion di parts is replacing grasp all or that you see the examination. However, our main product is huge. The product lifecycle Very divisive, recent being it's. But if we can educate the human decision oil because people can build with other people beyond space and yeah, young broader stop on by design education is now runs the media single on Japan. He doesn't 15 PBS probably star visited Stamp of the diversity and Bang. He announced that Japan, by design, will runs with vampires. That problem? Yeah, Japan Barzan program has started a University of Tokyo Osaka University and we've asked corroborating with Japanese government on Japanese medical device Industry s and change it to that. Yeah, this year that it's batch off Japan better than parachute on. So far more than five. Starting up as being that's all. Thank you very much for your application.

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi buddy welcome back to the cube this is Dave Volante and you're watching a special presentation data ops enacted made possible by IBM you know what's what's happening is the innovation engine in the IT economy is really shifted used to be Moore's Law today it's applying machine intelligence and AI to data really scaling that and operationalizing that new knowledge the challenges that is not so easy to operationalize AI and infuse it into the data pipeline but what we're doing in this program is bringing in practitioners who have actually had a great deal of success in doing just that and I'm really excited to have it Kumal a Himalayan Manali is here she's the executive head of data management or personal and business banking at Standard Bank of South Africa the tomb of length thanks so much for coming in the queue thank you for having me Dave you're very welcome and first of all how you holding up with this this bovid situation how are things in Johannesburg um things in Johannesburg are fine we've been on lockdown now I think it's day 33 if I'm not mistaken lost count and but we're really grateful for the swift action of government we we only I mean we have less than 4,000 places in the country and infection rate is is really slow so we've really I think been able to find the curve and we're grateful for being able to be protected in this way so all working from home or learning the new normal and we're all in this together that's great to hear why don't you tell us a little bit about your your role you're a data person we're really going to get into it but here with us you know how you spend your time okay well I head up a date operations function and a data management function which really is the foundational part of the data value chain that then allows other parts of the organization to monetize data and liberate it as as as the use cases apply we monetize it ourselves as well but really we're an enterprise wide organization that ensures that data quality is managed data is governed that we have the effective practices applied to the entire lineage of the data ownership and curation is in place and everything else from a regulatory as well as opportunity perspective then is able to be leveraged upon so historically you know data has been viewed as sort of this expense it's it's big it's growing it needs to be managed deleted after a certain amount of time and then you know ten years ago of the Big Data move data became an asset you had a lot of shadow I people going off and doing things that maybe didn't comply to the corporate ethics probably drove here here you're a part of the organization crazy but talk about that how what has changed but they in the last you know five years or so just in terms of how people approach data oh I mean you know the story I tell my colleague who are all bankers obviously is the fact that the banker in 1989 had to mainly just know debits credits and be able to look someone in the eye and know whether or not they'd be a credit risk or not you know if we lend you money and you pay it back the the banker of the late 90s had to then contend with the emergence of technologies that made their lives easier and allowed for automation and processes to run much more smoothly um in the early two-thousands I would say that digitization was a big focus and in fact my previous role was head of digital banking and at the time we thought digital was the panacea it is the be-all and end-all it's the thing that's gonna make organizations edit lo and behold we realized that once you've gotten all your digital platforms ready they are just the plate or the pipe and nothing is flowing through it and there's no food on the face if data is not the main photo really um it's always been an asset I think organizations just never consciously knew that data was that okay so so what sounds like once you've made that sort of initial digital transformation you really had to work it and what we're hearing from a lot of practitioners like self as challenges related to that involve different parts of the organization different skill sets of challenges and sort of getting everybody to work together on the same page it's better but maybe you could take us back to sort of when you started on this initiative around data Ops what was that like what were some of the challenges that you faced and how'd you get through them okay first and foremost Dave organizations used to believe that data was I t's problem and that's probably why you you then saw the emergence of things like chatter IP but when you really acknowledge that data is an essay just like money is an asset then you you have to then take accountability for it just the same way as you would any other asset in the organization and you will not abdicate its management to a separate function that's not cold to the business and oftentimes IT are seen as a support or an enabling but not quite the main show in most organizations right so what we we then did is first emphasize that data is a business capability the business function it presides in business makes to product management makes to marketing makes to everything else that the business needs for data management also has to be for to every role in every function to different degrees and varying bearing offense and when you take accountability as an owner of a business unit you also take accountability for the data in the systems that support the business unit for us that was the first picture um and convincing my colleagues that data was their problem and not something that we had to worry about they just kind of leave us to to it was was also a journey but that was kind of the first step into it in terms of getting the data operations journey going um you had to first acknowledge please carry on no you just had to first acknowledge that it's something you must take accountability of as a banker not just need to a different part of the organization that's a real cultural mindset you know in the game of rock-paper-scissors you know culture kinda beats everything doesn't it it's almost like a yep a trump card and so so the businesses embrace that but but what did you do to support that is there has to be trust in the data that it has to be a timeliness and so maybe you could take us through how you achieve those objectives and maybe some other objectives that business the man so the one thing I didn't mention Dave is that obviously they didn't embrace it in the beginning it wasn't a it wasn't there oh yeah that make sense they do that type of conversation um what what he had was a few very strategic people with the right mindset that I could partner with that understood the case for data management and while we had that as as an in we developed a framework for a fully matured data operations capability in the organization and what that would look like in a target date scenario and then what you do is you wait for a good crisis so we had a little bit of a challenge in that our local regulator found us a little bit wanting in terms of our date of college and from that perspective it then brought the case for data quality management so now there's a burning platform you have an appetite for people to partner with you and say okay we need this to comply to help us out and when they start seeing their opt-in action do they then buy into into the concept so sometimes you need to just wait for a good Christ and leverage it and only do that which the organization will appreciate at that time you don't have to go Big Bang data quality management was the use case at the time five years ago so we focused all our energy on that and after that it gave us leeway and license really bring to maturity all the other capabilities at the business might not well understand as well so when that crisis hit of thinking about people process in technology you probably had to turn some knobs in each of those areas can you talk about that so from a technology perspective that that's when we partnered with with IBM to implement information analyzer for us in terms of making sure that then we could profile the data effectively what was important for us is to to make strides in terms of showing the organization progress but also being able to give them access to self-service tools that will give them insight into their data from a technology perspective that was kind of I think the the genesis of of us implementing and the IBM suite in earnest from a data management perspective people wise we really then also began a data stewardship journey in which we implemented business unit stewards of data I don't like using the word steward because in my organization it's taken lightly almost like a part-time occupation so we converted them we call them data managers and and the analogy I would give is every department with a P&L any department worth its salt has a FDA or financial director and if money is important to you you have somebody helping you take accountability and execute on your responsibilities in managing that that money so if data is equally important as an asset you will have a leader a manager helping you execute on your data ownership accountability and that was the people journey so firstly I had kind of soldiers planted in each department which were data managers that would then continue building the culture maturing the data practices as as applicable to each business unit use cases so what was important is that every manager in every business unit to the Data Manager focus their energy on making that business unit happy by ensuring that they data was of the right compliance level and the right quality the right best practices from a process and management perspective and was governed and then in terms of process really it's about spreading through the entire ecosystem data management as a practice and can be quite lonely um in the sense that unless the whole business of an organization is managing data they worried about doing what they do to make money and most people in most business units will be the only unicorn relative to everybody else who does what they do and so for us it was important to have a community of practice a process where all the data managers across business as well as the technology parts and the specialists who were data management professionals coming together and making sure that we we work together on on specific you say so I wonder if I can ask you so the the industry sort of likes to market this notion of of DevOps applied to data and data op have you applied that type of mindset approach agile of continuous improvement is I'm trying to understand how much is marketing and how much actually applicable in the real world can you share well you know when I was reflecting on this before this interview I realized that our very first use case of data officers probably when we implemented information analyzer in our business unit simply because it was the first time that IT and business as well as data professionals came together to spec the use case and then we would literally in an agile fashion with a multidisciplinary team come together to make sure that we got the outcomes that we required I mean for you to to firstly get a data quality management paradigm where we moved from 6% quality at some point from our client data now we're sitting at 99 percent and that 1% literally is just the timing issue to get from from 6 to 99 you have to make sure that the entire value chain is engaged so our business partners will the fundamental determinant of the business rules apply in terms of what does quality mean what are the criteria of quality and then what we do is translate that into what we put in the catalog and ensure that the profiling rules that we run are against those business rules that were defined at first so you'd have upfront determination of the outcome with business and then the team would go into an agile cycle of maybe two-week sprints where we develop certain things have stand-ups come together and then the output would be - boarded in a prototype in a fashion where business then gets to go double check that out so that was the first iterate and I would say we've become much more mature at it and we've got many more use cases now and there's actually one that it's quite exciting that we we recently achieved over the end of of 2019 into the beginning of this year so what we did was they I'm worried about the sunlight I mean through the window you look creative to me like sunset in South Africa we've been on the we've been on CubeSat sometimes it's so bright we have to put on sunglasses but so the most recent one which was in in mates 2019 coming in too early this year we we had long kind of achieved the the compliance and regulatory burning platform issues and now we are in a place of I think opportunity and luxury where we can now find use cases that are pertinent to business execution and business productivity um the one that comes to mind is we're a hundred and fifty eight years old as an organization right so so this Bank was born before technology it was also born in the days of light no no no integration because every branch was a standalone entity you'd have these big ledges that transactions were documented in and I think once every six months or so these Ledger's would be taken by horse-drawn carriage to a central place to get go reconcile between branches and paper but the point is if that is your legacy the initial kind of ERP implementations would have been focused on process efficiency based on old ways of accounting for transactions and allocating information so it was not optimized for the 21st century our architecture had has had huge legacy burden on it and so going into a place where you can be agile with data is something that we constantly working toward so we get to a place where we have hundreds of branches across the country and all of them obviously telling to client servicing clients as usual and and not being able for any person needing sales teams or executional teams they were not able in a short space of time to see the impact of the tactic from a database fee from a reporting history and we were in a place where in some cases based on how our Ledger's roll up and the reconciliation between various systems and accounts work it would take you six weeks to verify whether your technique were effective or not because to actually see the revenue hitting our our general ledger and our balance sheet might take that long that is an ineffective way to operate in a such a competitive environment so what you had our frontline sales agents literally manually documenting the sales that they had made but not being able to verify whether that or not is bringing revenue until six weeks later so what we did then is we sat down and defined all the requirements were reporting perspective and the objective was moved from six weeks latency to 24 hours um and even 24 hours is not perfect our ideal would be that bite rows of day you're able to see what you've done for that day but that's the next the next epoch that will go through however um we literally had the frontline teams defining what they'd want to see in a dashboard the business teams defining what the business rules behind the quality and the definitions would be and then we had an entire I'm analytics team and the data management team working around sourcing the data optimising and curating it and making sure that the latency had done that's I think only our latest use case for data art um and now we're in a place where people can look at a dashboard it's a cubed self-service they can learn at any time I see the sales they've made which is very important right now at the time of covert nineteen from a form of productivity and executional competitiveness those are two great use cases of women lying so the first one you know going from data quality 6% the 99% I mean 6% is all you do is spend time arguing about the data bills profanity and then 99% you're there and you said it's just basically a timing issue use latency in the timing and then the second one is is instead of paving the cow path with an outdated you know ledger Barret data process week you've now compressed that down to 24 hours you want to get the end of day so you've built in the agility into your data pipeline I'm going to ask you then so when gdpr hit were you able to very quickly leverage this capability and and apply and then maybe other of compliance edik as well well actually you know what we just now was post TDP our us um and and we got GDP all right about three years ago but literally all we got right was reporting for risk and compliance purposes they use cases that we have now are really around business opportunity lists so the risk so we prioritize compliance report a long time it but we're able to do real-time reporting from a single transaction perspective I'm suspicious transactions etc I'm two hours in Bank and our governor so from that perspective that was what was prioritize in the beginning which was the initial crisis so what you found is an entire engine geared towards making sure that data quality was correct for reporting and regulatory purposes but really that is not the be-all and end-all of it and if that's all we did I believe we really would not have succeeded or could have stayed dead we succeeded because Dana monetization is actually the penis' t the leveraging of data for business opportunity is is actually then what tells you whether you've got the right culture or not you're just doing it to comply then it means the hearts and minds of the rest of the business still aren't in the data game I love this story because it's me it's nirvana for so many years we've been pouring money to mitigate risk and you have no choice do it you know the general council signs off on it the the CFO but grudgingly signs off on it but it's got to be done but for years decades we've been waiting to use these these risk initiatives to actually drive business value you know it kind of happened with enterprise data warehouse but it was too slow it was complicated and it certainly didn't happen with with email archiving that was just sort of a tech balk it sounds like you know we're at that point today and I want to ask you I mean like you know you we talking earlier about you know the crisis gonna perpetuated this this cultural shift and you took advantage of that so we're out who we the the mother nature dealt up a crisis like we've never seen before how do you see your data infrastructure your data pipeline your data ops what kind of opportunities do you see in front of you today as a result of ovid 19 well I mean because of of the quality of kind data that we had now we were able to very quickly respond to to pivot nineteen in in our context where the government put us on lockdown relatively early in in the curve or in the cycle of infection and what it meant is it brought a little bit of a shock to the economy because small businesses all of a sudden didn't have a source of revenue or potentially three to six weeks and based on the data quality work that we did before it was actually relatively easy to be agile enough to do the things that we did so within the first weekend of of lockdown in South Africa we were the first bank to proactively and automatically offer small businesses and student and students with loans on our books a instant three month payment holiday assuming they were in good standing and we did that upfront though it was actually an opt-out process rather than you had to fall in and arrange for that to happen and I don't believe we would have been able to do that if our data quality was not with um we have since made many more initiatives to try and keep the economy going to try and keep our clients in in a state of of liquidity and so you know data quality at that point and that Dharma is critical to knowing who you're talking to who needs what and in which solutions would best be fitted towards various segments I think the second component is um you know working from home now brings an entirely different normal right so so if we had not been able to provide productivity dashboard and and and sales and dashboards to to management and all all the users that require it we would not be able to then validate or say what our productivity levels are now that people are working from home I mean we still have essential services workers that physically go into work but a lot of our relationship bankers are operating from home and that face the baseline and the foundation that we said productivity packing for various methods being able to be reported on in a short space of time has been really beneficial the next opportunity for us is we've been really good at doing this for the normal operational and front line and type of workers but knowledge workers have also know not necessarily been big productivity reporters historically they kind of get an output then the output might be six weeks down the line um but in a place where teams now are not locate co-located and work needs to flow in an edge of passion we need to start using the same foundation and and and data pipeline that we've laid down as a foundation for the reporting of knowledge work and agile team type of metric so in terms of developing new functionality and solutions there's a flow in a multidisciplinary team and how do those solutions get architected in a way where data assists in the flow of information so solutions can be optimally developed well it sounds like you're able to map a metric but business lines care about you know into these dashboards you usually the sort of data mapping approach if you will which makes it much more relevant for the business as you said before they own the data that's got to be a huge business benefit just in terms of again we talked about cultural we talked about speed but but the business impact of being able to do that it has to be pretty substantial it really really is um and and the use cases really are endless because every department finds their own opportunity to utilize in terms of their also I think the accountability factor has has significantly increased because as the owner of a specific domain of data you know that you're not only accountable to yourself and your own operation but people downstream to you as a product and in an outcome depend on you to ensure that the quality of the data you produces is of a high nature so so curation of data is a very important thing and business is really starting to understand that so you know the cards Department knows that they are the owners of card data right and you know the vehicle asset Department knows that they are the owners of vehicle they are linked to a client profile and all of that creates an ecosystem around the plan I mean when you come to a bank you you don't want to be known as a number and you don't want to be known just for one product you want to be known across everything that you do with that with that organization but most banks are not structured that way they still are product houses and product systems on which your data reside and if those don't act in concert then we come across extremely schizophrenic as if we don't know our clients and so that's very very important stupid like I can go on for an hour talking about this topic but unfortunately we're we're out of time thank you so much for sharing your deep knowledge and your story it's really an inspiring one and congratulations on all your success and I guess I'll leave it with you know what's next you gave us you know a glimpse of some of the things you wanted to do pressing some of the the elapsed times and the time cycle but but where do you see this going in the next you know kind of mid term and longer term currently I mean obviously AI is is a big is a big opportunity for all organizations and and you don't get automation of anything right if the foundations are not in place so you believe that this is a great foundation for anything AI to be applied in terms of the use cases that we can find the second one is really providing an API economy where certain data product can be shared with third parties I think that probably where we want to take things as well we are really utilizing external third-party data sources I'm in our data quality management suite to ensure validity of client identity and and and residents and things of that nature but going forward because been picked and banks and other organizations are probably going to partner to to be more competitive going forward we need to be able to provide data product that can then be leveraged by external parties and vice-versa to be like thanks again great having you thank you very much Dave appreciate the opportunity thank you for watching everybody that we go we are digging in the data ops we've got practitioners we've got influencers we've got experts we're going in the crowd chat it's the crowd chat net flash data ops but keep it right there way back but more coverage this is Dave Volante for the cube [Music] you

>>from around the globe. It's the queue with digital coverage of women transforming technology brought to you by VM Ware. >>Hi, this is Lisa Martin covering fifth Annual Women Transforming Technology WT two from my home in San Jose, California Because this is the first year than WT two has gone digital. Very excited to welcome next one of the speakers from the executive track. We have Charmaine Macquarie, president of Macquarie Group, but also offer C Suite Advisor. You know, Speaker Charmaine. Nice to start with you. >>An absolute pleasure. Thank you for having me. >>So you have an incredible background. You have been for two decades working with leaders and I read 27 industries, five continents and from some pretty big, well known brands Coca Cola, Johnson and Johnson, my particular favorite Starbucks. Tell me a little bit about your background in your career and how you came to be working with potential leaders >>early on in my career, I was working in politics, actually helping politicians understand their constituency and then how to communicate effectively with them and then went on into marketing. And really, what I say is that what I do is a conglomeration of all of my life experience working with leaders either in politics, in marketing and sales on a variety of industries, including gas and oil, and coming together and helping them understand how to communicate their message effectively. How have executive presence and ensuring that they're seeing, heard and remembered >>what? One of the things. One of the things that talking about being remembered especially now during a crisis that nobody has ever experienced before, when there are so much, so much concern and so much uncertainty. Um, I e. Read that you said effective communication is more than just words and phrases, especially in today's climate. What is effective communication? >>Effective communication is making sure that people hear your value, your value proposition, and that is really essential today. One of the things you want to do is that you want to elevate your visibility and when elevate the value that you bring to your organization. There are a number of competing priorities, and what you want organization to understand is what is it that you see that others don't see, and that is a part of your value proposition. How are you going to help the organization innovate through this time, and wanting to do that is really speaking about what is the value. What is it that it's gonna make the difference for the organization today with this crises and that will also take it further into the future. >>Tell me a little bit about this session that you did at women transforming technology the other day. 35 minutes. Interactive session. Since everything for this year's event was digital, I love the name of your session. Speak up, Stand out. We heard talking a little bit about when you first learned maybe last month, that this event was going digital. Did you change anything? Were there certain elements of your expertise and your recommendations that are now more even more important? Respect to visibility and value? >>Yes, So what? I changed it. What I changed and Waas. I really wanted to make it as a conversational as possible, because in this isolation it's easy to not feel seen or heard, and I want people to be able to elevate again their visibility and their ability to add value. So a couple of things that people can do is they can actually rewrite their narrative if they need to meaning if you believe that if you do not define yourself, others well, and their definition will inevitably be inadequate. So if you know that you are seen as a very quiet person and a person that is in the background and you want to have greater visibility, this is a great opportunity for you to rewrite that narrative and make yourself more visible. Meaning, I think, the expertise that you have again the insight that you have, making sure that you bring that to the table. You can do it in a number of formats. You could do it not only on a zoom call with your colleagues, but you can. Also, your email is heightened if you're using language and the language of leadership language that really hurts. People's here, and that creates a visual. So now you want to do to really make sure that using language that is very vivid and allows a person to touch, taste and feel what it is that you're saying, so that's one of the things that you can do. The other is say, Is that what I want to make sure that my clients are not well kept secrets. I want to make sure that in this time of isolation that they're finding opportunities to reach out. So most everyone is at home sheltering in place so people have more time on their hands in terms of reading your emails. When researchers found that there is a 26% increase and say your newsletters being read your emails being written, so now is the time that you could actually heighten that kind of communication. >>That's fascinating. Look that you said about making what you're communicating in an email. Maybe it's even texture over something like slack, vivid. Say, somebody has a great idea, I think. All right, so terms have changed. My job function is difference, or it's challenging to complete certain Give me some words that you think. So now you're saying people are actually focusing more on reading what you're saying, What are some vivid words that I could use if I had an interesting finance project or a marketing project that I wanted to raise the visibility of and gets them to really feel what I'm looking at? >>So when you speak about up in a finance project, one of the things you want to do is think about what is a story that could articulate those numbers that can tell the story with those numbers. So if you were saying, um, let's just make it as simple as possible. Two plus two equals four. Well, what you want to think about is what is it that is going to be different when you finished this project, or what is it that's gonna be? It's gonna shift in the marketplace. And so you want to create that visual? What does the future look like? And using examples of things that are very basic to our life today, as opposed to using really complicated language. Now is the time to have your language simple, having very clear and having very vivid. So you >>run it, Go ahead. Sorry. >>No, please go. Right. Yet >>I'm glad that you brought up simplicity because so often I think people think maybe I'm managing a project or I'm creating a methodology, and I think, really, it's just it's the simple. But we often second guess ourselves because I think I included in this. A lot of folks think it can't be that simple. It's got to be more complex I need to show, you know, like an episode of I'm picturing an Apple sort of the Big Bang theory, and Sheldon's talking about strength there. You need to make it complex to show your value. And but sometimes it's the simplest methodology. The simplest way of communicating that is the most effective. Do you find out that sometimes spokes, regardless of their level of executive nous, are challenged to really step back and look at the simple way to communicate with the simple answer? >>Absolutely. And simplicity is best, whether it's during this time period or even beyond this pandemic, but particularly now. So I don't know if anybody's ever seen the show. The marvelous is, um, I think it's amazing. Yeah, single and one of the things that she asked her husband, She goes, Well, honey, what do you do? And so I think, in the first episode, and he says, You know, I signed papers, I do this, I do that and he says, I really don't know what the hell I do. And I remember an incident with one of my clients, and I asked her, What does she do? She gave me her job title and I said, Okay, how many people work in your company? And she said, 49,000 people work here. I said, How many people do you think have the same title issue? If she goes well, you know, I'm sure at least a couple 1000. I said yes. So what distinguishes you? And so she wanted to talk about the title, which is like talking about acronyms at a company. And I said So, Really, What do you do? What we realized is that what she does is that she was responsible the fastest growing market segment in her company that articulates your value proposition that made a very visit vivid and very brought it to life. So people are able to understand when someone asked me, What do I do? I don't say that I'm an executive coach because you may have read an article last week that says all executive coach us up, that defines May. I wanted to find myself. My value is, I hope smart people get promoted when they get promoted, they communicate the big picture. So I help smart people get promote and communicate the big picture. I provide executive coaching senior level executives. I articulated my value. You know who I work with their smart people, that they're not smart. They're not working with me when they work with me and get promoted. Why? Because it communicate the big picture. Really? Simple one sent it. So what is the value? That is what really heightens your visibility and heightens your and levels. Level up your ability to be seen and heard in organizations. >>And, you know, I was looking at your website. You've been 98% success rate of folks that have worked with you that have been promoted within the following 18 months. What are some of the both hard and soft skills that you're looking for? So when you work, when you select clients to work with that, that demonstrate they are ready to be in the six weeks >>Well, there's a couple of things. One is that person has to be open and willing and not being volunteered by the organization, meaning saying you need to do you have to do this. If it is mandatory that someone work with an executive coach, that's not a winning proposition. The winning propositions That person is open and open to change and ready to make change. As I say to my clients, if you want everything to remain the same, I am not the coach for you because you're going to see change and you're going to see significant change. So that's one the other is preparing your organization for the kind of change is going to take place so that your organization begins with C and hear what you're doing different. So, for example, I would say to a client, if you're prepared to really step up and make the commitment to making the shift, you want to let people know what kind of shift that you're taking you're making so that they can begin to look for people like to look for success. They like to be able to reward you when you're successful, but you've got to let them know that you're there >>for that shift. >>So that's one of the things that's really important is that people be open to it and they'd be ready to take their spotlight. If you want to do it and remain behind the curtain, that's wonderful. This is not the work for you. >>It requires a little bit of vulnerability that, or maybe a lot of vulnerability to be able to do that, not easy, unless you're bringing a brown fan like I am talk to me about, especially in this time with covered 19 The uncertainty in every aspect of our lives. Every single aspect is it's dense and it's an emotional challenge. So do you find that it's harder for some folks, whether they're men or women, to do what your title says? You know? Speak up, let them know I'm coming. I'm on my way. How are you advising folks from a psychological perspective, to be able to do this? >>Well, I think there's a couple of things. One is that with the three questions I ask every client and those three questions are one. How do you see yourself? How do other people see you? And the third is, How do you want to be seen? So when you're able to answer, become introspective and answer those questions from the heart from your heart, then you can get really clear about what you want the world to know about you and how you want to show up. And it does require vulnerability. It requires you to look inward first for you to make that decision on how you want the world to see you. And then once you're able to make that, get that clarity and so it's process make getting that clarity. Then you can speak about that to the world. My thing is, is again. If you don't define yourself, others will, and their definition is inadequate. So when you define yourself, you know who you are and what you stand for. You can then shout that at the top of your lungs. But you don't really have to, because your actions will speak very clearly about what it is and who you say you are and how you want the world to see you. And you're always asking, am I can grow it? >>I love that about defining yourself so that others don't do it incorrectly. Talk to me about how somebody can develop their own communication style. How what are some of the steps that they need to recognize that, for example, if you see someone, anything there too bold or there to brush, or maybe dial it back a bit, especially because messages are getting read more now, which that process internally that I would need to take to develop and effective communication style. What is it >>that you need to do to to develop that effective communication style one? As I said, being able to define what that looks like for you and what that is may not be appropriate for every organization and every corporate culture. So you need to find immediate. Make sure either evaluate whether not you're in the right corporate culture so that you can be successful and or find a new one so that you could be successful once you have that, really, um, helping the people in your organization to make it easy for them to come to you. So by extending by extending yourself first, that is one of the things that I would say it would be really important in terms of stepping up during this time frame is saying, I feel really this is really let's say, someone has been felt really shaken by this really shaken by this. But I am determined so leverage this as an opportunity to really show up as my best self and show my greatest humanity. And I think that when we let people know what did it, where we're going and where we're headed, This far more easy for people to support you and provide you with the venues in which to exhibit who you are. This is a great time for you to volunteer A so much as possible to have that visibility. Because I think one of the questions you asked me earlier is how do you get hadn't become comfortable with this? You get comfortable with it by practising, Lady Gaga says. We're born that way, but we are. The only way that it happens with people that are really successful is because they practice >>something that is so interesting. Is during this time in particular, is getting is accountability, right? It's so easy right now more than ever to lose accountability. And I like that. You said that That's what I'm hearing when you say, you know, let people know that direction that you're going in. I think for the person you set that okay, I publicly said this, I need to be held that I need to hold myself accountable so that I deliver. I think there's a lot of power in that >>there is, and when you step up and articulate to the world. Well, you're about what it is that you're going to deliver your level of excellence. You hold yourself accountable because the person who is most important for you to be accountable to is yourself. Others come second, actually, sort of like being on the airplane in the mask. You've got to do it for you first. Because if you let yourself down, that's the that is the most horrific. And so stepping up to that is so much. There's so much power. And I believe that people provide you with a lot of grace when you do that and people know they can count on you. >>And that's so important knowing demonstrating your dependability in any situation. Sherman, I wish we had more time. It's been such a pleasure talking to you. Thank you for sharing your insight. I'm gonna be visible show value and the vetted and communication and accountable. Thank you so much for joining me. >>Have a wonderful day. You >>as well. And for Charmaine McCleery. I'm Lisa Martin. You're watching the Cube's coverage of the digital version of women transforming technology 2020 for now. >>Yeah, >>Yeah, yeah, yeah, yeah, yeah

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cute conversation everybody welcome back to the cube this is Dave Volante and you're watching a special presentation data ops enacted made possible by IBM you know what's what's happening is the innovation engine in the IT economy is really shifted used to be Moore's Law today it's applying machine intelligence and AI to data really scaling that and operationalizing that new knowledge the challenges that is it's not so easy to operationalize AI and infuse it into the data pipeline but what we're doing in this program is bringing in practitioners who have actually had a great deal of success in doing just that and I'm really excited to have it Kumal a the tumor lang Manali is here she's the executive head of data management or personal and business banking at Standard Bank of South Africa the tumor length thanks so much for coming in the cube thank you for having me Dave you're very welcome and first of all how you holding up with this this bovid situation how are things in Johannesburg um things in Johannesburg are fine and we've been on lockdown now I think it's day 33 if I'm not mistaken lost count and but we're really grateful for the swift action of government we only I mean we have less than 4,000 places in the country and infection rate is is really slow so we've really I think been able to flatten the curve and we're grateful for being able to be protected in this way so we're all working from home or learning the new normal and we're all in this together that's great to hear why don't you tell us a little bit about your your role you're a data person we're really going to get in with here with us you know how you spend your time okay well I hit up a date operations function in a data management function which really is the foundational part of the data value chain that then allows other parts of the organization to monetize data and leverage it as as the use cases apply we monetize it ourselves as well but really we're an enterprise wide organization that ensures that data quality is managed data is governed that we have the effective practices applied to the entire lineage of the data ownership and curation is in place and everything else from a regulatory as well as opportunity perspective then is able to be leveraged upon so historically you know data has been viewed as sort of this expense it's it's big it's growing it needs to be managed deleted after a certain amount of time and then you know ten years ago the Big Data move data became an asset you had a lot of shadow ID people going off and doing things that maybe didn't comply to the corporate ethics probably drove here here you're a part of the organization crazy but talk about that how what has changed but they in the last you know five years or so just in terms of how people approach data oh I mean you know the story I tell my colleague who are all bankers obviously is the fact that um the banker in 1989 had to mainly just know debits credit and be able to look someone in the eye and know whether or not they'd be a credit risk or not you know if we lend you money and you pay it back um the the banker of the late 90s had to then contend with the emergence of technologies that made their lives easier and allowed for automation and processes to run much more smoothly um in the early two-thousands I would say that digitization was a big focus and in fact my previous role was head of digital banking and at the time we thought digital was the panacea it is the be-all and end-all is the thing that's gonna make organizations edit lo and behold we realized that once you've gotten all your digital platforms ready they are just the plate or the pipe and nothing is flowing through it and there's no food on the plate if data is not the main so really um it's always been an acid I think organizations just never consciously knew that data was there okay so so it sounds like once you've made that sort of initial digital transformation you really had to work it and what we're hearing from a lot of practitioners like toughest challenges related to that involve different parts of the organization different skill sets of challenges and sort of getting everybody to work together on the same page it's better but maybe you could take us back to sort of when you started on this initiative around data ops what was that like what were some of the challenges that you faced and how'd you get through them first and foremost Dave organizations used to believe that data was I t's problem and that's probably why you you then saw the emergence of things like shadow IP but when you really acknowledge that data is and si just like money is an asset then you you have to then take accountability for it just the same way as you would any other asset in the organization and you will not add the a its management to a separate function that's not code to the business and oftentimes IT are seen as a support for an enabling but not quite the main show in most organizations right so what we we then did is first emphasize that data is a business capability a business function it presides in business next to product management next to marketing makes to everything else that the business needs for data management also has to be for to every role in every function to different degrees and varying bearing events and when you take accountability as an owner of a business unit you also take accountability for the data in the systems that support the business unit for us that was the first picture um and convincing my colleagues that data was their problem and not something that we had to worry about and they just kind of leave us to - it was was also a journey but that was kind of the first step in - in terms of getting the data operations journey going um you had to first acknowledge please carry on no you just had to first acknowledge that it's something you must take accountability of as a banker not just need to a different part of the organization that's a real cultural mindset you know in the game of rock-paper-scissors you know culture kinda beats everything doesn't it it's almost like a yep a trump card and so so the businesses embrace that but but what did you do to support that is there has to be trust in the data that it has to be a timeliness and so maybe you could pick us through how you achieve those objectives and maybe some other objectives that business the man so the one thing I didn't mention Davis that obviously they didn't embrace it in the beginning it wasn't a it wasn't there oh yeah that make sense they do that type of conversation um what what he had was a few very strategic people with the right mindset that I could partner with that understood the case for data management and while we had that as as an in we developed a framework for a fully matured data operations capability in the organization and what that would look like in a target date scenario and then what you do is you wait for a good crisis so we had a little bit of a challenge in that our local regulator found us a little bit wanting in terms of our data quality and from that perspective it then brought the case for data quality management to the whole so now there's a burning platform you have an appetite for people to partner with you and say okay we need this to comply to help us out and when they start seeing their opt-in action do they stick then buy into into the concepts so sometimes you need to just wait for a good price and leverage it and only do that which the organization will appreciate at that time you don't have to go Big Bang data quality management was the use case at the time five years ago so we focused all our energy on that and after that it gave us leeway and license really bring to maturity or the other capabilities of the business might not well understand as well so when that crisis hit of thinking about people process in technology you probably had to turn some knobs in each of those areas can you talk about that so from a technology perspective that that when we partnered with with IBM to implement information analyzer for us in terms of making sure that then we could profile the data effectively what was important for us is to to make strides in terms of showing the organization progress but also being able to give them access to self-service tools that will give them insight into their data from a technology perspective that was kind of I think that the genesis of of us implementing and the IBM suite in earnest from a data management perspective people wise we really then um also began a data stewardship journey in which we implemented business unit stewards of data I don't like using the word steward because in my organization it's taken lightly it's almost like a part-time occupation so we converted them we call them data managers and and the analogy I would give is every department with a pl any department worth its salt has a FD or financial director and if money is important to you you have somebody helping you take accountability and execute on your responsibilities and managing that that money so if data is equally important as an asset you will have a leader a manager helping you execute on your data ownership accountability and that was the people journey so firstly I had kind of soldiers planted in each department which were data managers that would then continue building the culture maturing the data practices as as applicable to each business unit use cases so what was important is that every manager in every business unit to the Data Manager focus their energy on making that business unit happy by ensuring that their data was of the right compliance level and the right quality the right best practices from a process and management perspective and was governed through and then in terms of process really it's about spreading through the entire ecosystem data management as a practice and can be quite lonely in the sense that unless the core business of an organization is managing data they worried about doing what they do to make money and most people in most business units will be the only unicorn relative to everybody else who does what they do and so for us it was important to have a community of practice a process where all the data managers across business as well as the technology parts and the specialists who were data management professionals coming together and making sure that we we work together on on specific use so I wonder if I can ask you so the the industry sort of likes to market this notion of of DevOps applied to data and data op have you applied that type of mindset approach agile of continuous improvement is I'm trying to understand how much is marketing and how much actually applicable in the real world can you share well you know when I was reflecting on this before this interview I realized that our very first use case of data officers probably when we implemented information analyzer in our business unit simply because it was the first time that IT and business as well as data professionals came together to spec the use case and then we would literally in an agile fashion with a multidisciplinary team come together to make sure that we got the outcomes that we required I mean for you to to firstly get a data quality management paradigm where we moved from 6% quality at some point from our client data now we're sitting at 99 percent and that 1% literally is just the timing issue to get from from 6 to 99 you have to make sure that the entire value chain is engaged so our business partners were the fundamental determinant of the business rules apply in terms of what does quality mean what are the criteria of quality and then what we do is translate that into what we put in the catalog and ensure that the profiling rules that we run are against those business rules that were defined at first so you'd have upfront determination of the outcome with business and then the team would go into an agile cycle of maybe two-week sprints where we develop certain things have stand-ups come together and then the output would be - boarded in a prototype in a fashion where business then gets to go double check that out so that was the first iterate and I would say we've become much more mature at it and we've got many more use cases now and there's actually one that it's quite exciting that we we recently achieved over the end of 2019 into the beginning of this year so what we did was they've am worried about the sunlight coming through the window you look crazy to me like the sunset in South Africa we've been on the we've been on CubeSat sometimes it's so bright we have to put on sunglasses but so the most recent one which was in in late 2019 coming in too early this year we we had long kind of achieved the the compliance and the regulatory burning platform issues and now we are in a place of I think opportunity and luxury where we can now find use cases that are pertinent to business execution and business productivity the one that comes to mind is where a hundred and fifty eight years old as an organization right so so this Bank was born before technology it was also born in the days of light no no no integration because every branch was a standalone entity you'd have these big ledges that transactions were were documented in and I think once every six months or so these Ledger's would be taken by horse-drawn carriage to a central place to give go reconcile between branches and paper but the point is if that is your legacy the initial kind of ERP implementations would have been focused on process efficiency based on old ways of accounting for transactions and allocating information so it was not optimized for the 21st century our architecture had has had huge legacy burden on it and so going into a place where you can be agile with data is something that we're constantly working toward so we get to a place where we have hundreds of branches across the country and all of them obviously telling to client servicing clients as usual and and not being able for any person needing sales teams or executional teams they were not able in a short space of time to see the impact of the tactic from a data perspective um we were in a place where in some cases based on how our Ledger's roll up in the reconciliation between various systems and accounts work it would take you six weeks to verify whether your technique were effective or not because to actually see the revenue hitting our our general ledger and our balance sheet might take that long that is an ineffective way to operate in a such a competitive environment so what you had our frontline sales agents literally manually documenting the sales that they had made but not being able to verify whether that or not is bringing revenue until six weeks later so what we did then is we sat down and defined all the requirements from a reporting perspective and the objective was moved from six weeks latency to 24 hours um and even 24 hours is not perfect our ideal would be that bite rows of day you're able to see what you've done for that day but that's the next the next epoch that will go through however um we literally had the frontline teams defining what they'd want to see in a dashboard the business teams defining what the business rules behind the quality and the definitions would be and then we had an entire I'm analytics team and the data management team working around sourcing the data optimising and curating it and making sure that the latency had done that's I think only our latest use case for data art um and now we're in a place where people can look at a dashboard it's a cubed self-service they can Logan at any time I see the sales they've made which is very important right now and the time of overt nineteen from a from a productivity and executional competitiveness listing those are two great use cases of cooling so the first one you know going from data quality 6% the 99% I mean 6% is all you do is spend time arguing about the data stills probity and then 99% you're there and you said it's just basically a timing issue use latency in the timing and then the second one is is instead of paving the cow path with an outdated you know ledger Barratt data process week you've now compressed that down to 24 hours you want to get the end of day so you've built in the agility into your data pipeline I'm gonna ask you then so when GDP are hit were you able to very quickly leverage this capability and and imply and then maybe other of compliance edik as well Oh actually you know what we just now was post gdpr us um and and we got GDP all right about three years ago but literally all we got right was reporting for risk and compliance purposes the use cases that we have now are really around business opportunity lists so the risk so we prioritize compliance report a long time ago were able to do real-time reporting of a single transaction perspective I'm suspicious transactions etc I'm two hours in Bank and our governor so from that perspective that was what was prioritize in the beginning which was the initial crisis so what you found is an entire engine geared towards making sure that data quality was correct for reporting and regulatory purposes but really that is not the be-all and end-all of it and if that's all we did I believe we really would not have succeeded or could have stayed dead we succeeded because data monetization is actually the penisy the leveraging of data for business opportunity is is actually then what tells you whether you've got the right culture or not you're just doing it to comply then it means the hearts and minds of the rest of the business still aren't in the data game I love this story because it's me it's nirvana for so many years we've been pouring money to mitigate risk and you have no choice do it you know the general council signs off on it the the CFO but grudgingly signs off on it but it's got to be done but for years decades we've been waiting to use these these risk initiatives to actually drive business value you know kind of happened with enterprise data warehouse but it was too slow it was complicated it certainly didn't happen with with email archiving that was just sort of a tech balk it sounds like you know we're at that point today and I want to ask you to me like you know you we talking earlier about you know the crisis gonna perpetuated this this cultural shift and you took advantage of that so we're on the mother nature dealt up a crisis like we've never seen before how do you see your data infrastructure your data pipeline your data ops what kind of opportunities do you see in front of you today as a result of mobit nineteen well I mean because of of the quality of mind data that we had now we were able to very quickly respond to to pivot nineteen in in our context where the government and put us on lockdown relatively early in in the curve in disciple of infection and what it meant is it brought a little bit of a shock to the economy because small businesses all of a sudden didn't have a source of revenue for potentially three to six weeks and based on the data quality work that we did before it was actually relatively easy to be agile enough to do the things that we did so within the first weekend of of lockdown in South Africa we were the first bank to proactively and automatically offer small businesses and student um students with loans on our books a instant preman payment holiday assuming they were in good standing and we did that upfront though it was actually an up out process rather than you had to fall in and arrange for that to happen and I don't believe we would have been able to do that if our data quality was not with um we have since made many more initiatives to try and keep the economy going to try and keep our clients in in a state of of liquidity and so you know data quality at that point and that Dharma is critical to knowing who you're talking to who needs what and in which solutions would best be fitted towards various segments I think the second component is um you know working from home now brings an entirely different normal right so so if we have not been able to provide productivity dashboard and and sales and dashboards to to management and all all the users that require it we would not be able to then validate or say what our productivity levels are and other people are working from home I mean we still have essential services workers that physically go into work but a lot of our relationship bankers are operating from home and that face the baseline and the foundation that we said productivity packing for various metric being able to be reported on in a short space of time has been really beneficial the next opportunity for us is we've been really good at doing this for the normal operational and front line and type of workers but knowledge workers have also know not necessarily been big productivity reporters historically they kind of get an output then the output might be six weeks down the line um but in a place where teams now are not locate co-located and work needs to flow in an edge of passion we need to start using the same foundation and and and data pipeline that we've laid down as a foundation for the reporting of knowledge work and agile team type of metric so in terms of developing new functionality and solutions there's a flow in a multidisciplinary team and how do those solutions get architected in a way where data assists in the flow of information so solutions can be optimally developed well it sounds like you're able to map a metric the business lines care about you know into these dashboards you using the sort of data mapping approach if you will which makes it much more relevant for the business as you said before they own the data that's got to be a huge business benefit just in terms of again we talked about cultural we talked about speed but but the business impact of being able to do that it has to be pretty substantial it really really is um and and the use cases really are endless because every department finds their own opportunity to utilize in terms of their also I think the accountability factor has has significantly increased because as the owner of a specific domain of data you know that you're not only accountable to yourself and your own operation but people downstream to you as a product and and an outcome depend on you to ensure that the quality of the data you produces is of a high nature so so curation of data is a very important thing and business is really starting to understand that so you know the cards Department knows that they are the owners of card data right and you know the vehicle asset Department knows that they are the owners of vehicle they are linked to a client profile and all of that creates an ecosystem around the plan I mean when you come to a bank you you don't want to be known as a number and you don't want to be known just for one product you want to be known across everything that you do with that with that organization but most banks are not structured that way they still are product houses and product systems on which your data reside and if those don't act in concert then we come across extremely schizophrenic as if we don't know our clients and so that's very very important to me like I could go on for an hour talking about this topic but unfortunately we're out of time thank you so much for sharing your deep knowledge and your story it's really an inspiring one and congratulations on all your success and I guess I'll leave it with you know what's next you gave us you know a glimpse of some of the things you wanted to do pressing some of the the elapsed times and the time cycle but but where do you see this going in the next you know kind of mid term and longer term currently I mean obviously AI is is a big is a big opportunity for all organizations and and you don't get automation of anything right if the foundations are not in place so you believe that this is a great foundation for anything AI to to be applied in terms of the use cases that we can find the second one is really um providing an API economy where certain data product can be shared with third parties I think that probably where we want to take things as well we are ready utilizing external third-party data sources I'm in our data quality management suite to ensure validity of client identity and and and residents and things of that nature but going forward because been picked and banks and other organizations are probably going to partner to to be more competitive going forward we need to be able to provide data product that can then be leveraged by external parties and vice-versa the trooper like thanks again great having you thank you very much Dave appreciate the opportunity and thank you for watching everybody that we go we are digging in the data offs we've got practitioners we've got influencers we've got experts we're going in the crowd chat it's the crowd chat dot net flash data ops but keep it right there way back but more coverage this is Dave Volante for the cube [Music]

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hello and welcome to the cube conversation here in the Palo Alto studio I'm John four host of the cube we are here at the quarantine crew of the cube having the conversations that matter the most now and sharing that with you got a great guest here Phil Quaid was the chief information security officer of Fortinet also the author of book digital bing-bang which I just found out he wrote talking about the difference cybersecurity and the physical worlds coming together and we're living that now with kovat 19 crisis were all sheltering in place Phil thank you for joining me on this cube conversation so I want to get in this quickly that I think the main top thing is that we're all sheltering in place anxiety is high but people are now becoming mainstream aware of what we all in the industry have been known for a long time role of data cybersecurity access to remote tools and we're seeing the work at home the remote situation really putting a lot of pressure on as I've been reporting what I call at scale problems and one of them is security right one of them is bandwidth we're starting to see you know the throttling of the packets people are now living with the reality like wow this is really a different environment but it's been kind of a disruption and has created crimes of opportunity for bad guys so this has been a real thing everyone's aware of it across the world this is something that's now aware on everyone's mind what's your take on this because you guys are fighting the battle and providing solutions and we're doing for a long time around security this highlights a lot of the things in the surface area called the world with what's your take on this carbon 19 orton s been advocating for architectures and strategies that allow you to defend anywhere from the edge through the core all the way up to the cloud boom so with you know high speed and integration and so all the sudden what we're seeing not just you know in the US but the world as well is that that edge is being extended in places that we just hadn't thought about or our CV that people just hadn't planned for before so many people or telecommunication able to move that edge securely out to people's homes and more remote locations and do so providing the right type of security of privacy if those communications that are coming out of those delicate ears I noticed you have a flag in the background and for the folks that might not know you spent a lot of time at the NSA government agency doing a lot of cutting-edge work I mean going back to you know really you know post 9/11 - now you're in the private sector with Fortinet so you don't really speak with the agency but you did live through a time of major transformation around Homeland Security looking at data again different physical thing you know terrorist attacks but it did bring rise to large-scale data to bring to those things so I wanted to kind of point out I saw the flag there nice nice touch there but now that you're in the private sector it's another transformation it's not a transition we're seeing a transformation and people want to do it fast and they don't want to have disruption this is a big problem what's your reaction to that yeah I think what you're reporting out that sometimes sometimes there's catalysts that cause major changes in the way you do things I think we're in one of those right now that we're already in the midst of an evolutionary trend towards more distributed workforces and as I mentioned earlier doing so with the right type of security privacy but I would think what I think the global camp in debt endemic is showing is that we're all going to be accelerating that that thing is like it's gonna be a lot less evolutionary and a little bit more faster that's what happens when you have major world events like this being 911 fortunate tragedies it causes people to think outside the box or accelerate what they're already doing I think wearing that in that world today yeah it pulls forward a lot of things that are usually on the planning side and it makes them reality I want to get your thoughts because not only are CEOs and their employees all thinking about the new work environment but the chief information security officer is people in your role have to be more aware as more things happening what's on the minds of CISOs around the world these days obviously the pandemics there what are you seeing what are some of the conversations what are some of the thought processes what specifically is going on in the of the chief information security officer yeah I think there's probably a there's probably two different two different things there's the there's the emotional side and there's the analytic side on the emotional side you might say that some Caesars are saying finally I get to show how cyber security can be in an abler of business right I can allow you to to to maintain business continuity by allowing your workers to work from home and trying sustain business and allow you to keep paying their salary is very very important to society there's a very important time to step up as the seaso and do what's helpful to sustain mission in on the practical side you say oh my goodness my job's gotten a whole lot harder because I can rely less and less on someone's physical controls that use some of the physical benefits you get from people coming inside the headquarters facility through locked doors and there's personal congress's and personal identification authentication you need to move those those same security strategies and policies and you need to move it out to this broad eggs it's gotten a lot bigger and a lot more distributed so I want to ask you around some of the things they're on cyber screws that have been elevated to the top of the list obviously with the disruption of working at home it's not like an earthquake or a tornado or hurricane or flood you know this backup and recovery for that you know kind of disaster recovery this has been an unmitigated disaster in the sense of it's been unfor casted I was talking to an IT guy he was saying well we provisioned rvv lands to be your VPNs to be 30% and now they need a hundred percent so that disruption is causing I was an under forecast so in cyber as you guys are always planning in and protecting has there been some things that have emerged that are now top of mind that are 100 percent mindshare base or new solutions or new challenges why keep quite done what we're referring to earlier is that yep any good see so or company executive is going to prepare for unexpected things to a certain degree you need it whether it be spare capacity or the ability to recover from something an act of God as you mentioned maybe a flood or tornado or hurricane stuff like that what's different now is that we have a disruption who which doesn't have an end date meaning there's a new temporal component that's been introduced that most companies just can't plan for right even the best of companies that let's say Ronald very large data centers they have backup plans where they have spare fuel to run backup generators to provide electricity to their data centers but the amount of fuel they have might only be limited to 30 days or so it's stored on-site we might think well that's pretty that's a lot of for thinking by storing that much fuel on site for to allow you to sort of work your way through a hurricane or other natural disaster what we have now is a is a worldwide crisis that doesn't have a 30-day window on it right we don't know if it's gonna be 30 days or 120 days or or you know even worse than that so what's different now is that it's not just a matter of surging in doing something with band-aids and twine or an extra 30 days what we need to do is as a community is to prepare solutions that can be enduring solutions you know I have some things that if the absent I might like to provide a little color what those types of solutions are but that that would be my main message that this isn't just a surge for 30 days this is a surge or being agile with no end in sight take a minute explain some of those solutions what are you seeing whatever specific examples and solutions that you can go deeper on there yeah so I talked earlier about the the edge meaning the place where users interact with machines and company data that edge is no longer at the desktop down the hallway it could be 10 miles 450 miles away to where anyone where I'm telling you I'm commuting crumb that means we need to push the data confidentiality things out between the headquarters and the edge you do that with things like a secure secured tunnel it's called VPNs you also need to make sure that the user identification authentication this much is a very very secure very authentic and with high integrity so you do that with multi-factor authentication there's other things that we like that that are very very practical that you do to support this new architecture and the good news is that they're available today in the good news at least with some companies there already had one foot in that world but as I mentioned earlier not all companies had yet embraced the idea of where you're going to have a large percentage of your workforce - until a community so they're not quite so they're there they're reacting quickly to to make sure this edge is better protected by identification and authentication and begins I want to get to some of those edge issues that now translate to kind of physical digital virtualization of of life but first I want to ask you around operational technology and IT OT IT these are kind of examples where you're seeing at scale problem with the pandemic being highlighted so cloud providers etc are all kind of impacted and bring solutions to the table you guys at Foot are doing large scale security is there anything around the automation side of it then you've seen emerge because all the people that are taking care of being a supplier in this new normal or this crisis certainly not normal has leveraged automation and data so this has been a fundamental value proposition that highlights what we call the DevOps movement in the cloud world but automation has become hugely available and a benefit to this can you share your insights into how automation is changing with cyber I think you up a nice question for me is it allowed me to talk about not only automation but convergence so it's let's hit automation first right we all even even pre-crisis we need to be better at leveraging automation to do things that machines do best allow people to do higher-order things whether it's unique analysis or something else with a with a more distributed workforce and perhaps fewer resources automation is more important ever to automatically detect bad things that are about to happen automatically mitigating them before they get or they get to bad you know in the cybersecurity world you use things like agile segmentation and you use like techniques called soar it's a type of security orchestration and you want to eat leverage those things very very highly in order to leverage automation to have machines circum amount of human services but you also brought up on my favorite topics which is ot graceful technology though OTS you know are the things that are used to control for the past almost a hundred years now things in the physical world like electric generators and pipes and valves and things like that often used in our critical infrastructures in my company fort net we provide solutions that secure both the IT world the traditional cyber domain but also the OT systems of the world today where safety and reliability are about most important so what we're seeing with the co19 crisis is that supply chains transportation research things like that a lot of things that depend on OT solutions for safety and reliability are much more forefront of mine so from a cybersecurity strategy perspective what you want to do of course is make sure your solutions in the IT space are well integrated with you solutions in the OT space to the so an adversary or a mistake in cause a working to the crack in causing destruction that convergence is interesting you know we were talking before you came on camera around the fact that all these events are being canceled but that really highlights the fact that the physical spaces are no longer available the so-called ot operational technologies of events is the plumbing the face-to-face conversations but everyone's trying to move to digital or virtual eyes that it's not as easy as just saying we did it here we do it there there is a convergence and some sort of translation this new there's a new roles there's new responsibilities new kinds of behaviors and decision making that goes on in the physical and digital worlds that have to then come together and get reimagined and so what's your take on all this because this is not so much about events but although that's kind of prime time problem zooming it is not the answer that's a streaming video how do you replicate the value of physical into the business value in digital it's not a one-to-one so it's quite possible that that we might look back on this event to cover 19 experience we might look back at it in five or ten years and say that was simply a foreshadowing of our of the importance of making sure that our physical environment is appropriate in private what I mean is that with the with the rapid introduction of Internet of Things technologies into the physical world we're going to have a whole lot of dependencies on the thing inconveniences tendencies inconveniences on things an instrument our physical space our door locks or automobiles paths our temperatures color height lots of things to instrument the physical space and so there's gonna be a whole lot of data that's generated in that cyber in a physical domain increasingly in the future and we're going to become dependent upon it well what happens if for whatever reason in the in the future that's massively disruptive so all of a sudden we have a massive disruption in the physical space just like we're experiencing now with open 19 so again that's why it makes sense now to start your planning now with making sure that your safety and reliability controls in the physical domain are up to the same level security and privacy as the things in your IT delete and it highlights what's the where the value is to and it's a transformation I was just reading an article around spatial economics around distance not being together it's interesting on those points you wrote a book about this I want to get your thoughts because in this cyber internet or digital or virtualization of physical to digital whether it's events or actual equipment is causing people to rethink architectures you mentioned a few of them what's the state of the art thinking around someone who has the plan for this again is in its complex it's not just creating a gateway or a physical abstraction layer of software between two worlds there's almost a blending or convergence here what's your what's your thoughts on what's the state of the art thinking on this area yeah the book that I number of a very esteemed colleagues contribute to what we said is that it's time to start treating cybersecurity like a science let's not pretend it's a dark art that we have to relearn every couple years and what what we said in the in the digital Big Bang is that humankind started flourishing once we admitted our ignorance in ultimately our ignorance in the physical world and discovered or invented you can right word the disciplines of physics and chemistry and once we recognize that our physical world was driven by those scientific disciplines we started flourishing right the scientific age led to lots of things whether it would be transportation health care or lots of other things to improve our quality of life well if you fast forward 14 billion years after that cosmic Big Bang which was driven by physics 50 years ago or so we had a digital Big Bang where there was a massive explosion of bits with the invention of the internet and what we argue in the book is that let's start treating cybersecurity like a science or the scientific principle is that we ought to write down and follow a Rousseau's with you so we can thrive in the in the in a digital Big Bang in the digital age and one more point if you don't mind what we what we noted is that the internet was invented to do two things one connect more people or machines than ever imagined in to do so in speeds that were never imagined so the in the Internet is is optimized around speed in connectivity so if that's the case it may be a fundamental premise of cybersecurity science is make sure that your cyber security solutions are optimized around those same two things that the cyber domains are optimized around speed in integration continue from there you can you can build on more and more complex scientific principles if you focus on those fundamental things and speed and integration yeah that's awesome great insight they're awesome I wanted to throw in while you had the internet history lesson down there also was interesting was a very decentralization concept how does that factor in your opinion to some of the security paradigms is that helped or hurt or is it create opportunities for more secure or does it give the act as an advantage yeah I love your questions is your it's a very informed question and you're in a give me good segue to answer the way you know it should be answer yeah the by definition the distributed nature of the Internet means it's an inherently survivable system which is a wonderful thing to have for a critical infrastructure like that if one piece goes down the hole doesn't go down it's kind of like the power grid the u.s. the u.s. electrical power grid there's too many people who say the grid will go down well that's that's just not a practical thing it's not a reality thing the grades broken up into three major grades and there's AB ulis strategies and implementations of diversification to allow the grid to fail safely so it's not catastrophic Internet's the same thing so like my nipple like I was saying before we ought to de cyber security around a similar principle that a catastrophic failure in one partner to start cybersecurity architecture should result in cascading across your whole architecture so again we need to borrow some lessons from history and I think he bring up a good one that the internet was built on survivability so our cybersecurity strategies need to be the same one of the ways you do that so that's all great theory but one of the ways you do that of course is by making your cybersecurity solutions so that they're very well integrated they connect with each other so that you know speaking in cartoon language you know if one unit can say I'm about to fail help me out and another part of your architecture can pick up a slack and give you some more robust security in that that's what a connected the integrated cyber security architecture do for you yeah it's really fascinating insight and I think resiliency and scale are two things I think are going to be a big wave is going to be added into the transformations that going on now it's it's very interesting you know Phil great conversation I could do a whole hour with you and do a fish lead a virtual panel virtualize that our own event here keynote speech thanks so much for your insight one of things I want to get your thoughts on is something that I've been really thinking a lot lately and gathering perspectives and that is on biosecurity and I say biosecurity I'm referring to covet 19 as a virus because biology involves starting a lab or some people debate all that whether it's true or not but but that's what people work on in the biology world but it spreads virally like malware and has a similar metaphor to cybersecurity so we're seeing conversation starting to happen in Washington DC in Silicon Valley and some of my circles around if biology weapon or it's a tool like open-source software could be a tool for spreading cybersecurity Trojans or other things and techniques like malware spear phishing phishing all these things are techniques that could be deployed metaphorically to viral distribution a biohazard or bio warfare if you will will it look the same and how do you defend against the next covet 19 this is what you know average Americans are seeing the impact of the economy with the shelter in place is that what happens again and how do we prevent it and so a lot of people are thinking about this what is your thoughts because it kind of feels the same way as cybersecurity you got to see it early you got to know what's going on you got to identify it you got to respond to it time to close your contain similar concepts what's your thoughts on with BIOS we don't look with all due respect to the the the bio community let me make a quick analogy to the cyber security strategy right cyber security strategy starts with we start as an attacker so I parts of my previous career I'm an authorized had the opportunity to help develop tools that are very very precisely targeted against foreign adversaries and that's a harder job than you think I mean I think the same is true of anyone of a natural-born or a custom a buyer buyer is that not just any virus has the capability to do a lot of harm to a lot of people selling it so it's it's if that doesn't mean though you can sit back and say since it's hard it'll never happen you need to take proactive measures to look for evidence of a compromise of something whether it's a cyber cyber virus or otherwise you have to actively look for that you have to harm yourself to make sure you're not susceptible to it and once you detect one you need to make sure you have a the ability to do segmentation or quarantine very rapidly very very effectively right so in the cyber security community of course the fundamental strategy is about segmentation you keep different types of things separate that don't need to interact and then if you do have a compromise not everything is compromised and then lastly if you want to gradually say bring things back up to recover you can do some with small chunks I think it's a great analogy segmentation is a good analogy to I think what the nation is trying to do right now by warranty kneeing and gradually reopening up things in in segments in actually mention earlier that some of the other techniques are very very similar you want to have good visibility of where you're at risk and then you can automatically detect and then implement some some mitigations based on that good visibility so I agree with you that it turns out that the cyber security strategies might have a whole lot in common with biohazard I address it's interesting site reliability engineers which is a term that Google coined when they built out their large-scale cloud has become a practice that kind of mindset combined with some of the things that you're saying the cyber security mindset seemed to fit this at scale problem space and I might be an alarmist but I personally believe that we've been having a digital war for many many years now and I think that you know troops aren't landing but it's certainly digital troops and I think that we as a country and a global state and global society have to start thinking about you know these kinds of things where a virus could impact the United States shut down the economy devastating impact so I think Wars can be digital and so I may be an alarmist and a conspirators but I think that you know thinking about it and talking about it might be a good thing so appreciate your insights there Phil appreciated what one other point that might be interesting a few years back I was doing some research with the National Lab and we're looking for novel of cybersecurity analytics and we hired some folks who worked in the biology the bio the biomedical community who were studying a biome fires at the time and it was in recognition that there's a lot of commonality between those who are doing cybersecurity analytics and those reviewing bio biology or biomedical type analytics in you know there was a lot of good cross fertilization between our teams and it kind of helps you bring up one more there's one more point which is what we need to do in cybersecurity in general is have more diversity of workforces right now I don't mean just the traditional but important diversities of sex or color but diversity of experiences right some of the best people I've worked with in the cyber analytics field weren't computer science trained people and that's because they came in problems differently with a different background so one of the things that's really important to our field at large and of course the company my company fort net is to massively increase the amount of cyber security training that's available to people not just the computer scientists the world and the engineers but people in other areas as well the other degree to non-greek people and with that a you know higher level of cyber security training available to a more diverse community not only can we solve the problem of numbers we don't have enough cybersecurity people but we can actually increase our ability to defend against these things I have more greater diversity of thought experience you know that's such a great point I think I just put an exclamation point on that I get that question all the time and the skills gap is should I study computer science and like actually if you can solve problems that's a good thing but really diversity about diversity is a wonderful thing in the age of unlimited compute power because traditionally diversity whether it was protocol diversity or technical diversity or you know human you know makeup that's tend to slow things down but you get higher quality so that's a generalization but you get the point diversity does bring quality and if you're doing a data science you don't want have a blind spot I'm not have enough data so yeah I think a good diverse data set is a wonderful thing you're going to a whole nother level saying bringing diversely skill sets to the table because the problems are diverse is that what you're getting at it is it's one of our I'll say our platforms that we're talking about during the during the covered nineteen crisis which is perhaps there's perhaps we could all make ourselves a little bit better by taking some time out since we're not competing taking some time out and doing a little bit more online training where you can where you can either improve your current set of cybersecurity skills of knowledge or be introduced to them for the first time and so there's one or some wonderful Fortinet training available that can allow both the brand-new folks the field or or the the intermediate level folks with you become higher level experts it's an opportunity for all of us to get better rather than spending that extra hour on the road every day why don't we take at least you know 30 of those 60 minutes or former commute time and usually do some online soccer security treaty feel final question for you great insight great conversation as the world and your friends my friends people we don't know other members of society as they start to realize that the virtualization of life is happening just in your section it's convergence what general advice would you have for someone just from a mental model or mindset standpoint to alleviate any anxiety or change it certainly will be happening so how they can better themselves in their life was it is it thinking more about the the the experiences is it more learning how would you give advice to folks out there who are gonna come out of this post pandemic certainly it's gonna be a different world we're gonna be heightened to digital and virtual but as things become virtualized how can someone take this and make a positive outcome out of all this I I think that the future the future remains bright earlier we talked about sci-fi the integration of the cyber world in the physical world that's gonna provide great opportunities to make us more efficient gives us more free time detect bad things from happening earlier and hopefully mitigating those bad things from happening earlier so a lot of things that some people might use as scare tactics right convergence and Skynet in in robotics and things like that I believe these are things that will make our lives better not worse our responsibilities though is talking about those things making sure people understand that they're coming why they're important and make sure we're putting the right security and privacy to those things as these worlds this physical world and the soccer worlds converged I think the future is bright but we still have some work to do in terms of um making sure we're doing things at very high speeds there's no delay in the cybersecurity we put on top of these applications and make sure we have very very well integrated solutions that don't cause things to become more complex make make things easier to do certainly the winds of change in the big waves with the transformations happening I guess just summarize by saying just make it a head win I mean tailwind not a headwind make it work for you at the time not against it Phil thank you so much for your insights I really appreciate this cube conversation remote interview I'm John Ford with the cube talking about cybersecurity and the fundamentals of understanding what's going on in this new virtual world that we're living in to being virtualized as we get back to work and as things start to to evolve further back to normal the at scale problems and opportunities are there and of course the key was bringing it to you here remotely from our studio I'm John Ferrier thanks for watching [Music]

(upbeat music) >> >> Welcome back everybody to this special presentation of theCUBE where we're covering the rebirth of Oracle Consulting. It's a digital event, where we're going out, we're extracting the signal from the noise. We happen today to be in Chicago, which is obviously the center of the country, a lot of big customers here, a lot of consultants and consulting organizations here, a lot of expertise. Mike Owens is here. He is the group VP for Cloud Advisory and the General Manager of Oracle Elevate. Mike, thanks for coming on theCUBE. >> I appreciate it. Glad to be here. >> So I'm got to ask you, elevate, in your title, what is Oracle Elevate? >> Yeah, Oracle Elevate was actually announced Oracle OpenWorld last year. And it's the partnership that we really had to actually take our scale to the next level. So we actually did it with Deloitte Consulting. So the goal is to actually take the capabilities of both organizations. Deloitte really has functional capabilities and expertise, with an Oracle practice and obviously Oracle has, Oracle technical expertise. The combination the two really allows us to scale, provide sort of what I call the one plus one equals three, effort for customers. >> Now you've got a decent timeline or observation over the past several years. I think you joined three years ago, you were at some brand name companies. First of all, what attracted you to come to Oracle Consulting? >> Yeah, absolutely. So Oracle was in the point where they were doing a lot of stuff around on-prem, on-premise software, right? The old ERP type stuff, they were doing cloud, they sort of had to had this sort of transformational moment. I was asked to come in Oracle Consulting in the early days and say, "Hey, look, "we're trying to transform the organization "from on-prem consulting over to cloud consulting. "Come in and help us with this stuff "that you've worked from your prior two cloud companies, "and help us really move the organization forward "and look at things differently." So it's definitely been a journey over the last three years. I've taken it from nearly 85% of the 90% of our revenue around on-prem type of engagements, to now actually splitting the organization, being dedicated 100% on cloud, which is the huge transformation in the last three years. >> Yeah and so of course Oracle is a product company and your then CTO, Larry Ellison said, "We're going cloud first." And that happened during your tenure. You came in, I believe prior to that. What kind of effect did that have on the organization? I mean, we know from a product standpoint, but just culturally and just the mindset. >> Yeah, absolutely. It had a huge effect on the organization. They started splitting the organization to actually have be dedicated organizations, whether it's sales on product, whether it's support for product, pre sales support or our engineering and solutions architecture, and our consulting. So we've now split the organizations to primarily support those different lines of business, and what that allows us to do is actually focus that and put a lot of the stuff on cloud and moving the company a cloud first at this point. We still have a lot of organizations that do either on-prem type of work and things like that, they can't move over, that's supported, but you're going to see a larger shift of the cloud first, right? To actually move our customers and our organizations and back to what you hear a bunch of our executives talk about. We also actually use our own capabilities as well too. Whether it's AI or machine learning and the way we actually use it in our own HR systems. If I do my expense reporting, there's actually an AI bot that I can actually put stuff in there and automatically pulls it in. We actually take those capabilities and consume them ourselves because we have to believe in what we actually create as well. >> Your definition of cloud, of course, is different from the hyperscale cloud providers would say, "Hey, our cloud is hyperscale. "Put it in our cloud. "On-prem doesn't equal cloud." You guys don't buy into that obviously. Your definition is, it's the experience, wherever your data is, we're going to bring that cloud experience. Clarify that if you would. >> Yeah, I'll kind of give the Oracle version and what I've talked about for years for Oracle, or for cloud consultancy as a whole or cloud capabilities, right? So Oracle really looks at true enterprise capabilities. And it's kind of what I've been talking about for years publicly as well too. Cloud is really, when they say cloud, it's not just 100% in cloud, it's a combination that you pull from on-prem your systems and engagement. Your systems of record all get created together. Sometimes it's an ecosystem with another company, right? So the more connected we are, so cloud is really an enabler to sort of pull everything together, right? Oracle is really focused on a lot on the enterprise capabilities. Some of the other cloud providers do great on some of the systems of engagement, the smaller applications, what's sitting in someone's cell phone or hands all the time. Oracle is really around foundation of the database in data. So we start with that enterprise and come up versus creating that really snazzy application coming down to make it enterprise level. So we take at that approach. I look at cloud computing, and my definition is really different than most people and it's really around a way of doing business. And what I mean by that is, it's a business that's technology enabled specifically, right? So you have to change the way that you do business. The way that you engage with your customers, with their customers, right? The actual customer on the end line. Cloud capabilities really aren't changing your operating model, it's change the way that you organize, you govern. You can't just, if you take a great capability and move it forward, and then turn around and do it in the same way in process, that's where you lose the efficiency. If you talk about things like business case, where we see the technology itself as a standalone, will give 30% of that business case, changing the way that you operate and engage people, will actually give you the bigger benefit, right? So if you actually go forward and as we talked about a cloud transformation, not only is around changing the capabilities from the tool standpoint, it's your people and your skills and your operating model, right? So if you look at an operating model potentially has seven or eight dimensions depending on what organization you kind of talk to, right? Gartner or whatever. If you don't hit every single and understand the impacts of every portion of the operating model and make the change, you will not reap the benefits. >> And my litmus test is that experience has to be the same whether it's in your public cloud, whether it's on-prem, whether it's in a partner, multicloud, and that you guys actually came up with the notion of same, same. It took some time to actually deliver that, but do you feel like you're there now with customers that buy in and lean in? >> Yeah, absolutely. And so the concept of what I call your mess for less or picking it up and moving it over there, has no value. It could be the first step. So a cloud journey, it may give you incremental value, but it should be the first step in your journey. So if we talk about like cloud journeys, if you're going to say, no, it's the same, same, you're going to move it over there, that may give you back to the sort of the slope on the business case. That's going to give you an increment of that which should self fund then it to go okay, I'm going to take that, I'm going to decompose that. Okay, great. Now, I'm going to expand on that, I'm going to take that money to actually reinvest in automation, right? So if you move it over to infrastructure, right? Where are you going to get the automation, is really on the path's layer. All the services, the monitoring, the autonomous capabilities, all those kind of things, that's where you drive efficiency and scale. So you basically self fund with the infrastructure transformation with potentially, typical journey we see customers with right? As let's move it, let's use that funding to actually automate it, it gets more savings, we use that more for innovation. So it's kind of a continuous stream. You want to get to the point where you can actually have a continuous innovation stream. And what I mean by that is, you have a mechanism or a capability. If you look at our Gen 2 Cloud versus our Gen 1 Cloud. Gen 2 cloud actually can take advantage of all the capabilities that we have from the past layer through automation, right? And then as you do that, we actually want to have a continuous process where you constantly look for innovation and incrementally add pieces over time. It's no longer, it's a bing bing. It's just a continuous stream of innovation. >> So okay, so you've made the statement that the business case for Oracle Gen 2 Cloud is overwhelming. First of all, what really, what's the underpinning of Gen 2 Cloud? Can you give us sort of the bumper sticker on that? >> Yeah, well, the underpinning the Gen 2 Cloud is really, if you look at the Gen 1 Cloud was purely just an infrastructure layer. Gen 2 is really based on a segmenting security, which is a huge problem out in the marketplace, right Dave? So we actually have a sort of a world class way where we take this segments security outside of the actual environment itself. It's completely segmented. Which is awesome, right? But then they also, when you actually move it forward, the capability of the entire thing is built on sort of the autonomous enterprise or autonomous capabilities. Everything is sort of self healing, self funding, or no sorry, self healing and self aware that continually moves it forward. So the goal with that is, is if you have something that takes mundane tasks back to that, you have people that are no longer doing those capabilities today. So the underpinning of that, and what that allows you to do is actually take that business case, and you reduce that because you're no longer having a bunch of people do things that are no value add. Those people can actually move on to do back to the innovation and doing those higher level components. >> So the business case is really about, I mean, primarily, I would imagine about labor cost, right? IT labor costs, we're very labor intensive, we're doing stuff that doesn't necessarily add differentiation of value to the business. You're shifting that to other tasks, right? >> Yeah. So the big components are really the overall cost of the infrastructure, what it takes to maintain the infrastructure and that's broken up into kind of two components. One of it is typical power, physical location, a building, all those kinds of things. And then the people that do the automations that take care of that right? At the lower level. The third level is, as you continue to sort of process in automation going forward, the people capability that actually maintains the applications becomes easier because you can actually extend those capabilities out into the application. Then you require fewer people to actually do the typical day to day things, whether it's DBAs, et cetera, like that. So it kind of becomes a continuous stream. There's various elements of the business case, you could sort of start with just the pure infrastructure cost, and then get some of the process and automations going forward, and then actually go that even further, right? And then as organizations, as a CIO, one of the questions I always have is, where do you want to end on this? And they say, "What are you talking about?" All right? (Dave chuckles) And it's really-- >> You're never done. >> You're on a journey, you're on a transformation I go, this is the big boy, big girl conversation, right? Do you want to have an organization that actually, it stays the same from a headcount standpoint? Or are you trying to look to a partner to do the-- Where are you trying to get your operating model? What is your company trying to get you to look at, right? Because all those inflection points takes a different step in the cloud journey. So as an advisor, right? As a trusted adviser, I ask those a half a dozen or so questions, I would kind of walk your organization through on sort of a cloud strategy, and I'll pick the path that kind of works with them. And if they want to go to a managed service provider, at the end, we would actually prepare someone either bring the partner in or have an associated partner we paired it off too, but we put the right pieces in place to make sure that that business case works. >> Well, that's interesting. That's a really important point because a lot of customers would say, "I don't want to reduce headcount. "I want to, I'm starving for people. "I want to retrain people." Some companies may want to say, "Hey, okay, "I got to reduce headcount. "It's a mandate." But most at least in these boom times are saying, "I want to shift." So my point to the business case is, if you're not going to cut people, then you have to have those people be more productive. And so the example that you gave in terms of making the application developers more productive is relevant. And I want to explain this is that, for example, very simple example, I'm inferring, you're going to be able to compress the time to value, you're going to reduce, lower your breakeven, accelerate the time to positive cash flow, if you will. >> That's an example. >> Absolutely. >> Of a value component to the business and part of the business case. Do people at look is that real? >> Absolutely, that's what it is. Definitely in the business case and I want you to call it the, when you hit your rate of return, right? The more that we can compress that and I would say back to the conversation we had earlier about elevate and some of the partnerships we have with Deloitte around that, a lot of that is to actually come up with enough capabilities that we can actually take the business case and actually reduce that and have special other things we can do for our customers, we're on financing and things like that to make it easier for them, right? We have options to make customers and actually help that business case. Some of the business cases we've seen, our entire IT organization saving 30% plus. Well, if you multiply that on a large fortune 100, that may have a billion dollar budget, that's real money. >> Yeah, but and-- Okay, yes, no doubt. But then, when you translate that into the business impact, you talked about the IT impact, but if you look at the business impact now it becomes telephone numbers. And actually CFOs oftentimes just don't even believe it, but it's true. Because if you can make the entire organization just, a half a percentage point more productive and you got 100,000 employees I mean, that overwhelms actually the IT business case. >> Sure. Yeah, and that's where that back to the sort of the steps in the business case is on the business and application side is making those folks actually more productive in the business case and saving them and adding whether it's a financial services and you're getting an application out to market that actually generates revenue, right? So that's, it's sort of the trickle effect. So when I look at I definitely look at it from a IT all the way through business. I am technically a business architect that does IT pretty damn good. >> Yeah and IT enables that sort of business. >> Absolutely. >> How do you, let's talk about this notion of continuous improvement, how are people thinking about that? Because you're talking a lot about just sort of self funding, and self progressing, sort of an organic entity that you're describing. How are people thinking about that? >> Yeah, I would say they're kind of a little bit over their map, right? But I would say that the goal is what we're trying to embed back to the operating model, we want to really embed is, sort of the concept of the cloud center of excellence. And as part of that, at the end, you have to have a set of functionality of folks that's constantly looking at the applications and our services of the different cloud providers or capabilities you have across the board. Everyone's got a multicloud environment, right? How do they take those services? They're probably already paying for it anyways, and as the components get released, how can you continually put little pieces in there and do little micro releases quarterly or in sorry, weekly, every month versus a big bang twice a year, right? Those little automation pieces continually add innovation in smaller chunks. And that's really the goal of cloud computing. And as you can actually break it up. It's no longer the Big Bang Theory, right? And I love that concept. Embedding that, whether you actually have a partner, with some of the stuff that we're doing that actually embed what we call like a day two services, that that's what it is. It's to support them, but also constantly look for different ways to include capabilities that were just released to add value on an ongoing basis. You don't have to go, "Hey, great, that capability came out. "It'll be on next year's release." No, it could be next week, next month, right? >> Well, so the outcome should be dramatically lowering costs. Really accelerating your time to value. It really is what you're describing and we've been talking about in terms of the autonomous enterprise. It's really a prerequisite for scale, isn't it? >> It is, absolutely, right? And so, when we use the term autonomous enterprise, I love that because that's actually a term I've been using for a few years, even before Larry started talking about the autonomous database. I talk about that environment of constantly look at a cloud capability and everything that you can put from a machine earlier into AI under to actually, basically let it run itself. The more that you can do that, the higher the value. And you put those people off in a higher level tasks, right? That's been going on every provider for a while. Oracle just has the capabilities now within the database that takes it to the next level, right? So we still are the only organization with that. Put that on top of our Gen 2 Cloud where all that is built in, as part of it going forward, that's where we have the upper level really at the enterprise computing level, right? We can work at all types of workload, but where we are niches, is really those big enterprise workloads, because that's where we started from data enterprise. >> I don't want to make it a technology discussion but said the only organization. You mean the only technology company with that autonomous database capabilities. Is that correct? >> Mike: Yes sir, yes. >> Okay, so I know I should have sort of talk about it, but Oracle I think talks about it more forcefully. We'll dig into that and report back. Mike, thanks so much for coming on theCUBE. I really appreciate it. Good stuff. >> Thank you very much. >> And thank you for watching. We'll be right back with our next guest. You're watching theCUBE. We're here in Chicago covering the rebirth of Oracle Consulting. I'm Dave Vellante. We'll be right back. (soft music)