(sparkly music) >> Welcome to the Cube Special Program series "Women of the Cloud", brought to you by AWS. I'm your host, Lisa Martin. I'm very pleased to welcome Veronica McCarthy to the program, Senior Sales Manager ISB for Amazon Web Services. Veronica, great to have you on the program. Thanks for joining me today. >> Thanks for having me. >> Tell me a little bit about your current role. A little bit about yourself. >> Absolutely. Yeah, so I've been at Amazon just about four years now. I am really passionate about technology. I've been in the tech industry for about 20 plus years. Right now I'm a sales leader, so I lead a team of folks that help software companies build technology in the cloud or move technology to the cloud and help them scale and innovate in the cloud. >> Awesome, I love that. Talk a little bit about for, for those looking to grow their careers in tech, what are some of the tactical recommendations that you have that you think are really, really pertinent for others that are looking to climb that ladder? >> Yeah, it's so important to have that passion for technology 'cause that's what we do every day. It excites me to jump out of bed and learn what's new, what's coming, what we're building together and how early we are in cloud computing and in technology as a whole. So really get curious and even, you know feel free to get, get hands on. I remember early as a kid just building computers with my dad in his room. So get hands on. Today there's so many things available on the internet for free tiers. You can just play with software to get building websites, games, whatever interests you. And oh by the way, watch the Cube 'cause you're going to learn a lot and you're going to get immersed in technology, which is so important when you're learning to grow a career here because it comes across when you're interviewing, when you're talking with others, when you're networking, that you're really interested in the topic and you're really here to, to grow and and help build tech to be what it can be in the future. >> These are all great recommendations for really building that authenticity. I love your advice of really from an immersion perspective. You're right, there's so many opportunities for people of all ages to start playing around with tech and, and, but that your point of opening up your mind and being curious and embracing the different learning paths is also that curiosity. I always think creativity as well are just really important recommendations for others that are looking to grow their career in tech. >> I want to understand some of, based on some of, of those tactical recommendations. Talk to us about a success story that you've had where you've solved problems for customers relating to cloud computing based on some of your recommendations. >> Totally, just picking up on the curiosity theme that we were talking about, one of the things that I did when I was earlier in my career and I was looking after a customer, is I got curious about their business. How did they interact with their customers? And I worked backwards from that experience 'cause they were selling to consumers and I said what if they could do all these other things that could open up the consumer's eyes? So I came up with a zany idea of what if they did a partnership with Amazon and we flew their goods directly to the end consumer by a drone, you know, just crazy stuff. And I wrote something called a PRFAQ which at Amazon we use very often. It's a press release, frequently asked questions. This PRFAQ was, what could you do in the future with tech? What could, you know things what could we unlock with tech in your business? The C-suite of this company said, "You know what, that's really interesting. We're not going to do that crazy drone thing. But we like the thinking, we like the learning we like thinking about the future. How does cloud help us unlock that future?" So the long story short, they had a monolith OnPrem getting their, getting their technology from a OnPrem monolith to microservices in the cloud unlocks and opens up APIs for them to partner with other organizations to grow their customer base and in turn grow their revenue. This company in particular, pandemic hit, market change. They had to pivot or else they were going to go out of business. And because we had moved their technology from an OnPrem monolith to the cloud they were able to make that pivot and they survived the pandemic and are thriving. So it's a real life example of a success story of just getting curious, understanding the customer's business, coming back from that and then aligning for the future and getting a customer to, to get curious with you and build for the future, which worked out. And who could have predicted the pandemic, but it worked >> Right. But getting the the customer to be curious with you kind of leads me into talking about, you know, and, and the customer wanting to embrace and, and embrace cloud computing is really a transformative business model. Also takes cultural impact. Sounds like what you've been able to achieve with this particular success story. The customer had the appetite from a cultural transformation perspective but that's a hard thing to accomplish. Talk a little bit about that maybe from that customer's perspective and how they really were able to transform into a culture that embraces cloud computing. >> Absolutely. You're spot on . With all of these transformations, it's people process technology. Technology's the easy part, right? The cloud's there, we can, the architecture's there, we can build software. It's the people and the process that's hard. So as part of that transformation and part of that engagement, they actually hired me. So I left Amazon and I went and became the VP of technology for this company and I led 650 engineers globally through this transformation from an OnPrem model with microservices in the cloud. So they put faith in me because they knew this was the outcome we needed to get to but they needed the people in the process to change. So bringing the, the engineers on that journey of I know you've been building this way for a really long time and in this place, we're going to bring you into the future and we're all going to do it together. So it's a learning journey because we're all going to learn how to build microservices in the cloud and we're going to do it together and then it opens up their future as well as they continue to grow as engineers. So it's not easy to do, but it takes time. But we were able to do it in that case. >> But you bring up a great point, it's a learning journey. Yeah. And for organizations to have that appetite and that understanding and appreciation, that is as critical as the technology. You talk about, you know, people across technology. The technology is easy, it's really changing the frames of mind at the speed at which they need to change for organizations to be competitive so they can leverage cloud to really help unlock the competitive advantage as as that success story customer that you mentioned. >> Absolutely. Absolutely. And building on that innovation, right which innovation is just a, a flywheel of learning. So absolutely. >> It is. Let's shift gears a little bit, but speaking of people and processes, you know, what are some of the challenges that you see from a diversity perspective whether it's thought diversity in tech today? >> Yeah, great question. Tech is an opportunity for a level playing ground because tech is a platform with which you can build things. The important piece of building tech though is we need to make sure that many diversities are represented in the room. So when we're making tech decisions of how we're going to build, what our consumers are going to, how they're going to interact with our technology. Not everyone is one individual person. It's not a monolith out there, you know consuming our technology. So let's make sure we have that diversity in the decision making and building the tech as well as in the user use case and, and working backwards from our end users of our technology. I think one of the most, one of the easiest ways to start to approach, approach that diversity of thought and getting that diversity within your teams is looking at a gender diversity ratio. And, and we've seen historically, whilst we've seen gains in gender diversity and technology over the last few years, it's still not where it needs to be. There's a stat that I read recently in a McKinsey study that only one in four C-suite leaders are women today. And of all of all the entry level jobs from entry level to manager of all, like let's say you take a hundred men only 87 of those are women that are concurrently being promoted. Only 82 are women of color. So it's an opportunity for us to really level the playing field and think about how do we intentionally put people in the room when tech decisions are being made that can make change and build tech for who we, we know is out there to consume and, and are be a part of our tech community. >> Intention you mentioned. That is so critical for organizations really need to be looking at diversity, DEI from a, from an an intentional perspective. It can't just be ad hoc here and there. They really have to have a strategy behind it. And when I see companies, and there are a few that I've worked with that really caught my eye that have done a phenomenal job of that thought diversity, gender diversity, cultural diversity within their leadership even the people that they put on stage to talk to their events, they stand out incredibly well. We also know that there's, you probably have numbers on this, that organizations with women in the C-suite are far more profitable than organizations that don't have that. So the data, we want to talk nerdy tech, the data is there. It's demonstrating what the potentials are the capabilities, the, the opportunities. Yet we're still so far behind and we have so much road to cover. We know the direction we need to go in, we just got to be able to get the teams behind that to get there. >> Absolutely. And data's key. I read a study recently that said if you don't have at least 30% diversity in the room when you're making decisions, you are statistically not going to make the right decision, which is incredible. So the powers and the data. We know better decisions are made. Companies do better when there's diversity in the room of all types. >> Absolutely. And can you imagine the sky's the limit, if organizations are actually able to just start making headway on that percentage number and shifting it towards that diversity. What incredible opportunities and technologies and services and solutions that can be developed and delivered to meet the demanding consumers needs. So much potential there. It's, it's a, it's kind of like a crystal ball. If only we had one, we could actually see what we could actually be. >> Yeah, you're absolutely right. And I think thinking about some of the older reasons why maybe women didn't stay in the workforce longer or maybe didn't take a a career in tech, a lot of those were minimized during the pandemic. So we think about the work from home concept, right? Like that's so normal now it's, we're no longer grinding you know, I have to leave early for daycare pickup or whatever the challenges or the perceived challenges there were to women progressing in their careers. A lot of that can be managed now. So there was some good things that have come out of that pandemic time that, you know, it's much more acceptable to be home remote working. I think the balance isn't making sure that we continue our in-person innovation where we can. I find with customers today, bringing executive teams together in a room to have them brainstorm and innovate is still priceless, right? Like we still have to spend that time, we're humans, but as a woman in technology, I love the flexibility that we are now taking and adopting as a norm. And even, you know, some of my male peers that have kids at home, they love being around the kids at home and and it's a, it's a real positive impact I think that we've had amongst a lot of negative impacts by the pandemic as well. >> It is, they're definitely silver linings. That's one of them. I was talking with somebody in, in Italy this morning we were filming and you said, "I don't think my daughters are going to run in here." And I thought, you know what, even if they do that's part of totally the remote workforce, that's part of the hybrid workforce that we're all embracing. But you bring up a great point about the in-person innovation. You know, events are starting to come back, so exciting. There's just certain things about event from an innovation perspective you just can't replicate by video. So getting those executives in a room together. Talk about what you guys are doing there and, and some of the things that you think of over the next few years that will really help drive evolution and innovation of tech. >> Absolutely, yeah. I have a lot of clients that often will say, "Oh well we're we're a remote first company." So it's okay that we do our innovation session online. But then I remind them of when was the last happy hour you had online? Like do you remember the early days of the pandemic? And we all sat on, you know pick your web conferencing platform and we, you know drank wine and but there was only one person that you could hear in that. So when they're, everybody's going around and all the boxes are on the screen, it was difficult to have multiple conversations. If you walk into a happy hour in, in real life people all over the room are having multiple conversations and a lot of different things are happening in the room at the same time. It's the same thing with innovation. If we bring an executive team into the room, guess what? There's going to be a couple sidebar conversations going on as the big room progresses. And that's really healthy and that's a great way to get people that may not be the one, the star of the happy hour that wants to speak the whole time to also get their inputs and their feedback into the innovation process. So that's just an example of why it's so important. One of the things we do here at Amazon is we have so called a digital innovation workshop which is exactly as it sounds, right? Just get in a room with some whiteboards, with some thought leaders and really let's innovate for the future and it's a blank sheet of paper kind of start and out of it we come up with a business plan, a PRFAQ, like a press release I mentioned in my story earlier. That's the seeds of that. So it's really powerful and I'm so excited we're continuing to do those face to face 'cause it's so important. >> It's so important, you know, to have diversity present in the room when decisions are being made, whether it's decisions about technology or not. That thought diversity is, and as the data show that you mentioned, demonstrates how much more successful and profitable organizations can be. I'm going to ask you kind of switching gears again. Last question. If we look kind of down the road from an evolution perspective of of you're in cloud, of your role evolving. What are some of the things that you see down down the pike? >> Yeah, so great question. I am in a field sales organization today, so when the pandemic first hit, I thought, oh boy, that's the end of our career. I think we're not going to be going out and calling on customers face to face anymore. But it's actually been the opposite. I've seen more engagement from our customers. They, they really do want to spend time with us innovating. When we come into those conversations we come in with a curious mindset. So I think from a field sales perspective, it's it's not, you know, going away. And I think it's going to continue to build and it's a great career for women in particular to get into. Super flexible, the privilege of travel which is a nice vacation from home life sometimes. And the, the benefit of working from home as well. So a good balance there. So I think from a, my role specifically it's going to continue to evolve and continue to be a growth area. >> From previous roles I've had where I've worked in technology and, and software development, I think are we're still such at early stages in cloud computing and cloud technology that there is so much technology that we're continuing to build from an engineering standpoint. And I think back to my, you know, 20 year old self if I was in those shoes today and I would absolutely be doing a career in engineering. I think it's such an exciting space and as a person of, of of a, as a female I want to be at the forefront of the engineering team. So I encourage anyone if they're, you know of a diverse background, like you are the people that I want in engineering in the future because that's how you're going to build the future is build the tech, which is really cool. >> So absolutely. It's, it's very cool. I do have one more question for you. What's of your lens, what's next in cloud? What are some of the things that you think are coming down the horizon? >> Yeah, so great question. So I, I actually have a son who's special needs and I think about some of the accommodations that we have to make for him today. And I think about the tech that's coming in terms of personal tech on helping him communicate or helping him read or helping him write. And I'm excited for his future where I think a diagnosis like his, if I'd gotten it many years ago, I would be very fearful about his future. But I know that tech is going to support people like him. So I'm excited for what it's going to do for humanity. I'm excited for what it's going to help us unlock for people that may have been hindered in previous lives. My, my mom grew up with a disability and she had to keep her career relatively low level because she couldn't overcome that disability without tech. And now that she has tech, you know it would've changed the game for her. So I'm excited for my son and his future. That's what inspires me and, and I'm excited about. >> I love that. Well, with a mom like you, he's sure to succeed and fly flying colors. Veronica, it's been such a pleasure having you on the Cube. >> Thank you. >> Exciting special series of women in the cloud. We so appreciate your insights and your time. You'll have to come back. >> Thank you so much. I appreciate it. >> All right, Veronica McCarthy. I'm Lisa Martin. You're watching The Cube's special program series Women of the Cloud, brought to you by AWS. Thanks for watching. (sparkly music)

>> Narrator: From theCUBE Studios in Palo Alto and Boston bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante >> Enterprise tech practitioners, like most of us they want to make their lives easier so they can focus on delivering more value to their businesses. And to do so, they want to tap best of breed services in the public cloud, but at the same time connect their on-prem intellectual property to emerging applications which drive top line revenue and bottom line profits. But creating a consistent experience across clouds and on-prem estates has been an elusive capability for most organizations, forcing trade-offs and injecting friction into the system. The need to create seamless experiences is clear and the technology industry is starting to respond with platforms, architectures, and visions of what we've called the Supercloud. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis we give you a preview of Supercloud 2, the second event of its kind that we've had on the topic. Yes, folks that's right Supercloud 2 is here. As of this recording, it's just about four days away 33 guests, 21 sessions, combining live discussions and fireside chats from theCUBE's Palo Alto Studio with prerecorded conversations on the future of cloud and data. You can register for free at supercloud.world. And we are super excited about the Supercloud 2 lineup of guests whereas Supercloud 22 in August, was all about refining the definition of Supercloud testing its technical feasibility and understanding various deployment models. Supercloud 2 features practitioners, technologists and analysts discussing what customers need with real-world examples of Supercloud and will expose thinking around a new breed of cross-cloud apps, data apps, if you will that change the way machines and humans interact with each other. Now the example we'd use if you think about applications today, say a CRM system, sales reps, what are they doing? They're entering data into opportunities they're choosing products they're importing contacts, et cetera. And sure the machine can then take all that data and spit out a forecast by rep, by region, by product, et cetera. But today's applications are largely about filling in forms and or codifying processes. In the future, the Supercloud community sees a new breed of applications emerging where data resides on different clouds, in different data storages, databases, Lakehouse, et cetera. And the machine uses AI to inspect the e-commerce system the inventory data, supply chain information and other systems, and puts together a plan without any human intervention whatsoever. Think about a system that orchestrates people, places and things like an Uber for business. So at Supercloud 2, you'll hear about this vision along with some of today's challenges facing practitioners. Zhamak Dehghani, the founder of Data Mesh is a headliner. Kit Colbert also is headlining. He laid out at the first Supercloud an initial architecture for what that's going to look like. That was last August. And he's going to present his most current thinking on the topic. Veronika Durgin of Sachs will be featured and talk about data sharing across clouds and you know what she needs in the future. One of the main highlights of Supercloud 2 is a dive into Walmart's Supercloud. Other featured practitioners include Western Union Ionis Pharmaceuticals, Warner Media. We've got deep, deep technology dives with folks like Bob Muglia, David Flynn Tristan Handy of DBT Labs, Nir Zuk, the founder of Palo Alto Networks focused on security. Thomas Hazel, who's going to talk about a new type of database for Supercloud. It's several analysts including Keith Townsend Maribel Lopez, George Gilbert, Sanjeev Mohan and so many more guests, we don't have time to list them all. They're all up on supercloud.world with a full agenda, so you can check that out. Now let's take a look at some of the things that we're exploring in more detail starting with the Walmart Cloud native platform, they call it WCNP. We definitely see this as a Supercloud and we dig into it with Jack Greenfield. He's the head of architecture at Walmart. Here's a quote from Jack. "WCNP is an implementation of Kubernetes for the Walmart ecosystem. We've taken Kubernetes off the shelf as open source." By the way, they do the same thing with OpenStack. "And we have integrated it with a number of foundational services that provide other aspects of our computational environment. Kubernetes off the shelf doesn't do everything." And so what Walmart chose to do, they took a do-it-yourself approach to build a Supercloud for a variety of reasons that Jack will explain, along with Walmart's so-called triplet architecture connecting on-prem, Azure and GCP. No surprise, there's no Amazon at Walmart for obvious reasons. And what they do is they create a common experience for devs across clouds. Jack is going to talk about how Walmart is evolving its Supercloud in the future. You don't want to miss that. Now, next, let's take a look at how Veronica Durgin of SAKS thinks about data sharing across clouds. Data sharing we think is a potential killer use case for Supercloud. In fact, let's hear it in Veronica's own words. Please play the clip. >> How do we talk to each other? And more importantly, how do we data share? You know, I work with data, you know this is what I do. So if you know I want to get data from a company that's using, say Google, how do we share it in a smooth way where it doesn't have to be this crazy I don't know, SFTP file moving? So that's where I think Supercloud comes to me in my mind, is like practical applications. How do we create that mesh, that network that we can easily share data with each other? >> Now data mesh is a possible architectural approach that will enable more facile data sharing and the monetization of data products. You'll hear Zhamak Dehghani live in studio talking about what standards are missing to make this vision a reality across the Supercloud. Now one of the other things that we're really excited about is digging deeper into the right approach for Supercloud adoption. And we're going to share a preview of a debate that's going on right now in the community. Bob Muglia, former CEO of Snowflake and Microsoft Exec was kind enough to spend some time looking at the community's supercloud definition and he felt that it needed to be simplified. So in near real time he came up with the following definition that we're showing here. I'll read it. "A Supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." So not only did Bob simplify the initial definition he's stressed that the Supercloud is a platform versus an architecture implying that the platform provider eg Snowflake, VMware, Databricks, Cohesity, et cetera is responsible for determining the architecture. Now interestingly in the shared Google doc that the working group uses to collaborate on the supercloud de definition, Dr. Nelu Mihai who is actually building a Supercloud responded as follows to Bob's assertion "We need to avoid creating many Supercloud platforms with their own architectures. If we do that, then we create other proprietary clouds on top of existing ones. We need to define an architecture of how Supercloud interfaces with all other clouds. What is the information model? What is the execution model and how users will interact with Supercloud?" What does this seemingly nuanced point tell us and why does it matter? Well, history suggests that de facto standards will emerge more quickly to resolve real world practitioner problems and catch on more quickly than consensus-based architectures and standards-based architectures. But in the long run, the ladder may serve customers better. So we'll be exploring this topic in more detail in Supercloud 2, and of course we'd love to hear what you think platform, architecture, both? Now one of the real technical gurus that we'll have in studio at Supercloud two is David Flynn. He's one of the people behind the the movement that enabled enterprise flash adoption, that craze. And he did that with Fusion IO and he is now working on a system to enable read write data access to any user in any application in any data center or on any cloud anywhere. So think of this company as a Supercloud enabler. Allow me to share an excerpt from a conversation David Flore and I had with David Flynn last year. He as well gave a lot of thought to the Supercloud definition and was really helpful with an opinionated point of view. He said something to us that was, we thought relevant. "What is the operating system for a decentralized cloud? The main two functions of an operating system or an operating environment are one the process scheduler and two, the file system. The strongest argument for supercloud is made when you go down to the platform layer and talk about it as an operating environment on which you can run all forms of applications." So a couple of implications here that will be exploring with David Flynn in studio. First we're inferring from his comment that he's in the platform camp where the platform owner is responsible for the architecture and there are obviously trade-offs there and benefits but we'll have to clarify that with him. And second, he's basically saying, you kill the concept the further you move up the stack. So the weak, the further you move the stack the weaker the supercloud argument becomes because it's just becoming SaaS. Now this is something we're going to explore to better understand is thinking on this, but also whether the existing notion of SaaS is changing and whether or not a new breed of Supercloud apps will emerge. Which brings us to this really interesting fellow that George Gilbert and I RIFed with ahead of Supercloud two. Tristan Handy, he's the founder and CEO of DBT Labs and he has a highly opinionated and technical mind. Here's what he said, "One of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse inside of your data lake. These are core concepts that the business should be able to create applications around very easily. In fact, that's not the case because it involves a lot of data engineering pipeline and other work to make these available. So if you really want to make it easy to create these data experiences for users you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes and they don't need to." A lot of implications to this statement that will explore at Supercloud two versus Jamma Dani's data mesh comes into play here with her critique of hyper specialized data pipeline experts with little or no domain knowledge. Also the need for simplified self-service infrastructure which Kit Colbert is likely going to touch upon. Veronica Durgin of SAKS and her ideal state for data shearing along with Harveer Singh of Western Union. They got to deal with 200 locations around the world in data privacy issues, data sovereignty how do you share data safely? Same with Nick Taylor of Ionis Pharmaceutical. And not to blow your mind but Thomas Hazel and Bob Muglia deposit that to make data apps a reality across the Supercloud you have to rethink everything. You can't just let in memory databases and caching architectures take care of everything in a brute force manner. Rather you have to get down to really detailed levels even things like how data is laid out on disk, ie flash and think about rewriting applications for the Supercloud and the MLAI era. All of this and more at Supercloud two which wouldn't be complete without some data. So we pinged our friends from ETR Eric Bradley and Darren Bramberm to see if they had any data on Supercloud that we could tap. And so we're going to be analyzing a number of the players as well at Supercloud two. Now, many of you are familiar with this graphic here we show some of the players involved in delivering or enabling Supercloud-like capabilities. On the Y axis is spending momentum and on the horizontal accesses market presence or pervasiveness in the data. So netscore versus what they call overlap or end in the data. And the table insert shows how the dots are plotted now not to steal ETR's thunder but the first point is you really can't have supercloud without the hyperscale cloud platforms which is shown on this graphic. But the exciting aspect of Supercloud is the opportunity to build value on top of that hyperscale infrastructure. Snowflake here continues to show strong spending velocity as those Databricks, Hashi, Rubrik. VMware Tanzu, which we all put under the magnifying glass after the Broadcom announcements, is also showing momentum. Unfortunately due to a scheduling conflict we weren't able to get Red Hat on the program but they're clearly a player here. And we've put Cohesity and Veeam on the chart as well because backup is a likely use case across clouds and on-premises. And now one other call out that we drill down on at Supercloud two is CloudFlare, which actually uses the term supercloud maybe in a different way. They look at Supercloud really as you know, serverless on steroids. And so the data brains at ETR will have more to say on this topic at Supercloud two along with many others. Okay, so why should you attend Supercloud two? What's in it for me kind of thing? So first of all, if you're a practitioner and you want to understand what the possibilities are for doing cross-cloud services for monetizing data how your peers are doing data sharing, how some of your peers are actually building out a Supercloud you're going to get real world input from practitioners. If you're a technologist, you're trying to figure out various ways to solve problems around data, data sharing, cross-cloud service deployment there's going to be a number of deep technology experts that are going to share how they're doing it. We're also going to drill down with Walmart into a practical example of Supercloud with some other examples of how practitioners are dealing with cross-cloud complexity. Some of them, by the way, are kind of thrown up their hands and saying, Hey, we're going mono cloud. And we'll talk about the potential implications and dangers and risks of doing that. And also some of the benefits. You know, there's a question, right? Is Supercloud the same wine new bottle or is it truly something different that can drive substantive business value? So look, go to Supercloud.world it's January 17th at 9:00 AM Pacific. You can register for free and participate directly in the program. Okay, that's a wrap. I want to give a shout out to the Supercloud supporters. VMware has been a great partner as our anchor sponsor Chaos Search Proximo, and Alura as well. For contributing to the effort I want to thank Alex Myerson who's on production and manages the podcast. Ken Schiffman is his supporting cast as well. Kristen Martin and Cheryl Knight to help get the word out on social media and at our newsletters. And Rob Ho is our editor-in-chief over at Silicon Angle. Thank you all. Remember, these episodes are all available as podcast. Wherever you listen we really appreciate the support that you've given. We just saw some stats from from Buzz Sprout, we hit the top 25% we're almost at 400,000 downloads last year. So really appreciate your participation. All you got to do is search Breaking Analysis podcast and you'll find those I publish each week on wikibon.com and siliconangle.com. Or if you want to get ahold of me you can email me directly at David.Vellante@siliconangle.com or dm me DVellante or comment on our LinkedIn post. I want you to check out etr.ai. They've got the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Supercloud two or next time on breaking analysis. (light music)

>>Welcome to this cube conversation. I'm Lisa Martin. I'm joined by Derek manky next, the chief security insights and global threat alliances at 40 guard labs. Derek. Welcome back. >>Yeah, it's great to be here again. So then, uh, uh, a lot of stuff's happened since we last talked. >>One of the things that was really surprising from this year's global threat landscape report is a 10 more than 10 X increase in ransomware. What's going on? What have you guys seen? >>Yeah, so, uh, th th this is, is massive. We're talking about a thousand percent over a 10, a 10 X increase. This has been building police. So this, this has been building since, uh, December of 2020 up until then we saw relatively low, uh, high watermark with ransomware. Um, it had taken a hiatus really because cyber criminals were going after COVID-19 lawyers and doing some other things at the time, but we did see us a seven fold increase in December, 2020. That is absolutely continued. Uh, continued this year into a momentum up until today. It continues to build never subsided. Now it's built to this monster, you know, almost 11 times increase from, from what we saw back last December and what the, uh, the reason what's fueling. This is a new verticals that cyber criminals are targeting. We've seen the usual suspects like telecommunication government and, uh, position one and two, but new verticals that have risen up into this, uh, third and fourth position following our MSSP. And this is on the heels of the Casia attack. Of course, that happened in 2021, as well as operational technology. There's actually four segments, there's transportation, uh, automotive manufacturing, and then of course, energy and utility all subsequent to each other. So there's a huge focus now on, on OTA and MSSP for cybercriminals. >>One of the things that we saw last year, this time was that attackers had shifted their focus away from enterprise infrastructure devices, to home networks and consumer grade products. And now it looks like they're focusing on both. Are you seeing that? >>Yes, absolutely. I in two ways. So first of all, again, this is a kill chain that we talk about. They have to get a foothold into the infrastructure, and then they can load things like ransomware on there. They can little things like information Steelers as an example, the way they do that is through botnets. And, uh, what we reported in this, um, in the first half of 2021 is that Mariah, which is about a two to three-year old button that now is, is number one by far, it was the most prevalent bond that we've seen. Of course, the thing about Mariah is that it's an IOT based bot net. So it sits on devices, uh, sitting inside a consumer networks as an example, or home networks, right? And that, that can be a big problem. So that's the targets that cyber criminals are using. The other thing that we saw that was interesting was that one in four organizations detected malvertising. >>And so what that means at least, is that cyber criminals are shifting their tactics from going just from cloud-based or centralized email phishing campaigns to a web born threats, right? So they're infecting sites, waterhole attacks, where people would go to read their, their, their daily updates as an example of things that they do as part of their habits. Um, they're getting sent links to these sites that when they go to it, it's actually installing those botnets onto those systems. So they can get a foothold. We've also seen scare tactics, right? So they're doing new social engineering Lewis pretending to be human resource departments, uh, you know, uh, uh, it staff and personnel, as an example, with pop-ups through the web browser that looked like these people to fill out different forms and ultimately get infected on, on a home devices. >>Well, the home device we use is proliferate. It continues because we are still in this work from home work, from anywhere environment. Is that when you think a big factor in this increased from seven X to nearly 11 X, >>It is a factor. Absolutely. Yeah. Like I said, it's, it's also, it's a hybrid of sorts. So, so a lot of that activity is going to the MSSP, uh, angle, like I said, uh, to, to the OT. And so to those verticals, which by the way, are actually even larger than traditional targets in the past, like, uh, finance and banking is actually lower than that as an example. So yeah, we are seeing a shift to that. And like I said, that's, that's further, uh, backed up from what we're seeing on with the, the, the, the botnet activity specifically with Veronica too. Are >>You seeing anything in terms of the ferocity? We know that the volume is increasing. Are they becoming more ferocious? These attacks? >>Yeah. Yeah. There, there is. There's a lot of aggression out there, certainly from, from criminals. And I would say that the velocity is increasing, but the amount of, if you look at the cyber criminal ecosystem, the, the stakeholders, right. Um, that is increasing, it's not just one or two campaigns that we're seeing. Again, we're seeing, this has been a record cases here almost every week. We've seen one or two significant, you know, cyber security events that are happening. That is a dramatic shift compared to, to, to last year or even, you know, two years ago too. And this is because, um, because the cyber criminals are getting deeper pockets now, they're, they're becoming more well-funded and they have business partners, affiliates that they're hiring each one of those has their own methodology, and they're getting paid big. We're talking up to 70 to 80% commission, just if they actually successfully, you know, in fact, someone that pays for the ransom as an example. And so that's really, what's driving this too. It's, it's, it's a combination of this kind of perfect storm as we call it. Right. You have this growing attack surface and work from home, uh, environments, um, and footholds into those networks. But you have a whole bunch of other people now on the bad side that are orchestrating this and executing the attacks too. >>What can organizations do to start to slow down or limit the impacts of this growing ransomware as a service? >>Yeah, great question. Um, everybody has their role in this, I say, right? So, uh, if we look at, from a strategic point of view, we have to disrupt cyber crime. How do we do that? Um, it starts with the kill chain. It starts with trying to build resilient networks. So things like a ZTE and a zero trust network access, a SD LAN as an example, as an example for producting that land infrastructure on, because that's where the threats are floating to, right? That's how they get the initial footholds. So anything we can do on the, on the, you know, preventative, preventative side, making, uh, networks more resilient, um, also education and training is really key. Things like multi-factor authentication are all key to this because if you build that, uh, uh, preventatively and that's a relatively small investment upfront, Lisa compared to the collateral damage that can happen with these ransomware, it passes, the risk is very high. Um, that goes a long way. It also forces the attackers to it slows down their velocity. It forces them to go back to the drawing board and come up with a new strategy. So that is a very important piece, but there's also things that we're doing in the industry. There's some good news here too, uh, that we can talk about because there's, there's things that we can actually do. Um, apart from that to, to really fight cyber crime, to try to take the cyber criminal cell phone. >>All right. Hit me with the good news Derek. >>Yeah. So, so a couple of things, right. If we look at the bot net activity, there's a couple of interesting things in there. Yes, we are seeing Mariah rise to the top right now, but we've seen big problems of the past that have gone away or come back, not as prolific as before. So two specific examples, a motel that was one of the most prolific botnets that was out there for the past two to three years, there is a take-down that happened in January of this year. Uh, it's still on our radar, but immediately after that takedown, it literally dropped to half of the activity. It hadn't before. And it's been consistently staying at that low watermark now had that half percentage since, since that six months later. So that's very good news showing that the actual coordinated efforts that we're getting involved with law enforcement, with our partners and so forth to take down, these are actually hitting their supply chain where it hurts. >>Right. So that's good news part one trick. Bob was another example. This is also a notorious spot net take down attempt in Q4 of 2020. It went offline for about six months. Um, in our landscape report, we actually show that it came back online, uh, in about June this year. But again, it came down, it came back weaker and another form is not nearly as prolific as before. So we are hitting them where it hurts. That's, that's the really good news. And we're able to do that through new, um, what I call high resolution intelligence. >>Talk to me about that high resolution intelligence. What do you mean by that? >>Yeah, so this is cutting edge stuff really gets me excited and keeps, keeps me up at night in a good way. Uh, cause we're, we're looking at this under the microscope, right? It's not just talking about the why we know there's problems out there. We know there's, there's ransomware. We know there's the botnets, all these things, and that's good to know, and we have to know that, but we're able to actually zoom in on this now and look at it. So we, for the first time in the threat landscape report, we've published TTPs, the techniques, tactics procedures. So it's not just talking about the, what it's talking about, the how, how are they doing this? What's their preferred method of getting into systems? How are they trying to move from system to system and exactly how are they doing that? What's the technique. And so we've highlighted that it's using the MITRE attack framework TTP, but this is real-time data. >>And it's very interesting. So we're clearly seeing a very heavy focus from cyber criminals and attackers to get around security controls, to do defensive, Asian, to do privilege escalation on systems. So in other words, trying to be common administrator so they can take full control of the system. Uh, as an example, a lateral movement on there's still a preferred over 75%, 77, I believe percent of activity we observed from malware was still trying to move from system to system by infecting removable media like thumb drives. And so it's interesting, right? It's a brand new look on the, these a fresh look, but it's this high resolution is allowing us to get a clear image so that when we come to providing strategic guidance and solutions of defense, and also even working on these, take down that Fritz, it allows us to be much more effective. So >>One of the things that you said in the beginning was we talked about the increase in ransomware from last year to this year. You said, I don't think that we've hit that, that ceiling yet, but are we at an inflection points, the data showing that we're at an inflection point here with being able to get ahead of this? >>Yeah, I, I, I would like to believe so. Um, it, there is still a lot of work to be done. Unfortunately, if we look at, you know, there is a, a recent report put out by the department of justice in the S saying that, you know, the chance of, uh, criminal, uh, to be committing a crime, but to be caught in the U S is somewhere between 55 to 60%, the same chance for a cyber criminal lies less than 1% above 0.5%. And that's the bad news. The good news is we are making progress and sending messages back and seeing results. But I think there's a long road ahead. So, um, you know, there there's a lot of work to be done. We're heading in the right direction. But like I said, they say, it's not just about that. It's everyone has, has their role in this all the way down to organizations and end users. If they're doing their part and making their networks more resilient through this, through all the, you know, increasing their security stack and strategy, um, that is also really going to stop the, you know, really ultimately the profiteering, uh, that, that wave, you know, cause that continues to build too. So it's, it's a multi-stakeholder effort and I believe we are, we are getting there, but I continue to still, uh, you know, I continue to expect the ransomware wave to build. In the meantime, >>On the end user front, that's always one of the vectors that we talk about it's people, right? It's there's so there's so much sophistication in these attacks that even security folks and experts are nearly fooled by them. What are some of the things that you're saying that governments are taking action on some recent announcements from the white house, but other organizations like Interpol, the world, economic forum, cyber crime unit, what are some of the things that governments are doing that you're seeing that as really advantageous here for the good guys? >>Yeah, so absolutely. This is all about collaboration. Governments are really focused on public private sector collaboration. Um, so we've seen this across the board, uh, with 40 guard labs, we're on the forefront with this, and it's really exciting to see that it's great. Uh, there, there, there's always been a lot of will work together, but we're starting to see action now. Right. Um, Interpol is a great example. They recently this year held a high level forum on ransomware. I was actually spoken was part of that forum as well too. And the takeaways from that event were that we, this was a message to the world, that public private sector we need. They actually called ransomware a pandemic, which is what I've referred to it as before in itself as well too, because it is becoming that much of a problem and that we need to work together to be able to create action, action action against this measure, success become more strategic. >>The world economic forum, uh, were, were, uh, leading a project called the partnership against cyber crime threat map project. And this is to identify not just all this stuff we talked about in the threat landscape report, but also looking at, um, you know, things like how many different ransomware gangs are there out there. Uh, what are their money laundering networks look like? It's that side of the side of the supply chains of apple so that we can work together to actually take down those efforts. But it really is about this collaborative action that's happening and it's, um, innovation and there's R and D behind this as well. That's coming to the table to be able to make, you know, make it impactful. >>So it sounds to me like ransomware is no longer a for any organization in any, any industry you were talking about the expansion of verticals, it's no longer a, if this happens to us, but a matter of when and how do we actually prepare to remediate prevent any damage? Yeah, >>Absolutely. How do we prepare? The other thing is that there's a lot of, um, you know, with just the nature of, of, of cyber, there's a lot of, uh, connectivity. There's a lot of different, uh, it's not just always siloed attacks. Right? We saw that with colonial obviously this year where you have the talks on, on it that can affect consumers right now to consumers. Right. And so for that very reason, um, everybody's infected in this, uh, it, it truly is a pandemic, I believe on its own. Uh, but the good news is there's a lot of smart people, uh, on the good side and, you know, that's what gets me excited. Like I said, we're working with a lot of these initiatives and like I said, some of those examples I called up before, we're actually starting to see measurable progress against this as well. >>That's good. Well, never adult day, I'm sure. In your world, any thing that you think when we talk about this again, in a few more months of the second half of 2021, anything that, that you predict crystal ball wise that we're going to see? >>Yeah. I think that we're going to continue to see more of the, I mean, ransomware, absolutely. More of the targeted attacks. That's been a shift this year that we've seen. Right. So instead of just trying to infect everybody for ransom, but as an example of going after some of these new, um, you know, high profile targets, I think we're going to continue to see that happening from there. Add some more side on, on, and because of that, the average costs of these data breaches, I think they're going to continue to increase. Um, they had already did, uh, in, uh, 20, uh, 2021, as an example, if we look at the cost of the data breach report, it's gone up to about $5 million us on average, I think that's going to continue to increase as well too. And then the other thing too, is I think that we're going to start to see more, um, more, more action on the good side. Like we talked about, there was already a record amount of take downs that have happened five take downs that happened in January. Um, there were, uh, arrests made to these business partners that was also new. So I'm expecting to see a lot more of that coming out, uh, uh, towards the end of the year, too. >>So as the challenges persist, so do the good things that are coming out of this. They're working folks go to get this first half 2021 global threat landscape. What's the URL that they can go to. >>Yeah, you can check it all, all of our updates and blogs, including the threat landscape reports on blog about 40 nine.com under our threat research category. >>Excellent. I read that blog. It's fantastic. Derek, always a pleasure to talk to you. Thanks for breaking this down for us showing what's going on. Both the challenging things, as well as the good news. I look forward to our next conversation. >>Absolutely. It's great. Chatting with you again, Lisa. Thanks. >>Likewise for Derek manky. I'm Lisa Martin. You're watching this cube conversation.

>>Yeah, it's the queue covering the virtual vertical Big Data Conference 2020. Brought to you by vertical. >>Hi, everybody. And welcome to this cube special presentation of the vertical virtual Big Data conference. The Cube is running in parallel with Day One and day two of the vertical of Big Data event. By the way, the Cube has been every single big data event in It's our pleasure to be here in the virtual slash digital event as well. Gabriel Chapman is here. He's the director of Flash Blade Products Solutions Marketing at Pure Storage. Great to see you. Thanks for coming on. >>Great to see you too. How's it going? >>It's going very well. I mean, I wish we were meeting in Boston at the Encore Hotel, but, uh, you know, and hopefully we'll be able to meet it, accelerate at some point, future or one of the sub shows that you guys are doing the regional shows, but because we've been covering that show as well. But I really want to get into it. And the last accelerate September 2019 pure and vertical announced. Ah, partnership. I remember a joint being ran up to me and said, Hey, you got to check this out. The separation of compute and storage by EON mode now available on Flash Blade. So, uh and and I believe still the only company that can support that separation and independent scaling both on Prem and in the cloud. So I want to ask, what were the trends and analytical database and cloud led to this partnership? You know, >>realistically, I think what we're seeing is that there's been a kind of a larger shift when it comes to modern analytics platforms towards moving away from the traditional, you know, Hadoop type architecture where we were doing on and leveraging a lot of directors that storage primarily because of the limitations of how that solution was architected. When we start to look at the larger trends towards you know how organizations want to do this type of work on premises, they're looking at solutions that allow them to scale the compute storage pieces independently and therefore, you know, the flash blade platform ended up being a great solution to support America in their transition Tian mode. Leveraging essentially is an S three object store. >>Okay, so let's let's circle back on that you guys in your in your announcement of the flash blade, you make the claim that Flash Blade is the industry's most advanced file and object storage platform ever. That's a bold statement. So defend that What? >>I would like to go beyond that and just say, you know, So we've really kind of looked at this from a standpoint of, you know, as as we've developed Flash Blade as a platform and keep in mind, it's been a product that's been around for over three years now and has been very successful for pure storage. The reality is, is that fast file and fast object as a combined storage platform is a direction that many organizations are looking to go, and we believe that we're a leader in that fast object best file storage place in realistically, which we start to see more organizations start to look at building solutions that leverage cloud storage characteristics. But doing so on Prem for a multitude of different reasons. We've built a platform that really addresses a lot of those needs around simplicity around, you know, making things this year that you know, fast matters for us. Ah, simple is smart. Um we can provide, you know, cloud integrations across the spectrum. And, you know, there's a subscription model that fits into that as well. We fall that that falls into our umbrella of what we consider the modern day takes variance. And it's something that we've built into the entire pure portfolio. >>Okay, so I want to get into the architecture a little bit of flash blade and then understand the fit for, uh, analytic databases generally, but specifically for vertical. So it is a blade, so you got compute and network included. It's a key value store based system. So you're talking about scale out. Unlike, unlike, uh, pure is sort of, you know, initial products which were scale up, Um, and so I want on It is a fabric based system. I want to understand what that all means to take us through the architecture. You know, some of the quote unquote firsts that you guys talk about. So let's start with sort of the blade >>aspect. Yeah, the blade aspect of what we call the flash blade. Because if you look at the actual platform, you have, ah, primarily a chassis with built in networking components, right? So there's ah, fabric interconnect with inside the platform that connects to each one of the individual blades. Individual blades have their own compute that drives basically a pure storage flash components inside. It's not like we're just taking SSD is and plugging them into a system and like you would with the traditional commodity off the shelf hardware design. This is very much an engineered solution that is built towards the characteristics that we believe were important with fast filing past object scalability, massive parallel ization. When it comes to performance and the ability to really kind of grow and scale from essentially seven blades right now to 150 that's that's the kind of scale that customers are looking for, especially as we start to address these larger analytics pools. They are multi petabytes data sets, you know that single addressable object space and, you know, file performance that is beyond what most of your traditional scale up storage platforms are able to deliver. >>Yes, I interviewed cause last September and accelerate, and Christie Pure has been attacked by some of the competitors. There's not having scale out. I asked him his thoughts on that, he said Well, first of all, our flash blade is scale out. He said, Look, anything that adds complexity, you know we avoid. But for the workloads that are associated with flash blade scale out is the right sort of approach. Maybe you could talk about why that is. Well, >>realistically, I think you know that that approach is better when we're starting to work with large, unstructured data sets. I mean, flash blade is unique. The architected to allow customers to achieve superior resource utilization for compute and storage, while at the same time, you know, reducing significantly the complexity that has arisen around this kind of bespoke or siloed nature of big data and analytics solutions. I mean, we're really kind of look at this from a standpoint of you have built and delivered are created applications in the public cloud space of dress, you know, object storage and an unstructured data. And for some organizations, the importance is bringing that on Prem. I mean, we do see about repatriation coming on a lot of organizations as these data egress, charges continue to expand and grow, um, and then organizations that want even higher performance and what we're able to get into the public cloud space. They are bringing that data back on Prem They are looking at from a stamp. We still want to be able to scale the way we scale in the cloud. We still want to operate the same way we operate in the cloud, but we want to do it within control of our own, our own borders. And so that's, you know, that's one of the bigger pieces to that. And we start to look at how do we address cloud characteristics and dynamics and consumption metrics or models? A zealous the benefits and efficiencies of scale that they're able to afford but allowing customers to do that with inside their own data center. >>So you're talking about the trends earlier. You have these cloud native databases that allowed of the scaling of compute and storage independently. Vertical comes in with eon of a lot of times we talk about these these partnerships as Barney deals of you know I love you, You love me. Here's a press release and then we go on or they're just straight, you know, go to market. Are there other aspects of this partnership that they're non Barney deal like, in other words, any specific engineering. Um, you know other go to market programs? Could you talk about that a little bit? Yeah, >>it's it's It's more than just that what we consider a channel meet in the middle or, you know, that Barney type of deal. It's realistically, you know, we've done some first with Veronica that I think, really Courtney, if they think you look at the architecture and how we did, we've brought to market together. Ah, we have solutions. Teams in the back end who are, you know, subject matter experts. In this space, if you talk to joy and the people from vertical, they're very high on our very excited about the partnership because it often it opens up a new set of opportunities for their customers to leverage on mode and get into some of the the nuance task specs of how they leverage the depot depot with inside each individual. Compute node in adjustments with inside their reach. Additional performance gains for customers on Prem and at the same time, for them, that's still tough. The ability to go into that cloud model if they wish to. And so I think a lot of it is around. How do we partner is to companies? How do we do a joint selling motions? How do we show up in and do white papers and all of the traditional marketing aspects that we bring to the market? And then, you know, joint selling opportunities exist where they are, and so that's realistically. I think, like any other organization that's going to market with a partner on MSP that they have, ah, strong partnership with. You'll continue to see us, you know, talking about are those mutually beneficial relationships and the solutions that we're bringing to the market. >>Okay, you know, of course, he used to be a Gartner analyst, and you go to the vendor side now, but it's but it's, but it's a Gartner analyst. You're obviously objective. You see it on, you know well, there's a lot of ways to skin the cat There, there their strengths, weaknesses, opportunities, threats, etcetera for every vendor. So you have you have vertical who's got a very mature stack and talking to a number of the customers out there who are using EON mode. You know there's certain workloads where these cloud native databases makes sense. It's not just the economics of scaling and storage independently. I want to talk more about that. There's flexibility aspect as well. But Vertical really has to play its its trump card, which is Look, we've got a big on premise state, and we're gonna bring that eon capability both on Prem and we're embracing the cloud now. There obviously have been there to play catch up in the cloud, but at the same time, they've got a much more mature stack than a lot of these other cloud native databases that might have just started a couple of years ago. So you know, so there's trade offs that customers have to make. How do you sort through that? Where do you see the interest in this? And and what's the sweet spot for this partnership? You know, we've >>been really excited to build the partnership with vertical A and provide, you know, we're really proud to provide pretty much the only on Prem storage platform that's validated with the yang mode to deliver a modern data experience for our customers together. You know, it's ah, it's that partnership that allows us to go into customers that on Prem space, where I think that there's still not to say that not everybody wants to go there, but I think there's aspects and solutions that worked very well there. But for the vast majority, I still think that there's, you know, the your data center is not going away. And you do want to have control over some of the many of the assets with inside of the operational confines. So therefore, we start to look at how do we can do the best of what cloud offers but on prim. And that's realistically, where we start to see the stronger push for those customers. You still want to manage their data locally. A swell as maybe even worked around some of the restrictions that they might have around cost and complexity hiring. You know, the different types of skills skill sets that are required to bring applications purely cloud native. It's still that larger part of that digital transformation that many organizations are going for going forward with. And realistically, I think they're taking a look at the pros and cons, and we've been doing cloud long enough where people recognize that you know it's not perfect for everything and that there's certain things that we still want to keep inside our own data center. So I mean, realistically, as we move forward, that's, Ah, that better option when it comes to a modern architecture that can do, you know, we can deliver an address, a diverse set of performance requirements and allow the organization to continue to grow the model to the data, you know, based on the data that they're actually trying to leverage. And that's really what Flash was built for. It was built for a platform that could address small files or large files or high throughput, high throughput, low latency scale of petabytes in a single name. Space in a single rack is we like to put it in there. I mean, we see customers that have put 150 flash blades into production as a single name space. It's significant for organizations that are making that drive towards modern data experience with modern analytics platforms. Pure and Veronica have delivered an experience that can address that to a wide range of customers that are implementing uh, you know, particularly on technology. >>I'm interested in exploring the use case. A little bit further. You just sort of gave some parameters and some examples and some of the flexibility that you have, um, and take us through kind of what the customer discussions are like. Obviously you've got a big customer base, you and vertical that that's on Prem. That's the the unique advantage of this. But there are others. It's not just the economics of the granular scaling of compute and storage independently. There are other aspects of take us through that sort of a primary use case or use cases. Yeah, you >>know, I mean, I could give you a couple customer examples, and we have a large SAS analyst company which uses vertical on last way to authenticate the quality of digital media in real time, You know, then for them it makes a big difference is they're doing their streaming and whatnot that they can. They can fine tune the grand we control that. So that's one aspect that that we address. We have a multinational car car company, which uses vertical on flash blade to make thousands of decisions per second for autonomous vehicle decision making trees. You know, that's what really these new modern analytics platforms were built for, um, there's another healthcare organization that uses vertical on flash blade to enable healthcare providers to make decisions in real time. The impact lives, especially when we start to look at and, you know, the current state of affairs with code in the Corona virus. You know, those types of technologies, we're really going to help us kind of get of and help lower invent, bend that curve downward. So, you know, there's all these different areas where we can address that the goals and the achievements that we're trying to look bored with with real time analytics decision making tools like and you know, realistically is we have these conversations with customers they're looking to get beyond the ability of just, you know, a data scientist or a data architect looking to just kind of driving information >>that we're talking about Hadoop earlier. We're kind of going well beyond that now. And I guess what I'm saying is that in the first phase of cloud, it was all about infrastructure. It was about, you know, uh, spin it up. You know, compute and storage is a little bit of networking in there. >>It >>seems like the next new workload that's clearly emerging is you've got. And it started with the cloud native databases. But then bringing in, you know, AI and machine learning tooling on top of that Ah, and then being able to really drive these new types of insights and it's really about taking data these bog this bog of data that we've collected over the last 10 years. A lot of that is driven by a dupe bringing machine intelligence into the equation, scaling it with either cloud public cloud or bringing that cloud experience on Prem scale. You know, across organizations and across your partner network, that really is a new emerging workloads. You see that? And maybe talk a little bit about what you're seeing with customers. >>Yeah. I mean, it really is. We see several trends. You know, one of those is the ability to take a take this approach to move it out of the lab, but into production. Um, you know, especially when it comes to data science projects, machine learning projects that traditionally start out as kind of small proofs of concept, easy to spin up in the cloud. But when a customer wants to scale and move towards a riel you know, derived a significant value from that. They do want to be able to control more characteristic site, and we know machine learning, you know, needs toe needs to learn from a massive amounts of data to provide accuracy. There's just too much data retrieving the cloud for every training job. Same time Predictive analytics without accuracy is not going to deliver the business advantage of what everyone is seeking. You know, we see this. Ah, the visualization of Data Analytics is Tricia deployed is being on a continuum with, you know, the things that we've been doing in the long in the past with data warehousing, data Lakes, ai on the other end. But this way, we're starting to manifest it and organizations that are looking towards getting more utility and better elasticity out of the data that they are working for. So they're not looking to just build apps, silos of bespoke ai environments. They're looking to leverage. Ah, you know, ah, platform that can allow them to, you know, do ai, for one thing, machine learning for another leverage multiple protocols to access that data because the tools are so much Jeff um, you know, it is a growing diversity of of use cases that you can put on a single platform I think organizations are looking for as they try to scale these environment. >>I think it's gonna be a big growth area in the coming years. Gable. I wish we were in Boston together. You would have painted your little corner of Boston orange. I know that you guys have but really appreciate you coming on the cube wall to wall coverage. Two days of the vertical vertical virtual big data conference. Keep it right there. Right back. Right after this short break, Yeah.

>> from Cambridge, Massachusetts. It's the Cube covering M. I. T. Chief Data officer and Information Quality Symposium 2019 Brought to you by Silicon Angle Media >> Welcome back to M I. T. Everybody watching the Cube. The leader in live tech coverage we hear a Day two of the M I t chief data officer information Quality Conference Day Volonte with Paul Dillon. Andy Palmer's here. He's the co founder and CEO of Tamer. Good to see again. It's great to see it actually coming out. So I didn't ask this to Mike. I could kind of infirm from someone's dances. But why did you guys start >> Tamer? >> Well, it really started with an academic project that Mike was doing over at M. I. T. And I was over in of artists at the time. Is the chief get officer over there? And what we really found was that there were a lot of companies really suffering from data mastering as the primary bottleneck in their company did used great new tech like the vertical system that we've built and, you know, automated a lot of their warehousing and such. But the real bottleneck was getting lots of data integrated and mastered really, really >> quickly. Yeah, He took us through the sort of problems with obviously the d. W. In terms of scaling master data management and the scanning problems was Was that really the problem that you were trying to solve? >> Yeah, it really was. And when we started, I mean, it was like, seven years ago, eight years ago, now that we started the company and maybe almost 10 when we started working on the academic project, and at that time, people weren't really thinking are worried about that. They were still kind of digesting big data. A zit was called, but I think what Mike and I kind of felt was going on was that people were gonna get over the big data, Um, and the volume of data. And we're going to start worrying about the variety of the data and how to make the data cleaner and more organized. And, uh, I think I think way called that one pretty much right. Maybe >> we're a little >> bit early, but but I think now variety is the big problem >> with the other thing about your big day. Big data's oftentimes associated with Duke, which was a batch and then you sort of saw the shifter real time and spark was gonna fix all that. And so what are you seeing in terms of the trends in terms of how data is being used to drive almost near real time business decisions. >> You know, Mike and I came out really specifically back in 2007 and declared that we thought, uh, Hadoop and H D f s was going to be far less impactful than other people. >> 07 >> Yeah, Yeah. And Mike Mike actually was really aggressive and saying it was gonna be a disaster. And I think we've finally seen that actually play out of it now that the bloom is off the rose, so to speak. And so they're They're these fundamental things that big companies struggle with in terms of their data and, you know, cleaning it up and organizing it and making it, Iike want. Anybody that's worked at one of these big companies can tell you that the data that they get from most of their internal system sucks plain and simple, and so cleaning up that data, turning it into something it's an asset rather than liability is really what what tamers all about? And it's kind of our mission. We're out there to do this and it sort of pails and compare. Do you think about the amount of money that some of these companies have spent on systems like ASAP on you're like, Yeah, but all the data inside of the systems so bad and so, uh, ugly and unuseful like we're gonna fix that problem. >> So you're you're you're special sauce and machine learning. Where are you applying machine learning most most effectively when >> we apply machine learning to probably the least sexy problem on the planet. There are a lot of companies out there that use machine learning and a I t o do predictive algorithms and all kinds of cool stuff. All we do with machine learning is actually use it to clean up data and organize data. Get it ready for people to use a I I I started in the eye industry back in the late 19 eighties on, you know, really, I learned from the sky. Marvin Minsky and Mark Marvin taught me two things. First was garbage in garbage out. There's no algorithm that's worth anything unless you've got great data, and the 2nd 1 is it's always about the human in the machine working together. And I've really been working on those two same principles most of my career, and Tamer really brings both of those together. Our goal is to prepare data so that it can be used analytically inside of these companies, that it's actually high quality and useful. And the way we do that involves bringing together the machine, mostly these advanced machine learning algorithms with humans, subject matter experts inside of these companies that actually know all the ins and outs and all the intricacies of the data inside of their company. >> So say garbage in garbage out. If you don't have good training data course you're not going good ML model. How much how much upfront work is required. G. I know it was one of your customers and how much time is required to put together on ML model that can deal with 20,000,000 records like that? >> Well, you know, the amazing thing that this happened for us in the last five years, especially is that now we've got we've built enough models from scratch inside of these large global 2000 companies that very rarely do we go into a place where there we don't already have a model that's pre built. That they can use is a starting point. And I think that's the same thing that's happening in modeling in general. If you look a great companies like data robot Andi and even in in the Python community ml live that the accessibility of these modeling tools and the models themselves are actually so they're commoditized. And so most of our models and most of the projects we work on, we've already got a model. That's a starting point. We don't really have to start from scratch. >> You mentioned gonna ta I in the eighties Is that is the notion of a I Is it same as it was in the eighties and now we've just got the tooling, the horsepower, the data to take advantage of it is the concept changed? The >> math is all the same, like, you know, absolutely full stop, like there's really no new math. The two things I think that have changed our first. There's a lot more data that's available now, and, you know, uh, neural nets are a great example, right? in Marvin's things that, you know when you look at Google translate and how aggressively they used neural nets, it was the quantity of data that was available that actually made neural nets work. The second thing that that's that's changed is the cheap availability of Compute that Now the largest supercomputer in the world is available to rent by the minute. And so we've got all this data. You've got all this really cheap compute. And then third thing is what you alluded to earlier. The accessibility of all the math that now it's becoming so simple and easy to apply these math techniques, and they're becoming you know, it's It's almost to the point where the average data scientists not the advance With the average data, scientists can do a practice. Aye, aye. Techniques that 20 years ago required five PhDs. >> It's not surprising that Google, with its new neural net technology, all the search data that it has has been so successful. It's a surprise you that that Amazon with Alexa was able to compete so effectively. >> Oh, I think that I would never underestimate Amazon and their ability to, you know, build great tact. They've done some amazing work. One of my favorite Mike and I actually, one of our favorite examples in the last, uh, three years, they took their red shift system, you know, that competed with with Veronica and they they re implemented it and, you know, as a compiled system and it really runs incredibly fast. I mean, that that feat of engineering, what was truly exceptional >> to hear you say that Because it wasn't Red Shift originally Park. So yeah, that's right, Larry Ellison craps all over Red Shift because it's just open source offer that they just took and repackage. But you're saying they did some major engineering to Oh >> my gosh, yeah, It's like Mike and I both way Never. You know, we always compared par, excelled over tika, and, you know, we always knew we were better in a whole bunch of ways. But this this latest rewrite that they've done this compiled version like it's really good. >> So as a guy has been doing a eye for 30 years now, and it's really seeing it come into its own, a lot of a I project seems right now are sort of low hanging fruit is it's small scale stuff where you see a I in five years what kind of projects are going our bar company's gonna be undertaking and what kind of new applications are gonna come out of this? But >> I think we're at the very beginning of this cycle, and actually there's a lot more potential than has been realized. So I think we are in the pick the low hanging fruit kind of a thing. But some of the potential applications of A I are so much more impactful, especially as we modernize core infrastructure in the enterprise. So the enterprise is sort of living with this huge legacy burden. And we always air encouraging a tamer our customers to think of all their existing legacy systems is just dated generating machines and the faster they can get that data into a state where they can start doing state of the art A. I work on top of it, the better. And so really, you know, you gotta put the legacy burden aside and kind of draw this line in the sand so that as you really get, build their muscles on the A. I side that you can take advantage of that with all the data that they're generating every single day. >> Everything about these data repose. He's Enterprise Data Warehouse. You guys built better with MPP technology. Better data warehouses, the master data management stuff, the top down, you know, Enterprise data models, Dupin in big data, none of them really lived up to their promise, you know? Yeah, it's kind of somewhat unfair toe toe like the MPP guys because you said, Hey, we're just gonna run faster. And you did. But you didn't say you're gonna change the world and all that stuff, right? Where's e d? W? Did Do you feel like this next wave is actually gonna live up to the promise? >> I think the next phase is it's very logical. Like, you know, I know you're talking to Chris Lynch here in a minute, and you know what? They're doing it at scale and at scale and tamer. These companies are all in the same general area. That's kind of related to how do you take all this data and actually prepare it and turn it into something that's consumable really quickly and easily for all of these new data consumers in the enterprise and like so that that's the next logical phase in this process. Now, will this phase be the one that finally sort of meets the high expectations that were set 2030 years ago with enterprise data warehousing? I don't know, but we're certainly getting closer >> to I kind of hoped knockers, and we'll have less to do any other cool stuff that you see out there. That was a technology just >> I'm huge. I'm fanatical right now about health care. I think that the opportunity for health care to be transformed with technology is, you know, almost makes everything else look like chump change. What aspect of health care? Well, I think that the most obvious thing is that now, with the consumer sort of in the driver seat in healthcare, that technology companies that come in and provide consumer driven solutions that meet the needs of patients, regardless of how dysfunctional the health care system is, that's killer stuff. We had a great company here in Boston called Pill Pack was a great example of that where they just build something better for consumers, and it was so popular and so, you know, broadly adopted again again. Eventually, Amazon bought it for $1,000,000,000. But those kinds of things and health care Pill pack is just the beginning. There's lots and lots of those kinds of opportunities. >> Well, it's right. Healthcare's ripe for disruption on, and it hasn't been hit with the digital destruction. And neither is financialservices. Really? Certainly, defenses has not yet another. They're high risk industry, so Absolutely takes longer. Well, Andy, thanks so much for making the time. You know, You gotta run. Yeah. Yeah. Thank you. All right, keep it right. Everybody move back with our next guest right after this short break. You're watching the Cube from M I T c B O Q. Right back.