>>We're back at Super Computing, 22 in Dallas, winding down the final day here. A big show floor behind me. Lots of excitement out there, wouldn't you say, Dave? Just >>Oh, it's crazy. I mean, any, any time you have NASA presentations going on and, and steampunk iterations of cooling systems that the, you know, it's, it's >>The greatest. I've been to hundreds of trade shows. I don't think I've ever seen NASA exhibiting at one like they are here. Dave Nicholson, my co-host. I'm Paul Gell, in which with us is Satish Ier. He is the vice president of emerging services at Dell Technologies and Satit, thanks for joining us on the cube. >>Thank you. Paul, >>What are emerging services? >>Emerging services are actually the growth areas for Dell. So it's telecom, it's cloud, it's edge. So we, we especially focus on all the growth vectors for, for the companies. >>And, and one of the key areas that comes under your jurisdiction is called apex. Now I'm sure there are people who don't know what Apex is. Can you just give us a quick definition? >>Absolutely. So Apex is actually Dells for a into cloud, and I manage the Apex services business. So this is our way of actually bringing cloud experience to our customers, OnPrem and in color. >>But, but it's not a cloud. I mean, you don't, you don't have a Dell cloud, right? It's, it's of infrastructure as >>A service. It's infrastructure and platform and solutions as a service. Yes, we don't have our own e of a public cloud, but we want to, you know, this is a multi-cloud world, so technically customers want to consume where they want to consume. So this is Dell's way of actually, you know, supporting a multi-cloud strategy for our customers. >>You, you mentioned something just ahead of us going on air. A great way to describe Apex, to contrast Apex with CapEx. There's no c there's no cash up front necessary. Yeah, I thought that was great. Explain that, explain that a little more. Well, >>I mean, you know, one, one of the main things about cloud is the consumption model, right? So customers would like to pay for what they consume, they would like to pay in a subscription. They would like to not prepay CapEx ahead of time. They want that economic option, right? So I think that's one of the key tenets for anything in cloud. So I think it's important for us to recognize that and think Apex is basically a way by which customers pay for what they consume, right? So that's a absolutely a key tenant for how, how we want to design Apex. So it's absolutely right. >>And, and among those services are high performance computing services. Now I was not familiar with that as an offering in the Apex line. What constitutes a high performance computing Apex service? >>Yeah, I mean, you know, I mean, this conference is great, like you said, you know, I, there's so many HPC and high performance computing folks here, but one of the things is, you know, fundamentally, if you look at high performance computing ecosystem, it is quite complex, right? And when you call it as an Apex HPC or Apex offering offer, it brings a lot of the cloud economics and cloud, you know, experience to the HPC offer. So fundamentally, it's about our ability for customers to pay for what they consume. It's where Dell takes a lot of the day to day management of the infrastructure on our own so that customers don't need to do the grunge work of managing it, and they can really focus on the actual workload, which actually they run on the CHPC ecosystem. So it, it is, it is high performance computing offer, but instead of them buying the infrastructure, running all of that by themself, we make it super easy for customers to consume and manage it across, you know, proven designs, which Dell always implements across these verticals. >>So what, what makes the high performance computing offering as opposed to, to a rack of powered servers? What do you add in to make it >>Hpc? Ah, that's a great question. So, I mean, you know, so this is a platform, right? So we are not just selling infrastructure by the drink. So we actually are fundamentally, it's based on, you know, we, we, we launch two validated designs, one for life science sales, one for manufacturing. So we actually know how these PPO work together, how they actually are validated design tested solution. And we also, it's a platform. So we actually integrate the softwares on the top. So it's just not the infrastructure. So we actually integrate a cluster manager, we integrate a job scheduler, we integrate a contained orchestration layer. So a lot of these things, customers have to do it by themself, right? If they're buy the infrastructure. So by basically we are actually giving a platform or an ecosystem for our customers to run their workloads. So make it easy for them to actually consume those. >>That's Now is this, is this available on premises for customer? >>Yeah, so we, we, we make it available customers both ways. So we make it available OnPrem for customers who want to, you know, kind of, they want to take that, take that economics. We also make it available in a colo environment if the customers want to actually, you know, extend colo as that OnPrem environment. So we do both. >>What are, what are the requirements for a customer before you roll that equipment in? How do they sort of have to set the groundwork for, >>For Well, I think, you know, fundamentally it starts off with what the actual use case is, right? So, so if you really look at, you know, the two validated designs we talked about, you know, one for, you know, healthcare life sciences, and one other one for manufacturing, they do have fundamentally different requirements in terms of what you need from those infrastructure systems. So, you know, the customers initially figure out, okay, how do they actually require something which is going to require a lot of memory intensive loads, or do they actually require something which has got a lot of compute power. So, you know, it all depends on what they would require in terms of the workloads to be, and then we do havet sizing. So we do have small, medium, large, we have, you know, multiple infrastructure options, CPU core options. Sometimes the customer would also wanna say, you know what, as long as the regular CPUs, I also want some GPU power on top of that. So those are determinations typically a customer makes as part of the ecosystem, right? And so those are things which would, they would talk to us about to say, okay, what is my best option in terms of, you know, kind of workloads I wanna run? And then they can make a determination in terms of how, how they would actually going. >>So this, this is probably a particularly interesting time to be looking at something like HPC via Apex with, with this season of Rolling Thunder from various partners that you have, you know? Yep. We're, we're all expecting that Intel is gonna be rolling out new CPU sets from a powered perspective. You have your 16th generation of PowerEdge servers coming out, P C I E, gen five, and all of the components from partners like Invidia and Broadcom, et cetera, plugging into them. Yep. What, what does that, what does that look like from your, from your perch in terms of talking to customers who maybe, maybe they're doing things traditionally and they're likely to be not, not fif not 15 G, not generation 15 servers. Yeah. But probably more like 14. Yeah, you're offering a pretty huge uplift. Yep. What, what do those conversations look >>Like? I mean, customers, so talking about partners, right? I mean, of course Dell, you know, we, we, we don't bring any solutions to the market without really working with all of our partners, whether that's at the infrastructure level, like you talked about, you know, Intel, amd, Broadcom, right? All the chip vendors, all the way to software layer, right? So we have cluster managers, we have communities orchestrators. So we usually what we do is we bring the best in class, whether it's a software player or a hardware player, right? And we bring it together as a solution. So we do give the customers a choice, and the customers always want to pick what you they know actually is awesome, right? So they that, that we actually do that. And, you know, and one of the main aspects of, especially when you talk about these things, bringing it as a service, right? >>We take a lot of guesswork away from our customer, right? You know, one of the good example of HPC is capacity, right? So customers, these are very, you know, I would say very intensive systems. Very complex systems, right? So customers would like to buy certain amount of capacity, they would like to grow and, you know, come back, right? So give, giving them the flexibility to actually consume more if they want, giving them the buffer and coming down. All of those things are very important as we actually design these things, right? And that takes some, you know, customers are given a choice, but it actually, they don't need to worry about, oh, you know, what happens if I actually have a spike, right? There's already buffer capacity built in. So those are awesome things. When we talk about things as a service, >>When customers are doing their ROI analysis, buying CapEx on-prem versus, versus using Apex, is there a point, is there a crossover point typically at which it's probably a better deal for them to, to go OnPrem? >>Yeah, I mean, it it like specifically talking about hpc, right? I mean, why, you know, we do have a ma no, a lot of customers consume high performance compute and public cloud, right? That's not gonna go away, right? But there are certain reasons why they would look at OnPrem or they would look at, for example, Ola environment, right? One of the main reasons they would like to do that is purely have to do with cost, right? These are pretty expensive systems, right? There is a lot of ingress, egress, there is a lot of data going back and forth, right? Public cloud, you know, it costs money to put data in or actually pull data back, right? And the second one is data residency and security requirements, right? A lot of these things are probably proprietary set of information. We talked about life sciences, there's a lot of research, right? >>Manufacturing, a lot of these things are just, just in time decision making, right? You are on a factory floor, you gotta be able to do that. Now there is a latency requirement. So I mean, I think a lot of things play, you know, plays into this outside of just cost, but data residency requirements, ingress, egress are big things. And when you're talking about mass moments of data you wanna put and pull it back in, they would like to kind of keep it close, keep it local, and you know, get a, get a, get a price >>Point. Nevertheless, I mean, we were just talking to Ian Coley from aws and he was talking about how customers have the need to sort of move workloads back and forth between the cloud and on-prem. That's something that they're addressing without posts. You are very much in the, in the on-prem world. Do you have, or will you have facilities for customers to move workloads back and forth? Yeah, >>I wouldn't, I wouldn't necessarily say, you know, Dell's cloud strategy is multi-cloud, right? So we basically, so it kind of falls into three, I mean we, some customers, some workloads are suited always for public cloud. It's easier to consume, right? There are, you know, customers also consume on-prem, the customers also consuming Kohler. And we also have like Dell's amazing piece of software like storage software. You know, we make some of these things available for customers to consume a software IP on their public cloud, right? So, you know, so this is our multi-cloud strategy. So we announced a project in Alpine, in Delta fold. So you know, if you look at those, basically customers are saying, I love your Dell IP on this, on this product, on the storage, can you make it available through, in this public environment, whether, you know, it's any of the hyper skill players. So if we do all of that, right? So I think it's, it shows that, you know, it's not always tied to an infrastructure, right? Customers want to consume the best thumb and if we need to be consumed in hyperscale, we can make it available. >>Do you support containers? >>Yeah, we do support containers on hpc. We have, we have two container orchestrators we have to support. We, we, we have aner similarity, we also have a container options to customers. Both options. >>What kind of customers are you signing up for the, for the HPC offerings? Are they university research centers or is it tend to be smaller >>Companies? It, it's, it's, you know, the last three days, this conference has been great. We probably had like, you know, many, many customers talking to us. But HC somewhere in the range of 40, 50 customers, I would probably say lot of interest from educational institutions, universities research, to your point, a lot of interest from manufacturing, factory floor automation. A lot of customers want to do dynamic simulations on factory floor. That is also quite a bit of interest from life sciences pharmacies because you know, like I said, we have two designs, one on life sciences, one on manufacturing, both with different dynamics on the infrastructure. So yeah, quite a, quite a few interest definitely from academics, from life sciences, manufacturing. We also have a lot of financials, big banks, you know, who wants to simulate a lot of the, you know, brokerage, a lot of, lot of financial data because we have some, you know, really optimized hardware we announced in Dell for, especially for financial services. So there's quite a bit of interest from financial services as well. >>That's why that was great. We often think of Dell as, as the organization that democratizes all things in it eventually. And, and, and, and in that context, you know, this is super computing 22 HPC is like the little sibling trailing around, trailing behind the super computing trend. But we definitely have seen this move out of just purely academia into the business world. Dell is clearly a leader in that space. How has Apex overall been doing since you rolled out that strategy, what, two couple? It's been, it's been a couple years now, hasn't it? >>Yeah, it's been less than two years. >>How are, how are, how are mainstream Dell customers embracing Apex versus the traditional, you know, maybe 18 months to three year upgrade cycle CapEx? Yeah, >>I mean I look, I, I think that is absolutely strong momentum for Apex and like we, Paul pointed out earlier, we started with, you know, making the infrastructure and the platforms available to customers to consume as a service, right? We have options for customers, you know, to where Dell can fully manage everything end to end, take a lot of the pain points away, like we talked about because you know, managing a cloud scale, you know, basically environment for the customers, we also have options where customers would say, you know what, I actually have a pretty sophisticated IT organization. I want Dell to manage the infrastructure, but up to this level in the layer up to the guest operating system, I'll take care of the rest, right? So we are seeing customers who are coming to us with various requirements in terms of saying, I can do up to here, but you take all of this pain point away from me or you do everything for me. >>It all depends on the customer. So we do have wide interest. So our, I would say our products and the portfolio set in Apex is expanding and we are also learning, right? We are getting a lot of feedback from customers in terms of what they would like to see on some of these offers. Like the example we just talked about in terms of making some of the software IP available on a public cloud where they'll look at Dell as a software player, right? That's also is absolutely critical. So I think we are giving customers a lot of choices. Our, I would say the choice factor and you know, we are democratizing, like you said, expanding in terms of the customer choices. And I >>Think it's, we're almost outta our time, but I do wanna be sure we get to Dell validated designs, which you've mentioned a couple of times. How specific are the, well, what's the purpose of these designs? How specific are they? >>They, they are, I mean I, you know, so the most of these valid, I mean, again, we look at these industries, right? And we look at understanding exactly how would, I mean we have huge embedded base of customers utilizing HPC across our ecosystem in Dell, right? So a lot of them are CapEx customers. We actually do have an active customer profile. So these validated designs takes into account a lot of customer feedback, lot of partner feedback in terms of how they utilize this. And when you build these solutions, which are kind of end to end and integrated, you need to start anchoring on something, right? And a lot of these things have different characteristics. So these validated design basically prove to us that, you know, it gives a very good jump off point for customers. That's the way I look at it, right? So a lot of them will come to the table with, they don't come to the blank sheet of paper when they say, oh, you know what I'm, this, this is my characteristics of what I want. I think this is a great point for me to start from, right? So I think that that gives that, and plus it's the power of validation, really, right? We test, validate, integrate, so they know it works, right? So all of those are hypercritical. When you talk to, >>And you mentioned healthcare, you, you mentioned manufacturing, other design >>Factoring. We just announced validated design for financial services as well, I think a couple of days ago in the event. So yep, we are expanding all those DVDs so that we, we can, we can give our customers a choice. >>We're out of time. Sat ier. Thank you so much for joining us. Thank you. At the center of the move to subscription to everything as a service, everything is on a subscription basis. You really are on the leading edge of where, where your industry is going. Thanks for joining us. >>Thank you, Paul. Thank you Dave. >>Paul Gillum with Dave Nicholson here from Supercomputing 22 in Dallas, wrapping up the show this afternoon and stay with us for, they'll be half more soon.

(upbeat music) >> Welcome back to theCUBE's continuing coverage of Snowflake Summit 22 live from Caesars Forum in Las Vegas. I'm Lisa Martin with Dave Vellante. We've got a couple of guests joining us now. We're going to be talking about financial services. Rinesh Patel joins us, the Global Head of Financial Services for Snowflake, and Jack Berkowitz, Chief Data Officer at ADP. Guys, welcome to the program. >> Thanks, thanks for having us. >> Thanks for having us. >> Talk to us about what's going on in the financial services industry as a whole. Obviously, we've seen so much change in the last couple of years. What does the data experience look like for internal folks and of course, for those end user consumers and clients? >> So, one of the big things happening inside of the financial services industry is overcoming the COVID wait, right? A lot of banks, a lot of institutions like ours had a lot of stuff on-prem. And then the move to the Cloud allows us to have that flexibility to deal with it. And out of that is also all these new capabilities. So the machine learning revolution has really hit the services industry, right? And so it's affecting how our IT teams or our data teams are building applications. Also really affecting what the end consumers get out of them. And so there's all sorts of consumerization of the experience over the past couple of years much faster than we ever expected it to happen. >> Right, we have these expectations as consumers that bleed into our business lives that I can do transactions. It's going to be on the swipe in terms of checking authenticity, fraud detection, et cetera. And of course we don't want things to go back in terms of how brands are serving us. Talk about some of the things that you guys have put in place with Snowflake in the last couple of years, particularly at ADP. >> Yeah, so one of the big things that we've done, is, one of the things that we provide is compensation data. So we issue a thing called the National Employment Report that informs the world as to what's happening in the U.S. economy in terms of workers. And then we have compensation data on top of that. So the thing that we've been able to do with Snowflake is to lower the time that it takes us to process that and get that information out into the fingertips of people. And so people can use it to see what's changed in terms of with the worker changes, how much people are making. And they can get it very, very quickly. And we're able to do that with Snowflake now. Used to take us weeks, now it's in a matter of moments we can get that updated information out to people. >> Interesting. It helps with the talent war and- >> Helps in the talent war, helps people adjust, even where they're going to put supply chain in reaction to where people are migrating. We can have all of that inside of the Snowflake system and available almost instantaneously. >> You guys announced the Financial Data Cloud last year. What was that like? 'Cause I know we had Frank on early, he clearly was driving the verticalization of Snowflake if you will, which is kind of rare for a relatively new software company but what's that been like? Give us the update on where you're at and biggest vertical, right? >> Absolutely, it's been an exciting 12 months. We're a platform, but the journey and the vision is more. We're trying to bring together a fragmented ecosystem across financial services. The aim is really to bring together key customers, key data providers, key solution providers all across the different Clouds that exist to allow them to collaborate with data in a seamless way. To solve industry problems. To solve industry problems like ESG, to solve industry problems like quantitative research. And we're seeing a massive groundswell of customers coming to Snowflake, looking at the Financial Services Data Cloud now to actually solve business problems, business critical problems. That's really driving a lot of change in terms of how they operate, in terms of how they win customers, mitigate risk and so forth. >> Jack, I think, I feel like the only industry that's sometimes more complicated than security, is data. Maybe not, security's still maybe more fragmented- >> Well really the intersection of the two is a nightmare. >> And so as you look out on this ecosystem, how do you as the chief data officer, how do you and your organization, what process do you use to decide, okay, which of the, like a chef, which of these ingredients am I going to put together for my business. >> It's a great question, right? There's been explosion of companies. We kind of look at it in two ways. One is we want to make sure that the software and the data can interoperate because we don't want to be in the business of writing bridge code. So first thing is, is having the ecosystem so that the things are tested and can work together. The other area is, and it's important to us is understanding the risk profile of that company. We process about 20% of the U.S. payroll, another 25% of the taxes. And so there's a risk to us that we have an imperative to protect. So we're looking at those companies are they financed, what's their management team. What's the sales experience like, that's important to us. And so technology and the experience of the company coming together are super important to us. >> What's your purview as a chief data officer, I mean, a lot of CDOs that I know came out of the back office and it was a compliance or data quality. You come out of industry from a technology company. So you're sort of the modern... You're like the modern CDO. >> Thanks. Thanks. >> Dave: What's your role? >> I appreciate that. >> You know what I'm saying though? >> And for a while it was like, oh yeah, compliance. >> So I actually- >> And then all of a sudden, boom, big deal. >> Yeah, I really have two jobs. So I have that job with data governance but a lot of data security. But I also have a product development unit, a massive business in monetization of data or people analytics or these compensation benchmarks or helping people get mortgages. So providing that information, so that people can get their mortgage, or their bank loans, or all this other type of transactional data. *So it's both sides of that equation is my reading inside. >> You're responsible for building data products? >> That's right. >> Directly. >> That's right. I've got a massive team that builds data products. >> Okay. That's somewhat unique in your... >> I think it's where CDOs need to be. So we build data products. We build, and we assist as a hub to allow other business units to build analytics that help them either optimize their cost or increase their sales. And then we help with all that governance and communication, we don't want to divide it up. There's a continuum to it. >> And you're a peer of the CIO and the CISO? >> Yeah, exactly. They're my peers. I actually talk to them almost every day. So I've got the CIO as a peer. >> It's a team. >> I've got the security as a peer and we get things done together. >> Talk about the alignment with business. We've been talking a lot about alignment with the data folks, the business folks, the technical folks to identify the right solutions, to be able to govern data, to monetize it, to create data products. What does that... You mentioned a couple of your cohorts, but on the business side, who are some of those key folks? >> So we're like any other big, big organization. We have lots of different business units. So we work directly with either the operational team or the heads of those business units to divine analytic missions that they'll actually execute. And at the same time, we actually have a business unit that's all around data monetization. And so I work with them every single day. And so these business units will come together. I think the big thing for us is to define value and measure that value as we go. As long as we're measuring that value as we go, then we can continue to see improvements. And so, like I said, sometimes it's bottom line, sometimes it's top line, but we're involved. Data is actually a substrate of the company. It's not a side thing to the company. >> Yeah, you are. >> ADP. >> Yeah but if they say data first but you really are data first. >> Yeah. I mean, our CEO says- >> Data's your product. >> Data's our middle name. And it literally is. >> Well, so what do you do in the Snowflake financial services data Cloud? Are you monetizing? >> Yeah. >> What's the plan? >> Yeah, so we have clients. So part of our data monetization is actually providing aggregate and anonymized information that helps other clients make business decisions. So they'll take it into their analytics. So, supply chain optimization, where should we actually put the warehouses based on the population shifts? And so we're actually using the file distribution capabilities or the information distribution, no longer files, where we use Snowflake to actually be that data cloud for those clients. So the data just pops up for our other clients. >> I think the industry's existed a lot with the physical movement of data. When you physically move data, you also physically move the data management challenges. Where do you store it? How do you map it? How do you concord it? And ultimately data sharing is taking away that friction that exists. So it's easier to be able to make informed decisions with the data at hand across two counterparties. >> Yeah, and there's a benefit to us 'cause it lowers our friction. We can have a conversation and somebody can be... Obviously the contracts have to be signed, but once they get done, somebody's up and running on it within minutes. And where it used to be, as you were saying, the movement of data and loss of control, we never actually lose control of it. We know where it is. >> Or yeah, contracts signed, now you got to go through this long process of making sure everything's cool, or a lot of times it could slow down the sale. >> That's right. >> Let's see how that's going to... Let's do a little advanced work. Now you're working without a contract. Here, you can say, "Hey, we're in the Snowflake data cloud. It's governed, you're a part of the ecosystem." >> Yeah, and the ecosystem we announced, oh gee, I think it's probably almost a year and a half ago, a relationship with ICE, Intercontinental Exchange, where they're actually taking our information and their information and creating a new data product that they in turn sell. So you get this sort of combination. >> Absolutely. The ability to form partnerships and monetize data with your partners vastly increases as a consequence. >> Talk to us about the adoption of the financial services data cloud in the last what, maybe nine months or so, since it was announced? And also in terms of the its value proposition, how does the ADP use case articulate that? >> So, very much so. So in terms of momentum, we're a global organization, as you mentioned, we are verticalized. So we have increasingly more expertise and expertise experience now within financial services that allows us to really engage and accelerate our momentum with the top banks, with the biggest asset managers by AUM, insurance companies, sovereign wealth funds on Snowflake. And obviously those data providers and solution providers that we engage with. So the momentum's really there. We're really moving very, very fast in a great market because we've got great opportunity with the capabilities that we have. I mean, ADP is just one of many use cases that we're working with and collaborations that we're taking to market. So yeah, the opportunity to monetize data and help our partners monetize the data has vastly increased within this space. >> When you think about... Oh go ahead, please. >> Yeah I was just going to say, and from our perspective, as we were getting into this, Snowflake was with us on the journey. And that's been a big deal. >> So when you think about data privacy, governance, et cetera, and public policy, it seems like you have, obviously you got things going on in Europe, and you got California, you have other states, there's increasing in complexity. You guys probably love that. (Dave laughs) More data warehouses, but where are we at with that whole? >> It's a great question. Privacy is... We hold some of the most critical information about people because that's our job to help people get paid. And we respect that as sort of our prime agenda. Part of it deals with the technology. How do you monitor, how do you see, make sure that you comply with all these regulations, but a lot of it has to do with the basic ethics of why you're doing and what you're doing. So we have a data and AI ethics board that meets and reviews our use cases. Make sure not only are we doing things properly to the regulation, but are these the types of products, are these the types of opportunities that we as a company want to stand behind on behalf of the consumers? Our company's been around 75 years. We talk about ourselves as a national asset. We have a trust relationship. We want to ensure that that trust relationship is never violated. >> Are you in a position where you can influence public policy and create more standards or framework. >> We actually are, right. We issue something every month called the National Employment Report. It actually tells you what's happening in the U.S. economy. We also issue it in some overseas countries like France. Because of that, we work a lot with various groups. And we can help shape, either data policy, we're involved in understanding although we don't necessarily want to be out in the front, but we want to learn about what's happening with federal trade commission, EOC, because at the end of the day we serve people, I always joke ADP, it's my grandfather's ADP. Well, it was actually my grandfather's ADP. (Dave laughs) He was a small businessman, and he used a ADP all those years ago. So we want to be part of that conversation because we want to continue to earn that trust every day. >> Well, plus your observation space is pretty wide. >> And you've got context and perspective on that that you can bring. >> We move somewhere between two, two and a half trillion dollars a year through our systems. And so we understand what's happening in the economy. >> What are some of the, oh sorry. >> Can your National Employment Report combined with a little Snowflake magic tell us what the hell's going to happen with this economy? >> It's really interesting you say that. Yeah, we actually can. >> Okay. (panelists laugh) >> I think when you think about the amount of data that we are working with, the types of partners that we're working with, the opportunities are infinite. They really, really are. >> So it's either a magic eight ball or it's a crystal ball, but you have it. >> We think- >> We've just uncovered that here on theCUBE. >> We think we have great partners. We have great data. We have a set of industry problems out there that we're working, collaboration with the community to be able to solve. >> What are some of the upcoming use cases Rinesh, that excite you, that are coming up in financial services- >> Great question. >> That snowflake is just going to knock out of the park. >> So look, I think there's a set of here and now problems that the industry faces, ESG's a good one. If you think about ESG, it means many different things from business ethics, to diversity, to your carbon footprint and every asset manager has to make sure they have now some form of green strategy that reflects the values of their investors. And every bank is looking to put in place sustainable lending to help their corporate customers transition. That's a big data problem. And so we're very much at the center of helping those organizations support those informed investors and help those corporates transition to a more sustainable landscape. >> Let me give you an example on Snowflake, we launched capabilities about diversity benchmarks. The first time in the industry companies can understand for their industry, their size, their location what their diversity profile looks like and their org chart profile looks like to differentiate or at least to understand are they doing the right things inside the business. The ability for banks to understand that and everything else, it's a big deal. And that was built on Snowflake. >> I think it's massive, especially in the context of the question around regulation 'cause we're seeing more and more disclosure agreements come out where regulators are making sure that there's no greenwashing taking place. So when you have really strong sources of data that are standardized, that allow that investment process to ingest that data, it does allow for a better outcome for investors. >> Real data, I mean, that diversity example they don't have to rely on a survey. >> It's not a survey. >> Anecdotes. >> It's coming right out of the transactional systems and it's updated, whenever those paychecks are run, whether it's weekly, whether it's biweekly or monthly, all that information gets updated and it's available. >> So it sounds like ADP is a facilitator of a lot of companies ESG initiatives, at least in part? >> Well, we partner with companies all the time. We have over 900,000 clients and all of them are... We've never spoken to a client who's not concerned about their people. And that's just good business. And so, yeah we're involved in that and we'll see where it goes over time now. >> I think there's tremendous opportunity if you think about the data that the ADP have in terms of diversity, in terms of gender pay gap. Huge, huge opportunity to incorporate that, as I said into the ESG principles and criteria. >> Good, 'cause that definitely is what needs to be addressed. (Lisa laughs) Guys thank you so much for joining Dave and me on the program, talking about Snowflake ADP, what you're doing together, and the massive potential that you're helping unlock with the value of data. We appreciate your insights and your time. >> Thank you for having us. >> Dave: Thanks guys. >> Thank you so much. >> For our guests, and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, live in Las Vegas at Snowflake Summit 22. Dave and I will be right back with our next guest. (upbeat music)

(bright music) >> Okay, we're back in theCUBE. We said we were signing off for the night, but during the hallway track, we ran into old friend Stu Miniman who was the Director of Market Insights at Red Hat. Stu, friend of theCUBE done the thousands of CUBE interviews. >> Dave, it's great to be here. Thanks for pulling me on, you and I hosted Red Hat Summit before. It's great to see Paul here. I was actually, I was talking to some of the Red Hatters walking around Boston. It's great to have an event here. Boston's got strong presence and I understand, I think was either first or second year, they had it over... What's the building they're tearing down right down the road here. Was that the World Trade Center? I think that's where they actually held it, the first time they were here. We hosted theCUBE >> So they moved up. >> at the Hines Convention Center. We did theCUBE for summit at the BCEC next door. And of course, with the pandemic being what it was, we're a little smaller, nice intimate event here. It's great to be able to room the hall, see a whole bunch of people and lots watching online. >> It's great, it's around the same size as those, remember those Vertica Big Data events that we used to have here. And I like that you were commenting out at the theater and the around this morning for the keynotes, that was good. And the keynotes being compressed, I think, is real value for the attendees, you know? 'Cause people come to these events, they want to see each other, you know? They want to... It's like the band getting back together. And so when you're stuck in the keynote room, it's like, "Oh, it's okay, it's time to go." >> I don't know that any of us used to sitting at home where I could just click to another tab or pause it or run for, do something for the family, or a quick bio break. It's the three-hour keynote I hope has been retired. >> But it's an interesting point though, that the virtual event really is driving the physical and this, the way Red Hat marketed this event was very much around the virtual attendee. Physical was almost an afterthought, so. >> Right, this is an invite only for in-person. So you're absolutely right. It's optimizing the things that are being streamed, the online audience is the big audience. And we just happy to be in here to clap and do some things see around what you're doing. >> Wonderful see that becoming the norm. >> I think like virtual Stu, you know this well when virtual first came in, nobody had a clue with what they were doing. It was really hard. They tried different things, they tried to take the physical and just jam it into the virtual. That didn't work, they tried doing fun things. They would bring in a famous person or a comedian. And that kind of worked, I guess, but everybody showed up for that and then left. And I think they're trying to figure it out what this hybrid thing is. I've seen it both ways. I've seen situations like this, where they're really sensitive to the virtual. I've seen others where that's the FOMO of the physical, people want physical. So, yeah, I think it depends. I mean, reinvent last year was heavy physical. >> Yeah, with 15,000 people there. >> Pretty long keynotes, you know? So maybe Amazon can get away with it, but I think most companies aren't going to be able to. So what is the market telling you? What are these insights? >> So Dave just talking about Amazon, obviously, the world I live in cloud and that discussion of cloud, the journey that customers are going on is where we're spending a lot of the discussions. So, it was great to hear in the keynote, talked about our deep partnerships with the cloud providers and what we're doing to help people with, you like to call it super cloud, some call it hybrid, or multi-cloud... >> New name. (crosstalk) Meta-Cloud, come on. >> All right, you know if Che's my executive, so it's wonderful. >> Love it. >> But we'll see, if I could put on my VR Goggles and that will help me move things. But I love like the partnership announcement with General Motors today because not every company has the needs of software driven electric vehicles all over the place. But the technology that we build for them actually has ramifications everywhere. We've working to take Kubernetes and make it smaller over time. So things that we do at the edge benefit the cloud, benefit what we do in the data center, it's that advancement of science and technology just lifts all boats. >> So what's your take on all this? The EV and software on wheels. I mean, Tesla obviously has a huge lead. It's kind of like the Amazon of vehicles, right? It's sort of inspired a whole new wave of innovation. Now you've got every automobile manufacturer kind of go and after. That is the future of vehicles is something you followed or something you have an opinion on Stu? >> Absolutely. It's driving innovation in some ways, the way the DOS drove innovation on the desktop, if you remember the 64K DOS limit, for years, that was... The software developers came up with some amazing ways to work within that 64K limit. Then when it was gone, we got bloatware, but it actually does enforce a level of discipline on you to try to figure out how to make software run better, run more efficiently. And that has upstream impacts on the enterprise products. >> Well, right. So following your analogy, you talk about the enablement to the desktop, Linux was a huge influence on allowing the individual person to write code and write software, and what's happening in the EV, it's software platform. All of these innovations that we're seeing across industries, it's how is software transforming things. We go back to the mark end reasons, software's eating the world, open source is the way that software is developed. Who's at the intersection of all those? We think we have a nice part to play in that. I loved tha- Dave, I don't know if you caught at the end of the keynote, Matt Hicks basically said, "Our mission isn't just to write enterprise software. "Our mission is based off of open source because open source unlocks innovation for the world." And that's one of the things that drew me to Red Hat, it's not just tech in good places, but allowing underrepresented, different countries to participate in what's happening with software. And we can all move that ball forward. >> Well, can we declare victory for open source because it's not just open source products, but everything that's developed today, whether proprietary or open has open source in it. >> Paul, I agree. Open source is the development model period, today. Are there some places that there's proprietary? Absolutely. But I had a discussion with Deepak Singh who's been on theCUBE many times. He said like, our default is, we start with open source code. I mean, even Amazon when you start talking about that. >> I said this, the $70 billion business on open source. >> Exactly. >> Necessarily give it back, but that say, Hey, this is... All's fair in tech and more. >> It is interesting how the managed service model has sort of rescued open source, open source companies, that were trying to do the Red Hat model. No one's ever really successfully duplicated the Red Hat model. A lot of companies were floundering and failing. And then the managed service option came along. And so now they're all cloud service providers. >> So the only thing I'd say is that there are some other peers we have in the industry that are built off open source they're doing okay. The recent example, GitLab and Hashicorp, both went public. Hashi is doing some managed services, but it's not the majority of their product. Look at a company like Mongo, they've heavily pivoted toward the managed service. It is where we see the largest growth in our area. The products that we have again with Amazon, with Microsoft, huge growth, lots of interest. It's one of the things I spend most of my time talking on. >> I think Databricks is another interesting example 'cause Cloudera was the now company and they had the sort of open core, and then they had the proprietary piece, and they've obviously didn't work. Databricks when they developed Spark out of Berkeley, everybody thought they were going to do kind of a similar model. Instead, they went for all in managed services. And it's really worked well, I think they were ahead of that curve and you're seeing it now is it's what customers want. >> Well, I mean, Dave, you cover the database market pretty heavily. How many different open source database options are there today? And that's one of the things we're solving. When you look at what is Red Hat doing in the cloud? Okay, I've got lots of databases. Well, we have something called, it's Red Hat Open Database Access, which is from a developer, I don't want to have to think about, I've got six different databases, which one, where's the repository? How does all that happen? We give that consistency, it's tied into OpenShift, so it can help abstract some of those pieces. we've got same Kafka streaming and we've got APIs. So it's frameworks and enablers to help bridge that gap between the complexity that's out there, in the cloud and for the developer tool chain. >> That's really important role you guys play though because you had this proliferation, you mentioned Mongo. So many others, Presto and Starbursts, et cetera, so many other open source options out there now. And companies, developers want to work with multiple databases within the same application. And you have a role in making that easy. >> Yeah, so and that is, if you talk about the question I get all the time is, what's next for Kubernetes? Dave, you and I did a preview for KubeCon and it's automation and simplicity that we need to be. It's not enough to just say, "Hey, we've got APIs." It's like Dave, we used to say, "We've got standards? Great." Everybody's implementation was a little bit different. So we have API Sprawl today. So it's building that ecosystem. You've been talking to a number of our partners. We are very active in the community and trying to do things that can lift up the community, help the developers, help that cloud native ecosystem, help our customers move faster. >> Yeah API's better than scripts, but they got to be managed, right? So, and that's really what you guys are doing that's different. You're not trying to own everything, right? It's sort of antithetical to how billions and trillions are made in the IT industry. >> I remember a few years ago we talked here, and you look at the size that Red Hat is. And the question is, could Red Hat have monetized more if the model was a little different? It's like, well maybe, but that's not the why. I love that they actually had Simon Sinek come in and work with Red Hat and that open, unlocks the world. Like that's the core, it's the why. When I join, they're like, here's a book of Red Hat, you can get it online and that why of what we do, so we never have to think of how do we get there. We did an acquisition in the security space a year ago, StackRox, took us a year, it's open source. Stackrox.io, it's community driven, open source project there because we could have said, "Oh, well, yeah, it's kind of open source and there's pieces that are open source, but we want it to be fully open source." You just talked to Gunnar about how he's RHEL nine, based off CentOS stream, and now developing out in the open with that model, so. >> Well, you were always a big fan of Whitehurst culture book, right? It makes a difference. >> The open organization and right, Red Hat? That culture is special. It's definitely interesting. So first of all, most companies are built with the hierarchy in mind. Had a friend of mine that when he joined Red Hat, he's like, I don't understand, it's almost like you have like lots of individual contractors, all doing their things 'cause Red Hat works on thousands of projects. But I remember talking to Rackspace years ago when OpenStack was a thing and they're like, "How do you figure out what to work on?" "Oh, well we hired great people and they work on what's important to them." And I'm like, "That doesn't sound like a business." And he is like, "Well, we struggle sometimes to that balance." Red Hat has found that balance because we work on a lot of different projects and there are people inside Red Hat that are, you know, they care more about the project than they do the business, but there's the overall view as to where we participate and where we productize because we're not creating IP because it's all an open source. So it's the monetizations, the relationships we have our customers, the ecosystems that we build. And so that is special. And I'll tell you that my line has been Red Hat on the inside is even more Red Hat. The debates and the discussions are brutal. I mean, technical people tearing things apart, questioning things and you can't be thin skinned. And the other thing is, what's great is new people. I've talked to so many people that started at Red Hat as interns and will stay for seven, eight years. And they come there and they have as much of a seat at the table, and when I talk to new people, your job, is if you don't understand something or you think we might be able to do it differently, you better speak up because we want your opinion and we'll take that, everybody takes that into consideration. It's not like, does the decision go all the way up to this executive? And it's like, no, it's done more at the team. >> The cultural contrast between that and your parent, IBM, couldn't be more dramatic. And we talked earlier with Paul Cormier about has IBM really walked the walk when it comes to leaving Red Hat alone. Naturally he said, "Yes." Well what's your perspective. >> Yeah, are there some big blue people across the street or something I heard that did this event, but look, do we interact with IBM? Of course. One of the reasons that IBM and IBM Services, both products and services should be able to help get us breadth in the marketplace. There are times that we go arm and arm into customer meetings and there are times that customers tell us, "I like Red Hat, I don't like IBM." And there's other ones that have been like, "Well, I'm a long time IBM, I'm not sure about Red Hat." And we have to be able to meet all of those customers where they are. But from my standpoint, I've got a Red Hat badge, I've got a Red Hat email, I've got Red Hat benefits. So we are fiercely independent. And you know, Paul, we've done blogs and there's lots of articles been written is, Red Hat will stay Red Hat. I didn't happen to catch Arvin I know was on CNBC today and talking at their event, but I'm sure Red Hat got mentioned, but... >> Well, he talks about Red Hat all time. >> But in his call he's talking backwards. >> It's interesting that he's not here, greeting this audience, right? It's again, almost by design, right? >> But maybe that's supposed to be... >> Hundreds of yards away. >> And one of the questions being in the cloud group is I'm not out pitching IBM Cloud, you know? If a customer comes to me and asks about, we have a deep partnership and IBM will be happy to tell you about our integrations, as opposed to, I'm happy to go into a deep discussion of what we're doing with Google, Amazon, and Microsoft. So that's how we do it. It's very different Dave, from you and I watch really closely the VMware-EMC, VMware-Dell, and how that relationship. This one is different. We are owned by IBM, but we mostly, it does IBM fund initiatives and have certain strategic things that are done, absolutely. But we maintain Red Hat. >> But there are similarities. I mean, VMware crowd didn't want to talk about EMC, but they had to, they were kind of forced to. Whereas, you're not being forced to. >> And then once Dell came in there, it was joint product development. >> I always thought a spin in. Would've been the more effective, of course, Michael Dell and Egon wouldn't have gotten their $40 billion out. But I think a spin in was more natural based on where they were going. And it would've been, I think, a more dominant position in the marketplace. They would've had more software, but again, financially it wouldn't have made as much sense, but that whole dynamic is different. I mean, but people said they were going to look at VMware as a model and it's been largely different because remember, VMware of course was a separate company, now is a fully separate company. Red Hat was integrated, we thought, okay, are they going to get blue washed? We're watching and watching, and watching, you had said, well, if the Red Hat culture isn't permeating IBM, then it's a failure. And I don't know if that's happening, but it's definitely... >> I think a long time for that. >> It's definitely been preserved. >> I mean, Dave, I know I read one article at the beginning of the year is, can Arvin make IBM, Microsoft Junior? Follow the same turnaround that Satya Nadella drove over there. IBM I think making some progress, I mean, I read and watch what you and the team are all writing about it. And I'll withhold judgment on IBM. Obviously, there's certain financial things that we'd love to see IBM succeed. We worry about our business. We do our thing and IBM shares our results and they've been solid, so. >> Microsoft had such massive cash flow that even bomber couldn't screw it up. Well, I mean, this is true, right? I mean, you think about how were relevant Microsoft was in the conversation during his tenure and yet they never got really... They maintained a position so that when the Nadella came in, they were able to reascend and now are becoming that dominant player. I mean, IBM just doesn't have that cash flow and that luxury, but I mean, if he pulls it off, he'll be the CEO of the decade. >> You mentioned partners earlier, big concern when the acquisition was first announced, was that the Dells and the HP's and the such wouldn't want to work with Red Hat anymore, you've sort of been here through that transition. Is that an issue? >> Not that I've seen, no. I mean, the hardware suppliers, the ISVs, the GSIs are all very important. It was great to see, I think you had Accenture on theCUBE today, obviously very important partner as we go to the cloud. IBM's another important partner, not only for IBM Cloud, but IBM Services, deep partnership with Azure and AWS. So those partners and from a technology standpoint, the cloud native ecosystem, we talked about, it's not just a Red Hat product. I constantly have to talk about, look, we have a lot of pieces, but your developers are going to have other tools that they're going to use and the security space. There is no such thing as a silver bullet. So I've been having some great conversations here already this week with some of our partners that are helping us to round out that whole solution, help our customers because it has to be, it's an ecosystem. And we're one of the drivers to help that move forward. >> Well, I mean, we were at Dell Tech World last week, and there's a lot of talk about DevSecOps and DevOps and Dell being more developer friendly. Obviously they got a long way to go, but you can't have that take that posture and not have a relationship with Red Hat. If all you got is Pivotal and VMware, and Tansu >> I was thrilled to hear the OpenShift mention in the keynote when they talked about what they were doing. >> How could you not, how could you have any credibility if you're just like, Oh, Pivotal, Pivotal, Pivotal, Tansu, Tansu. Tansu is doing its thing. And they smart strategy. >> VMware is also a partner of ours, but that we would hope that with VMware being independent, that does open the door for us to do more with them. >> Yeah, because you guys have had a weird relationship with them, under ownership of EMC and then Dell, right? And then the whole IBM thing. But it's just a different world now. Ecosystems are forming and reforming, and Dell's building out its own cloud and it's got to have... Look at Amazon, I wrote about this. I said, "Can you envision the day where Dell actually offers competitive products in its suite, in its service offering?" I mean, it's hard to see, they're not there yet. They're not even close. And they have this high say/do ratio, or really it's a low say/do, they say high say/do, but look at what they did with Nutanix. You look over- (chuckles) would tell if it's the Cisco relationship. So it's got to get better at that. And it will, I really do believe. That's new thinking and same thing with HPE. And, I don't know about Lenovo that not as much of an ecosystem play, but certainly Dell and HPE. >> Absolutely. Michael Dell would always love to poke at HPE and HP really went very far down the path of their own products. They went away from their services organization that used to be more like IBM, that would offer lots of different offerings and very much, it was HP Invent. Well, if we didn't invent it, you're not getting it from us. So Dell, we'll see, as you said, the ecosystems are definitely forming, converging and going in lots of different directions. >> But your position is, Hey, we're here, we're here to help. >> Yeah, we're here. We have customers, one of the best proof points I have is the solution that we have with Amazon. Amazon doesn't do the engineering work to make us a native offering if they didn't have the customer demand because Amazon's driven off of data. So they came to us, they worked with us. It's a lot of work to be able to make that happen, but you want to make it frictionless for customers so that they can adopt that. That's a long path. >> All right, so evening event, there's a customer event this evening upstairs in the lobby. Microsoft is having a little shin dig, and then serves a lot of customer dinners going on. So Stu, we'll see you out there tonight. >> All right, thanks you. >> Were watching a brewing somewhere. >> Keynotes tomorrow, a lot of good sessions and enablement, and yeah, it's great to be in person to be able to bump some people, meet some people and, Hey, I'm still a year and a half in still meeting a lot of my peers in person for the first time. >> Yeah, and that's kind of weird, isn't it? Imagine. And then we kick off tomorrow at 10:00 AM. Actually, Stephanie Chiras is coming on. There she is in the background. She's always a great guest and maybe do a little kickoff and have some fun tomorrow. So this is Dave Vellante for Stu Miniman, Paul Gillin, who's my co-host. You're watching theCUBEs coverage of Red Hat Summit 2022. We'll see you tomorrow. (bright music)

>>Welcome everyone to the cubes presentation of the AWS startup showcase open cloud innovations. This is season two episode one of the ongoing series and we're covering exciting and innovative startups from the AWS ecosystem. Today. We're going to focus on the open source community. I'm your host, Dave Vellante. And right now we're going to talk about open source security and mitigating risk in light of a recent discovery of a zero day flaw in log for J a Java logging utility and a related white house executive order that points to the FTC pursuing companies that don't properly secure consumer data as a result of this vulnerability and with me to discuss this critical issue and how to more broadly address software supply chain risk is Don Fisher. Who's the CEO of tide lift. Thank you for coming on the program, Donald. >>Thanks for having me excited to be here. Yeah, pleasure. >>So look, there's a lot of buzz. You open the news, you go to your favorite news site and you see this, you know, a log for J this is an, a project otherwise known as logged for shell. It's this logging tool. My understanding is it's, it's both ubiquitous and very easy to exploit. Maybe you could explain that in a little bit more detail. And how do you think this vulnerability is going to affect things this year? >>Yeah, happy to, happy to dig in a little bit in orient around this. So, you know, just a little definitions to start with. So log for J is a very widely used course component that's been around for quite a while. It's actually an amazing piece of technology log for J is used in practically every serious enterprise Java application over the last 10 going on 20 years. So it's, you know, log for J itself is fantastic. The challenge that organization organizations have been facing relate to a specific security vulnerability that was discovered in log for J and that has been given this sort of brand's name as it happens these days. Folks may remember Heartbleed around the openness to sell vulnerability some years back. This one has been dubbed logged for shell. And the reason why it was given that name is that this is a form of security vulnerability that actually allows attackers. >>You know, if a system is found that hasn't been patched to remediate it, it allows hackers to get full control of a, of a system of a server that has the software running on it, or includes this log for J component. And that means that they can do anything. They can access, you know, private customer data on that system, or really do anything and so-called shell level access. So, you know, that's the sort of definitions of what it is, but the reason why it's important is in the, in the small, you know, this is a open door, right? It's a, if, if organizations haven't patched this, they need to respond to it. But one of the things that's kind of, you know, I think important to recognize here is that this log for J is just one of literally thousands of independently created open source components that flow into the applications that almost every organization built and all of them all software is going to have security vulnerabilities. And so I think that log for J is, has been a catalyst for organizations to say, okay, we've got to solve this specific problem, but we all also have to think ahead about how is this all gonna work. If our software supply chain originates with independent creators across thousands of projects across the internet, how are we going to put a better plan in place to think ahead to the next log for J log for shell style incident? And for sure there will be more >>Okay. So you see this incident as a catalyst to maybe more broadly thinking about how to secure the, the digital supply chain. >>Absolutely. Yeah, it's a, this is proving a point that, you know, a variety of folks have been making for a number of years. Hey, we depend, I mean, honestly these days more than 70% of most applications, most custom applications are comprised of this third party open source code. Project's very similar in origin and governance to log for J that's just reality. It's actually great. That's an amazing thing that the humans collaborating on the internet have caused to be possible that we have this rich comments of open source software to build with, but we also have to be practical about it and say, Hey, how are we going to work together to make sure that that software as much as possible is vetted to ensure that it meets commercial standards, enterprise standards ahead of time. And then when the inevitable issues arise like this incident around the log for J library, that we have a great plan in place to respond to it and to, you know, close the close the door on vulnerabilities when they, when they show up. >>I mean, you know, when you listen to the high level narrative, it's easy to point fingers at organizations, Hey, you're not doing enough now. Of course the U S government has definitely made attempts to emphasize this and, and shore up in, in, in, in, in push people to shore up the software supply chain, they've released an executive order last may, but, but specifically, I mean, it's just a complicated situation. So what steps should organizations really take to make sure that they don't fall prey to these future supply chain attacks, which, you know, are, as you pointed out are inevitable. >>Yeah. I mean, it's, it's a great point that you make that the us federal government has taken proactive steps starting last year, 2021 in the fallout of the solar winds breach, you know, about 12 months ago from the time that we're talking, talking here, the U S government actually was a bit ahead of the game, both in flagging the severity of this, you know, area of concern and also directing organizations on how to respond to it. So the, in May, 2021, the white house issued an executive order on cybersecurity and it S directed federal agencies to undertake a whole bunch of new measures to ensure the security of different aspects of their technology and software supply chain specifically called out open source software as an area where they put, you know, hard requirements around federal agencies when they're acquiring technology. And one of the things that the federal government that the white house cybersecurity executive order directed was that organizations need to start with creating a list of the third-party open source. >>That's flowing into their applications, just that even have a table of contents or an index to start working with. And that's, that's called a, a software bill of materials or S bomb is how some people pronounce that acronym. So th the federal government basically requires federal agencies to now create Nessbaum for their applications to demand a software bill of materials from vendors that are doing business with the government and the strategy there has been to expressly use the purchasing power of the us government to level up industry as a whole, and create the necessary incentives for organizations to, to take this seriously. >>You know, I, I feel like the solar winds hack that you mentioned, of course it was widely affected the government. So we kind of woke them up, but I feel like it was almost like a stuck set Stuxnet moment. Donald were very sophisticated. I mean, for the first time patches that were supposed to be helping us protect, now we have to be careful with them. And you mentioned the, the bill of its software, bill of materials. We have to really inspect that. And so let's get to what you guys do. How do you help organizations deal with this problem and secure their open source software supply chain? >>Yeah, absolutely happy to tell you about, about tide lift and, and how we're looking to help. So, you know, the company, I co-founded the company with a couple of colleagues, all of whom are long-term open source folks. You know, I've been working in around commercializing open source for the last 20 years that companies like red hat and, and a number of others as have my co-founders the opportunity that we saw is that, you know, while there have been vendors for some of the traditional systems level, open source components and stacks like Linux, you know, of course there's red hat and other vendors for Linux, or for Kubernetes, or for some of the databases, you know, there's standalone companies for these logs, for shell style projects, there just hasn't been a vendor for them. And part of it is there's a challenge to cover a really vast territory, a typical enterprise that we inspect has, you know, upwards of 10,000 log for shell log for J like components flowing into their application. >>So how do they get a hand around their hands around that challenge of managing that and ensuring it needs, you know, reasonable commercial standards. That's what tide lifts sets out to do. And we do it through a combination of two elements, both of which are fairly unique in the market. The first of those is a purpose-built software solution that we've created that keeps track of the third-party open source, flowing into your applications, inserts itself into your DevSecOps tool chain, your developer tooling, your application development process. And you can kind of think of it as next to the point in your release process, where you run your unit test to ensure the business logic in the code that your team is writing is accurate and sort of passes tests. We do a inspection to look at the state of the third-party open source packages like Apache log for J that are flowing into your, into your application. >>So there's a software element to it. That's a multi-tenant SAS service. We're excited to be partnered with, with AWS. And one of the reasons why we're here in this venue, talking about how we are making that available jointly with AWS to, to drink customers deploying on AWS platforms. Now, the other piece of the, of our solution is really, really unique. And that's the set of relationships that Tyler has built directly with these independent open source maintainers, the folks behind these open source packages that organizations rely on. And, you know, this is where we sort of have this idea. Somebody is making that software in the first place, right? And so would those folks be interested? Could we create a set of aligned incentives to encourage them, to make sure that that software meets a bunch of enterprise standards and areas around security, like, you know, relating to the log for J vulnerability, but also other complicated parts of open source consumption like licensing and open source license, accuracy, and compatibility, and also maintenance. >>Like if somebody looking after the software going forward. So just trying to basically invite open source creators, to partner with us, to level up their packages through those relationships, we get really, really clean, clear first party data from the folks who create, maintain the software. And we can flow that through the tools that I described so that end organizations can know that they're building with open source components that have been vetted to meet these standards, by the way, there's a really cool side effect of this business model, which is that we pay these open source maintainers to do this work with us. And so now we're creating a new income stream around what previously had been primarily a volunteer activity done for impact in this universe of open source software. We're helping these open source maintainers kind of GoPro on an aspect of what they do around open source. And that means they can spend more time applying more process and tools and methodology to making that open source software even better. And that's good for our customers. And it's good for everyone who relies on open source software, which is really everyone in society these days. That's interesting. I >>Was going to ask you what's their incentive other than doing the right thing. Can you give us an example of, of maybe a example of an open source maintainer that you're working with? >>Yeah. I mean, w we're working with hundreds of open source maintainers and a few of the key open source foundations in different areas across JavaScript, Java PHP, Ruby python.net, and, you know, like examples of categories of projects that we're working with, just to be clear, are things like, you know, web frameworks or parser libraries or logging libraries, like a, you know, log for J and all the other languages, right? Or, you know, time and date manipulation libraries. I mean, they, these are sort of the, you know, kind of core building blocks of applications and individually, they, you know, they may seem like, you know, maybe a minor, a minor thing, but when you multiply them across how many applications these get used in and log for J is a really, really clarifying case for folks to understand this, you know, what can seemingly a small part of your overall application estate can have disproportionate impact on, on your operations? As we saw with many organizations that spent, you know, a weekend or a week, or a large part of the holidays, scrambling to patch and remediate this, a single vulnerability in one of those thousands of packages in that case log. >>Okay, got it. So you have this two, two headed, two vectors that I'm going to call it, your ecosystem, your relationship with these open source maintainers is kind of a, that just didn't happen overnight, and it develop those relationships. And now you get first party data. You monetize that with a software service that is purpose built as the monitor of the probe that actually tracks that third, third party activity. So >>Exactly right. Got it. >>Okay. So a lot of companies, Donald, I mean, this is, like I said before, it's a complicated situation. You know, a lot of people don't have the skillsets to deal with this. And so many companies just kind of stick their head in the sand and, you know, hope for the best, but that's not a great strategy. What are the implications for organizations if they don't really put the tools and processes into place to manage their open source, digital supply chain. >>Yeah. Ignoring the problem is not a viable strategy anymore, you know, and it's just become increasingly clear as these big headline incidents that happened like Heartbleed and solar winds. And now this logged for shell vulnerability. So you can, you can bet on that. Continuing into the future and organizations I think are, are realizing the ones that haven't gotten ahead of this problem are realizing this is a critical issue that they need to address, but they have help, right. You know, the federal government, another action beyond that cybersecurity executive order that was directed at federal agencies early last year, just in the last week or so, the FTC of the U S federal trade commission has made a much more direct warning to private companies and industry saying that, you know, issues like this log for J vulnerability risk exposing private, you know, consumer data. That is one of the express mandates of the FTC is to avoid that the FTC has said that this is, you know, bears on both the federal trade commission act, as well as the Gramm-Leach-Bliley act, which relates to consumer data privacy. >>And the FTC just came right out and said it, they said they cited the $700 million settlements that Equifax was subject to for their data breach that also related to open source component, by the way, that that had not been patched by, by Equifax. And they said the FTC intents to use its full legal authority to pursue companies that failed to take reasonable steps, to protect consumer data from exposure as a result of log for J or similar known vulnerabilities in the future. So the FTC is saying, you know, this is a critical issue for consumer privacy and consumer data. We are going to enforce against companies that do not take reasonable precautions. What are reasonable precautions? I think it's kind of a mosaic of solutions, but I'm glad to say tide lift is contributing a really different and novel solution to the mix that we hope will help organizations contend with this and avoid that kind of enforcement action from FTC or other regulators. >>Well, and the good news is that you can tap a tooling like tide lift in the cloud as a service and you know, much easier today than it was 10 or 15 years ago to, to resolve, or at least begin to demonstrate that you're taking action against this problem. >>Absolutely. There's new challenges. Now I'm moving into a world where we build on a foundation of independently created open source. We need new solutions and new ideas, and that's a, you know, that's part of what we're, we're, we're showing up with from the tide lift angle, but there's many other elements that are going to be necessary to provide the full solution around securing the open source supply chain going forward. >>Well, Donald Fisher of tide lift, thanks so much for coming to the cube and best of luck to your organization. Thanks for the good work that you guys do. >>Thanks, Dave. Really appreciate your partnership on this, getting the word out and yeah, thanks so much for today. >>Very welcome. And you are watching the AWS startup showcase open cloud innovations. Keep it right there for more action on the cube, your leader in enterprise tech coverage.

>>Yeah, yeah. >>Welcome back. I'm so excited to introduce our next session empowerment through inclusion, reimagining society and technology. This is a topic that's personally very near and dear to my heart. Did you know that there's only 2% of Latinas in technology as a Latina? I know that there's so much more we could do collectively to improve these gaps and diversity. I thought spot diversity is considered a critical element across all levels of the organization. The data shows countless times. A diverse and inclusive workforce ultimately drives innovation better performance and keeps your employees happier. That's why we're passionate about contributing to this conversation and also partnering with organizations that share our mission of improving diversity across our communities. Last beyond, we hosted the session during a breakfast and we packed the whole room. This year, we're bringing the conversation to the forefront to emphasize the importance of diversity and data and share the positive ramifications that it has for your organization. Joining us for this session are thought spots Chief Data Strategy Officer Cindy Housing and Ruhollah Benjamin, associate professor of African American Studies at Princeton University. Thank you, Paola. So many >>of you have journeyed with me for years now on our efforts to improve diversity and inclusion in the data and analytic space. And >>I would say >>over time we cautiously started commiserating, eventually sharing best practices to make ourselves and our companies better. And I do consider it a milestone. Last year, as Paola mentioned that half the room was filled with our male allies. But I remember one of our Panelists, Natalie Longhurst from Vodafone, suggesting that we move it from a side hallway conversation, early morning breakfast to the main stage. And I >>think it was >>Bill Zang from a I G in Japan. Who said Yes, please. Everyone else agreed, but more than a main stage topic, I want to ask you to think about inclusion beyond your role beyond your company toe. How Data and analytics can be used to impact inclusion and equity for the society as a whole. Are we using data to reveal patterns or to perpetuate problems leading Tobias at scale? You are the experts, the change agents, the leaders that can prevent this. I am thrilled to introduce you to the leading authority on this topic, Rou Ha Benjamin, associate professor of African studies at Princeton University and author of Multiple Books. The Latest Race After Technology. Rou ha Welcome. >>Thank you. Thank you so much for having me. I'm thrilled to be in conversation with you today, and I thought I would just kick things off with some opening reflections on this really important session theme. And then we could jump into discussion. So I'd like us to as a starting point, um, wrestle with these buzzwords, empowerment and inclusion so that we can have them be more than kind of big platitudes and really have them reflected in our workplace cultures and the things that we design in the technologies that we put out into the world. And so to do that, I think we have to move beyond techno determinism, and I'll explain what that means in just a minute. Techno determinism comes in two forms. The first, on your left is the idea that technology automation, um, all of these emerging trends are going to harm us, are going to necessarily harm humanity. They're going to take all the jobs they're going to remove human agency. This is what we might call the techno dystopian version of the story and this is what Hollywood loves to sell us in the form of movies like The Matrix or Terminator. The other version on your right is the techno utopian story that technologies automation. The robots as a shorthand, are going to save humanity. They're gonna make everything more efficient, more equitable. And in this case, on the surface, he seemed like opposing narratives right there, telling us different stories. At least they have different endpoints. But when you pull back the screen and look a little bit more closely, you see that they share an underlying logic that technology is in the driver's seat and that human beings that social society can just respond to what's happening. But we don't really have a say in what technologies air designed and so to move beyond techno determinism the notion that technology is in the driver's seat. We have to put the human agents and agencies back into the story, the protagonists, and think carefully about what the human desires worldviews, values, assumptions are that animate the production of technology. And so we have to put the humans behind the screen back into view. And so that's a very first step and when we do that, we see, as was already mentioned, that it's a very homogeneous group right now in terms of who gets the power and the resource is to produce the digital and physical infrastructure that everyone else has to live with. And so, as a first step, we need to think about how to create more participation of those who are working behind the scenes to design technology now to dig a little more a deeper into this, I want to offer a kind of low tech example before we get to the more hi tech ones. So what you see in front of you here is a simple park bench public bench. It's located in Berkeley, California, which is where I went to graduate school and on this particular visit I was living in Boston, and so I was back in California. It was February. It was freezing where I was coming from, and so I wanted to take a few minutes in between meetings to just lay out in the sun and soak in some vitamin D, and I quickly realized, actually, I couldn't lay down on this bench because of the way it had been designed with these arm rests at intermittent intervals. And so here I thought. Okay, the the armrest have, ah functional reason why they're there. I mean, you could literally rest your elbows there or, um, you know, it can create a little bit of privacy of someone sitting there that you don't know. When I was nine months pregnant, it could help me get up and down or for the elderly, the same thing. So it has a lot of functional reasons, but I also thought about the fact that it prevents people who are homeless from sleeping on the bench. And this is the Bay area that we were talking about where, in fact, the tech boom has gone hand in hand with a housing crisis. Those things have grown in tandem. So innovation has grown within equity because we haven't thought carefully about how to address the social context in which technology grows and blossoms. And so I thought, Okay, this crisis is growing in this area, and so perhaps this is a deliberate attempt to make sure that people don't sleep on the benches by the way that they're designed and where the where they're implemented and So this is what we might call structural inequity. By the way something is designed. It has certain effects that exclude or harm different people. And so it may not necessarily be the intense, but that's the effect. And I did a little digging, and I found, in fact, it's a global phenomenon, this thing that architects called hostile architecture. Er, I found single occupancy benches in Helsinki, so only one booty at a time no laying down there. I found caged benches in France. And in this particular town. What's interesting here is that the mayor put these benches out in this little shopping plaza, and within 24 hours the people in the town rallied together and had them removed. So we see here that just because we have, uh, discriminatory design in our public space doesn't mean we have to live with it. We can actually work together to ensure that our public space reflects our better values. But I think my favorite example of all is the meter bench. In this case, this bench is designed with spikes in them, and to get the spikes to retreat into the bench, you have to feed the meter you have to put some coins in, and I think it buys you about 15 or 20 minutes. Then the spikes come back up. And so you'll be happy to know that in this case, this was designed by a German artists to get people to think critically about issues of design, not just the design of physical space but the design of all kinds of things, public policies. And so we can think about how our public life in general is metered, that it serves those that can pay the price and others are excluded or harm, whether we're talking about education or health care. And the meter bench also presents something interesting. For those of us who care about technology, it creates a technical fix for a social problem. In fact, it started out his art. But some municipalities in different parts of the world have actually adopted this in their public spaces in their parks in order to deter so called lawyers from using that space. And so, by a technical fix, we mean something that creates a short term effect, right. It gets people who may want to sleep on it out of sight. They're unable to use it, but it doesn't address the underlying problems that create that need to sleep outside in the first place. And so, in addition to techno determinism, we have to think critically about technical fixes that don't address the underlying issues that technology is meant to solve. And so this is part of a broader issue of discriminatory design, and we can apply the bench metaphor to all kinds of things that we work with or that we create. And the question we really have to continuously ask ourselves is, What values are we building in to the physical and digital infrastructures around us? What are the spikes that we may unwittingly put into place? Or perhaps we didn't create the spikes. Perhaps we started a new job or a new position, and someone hands us something. This is the way things have always been done. So we inherit the spike bench. What is our responsibility when we noticed that it's creating these kinds of harms or exclusions or technical fixes that are bypassing the underlying problem? What is our responsibility? All of this came to a head in the context of financial technologies. I don't know how many of you remember these high profile cases of tech insiders and CEOs who applied for Apple, the Apple card and, in one case, a husband and wife applied and the husband, the husband received a much higher limit almost 20 times the limit as his wife, even though they shared bank accounts, they lived in Common Law State. And so the question. There was not only the fact that the husband was receiving a much better interest rate and the limit, but also that there was no mechanism for the individuals involved to dispute what was happening. They didn't even know what the factors were that they were being judged that was creating this form of discrimination. So in terms of financial technologies, it's not simply the outcome that's the issue. Or that could be discriminatory, but the process that black boxes, all of the decision making that makes it so that consumers and the general public have no way to question it. No way to understand how they're being judged adversely, and so it's the process not only the product that we have to care a lot about. And so the case of the apple cart is part of a much broader phenomenon of, um, racist and sexist robots. This is how the headlines framed it a few years ago, and I was so interested in this framing because there was a first wave of stories that seemed to be shocked at the prospect that technology is not neutral. Then there was a second wave of stories that seemed less surprised. Well, of course, technology inherits its creator's biases. And now I think we've entered a phase of attempts to override and address the default settings of so called racist and sexist robots, for better or worse. And here robots is just a kind of shorthand, that the way people are talking about automation and emerging technologies more broadly. And so as I was encountering these headlines, I was thinking about how these air, not problems simply brought on by machine learning or AI. They're not all brand new, and so I wanted to contribute to the conversation, a kind of larger context and a longer history for us to think carefully about the social dimensions of technology. And so I developed a concept called the New Jim Code, which plays on the phrase Jim Crow, which is the way that the regime of white supremacy and inequality in this country was defined in a previous era, and I wanted us to think about how that legacy continues to haunt the present, how we might be coding bias into emerging technologies and the danger being that we imagine those technologies to be objective. And so this gives us a language to be able to name this phenomenon so that we can address it and change it under this larger umbrella of the new Jim Code are four distinct ways that this phenomenon takes shape from the more obvious engineered inequity. Those were the kinds of inequalities tech mediated inequalities that we can generally see coming. They're kind of obvious. But then we go down the line and we see it becomes harder to detect. It's happening in our own backyards. It's happening around us, and we don't really have a view into the black box, and so it becomes more insidious. And so in the remaining couple minutes, I'm just just going to give you a taste of the last three of these, and then a move towards conclusion that we can start chatting. So when it comes to default discrimination. This is the way that social inequalities become embedded in emerging technologies because designers of these technologies aren't thinking carefully about history and sociology. Ah, great example of this came Thio headlines last fall when it was found that widely used healthcare algorithm affecting millions of patients, um, was discriminating against black patients. And so what's especially important to note here is that this algorithm healthcare algorithm does not explicitly take note of race. That is to say, it is race neutral by using cost to predict healthcare needs. This digital triaging system unwittingly reproduces health disparities because, on average, black people have incurred fewer costs for a variety of reasons, including structural inequality. So in my review of this study by Obermeyer and colleagues, I want to draw attention to how indifference to social reality can be even more harmful than malicious intent. It doesn't have to be the intent of the designers to create this effect, and so we have to look carefully at how indifference is operating and how race neutrality can be a deadly force. When we move on to the next iteration of the new Jim code coded exposure, there's attention because on the one hand, you see this image where the darker skin individual is not being detected by the facial recognition system, right on the camera or on the computer. And so coated exposure names this tension between wanting to be seen and included and recognized, whether it's in facial recognition or in recommendation systems or in tailored advertising. But the opposite of that, the tension is with when you're over included. When you're surveiled when you're to centered. And so we should note that it's not simply in being left out, that's the problem. But it's in being included in harmful ways. And so I want us to think carefully about the rhetoric of inclusion and understand that inclusion is not simply an end point. It's a process, and it is possible to include people in harmful processes. And so we want to ensure that the process is not harmful for it to really be effective. The last iteration of the new Jim Code. That means the the most insidious, let's say, is technologies that are touted as helping US address bias, so they're not simply including people, but they're actively working to address bias. And so in this case, There are a lot of different companies that are using AI to hire, create hiring software and hiring algorithms, including this one higher view. And the idea is that there there's a lot that AI can keep track of that human beings might miss. And so so the software can make data driven talent decisions. After all, the problem of employment discrimination is widespread and well documented. So the logic goes, Wouldn't this be even more reason to outsource decisions to AI? Well, let's think about this carefully. And this is the look of the idea of techno benevolence trying to do good without fully reckoning with what? How technology can reproduce inequalities. So some colleagues of mine at Princeton, um, tested a natural learning processing algorithm and was looking to see whether it exhibited the same, um, tendencies that psychologists have documented among humans. E. And what they found was that in fact, the algorithm associating black names with negative words and white names with pleasant sounding words. And so this particular audit builds on a classic study done around 2003, before all of the emerging technologies were on the scene where two University of Chicago economists sent out thousands of resumes to employers in Boston and Chicago, and all they did was change the names on those resumes. All of the other work history education were the same, and then they waited to see who would get called back. And the applicants, the fictional applicants with white sounding names received 50% more callbacks than the black applicants. So if you're presented with that study, you might be tempted to say, Well, let's let technology handle it since humans are so biased. But my colleagues here in computer science found that this natural language processing algorithm actually reproduced those same associations with black and white names. So, too, with gender coded words and names Amazon learned a couple years ago when its own hiring algorithm was found discriminating against women. Nevertheless, it should be clear by now why technical fixes that claim to bypass human biases are so desirable. If Onley there was a way to slay centuries of racist and sexist demons with a social justice box beyond desirable, more like magical, magical for employers, perhaps looking to streamline the grueling work of recruitment but a curse from any jobseekers, as this headline puts it, your next interview could be with a racist spot, bringing us back to that problem space we started with just a few minutes ago. So it's worth noting that job seekers are already developing ways to subvert the system by trading answers to employers test and creating fake applications as informal audits of their own. In terms of a more collective response, there's a federation of European Trade unions call you and I Global that's developed a charter of digital rights for work, others that touches on automated and a I based decisions to be included in bargaining agreements. And so this is one of many efforts to change their ecosystem to change the context in which technology is being deployed to ensure more protections and more rights for everyday people in the US There's the algorithmic accountability bill that's been presented, and it's one effort to create some more protections around this ubiquity of automated decisions, and I think we should all be calling from more public accountability when it comes to the widespread use of automated decisions. Another development that keeps me somewhat hopeful is that tech workers themselves are increasingly speaking out against the most egregious forms of corporate collusion with state sanctioned racism. And to get a taste of that, I encourage you to check out the hashtag Tech won't build it. Among other statements that they have made and walking out and petitioning their companies. Who one group said, as the people who build the technologies that Microsoft profits from, we refuse to be complicit in terms of education, which is my own ground zero. Um, it's a place where we can we can grow a more historically and socially literate approach to tech design. And this is just one, um, resource that you all can download, Um, by developed by some wonderful colleagues at the Data and Society Research Institute in New York and the goal of this interventionist threefold to develop an intellectual understanding of how structural racism operates and algorithms, social media platforms and technologies, not yet developed and emotional intelligence concerning how to resolve racially stressful situations within organizations, and a commitment to take action to reduce harms to communities of color. And so as a final way to think about why these things are so important, I want to offer a couple last provocations. The first is for us to think a new about what actually is deep learning when it comes to computation. I want to suggest that computational depth when it comes to a I systems without historical or social depth, is actually superficial learning. And so we need to have a much more interdisciplinary, integrated approach to knowledge production and to observing and understanding patterns that don't simply rely on one discipline in order to map reality. The last provocation is this. If, as I suggested at the start, inequity is woven into the very fabric of our society, it's built into the design of our. Our policies are physical infrastructures and now even our digital infrastructures. That means that each twist, coil and code is a chance for us toe. We've new patterns, practices and politics. The vastness of the problems that we're up against will be their undoing. Once we accept that we're pattern makers. So what does that look like? It looks like refusing color blindness as an anecdote to tech media discrimination rather than refusing to see difference. Let's take stock of how the training data and the models that we're creating have these built in decisions from the past that have often been discriminatory. It means actually thinking about the underside of inclusion, which can be targeting. And how do we create a more participatory rather than predatory form of inclusion? And ultimately, it also means owning our own power in these systems so that we can change the patterns of the past. If we're if we inherit a spiked bench, that doesn't mean that we need to continue using it. We can work together to design more just and equitable technologies. So with that, I look forward to our conversation. >>Thank you, Ruth. Ha. That was I expected it to be amazing, as I have been devouring your book in the last few weeks. So I knew that would be impactful. I know we will never think about park benches again. How it's art. And you laid down the gauntlet. Oh, my goodness. That tech won't build it. Well, I would say if the thoughts about team has any saying that we absolutely will build it and will continue toe educate ourselves. So you made a few points that it doesn't matter if it was intentional or not. So unintentional has as big an impact. Um, how do we address that does it just start with awareness building or how do we address that? >>Yeah, so it's important. I mean, it's important. I have good intentions. And so, by saying that intentions are not the end, all be all. It doesn't mean that we're throwing intentions out. But it is saying that there's so many things that happened in the world, happened unwittingly without someone sitting down to to make it good or bad. And so this goes on both ends. The analogy that I often use is if I'm parked outside and I see someone, you know breaking into my car, I don't run out there and say Now, do you feel Do you feel in your heart that you're a thief? Do you intend to be a thief? I don't go and grill their identity or their intention. Thio harm me, but I look at the effect of their actions, and so in terms of art, the teams that we work on, I think one of the things that we can do again is to have a range of perspectives around the table that can think ahead like chess, about how things might play out, but also once we've sort of created something and it's, you know, it's entered into, you know, the world. We need to have, ah, regular audits and check ins to see when it's going off track just because we intended to do good and set it out when it goes sideways, we need mechanisms, formal mechanisms that actually are built into the process that can get it back on track or even remove it entirely if we find And we see that with different products, right that get re called. And so we need that to be formalized rather than putting the burden on the people that are using these things toe have to raise the awareness or have to come to us like with the apple card, Right? To say this thing is not fair. Why don't we have that built into the process to begin with? >>Yeah, so a couple things. So my dad used to say the road to hell is paved with good intentions, so that's >>yes on. In fact, in the book, I say the road to hell is paved with technical fixes. So they're me and your dad are on the same page, >>and I I love your point about bringing different perspectives. And I often say this is why diversity is not just about business benefits. It's your best recipe for for identifying the early biases in the data sets in the way we build things. And yet it's such a thorny problem to address bringing new people in from tech. So in the absence of that, what do we do? Is it the outside review boards? Or do you think regulation is the best bet as you mentioned a >>few? Yeah, yeah, we need really need a combination of things. I mean, we need So on the one hand, we need something like a do no harm, um, ethos. So with that we see in medicine so that it becomes part of the fabric and the culture of organizations that that those values, the social values, have equal or more weight than the other kinds of economic imperatives. Right. So we have toe have a reckoning in house, but we can't leave it to people who are designing and have a vested interest in getting things to market to regulate themselves. We also need independent accountability. So we need a combination of this and going back just to your point about just thinking about like, the diversity on teams. One really cautionary example comes to mind from last fall, when Google's New Pixel four phone was about to come out and it had a kind of facial recognition component to it that you could open the phone and they had been following this research that shows that facial recognition systems don't work as well on darker skin individuals, right? And so they wanted Thio get a head start. They wanted to prevent that, right? So they had good intentions. They didn't want their phone toe block out darker skin, you know, users from from using it. And so what they did was they were trying to diversify their training data so that the system would work better and they hired contract workers, and they told these contract workers to engage black people, tell them to use the phone play with, you know, some kind of app, take a selfie so that their faces would populate that the training set, But they didn't. They did not tell the people what their faces were gonna be used for, so they withheld some information. They didn't tell them. It was being used for the spatial recognition system, and the contract workers went to the media and said Something's not right. Why are we being told? Withhold information? And in fact, they told them, going back to the park bench example. To give people who are homeless $5 gift cards to play with the phone and get their images in this. And so this all came to light and Google withdrew this research and this process because it was so in line with a long history of using marginalized, most vulnerable people and populations to make technologies better when those technologies are likely going toe, harm them in terms of surveillance and other things. And so I think I bring this up here to go back to our question of how the composition of teams might help address this. I think often about who is in that room making that decision about sending, creating this process of the contract workers and who the selfies and so on. Perhaps it was a racially homogeneous group where people didn't want really sensitive to how this could be experienced or seen, but maybe it was a diverse, racially diverse group and perhaps the history of harm when it comes to science and technology. Maybe they didn't have that disciplinary knowledge. And so it could also be a function of what people knew in the room, how they could do that chest in their head and think how this is gonna play out. It's not gonna play out very well. And the last thing is that maybe there was disciplinary diversity. Maybe there was racial ethnic diversity, but maybe the workplace culture made it to those people. Didn't feel like they could speak up right so you could have all the diversity in the world. But if you don't create a context in which people who have those insights feel like they can speak up and be respected and heard, then you're basically sitting on a reservoir of resource is and you're not tapping into it to ensure T to do right by your company. And so it's one of those cautionary tales I think that we can all learn from to try to create an environment where we can elicit those insights from our team and our and our coworkers, >>your point about the culture. This is really inclusion very different from just diversity and thought. Eso I like to end on a hopeful note. A prescriptive note. You have some of the most influential data and analytics leaders and experts attending virtually here. So if you imagine the way we use data and housing is a great example, mortgage lending has not been equitable for African Americans in particular. But if you imagine the right way to use data, what is the future hold when we've gotten better at this? More aware >>of this? Thank you for that question on DSO. You know, there's a few things that come to mind for me one. And I think mortgage environment is really the perfect sort of context in which to think through the the both. The problem where the solutions may lie. One of the most powerful ways I see data being used by different organizations and groups is to shine a light on the past and ongoing inequities. And so oftentimes, when people see the bias, let's say when it came to like the the hiring algorithm or the language out, they see the names associated with negative or positive words that tends toe have, ah, bigger impact because they think well, Wow, The technology is reflecting these biases. It really must be true. Never mind that people might have been raising the issues in other ways before. But I think one of the most powerful ways we can use data and technology is as a mirror onto existing forms of inequality That then can motivate us to try to address those things. The caution is that we cannot just address those once we come to grips with the problem, the solution is not simply going to be a technical solution. And so we have to understand both the promise of data and the limits of data. So when it comes to, let's say, a software program, let's say Ah, hiring algorithm that now is trained toe look for diversity as opposed to homogeneity and say I get hired through one of those algorithms in a new workplace. I can get through the door and be hired. But if nothing else about that workplace has changed and on a day to day basis I'm still experiencing microaggressions. I'm still experiencing all kinds of issues. Then that technology just gave me access to ah harmful environment, you see, and so this is the idea that we can't simply expect the technology to solve all of our problems. We have to do the hard work. And so I would encourage everyone listening to both except the promise of these tools, but really crucially, um, Thio, understand that the rial kinds of changes that we need to make are gonna be messy. They're not gonna be quick fixes. If you think about how long it took our society to create the kinds of inequities that that we now it lived with, we should expect to do our part, do the work and pass the baton. We're not going to magically like Fairy does create a wonderful algorithm that's gonna help us bypass these issues. It can expose them. But then it's up to us to actually do the hard work of changing our social relations are changing the culture of not just our workplaces but our schools. Our healthcare systems are neighborhoods so that they reflect our better values. >>Yeah. Ha. So beautifully said I think all of us are willing to do the hard work. And I like your point about using it is a mirror and thought spot. We like to say a fact driven world is a better world. It can give us that transparency. So on behalf of everyone, thank you so much for your passion for your hard work and for talking to us. >>Thank you, Cindy. Thank you so much for inviting me. Hey, I live back to you. >>Thank you, Cindy and rou ha. For this fascinating exploration of our society and technology, we're just about ready to move on to our final session of the day. So make sure to tune in for this customer case study session with executives from Sienna and Accenture on driving digital transformation with certain AI.

>>Thank you. Thank you so much for having me. I'm thrilled to be in conversation with you today. And I thought I would just kick things off with some opening reflections on this really important session theme, and then we can jump into discussion. So I'd like us to, as a starting point, um, wrestle with these buzz words, empowerment and inclusion so that we can, um, have them be more than kind of big platitudes and really have them reflected in our workplace cultures and the things that we design and the technologies that we put out into the world. And so to do that, I think we have to move beyond techno determinism and I'll explain what that means in just a minute. And techno determinism comes in two forms. The first on your left is the idea that technology automate. Um, all of these emerging trends are going to harm us are going to necessarily, um, harm humanity. >>They're going to take all the jobs they're going to remove human agency. This is what we might call the techno dystopian version of the story. And this is what Hollywood loves to sell us in the form of movies like the matrix or Terminator. The other version on your right is the techno utopian story that technologies automation, the robots, as a shorthand are going to save humanity. They're going to make everything more efficient, more equitable. And in this case, on the surface, they seem like opposing narratives, right? They're telling us different stories. At least they have different endpoints, but when you pull back the screen and look a little bit more closely, you see that they share an underlying logic, that technology is in the driver's seat and that human beings, that social society can just respond to what's happening. But we don't, I really have a say in what technologies are designed. >>And so to move beyond techno determinism, the notion that technology is in the driver's seat, we have to put the human agents and agencies back into the story protagonists and think carefully about what the human desires, worldviews values assumptions are that animate the production of technology. We have to put the humans behind the screen back into view. And so that's a very first step in when we do that. We see as was already mentioned that it's a very homogenous group right now in terms of who gets the power and the resources to produce the digital and physical infrastructure that everyone else has to live with. And so, as a first step, we need to think about how to, to create more participation of those who are working behind the scenes to design technology. Now, to dig a little more deeper into this, I want to offer a kind of low tech example before we get to the more high tech ones. >>So what you see in front of you here is a simple park bench public it's located in Berkeley, California, which is where I went to graduate school. And on this one particular visit, I was living in Boston. And so I was back in California, it was February, it was freezing where I was coming from. And so I wanted to take a few minutes in between meetings to just lay out in the sun and soak in some vitamin D. And I quickly realized actually I couldn't lay down on the bench because of the way it had been designed with these arm rests at intermittent intervals. And so here I thought, okay, th th the armrests have a functional reason why they're there. I mean, you could literally rest your elbows there, or, um, you know, it can create a little bit of privacy of someone sitting there that you don't know. >>Um, when I was nine months pregnant, it could help me get up and down or for the elderly the same thing. So it has a lot of functional reasons, but I also thought about the fact that it prevents people who are, are homeless from sleeping on the bench. And this is the Bay area that we're talking about, where in fact, the tech boom has gone hand in hand with a housing crisis. Those things have grown in tandem. So innovation has grown with inequity because we have, I haven't thought carefully about how to address the social context in which technology grows and blossoms. And so I thought, okay, this crisis is growing in this area. And so perhaps this is a deliberate attempt to make sure that people don't sleep on the benches by the way that they're designed and where the, where they're implemented. And so this is what we might call structural inequity, by the way something is designed. >>It has certain yeah. Affects that exclude or harm different people. And so it may not necessarily be the intent, but that's the effect. And I did a little digging and I found, in fact, it's a global phenomenon, this thing that architect next call, hostile architecture around single occupancy, benches and Helsinki. So only one booty at a time, no Nolan down there. I've found caged benches in France. Yeah. And in this particular town, what's interesting here is that the mayor put these benches out in this little shopping Plaza and within 24 hours, the people in the town rally together and have them removed. So we see here that just because we, we have a discriminatory design in our public space, doesn't mean we have to live with it. We can actually work together to ensure that our public space reflects our better values. But I think my favorite example of all is the metered bench. >>And then this case, this bench is designed with spikes in them and to get the spikes to retreat into the bench, you have to feed the meter. You have to put some coins in, and I think it buys you about 15, 20 minutes, then the spikes come back up. And so you will be happy to know that in this case, uh, this was designed by a German artist to get people to think critically about issues of design, not the design of physical space, but the design of all kinds of things, public policies. And so we can think about how our public life in general is metered, that it serves those that can pay the price and others are excluded or harmed. Whether we're talking about education or healthcare. And the meter bench also presents something interesting for those of us who care about technology, it creates a technical fix for a social problem. >>In fact, it started out as art, but some municipalities in different parts of the world have actually adopted this in their public spaces, in their parks in order to deter so-called loiters from using that space. And so by a technical fix, we mean something that creates a short-term effect, right? It gets people who may want to sleep on it out of sight. They're unable to use it, but it doesn't address the underlying problems that create that need to sleep outside of the first place. And so, in addition to techno determinism, we have to think critically about technical fixes, that don't address the underlying issues that the tech tech technology is meant to solve. And so this is part of a broader issue of discriminatory design, and we can apply the bench metaphor to all kinds of things that we work with, or that we create. >>And the question we really have to continuously ask ourselves is what values are we building in to the physical and digital infrastructures around us? What are the spikes that we may unwittingly put into place? Or perhaps we didn't create the spikes. Perhaps we started a new job or a new position, and someone hands us something, this is the way things have always been done. So we inherit the spiked bench. What is our responsibility? When we notice that it's creating these kinds of harms or exclusions or technical fixes that are bypassing the underlying problem, what is our responsibility? All of this came to a head in the context of financial technologies. I don't know how many of you remember these high profile cases of tech insiders and CEOs who applied for apples, >>The Apple card. And in one case, a husband and wife applied, and the husband, the husband received a much higher limit, almost 20 times the limit as his, >>His wife, even though they shared bank accounts, they lived in common law state. Yeah. >>And so the question there was not only the fact that >>The husband was receiving a much better rate and a high and a better >>The interest rate and the limit, but also that there was no mechanism for the individuals involved to dispute what was happening. They didn't even know how, what the factors were that they were being judged that was creating this form of discrimination. So >>In terms of financial technologies, it's not simply the outcome, that's the issue, or that can be discriminatory, >>But the process that black box is all of the decision-making that makes it so that consumers and the general public have no way to question it, no way to understand how they're being judged adversely. And so it's the process, not only the product that we have to care a lot about. And so the case of the Apple card is part of a much broader phenomenon >>Of, um, races >>And sexist robots. This is how the headlines framed it a few years ago. And I was so interested in this framing because there was a first wave of stories that seemed to be shocked at the prospect, that technology is not neutral. Then there was a second wave of stories that seemed less surprised. Well, of course, technology inherits its creators biases. And now I think we've entered a phase of attempts to override and address the default settings of so-called racist and sexist robots for better or worse than here. Robots is just a kind of shorthand that the way that people are talking about automation and emerging technologies more broadly. And so, as I was encountering these headlines, I was thinking about how these are not problems simply brought on by machine learning or AI. They're not all brand new. And so I wanted to contribute to the conversation, a kind of larger context and a longer history for us to think carefully about the social dimensions of technology. And so I developed a concept called the new Jim code, >>Which plays on the phrase, >>Jim Crow, which is the way that the regime of white supremacy and inequality in this country was defined in a previous era. And I wanted us to think about how that legacy continues to haunt the present, how we might be coding bias into emerging technologies and the danger being that we imagine those technologies to be objective. And so this gives us a language to be able to name this phenomenon so that we can address it and change it under this larger umbrella of the new Jim code are four distinct ways that this phenomenon takes shape from the more obvious engineered inequity. Those are the kinds of inequalities tech mediated in the qualities that we can generally see coming. They're kind of obvious, but then we go down the line and we see it becomes harder to detect it's happening in our own backyards, it's happening around us. And we don't really have a view into the black box. And so it becomes more insidious. And so in the remaining couple of minutes, I'm just, just going to give you a taste of the last three of these, and then a move towards conclusion. Then we can start chatting. So when it comes to default discrimination, this is the way that social inequalities >>Become embedded in emerging technologies because designers of these technologies, aren't thinking carefully about history and sociology. A great example of this, uh, came to, um, uh, the headlines last fall when it was found that widely used healthcare algorithm, effecting millions of patients, um, was discriminating against black patients. And so what's especially important to note here is that this algorithm, healthcare algorithm does not explicitly take note of race. That is to say it is race neutral by using cost to predict healthcare needs this digital triaging system unwittingly reproduces health disparities, because on average, black people have incurred fewer costs for a variety of reasons, including structural inequality. So in my review of this study, by Obermeyer and colleagues, I want to draw attention to how indifference to social reality can be even more harmful than malicious intent. It doesn't have to be the intent of the designers to create this effect. >>And so we have to look carefully at how indifference is operating and how race neutrality can be a deadly force. When we move on to the next iteration of the new Jim code, coded exposure, there's a tension because on the one hand, you see this image where the darker skin individual is not being detected by the facial recognition system, right on the camera, on the computer. And so coded exposure names, this tension between wanting to be seen and included and recognized whether it's in facial recognition or in recommendation systems or in tailored advertising. But the opposite of that, the tension is with when you're over, it >>Included when you're surveilled, when you're >>Too centered. And so we should note that it's not simply in being left out, that's the problem, but it's in being included in harmful ways. And so I want us to think carefully about the rhetoric of inclusion and understand that inclusion is not simply an end point, it's a process, and it is possible to include people in harmful processes. And so we want to ensure that the process is not harmful for it to really be effective. The last iteration of the new Jim code. That means the, the most insidious let's say is technologies that are touted as helping us address bias. So they're not simply including people, but they're actively working to address bias. And so in this case, there are a lot of different companies that are using AI to hire, uh, create hiring, um, software and hiring algorithms, including this one higher view. >>And the idea is that there there's a lot that, um, AI can keep track of that human beings might miss. And so, so the software can make data-driven talent decisions after all the problem of employment discrimination is widespread and well-documented, so the logic goes, wouldn't this be even more reason to outsource decisions to AI? Well, let's think about this carefully. And this is the idea of techno benevolence, trying to do good without fully reckoning with what, how technology can reproduce inequalities. So some colleagues of mine at Princeton, um, tested a natural learning processing algorithm and was looking to see whether it exhibited the same, um, tendencies that psychologists have documented among humans. And what they found was that in fact, the algorithm associated black names with negative words and white names with pleasant sounding words. And so this particular audit builds on a classic study done around 2003 before all of the emerging technologies were on the scene where two university of Chicago economists sent out thousands of resumes to employers in Boston and Chicago. >>And all they did was change the names on those resumes. All of the other work history education were the same. And then they waited to see who would get called back and the applicants, the fictional applicants with white sounding names received 50% more callbacks than the, the black applicants. So if you're presented with that study, you might be tempted to say, well, let's let technology handle it since humans are so biased. But my colleagues here in computer science found that this natural language processing algorithm actually reproduced those same associations with black and white names. So two with gender coded words and names as Amazon learned a couple years ago, when its own hiring algorithm was found discriminating against women, nevertheless, it should be clear by now why technical fixes that claim to bypass human biases are so desirable. If only there was a way to slay centuries of racist and sexist demons with a social justice bot beyond desirable, more like magical, magical for employers, perhaps looking to streamline the grueling work of recruitment, but a curse from any job seekers as this headline puts it. >>Your next interview could be with a racist bot, bringing us back to that problem space. We started with just a few minutes ago. So it's worth noting that job seekers are already developing ways to subvert the system by trading answers to employers tests and creating fake applications as informal audits of their own. In terms of a more collective response. There's a Federation of European trade unions call you and I global that's developed a charter of digital rights for workers that touches on automated and AI based decisions to be included in bargaining agreements. And so this is one of many efforts to change the ecosystem, to change the context in which technology is being deployed to ensure more protections and more rights for everyday people in the U S there's the algorithmic accountability bill that's been presented. And it's one effort to create some more protections around this ubiquity of automated decisions. >>And I think we should all be calling for more public accountability when it comes to the widespread use of automated decisions. Another development that keeps me somewhat hopeful is that tech workers themselves are increasingly speaking out against the most egregious forms of corporate collusion with state sanctioned racism. And to get a taste of that, I encourage you to check out the hashtag tech, won't build it among other statements that they've made and walking out and petitioning their companies. One group said as the, at Google at Microsoft wrote as the people who build the technologies that Microsoft profits from, we refuse to be complicit in terms of education, which is my own ground zero. Um, it's a place where we can, we can grow a more historically and socially literate approach to tech design. And this is just one resource that you all can download, um, by developed by some wonderful colleagues at the data and society research Institute in New York. >>And the, the goal of this intervention is threefold to develop an intellectual understanding of how structural racism operates and algorithms, social media platforms and technologies not yet developed and emotional intelligence concerning how to resolve racially stressful situations within organizations and a commitment to take action, to reduce harms to communities of color. And so as a final way to think about why these things are so important, I want to offer, uh, a couple last provocations. The first is pressed to think a new about what actually is deep learning when it comes to computation. I want to suggest that computational depth when it comes to AI systems without historical or social depth is actually superficial learning. And so we need to have a much more interdisciplinary, integrated approach to knowledge production and to observing and understanding patterns that don't simply rely on one discipline in order to map reality. >>The last provocation is this. If as I suggested at the start in the inequity is woven into the very fabric of our society. It's built into the design of our, our policies, our physical infrastructures, and now even our digital infrastructures. That means that each twist coil and code is a chance for us to weave new patterns, practices, and politics. The vastness of the problems that we're up against will be their undoing. Once we, that we are pattern makers. So what does that look like? It looks like refusing colorblindness as an anecdote to tech media discrimination, rather than refusing to see difference. Let's take stock of how the training data and the models that we're creating. Have these built in decisions from the past that have often been discriminatory. It means actually thinking about the underside of inclusion, which can be targeting and how do we create a more participatory rather than predatory form of inclusion. And ultimately it also means owning our own power in these systems so that we can change the patterns of the past. If we're, if we inherit a spiked bench, that doesn't mean that we need to continue using it. We can work together to design more, just an equitable technologies. So with that, I look forward to our conversation.

(upbeat music) >> Announcer: From the CUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE Conversation. >> Hey, welcome back everybody Jeffrey Frick with theCUBE. We are getting through the COVID crisis. It continues and impacting the summer. I can't believe the summer's almost over, but there's a whole lot of things going on in terms of privacy and contact tracing and this kind of this feeling that there's this conflict between kind of personal identification and your personal privacy versus the public good around things like contact tracing. And I was in a session last week with two really fantastic experts. I wanted to bring them on the show and we're really excited to have back for I don't even know how many times Michelle has been on Michelle Dennedy, She is the former chief privacy officer at Cisco and now she's running the CEO of Identity, Michelle great to see you. >> Good to see you always Jeff >> Yeah and for the first time Dr. Ann Cavoukian and she is the executive director Global Privacy & Security By Design Center. Joining us from Toronto, worked with the government and is not short on opinions about privacy. (laughing) Ann good to see you. >> Hi Jeff thank you >> Yes, so let's jump into it cause I think one of the fundamental issues that we keep hearing is this zero-sum game. And I know and it's a big topic for you that there seems to be this trade off this either or and specifically let's just go to contact tracing. Cause that's a hot topic right now with COVID. I hear that it's like you're telling everybody where I'm going and you're sharing that with all these other people. How is this even a conversation and where do I get to choose whether I want to participate or not? >> You can't have people traced and tracked and surveil. You simply can't have it and it can't be an either or win lose model. You have to get rid of that data. Zero-sum game where only one person can win and the other one loses and it sums to a total of zero. Get rid of that, that's so yesterday. You have to have both groups winning positive sum. Meaning yes, you need public health and public safety and you need privacy. It's not one versus the other. We can do both and that's what we insist upon. So the contact term tracing app that was developed in Canada was based on the Apple Google framework, which is actually called exposure notification. It's totally privacy protective individuals choose to voluntarily download this app. And no personal information is collected whatsoever. No names, no geolocation data, nothing. It's simply notifies you. If you've been exposed to someone who is COVID-19 positive, and then you can decide on what action you wish to take. Do you want to go get tested? Do you want to go to your family doctor, whatever the decision lies with you, you have total control and that's what privacy is all about. >> Jeffrey: But what about the person who was sick? Who's feeding the top into that process and is the sick person that you're no notifying they obviously their personal information is part of that transaction. >> what the COVID alerts that we developed based on the Apple Google framework. It builds on manual contact tracing, which also take place the two to compliment each other. So the manual contact tracing is when individuals go get to get tested and they're tested as positive. So healthcare nurses will speak to that individual and say, please tell us who you've been in contact with recently, family, friends, et cetera. So the two work together and by working together, we will combat this in a much more effective manner. >> Jeffrey: So shifting over to you Michelle, you know, there's PIN and a lot of conversations all the time about personal identifiable information but right. But then medical has this whole nother class of kind of privacy restrictions and level of care. And I find it really interesting that on one hand, you know, we were trying to do the contract tracing on another hand if you know, my wife works in a public school. If they find out that one of the kids in this class has been exposed to COVID somehow they can't necessarily tell the teacher because of HIPAA restriction. So I wonder if you could share your thoughts on this kind of crossover between privacy and health information when it gets into this kind of public crisis and this inherent conflict for the public right to know and should the teacher be able to be told and it's not a really clean line with a simple answer, I don't think. >> No and Jeff, and you're also layering, you know, when you're talking about student data, you layering another layer of legal restriction. And I think what you're putting your thumb on is something that's really critical. When you talk about privacy engineering, privacy by design and ethics engineering. You can't simply start with the legal premise. So is it lawful to share HIPAA covered data. A child telling mommy I don't feel well not HIPAA covered. A child seeing a doctor for medical services and finding some sort of infection or illness covered, right? So figuring out the origin of the exact same zero one. Am I ill or not, all depends on context. So you have to first figure out, first of all let's tackle the moral issues. Have we decided that it is a moral imperative to expose certain types of data. And I separate that from ethics intentionally and with apologies to true ethicists. The moral imperative is sort of the things we find are so wrong. We don't want a list of kids who are sick or conversely once the tipping point goes the list of kids who are well. So then they are called out that's the moral choice. The ethical choice is just because you can should you, and that's a much longer conversation. Then you get to the legal imperative. Are you allowed to based on the past mistakes that we made. That's what every piece of litigation or legislation is particularly in a common law construct in the US. It's very important to understand that civil law countries like the European theater. They try to prospectively legislate for things that might go wrong. The construct is thinner in a common law economy where you do, you use test cases in the courts of law. That's why we are such a litigious society has its own baggage. But you have to now look at is that legal structure attempting to cover past harms that are so bad that we've decided as a society to punish them, is this a preventative law? And then you finally get to what I say is stage four for every evaluation is isn't viable, are the protections that you have to put on top of these restrictions. So dire that they either cannot be maintained because of culture process or cash or it just doesn't make sense anymore. So does it, is it better to just feel someone's forehead for illness rather than giving a blood assay, having it sent away for three weeks and then maybe blah, blah, blah, blah, blah, blah. >> Right. >> You have to look at this as a system problem solving issue. >> So I want to look at it in the context of, again kind of this increased level of politicization and or, you know, kind of exposure outside of what's pretty closed. And I want to bring up AIDS and the porn industry very frankly right? Where people behaving in the behavior of the business risk a life threatening disease of which I still don't think it as a virus. So you know why, cause suddenly, you know, we can track for that and that's okay to track for that. And there's a legitimate reason to versus all of the other potential medical conditions that I may or may not have that are not necessarily brought to bear within coming to work. And we might be seeing this very soon. As you said, if people are wanting our temperatures, as we come in the door to check for symptoms. How does that play with privacy and healthcare? It's still fascinates me that certain things is kind of pop out into their own little bucket of regulation. I'm wondering if you could share your thoughts on that Ann. >> You know, whenever you make it privacy versus fill in the blank, especially in the context of healthcare. You end up turning it to a lose lose as opposed to even a win lose. Because you will have fewer people wanting to allow themselves to be tested, to be brought forward for fear of where that information may land. If it lands in the hands of your employer for example or your whoever owns your house if you're in renting, et cetera. It creates enormous problems. So regardless of what you may think of the benefits of that model. History has shown that it doesn't work well that people end up shying away from being tested or seeking treatment or any of those things. Even now with the contact tracing apps that have been developed. If you look globally the contact tracing apps for COVID-19. They have failed the ones that identify individuals in the UK, in Australia, in Western Canada that's how it started out. And they've completely dropped them because they don't work. People shy away from them. They don't use them. So they've gotten rid of that. They've replaced it with the, an app based on the Apple Google framework, which is the one that protects privacy and will encourage people to come forward and seek to be tested. If there's a problem in Germany. Germany is one of the largest privacy data protection countries in the world. Their privacy people are highly trusted in Germany. Germany based their app on the Apple Google framework. About a month ago they released it. And within 24 hours they had 6.5 million people download the app. >> Right. >> Because there is such trust there unlike the rest of the world where there's very little trust and we have to be very careful of the trust deficit. Because we want to encourage people to seek out these apps so they can attempt to be tested if there's a problem, but they're not going to use them. They're just going to shy away from them. If there is such a problem. And in fact I'll never forget. I did an interview about a month ago, three weeks ago in the US on a major major radio station that has like 54 million people followers. And I was telling them about the COVID alert the Canadian contact tracing app, actually it's called exposure notification app, which was built on the Apple Google framework. And people in hoard said they wouldn't trust anyone with it in the US. They just wouldn't trust it. So you see there's such a trust deficit. That's what we have to be careful to avoid. >> So I want to hold on the trust for just a second, but I want to go back to you Michelle and talk about the lessons that we can learn post 9/11. So the other thing right and keep going back to this over and over. It's not a zero-sum game. It's not a zero-sum game and yet that's the way it's often positioned as a way to break down existing barriers. So if you go back to 9/11 probably the highest profile thing being the Patriot Act, you know, where laws are put in place to protect us from terrorism that are going to do things that were not normally allowed to be done. I bet without checking real exhaustively that most of those things are still in place. You know, cause a lot of times laws are written. They don't go away for a long time. What can we learn from what happened after 9/11 and the Patriot Act and what should be really scared of, or careful of or wary of using that as a framework for what's happening now around COVID and privacy. >> It's a perfect, it's not even an analogy because we're feeling the shadows of the Patriot Act. Even now today, we had an agreement from the United States with the European community until recently called the Privacy Shield. And it was basically if companies and organizations that were, that fell under the Federal Trade Commissions jurisdiction, there's a bit of layering legal process here. But if they did and they agreed to supply enough protection to data about people who were present in the European Union to the same or better level than the Europeans would. Then that information could pass through this Privacy Shield unencumbered to and from the United States. That was challenged and taken down. I don't know if it's a month ago or if it's still March it's COVID time, but very recently on basis that the US government can overly and some would say indifferent nations, improperly look at European data based on some of these Patriot Act, FISA courts and other intrusive mechanisms that absolutely do apply if we were under the jurisdiction of the United States. So now companies and private actors are in the position of having to somehow prove that they will mechanize their systems and their processes to be immune from their own government intrusion before they can do digital trade with other parts of the world. We haven't yet seen the commercial disruption that will take place. So the unintended consequence of saying rather than owning the answers or the observations and the intelligence that we got out of the actual 9/11 report, which said we had the information we needed. We did not share enough between the agencies and we didn't have the decision making activity and will to take action in that particular instance. Rather than sticking to that knowledge. Instead we stuck to the Patriot Act, which was all but I believe to Congress people. When I mean, you see the hot mess. That is the US right now. When everyone but two people in the room vote for something on the quick. There's probably some sort of a psychological gun to your head. That's probably well thought out thing. We fight each other. That's part of being an American dammit. So I think having these laws that say, you've got to have this one solution because the boogeyman is coming or COVID is coming or terrorists or child pornographers are coming. There's not one solution. So you really have to break this down into an engineering problem and I don't mean technology when I say engineering. I mean looking at the culture, how much trust do you have? Who is the trusted entity? Do we trust Microsoft more than we trust the US government right now? Maybe that might be your contact. How you're going to build people, process and technology not to avoid a bad thing, but to achieve a positive objective because if you're not achieving that positive objective of understanding that safe to move about without masks on, for example, stop, just stop. >> Right, right. My favorite analogy Jeff, and I think I've said this to you in the past is we don't sit around and debate the merits of viscosity of water to protect concrete holes. We have to make sure that when you lead them to the concrete hole, there's enough water in the hole. No, you're building a swimming pool. What kind of a swimming pool do you want? Is it commercial, Is it toddlers? Is it (indistinct), then you build in correlation, protection and da da da da. But if you start looking at every problem as how to avoid hitting a concrete hole. You're really going to miss the opportunity to build and solve the problem that you want and avoid the risk that you do not want. >> Right right, and I want to go back to you on the trust thing. You got an interesting competent in that other show, talking about working for the government and not working directly for the people are voted in power, but for the kind of the larger bureaucracy and agency. I mean, the Edelman Trust Barometer is really interesting. They come out every year. I think it's their 20th year. And they break down kind of like media, government and business. And who do you trust and who do you not trust? What what's so fascinating about the time we're in today is even within the government, the direction that's coming out is completely diametrically opposed oftentimes between the Fed, the state and the local. So what does kind of this breakdown of trust when you're getting two different opinions from the same basic kind of authority due to people's ability or desire to want to participate and actually share the stuff that maybe or maybe not might get reshared. >> It leaves you with no confidence. Basically, you can't take confidence in any of this. And when I was privacy commissioner. I served for three terms, each term that was a different government, different political power in place. And before they had become the government, they were all for privacy and data protection believed in and all that. And then once they became the government all that changed and all of a sudden they wanted to control everyone's information and they wanted to be in power. No, I don't trust government. You know, people often point to the private sector as being the group you should distrust in terms of privacy. I say no, not at all. To me far worse is actually the government because everyone thinks they're there to do good job and trust them. You can't trust. You have to always look under the hood. I always say trust but verify. So unfortunately we have to be vigilant in terms of the protections we seek for privacy both with private sector and with the government, especially with the government and different levels of government. We need to ensure that people's privacy remains intact. It's preserved now and well into the future. You can't give up on it because there's some emergency a pandemic, a terrorist incident whatever of course we have to address those issues. But you have to insist upon people's privacy being preserved. Privacy forms the foundation of our freedom. You cannot have free and open societies without a solid foundation of privacy. So I'm just encouraging everyone. Don't take anything at face value, just because the government tells you something. It doesn't mean it's so always look under the hood and let us ensure the privacy is strongly protected. See emergencies come and go. The pandemic will end. What cannot end is our privacy and our freedom. >> So this is a little dark in here, but we're going to lighten it up a little bit because there's, as Michelle said, you know, if you think about building a pool versus putting up filling a hole, you know, you can take proactive steps. And there's a lot of conversation about proactive steps and I pulled Ann your thing Privacy by Design, The 7 Foundational Principles. I have the guys pull up a slide. But I think what's really interesting here is, is you're very, very specific prescriptive, proactive, right? Proactive, not reactive. Privacy is the default setting. You know, don't have to read the ULAs and I'm not going to read the, all the words we'll share it. People can find it. But what I wanted to focus on is there is an opportunity to get ahead of the curve, but you just have to be a little bit more thoughtful. >> That's right, and Privacy By Design it's a model of prevention, much like a medical model of prevention where you try to prevent the harms from arising, not just deal with them after the facts through regulatory compliance. Of course we have privacy laws and that's very important, but they usually kick in after there's been a data breach or privacy infraction. So when I was privacy commissioner obviously those laws were intact and we had to follow them, but I wanted something better. I wanted to prevent the privacy harms from arising, just like a medical model of prevention. So that's a Privacy By Design is intended to do is instantiate, embed much needed privacy protective measures into your policies, into your procedures bake it into the code so that it has a constant presence and can prevent the harms from arising. >> Jeffrey: Right right. One of the things I know you love to talk about Michelle is compliance, right? And is compliance enough. I know you like to talk about the law. And I think one of the topics that came up on your guys' prior conversation is, you know, will there be a national law, right? GDPR went through on the European side last year, the California Protection Act. A lot of people think that might become the model for more of a national type of rule. But I tell you, when you watch some of the hearings in DC, you know, I'm sure 90% of these people still print their emails and have their staff hand them to them. I mean, it's really scary that said, you know, regulation always does kind of lag probably when it needs to be put in place because people maybe abuse or go places they shouldn't go. So I wonder if you could share your thoughts on where you think legislation is going to going and how should people kind of see that kind of playing out over the next several years, I guess. >> Yeah, it's such a good question Jeff. And it's like, you know, I think even the guys in Vegas are having trouble with setting the high laws on this. Cameron said in I think it was December of 2019, which was like 15 years ago now that in the first quarter of 2020, we would see a federal law. And I participated in a hearing at the Senate banking committee, again, November, October and in the before times. I'm talking about the same thing and here we are. Will we have a comprehensive, reasonable, privacy law in the United States before the end of this president's term. No, we will not. I can say that with just such faith and fidelity. (laughing) But what does that mean? And I think Katie Porter who I'm starting to just love, she's the Congresswoman who's famous for pulling on her white board and just saying, stop fudging the numbers. Let's talk about the numbers. There's about a, what she calls the 20% legislative flip phone a caucus. So there are 20% or more on both sides of the aisle of people in the US who are in the position of writing our laws. who are still on flip phones and aren't using smart phones and other kinds of technologies. There's a generation gap. And as much as I can kind of chuckle at that a little bit and wink, wink, nudge, nudge, isn't that cute. Because you know, my dad, as you know, is very very technical and he's a senior citizen. This is hard. I hope he doesn't see that but... (laughing) But then it's not old versus young. It's not let's get a whole new group and crop and start over again. What it is instead and this is, you know, as my constant tome sort of anti compliance. I'm not anti compliance. You got to put your underwear on before your pants or it's just really hard. (laughing) And I would love to see anyone who is capable of putting their underwater on afterwards. After you've made the decision of following the process. That is so basic. It comes down to, do you want the data that describes or is donated or observed about human beings. Whether it's performance of your employees. People you would love to entice onto your show to be a guest. People you'd like to listen and consume your content. People you want to meet. People you want to marry. Private data as Ann says, does the form the foundation of our freedom, but it also forms the foundation of our commerce. So that compliance, if you have stacked the deck proactively with an ethics that people can understand and agree with and have a choice about and feel like they have some integrity. Then you will start to see the acceleration factor of privacy being something that belongs on your balance sheet. What kind of data is high quality, high nutrition in the right context. And once you've got that, you're in good shape. >> I'm laughing at privacy on the balance sheet. We just had a big conversation about data on the balance sheets. It's a whole, that's a whole another topic. So we can go for days. I have Pages and pages of notes here. But unfortunately I know we've got some time restrictions. And so, and I want to give you the last word as you look forward. You've been in this for a while. You've been in it from the private side, as well as the government side. And you mentioned lots of other scary things, kind of on the horizon. Like the kick of surveillance creep, which there's all kinds of interesting stuff. You know, what advice do you give to citizens. What advice do you give to leaders in the public sector about framing the privacy conversation >> I always want to start by telling them don't frame privacy as a negative. It's not a negative. It's something that can build so much. If you're a business, you can gain a competitive advantage by strongly protecting your customer's privacy because then it will build such loyalty and you'll gain a competitive advantage. You make it work for you. As a government you want your citizens to have faith in the government. You want to encourage them to understand that as a government you respect their privacy. Privacy is highly contextual. It's only the individual who can make determinations relating to the disclosure of his or her personal information. So make sure you build that trust both as a government and as a business, private sector entity and gain from that. It's not a negative at all, make it work for you, make it work for your citizens, for your customers, make it a plus a win win that will give you the best returns. >> Isn't it nice when doing the right thing actually provides better business outcomes too. It's like diversity of opinion and women on boards. And kind of things- >> I love that. we cover these days. >> Well ladies, thank you very very much for your time. I know you've got a hard stop, so I'm going to cut you loose or else we would go for probably another hour and a half, but thank you so much for your time. Thank you for continuing to beat the drum out there and look forward to our next conversation. Hopefully in the not too distant future. >> My pleasure Jeff. Thank you so much. >> Thank you. >> Thank you too. >> All right She's Michelle. >> She's Ann. I'm Jeff. You're watching theCUBE. Thanks for watching. We'll see you next time. (upbeat music)

>> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hey welcome back everybody, Jeff Frick here with theCUBE we're in our Palo Alto studio, it's still 2020, we're still gettin' through the COVID crisis and we're still reaching out to our community really to talk to leaders who have lead through difficult times, led through transitions, and really go out to the experts and get some advice from people who have been around the block a few times, and I'm really, really excited to have one of my all time favorite business executives joining us, I haven't talked to him in years and years and almost decades, David Pottruck is joining us, he is formerly the CEO of Schwab, how he kind of made his name, now he's an author, he's teaching at the Wharton School, he's a New York Times best selling author and he's also the chairman of Red Eagle Ventures, David, great to see you. >> Thanks, Jeff, it's good to be with you today. >> Absolutely, so before we get in, just to check in, how are you doing, how are you gettin' through 2020, I can't believe we're already on the backside of this crazy year. >> Well, it's been a pretty challenging year as you know, and we've seen companies learn to operate in a virtual world. Zoom has been one of the huge beneficiaries, but technology companies in general, the whole FAANG group of Facebook, Amazon, Netflix and such, they've all benefited from people getting more virtual, and one of the non profits I'm involved with sends out videos to schools on social and emotional learning and that's seen a big uptick. So, the world is changing, and changing in very substantial ways, and I don't think we'll ever go back to the way it was in total, we will go back to having face to face meetings, of course, but I do think that operating virtually and doing more things remotely, remote business meetings over zoom are going to be a fixed part of the future, >> Right, right. >> At least in my opinion. >> So, the reason I wanted to reach out to you is you've managed through some crazy transitions and some crazy disruptions back in the day and for a lot of the young people that don't remember, there was a time before we did everything online. There was a time where you had a broker and you called him on the phone and you paid a pretty big price based on a percentage of the transactions. You were at Schwab in the late 90s when this new thing called the internet came along, and these new things called internet only businesses to compete with you, I wonder if you can kind of take us back as you started to see some of these new kinds of threats, coming not necessarily from people that you recognize from up and down the street, but people who are coming over horizons that you've never ever seen before. And how did you start to get a feel for hmm, the landscapes a changin'. >> You know it's really funny to look back that there actually was a day when something called the internet didn't exist. And, there was no connectivity, there was no internet. We were, of course, at that time a telephone based brokerage firm, what used to be called discount brokers. We don't use that phrase very much anymore at Schwab, but, we were a telephone based discount broker, and the internet popped up and started becoming commercialized, and some online only brokerage firms popped up. And these firms didn't have call centers, they didn't have branch offices, if you wanted to do a trade you did it over your computer, online, and the pricing was dramatically less. To give you some idea, to buy 100 shares of IBM, Merrill Lynch would have charged you $250, for that one trade, Schwab would have charged you $80 and E-Trade would have charged you $25. So, we were much cheaper than Merrill Lynch, but E-Trade was much cheaper than us. So, we were, at the time, we were worried about is there enough security on the internet, can we do trades. We have a reputation to protect, a brand new company they don't have a reputation to protect, we have customer security, we have a reputation to protect. Well, we started doing online trades, and the way we did it was we gave all of our customers a 20% discount on our normal pricing, so instead of charging 80-something dollars, you paid something like $60. So, it was a nice discount, customers liked it, they were doing online trades, and we're seeing that is just taking off, it's getting huge, and we're getting great press, the analysts love it, Wall Street loves it, we're a public company and it's going great, but of course at the same time I'm getting, a basket full of letters and emails from our customers saying "why can't you do trades for $25 like E-Trade? Why are they able to do an online trade for $25 and you're charging $65? I thought you stood for value, I thought you guys wanted to be the best value for the money." So, I'm in this dilemma where Wall Street doesn't see these letters, they don't get reported, I see them, and there dozens and then hundreds, and then thousands. >> Wow. >> We had millions of customers, so to get a thousand letters or emails in a month that's very possible. And so I go to Chuck with this and I said you know, I think we need to make a change because no great company was built on the back of unhappy customers. >> Right, right. But you know, it's so funny, not funny, I'm sure it was a huge challenge in the moment, but you know, Clayton Christensen's another one of my favorite business leaders and why I like him so much, and rest in peace he passed earlier this year, is his very simple statement in "The Innovator's Dilemma" that smart people making sound business decisions based on their customer feedback will always miss discontinuous change. You were right in the middle of this thing and you had to get discontinuous change and it's funny, you've mentioned quite a bit in some of your other conversations about looking for faint signals, well this was not a faint signal, this was pretty much, sounds like came up and banged you over the head. So, how do you make and convince the rest of the people of the team that this is kind of a short-term pain but it's a long-term gain, really thinking about this long-term relationship with our customers, even though it's going to cost us on a per transaction basis in the short-term. >> Well, I had our financial staff run some models, and show me what would be the impact if we reduced our pricing from 60 something dollars a trade to $29 a trade, and the assumption of more and more trades moving to the internet. We also had a model into that the fact that people trade a little more when prices go down, costs go down cause I don't have the cost of someone answering the telephone, so there were some benefits, and I had to run the math to understand how long would it take us to go through the trough to get to the other side. A big important part of this is modeling the numbers. You don't just make this decision as a public company and just hope for the best >> Jeff: Right. >> You need to model it out, you need to run math and say how long will it take, what do we have to assume, what do we need to do, what costs do we need to cut, how are we going to protect ourselves as best as we can? And we knew that the math said that our profitability will go down 25% when we make this change of internet pricing, and we expected that Wall Street would be so upset, because they didn't see this coming, no analyst saw this coming cause they don't know about complaint letters I'm getting, so, analysts would be upset and the stock would go down 40%, going to your board and telling them you want approval for a 25% reduction in profits and a 40% reduction in your stock price is not what you want to do as a CEO, you don't want to go to your board with that and when they ask you, well how sure are you that we're going to climb out of this, you say it's going to take 18 months, what if it takes three years, you know, I was, I didn't see the choice we had, honestly, in my heart, you don't build a great company with an increasing number of unhappy customers. I didn't think we had a choice, and Clayton Christensen was one of the consultants that I used to help me think all this through because it was really hard to make this change, Jeff, because we were doing so well. >> Right. >> Ostensibly, we were killing it. >> Right, so it's interesting, I wonder if you could contrast it to what's happening say now with COVID, right, it was this, didn't sneak up on anyone, it was a really kind of a light switch moment in mid-March where suddenly everyone has to work from home, all your digital transformation initiatives are now put on fast forward, but we still have this situation where there's a variety of potential outcomes and timing that's really hard to gauge, so when you're thinking about managing through change within perfect information and you almost have kind of will we go back to normal, will we stay where we are or some spectrum in between, how do you help people think about how they should come up with contingency plans and think about managing through a number of options with imperfect information and really kind of no clear line, you said you had an 18 month ROI that the analytics point to, we're not really sure how long this thing is going to go and what it's going to look like when we get to the other side. >> Well, I think there's two issues there, one of them is how we get through this pandemic period. Until we get to, there's three things we need, we need inexpensive testing that is not done by a professional that we can do at home to see if we're safe. That's number one. Number two, we need a treatment that helps us get through this and get to the other side without dying, we need the fatality rate to even drop further. And number three we need a vaccine. So those are the three things that we need, that the world is working on all three of those, and my guess is that in the first half of 2021 we will have all three of those, we'll have all three of those and this will be a thing, basically, a thing of the past. >> Jeff: Right. >> So, but I don't think the world goes back, to exactly the way it was. People have learned they can have very effective meetings without everybody flying to Chicago, or New York, or Las Angeles, they can do it over Zoom, that doesn't mean meetings go away, but I think they're going to go down in numbers and more online things are going to happen. More people are going to be working from home at least part of the week. It's going to be different. >> Yeah. >> Those CEO's who sit in a somewhat of an ivory tower and get numbers fed to them from their financial staff, and they're not out talking to customers directly, people look at that as anecdotal information, I think it's more important than that, I think you need to see the passion behind the voice and the eyeballs of some of your best customers to understand what's going on with them, and a lot of CEO's don't actually do that. >> Right. You've made a really interesting comment in another interview that you did earlier, and you talked about the high gain questions. And one of the challenges of all CEO's is nobody wants to be the one that tells his CEO bad news, whether that be someone on your staff, whether that be some lower level person who's on the front lines and really knows there's some broken things, or whether it's a good customer as you said and kind of a social setting, how you doin', oh we love you, blah blah blah. But as a CEO you really have stressed that that is really some important hard to find, and hard to filter information up to the executive suite, so what were some of the tips and tricks you used to make sure that people either A. weren't afraid to tell you bad news, and B. that you could kind of go out and sniff it out a little bit more creatively than just kind of waiting for it to come through in the weekly reports. >> Well, obviously, you know, I think all kinds of executives get out and they talk to their customers on a regular basis, they're out and they're talking to them, the problem with those kind of discussions are no one wants to be disrespectful, people want to be nice in those meetings by and large, and you ask questions "how are we doing" "oh you guys are doing great", meanwhile the guy who tells you you're doing great is also looking at some newer technology that might replace you. (laughs) So that kind of question doesn't get you very far. So what we used to do, to be quite specific, is that we used to do a monthly luncheon where I had 12 of my mostly top executives but some people a level or two down, 12 Schwab people with 24 customers. And so they were tables of six, two of us, four customers, and we had a theme that we would talk through and the themes were always around things of, if you had to pick out three things we don't do well, what would they be? Give the customer permission to be comfortable being critical. What are the three things that you've heard about our customers, our competitors doing, that are better than us? What are the things that we need to change to make you even more delighted? You need to ask those kinds of high gain questions where there's no polite answer, the customer is permitted and given the opportunity to answer in a truthful and critical fashion. >> That's a great lesson, as you said give them permission and give them the format and the forum to say some of those things so that you get some of that information. Another great leadership principle that you shared many times, I want to dig into a little bit is kind of motivation verses inspiration. And that those are often confused, but very different concepts in the way that you lead people. I wonder if you can dig in a little bit on your philosophy on those two things. >> Sure, you know it's funny, those terms motivation and inspiration are used almost interchangeably as if they're the same thing. And they're not. Motivation is fundamental in business, and it's the exchange of behaviors for rewards. I was a psychology major in college, this was one of the things we learned about the exchange of behaviors for rewards and that's motivation. Inspiration on the other hand, is the effort to make people want to do something for, not for rewards that are tangible, but to be part of something great. We want you to be part of a movement, we want you to be part of something special, something that's going to change the world for the better and trying to get your employees to buy into this notion that we are on a mission and that mission is to make the world a somewhat better place, it doesn't mean we don't make money, of course we make money, but we're also out for more than a financial bottom line, we're out for a bottom line that's great for customers and maybe pretty great for employees as well. >> So it's interesting, cause you've seen 'em right, you've been in finance for ever, it's always about the shareholders, you've talked about the stock price a number of times in terms of a measure, but it seems more purposed led or purpose forward organizations now are more appealing to the younger generation, I think the search for a little bit more meaning in our day to day job and what that company is all about seems to have elevated over the last several years and taken a higher role in what they used to call triple line accounting, is it not only your shareholders who always are at the top of the list and have been traditionally, but your customers, your employee, and more and more your community and even the environment. Have you seen the swing towards, it's not just about shareholder value? >> Well, not on Wall Street. (laughs) I think, Wall Street is about money, and the people who go to work on Wall Street, and the way Wall Street operates, it's measured in dollars and cents and share price and profits and distributions to private equity partners and so forth, it's a numbers game and it is a profit game on Wall Street, we should be honest about that, it is what it is. >> Jeff: Sure. >> And, I have yet to see the Wall Street firm that is talking about triple bottom lines cause that just doesn't happen very much on Wall Street, it doesn't happen from my perspective, it almost doesn't happen at all. But there are other companies where they do talk about a more triple bottom line, and I think as a leader if you want to be that kind of company and you want to be that kind of leader you have to be comfortable talking about that, and not feel embarrassed by it, not feel that oh, that's too airy fairy, that's too goody two shoes. If you really believe that our goal is to have a triple bottom line, profitability, great for employees, and great for customers and the world at large, then as a leader you need to talk about that. You need to be willing to stand up and have those kinds of conversations and let yourself be challenged by perhaps the press, employees, shareholders, who think that that's not a good strategy. I believe that in many cases that's a great strategy because on a long-term basis you don't want every employee in your company, and all of your senior executives to basically be up for sale, that if a bigger job comes in with a bigger compensation, they're out the door. You're looking for loyalty, you're looking for buy in, for participation, for wanting to give every bit of themselves for the mission of the company. And as the CEO, if you want to take that path, you got to be willing to put yourself out there and talk about it and suffer the slings and arrows from those who don't believe that that's the best path for the company. >> Right, right. Well and that's another thing that you've talked about quite often, is really that the company feeds off the passion of the CEO, and the CEO has to have that passion because they're lookin', they're watchin', they're lookin' at your moves, they're lookin' at what you say, they're lookin' at your body language, they're lookin' at everything that you do. And I think within the context of these transitions and these difficult times, you have another great line that you've used a number of times, which is: "You need to have a perception of momentum." I love that line, so everyone needs to think that we're on the right path, we're not there yet, I feel it, he looks like he feels it, he looks like he's confident, so now I'm confident and I'm going to jump in and help be part of this change process. You've seen that time and time. >> Well, momentum is a tricky thing, you can have momentum and not have the perception of momentum. Because if you're doing a turn around, what often happens is in the early stages of the turn around, the numbers start to change but they're small, and you really haven't seen, it's not as steep. The turn around doesn't go steep, the turn around goes and builds slowly. And, what you need to be measuring in the beginning, are kind of the inputs and behaviors rather than the outputs, sales and profits. Those take longer. But you need to build belief, you need to build buy in, because it can take a long time before things start getting better and you don't want your best people to wonder whether this is the right move, should I be looking for another job, so, you have to build the perception of momentum even as you're building the reality of momentum. >> Right, right. So another thing we cover a lot of tech conferences, obviously, Cloud and AI, machine learning are hot things. But, you know, it always goes back to the big three. It's the technology, okay, but it's also people, and more importantly I think that gets left out is process. So, when you're thinking about, you know you're management is, and again, especially through a transition or a difficult time or some unknown and choppy waters, how do you think about those three, prioritizing those three and organizing those three between people, process and technology? >> Okay, well, you know always looking for technology that can be implemented to give you productivity, better customer service, you need to be monitoring what you're competitors are doing, and be looking out, sometimes at the bleeding edge, where you don't need to implement those kinds of changes right away, but you need to know where you want to go down the road, so you have some sense of that. As far as process goes, your processes are both a strength and a weakness because the strength of how well you run your processes today is also how hard they're going to be to change tomorrow. You know, companies are built for predictability, reliability, risk minimization, and all of your processes are built for those things. But those are also the things that are the opposite of big breakthrough changes. So you need to be thinking about, all right, are we strengthening our processes but also, if we have a change coming that's going to require a change of some of those processes, how is that going to get in our way and how are we going to get past that? >> Jeff: Right. >> I've left people for the last because to me that's the heart and soul of a successful executive. One person never gets everything done, it's all about the quality of your team. You've got to be a recruiter, you've got to be always on the look out for new talent that can help your company, and you've got to be thinking about how you're going to recruit that talent. You have to be a magnet for talent. When I sit on boards and I talk to the CEOs, I ask them, what are you doing to be a magnet for talent? What does that mean? What are you doing for great people to want to work for you? For you, and your company, what are you doing, how are you reinvesting in people, how are you putting time and energy in their professional development, in their growth? How are you getting to know them? How are you understanding their ambitions, their hopes and desires for the future? How much time and effort do you spend on that? And that's all part of having people not leave, everyone, in a way you can look at the world and think everyone is for sale. But you want people that are not for sale, that are committed to you and committed to the mission and in today's world where everything seems so fluid, I know my ideas about this probably seem very old and perhaps out of date, but I still believe in them with all my heart, that you want people that are committed to you and what we are accomplishing together. And you have to be reinforcing that with your words, and even more importantly with your actions. >> Yeah, I think it goes back to your inspiration, people are much more motivated by inspiration than just collecting a paycheck or getting a compensation back for what they're doing, which is a great segue to the last topic I wanted to cover with you, and I remember this, we had dinner, I think it was 1996 at the Wharton's Zweig Series, and you were such a phenomenal speaker, and I remember asking you the question and I remember your answer, and I've repeated it ad nauseam for the last 20 years. I said, "David, you're such a great speaker, why, how?" And you were so matter of fact in that you just said "hey, it's an important part of my job, I treat it as a skill, I hired a coach, I practiced like I would do any other skill", and why that's such a powerful story is you clearly are in a position of power, you could clearly have a crazy ego that got in the way of such a matter of fact accomplishment of these tasks and all the PR people I talk to and they hear this story "oh my gosh, we got to get him talking to my executives" because so many people let ego get in the way of what is really an important task for a CEO and a leader which is communication and you recognize that early on and really went after it to make sure that you were very good at this very important task. >> Well, what happened to me, I got lucky, I got lucky. When I got promoted to be the CEO of Schwab, I knew I was going to have to do a lot more public speaking and I already thought I was pretty good at being a public speaker, but I thought I needed to fine tune my messaging, I needed to get it better. So, I looked around and I got some referrals and I hired a guy that I thought was going to be a speech writer for me, that would help craft the message. And, we had our first meeting, and we're talking about an upcoming speech and he says to me things like, "Well, Dave, I want to know more about your life. Tell me how you grew up, tell me what you're proudest moments were, I want to learn about you." And I said to him, "Terry, I'm not looking for a biographer, I want a speech writer, I need a guy that can help me craft my message." And he said, "Well, Dave, that's not how I do things. I need to know who you are, I need to know what your passions are and where they come from so that we can give a message that has more than just words it has meaning, it has your passion built into it, that's what we need to do." And that's what Terry taught me, was that it's not just the words, it's also the passion, energy, and meaning and connection behind the words. And I want to mention one other thing that I think is very important. When people talk about being really good communicators, they often talk about speaking. They don't focus on listening. And listening is a tremendously important skill. So for example, you give a speech, you're the CEO or Senior Executive, you give a speech, do you stay there and do you do a Q+A session? The Q+A session can even be more important than the speech sometimes, because all the employees know that the speech is something that was pre-arranged, it's not on the cuff, it's something that's been thought about and prepared. But the questions and answers are authentic and in the moment. People are clamoring for authentic leadership. That Q+A session, where you're listening for the question and maybe the question behind the question. So you're not just trying to get through them as fast as you can, but you're trying to really answer and listen for the question and the question behind the question. And then answer those from the heart with passion, and that's how you will score the most points with your audience. >> That's great. And then who knows what comes from it, in getting ready for this I came across your blog post talking about Gopi Kallayil a mutual friend at Wharton who reached out to you after that same dinner, and you were happy enough, or you were kind enough to respond and grow a friendship and a relationship that again is lasted for decades. So that's such an important message to listen, as somebody said right, "God gave you two ears and one mouth should try to use them in that ratio." (laughs) Well David, thank you so much for taking some time, again I think these are really trying times in leadership, I think it's really an opportunity for great leaders to shine and those that don't there's really no place to hide. So I really appreciate you sharing your insight and taking a few minutes with us. >> Thanks, Jeff, I hope all the people that follow you and listen to your broadcasts learn something today and come away with some benefit from this time we've spent together. >> Undoubtedly, undoubtedly. Well, thanks again. All right, he's Dave Pottruck, I'm Jeff Frick, you're watching theCUBE, thanks for watching and we'll see you next time. (upbeat music)

>> David: It's the cube covering the virtual Vertica Big Data conference 2020 brought to you by Vertica. Hello, buddy, welcome to this special digital presentation of the cube. We're tracking the Vertica virtual Big Data conferences, the cubes. I think fifth year doing the BDC. We've been to every big data conference that they've held and really excited to be helping with the digital component here in these interesting times. Ron Cormier is here, Principal database engineer at the Trade Desk. Ron, great to see you. Thanks for coming on. >> Hi, David, my pleasure, good to see you as well. >> So we're talking a little bit about your background you got, you're basically a Vertica and database guru, but tell us about your role at Trade Desk and then I want to get into a little bit about what Trade Desk does. >> Sure, so I'm a principal database engineer at the Trade Desk. The Trade Desk was one of my customers when I was working with Hp, at HP, as a member of the Vertica team, and I joined the Trade Desk in early 2016. And since then, I've been working on building out their Vertica capabilities and expanding the data warehouse footprint and as ever growing database technology, data volume environment. >> And the Trade Desk is an ad tech firm and you are specializing in real time ad serving and pricing. And I guess real time you know, people talk about real time a lot we define real time as before you lose the customer. Maybe you can talk a little bit about you know, the Trade Desk in the business and maybe how you define real time. >> Totally, so to give everybody kind of a frame of reference. Anytime you pull up your phone or your laptop and you go to a website or you use some app and you see an ad what's happening behind the scenes is an auction is taking place. And people are bidding on the privilege to show you an ad. And across the open Internet, this happens seven to 13 million times per second. And so the ads, the whole auction dynamic and the display of the ad needs to happen really fast. So that's about as real time as it gets outside of high frequency trading, as far as I'm aware. So we put the Trade Desk participates in those auctions, we bid on behalf of our customers, which are ad agencies, and the agencies represent brands so the agencies are the madman companies of the world and they have brands that under their guidance, and so they give us budget to spend, to place the ads and to display them and once the ads get displayed, so we bid on the hundreds of thousands of auctions per second. Once we make those bids, anytime we do make a bid some data flows into our data platform, which is powered by Vertica. And, so we're getting hundreds of thousands of events per second. We have other events that flow into Vertica as well. And we clean them up, we aggregate them, and then we run reports on the data. And we run about 40,000 reports per day on behalf of our customers. The reports aren't as real time as I was talking about earlier, they're more batch oriented. Our customers like to see big chunks of time, like a whole day or a whole week or a whole month on a single report. So we wait for that time period to complete and then we run the reports on the results. >> So you you have one of the largest commercial infrastructures, in the Big Data sphere. Paint a picture for us. I understand you got a couple of like 320 node clusters we're talking about petabytes of data. But describe what your environment looks like. >> Sure, so like I said, we've been very good customers for a while. And we started out with with a bunch of enterprise clusters. So the Enterprise Mode is the traditional Vertica deployment where the compute and the storage is tightly coupled all raid arrays on the servers. And we had four of those and we're doing okay, but our volumes are ever increasing, we wanted to store more data. And we wanted to run more reports in a shorter period of time, was to keep pushing. And so we had these four clusters and then we started talking with Vertica about Eon mode, and that's Vertica separation of compute and storage where you get the compute and the storage can be scaled independently, we can add storage without adding compute or vice versa or we can add both, like. So that was something that we were very interested in for a couple reasons. One, our enterprise clusters, we're running out of disk, like when adding disk is expensive. In Enterprise Mode, it's kind of a pain, you got to add, compute at the same time, so you kind of end up in an unbalanced place. So beyond mode that problem gets a lot better. We can add disk, infinite disk because it's backed by S3. And we can add compute really easy to scale, the number of things that we run in parallel concurrency, just add a sub cluster. So they are two US East and US west of Amazon, so reasonably diverse. And and the real benefit is that they can, we can stop nodes when we don't need them. Our workload is fairly lumpy, I call it. Like we, after the day completes, we do the ingest, we do the aggregation for ingesting and aggregating all day, but the final hour, so it needs to be completed. And then once that's done, then the number of reports that we need to run spikes up, it goes really high. And we run those reports, we spin up a bunch of extra compute on the fly, run those reports and then spin them down. And we don't have to pay for that, for the rest of the day. So Eon has been a nice Boone for us for both those reasons. >> I'd love to explore you on little bit more. I mean, it's relatively new, I think 2018 Vertica announced Eon mode, so it's only been out there a couple years. So I'm curious for the folks that haven't moved the Eon mode, can you which presumably they want to for the same reasons that you mentioned why by the stories and chunks when you're on Storage if you don't have to, what were some of the challenges that you had to, that you faced in going to Eon mode? What kind of things did you have to prepare for? Were there any out of scope expectations? Can you share that experience with us? >> Sure, so we were an early adopter. We participated in the beta program. I mean, we, I think it's fair to say we actually drove the requirements and a lot of ways because we approached Vertica early on. So the challenges were what you'd expect any early adopter to be going through. The sort of getting things working as expected. I mean, there's a number of cases, which I could touch upon, like, we found an efficiency in the way that it accesses the data on S3 and it was accessing the data too frequently, which ended up was just expensive. So our S3 bill went up pretty significantly for a couple of months. So that was a challenge, but we worked through that another was that we recently made huge strides in with Vertica was the ability to stop and start nodes and not have to start them very quickly. And when they start to not interfere with any running queries, so when we create, when we want to spin up a bunch to compute, there was a point in time when it would break certain queries that were already running. So that that was a challenge. But again, the very good team has been quite responsive to solving these issues and now that's behind us. In terms of those who need to get started, there's or looking to get started. there's a number of things to think about. Off the top of my head there's sort of new configuration items that you'll want to think about, like how instance type. So certainly the Amazon has a variety of instances and its important to consider one of Vertica's architectural advantages in these areas Vertica has this caching layer on the instances themselves. And what that does is if we can keep the data in cache, what we've found is that the performance is basically the same performance of Enterprise Mode. So having a good size cast when needed, can be a little worrying. So we went with the I three instance types, which have a lot of local NVME storage that we can, so we can cache data and get good performance. That's one thing to think about. The number of nodes, the instance type, certainly the number of shards is a sort of technical item that needs to be considered. It's how the data gets, its distributed. It's sort of a layer on top of the segmentation that some Vertica engineers will be familiar with. And probably I mean, the, one of the big things that one needs to consider is how to get data in the database. So if you have an existing database, there's no sort of nice tool yet to suck all the data into an Eon database. And so I think they're working on that. But we're at the point we got there. We had to, we exported all our data out of enterprise cluster as cache dumped it out to S3 and then we had the Eon cluster to suck that data. >> So awesome advice. Thank you for sharing that with the community. So but at the end of the day, so it sounds like you had some learning to do some tweaking to do and obviously how to get the data in. At the end of the day, was it worth it? What was the business impact? >> Yeah, it definitely was worth it for us. I mean, so right now, we have four times the data in our Eon cluster that we have in our enterprise clusters. We still run some enterprise clusters. We started with four at the peak. Now we're down to two. So we have the two young clusters. So it's been, I think our business would say it's been a huge win, like we're doing things that we really never could have done before, like for accessing the data on enterprise would have been really difficult. It would have required non trivial engineering to do things like daisy chaining clusters together, and then how to aggregate data across clusters, which would, again, non trivial. So we have all the data we want, we can continue to grow data, where running reports on seasonality. So our customers can compare their campaigns last year versus this year, which is something we just haven't been able to do in the past. We've expanded that. So we grew the data vertically, we've expanded the data horizontally as well. So we were adding columns to our aggregates. We are, in reaching the data much more than we have in the past. So while we still have enterprise kicking around, I'd say our clusters are doing the majority of the heavy lifting. >> And the cloud was part of the enablement, here, particularly with scale, is that right? And are you running certain... >> Definitely. >> And you are running on prem as well, or are you in a hybrid mode? Or is it all AWS? >> Great question, so yeah. When I've been speaking about enterprise, I've been referring to on prem. So we have a physical machines in data centers. So yeah, we are running a hybrid now and I mean, and so it's really hard to get like an apples to apples direct comparison of enterprise on prem versus Eon in the cloud. One thing that I touched upon in my presentation is it would require, if I try to get apples to apples, And I think about how I would run the entire workload on enterprise or on Eon, I had to run the entire thing, we want both, I tried to think about how many cores, we would need CPU cores to do that. And basically, it would be about the same number of cores, I think, for enterprise on prime versus Eon in the cloud. However, Eon nodes only need to be running half the course only need to be running about six hours out of the day. So the other the other 18 hours I can shut them down and not be paying for them, mostly. >> Interesting, okay, and so, I got to ask you, I mean, notwithstanding the fact that you've got a lot invested in Vertica, and get a lot of experience there. A lot of you know, emerging cloud databases. Did you look, I mean, you know, a lot about database, not just Vertica, your database guru in many areas, you know, traditional RDBMS, as well as MPP new cloud databases. What is it about Vertica that works for you in this specific sweet spot that you've chosen? What's really the difference there? >> Yeah, so I think the key differences is the maturity. There are a number, I am familiar with another, a number of other database platforms in the cloud and otherwise, column stores specifically, that don't have the maturity that we're used to and we need at our scale. So being able to specify alternate projections, so different sort orders on my data is huge. And, there's other platforms where we don't have that capability. And so the, Vertica is, of course, the original column store and they've had time to build up a lead in terms of their maturity and features and I think that other other column stores cloud, otherwise are playing a little bit of catch up in that regard. Of course, Vertica is playing catch up on the cloud side. But if I had to pick whether I wanted to write a column store, first graph from scratch, or use a defined file system, like a cloud file system from scratch, I'd probably think it would be easier to write the cloud file system. The column store is where the real smarts are. >> Interesting, let's talk a little bit about some of the challenges you have in reporting. You have a very dynamic nature of reporting, like I said, your clients want to they want to a time series, they just don't want to snap snapshot of a slice. But at the same time, your reporting is probably pretty lumpy, a very dynamic, you know, demand curve. So first of all, is that accurate? Can you describe that sort of dynamic, dynamism and how are you handling that? >> Yep, that's exactly right. It is lumpy. And that's the exact word that I use. So like, at the end of the UTC day, when UTC midnight rolls around, that's we do the final ingest the final aggregate and then the queue for the number of reports that need to run spikes. So the majority of those 40,000 reports that we run per day are run in the four to six hours after that spikes up. And so that's when we need to have all the compute come online. And that's what helps us answer all those queries as fast as possible. And that's a big reason why Eon is advantage for us because the rest of the day we kind of don't necessarily need all that compute and we can shut it down and not pay for it. >> So Ron, I wonder if you could share with us just sort of the wrap here, where you want to take this you're obviously very close to Vertica. Are you driving them in a heart and Eon mode, you mentioned before you'd like, you'd have the ability to load data into Eon mode would have been nice for you, I guess that you're kind of over that hump. But what are the kinds of things, If Column Mahoney is here in the room, what are you telling him that you want the team, the engineering team at Vertica to work on that would make your life better? >> I think the things that need the most attention sort of near term is just the smoothing out some of the edges in terms of making it a little bit more seamless in terms of the cloud aspects to it. So our goal is to be able to start instances and have them join the cluster in less than five minutes. We're not quite there yet. If you look at some of the other cloud database platforms, they're beating that handle it so I know the team is working on that. Some of the other things are the control. Like I mentioned, while we like control in the column store, we also want control on the cloud side of things in terms of being able to dedicate cluster, some clusters specific. We can pin workloads against a specific sub cluster and take advantage of the cast that's over there. We can say, okay, this resource pool. I mean, the sub cluster is a new concept, relatively new concept for Vertica. So being able to have control of many things at sub cluster level, resource pools, configuration parameters, and so on. >> Yeah, so I mean, I personally have always been impressed with Vertica. And their ability to sort of ride the wave adopt new trends. I mean, they do have a robust stack. It's been, you know, been 10 plus years around. They certainly embraced to do, the embracing machine learning, we've been talking about the cloud. So I actually have a lot of confidence to them, especially when you compare it to other sort of mid last decade MPP column stores that came out, you know, Vertica is one of the few remaining certainly as an independent brand. So I think that speaks the team there and the engineering culture. But give your final word. Just final thoughts on your role the company Vertica wherever you want to take it. >> Yeah, no, I mean, we're really appreciative and we value the partners that we have and so I think it's been a win win, like our volumes are, like I know that we have some data that got pulled into their test suite. So I think it's been a win win for both sides and it'll be a win for other Vertica customers and prospects, knowing that they're working with some of the highest volume, velocity variety data that (mumbles) >> Well, Ron, thanks for coming on. I wish we could have met face to face at the the Encore in Boston. I think next year we'll be able to do that. But I appreciate that technology allows us to have these remote conversations. Stay safe, all the best to you and your family. And thanks again. >> My pleasure, David, good speaking with you. >> And thank you for watching everybody, we're covering this is the Cubes coverage of the Vertica virtual Big Data conference. I'm Dave volante. We'll be right back right after this short break. (soft music)

(upbeat music) >> Announcer: Live from New York, it's the Cube, covering AWS Global Summit 2019. Brought to you by Amazon Web Services. >> Welcome back, we're here in New York City at AWS Summit, one of the regional summits. Over 10,000 people in attendance. I'm Stu Miniman. My cohost is Corey Quinn and happen to welcome Slalom to the program for the first time. So, Slalom, like Amazon themselves, is based in Seattle, yet, also has a presence here in New York City. And representing that, to my right, we have Parul Patel, who is the managing director of middle market for Slalom, based here in New York City. >> That's right. >> World Trade Center, I believe that's where your office is. >> That's right. >> That's excellent. And Joe Berg is the managing director with Slalom based out of Seattle. Thank you so much for joining us. >> Yeah, thank you. >> All right, so, I did walk by the booth this morning. Build as a service is the big takeaway. But for our audience that might not be familiar with Slalom, give us the bumper sticker. >> Yeah, so, the way we like to tell the story is Slalom is a modern consulting company focused on strategy, technology and business transformation. As a part of the technology work that we've been doing for clients for the last couple decades, we started to see a shift in that really with the advent of cloud and companies like AWS. Really changing the technology landscape and what was really possible. You mentioned the build as a service tagline. That's really what the operating model that we built to serve those customers at the scale and at the velocity that they're starting to execute on their most mission critical digital initiatives today. So build as a service is really how we dig in and leverage platforms like AWS and provide value for customers. All right, so, Parul, one of the things we like about these regional summits is it's not just little bit rinse and repeat when you go to the environments-- >> Parul: Right. >> But they do speak to the local market. So when you look at that, some of the customers in the keynotes, you expect to see some financial services-- >> Parul: Right. >> Being here in New York City. A startup like Door Dash, where they were here. Give us your viewpoint, what is special or unique about the greater metropolitan region here in New York City that you see with your customers. >> Sure. So I think as we think about New York as a market, a lot of industries, a lot of companies that are based here. Certainly financial service is one of the big ones. But the buzz in the market is all about cloud. What are we going to do, how are we going to get into the cloud? The question we like to ask our customers is, why. Why do you want to be in the cloud? And what we're seeing, especially in financial services, is a lot of innovation. So as we think about what Joe does from a build as a service perspective, we have a client in financial services who they wanted to figure out, how do we generate more revenue? So we built them, with our build as a service capability, an AWS platform that helped them bring data together and figure out how to monetize that data across different business units and innovate. And so I think it's things like that that we ask that question of why. We can leverage cloud to really do that transformation. >> That's great. We always talk about IT can't be the organization of no. Or, as a friend of mine, Alan Cohen, said, that there's the triangle of no and slow and we need to move up to the top, which is go. >> Right. >> So how does cloud help with that move forward. That love story you talk about, how do I monetize data, how do I move that forward. There's been that promise of that but how do I turn it from a lofty goal into actual reality? >> Yeah, maybe Joe, I'll let you answer that with a little bit of how we bring it to life with our build as a service. >> Honestly, we look at cloud, it's not just an enabler of business today. It's almost fueling business today. And the reality is, the customer consumer demand out there for digital experiences is exponentially growing, right? Organizations are trying to transform themselves into these modern technology companies. Doesn't matter what industry, financial services-- >> Parul: That's right. >> Or otherwise, they're really trying to transform themselves. And cloud is really allowing them to get out of the procurement game, out of the infrastructure game, out of the data center game and really start to lean into, how do I just make use of this in a meaningful way that's going to translate into those revenue streams that Parul talked about. >> It's deceptively complex. Sorry, it's deceptively simple, I suppose, to take a look at what cloud represents, of, okay, now whatever you want instead of buying it, waiting six weeks for it to show up, if you're lucky, and then racking it. Suddenly, it's an API call away. The technology piece is interesting but how does that impact the cultural change, the processes, the governance story about it? The cost control, speaking as a cloud economist, how do you find that this is revolutionizing these companies as they are migrating into this brave new world and transforming? >> Joe: Yeah. >> When I think about cloud, so to me, it isn't a technology play at all across a business. It's about changing your business that starts with changing your mindset. So, being in the cloud, and leveraging cloud, is about how do I do things different? And that means, I'm looking at my fundamental operating model. I'm looking at who my customers are and then changing the mindset of my people. And culturally, we're going to become faster, we're going to iterate a lot more. And having things like cloud, which I can spin up instances at the click of a button, makes it easier for me to do that. But it comes with, I've got to think about my people, right? And I always tell our clients, explain to your people why this is important to them and why it's important to the business because they're going to be able to learn new skills. They're going to be able to do more and become more marketable out there. And so, to me it's a company transformation, not necessarily a technology play at all. >> Yeah, and I'll just maybe piggyback on the back of that. When you take your strategy and you start to think about translating how we're going to do things in a digital business environment and you start to think about the demands that consumer base has on how fast you release features, how quickly you are procuring new experiences for them. It is absolutely about an operating model that can translate strategy and do initiative and budgeting planning into execution very quickly. It's also, then, about when they move into the actual execution. IT organizations were not built to build technology products. They were there to build technology projects. And the confluence of those events of this becoming mission critical and part of their external facing strategy has really required that transformation and cultural shift as well, in terms of how do we build things very fastly and quickly-- >> Parul: That's right. >> Get them out to market in a iterative way that has impact and benefit and value to consumer. And I think that is the holistic complexity that organizations are dealing with, with something that is making technology very simple but the actual then motion of getting that technology to be useful is complex. >> Yeah, and it becomes very challenging to get to a point of people who are used to the old way of doing things. they're seeing the skillset that's required continue to evolve. And it's very challenging for a large-scale company to say, okay, I'm going to go out this week and hire 2,000 new people who are all up to speed on a cloud provider. >> Parul: Yeah. >> That's something that's almost impossible for people to do. So there has to be a bridge. There has to be a story that isn't, well, we're going to replace you with a younger version. >> Right. >> There has to be something that opens a door and a way to get there. And doing that both culturally and on an individual level seems like it's something a lot of companies are struggling with right now. Is that something you're seeing in your customer base? >> Absolutely. I love that question because it gives me an invitation to talk about build as a service. >> That's right. >> And build as a service, we're playing on the as a service language that companies like AWS establish, right? And the idea about build as a service is it's instantly available. You've got idea, you need to go start executing quickly. Maybe competitor A has already built an experience out there that is surpassing you in the marketplace. You don't time to think about, how do I pull all these things together? How do I upskill my resources in terms of skillsets and capabilities to then get to the point where I can execute? I need to do that now. But, I'm also on this journey of transforming my internal culture and my people and my skillsets. So how do I get a jumpstart in that. We have built a model to help our customers instantly tap into that. And these multidisciplinary teams that really holistically are bringing solution to customer, but we're also doing this in what we call a co-creation model. How do we help them learn and adopt those same principles that are going to help them build modern technology, software and products when we're gone and they're becoming self-dependent. And I think that is part of the journey of how you can leverage a company like Slalom. >> And that's why I would add, Joe, as we think about our offering, it is about getting to velocity in the software engineering space in the cloud. But this co-creation concept, I think, is one that we've heard from our clients that not a lot of people do. It's easy for partners to come in and say, here, we'll just do it for you. And our model is, we want to do it with you to the point where, when you have an agile team, we've got a mixed team of Slalom team members and client team members where we're helping the client team members learn along the way because these are all new technologies that are evolving so fast that it's hard to keep up, for anyone. >> It give me hope to hear what you're saying here, 'cause we all have the scars of listing through. It's like, okay I did a big rollout. Oh how'd it go? Well, you know, it was six to 12 months later than we thought and we all did the corporate mandated training. Yet, a month later, we're all lookin' at each other sayin, oh my gosh, how do we deal with what we have? And of course, it is no longer just waterfall and throw things over there. It is constantly changing. Therefore, co-creation is a term we love-- >> Joe: Yeah. >> And help us walk through. How long is an engagement like this? How much is there the ramp up? And then, as a service, so I'm assuming there is maintenance and you're staying engaged as after we are through some of those milestones. >> Sure, sure. Well, I always kind of start with, we moved from, as I said earlier, a project mindset into a product mindset. So each of these we consider its own piece of software. And product really starts way out here on the ideation site. So Parul talks a lot with customers about the strategy of what new revenue streams you need be thinking about. how do you engage with experiences? Once we move into this I know what I want to build. Now I just don't know how I'm going to get there to the finish line, as you were talking about earlier, Stu. That's really where we enter in with this build as a service model. And we start with a short four to six week discovery phase. So we can start to establish the foundation of what we're going to build together with our customers. That's where co-creation starts, right? What are other priorities? What are the features? How do we do agile together, which is usually a term companies use but it's not a term they know how to use, or a motion they know how to exercise well with. And so, how do we establish those things that we're going to create together? And then we scale into what we would call an MVP release cycle. Our whole idea is that we help you get to an MVP. We help you get to more viable product and then you start to become the owners of those future releases. That's that co-creation piece, where we can bring you alongside us, establish culture, actually create business value by actually getting something out the door. And then, you start to own it yourself. Depending on the competency and the abilities of the customers we work with, that can vary in terms of when those transitions happen. But we look at that as typically anywhere from a 10 to 14 week exercise to get that first iteration out. And then we start to iterate faster than that. >> Are most of your customers, are they just dealing with the people that they have in house? Or are they having to bring in new people to help with that transition along the way? I'm assuming it's a bit of a mix. >> I think it is a bit of a mixed bag and I think one of the keys, what I like about our philosophy, is that, we're all about how do we get you working software as quickly as possible. While we can do a four to six week discovery, we have client in a startup in the healthcare space, where we got them through discovery within four weeks. We do two week sprints. After three sprints, we had software up and running. And so, within 10 weeks, we said, here's what you need, and here's some working software. That I think, in a lot of ways, people say, hey, we're agile, we work fast. People typically are not delivering software in 10 weeks. And that to me, is the differentiator for the way we approach our problems, is we want to get to that working software as fast as possible. >> Right, at some point it almost feels like agile stopped meaning agility and started meaning we have a lot of meetings every morning. >> Parul: Yes. >> Joe: That's right. >> And that doesn't work. >> Yeah. >> That's right. That's a great way to say it, yeah. >> All right, a lot of customers here. Tell us what are some of the top things you're hearing from people. What bring them to your booth? What are some of those things that kind of set off the, oh this is a good fit for working with Slalom. >> Sure, well, I get asked all the time, what industries do you guys work in? Where is this most relevant, especially when you're talking about build as a service. And the reality is, it just slices horizontally right through every industry. Because, I don't know of an industry, whether it be healthcare, financial services, retail, manufacturing, I don't know of one that isn't on that journey. They're at different places on that journey, and the adoption curve, but usually we seem them coming. I think there's a stat out there that says 80% of the enterprise customers have adopted cloud. But only about 10% of the work clothes are on cloud, right? >> Parul: That's right. >> So they're coming to us with saying, hey we know we're on this journey of moving to the cloud, but we're stuck in really getting the most value out of the cloud and how can you help us accelerate the value that we believe is there with a platform like AWS? And that's where we're really entering in and finding those critical experiences that are going to create value, not only internally in terms of momentum, but externally in terms of their business. >> Yeah. And I would say that as we think about when companies look at us and why they picked Slalom as an organization to work with, one of the key differentiators is we like to work with people that we enjoy working with. So we truly want to partner with our clients and so companies say, you know what? We want people that we enjoy working with. we want people that are going to challenge us and be innovative. And that's what you're going to get. When you get Slalom, if you're lookin' for someone to be innovative and challenging a little bit, we're probably not the best fit for your company, right? That's just being honest out there. But I think the other piece of it is that we want to accelerate your journey and enable you to do it. So, we're not in the business. While we have long-term capabilities, like as a service, etc, we're not in the business of taking over your business or being in the outsourcing space. And so, our mindset is all about how do we make you better? And help you realize your vision? And I think that's why we work across a lot of different industries and a lot of different types of companies. >> Joe and Perul, really appreciate you helping share how you're helping customers through that journey, through great adoption in the cloud. Thanks for sharin' and all the updates on Slalom. >> Thank for having us! >> Yeah, thanks for havin' us. >> All right. for Corey Quinn, >> Take care. >> I'm Stu Minimann. We'll be back here with lots more coverage from AWS Summit in New York City. Thanks for watchin' the Cube. (upbeat music)

>> Welcome to the Special Cube conversation. We're here in Palo Alto, California Cube headquarters. I'm John for a host of the Cube were Mohit parents, founder and CEO of Cohesive Serial entrepreneur. Successful Distribute computing, phD, computer science. Welcome to the Cube. Thanks for having me here. So thanks for coming. You guys been very successful. You found the couple in twenty thirteen. Great traction. Great success, Great technology. What's the vision of Cohee City? >> Let me first start by describing the problem. And then I'll go under describing the vision. The problem in a nutshell, is ah what we call mass data fragmentation. It refers to the fact that everything sets in silos, whether it's the sender or whether it's the cloud All our data sets in silos in appliances. Just expect all across the whole universe. And our vision is to basically consolidate that onto one platform I The easiest way to understand our vision is to look at it. What a smartphone that in the consumer space before the smartphone came the all used to carry multiple devices, right? Phone, music, player, camera, and so on. So forth. Uh, the smartphone came. It put all of those on one platform gave us a single U I to manage it all, um, gave us the notion ofthe marketplace from where we could download maps and run on this platform and gave us machine learning. Our vision is something very similar for the world of leader in the world. That data is the most valuable resource today in the world, much more so than oil. And he had the infrastructure. Where we put that data is very fragmented. Let's look at the ladies under backups is one silo probably bought from different renders test. And there was another side of analytics is another one five chairs and object storage is another one. Our vision is is to put all of that on one platform, make it very simple. Make that platform span the data center and the cloud manager using one us bring machine learning concepts to it and at a market place from where people >> could, you know, the smart phones. A good analogy. I like that because you had a market where they made devices to make phone calls and then text messaging. Beak was like killer half of the time. But having the computer enable the whole new class of services functionality, usability and capability and that that iPhone was a seminal moment There. You see, the same thing in Tech right now with Cloud Cloud has changed again. Seeing cloud be successful. Scale is a huge thing. So functionality, new kinds of functionality and large scales with cloud computing has proven. And APS have come around that. So I gotta ask you, you know, backup has been in category that has been dominated. Public offerings dated domain, but the list is endless of great companies built great backup solutions or a K phones. And I think that's what you're getting at the phones is the backup. You guys are building new functions. I want to explain the reels, um, capabilities that's going to come out of the data because if you have data being backed up, you're touching the data. So if you built a platform for scale, it seems that you guys have talked about that product. What is the unique thinking behind it? How did you come to it? And what are some of the examples? >> Yeah, so let's start one step at a time. So, uh, even though it's a platform that can do multiple things just like the smartphone had to be a great phone to begin with. This is a great backup product to begin with. And once we've solved the back a problem for the customer, then we encouraged them to do more on this may be to file shares, baby to object storage. Maybe start using the clouds and sunset. The next thing you'LL say that. Imagine you will work on that data. So you've ingested some data using backups and you want to get some insights from that data today? What you're forced to do is you probably have to copy that data out into another side of creating one more fragment. One more copy of the data. Why not move APS to the data? But other than dated adapts. So our whole concept is that take this platform and take whatever happened. You wanted to run outside off this just running on this platform and thereby you're moving APS to the data. Not the dinner, perhaps moving their eyes. Heart. It is. Ah, is big moving abscess. Easy. So and that's what the hell is this about On That's the platform. That's the capability of the platform. It's a distributed platform. Let's you're on APS close to where that it is. That's the underlying a lot of >> people say I remember we're going back a couple years now talking about Cloud or once I want to be like Google. I want to be like Amazon because they were offering at large scale using open source software. You can. You were lead engineer on Google file system, so you know a lot about scale. But a lot of people wanted the scale and functionality of Google, but they wanted the ease of use of Apple. And I've heard you mentioned that when were before we came on. So this is actually an interesting dynamic. But not everyone's like, Oh, but they have now data scaling similar challenges that Google has one song or another's large scale. Talk about that dynamic because you're changing the game on backup did since you touching the data, you're going to make that more valuable beyond just backing up. And this the concept of moving absolute data talkabout this dynamic of scale, functionality and ease of use because if you're doing all the work with the data, why not extend that out? This is essentially what you're doing. Can you explain that? >> Yeah. I think about the problems that Google would have if they were dealing with lots and lots of fragments of data. If everything was studying in a different appliance, Uh, with the volume of data that day deal that they'LL just be going knots pulling their hair all day long, right? So they built a web scale system that was sort of like a single platform. I was fortunate to be part ofthe some of those technologies, like the Google file system. So they built that Web scale file system to make it look like make all of that look like one platform. And now that it was one platform, they could move the APP store. And we're basically trying tow do something similar to the realm ofthe second reader naps. Because we have lots and lots of data here today. It sets and silos be the backups or passed on diver filers, Object storage. We're gonna build one big platform that scales out in a Google like fashion which can be managed very simply, using one you Iike an apple like manageability. And with this concept, we become very similar to those hyper skill er's, and we bring some of the same innovations to people out there. I >> want to share a common e we were talking about before we came on camera. You were just preferred something. You said I'd like to solve one problem at a time and then move on. But what's interesting here? Competitive strategy wise, you're solving the backup problem. But why you got your hands on the data? You're actually going to re imagine the usability of that data. So you're essentially adding value to a basic function back up, putting a platform around and extending that out, perhaps to come to it. And it's kind >> of a >> land grab that's working. This is a unique It's a different way to think about, Is that right? >> So I like to say that we like the master's off one trade at a time, nor Jack of all trades, uh, and that first trade for us that we would be masters off his backups once we're happy there. Then we can go on and focus on, you know, maybe filers or object storage. And this is how we build the platform right eye. I always say that when you architect a system, you have to think about all this from day one. You can't incrementally at patches and expect the system to grow right. I sometimes draw an analogy between why Google won the war against Yahoo. Google, Tara, Phil are all as a platform there. Thought about all the use cases they'd be, you know, putting on the platform. Yeah, who just build something that was good for search. Didn't think beyond that. That's why they you know about a bunch of naps. And >> that's where they saw it and thought of >> the Google file system and then YouTube on top and Gmail on top and blah, blah, blah. No. So I was the same approach. We've talked about the problem and the problem off. The problem We want to address mastered a recommendation up front, and our system has bean architected to solve that. Even if we start by being masters of backups first, the system has been architected tto do way more than that. >> So it be safe to say that cohesive from a software core competency standpoint is distributed computing core competence or disputed systems large scale from a computer science, you know standpoint and then data. So expertise are those two is intact. >> Yes. Oh, distributed computing and distributed file systems. Those would be there to core competencies. But then again, depending on like whether it's backups or its testing, that their competences of within those domains. >> So I want to get into the private tech. First of all, thanks for saying you have responded to that. The product text. Phenomenal. You have platform can do multiple things. I want to talk about span F S on Spann Os. You have some news. You've got something share on overview of what that is and what the new news is. >> So when you're trying to control on manage of lots and lots of data, you better have a distributed file system. So we built one, and we call it Spanish Fast. The name comes from the fact that it's supposed to span nodes in the very center that's supposed to span multiple kinds of storage in the data center. It's supposed to span the data center and your multi cloud environment, their hands the names pan a fast, But since we were building it like a platform, that's not just there for your data. It also runs apse on top off this platform. Uh, the span of fast is not enough. It becomes full scale us, if you may want to call it. What? So where's it has a file system and it has the ability to run laps on the file system, and the same ability was built here. And the name's patter well, so we can store data, but we can also naps close to that >> and with multi cloud on the horizon are actually president today. A lot of people use multiple clouds, and certainly Salesforce's considered cloud you got Amazon. So especially this moment clouds of existing today in the Enterprise, the coordinated all but hybrid and and these things they're going on. Premise. It's cloud operations. This becomes an important part of the distributed environments that need to be managed. Talk about the impact of multi cloud in today's world because it's a systems thinking. You gotta think about it from day one, which is kind of today. I got on premise. I got multiple clouds out there, and some clouds or great, depending on the workload, picked the cloud for the workload. I'm a big believer in that. Your thoughts, though, on as people tried to get their arms around this and make it, you know, one environment with a lot of decoupled elements that are highly cohesive. Talk about that dynamic. >> Yeah. So Cloud is a very, um, nice entrant into the infrastructure world. It provides a lot ofthe functionality, but it doesn't quite solve that problem off massive fragmentation. When you put your dinner in the cloud, it's still fragmented. And when you're dealing with, often our customers are big. Customers are dealing with multiple clouds and the data centers, and they have dedicated people trying to move data and applications between them. That's the problem that Cohee City can actually solve very well, because we're building a platform that spans all this. Um, all of that becomes underlying infrastructure that we use. And now through us, they can easily move APS. They could easily move data. They can access the data anywhere. That's the value we been to them. We have a customer here in California, and that was spending, uh, hundred twenty thousand dollars per month. It's a new company, uh, one hundred one hundred twenty thousand dollars per month on the eight of us both after they consolidated that stuff threw us in the cloud, their ability used to seventeen thousand dollars per month. That's the kind of value we can bring. The customers >> well, the Amazon Dana. It's interesting cause you got storage and you got E C two of the compute you need compute to manage towards so against. Not just storage. That's the cost. It's it's data is driving the economics. That's where you're getting it. >> Yeah, So I think data and storage and compute go together as I'm a big fan off hyper convergence, which me, along with the rest of my team Edna tonics. And Monday it's gonna doing multiple things on the side I'm back from. And you can't do that without storage and compute both working in tandem >> so consolidating with cohesive because I'll be using cohesive, he allows the better management lower costs on Amazon. >> That's right. That's right, because we store the data efficiently on Amazon, cutting the costs, and then you can run your raps on top. You don't have to copy out the data toe, run your wraps, you can actually land on the platform and all that saves costs. >> That's a great tidbit. Notes no to the audience out there. Great to tip their pro tip. Talk about the announcement you have now have APS coming out. You got three native cohesively absence. My word. I don't know. You guys call it Think Caps is going to the Alps and then for third party application developers. So again, this kind of teases out there beyond backup story, which is platform. What of the apse, Where this come from? What? Some of the reasons why they're being built. Can you share specifics on that news? >> This goes back to our analogy to a smartphone on one of the innovations the smartphone, brother. The world was the notion of a marketplace. You could go to the marketplace and down wrap. Some of the gaps are from the vendor who built the smartphone. Some of them are from third parties. So we are. And when the first iphone came out that I had basically five straight and then now there are millions of them. So what we have seeded the system with is we have, ah, a couple ofthe third party apse for in particular one a splunk that runs on the platform with in a container. One is from a company called Menace. One is actually two laps are anti virus absent. One vendor is scented. One when is clam? Maybe, um though that third party APS But then we've built some, um, APs from cohesively itself when his app called spotlight on the security app. One is an app called Insight searches through the data when his app called Easy Scripts allows our customers to upload scraps on drawing them from Go easy. So these are the apse that I'd be exceeded the system where were also announcing an SD came in just like your smartphone has a nasty cave. The world out there can go and use that and build ups on top if he would like people out there in the world. Third parties are partners to build ups and run on this bathroom >> so moment, what's their motivation behind the app system or functionality? As the demand grows, functionalities needed. So I'll see platforms should be enabling, so I get why APS could build on platforms. But what was the motivation that around the apse now just l of evolution capabilities? What's the thoughts >> It goes back to our philosophy that if you need to do something, you shouldn't buy one more silo to do it. You should be able to extend your existing platform and then do stuff. That's what your smartphone does. Uh, basically, even you, by your smartphone, it can be a phone, and I'm number for the things. But then you extended the functionality of that by downloading maps. It's the same motivation, you know, extend the abilities of this platform. Just download maps and then extended right. >> Give the value proposition pitch for the developers out there. Why would they want to develop on? Complicity is it is a certain kind of developer. What's the makeup of the target audience? Who would build on obesity? >> So all kinds of people we expect to build on this platform. So the value for our customers, for instance, now rather than, uh, copying the data out of this platform onto one more silo and that's very expensive, they can actually build a nap that runs on this platform so that they don't have to move the data around, and it's very, very simple. That's the value for our customers. For the developers out there. Uh, it's the same value that they get when they build an app on a smart phone. Uh, they building up some cash, but out there can download that app and the APP and then pay that developer some money so they don't have to build the whole company or the whole thing. Now they can build a nap that runs on cohesive. It's really simple for them. They get a cut of whatever the customer pays, so there's value all around. It's a ven ven for everyone >> it's not. And it's good business model, too good community going to get an ecosystem developing its a classic growth growth opportunity for you guys. Congratulate. So what a business you guys have talked about a couple quarters ago Publicly, about two million to million dollars run rate. Give us the update on the business in terms of growth. Employee headcount. Key milestones. Can you share? Seok was empty, >> so you know the momentum is phenomenal. We're very flattered by the fact that despite the fact that we're a young company we've been selling for more than three years, of seventy percent of our customers are enterprise customers. The big guys with lots and lots of data. Uh, some of the biggest banks in the world now use us. Some of the biggest credit card companies in the world use us. Uh, a lot of the secret of federal agencies. You, us? Um, uh, some of the public customers I convention Hyatt uses us. Ah, big financial. Northern Trust uses us the famous. Uh uh, you know, food chain. Wendy's uses us. So those are the names I can I can mention that are actually using and benefiting from cohesive. Um, so lots of lots of great stuff. Um, we had three hundred percent year over year growth in revenue. Our head count, actually, er this week crossed one thousand people. So we spoke to our chief people. Officer. We should mention our one thousand employees in a special way. So all that great stuff is happening. >> It's like walking through the door. All the bills go office because you guys were two hundred last year. About this time >> when you get back, we are about to enter. People's a factor of five growth and about one years phenomenal had come growth. >> Well, that's massive growth. How big is this guy's a real state growing and buy more office space. >> Yeah, well, uh, they're headquartered in a building and son who's a downtown. We start, but we got it. That building about when you're back, we only had two floors were really expanded toe like five floors now and looking toe, you know, rent more. We've also expanded to other locations. Geographically, we now have an office and rally. We have ah, uh in office and cork in Ireland. We already had an office in Bangalore. We setting one up in pony. We're setting one up in Toronto, So lots and lots of expansion worldwide. Not >> really looking good as well. I mean, let's think about the economics. >> So this is the time they're being in mustard and growth. That's looking phenomenal on DH. There's a path to profitability. Um uh, it all depends on you know, our economics and what the board decides on how and when we wanna charge towards profitability, we can get there. It's looks easy, but I think it's our productive ity off our sales reps looks phenomenal. On average, productively is very high, which basically means that you know, we can get to profitability fairly quickly. If you want. >> We're going to say, very impressed with the growth and impressed that you go out on the road, talk to customers closing business. That's sign of a great CEO. Always make sure the customers are happy. >> Um, eventually, that sort of companies about a happy employees and be happy customers. Uh, and my job is to see you is to make sure what happened >> before we get in Some of the questions I have from the community. I prepare because people want knew you were coming on. I want to ask you about entrepreneurship in your journey. You've had quite the career Google image in that nutanix. And now here, >> Look at look at >> today's environment. I mean, it was a lot of talk about how entrepreneurship changed and starting a company, you know, you got a rocket ship, so you had a lot people coming on Now from the your journey you're on now. But a lot of other offers out there right now, kind of like looking transition. People say tech is bad, not good for society. Seen bad, negative press in their entrepreneurship is a great opportunity right now in tech. What's your thoughts on the current landscape and opportunities for, you know, folks out there building new things and going in solving a problem from old market and reimagining it for the new. Because a lot of new going on seeing a new sea change with cloud. And on premise, >> I would say, Um, this is probably the best time to do a company then ever in the past because technology is there to help people. Young entrepreneurs. Uh, there's plenty of money to be raised from the sea. Species are very happy to be helping. End of news a couple of pieces of caution that I wantto give to would be entrepreneurs. Uh, number one. Don't be in a hurry. Learn their hopes of doing a company first. Ah, before jumping and doing it because often I find that they burn their fingers and then they don't want to do a company again. First, go to a good company, learn the ropes of playing a company, and then do a company. That's number one number two. Uh, I would like to incorrigible and avenues to think about their ideas in the context. Off the following two thoughts one is, uh, the company needs to have a great entry point. That's how the company takes off. But then it also needs to have a bigger vision to look up to. And I often find that company's lack one or the other of these, Uh, and that's why they eventually fail or they never take off the ground. In our case, the entry point was backups, and the big vision is the consolidation off seconded and haps that I spoke about, Ah, one or the other if they're missing, it's not >> an extensive abilities key there, too. You get the beachheads real specific seconds, and then you see you point >> out of a vision. That's >> what broader beachhead without trying to take it all too fast or not knowing where to lay. That's gonna much the analogy. >> That's what I say. I beat master of one traitor, go ahead in the beachhead and then expanded the bigger >> and by the way, that's a classic proven way to do it. So, you know, just stay with what works, All right, let's get to the questions from the community. A lot of people wanted to ask your first question moment. You've a great perspective on the difference between hyper scale on enterprise worlds Is the enterprise still ten plus years behind the Giants in Tech? And how have you helped bring hyper scale thinking to the enterprise architecture? >> Um, the enterprise is, actually, surprisingly is getting closer and closer. Uh, with all the great technologies available, hyper convergence has bean. One of those technologies that has made hyper convergence combined with upscale, uh, is one of those technologies that has brought the enterprise were very close to the hyper scholars. Now they can buy products that are hyper energy that scale out in a group like fashion, and they can get some of the same benefits that the hyper scholars have enjoyed over the years, eh? So I won't say they have that far behind anymore. They're catching up, and they're catching up. Eyes >> used to be a few years ago, you could look at saying old relic, you know, modern cloud >> the and and the companies that I have found it have. I'm very flattered to say that have gonna, uh, hasten that journey. Uh, happy convergence. And he's even solving this problem of massive fragmentation. The hyper skills have kind of, you know, already solved that problem. They have massive, upscale systems that don't deliver data fragmentation. It's one platform, and you're gonna bring that value to the world through cohesive, >> great, great success. Okay, second question. There's a ton of money pouring into the data protection space again, a category that's there's a card in magic water for that. But again, you start Cummings that don't have magic watches because it's new. Why is this money pouring into space? Why now? >> Number one dealer is exploding. There's lots of lots of data. Ah, bulk off the data sets in what we call second story. It comes to it through back up straight. Your your production stuff has some production data, but eventually that data. Nobody wants to believe that they would keep it in there for at least six seven years, maybe forever. All dated, it comes to backups. The opportunity that people have seen is that they can actually now doom or with that data. It's not just dumb waiter sitting there, so it's not just data protection. It becomes more of a data management and you do data management through APS. That's what cohesion is exploding. We get the data onto a platform through backups, but then we expand into arrest of the vision and Kendra naps to extract value from the dealer right? That's why the money is coming. >> Well, you just answer the next question, which is, you know, why cohesively wind now the space is crowded, a lot of competition, So I'll just move on Ransomware, what's going on there and what's unique about Kohi City and what do you bring to the table with respect to Ransomware. >> So Ransomware is, uh, uh, something that we now live in. Its every enterprise is at risk, uh, being affected by ransomware. So what we have announced recently eating a month back, we announced our ransomware support. Uh, we can offer not just the detection, but also a number for the things we can detect Ransom where we can allow our customers toe apply fixes. When When that happens, we really allow things to be recovered once ransomware happened. So it's built into our data protection environment, right? That's how customers like it. So it adds value to the data that they already have. It's not just a dumb backup. >> And with all the third party and S t k stuff happening potential extensive bility on that core, >> that's right. Now we can have apse that can detect more round somewhere by virtue of the fact that we can support running absolutes to data. Some of those APs could be Andy dancing, perhaps help protect the data, do some custom stuff. Once said handsome, it is detected. All that becomes possible >> last question from the crowd here, the community multi cloud. Everyone's going up to the space. What is multi cloud data protection really about? And why cohesive? Isn't this just really a multi cloud vendor? Khun, do it all mean a lot of people saying they're multi cloud vendors. Y you what is multi cloud data protection all about? >> So, you know, big enterprise customers probably have a foot in every cloud, and they call it a multi cloud infrastructure. And if they want to protect the data and forced me, the data is very fragmented. So they need a backup solution for one for every cloud that's roughly multi cloudy. The production. Uh, we're cool. Here's the adds value. It's building one platform that spans your multicolored environment. So one platform can now take care ofall that those backups eso it really simplifies the job off doing backups or data protection in a multicolored environment. And that's where the Queen's devalue comes in. >> Well, congratulations. Final question for this interview. How would you summarize the state of cohesive the right now? Thousand employees growth on the customer traction side and revenue business funding. Males look good economic with a platform, certainly software margins looking very good growth. What's it all about right now? Culture value, proposition don't. >> It's kind of like a rocket ship, and we're just hanging on. But it's Ah, I think that focus is, um, when you grow this fast, uh, the challenge becomes, uh, keeping your culture intact and we tryto put a lot of effort on our culture. Our core values are cultural guidelines were fanatics about that. So we want everyone to feel that they're coming in and this is home away from home, and they treat others to make them feel it's home away from home. We're trying to build a family here, so there's a lot of emphasis on that. But at the same time, you know, we all work hard and let the company >> and the new ecosystem opportunity for you is looking really good because if he zaps takeoff, certainly the cohesively APS. And now you got third party with an S t. K. This is potentially a game changer for you as a company to a CZ Wells, you have product company. Software company makes a lot of scared, but now you're gonna be bringing developers and impact there. >> The impact, the talk, leadership impact. Uh, you know, I'm personally very fun off er you know I do these companies because I want to change the world. I won't change the way the world thinks this is the way I think. And if I can help the world think in this fashion contributed something to the world. And so that's the excitement that sort of mission is. Team is excited about that. It's just >> we got a great mind phD in computer science and two ships systems entrepreneur that thinks up new things that disrupt the status quo. And the old guard certainly track record their congratulations. Know what? Thanks for coming on The Cube. This's the Cube conversation here. Palo Alto. I'm John every year. Thanks for watching. What?

>> Live from Toronto Canada, it's The Cube, covering Global Cloud and Blockchain Summit 2018, brought to you by The Cube. >> Hello, everyone welcome back to The Cube's live coverage here in Toronto for the first Global Cloud and Blockchain Summit in conjunction with the Blockchain futurist happening this week it's run. I'm John Fourier, my cohost Dave Vellante, we're here with Cube alumni, Bradley Rotter, pioneer Blockchain investor, seasoned pro was there in the early days as an investor in hedge funds, continuing to understand the impacts of cryptocurrency, and its impact for investors, and long on many of the crypto. Made some great predictions on The Cube last time at Polycon in the Bahamas. Bradley, great to see you, welcome back. >> Thank you, good to see both of you. >> Good to have you back. >> So I want to just get this out there because you have an interesting background, you're in the cutting edge, on the front lines, but you also have a history. You were early before the hedge fund craze, as a pioneer than. >> Yeah. >> Talk about that and than how it connects to today, and see if you see some similarities, talk about that. >> I actually had begun trading commodity futures contracts when I was 15. I grew up on a farm in Iowa, which is a small state in the Midwest. >> I've heard of it. >> And I was in charge of >> Was it a test market? (laughing) >> I was in charge of hedging our one corn contract so I learned learned the mechanisms of the market. It was great experience. I traded commodities all the way through college. I got to go to West Point as undergrad. And I raced back to Chicago as soon as I could to go to the University of Chicago because that's where commodities were trading. So I'd go to night school at night at the University of Chicago and listen to Nobel laureates talk about the official market theory and during the day I was trading on the floor of the the Chicago Board of Trade and the Chicago Mercantile Exchange. Grown men yelling, kicking, screaming, shoving and spitting, it was fabulous. (laughing) >> Sounds like Blockchain today. (laughing) >> So is that what the dynamic is, obviously we've seen the revolution, certainly of capital formation, capital deployment, efficiency, liquidity all those things are happening, how does that connect today? What's your vision of today's market? Obviously lost thirty billion dollars in value over the past 24 hours as of today and we've taken a little bit of a haircut, significant haircut, since you came on The Cube, and you actually were first to predict around February, was a February? >> February, yeah. >> You kind of called the market at that time, so props to that, >> Yup. >> Hope you're on the right >> Thank you. >> side of those shorts >> Thank you. >> But what's going on? What is happening in the capital markets, liquidity, why are the prices dropping? What's the shift? So just a recap, at the time in February, you said look I'm on short term bear, on Bitcoin, and may be other crypto because all the money that's been made. the people who made it didn't think they had to pay taxes. And now they're realizing, and you were right on. You said up and up through sort of tax season it's going to be soft and then it's going to come back and it's exactly what happened. Now it's flipped again, so your thoughts? >> So my epiphany was I woke up in the middle of the night and said oh my God, I've been to this rodeo before. I was trading utility tokens twenty years ago when they were called something else, IRUs, do you remember that term? IRU was the indefeasible right to use a strand of fiber, and as the internet started kicking off people were crazy about laying bandwidth. Firms like Global Crossing we're laying cable all over the ocean floors and they laid too much cable and the cable became dark, the fiber became dark, and firms like Global Crossing, Enron, Enron went under really as a result of that miss allocation. And so it occurred to me these utility tokens now are very similar in characteristic except to produce a utility token you don't have to rent a boat and lay cable on the ocean floor in order to produce one of these utility tokens, that everybody's buying, I mean it takes literally minutes to produce a token. So in a nutshell it's too many damn tokens. It was like the peak of the internet, which we were all involved in. It occurred to me then in January of 2000 the market was demanding internet shares and the market was really good at producing internet shares, too many of them, and it went down. So I think we're in a similar situation with cryptocurrency, the Wall Street did come in, there were a hundred plus hedge funds of all shapes and sizes scrambling and buying crypto in the fall of last year. It's kind of like Napoleon's reason for attacking Russia, seemed like a good idea at the time. (laughing) And so we're now in a corrective phase but literally there's been too many tokens. There are so many tokens that we as humans can't even deal with that. >> And the outlook, what's the outlook for you? I mean, I'll see there's some systemic things going to be flushed out, but you long on certain areas? What do you what do you see as a bright light at the end of the tunnel or sort right in front of you? What's happening from a market that you're excited about? >> At a macro scale I think it's apparent that the internet deserves its own currency, of course it does and there will be an internet currency. The trick is which currency shall that be? Bitcoin was was a brilliant construct, the the inventor of Bitcoin should get a Nobel Prize, and I hope she does. (laughing) >> 'Cause Satoshi is female, everyone knows that. (laughing) >> I got that from you actually. (laughing) But it may not be Bitcoin and that's why we have to be a little sanguine here. You know, people got a little bit too optimistic, Bitcoin's going to a hundred grand, no it's going to five hundred grand. I mean, those are all red flags based on my experience of trading on the floor and investing in hedge funds. Bitcoin, I think I'm disappointed in Bitcoins adoption, you know it's still very difficult to use Bitcoin and I was hoping by now that that would be a different scenario but it really isn't. Very few people use Bitcoin in their daily lives. I do, I've been paying my son his allowance for years in Bitcoin. Son of a bitch is rich now. (laughing) >> Damn, so on terms of like the long game, you seeing the developers adopted a theory and that was classic, you know the decentralized applications. We're here at a Cloud Blockchain kind of convergence conference where developers mattered on the Cloud. You saw a great developer, stakeholders with Amazon, Cloud native, certainly there's a lot of developers trying to make things easier, faster, smarter, with crypto. >> Yup. >> So, but all at the same time it's hard for developers. Hearing things like EOS coming on, trying to get developers. So there's a race for developer adoption, this is a major factor in some of the success and price drops too. Your thoughts on, you know the impact, has that changed anything? I mean, the Ethereum at the lowest it's been all year. >> Yup. Yeah well, that was that was fairly predictable and I've talked about that at number of talks I've given. There's only one thing that all of these ICOs have had in common, they're long Ethereum. They own Ethereum, and many of those projects, even out the the few ICO projects that I've selectively been advising I begged them to do once they raised their money in Ethereum is to convert it into cash. I said you're not in the Ethereum business, you're in whatever business that you're in. Many of them ported on to that stake, again caught up in the excitement about the the potential price appreciation but they lost track of what business they were really in. They were speculating in Ethereum. Yeah, I said they might as well been speculating in Apple stock. >> They could have done better then Ethereum. >> Much better. >> Too much supply, too many damn tokens, and they're easy to make. That's the issue. >> Yeah. >> And you've got lots of people making them. When one of the first guys I met in this space was Vitalik Buterin, he was 18 at the time and I remember meeting him I thought, this is one of the smartest guys I've ever met. It was a really fun meeting. I remember when the meeting ended and I walked away I was about 35 feet away and he LinkedIn with me. Which I thought was cute. >> That's awesome, talk about what you're investing-- >> But, now there's probably a thousand Vitalik Buterin's in the space. Many of them are at this conference. >> And a lot of people have plans. >> Super smart, great ideas, and boom, token. >> And they're producing new tokens. They're all better improved, they're borrowing the best attributes of each but we've got too many damn tokens. It's hard for us humans to be able to keep track of that. It's almost like requiring a complicated new browser download for every website you went to. We just can't do that. >> Is the analog, you remember the dot com days, you referred to it earlier, there was quality, and the quality lasted, sustained, you know, the Amazon's, the eBay's, the PayPal's, etc, are there analogs in this market, in your view, can you sniff out the sort of quality? >> There are definitely analogs, I think, but I think one of the greatest metrics that we can we can look at is that utility token being utilized? Not many of them are being utilized. I was giving a talk last month, 350 people in the audience, and I said show of hands, how many people have used a utility token this year? One hand went up. I go, Ethereum? Ethereum. Will we be using utility tokens in the future? Of course we will but it's going to have to get a whole lot easier for us humans to be able to deal with them, and understand them, and not lose them, that's the big issue. This is just as much a cybersecurity play as it is a digital currency play. >> Elaborate on that, that thought, why is more cyber security playing? >> Well, I've had an extensive background in cyber security as an investor, my mantra since 9/11 has been to invest in catalyze companies that impact the security of the homeland. A wide variety of security plays but primarily, cyber security. It occurred to me that the most valuable data in the world used to be in the Pentagon. That's no longer the case. Two reasons basically, one, the data has already been stolen. (laughing) Not funny. Two, if you steal the plans for the next generation F39 Joint Strike Force fighter, good for you, there's only two buyers. (laughing) The most valuable data in the world today, as we sit here, is a Bitcoin private key, and they're coming for them. Prominent Bitcoin holders are being hunted, kidnapped, extorted, I mean it's a rather extraordinary thing. So the cybersecurity aspect of if all of our assets are going to be digitized you better damn well keep those keys secure and so that's why I've been focused on the cybersecurity aspect. Rivets, one of the ICOs that I invested in is developing software that turns on the power of the hardware TPM, trusted execution environment, that's already on your phone. It's a place to hold keys in hardware. So that becomes fundamentally important in holding your keys. >> I mean certainly we heard stories about kidnapping that private key, I mean still how do you protect that? That's a good question, that's a really interesting question. Is it like consensus, do you have multiple people involved, do you get beaten up until you hand over your private key? >> It's been happening. It's been happening. >> What about the security token versus utility tokens? A lot of tokens now, so there's yeah, too many tokens on the utility side, but now there's a surge towards security tokens, and Greg Bettinger wrote this morning that the market has changed over and the investor side's looking more and more like traditional in structures and companies, raising money. So security token has been a, I think relief for some people in the US for sure around investing in structures they understand. Is that a real dynamic or is that going to sustain itself? How do you see security tokens? >> And we heard in the panel this morning, you were in there, where they were predicting the future of the valuation of the security tokens by the end of the year doubling, tripling, what ever it was, but what are your thoughts? >> I think security tokens are going to be the next big thing, they have so many advantages to what we now regard as share certificates. My most exciting project is that I'm heavily involved in is a project called the Entanglement Institute. That's going to, in the process of issuing security infrastructure tokens, so our idea is a public-private partnership with the US government to build the first mega quantum computing center in Newport, Rhode Island. Now the private part of the public-private partnership by the issuance of tokens you have tremendous advantages to the way securities are issued now, transparency, liquidity. Infrastructure investments are not very liquid, and if they were made more liquid more people would buy them. It occurred to me it would have been a really good idea if grandpa would have invested in the Hoover Dam. Didn't have the chance. We think that there's a substantial demand of US citizens that would love to invest in our own country and would do so if it were more liquid, if it was more transparent, if the costs were less of issuing those tokens. >> More efficient, yeah. >> So you see that as a potential way to fund public infrastructure build-outs? >> It will be helpful if infrastructure is financed in the future. >> How do you see the structure on the streets, this comes up all the time, there's different answers to this. There's not like there's one, we've seen multiple but I'm putting a security token, what am i securing against, cash flow, equity, right to convert to utility tokens? So we're starting to see a variety of mechanisms, 'cause you have to investor a security outcome. >> Yeah, so as an investor, what do you look for? >> Well, I think it's almost limitless of what these smart securities, you know can be capable of, for example one of the things that were that we're talking with various parts of the government is thinking about the tax credit. The tax credit that have been talked about at the Trump administration, that could be really changed on its head if you were able to use smart securities, if you will. Who says that the tax credit for a certain project has to be the same as all other projects? The president has promised a 1.5 trillion dollar infrastructure investment program and so far he's only 1.5 trillion away from the goal. It hasn't started yet. Wilbur Ross when, in the transition team, I had seen the white paper that he had written, was suggesting an 82% tax credit for infrastructure investment. I'm going 82%, oh my God, I've never. It's an unfathomable number. If it were 82% it would be the strongest fiscal stimulus of your lifetime and it's a crazy number, it's too big. And then I started thinking about it, maybe an 82% tax credit is warranted for a critical infrastructure as important as quantum computing or cyber security. >> Cyber security. >> Exactly, very good point, and maybe the tax credit is 15% for another bridge over the Mississippi River. We already got those. So a smart infrastructure token would allow the Larry Kudlow to turn the dial and allow economic incentive to differ based on the importance of the project. >> The value of the project. >> That is a big idea. >> That is a big idea. >> That is what we're working on. >> That is a big idea, that is a smart contract, smart securities that have allocations, and efficiencies, and incentives that aren't perverse or generic. >> It aligns with the value of the society he needs, right. Talk about quantum computing more, the potential, why quantum, what attracted you to quantum? What do you see as the future of quantum computing? >> You know, you don't you don't have to own very much Bitcoin before what wakes you up in the middle of the night is quantum computing. It's a hundred million times faster than computing as we know it today. The reason that I'm involved in this project, I believe it's a matter of national security that we form a national initiative to gain quantum supremacy, or I call it data supremacy. And right now we're lagging, the Chinese have focused on this acutely and are actually ahead, I believe of the United States. And it's going to take a national initiative, it's going to take a Manhattan Project, and that's that's really what Entanglement Institute is, is a current day Manhattan Project partnering with government and three-letter agencies, private industry, we have to hunt as a pack and focus on this or we're going to be left behind. >> And that's where that's based out of. >> Newport, Rhode Island. >> And so you got some DC presence in there too? >> Yes lots of DC presence, this is being called Quantum summer in Washington DC. Many are crediting the Entanglement Institute for that because they've been up and down the halls of Congress and DOD and other-- >> Love to introduce you to Bob Picciano, Cube alumni who heads up quantum computing for IBM, would be a great connection. They're doing trying to work their, great chips to building, open that up. Bradley thanks for coming on and sharing your perspective. Always great to see you, impeccable vision, you've got a great vision. I love the big ideas, smart securities, it's coming, that is, I think very clear. >> Thank you for sharing. >> Thank you. The Cube coverage here live in Toronto. The Cube, I'm John Furrier, Dave Vellante, more live coverage, day one of three days of wall-to-wall coverage of the Blockchain futurist conference. This is the first global Cloud Blockchain Summit here kicking off the whole week. Stay with us for more after this short break.

>> Live, from Washington DC, it's theCube, covering the AWS Public Sector Summit 2018. Brought to you by Amazon Web Services, and its ecosystem partners. (techno music) >> Welcome back everyone it's theCube's exclusive coverage here, day two of the Amazon Web Sources public sector summit. This is the public sector across the globe. This is their reinvent, this is their big event. I'm John Furrier, Stu Miniman, and also David Vellante's been here doing interviews. Our next guest is, we got Doug Van Dyke, he's the director of U.S. Federal Civilian and Non Profit Sectors of the group, welcome to theCube, good to see you. >> John, thank you very much for having me. >> So you've been in the federal, kind of game, and public sector for a while. You've known, worked with Theresa, at Microsoft before she came to Reinvent. >> 15 years now. >> How is she doing? >> She's doing great, we saw her on main stage yesterday. Force of nature, love working with her, love working for her. This is, like you were saying, this is our re-invent here in D.C. and 14,000 plus, 15,000 registrations, she's on the top of her game. >> What I'm really impressed with her and your team as well, is the focus on growth, but innovation, right? it's not just about, knock down the numbers and compete. Certainly you're competing against people who are playing all kinds of tricks. You got Oracle out there, you got IBM, we've beaten at the CIA. It's a street battle out there in this area in D.C. You guys are innovative, in that you're doing stuff with non-profits, you got mission driven, you're doing the educate stuff, so it's not just a one trick pony here. Take us through some of the where you guys heads are at now, because you're successful, everyone's watching you, you're not small anymore. What's the story? >> So, I think the differentiator for us is our focus on the customers. You know, we've got a great innovation story at the Department of Veterans Affairs with vets.gov. So five years ago if a veteran went out to get the services that the government was going to provide them, they've have to pick from 200 websites. It just wasn't to navigate through 200 websites. So, the innovation group at Veteran's Affairs, the digital services team, figured out, let's pull this all together under a single portal with vets.gov. It's running on AWS, and now veterans have a single interface into all the services they want. >> Doug, one of the things I've been impressed, my first year coming to this. I've been to many other AWS shows, but you've got all these kind of overlapping communities. Of course, the federal government, plus state and local, education. You've got this civilian agencies, so give us a little bit of flavor about that experience here at the show. What trends your hearing from those customers. >> So what's great for me is I've been here almost six and a half years, and I've seen the evolution. And you know, there were the early customers who were just the pioneers like Tom Soderstrom, from JPL, who was on main stage. And then we saw the next wave where there were programs that needed a course correction, like Center for Medicare Medicaid with Healthcare.gov. Where Amazon Web Services came in, took over, helped them with the MarketPlace, you know, get that going. And now we're doing some great innovative things at CMS, aggregating data from all 50 states, about 75 terabytes, so they can do research on fraud, waste, and abuse that they couldn't do before. So we're helping our customers innovate on the cloud, and in the cloud, and it's been a great opportunity. >> Oh my God, I had the pleasure of interviewing Tom Soderstrom two years ago. >> Okay. >> Everybody gets real excited when you talk about space. It's easy to talk about innovation there, but you know, talk about innovation throughout the customers, because some people will look at it, and be like, oh come on, government and their bureaucracy, and they're behind. What kind of innovation are you hearing from your customers? >> So there's an exciting with Department of Energy. They, you know there's a limited amount of resources that you have on premise. Well, they're doing research on the large Hadron Collider in Cern, Switzerland. And they needed to double the amount of capacity that they had on premise. So, went to the AWS cloud, fired up 50,000 cores, brought the data down, and they could do research on it. And so, we're making things possible that couldn't be done previously. >> What are some of the examples that government entities and organizations are doing to create innovation in the private sector? Cause the private sector's been the leader to the public sector, and know you're seeing people starting to integrate it. I mean, half the people behind us, that are exhibiting here, are from the commercial side doing business in the public sector. And public sector doing, enabling action in the private sector. Talk about that dynamic, cause it's not just public sector. >> Right. >> Can you just share your? >> These public, private. Great example with NOAA, the National Oceanic Atmospheric Administration. They have a new program called NEXRAD. It's the next generation of doppler radar. They have 160 stations across the world, collecting moisture, air pressure, all of the indicators that help predict the weather. They partner with us at AWS to put this data out, and through our open data program. And then organizations like the Weather Bug can grab that information, government information, and use it to build the application that you have on your I-Phone that predicts the weather. So you know whether to bring an umbrella to work tomorrow. >> So you're enabling the data from, or stuff from the public, for private, entrepreneurial activity? >> Absolutely. >> Talk about the non-profits. What's going on there? Obviously, we heard som stuff on stage with Teresa. The work she's showcasing, a lot of the non-profit. A lot of mission driven entrepreneurships happening. Here in D.C, it's almost a Silicon Valley like dynamic, where stuff that was never funded before is getting funded because they can do Cloud. They can stand it up pretty quickly and get it going. So, you're seeing kind of a resurgence of mission driven entrepreneurships. What is the nonprofit piece of it look now for AWS? How do you talk about that? >> Sure. Well again, one of the areas that I'm really passionate about being here, and being one of the people who helped start our nonprofit vertical inside of AWS, we now have over 12, I'm sorry, 22,000 nonprofits using AWS to keep going. And the mission of our nonprofit vertical is just to make sure that no nonprofit would ever fail for lack of infrastructure. So we partnered with Tech Soup, which is an organization that helps vet and coordinate our Cloud credits. So nonprofits, small nonprofit organizations can go out through Tech Soup, get access to credits, so they don't have to worry about their infrastructure. And you know we.. >> Free credits? >> Those credits, with the Tech Soup membership, they get those, yeah, and using the word credit, it's more like a grant of AWS cloud. >> You guys are enabling almost grants. >> Yes, cloud grants. Not cash grants, but cloud grants. >> Yeah, yeah great. So, how is that converting for you, in your mind? Can you share some examples of some nonprofits that are successful? >> Sure. A great presentation, and I think it was your last interview. A game changer. Where these smaller nonprofits can have a really large impact. And, but then we're also working with some of the larger nonprofits too. The American Heart Association, that built their precision medicine platform to match genotype, phenotype information, so we can further cardiovascular research. They have this great mission statement, they want to reduce cardiovascular disease by 20 percent by 2020. And we're going to help them do that. >> You guys are doing a great job, I got to say. It's been fun to watch, and now, we've been covering you guys for the past two years now, here at the event. A lot more coming on, in D.C. The CIA went in a few years ago. Certainly a shot heard around the cloud. That's been well documented. The Department of Defense looking good off these certain indicators. But, what's going on in the trends in the civilian agencies? Can you take a minute to give an update on that? >> Yeah, so I started earlier saying I've seen the full spectrum. I saw the very beginning, and then I've seen all the way to the end. Where, I think it was three years ago at this event, I talked to Joe Piva, who is the former CIO for the Department of Commerce ITA, the International Trade Association. He had data center contracts coming up for renewal. And he made a really brave decision to cancel those contracts. So he had 18 months to migrate the entire infrastructure for ITA over on to AWS. And you know, there's nothing like an impending date to move. So, we've got agencies that are going all in on AWS, and I think that's just a sign of the times. >> Data centers, I mean anyone who were startup nine years into it, we've never had a data center. I think most startups don't.. >> Born in the cloud. >> Born in the cloud. Thanks so much Dave, for coming on. Appreciate the time. Congratulations on your success. AWS public sector doing great, global public sector. You guys are doing great. Building nations, we had Baharain on as well. Good luck, and the ecosystems looks good. You guys did a good job. So, congratulations. >> John, Stu, thank you very much for having me here today. >> Live coverage here, we are in Washington D.C. For Cube. Coverage of AWS Public Sector Summit. We'll be back with more. Stay with us, we've got some more interviews after this short break. (techno music)