>>from around the globe. It's the Cube presenting enterprise. Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Hello, everyone, and welcome to our continuing Siri's covering data automation brought to you by Io Tahoe. Today we're gonna look at how to ensure enterprise resilience for hybrid and multi cloud. Let's welcome in age. Eva Hora, who is the CEO of Iota A J. Always good to see you again. Thanks for coming on. >>Great to be back. David Pleasure. >>And he's joined by Fozzy Coons, who is a global principal architect for financial services. The vertical of financial services. That red hat. He's got deep experiences in that sector. Welcome, Fozzie. Good to see you. >>Thank you very much. Happy to be here. >>Fancy. Let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and and how it works. >>Sure, yes. So the hybrid cloud is a 90 architecture that incorporates some degree off workload, possibility, orchestration and management across multiple clouds. Those clouds could be private cloud or public cloud or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand. Allocation of resources across clouds and separate clouds can become hydrate when they're similarly >>interconnected. And >>it is that interconnectivity that allows the workloads workers to be moved and how management can be unified in off the street. You can work and how well you have. These interconnections has a direct impact on how well your hybrid cloud will work. >>Okay, so we'll fancy staying with you for a minute. So in the early days of Cloud that turned private Cloud was thrown a lot around a lot, but often just meant virtualization of an on PREM system and a network connection to the public cloud. Let's bring it forward. What, in your view, does a modern hybrid cloud architecture look like? >>Sure. So for modern public clouds, we see that, um, teams organizations need to focus on the portability off applications across clouds. That's very important, right? And when organizations build applications, they need to build and deploy these applications as small collections off independently, loosely coupled services, and then have those things run on the same operating system which means, in other words, running it on Lenox everywhere and building cloud native applications and being able to manage and orchestrate thes applications with platforms like KUBERNETES or read it open shit, for example. >>Okay, so that Z, that's definitely different from building a monolithic application that's fossilized and and doesn't move. So what are the challenges for customers, you know, to get to that modern cloud? Aziz, you've just described it. Is it skill sets? Is that the ability to leverage things like containers? What's your view there? >>So, I mean, from what we've seen around around the industry, especially around financial services, where I spent most of my time, we see that the first thing that we see is management right now because you have all these clouds and all these applications, you have a massive array off connections off interconnections. You also have massive array off integrations, possibility and resource allocations as well, and then orchestrating all those different moving pieces. Things like storage networks and things like those are really difficult to manage, right? That's one. What s O Management is the first challenge. The second one is workload, placement, placement. Where do you place this? How do you place this cloud? Native applications. Do you or do you keep on site on Prem? And what do you put in the cloud? That is the the the other challenge. The major one. The third one is security. Security now becomes the key challenge and concern for most customers. And we could talk about how hundreds? Yeah, >>we're definitely gonna dig into that. Let's bring a J into the conversation. A J. You know, you and I have talked about this in the past. One of the big problems that virtually every companies face is data fragmentation. Um, talk a little bit about how I owe Tahoe unifies data across both traditional systems legacy systems. And it connects to these modern I t environments. >>Yeah, sure, Dave. I mean, fancy just nailed it. There used to be about data of the volume of data on the different types of data. But as applications become or connected and interconnected at the location of that data really matters how we serve that data up to those those app. So working with red hat in our partnership with Red Hat being able Thio, inject our data Discovery machine learning into these multiple different locations. Would it be in AWS on IBM Cloud or A D. C p R. On Prem being able thio Automate that discovery? I'm pulling that. That single view of where is all my data then allows the CEO to manage cast that can do things like one. I keep the data where it is on premise or in my Oracle Cloud or in my IBM cloud on Connect. The application that needs to feed off that data on the way in which you do that is machine learning. That learns over time is it recognizes different types of data, applies policies to declassify that data. Andi and brings it all together with automation. >>Right? And that's one of the big themes and we've talked about this on earlier episodes. Is really simplification really abstracting a lot of that heavy lifting away so we can focus on things A. J A. Z. You just mentioned e nifaz e. One of the big challenges that, of course, we all talk about his governance across thes disparity data sets. I'm curious as your thoughts. How does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations, which, of course, are are particularly acute within financial services. >>Oh, yeah, Yes. So for banks and the payment providers, like you've just mentioned their insurers and many other financial services firms, Um, you know, they have to adhere Thio standards such as a PC. I. D. S s in Europe. You've got the G g d p g d p r, which requires strange and tracking, reporting documentation. And you know, for them to to remain in compliance and the way we recommend our customers to address these challenges is by having an automation strategy. Right. And that type of strategy can help you to improve the security on compliance off the organization and reduce the risk after the business. Right. And we help organizations build security and compliance from the start without consulting services residencies. We also offer courses that help customers to understand how to address some of these challenges. And that's also we help organizations build security into their applications without open sources. Mueller, where, um, middle offerings and even using a platform like open shift because it allows you to run legacy applications and also continue rights applications in a unified platform right And also that provides you with, you know, with the automation and the truly that you need to continuously monitor, manage and automate the systems for security and compliance >>purposes. Hey, >>Jay, anything. Any color you could add to this conversation? >>Yeah, I'm pleased. Badly brought up Open shift. I mean, we're using open shift to be able. Thio, take that security application of controls to to the data level. It's all about context. So, understanding what data is there being able to assess it to say who should have access to it. Which application permission should be applied to it. Um, that za great combination of Red Hat tonight. Tahoe. >>But what about multi Cloud? Doesn't that complicate the situation even even further? Maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi >>cloud a swell. Yeah, sure. >>Yeah. So the right automation solution, you know, can be the difference between, you know, cultivating an automated enterprise or automation caress. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So that means have an automation solution that provides that provides, um, you know, promotes I t availability and reliability with your platform so that you can provide, you know, enterprise great support, including security and testing, integration and clear roadmaps. The second thing is vendor interoperability interoperability in that you are going to be integrating multiple clouds. So you're going to need a solution that can connect to multiple clouds. Simples lee, right? And with that comes the challenge off maintain ability. So you you you're going to need to look into a automation Ah, solution that that is easy to learn or has an easy learning curve. And then the fourth idea that we tell our customers is scalability in the in the hybrid cloud space scale is >>is >>a big, big deal here, and you need a to deploy an automation solution that can span across the whole enterprise in a constituent, consistent manner, right? And then also, that allows you finally to, uh, integrate the multiple data centers that you have, >>So A J I mean, this is a complicated situation, for if a customer has toe, make sure things work on AWS or azure or Google. Uh, they're gonna spend all their time doing that, huh? What can you add really? To simplify that that multi cloud and hybrid cloud equation? >>Yeah. I could give a few customer examples here Warming a manufacturer that we've worked with to drive that simplification Onda riel bonuses for them is has been a reduction cost. We worked with them late last year to bring the cost bend down by $10 million in 2021 so they could hit that reduced budget. Andre, What we brought to that was the ability thio deploy using open shift templates into their different environments. Where there is on premise on bond or in as you mentioned, a W s. They had G cps well, for their marketing team on a cross, those different platforms being out Thio use a template, use pre built scripts to get up and running in catalog and discover that data within minutes. It takes away the legacy of having teams of people having Thio to jump on workshop cause and I know we're all on a lot of teens. The zoom cause, um, in these current times, they just sent me is in in of hours in the day Thio manually perform all of this. So yeah, working with red hat applying machine learning into those templates those little recipes that we can put that automation toe work, regardless of which location the data is in allows us thio pull that unified view together. Right? >>Thank you, Fozzie. I wanna come back to you. So the early days of cloud, you're in the big apple, you know, financial services. Really well. Cloud was like an evil word within financial services, and obviously that's changed. It's evolved. We talked about the pandemic, has even accelerated that, Um And when you really, you know, dug into it when you talk to customers about their experiences with security in the cloud it was it was not that it wasn't good. It was great, whatever. But it was different. And there's always this issue of skill, lack of skills and multiple tools suck up teams, they're really overburdened. But in the cloud requires new thinking. You've got the shared responsibility model you've got obviously have specific corporate requirements and compliance. So this is even more complicated when you introduce multiple clouds. So what are the differences that you can share from your experience is running on a sort of either on Prem or on a mono cloud, um, or, you know, and versus across clouds. What? What? What do you suggest there? >>Yeah, you know, because of these complexities that you have explained here, Miss Configurations and the inadequate change control the top security threats. So human error is what we want to avoid because is, you know, as your clouds grow with complexity and you put humans in the mix, then the rate off eras is going to increase, and that is going to exposure to security threat. So this is where automation comes in because automation will streamline and increase the consistency off your infrastructure management. Also application development and even security operations to improve in your protection, compliance and change control. So you want to consistently configure resources according to a pre approved um, you know, pre approved policies and you want to proactively maintain a to them in a repeatable fashion over the whole life cycle. And then you also want to rapid the identified system that require patches and and reconfiguration and automate that process off patching and reconfiguring so that you don't have humans doing this type of thing, right? And you want to be able to easily apply patches and change assistant settings. According Thio, Pre defined, based on like explained before, you know, with the pre approved policies and also you want is off auditing and troubleshooting, right? And from a rate of perspective, we provide tools that enable you to do this. We have, for example, a tool called danceable that enables you to automate data center operations and security and also deployment of applications and also obvious shit yourself, you know, automates most of these things and obstruct the human beings from putting their fingers on, causing, uh, potentially introducing errors right now in looking into the new world off multiple clouds and so forth. The difference is that we're seeing here between running a single cloud or on prem is three main areas which is control security and compliance. Right control here it means if your on premise or you have one cloud, um, you know, in most cases you have control over your data and your applications, especially if you're on Prem. However, if you're in the public cloud, there is a difference there. The ownership, it is still yours. But your resources are running on somebody else's or the public clouds. You know, e w s and so forth infrastructure. So people that are going to do this need to really especially banks and governments need to be aware off the regulatory constraints off running, uh, those applications in the public cloud. And we also help customers regionalize some of these choices and also on security. You will see that if you're running on premises or in a single cloud, you have more control, especially if you're on Prem. You can control this sensitive information that you have, however, in the cloud. That's a different situation, especially from personal information of employees and things like that. You need to be really careful off that. And also again, we help you rationalize some of those choices. And then the last one is compliant. Aziz. Well, you see that if you're running on Prem or a single cloud, um, regulations come into play again, right? And if you're running a problem, you have control over that. You can document everything you have access to everything that you need. But if you're gonna go to the public cloud again, you need to think about that. We have automation, and we have standards that can help you, uh, you know, address some of these challenges for security and compliance. >>So that's really strong insights, Potsie. I mean, first of all, answerable has a lot of market momentum. Red hats in a really good job with that acquisition, your point about repeatability is critical because you can't scale otherwise. And then that idea you're you're putting forth about control, security compliance It's so true is I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe a W s is gonna physically secure the, you know, s three, but in the bucket. But we saw so many Miss configurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So this all sounds great. A j. You're sharp, you know, financial background. What about the economics? >>You >>know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. E especially when you think about the work from home pivot and and all the areas that they had toe the holes that they had to fill their, whether it was laptops, you know, new security models, etcetera. So how do organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs so I could, you know, pay it forward or there's a There's a risk reduction angle. What can you share >>their? Yeah. I mean, the perspective I'd like to give here is, um, not being multi cloud is multi copies of an application or data. When I think about 20 years, a lot of the work in financial services I was looking at with managing copies of data that we're feeding different pipelines, different applications. Now what we're saying I talk a lot of the work that we're doing is reducing the number of copies of that data so that if I've got a product lifecycle management set of data, if I'm a manufacturer, I'm just gonna keep that in one location. But across my different clouds, I'm gonna have best of breed applications developed in house third parties in collaboration with my supply chain connecting securely to that. That single version of the truth. What I'm not going to do is to copy that data. So ah, lot of what we're seeing now is that interconnectivity using applications built on kubernetes. Um, that decoupled from the data source that allows us to reduce those copies of data within that you're gaining from the security capability and resilience because you're not leaving yourself open to those multiple copies of data on with that. Couldn't come. Cost, cost of storage on duh cost of compute. So what we're seeing is using multi cloud to leverage the best of what each cloud platform has to offer That goes all the way to Snowflake and Hiroko on Cloud manage databases, too. >>Well, and the people cost to a swell when you think about yes, the copy creep. But then you know when something goes wrong, a human has to come in and figured out um, you brought up snowflake, get this vision of the data cloud, which is, you know, data data. I think this we're gonna be rethinking a j, uh, data architectures in the coming decade where data stays where it belongs. It's distributed, and you're providing access. Like you said, you're separating the data from the applications applications as we talked about with Fozzie. Much more portable. So it Z really the last 10 years will be different than the next 10 years. A. >>J Definitely. I think the people cast election is used. Gone are the days where you needed thio have a dozen people governing managing black policies to data. Ah, lot of that repetitive work. Those tests can be in power automated. We've seen examples in insurance were reduced teams of 15 people working in the the back office China apply security controls compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDP are in CCP a last year, very much the economic effect of reduce headcounts on on enterprises of running lean looking to reduce that cost. This year, we can see that already some of the more proactive cos they're looking at initiatives such as net zero emissions how they use data toe under understand how cape how they can become more have a better social impact. Um, and using data to drive that, and that's across all of their operations and supply chain. So those regulatory compliance issues that may have been external we see similar patterns emerging for internal initiatives that benefiting the environment, social impact and and, of course, course, >>great perspectives. Yeah, Jeff Hammer, Bucker once famously said, The best minds of my generation are trying to get people to click on ads and a J. Those examples that you just gave of, you know, social good and moving. Uh, things forward are really critical. And I think that's where Data is gonna have the biggest societal impact. Okay, guys, great conversation. Thanks so much for coming on the program. Really appreciate your time. Keep it right there from, or insight and conversation around, creating a resilient digital business model. You're watching the >>Cube digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data Lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated, sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands In terms of digital resilience, Sign up for a minimal cost commitment. Free data Health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer Now >>Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iot, Tahoe and Shirish County up in. Who's the vice president and head of U. S. Sales at happiest Minds? Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Trust you guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. >>A former in 2011 Happiest Mind is a born digital born a child company. The reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, Our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 i t services company in the great places to work serving hour glass to ratings off 41 against the rating off. Five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you said you had up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What >>do you what? Your >>day to day focus with customers and partners. What you focused >>on? Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds, you know? Why do you guys choose toe work closely together? >>Very good question. Um, we see Hyo Tahoe on happiest minds as a great mutual fit. A Suresh has said, uh, happiest minds are very agile organization um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. Uh, we're using machine learning algorithms to make data discovery data cataloging, understanding, data done. See, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility that happiest minds have that that's a really nice combination work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said, are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera on. Then finally, I think they're both Challenger brands on happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us at Ideo Tahoe to >>great thank you for that. So Russia, let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see, and maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic, times when you say Dave, customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organisation's trying to adopt onto the digital technologies. Right there has bean lot off data which has been to manage by these customers on There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology, right where we bring in the data. Complaints as a service were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business continuity processes from day one, where we were ableto deliver our services without any interruption to the services. What we were delivered to our customers So that is where the digital resilience with business community process enabled was very helpful for us. Toe enable our customers continue their business without any interruptions during pandemics. >>So I mean, some of the challenges that customers tell me they obviously they had to figure out how to get laptops to remote workers and that that whole remote work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, But it sounds like you've got a digital business. Means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on that, for the first step is to identify the critical data. Right. So we this is a six step process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on see how critical their data is, then we help the customers to strategies that right. The most important thing is to identify the most important critical herself. Data being the most critical assert for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them >>at >>all levels in the organization. That is a P for people to understand the importance off the digital ourselves and then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and a holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time, and finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment, we do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, so this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards their digital journey on. They have to face all these as part off the evolving environment on digital journey. And that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance when when your digital business, you're, as you say, you're a data business, so that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data soldiers. It could be on data basis, or it could be even on the data legs. Or it could be a no even on compromise all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. On finally, we also bringing the automated data governance where we can manage the sensory data policies on their later relationships in terms off mapping on manage their business roots on we drive reputations toe Also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. I'm gonna be great if you had an example is well, but maybe you could pick it up from there, >>John. I mean, at a high level, assertions are clearly articulated. Really? Um, Hyoty, who delivers business agility. So that's by, um accelerating the time to operationalize data, automating, putting in place controls and actually putting helping put in place digital resilience. I mean way if we step back a little bit in time, um, traditional resilience in relation to data often met manually, making multiple copies of the same data. So you have a d b A. They would copy the data to various different places, and then business users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. ONDA course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is. And I realized that expression. They used David the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a p I s on. So you don't have the same need thio to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate and that's really where I attack comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, discovering what's dubica? What's redundant? Uh, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates. With our tire, you could do it really very quickly on you can have tangible results within weeks and months on Ben, you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then, once you've done there. Your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls. Um, on you've got a drug toward the business outcomes. Uh, and it's doing those three things together that really deliver for the customer. >>Thank you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome. And we talked to a number of customers in the Cube, and the conclusion is, it's really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed today. >>Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check. Um, this is a is a 2 to 3 week process, uh, to really quickly start to understand on deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data. Onda. We can very rapidly demonstrate how they discovery those catalog e on understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, And so what we tend to find is that we can very quickly, as I say in the matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on then how they can scale that up, take it into production on, then really understand their data state? Better on build. Um, Brasiliense into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys, great conversation. Thanks so much for coming on the program. Best of luck to you and the partnership Be well, >>Thank you, David Suresh. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban are ongoing Siris on data automation without >>Tahoe, digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands in terms of digital resilience. Sign up for our minimal cost commitment. Free data health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer. Now. >>Okay, now we're >>gonna go into the demo. We want to get a better understanding of how you can leverage open shift. And I owe Tahoe to facilitate faster application deployment. Let me pass the mic to Sabetta. Take it away. >>Uh, thanks, Dave. Happy to be here again, Guys, uh, they've mentioned names to be the Davis. I'm the enterprise account executive here. Toyota ho eso Today we just wanted to give you guys a general overview of how we're using open shift. Yeah. Hey, I'm Noah Iota host data operations engineer, working with open ship. And I've been learning the Internets of open shift for, like, the past few months, and I'm here to share. What a plan. Okay, so So before we begin, I'm sure everybody wants to know. Noel, what are the benefits of using open shift. Well, there's five that I can think of a faster time, the operation simplicity, automation control and digital resilience. Okay, so that that's really interesting, because there's an exact same benefits that we had a Tahoe delivered to our customers. But let's start with faster time the operation by running iota. Who on open shift? Is it faster than, let's say, using kubernetes and other platforms >>are >>objective iota. Who is to be accessible across multiple cloud platforms, right? And so by hosting our application and containers were able to achieve this. So to answer your question, it's faster to create and use your application images using container tools like kubernetes with open shift as compared to, like kubernetes with docker cry over container D. Okay, so we got a bit technical there. Can you explain that in a bit more detail? Yeah, there's a bit of vocabulary involved, uh, so basically, containers are used in developing things like databases, Web servers or applications such as I have top. What's great about containers is that they split the workload so developers can select the libraries without breaking anything. And since Hammond's can update the host without interrupting the programmers. Uh, now, open shift works hand in hand with kubernetes to provide a way to build those containers for applications. Okay, got It s basically containers make life easier for developers and system happens. How does open shift differ from other platforms? Well, this kind of leads into the second benefit I want to talk about, which is simplicity. Basically, there's a lot of steps involved with when using kubernetes with docker. But open shift simplifies this with their source to image process that takes the source code and turns it into a container image. But that's not all. Open shift has a lot of automation and features that simplify working with containers, an important one being its Web console. Here. I've set up a light version of open ship called Code Ready Containers, and I was able to set up her application right from the Web console. And I was able to set up this entire thing in Windows, Mac and Lennox. So its environment agnostic in that sense. Okay, so I think I've seen the top left that this is a developers view. What would a systems admin view look like? It's a good question. So here's the administrator view and this kind of ties into the benefit of control. Um, this view gives insights into each one of the applications and containers that are running, and you could make changes without affecting deployment. Andi can also, within this view, set up each layer of security, and there's multiple that you can prop up. But I haven't fully messed around with it because with my luck, I'd probably locked myself out. So that seems pretty secure. Is there a single point security such as you use a log in? Or are there multiple layers of security? Yeah, there are multiple layers of security. There's your user login security groups and general role based access controls. Um, but there's also a ton of layers of security surrounding like the containers themselves. But for the sake of time, I won't get too far into it. Okay, eso you mentioned simplicity In time. The operation is being two of the benefits. You also briefly mention automation. And as you know, automation is the backbone of our platform here, Toyota Ho. So that's certainly grabbed my attention. Can you go a bit more in depth in terms of automation? Open shift provides extensive automation that speeds up that time the operation. Right. So the latest versions of open should come with a built in cryo container engine, which basically means that you get to skip that container engine insulation step and you don't have to, like, log into each individual container host and configure networking, configure registry servers, storage, etcetera. So I'd say, uh, it automates the more boring kind of tedious process is Okay, so I see the iota ho template there. What does it allow me to do? Um, in terms of automation in application development. So we've created an open shift template which contains our application. This allows developers thio instantly, like set up our product within that template. So, Noah Last question. Speaking of vocabulary, you mentioned earlier digital resilience of the term we're hearing, especially in the banking and finance world. Um, it seems from what you described, industries like banking and finance would be more resilient using open shift, Correct. Yeah, In terms of digital resilience, open shift will give you better control over the consumption of resource is each container is using. In addition, the benefit of containers is that, like I mentioned earlier since Hammond's can troubleshoot servers about bringing down the application and if the application does go down is easy to bring it back up using templates and, like the other automation features that open ship provides. Okay, so thanks so much. Know us? So any final thoughts you want to share? Yeah. I just want to give a quick recap with, like, the five benefits that you gained by using open shift. Uh, the five are timeto operation automation, control, security and simplicity. You could deploy applications faster. You could simplify the workload you could automate. A lot of the otherwise tedious processes can maintain full control over your workflow. And you could assert digital resilience within your environment. Guys, >>Thanks for that. Appreciate the demo. Um, I wonder you guys have been talking about the combination of a Iot Tahoe and red hat. Can you tie that in subito Digital resilience >>Specifically? Yeah, sure, Dave eso when we speak to the benefits of security controls in terms of digital resilience at Io Tahoe, we automated detection and apply controls at the data level, so this would provide for more enhanced security. >>Okay, But so if you were trying to do all these things manually. I mean, what what does that do? How much time can I compress? What's the time to value? >>So with our latest versions, Biota we're taking advantage of faster deployment time associated with container ization and kubernetes. So this kind of speeds up the time it takes for customers. Start using our software as they be ableto quickly spin up io towel on their own on premise environment are otherwise in their own cloud environment, like including aws. Assure or call GP on IBM Cloud a quick start templates allow flexibility deploy into multi cloud environments all just using, like, a few clicks. Okay, so so now just quickly add So what we've done iota, Who here is We've really moved our customers away from the whole idea of needing a team of engineers to apply controls to data as compared to other manually driven work flows. Eso with templates, automation, previous policies and data controls. One person can be fully operational within a few hours and achieve results straight out of the box on any cloud. >>Yeah, we've been talking about this theme of abstracting the complexity. That's really what we're seeing is a major trend in in this coming decade. Okay, great. Thanks, Sabina. Noah, How could people get more information or if they have any follow up questions? Where should they go? >>Yeah, sure. They've. I mean, if you guys are interested in learning more, you know, reach out to us at info at iata ho dot com to speak with one of our sales engineers. I mean, we love to hear from you, so book a meeting as soon as you can. All >>right. Thanks, guys. Keep it right there from or cube content with.

>>from around the globe. It's the Cube presenting enterprise, Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iota Ho and Shirish County. Up in Who's the vice president and head of U. S. Sales at happiest Minds. Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Stretch. You guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. A former in 2011 Happiest minds Up Born digital born a child company. >>The >>reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 I t services company in the great places to work serving hour glass to ratings off 4.1 against the rating off five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values, right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you have you head up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What do you what's your day to day focus with customers and partners? What you focused on? >>Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds. You know, why do you guys choose toe work closely together? >>Very good question. Um, we see Io Tahoe on Happiest minds as a great mutual fit. A Suresh has said happiest minds are very agile organization. Um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. We're using machine learning algorithms to make data discovery data cataloging, understanding, data, redundancy, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility, the happiest minds have that. That's a really nice combination. Work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera, uh, on. Then finally, I think that both challenger brands Andi happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us that I have tied to its >>great thank you for that. So Russia, Let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see. And maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic times when you see Dave customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organizations trying to adopt onto the digital technologies right there has bean lot off data which has been to managed by these customers on. There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology fight the where we're bringing the data complaints as a service, we were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business community processes from day one, where we were ableto deliver our services without any interruption to the services what we were delivering to our customers. >>So >>that is where the digital resilience with business community process enabled was very helpful for us who enable our customers continue there business without any interruptions during pandemics. >>So, I mean, some of the challenges that that customers tell me they obviously had to figure out how to get laptops to remote workers and that that whole remote, you know, work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, but it sounds like you've got a digital business means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on this for the first step is to identify the critical data. Right. So we this is 1/6 process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on See how critical their data is? Then we help the customers to strategies that right the most important thing is to identify the most important critical herself. Data being the most critical assault for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them at all levels in the organization. That is a P for people to understand the importance off the residual our cells. And then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and the holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time. And finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment. We do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, >>so >>this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards the digital journey on. They have to face all these as part off the evolving environment on digital journey, and that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance. When? When your digital business. Here, as you say, you're a data business. So that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital race against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data sources. It could be on data basis or it could be even on the data lakes. Or it could be or no even on compromise, all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify, classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules. So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. And finally we also bringing the automatic data governance where we can manage the sensory data policies on their data relationships in terms off, mapping on manage their business rules on we drive reputations toe also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. And I'm gonna be great if you had an example is well, but maybe you could pick it up from there. >>Sure. I mean, at a high level, assertions are clearly articulated. Really? Um, Iota, who delivers business agility. So that's by, um, accelerating the time to operationalize data, automating, putting in place controls and ultimately putting, helping put in place digital resilience. I mean, way if we step back a little bit in time, um, traditional resilience in relation to data are often met manually, making multiple copies of the same data. So you have a DB A. They would copy the data to various different places on business. Users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. Onda course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is, and I realized that expression they used David, the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a P I s. And so you don't have the same need to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate, and that's really where I Tahoe comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, um, discovering what's duplicate what's redundant, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates with a tire. You could do it really very quickly on you can have tangible results within weeks and months. Um, and then you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then once you've done there, your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls, um, on you've got a drug towards the business outcomes and it's doing those three things together that really deliver for the customer. Thank >>you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome and we talked to a number of customers in the Cube. And the conclusion is really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed >>today? Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check on. Dis is a is a 2 to 3 weeks process are two Really quickly start to understand and deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data Onda. We can very rapidly demonstrate how date discovery those catalog e understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, and so what we tend to find is that we can very quickly as I say in a matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on. Then how they can scale that up, take it into production on, then really understand their data state Better on build resilience into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys. Great conversation. Thanks so much for coming on the program. Best of luck to you in the partnership. Be well. >>Thank you, David. Sorry. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban Are ongoing Siris on data Automation without Tahoe.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon Angle. Hi, this is David Linton. You're watching the Cubes coverage of the Cube on Cloud, our own virtual event where we're trying to understand the future of cloud, where we've come from and where we're going. And we're bringing in visionaries to really have that detailed conversation. Daniel Jones is here. He's the CEO of automation specialist. You. I path Daniel. Thanks for coming on and sharing your insights here. >>Thank you so much for inviting me. They've appreciated. >>That's always a pleasure to get together with folks that have started companies with a seed of a vision and have exploded in tow. You know, great success. And when I wanna go back to the the the founding days of you, I path 2005. It was a pre cloud. There's certainly pre cloud as we know it today. A w s came out in 2006. Aw, and then we saw the clouds Ascendancy. But but your original founding premise there was no cloud, you know, it wasn't like a startup could just spend up stuff in the cloud. But what you've seen that evolution. So when you first started to see cloud evolved, What did you think? Did you think Oh, well, we'll see what happens. Or did you? Did you know at the time that this was gonna be a bigas? It actually has become. What were your thoughts back then? >>Well, I honestly, I thought that we are kind of agent. And maybe it's stupid to not to pie foot in tow, The new trends in technology like Cloud Mobile social and I we kept, you know, working on this computer vision technology that 15 years ago, war was not really hot. But with the evolution of self driving cars and the latest development in AI, we we've been able to capture our investments in the domain that was not hot. But suddenly, you know, became the word the of the greatest minds in I t. And we definitely we specialize Our computer vision toe a narrow use case, but still, it's the It's the key of what we've done in, uh, in the end, the robots are powered by computer vision technology. This kind of a robot emulate how human user work. So obviously we use vision a lot in our day by day work and having the best technology that allows our robots to interact with the computer screen more like human user is quintessential and, uh, making our business reliable and easy to use. So we were lucky. But I always felt that maybe I should change it. And we were feeling I remember you know, many discussions with my, you know, initial developers because we like what you're doing. What we felt a bit left outside my door. What way? Got lucky in the end. >>So So I have a premise here and that when you go back to the early days of cloud, what they got right was they were attacking the human labor problem and they automate it was storage. It was it was networking. It was compute. But really the automation that they brought toe i t. And the quality that that drove and the flexibility was, you know, a game changer. Of course, we know that now. And you know, many of us at the time were very excited about Cloud. I'm not sure we predicted the impact that it had, but my premise is that there's a parallel in your business with the automation that you're driving into the business. We've talked toe people, for instance, that some of your customers have said, You know I can't do Six Sigma. I can't afford to do six Sigma before things like R P. A. For business process. I do that for Mission critical things, but now I can apply six Sigma thinking across my entire business that drives quality. It takes costs out of my business. So what do you think about that premise? That there's a parallel between the early days of cloud taking human labor out of the equation and driving quality and flexibility, cost saving speed and revenue, etcetera and what you're doing on the business side, >>it is clearly a parallel. I can tell that the cloud was built by looking at ICTY Automation use cases first of all, because this is all software engineers understand the most software engineers. Let's be you little on this. They don't understand the business work. They don't understand all how the rial work is performing a big enterprise and they don't care. Sometimes when in my own discussions with our CFO, he is surprised that I don't know all the use cases in the world. Yes, of course. I don't know exactly how an insurance company work All the processes in a health care, all the banking processes. I have intellectual curiosity how they were. But what interests me the most is our computer vision technology that works uniformly well across different. That was the same from the cloud. So initially they built and they build a cow cloud one toe, help them when what they know the best. And now, for we were put in the face of having great technology, this computer region technology, but without having a great use case in the I t world that we understood. And when we when I'm speaking about our early days like 12, 13, 14, I believe this technology has a lot less applicable bility in the real world. Because again, we were thinking of some sorts of small I T automation gigs that were not possible just doing the AP ice. But when I discovered the messy world of business processes and how important is to emulate people when you think automation, that was a big ah ha moment. So I believe that we can do for business processes what the cloud has done for I t processes on. We are really patient now about this business processes on helping people toe eliminate all the repetitive work that is their delegate. This work two robots and have the people that are required to do this work do do better. A smaller number of tasks every day. Everyone has own, as on her or him played today like, let's say, 10, 20 different activities. Some of them can be completely delegated to rob to robots, and they are the low value type of activities, while they can focus on the high value activities like interaction with people, creativity, decision making and this type of human like things that we as humans really love. >>I love that you shared that story, but you thought it was a very narrow, sort of set of use cases when you first started and then, you know, that's that's just an awesome founders, you know, really ization. I love it when we've often said in the Cube that, you know, for decades we've marched to the tune of Moore's Law. That was the innovation engine. No longer is that case. It's a combination of of data, applied machine intelligence and cloud for scale. And I guess the computer vision pieces How you in just the data you've you've made some investments in a I and there's many more to come the industry in general and the cloud is sort of the piece of that equation that we see for scale. So I wonder how you see those pieces fitting to your business. Uh, and how important is the cloud for your scale? At last? Uh, at last year, I path forward. There was a lot of talk amongst your customers about scaling. Is the cloud critical for that scale? >>Yeah, I believe so. And we are thinking of clouds in tow. Distinct ways number one. We're offering Onda manage automation service in our own close, using where we host everything by ourselves, including our orchestrator, and then be next to have the plans to include our the robots that execute the automation And people simply can't connect to our cloud building automation and just scheduled to run without any maintainers. And they will have access to oh, great analytics, Everything integrated. So this is a major force to us, and the way we launching G a. This cloud offering in April this year, and I can tell you that until now, 20% of our customers already are in a shape or another in this type of offering, not 20% dollar amount, but 20% of our customers. And it's clear that at this point this has mawr applicability into the long tail, a smaller customers than in the on our biggest customers. But the second, this thing type of cloud offering that we focus on is toe have best in class support and best in class multi cloud support for the cloud of choice of our customers. For instance, if you go in if you go in a w, g, c, p usher and you buy a subscription there, you wear buildings. Specialized editions were with one click. You will be able to install our technology in those clouds and you'll be ableto scale up and down your robots. You can connect your robots to our many service were within your tenant, but basically the angle is toe lesson. Ah lot the administration, the maintainers footprint of your installation, either on our own cloud, even on your cloud of choice. I'm a strong believer that we will see an accelerated transition from the completely on Prem Workloads into these two source of cloud workloads. >>I wanna ask you, is a a technologist if you see. So you mentioned that you're gonna take your products and your support. Multiple clouds will run on any cloud in A lot of companies are talking about that, you know, for their respective whether it's a database or, you know, whatever storage device, etcetera. Do you see the day where you'll actually start? You're collaborating across clouds. Where the user, uh, maybe maybe the user today doesn't know, but maybe a developer does know which cloud it's running on. But do you see any value in actual, you know, connecting across clouds where the data and one cloud is relevant for the data? Another cloud is I know there are latent see issues. Is that you know, technically feasible. And is it it? Will it drive business value? What do you think about that cross cloud connection? >>I believe it is already happening. There is a mesh between between various services and who knows in which cloud they are awful. Already. I feel the Leighton see is less and less of a problem as much as the biggest cloud provider have have a very distributed geographically president. So as long as I can playing AWS in East Coast, on on Asia in East Coast, it's not such a big Leighton see issue. Uh huh. Frankly, in the past, our customers at least start telling us they seen how it is to be completely looking toe one technology on people would like Toa have optionality. It's not necessarily that I will use three clothes, but I would like to use the vendor that gives me optionally even. And this is what we're trying to offer. >>Do you, when you think about the future of work? I mean, e said before the cloud one dato was infrastructure storage, networking, computing Uh, it seems like to Dato we're bringing in more ai new workloads. We're seeing, you know, analytics and machine intelligence applied to the data and then, you know, distributed at scale self serve to the business. How do you see the future of work specifically as it relates toe automation affecting that, uh on you know what role does cloud play there? What's your vision? >>So as the workloads will move to cloud. It's absolutely critical that the processes will move to cloud, so there is no way back. I think, that moving in tow, moving from home for and software into cloud will make even easier toe automate this type of workloads into the cloud. It's gonna be less maintain us. You will deal less with legacy applications that require some special care. It's kind of a bit more easier to automate modern Onley, Web based type of application so that Z we'll see an acceleration on the moving to cloud. But again, there will be different sorts of cloud from a completely manage automation service from us toe managing yourself the automation in your cloud tenant, but not on prayer. I'm not a big believer that we will accept unless very few critical sectors I don't think that we will see home Primor roads in the past five years. >>I mean, I agree in this case, the business case for on Prem just gets, you know, less and less. I mean, it'll be a certain applications for sure. My last question is, when thinking about from a software developer standpoint, you obviously you're gonna wanna run in a W S and G, C P and Azure. Uh, perhaps Alibaba, Uh, do you look at other clouds? Whether their regional clouds, of course. You got your own cloud. Maybe Oracle. IBM. How do you think about those? Do you just sort of evaluated on a case by case basis? You let customers, you know, tell you where you need to be. >>Yeah, way focus on the on the three big clouds today, but we're building on the top off Q Burnett is most of our way. We have a big shift in tow building que Burnett is micro services. And my guess is that all mother clouds would offer fantastic support for kubernetes. So what What it takes when you create a new edition for another cloud is toe is toe have the underlying services. Like if we plan to use snowflake, for instance in our analytics offering, you better have snowflake in another cloud. Otherwise, probably the the analytics will will have toe be delayed or use a less of one part technology. So it's not only about what we are building, but it's also, you know, the vast availability of other set of technologies that we try toe use when you choose a technology. Now, first of all, we are looking. We need to choose something that is multi cloud. There's who's dedicated from one cloud vendor. That's that's our first priority. This is why I've mentioned snowflake and then when when we moved into a cloud. We are limited by the offerings that are there, but I my belief is in the main clouds, probably in the US I don't know one of the region's what's gonna happen, but in the main crowds in the U. S. In I believe that they will. In the end, they will catch up in terms off offering and convincing of other defenders toe have kind of kind of similar offering on their own. I don't know if, besides, the Big Three, or you'll see someone and that is able to compete could be too much fragmented. Maybe they will be dedicated clouds for certain services. But for General Cloud, I think three is more than enough. >>Yeah, and so, you know, in the early days of cloud, people talked about dial tone, and essentially, that's what's becoming. It's the it's the value that's running on top of the cloud from software companies like ey Path and others that is really driving. So the cloud to Dato the next generation Daniel Dennett is thanks so much for sharing your vision on participating in the Cuban cloud. Really appreciate it. >>My pleasure, Dave. Thank you so much for inviting. >>You're welcome. You always great to talk to you. And thank you for watching everybody keep it right there. We'll be back with our next guest right into this short break. This is Dave Volonte for the Cube. Yeah.

>>from around the globe. It's the Cube presenting Cuban Cloud brought to you by Silicon Angle. >>Welcome back to the Cubes. Special Presentation on the Future of Cloud. Three years ago, Alan Nance said to me that in order to really take advantage of Cloud and Dr Billions of dollars of value, you have to change the operating model. I've never forgotten that statement have explored it from many angles over the last three years. In fact, it was one of the motivations for me actually running this program for our audience. Of course with me is Alan Nance. He's a change agent. He's led transformations that large organizations, including I N G Bank, Royal, Philips, Barclays Bank and many others. He's also a co founder of Citrus Collab. Alan, great to see you. Thanks for coming on the program. >>Thanks for having me again there. >>All right. So when we were preparing for this interview you shared with me the following you said enterprise, I t often hasn't really tapped the true powers that are available to them to make real connections to take advantage of that opportunity. Connections to the business, That is What >>do >>you mean by that. >>Well, I think, you know, we've been saying for quite a long time that enterprise. It is certainly a big part of our past in technology. But you know, just how much is it going to be in the future on, you know, enterprise, I t has had a difficult time under The pressure's off being a centralized organization with large expanse of large Catholics, while at the same time we see obviously the digital operations growing oftentimes in separate reporting structures and closer to the business on. And what I'm thinking right now is enterprise i t. If it has made this transition to cloud operating models, whether they are proprietary or whether they are public cloud, there's a huge opportunity for enterprise. I t. Thio connect the dots in a way that no other part of the organization can do that. And when they connect those dots working closely with the business, they unleash a huge amount of value that is beyond things like efficiency or things like just just just providing cloud computing to be flexible. It has to be much more about value generation. Andi. I think that a lot of leaders of enterprise I t have not really grasped that, Andi. I think that's the opportunity is sitting right in front of them right now. >>You know what I've seen lately? I wonder if you could. Comment is You know, obviously we always talk about the stove pipes, but you've you've seen, you know, the CEO, >>the chief >>data officer that you just mentioned the chief digital officer, the chief information security officer. They've largely been in their own silos. I'm definitely seeing a move to bring those together. I'm seeing a lot of CDOs and CEO roles come together and even the chief information or the head of security reporting up into that where there's there seems to be as your sort of suggesting just a lot more visibility across the entire organization. Is it Is it an organizational issue? Is it? Ah, is it a mindset? But only if you could comment. >>Well, I would say it zits, two or three different things, but certainly it's an organizational issue. But I think it starts off with a cultural issue. Andi, I think what you're seeing, and if you look at the more progressive companies that you see, I think you are also seeing a new emergence off the enlightened technology leader s O. With all respect to me and my generation, our tenure as the owners off the large enterprise, it is coming to an end. And we grew up trying to master the complexity of the off the silos. As you so definitely pointed out, we were battling this falling technology, trying to get it under control, trying to get the costs down, trying to reduce Catholics. And a lot of that was focused on the partnerships that we had with technology suppliers on DSO. That mindset of being engineers struggling for control. Having your most important part of being a technology company itself that now I think is giving way is giving way to a new generation of technology leaders who haven't grown up with that culture. Onda. Oftentimes what I see is that the new enlightened CEOs are female, and they are coming into the role outside of the regular promotion change. So they're coming to these rolls through finance H R marketing on their bringing. A different focus on the focus is much more about how do we work together to create an amazing experience for our employees and for our customers on an experience that drives value. So I think there's a reset in the culture. And clearly, when you start talking about creating a value chain to improve experience, you're also talking about bringing people together from different multidisciplinary backgrounds to make that happen. >>Well, that's kind of, you know, it makes me think about Amazon's mantra of working backwards. You know, start with the experience and and and a lot of a lot of CEOs that I know would love tow beam or involved in the business. But they're just so busy trying to keep the lights on like you said, trying to manage vendors. And like, you know, I had a discussion the other day, Allen with an individual. We were talking about how you know, you got a shift from a product mindset to a platform mindset. But you know, you've said that that platform thinking you're always ahead of the game platform, thinking it needs to make way for ecosystem thinking, you know, unless you're Internet giant scale business like Amazon or Spotify, you said you're gonna be in a niche market if you really don't tap that ecosystem again. If you could explain what you mean by that. >>I think right now if this movement to experience is fundamental, right? So Joe Pine and Gilmore wrote about the experience economy as far back in 1990. But the things that they predicted then are here now. And so what we're now seeing is that consumers have choice. Employees have choice. I think the pandemic has accelerated that. And so what happens when you, when you when you put an enterprise under that type of external pressure, is that it fragments and even fragment into ways it can fragment dysfunctional E so that every silo tries to go into a a defensive mode protective mode? That's obviously the wrong way to go. But the fragmentation that's exciting is when it fragments into ecosystems that are actually working together to solve an experience problem. And those are not platforms. They're too big, you know, When I was Phillips, I was very enthusiastic about working on this connected health care platform, but I think what I started to realize was it takes too much time. It requires too much investment on you are bringing people to you based on your capability. Where is what the market needs is much more agile than that. So if we look in health care, for instance, and you want to connect patients at home with patient with the doctors in the hospital, in the old model you so I'm gonna build a platform for this. I'm gonna have doctors with a certain competence and they're gonna be connecting into this. And so are the patients in some way. And so are the insurers. I think what you're going to see now is different. We're going to say, Let's get together A small team that understands it's called, For instance, let's get a an insurance provider. Let's get a health care operator. Let's get a healthcare tech company on. Let's pull their data in a way that helps us to create solutions now that that can roll out in 30 60 or 90 days. And the thing that that makes that possible is the move to the public crowd because now there are so many specialized supplier, specialized skill sets available that you can connect to through Amazon through Google, through through azure that that these these things that we usedto I think we're very, very difficult are now much easier. I don't want to minimize the effort, but these things are on the table right now. Thio Revalue. >>So you're also a technologist and I wanna ask you and and everybody always says, it's the technology is easy part. It's the people in the process and, you know, way we can all agree on that. However, sometimes technology could be a blocker. And the example that you just mentioned, I have a couple of takeaways from that. First of all, you know the platform thinking it sounds like it's more command and control, and you're advocating for Let's get the ecosystem who are closest to the problem. To solve those problems, however, they decide and leverage the cloud. So my question is from a technology standpoint, does that echo have system have to be on the same cloud with the state of today's technology? Can it be across clouds can be there pieces on Prem? What's your thinking on that? >>I think I think exactly the opposite. It cannot be monolithic and centralized. It's just not practical because that was that was that would cause you too much time on interoperability and who owns what you see The power behind experience is data. And so the most important technical part of this is dealing with data liquidity. So the data that for instance, um, somebody like Kaiser has or the the Harvard Health Care have or the Philips have that's not going to be put into a central place. But for the ecosystem mobilization, there will be subsets of that data flowing between those parties. So the technical, the heart there is how do we manage data liquidity? How do we manage the security around the data liquidity on How do we also understand that what we're building is going to be ever changing and maybe temporary, because on idea may not work, eh? So you've got this idea that the timeliness is very, very important. The duration is very uncertain. The motor the energy for this is data liquidity data transfer, data sharing. But the vehicle is the combination off. Probably crowd in my mind. >>Somebody said to me, Hey, that data is like water. It'll go. It'll go where it wants to go where it needs to go. You can't try to control it. It's let it go. Uh, now, of course, many organizations, particularly large incumbent organizations there. They have many, many data pipelines. They have many processes, many roles, and they're struggling toe actually kind of inject automation into those pipelines. Maybe that's machine intelligence, uh, really doom or data sharing across that pipeline and and ultimately compress the end and cycle. Time to go from raw data insights that are actionable. What are you seeing there and what's your advice? >>Well, I think the the you make some really good points. But what I hear also a little bit in your observation is you're still observing Enterprises on the end of the focus of the enterprise has been on optimizing the processes within the boundaries of its own system. That's why we have s a P. And that's why we have a sales force and, to some degree, even service. Now it's all been about optimizing how we move data, how we create products and services on. That's not the game. Now that's not an important game. Three important game right now is how do I connect to my employees? How do I connect to my customers in a way that provides them a memorable experience? And the realization is we've seen this already a manufacturing for some years. I can't be allowed things to people. So I have to understand where the first part of data comes in. I have to understand who this person is that I am trying to target. Who is the person that needs this memorable experience on what is that memorable experience gonna look like? And I'm going to need my data. But I'm also going to need the data of other actors in that ecosystem. And then I'm gonna have to build that ecosystem really quickly to take advantage off the system. So this throws a monkey wrench in traditional ideas of standardization. It throws a monkey wrench in the idea that enterprise I t is about efficiency on. But if I may, I just want to come back to the day I because I think we're looking in the wrong places. Things like a I let me give you an example. Today there are 2.2 million people working in call centers around the world. If we imagine that they work in three shifts, that means that any one time there are 700,000 people on the phone to a customer on that customer is calling that company because they're vested. They're calling them with advice. They're calling them with a question. They're calling them with a complaint. It is the most important source off valuable data that any company has. And yet what have we done with that? What we've done with that is we have attacked it with efficiency. So instead of saying these are the most valuable sources of information, let's use a I to to tag the sentiment in the recordings that we make with our most valuable stakeholders on this and analyze them for trends, ideas, things that need to change. We don't do that. What we do is we were going to give every call agent two minutes to get them off the phone. For God's sake, don't ask so many import difficult questions. Don't spend money talking to the customer. Try to make them happy so they get a score and say they hire you at the end of the core and then you're done. So so where the AI and automation needs to come in is not in improving efficiency but in mining value. And the real opportunity with a I Is that Joe Pine says this. If you are able to understand the customer rather than interpret them, that is so valuable to the customer that they will pay money for that. I think that's where the whole focus needs to be in this new teaming of enterprise I t. And that's true business. >>It's a great observations. I think we can all relate to that in your call center example, or you've been in a restaurant. You're trying to turn the tables fast and get you out of there. And that's the last time you ever go to that restaurant and you're you're taking that notion of systems thinking and broadening it to ecosystems thinking. And you've said ecosystems have a better chance of success when they're used to stage an experience for whether it's the employees for the brand and of course, the customer and the partners. >>That's it. That's exactly yet. So every technology leader should be asking themselves what contribution can can my and my organization makes of this movement because the business understands the problem, they don't understand how to solve it, and we've chosen a different dialogues. We've been talking a lot about what cloud could do and the functionality that clown has and the potential that clown has on those aerial good things. But it really comes together now when we work together and we, as the technology group brings in, they know how we know how toe connect quickly through the public cloud. We know how to do that in a secure way. We know how to manage data, liquidity at scale, and we can stand these things up through our, you know, our new learning of agile and devils we can stand. These ecosystems are fairly quickly now. There's still a whole bunch of culture between different businesses that have to work together through the idea that I have to protect my data rather than serve the customer. But once you get past that, there's a whole new conversation enterprise. It you can have that, I think, gives them a new lease of life, new value. And I just think it's a really, really exciting time. Yes, >>so you're seeing the intersection of a lot of different things. You talk about cloud as you know, an enabler for sure, and that's great. We could talk about that, but you've got this what you're referring to before is, you know, maybe you're in a niche market, but you have your marketplace and like you're saying, you can actually use that through an ecosystem to really leave her a much, much broader available market and then vector that into the experience economy. You know, we talk about subscriptions, the AP economy. That really is new thinking, >>yes, and I think what you're seeing here is it zits, not radical. Inasmuch as all of these ideas have been around, some of them have been around since the nineties. But what's radical is the way in which we can now mix and match these technologies to make this happen. That's gone so quickly on, I would argue to you, and I've argued this before. Scale scale is a concept within an organization is dead. It doesn't give you enough value. It gives you enough efficiency, and it gives you a cloud. But it doesn't give you three opportunity to target the niche experiences that you need to do. So. If we start to think off an organization as a a combination off known and unknown potential ecosystems, you start to build a different operating model, a different architectural idea you start to look outside more than you start to look insight. Which is why the cultural change that we were talking about just now goes hand in hand with this because people have to be comfortable thinking in ecosystems that may not yet exist on partnering with people where they bring to the table there, you know, 2030 years of experience in a new and different way. >>Let me make sure I understand that. So you're basically if I understand you're saying that if you're sort of end goal is scale and efficiency at scale, you're you're gonna have a vanilla solution for your customers and your ecosystem. Whereas if you will allow this outside in thinking to come in, you're gonna be able to actually customize those experience experiences and get the value of scale and efficiency. >>Right? So, I mean, Rory Sutherland, who is ah, big finger in the in. The marketing world has always said, ultimately, scale standardization and best practice lead to mediocrity because you are not focused on the most important thing for your employees or your brand, or you're you're focused on the efficiency factors on. They create very little value in fact, we know that they subvert value. So, yes, we need to have a very big mindset change. >>Yeah, You're a top line thinker, Allen. And and always at the forefront. I really appreciate you coming on to the to the Cuban. Participate in this program. Give us the last word. So if you're a change agent, I wanna I'm an organization, and I want to inject this type of change. Where do I >>start? Well, I think it starts by identifying. Are we going to? Is it are we gonna work on the employee experience? Do we feel that we have a model where the employees that are on stage with customers are so important that the focus has to be employees? We go down that route and we look at what happened to the pandemic. What type of experiences are we going to bring to those employees around their ability to have flow in their work, to get returned on energy, to excite the customers? Let's do that. Let's figure out what experience are we driving now? What does that experience need to be if we're the customer side? As I said, let's look ALS. The sources of information that we already have. You know, I know companies to spend hundreds of millions a year trying to figure out what consumers what. And yet if we look in their call centers, you will call up and and they will say to Your call may be recorded for quality purposes and training on this is not true. Less than 10% of those calls that ever listened to on if they are listening to its compliance that's driving that, not the burning desire to better understand the consumer. So if we change that, then we say Okay, so what can we change? What is the experience that we are now able to stage with all we know and with all weaken dio on debts? Start there. Let's start with what is the experience you want to stage? What's the experience landscape look like now? And who do we bring together to make that happen? >>Allen. Fantastic. Having you back in the Cube, it's always a pleasure. And, uh, and thanks so much for participating. >>Thank you, Dave. It's always a pleasure to speak with you. >>Thank you. Everybody, this is Dave Volonte. The Cuban cloud will be right back right after this short break. Stay with

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Okay, we're now going >>to explore what it's like to be the CEO of a fast paced growth company in Silicon Valley. And how the cloud, however, you wanted to find the cloud public cloud on Prem Hybrid, etcetera. How it supported that growth. And with me is Kathy Southwick, who is the CEO of pure storage. Kathy is really deep experience. Managing technology organizations spent a number of years overseeing A T and T s cloud planning and engineering and another few years overseeing a team of a Couple 1000 network and I T engineers working to break the physical stranglehold of fossilized telco networks, implementing network functions, virtualization and a software defined methodology for the company. And, of course, you spent the last couple of years is the CEO of Pure. So Cathy, it's great to see you again. Thank you for coming on the program. >>Thanks for having me. It's good to be here. >>You're very welcome. And so so >>given your >>experience with cloud, you know, dating back to really the early part of last decade. How did you look at cloud back then and how How is it evolved from your point of view? >>You know, it's Ah, it's an interesting question because I think that we've there's some things that have moved very fast and there's some some things that are very much the same as they were even a decade ago. I think that all companies are very focused on How do you think about Cloud? Do you think about it as on Prem? And when I started, we really were focused on an on Prem solution, and I'm in building an on Prem private cloud to help modernize our business. So I think that, you know, with that all companies are still in that same mindset of how do I want to think about Cloud? And how do I want to think about that on Prem versus Public versus, you know, combination or some type of hybrid solution? So I think all of us around that journey, it just seems like it's taken. It's probably a bit longer than most of us probably thought from beginning. >>So as a CEO thinking about that evolution, how has that informed the way you think about applying specifically the public cloud to pure business. >>You know, I think that we've been a for pure ourselves. I think we're in a really unique position. We were essentially born in the cloud. So we're, you know, company. That's 10 11 years old. And if I If I give the contrast of that of 18 t being, you know, 130 year old company Onda having a lot of applications that have, you know, lived historically on prim. There's very different issues and challenges that you have pure has had that. I think the advantage just like many other companies that were born in the cloud who have can see what advantages are very quickly. And we made decisions early on that said that we were gonna actually do both. We were gonna look to say, How do I put those applications in that in that data, whether it was on public or in on Prem and be able to do that both in the i t. Side as well as within the product side? So how we build our products now, >>as I mentioned up front, you have obviously a lot of experience managing large technology teams. My question is. When you first saw the emergence of the modern cloud, how did you communicate with your team members? I mean, you mentioned you were kind of building your own private cloud, so I guess that's less threatening to people. But what was it like? You know, Was there a concern? You know, with the eager to jump in? What was that dynamic like? And how did you manage >>it? You know, it's really it's a different depending on the different part of the organization. So I'll give you kind of two things I learned one of them was that our teams in the operation side, they saw it as a huge advantage. They saw it as an opportunity to really modernized to really get themselves both their own individual skill sets advanced, as well as provide a better level of service for our internal, you know, customer, so to speak. Our application in our data partners that we had to work with, um, they thought is an opportunity to bring agility to their applications quicker speed to market, um, or currency of their applications. So they actually got some benefits that they weren't. Actually, I'll call planning for they were they had the opportunity toe get investment in their applications without having to put the that investment on themselves. I would tell you the thing I learned from the teams, this is probably might be a little bit surprised. But often, you know, leaders believe like, you gotta have all the answers. You're gonna drive everything you're gonna let make sure everyone knows what needs to get done and what I actually found. This was actually one of my big moments, I think, was our Our individuals are employees are teams. They're so brilliant and so bright on driving change. And a lot of times leaders, I think, get in the way that so for cloud and adoption, it was really about me getting out of the way. It was really about setting that north star for where we want to go from the ability to deliver fast and quick for our business. And they get out of the way and let our teams actually drive. So it was a great, um, it was we actually actually saw the reverse. I saw more employees wanting to drive, and I needed to, like, back out and just say, Here's what we need to go. Let them drive us there. >>Alright, So I gotta ask you don't Please don't hate me for asking this question, but was your your gender and advantage was at a disadvantage. It wasn't really irrelevant in that regard. >>It was a relevant um, I think that it was I actually I truly believe it's irrelevant. I think it was literally recognizing that leaders need to set vision and what we want to achieve and let our letter of teams help us drive to get there. And I think that that is, you know, gender neutral. I think it's really about, you know, kind of checking your ego and everything else out to the side. And it's really about empowering people in our teams. Thio help drive us there. >>So thinking about that that learning specifically are there any similar tectonic shifts that you're you're seeing today where you can apply that experience? I'm just like, for instance, new modes of application development and requiring new skill sets are, or maybe another that you can think of. >>Yeah, I think I think honestly, it traverse is everything that we that we have to do as a you know, as a leader of a technology team, and whether you're in a high growth company like Pure or you're in a company that's trying to take costs out of your business or trying to, you know, do things. I think that it, um it really is a matter of leaders needing to set the stage. And so if we're trying to drive, you know, changing the business, it's really making sure that we're doing I'll calm or more empowering of our employees and they because they will see the way that we can get there. It's just a matter of, you know, letting them have that ability to do it. >>So you joined pure around two years ago and obviously growing very quickly. I love pandemic has changed the trajectory of that growth, but still good outlook. Um, but Silicon Valley fast paced company, you know, I kind of put it in the camp of the the work days, and the service now is that could have similar similar cultural patterns there. So you talked a little bit about this, but I wonder if we could come back and more specifically how you're leveraging cloud, how you're thinking about it, you know, on Prem Hybrid, Now the edge. And how did that contribute Thio Puros growth? >>Yeah, that za great question because I think that why I shared earlier, you know, we were essentially born in the cloud. I think that what it's really driven us is to be thinking more forward about where customers were going and what their challenges are. So whether it's for the I t. Teams on what we're trying to do to deliver for our business and, you know, innovation, they're obviously trying to make sure they can hit their revenue goals and all those things that important that every business deals with. But we also have that same mindset on how we develop our products. So it's really all driven by where the customer is going that they need data mobility. They need application mobility. They need really portability so that the moment that you have that ability where you can kind of control your destiny and define it, and you only could get that by having, you know, applications that are portable and data that is mobile and secure, that you have that kind of flexibility. So I think for pure we've been definitely in a great position to drive for our customers or drive where our customers are going. And so we have to find our entire product set. So not just how we operate as a business and run our business. But then how we define for our customers Same mindset is if our customers are going to the cloud that we need, have products that can help them to be in the cloud or be, you know, on print and let them decide what that looks like. Well, >>it's interesting you mentioned that and I hearken back to the The Port Works acquisition, which is an attempt to really change the way application development has done is another sort of approach Thio in a sort of modern data architecture, you, as the CEO of a technology company, most CEO, is that I know inside the tech companies that they're sort of the dog Fuding or champagne drinking, you know, testing. So So had you already started to sort of use that tech? Are you starting to, you know, Does it support that vision that you just put forth? Maybe you could talk a little bit about that. >>Yeah, It does. So we eso We had not been using port works as a za product. We were just starting down that path of looking at How do we do container ization for the applications that we do have on Prem? That's both in our engineering side as well as within I t. And so But we quickly have recognized, just like you know, And part of that acquisition is applications or companies won't have the ability to have that portability of their applications and have that flexibility that they're all striving for unless they've done things like containerized or applications made them that they're able to move them across different cloud environments, whether that's on Prem or off Prem or some hybrid eso for ourselves. You know, Port Works was a really critical acquisition, will help us on our own journey of doing the application, modernization and putting that keep those capabilities in place. But it will also enable our customers to have that same flexibility. So, again, going back to the we've adopt, these things aren't like a this is for this group, and this is for you know, this customer. It's really about how we operate both internally and then what we are providing for our customers so that portability and being able to have control of your own destiny, that's that's really to me what hybrid cloud is all about. And you can't really achieve that If you don't have some of these capabilities within your, you know, within kind of your toolbox. >>Great. Thank you for that. So I'm interested in is the head of, ah technology group at a tech company? And what are the meaningful differences? I mean, a lot of differences, but relative to CEO of a large telco or or other incumbent, you know, what are some of the good, the bad? And, uh, you know, the ugly, the differences. >>Yeah, you know, it's I meet with a lot of CEOs across Silicon Valley and we kind of joked that when you are working in a company that is a technology based company, you know, everybody knows how to dio, you know, because you do you have a brilliant engineers and and that they do know. I think the difference that you start to see is that you know, I t is, um is required to make sure that availability is their inherent in what you're doing on immediate roll out with like, you know, an application that's occurring. That's very different than how you do product lifecycle management. Um, what what we've what I've seen, actually, though, is more similarities. I know that's probably surprised to you, but coming out of a T and T, what I have been working on those last couple of years was actually doing the combination of engineering and I t into one organization and that you do have a lot of benefits for, for how you can then develop, how you can manage and the skill sets. There's a lot of similarities. So there's there's actually probably more similarities between companies and on what they're trying to achieve than than you would probably think there would be just because we're all trying to make sure that we can develop quickly. How about is >>it relates to cloud Cathy? I mean, I remember the early days of cloud, a lot of the big banks that we could build our own cloud. We can essentially compete at scale with with Amazon, where you know the big bank on. Then I think they quickly realized well, the economics actually don't favor us necessarily. Do you think there's a different perception about the use of cloud between sort of traditional incumbents and a tech company in Silicon Valley? And if so, how? >>So now I think that the if you are, you know, a bank is you refer to, and having it really is where you're starting from. If you have a very large infrastructure footprint and application footprint, your applications probably not born in the cloud. There's a lot of modernization that has to be done with those applications so that they could operate as efficiently in a public cloud as an example. And I think that's something that sometimes gets overlooked is there are enormous benefits going to public cloud. But there's also cost if your applications or your data doesn't really fit as well in that type of environment. So I think that for large enterprises like the banks, some of the telcos they've got very large footprints of infrastructure. Already, those investments have been made, and what they're really looking for is how doe I increase my ability to, you know, whether it's agility or its speed, or it's lower cost or it's all those things, and I think that's the That's a different path of different journey that they're on. So they're trying to balance all those equations of, you know, the economics as well as the ability to have, you know, no more investment or minimal investment in that infrastructure. For companies like Pure, where we started off of those investments are decision and kind of. The decision tree that we use is if it makes sense. And I don't have to make that investment on Prem for whatever reason, that I should go ahead and make that investment in a public cloud strategy or a hybrid cloud strategy kind. Differentiate that because I think that it's different depending on the company. You are, um, and so it really kind of depends on where you're starting from then. It also depends on what you're trying to achieve if you're just trying to achieve an economic solution. If you're trying to achieve a strategic solution, if you're trying to get agility. Andi, I think it is different for companies, and it's different depending where you're at in your kind of journey. So for a Silicon Valley company whose you know hyper growth, you know, one. We're very focused on abilities. You know everything from scale, because we've got to scale quickly. And those are things that we don't wanna have to start going and building all these data centers to go do that. We don't have those embedded investments. So it's Ah, it's a real difference in where your starting point is. And I think there I think there's value in in all those different type of approaches, >>right? And it's a real advantage for you that you don't have to shell out all that cap ex on Data Center. >>That's right. Um, as you look >>back at the last 10 years of cloud, you know, it was largely about eliminating the heavy lift of infrastructure deployment and SAS if I ng you know the business, what do you see? Going forward? What do you think the was gonna unfold in the 2020 is? Is it gonna be more of the same? Or do you expect meaningful differences? >>I think that we're going to get better as, um as you know, technology leaders on how to quickly make decisions. Um, and not its have it less political. And I think Kobe is actually taught us a lot about that around companies more willing to make. I'll call it a A you know, a faster decision and remove some of the red tape. I've heard this from many of my peers that things that might have taken them months and months to get approved. Um, it's nowadays if even if they even have to go get approval. So I think that what we're going to see is we'll see the continuance of, um, you know, a public and I'll call really hybrid cloud type of solutions. And I think it will be more purposeful about what goes there and how. How that can help us toe, you know, I'll call it enable us much faster than we've been able to do it before. I think that's been our challenges. We've, you know, we get mired into some of the you know, the details of some of these things that maybe it would be easier for us to just make the decision to move forward than Thio. Keep going around around on what's the right way to do it. Yeah, >>so that's interesting. You're saying about the fast decisions? I felt like, ah, lot of 2020 was very tactical. Okay, go deal with the work from home, etcetera. Although you you definitely see I t spending, uh, suppressed in 2020. Our forecast was minus 4% but we're saying it's gonna grow. We actually see a decent snapback. You know, what are you seeing? Generally, Not even necessarily pure. But when you talk to some of your colleagues, you obviously in the technology business, it's good to be in the technology business these days. But to use do you see spending, you know, generally coming back And maybe the timing first half, maybe a little soft second. What are you seeing >>there? Yeah, almost identical wage that. I think that we'll see, you know, a little bit of, ah tendency toe, not really hold back, but really kind of see what's happening in the first quarter of the year. There's a lot, you know, going on with companies and everyone's having to kind of balance at what that looks like. I do see. And what I'm hearing from several of my peers is that, you know, it's not necessarily budget cuts. It might be budget re directions. It might be rude prioritization, but definitely technology investments are still there, and it's still important for businesses to keep on their journeys on. But we do see that even at pure as a way to differentiate ourselves in the market as well, do you? What >>about the work from home piece? I mean, prior to co vid, I think the average was about 15 or 16% of employees work from home. You know, now it's gotta be, you know, well, over in the high seventies, Onda CEO is that we've talked to suggest that, you know, that's gonna come down in the first half, maybe down toe, still pretty high 50 60%. But then eventually is gonna settle at a higher rate than it was pre pre covert. Maybe double that rate may be in the 30 35 maybe even 40%. You know? What are you expecting >>Something probably very similar. I think that what companies have recognized and I actually tell you CEO have thought this many of them for many years that there is a huge value value and having some type of hybrid model. There's value in having, you know, both from a business perspective as well as a personal perspective. So employees work life balance and trying to balance that. So I think that, you know, we a pure and myself, As you know the CEO hugely expect that we will see some type of you know, I'll call leveling off, figure out what's the right for the right group. And I think what we don't want to get into is, you know, Chris prescriptive that says, You know, this is what the company will look like as a whole. I think it really is going to come down to certain certain types of work are more conducive to a more work, remote environment others need to have. And I always kind of uses term of individual, you know, productivity versus team. You know, productivity. We've seen, you know, great advances and or individual productivity. A team productivity is still a challenge when you're still trying to do very collaborative, you know, brainstorming sessions. And so we are looking at capabilities to be able to enable our employees to do that. But there there's some things you just can't replace. The human interaction and ability to very quickly inter actively, you know, five minutes catch someone to do that. So I think we'll see. We'll see both. We'll see some leveling off, and I think we'll see some areas of businesses that have once thought You can't do that remote. They might actually say, Hey, that is work that commute remote So I think we'll see a combination of both. That's an >>interesting perspective on productivity. And what's the What's the old saying is You could go go faster alone. But further as a team and and not a lot of folks have been talking about that team productivity, we we clearly saw the hit the positive hit on productivity, especially in the in the technology business. So So my question then is so you expect? You know H Q doesn't go away. Maybe it gets, you know, maybe it gets smaller, Uh, but so is their pent up demand for technology spending at the headquarters. Because you've been you've been, you know, pushing tech out out to the edge out to the remote workers. Securing those remote workers figuring out better ways to collaborate is their pent up demand at H. Q. >>Um, absolutely. We've been, you know, we've been actually exploring different technologies. We've been uh, looking at what are things that you know could help create a different kind of experience, eh? So I do think it will be some different types of technology. Those would be the things that maybe aren't even out there developed yet on Have you create some of those comparable experiences. So I think that the notion of you know individuals will continue to thrive, but we've got to start working on How do we continue to enhance that? That team, um, collaborative productivity environment that looks and feels different than what it might look like today. Yeah. >>They got to leave it there. Great as always. Having you in the Cube. Thanks so much for participating in Cuban Cloud. >>Great. It's great to be here. Thank you. >>Keep it right there. Back more content right after this short break. >>Yeah.

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>Yeah. >>Welcome back for our last session of the day how to deliver career making business outcomes with Search and AI. So we're very lucky to be hearing from Canada. Canadian Tire, one of Canada's largest and most successful retailers, have been powered 4.5 1000 employees to maximize the value of data with self service insights. So today we're joining us. We have Yarrow Baturin, who is the manager of Merch analytics and planning to support at Canadian Tire and then also Andrea Frisk, who is the engagement manager manager for thoughts. What s O U R Andrea? Thanks so much for being here. And with >>that, >>I'll pass the mic to you guys. >>Thank you for having us. Um, already, I I think I'll start with an introduction off who I am, what I do. A Canadian entire on what Canadian pair is all about. So, as a manager of Merch analytics at Canadian Tire, I support merchant organization with reporting tools, and then be I platform to enable decision making on a day to day basis. What is? Canadian Tire's Canadian tire is one of the largest retailers in Canada. Um, serving Canadians with a number of lines of business spanning automotive fixing, living, playing and SNG departments. We have a number of banners, including sport check Marks Party City Phl that covers more than 1700 locations. So as an organization, we've got vast variety of different data, whether it's product or loyalty. Now, as the time goes on, the number of asks the number off data points. The complexity of the analysis has been increasing on banned traditional tools. Analytical tools such as Excel Microsoft Access do find job but start hitting their limitations. So we started on the journey of exploring what other B I platforms would be suitable for our needs. And the criteria that we thought about as we started on that journey is to make sure that we enable customization as well as the McCarthy ization of data. What does that mean? That means we wanted to ensure that each one of the end users have ability to create their own versions off the report while having consistency from the data standpoint, we also wanted Thio ensure that they're able to create there at hawks search queries and draw insights based on the desired business needs. As each one of our lines of business as each one of our departments is quite unique in their nature. And this is where thoughts about comes into play. Um, you checked off all the boxes? Um, as current customers, as potential customers, you will discover that this is the tool that allows that at hawks search ability within a matter of seconds and ability to visualize the information and create those curated pin boards for each one of the business units, depending on what the needs are. And now where? I guess well, Andrea will talk a little bit more about how we gained adoption, but the usage was like and how we, uh, implemented the tool successfully in the organization. >>Okay, so I actually used to work for Canadian tire on DSO. During that time, I helped Thio build training and engaging users to sort of really kick start our use cases. Andi, the ongoing process of adopting thought spot through Canadian Tire s 01 of the sort of reasons that we moved into using thought spot was there was a need Thio evolve, um, in order to see the wealth of data that we had coming in. So the existing reporting again. And this is this sort of standard thoughts bought fix is, um, it brings the data toe. Everyone on git makes it more accessible, so you get more out of your data. So we want to provide users with the ability to customize what they could see and personalized three information so that they could get their specific business requirements out of the data rather than relying on the weekly monthly quarterly reporting. That was all usually fairly generic eso without the ability to deep dive in. So this gave the users the agility thio optimize their campaigns, optimize product murder, urgency where products are or where there's maybe supply chain gaps. Andi just really bring this out for trillions of rose to become accessible. Thio the Canadian tire. That's what user base think. That's the slide. >>That's the slight, Um So as Andrea talked about the business use of the particular tool, let's talk a little bit about how we set it up and a wonderful journey of how it's evolved. So we first implemented 5.3 version of that spot on the Falcon server on we've been adding horsepower to it over time. Now mhm. What I want to stress is the importance off the very first, Data said. That goes into the tool toe. Actually engage the users and to gain the adoption and to make sure there is no argument whether the tool is accurate or not. So what we've started with is a key p I marked layer with all the major metrics that we have and all the available permutations and combinations off the dimensions, whether it's a calendar dimension, proud of dimension or, let's say, customer attribute now, as we started with that data set, we wanted to make sure that we're we have the ability to add and the dimensions right. So now, as we're implementing the tool, we're starting to add in more dimension tables to satisfy the needs off our clients if you want to call it that way as they want to evolve their analytics. So we started adding in some of the store attributes we started adding in some of the product attributes on when I refer to a product attributes, let's say, uh, it involves costs and involves prices involved in some of the strategic internal pieces that we're thinking about now as the comprehensive mark contains right now, in our instance, close to five billion records. This is where it becomes the one source of truth for people declaring information against right so as they go in, we also wanted to make sure when they Corey thought spot there, we're really Onley. According one source of data. One source of truth. It became apparent over time, obviously, that more metrics are needed. They might not be all set up in that particular mark. And that's when we went on the journey off implementing some of the new worksheets or some of the new data sets particularly focused on the four looking pieces. And uh, that's where it becomes important to say This is how you gain the interest and keep the interests of the public right. So you're not just implementing a number off data sets all at once and then letting the users be you're implementing pieces and stages. You're keeping the interest thio, the tool relevant. You're keeping, um, the needs of the public in mind. Now, as you can imagine on the Falcon server piece, um, adding in the horsepower capacity might become challenging the mawr. Billions of Rosie erratic eso were actually in the middle of transitioning our environment to azure in snowflake so that we can connect it. Thio embrace capability of thoughts cloud. And that's where I'm looking forward to that in 2021 I truly believe this will enable us Thio increase the speed off adoption Increase the speed of getting insights out of the tool and scale with regards Thio new data sets that we're thinking about implementing as we're continuing our thoughts about journey >>Okay, so how we drove adoption Thio 4500 plus users eso When we first started Thio approach our use case with the merchants within Canadian Tire We had meetings with these users with who are used place is gonna be with and sort of found out. What are they searching for, Where they typically looking at what existing reports are available for them. Andi kind of sought out to like, What are those things where you're pulling this on your own or someone else's pulling this data because it's not accessible yet And we really use that as our foundation to determine one what data we needed to initially bring into the system but also to sort of create those launchpad pin boards that had the base information that the users we're gonna need so that we could twofold, make it easy for them, toe adopt into the tool and also quickly start Thio, deactivate or discontinue those reports. And just like these air now only available in thought spot because with the sort of formatting within thought spot around dates, it's really easy to make this year's report last year report etcetera. Just have everything roll over every month or a recorder s. So that was kind of some of the pre work foundation when we originally did it. But really, it's been a lot of training, a lot of training. So we conducted ah, lot of in person training, obviously pre co vid eso. We've started to train the group that we targeted, which was the merchants and all of the like, surrounding support groups. Eso we had planners going in and training as well, so that everyone who was really closely connected to the merchants I had an idea of what thoughts about what was and how to use it and where the reports were, and so we just sort of rolled it out that way, and then it started to fly like wildfire. Eso the merchants start to engage with supply chain to have conversations, or the merchants were engaging with the vendors to sort of have negotiations about pricing. And they're creating these reports and getting the access to the information so quickly, and they're sharing it out that we had other groups just coming to us asking, How do I get into thoughts about how can I get in on DSO on top of those groups, we also sought out other heavy analytics groups such a supply chain where we felt like they could have the same benefits if they on boarded into thought spot with their data as well on Ben. Just continuing to evolve the training roll out. Um, you know, we continued to engage with the users, >>so >>we had a newsletter briefly Thio, sort of just keep informing users of the new data coming in or when we actually upgraded our system. So the here are the new features that you'll start seeing. We did virtual trainings and maintaining an F A Q document with the incoming questions from the users, and then eventually evolved into a self guided learning so that users that were coming to a group, or maybe we've already done a full rollout could come in and have the opportunity to learn how to use thought spot, have examples that were relevant to the business and really get started. Eso then each use case sort of after our initial started to build into a formula of the things that we needed to have. So you need to understand it. Having SMEs ready and having the database Onda worksheets built out sort of became the step by step path to drive adoption. Um, from an implementation timeline, I think they're saying, Took about two months and about half of that waas Kenny entire figuring out how figuring out our security, how to get the data in on, Do we need the time to set up the environment and get on Falcon? So then, after that initial two months, then each use case that we come through. Generally, we've got users trained and SMEs set up within about 2 to 3 weeks after the data is ingested. It's not obviously, once snowflakes set up on the data starts to get into that and the data feeds in, then you're really just looking at the 2 to 3 weeks because the data is easily connected in, >>um, no. All right, let's talk about some of the use cases. So we started with what data we've implemented. Andrea touched upon what Use a training look like what the back curate that piece wants. Now let's talk a little bit about use cases and how we actually leverage thoughts bought together the insights. So the very first one is ultimately the benefit of the tool to the entire organization. Israel Time insights. To reiterate what Andrea said, we first implemented the tool with our buyers. They're the nucleus of any retail organization as they work with everybody within the company and as the buyer's eyes, Their responsibility to ensure both the procurement and the sales channel, um, stays afloat at the end of the day, right? So they need information on a regular basis. They needed fast. They needed timely, and they needed in a fashion that they choose to digest it. It right? Not every business is the same. Not every individual is the same. They consume digest, analyze information differently. And that's what that's what allows you to dio whether it's the search, whether it's a customized onboard, please now supply chain unexpected things. As Andrea mentioned Irish work a lot of supply chain. What is the goal of supply chain to receive product and to be able to ship that product to the stores Now, as our organization has been growing and is doing extremely well, we've actually published Q three results recently. Um, the aspect off prioritization at D C level becomes very important, And what drives some of that prioritization is the analysis around what the upcoming sales would be for specific products for specific categories. And that's where again thoughts. But is one of the tools that we've utilized recently to set our prioritization logic from both inbound and outbound us. It's right because it gives you most recent results. It gives you most granular results, depending on the business problem that you're trying to tackle. Now let's chat a little bit about covert 19 response, because this one is an extremely interesting case as a pandemic hit back in March. Um, as you can imagine, the everyday life a Canadian entire became as business unusual is our executives referred to it under business unusual. This speed and the intensity of the insights and the analytics has grown exponentially. And the speed and the intensity of the insights is driven by the fact that we were trying Thio ensure that we have the right selection of products for our Canadian customers because that's ultimately bread and butter off all of the retailers is the customers, right? So thoughts bought allowed us to have early trends off both sales and inventory patterns, where, whether we were stalking out of some of the products in specific stories of provinces, whether we saw some of the upload off different lines of business, depending on the region, ality right as pandemic hit, for example, um, gym's closed restaurants closed. So as Canadian pack carries a wide variety of different lines of business, we actually offer a wide selection of exercise equipment and accessories, cycling products as well as the kitchen appliances and kitchen accessories pieces. Right? So all of those items started growing exponentially and in certain areas more than others. And this is where thoughts about comes into play. A typical analysis on what the region ality of the sales has been over the last couple of days, which is lifetime and pandemic terms, um, could have taken days weeks for analysts to ultimately cobbled together an Excel spreadsheet. Meanwhile, it can take a couple of seconds for 12 Korean tosspot set up a PIN board that can be shared through a wide variety of individuals rather than fording that one Excel spreadsheet that gets manipulated every single time. And then you don't get the right inside. So from again merch supply chain covert response aspect of things. That spot has been one of those blessings and one of those amazing tools to utilize and improve the speed off insights, improved the speed of analytics and improve the speed of decision making that's ultimately impacting, then consumer at the store level. So Andrea talked about 4500 users that we have that number of school. But what I owe the recently like to focus on, uh, Andrew and I laughing because I think the last time we've spoken at a larger forum with the fastball community, I think we had only 500 users. That was in the beginning >>of the year in in February, we were aiming to have like 1000 >>exactly. So mission accomplished. So we've got 4500 employees now. Everybody asked me, Yeah, that's a big number, but how many times do people actually log in on a weekly or daily basis? I'm or interested in that statistic? So lately, um, we've had more than 400 users on the weekly basis. What's what's been cool lately is, uh, the exponential growth off ad hoc ways. So throughout October, we've reached a 75,000 ad hoc ways in our system and about 13,000 PIN board views. So why is that's that's significant? We started off, I would say, in January of 2020 when Andrea refers to it, I think we started off with about 40 45,000 ad hoc worries a month. So again, that was cool. But at the end of the day, we were able to thio double that amount as more people migrate to act hawk searches from PIN board views, and that's that's a tremendous phenomena, because that's what that's about is all about. So I touched upon a little bit about exercise and cycling. So these are our quarterly results for Q two, um, that have showed tremendous growth that we did not plan for, that we were able to achieve with, ultimately the individuals who work throughout the organization, whether it's the merch organization or whether it's the supply chain side of the business. But coming together and utilizing a B I platform by tools such a hot spot, we can see triple digit growth results. Eso What's next for us users at Hawks searches? That's fantastic. I would still like to get to more than 1200 people on the weekly basis. The cool number to me is if all of our lifetime users were you were getting into the tool on a weekly basis. That would be cool. And what's proven to be true is ultimately the only way to achieve it is to keep surprising and delighting them and your surprising and delighting them with the functionality of the tool. With more of the relevant content and ultimately data adding in more data, um, is again possible through ET else, and it's possible through pulling that information manually. But it's expensive, expensive not from the sense of monetary value, but it's expensive from the size time, all of those aspects of things So what I'm looking forward to is migrating our platform to azure in snowflake and being able thio scale our insights accordingly. Toe adding more data to Adam or incites more, uh, more individual worksheets and data sets for people to Korea against helps the each one of the individuals learn. Get some of the insights. Helps my team in particular be, well, more well versed in the data that we have existing throughout the organization. Um, and then now Andrea, in touch upon how we scale it further and and how each one of the individuals can become better with this wonderful >>Yeah, soas used a zero mentioned theater hawk searches going up. It's sort of it's a little internal victory because our starting platform had really been thio build the pin boards to replicate what the users were already expecting. So that was sort of how we easily got people in. And then we just cut off the tap Thio, whatever the previous report waas. So it gave them away. Thio get into the tool and understand the information. So now that they're using ad hoc really means they understand the tool. Um, then they they have the data literacy Thio access the information and use it how they need. So that's it's a really cool piece. Um, that worked on for Canadian tire. A very report oriented and heavy organization. So it was a good starting platforms. So seeing those ad hoc searches go up is great. Um, one of the ways that we sort of scaled out of our initial group and I kind of mentioned this earlier I sort of stepped on my own toes here. Um is that once it was a proven success with the merchants and it started to spread through word of mouth and we sought out the analyst teams. Um, we really just kept sort of driving the insights, finding the data and learning more about the pieces of the business. As you would like to think he knows everything about everything. He only knows what he knows. Eso You have to continue to cultivate the internal champions. Um Thio really keep growing the adoption eso find this means that air excited about the possibility of using thought spot and what they can do with it. You need to find those people because they're the ones who are going to be excited to have this rapid access to the information and also to just be able to quickly spend less time telling a user had access it in thought spot. Then they would running the report because euro mentioned we basically hit a curiosity tax, right? You you didn't want to search for things or you didn't want to ask questions of the data because it was so conversed. Um, it was took too much time to get the data. And if you didn't know exactly what you were looking for, it was worse. So, you know, you wouldn't run a query and be like, Oh, that's interesting. Let me let me now run another query of all that information to get more data. Just not. It's not time effective or resource effective. Actually, at the point, eso scaling the adoption is really cultivating those people who are really into it as well. Um, from a personal development perspective, sort of as a user, I mean, one who doesn't like being smartest person in the room on bought spot sort of provides that possibility. Andi, it makes it easier for you to get recognized for delivering results on Dahlia ble insights and sort of driving the business forward. So you know, B b that all star be the Trailblazer with all the answers, and then you can just sort of find out what really like helping the organization realized the power of thought spot on, baby. Make it into a career. >>Amazing. I love love that you've joined us, Andrea. Such a such an amazing create trajectory. No bias that all of my s o heaps of great information there. Thank you both. So much for sharing your story on driving such amazing adoption and the impact that you've been able to make a T organization through. That we've got a couple of minutes remaining. So just enough time for questions. Eso Andrea. Our first questions for you from your experience. What is one thing you would recommend to new thoughts about users? >>Um, yeah, I would say Be curious and creative. Um, there's one phrase that we used a lot in training, which was just mess around in the tool. Um, it's sort of became a catchphrase. It is really true. Just just try and use it. You can't break. It s Oh, just just play around. Try it you're only limitation of what you're gonna find is your own creativity. Um, and the last thing I would say is don't get trapped by trying to replicate things. Is that exactly as they were? B, this is how we've always done it. Isin necessarily The the best move on day isn't necessarily gonna find new insights. Right. So the change forces you thio look at things from a different perspective on defined. Find new value in the data. >>Yeah, absolutely. Sage advice there. Andan another one here for Yaro. So I guess our theme for beyond this year is analytics meets Cloud Open for everyone. So, in your experience, what does What does that mean for you? >>Wonderful question. Yeah. Listen, Angela Okay, so to me, in short, uh, means scale and it means turning Yes. Sorry. No, into a yes. Uh, no, I'm gonna elaborate. Is interest is laughing at me a little bit. That's right. >>I can talk >>Fancy Two. Okay, So scale from the scale perspective Cloud a zai touched upon Throw our conversation on our presentation cloud enables your ability Thio store have more data, have access to more data without necessarily employing a number off PTL developers and going toe a number of security aspect of things in different data sources now turning a no into a yes. What does that mean with more data with more scalability? Um, the analytics possibilities become infinite throughout my career at Canadian Tire. Other organizations, if you don't necessarily have access thio data or you do not have the necessary granularity, you always tell individuals No, it's not possible. I'm not able to deliver that result. And quite often that becomes the norm, saying no becomes the norm. And I think what we're all striving towards here on this call Aziz part the conference is turning that no one say yes on then making a yes a new, uh, standard a new form. Um, as we have more access to the data, more access to the insights. So that would be my answer. >>Love it. Amazing. Well, that kind of brings in into this session. So thank you, everyone for joining us today on did wrap up this dream. Don't miss the upcoming product roadmap eso We'll be sticking around to speak thio some of the speakers you heard earlier today and I'll make the experts round table, and you can absolutely continue the conversation with this life. Q. On Q and A So you've got an opportunity here to ask questions that maybe keep you up at night. Perhaps, but yet stay tuned for the meat. The experts secrets to scaling analytics adoption after the product roadmap session. Thanks everyone. And thank you again for joining us. Guys. Appreciate it. >>Thank you. Thanks. Thanks.

>>Yeah, yeah. >>Welcome back, everyone. And let's get ready for session number two, which is all around picking the right use cases. We're going to take a look at how to make the most of your data driven journey through the lens of some instructive customer examples. So today we're joined by thought squads David Copay, who is a director of business value consulting like Daniel, who's a customer success manager and then engagement manager. Andrea Frisk, who not so long ago was actually a product manager. Canadian Tire, who are one of our customers. And she was responsible for the thoughts. What implementation? So we figured Who better to get involved? But yeah, let's Let's take it away, David. >>Thanks, Gina. Welcome, everybody. And Andrea Blake looking forward to this session with you. A zoo. We all know preparation early is key to success on Duin. Any project having the right team on sponsorship Thio, build and deploy. Ah, use case is critical being focused on three outcome that you have in mind both the business deliverables and then also the success criteria of how you're going to manage, uh, manage and define success. When you get there, Eyes really critical to to set you up in the right direction initially. So, Andrea, as as we mentioned, uh, you came from an organization that quite several use cases on thoughts about. So maybe you can talk us through some of those preparation steps that, yeah, that you went through and and share some insights on how folks can come prepare appropriately. >>Eso having the right team members makes such a difference. Executive support really helped the Canadian tire adoption spread. It gave the project presence and clout in leadership meetings and helped to drive change from the top down. We had clear goals and success criteria from our executive that we used to shape the go forward plan with training and frame the initial use case roadmap. One of the other key benefits over executive sponsor was that the reporting team for our initial use case rolled up by underhand. So there was a very clear directive for a rapid phase out of the old tools once thought Spot supported the same data story. And this is key because as you start to roll through use cases, you wanna realize the value. And if you're still executing the old the same time as the new. That's not gonna happen. As we expanded into areas where we were unfamiliar with the data in business utilization, we relied on the data experts and and users to inform what success would look like in the new use cases. We learned early on that those who got volunteer old and helping didn't always become the champions. That would help you drive value from the use case. Using the thoughts about it meant tables. We started to seek out users who are consistently logging in after an initial training, indicating their curiosity and appetite to learn more. We also looked for activities outside of just pin board views toe identify users that had the potential to build and guide new users as subject matter experts, not just in a data but in thought spot. This helps us find the right people to cultivate who were already excited about the potential of thought spot and could help us champion a use case. >>That's really helpful, great, great insight for someone who's been there and done that. Blake is as a customer success manager. Obviously, you approach many of the same situations, anything you'd like to add that >>I still along with the right team. My first question with any use cases. Why Why are we doing this? You've gathered all this data and now we want to use it. But But what for? When you get that initial response on Why this use case? Don't stop there. Keep asking Why keep digging? Keep digging. Keep digging. So what you're essentially trying to get at is what does the decision is that we will be made or potentially be made because of this use case. For example, let's say that we're looking at an expenses use case. What will be done with the insides gathered with this use case? Are those insights going? Thio change the expense approval process Now, Once you have that, why defined now it becomes a lot easier to define the success criteria. Success criteria they use. Face can sometimes be difficult to truly defined. But when you understand why it becomes much easier, so now you can document that success criteria. And the hard part at that point is to actually track that success over time, track the success of the use case, which is something that is easily miss but It's something that is incredibly useful to the overall initiative. >>Right measure. Measure the outcomes. You can't manage what you what? You can't what you don't measure right? As the old adage goes, and you know it's part of the business consulting team. That's really where we come in. Is helping customers really fundamentally define? How are we going to measure a success? Aziz. We move forward. Andi, I think you know, I think we've alluded to this a little bit in terms of that sort of ongoing nature of This is, you know, after the title of the session, eyes choosing the right news cases in the plural right? So it's very important to remember that this is not a single point in time event that happens once. This is a constant framework or process, because most organizations will find that there's many use cases, potentially dozens of use cases that thoughts what could be used for, and clearly you can't move forward with all of them. At the same time, eso. Another thing that our team helps customers walk through is what's the impact, the potential value, other particular use case. You know, you, Blake, you mentioned some of those outcomes, is it? Changing the expense processes it around? Reducing customer churn is an increasing speed toe insight and speak the market on defining those measurable outcomes that define the vertical axis here. The strategic importance off that use case. Um, but that's not the only dimension that you're gonna look at the East to deploy factors into that you could have the most valuable use case ever. But if it's going to take you to three years to get it implemented for various reasons, you're not really gonna start with that one, right? So the combination of east to deploy, aligned with the strategic importance or business value really gives you that road map of where to focus to prioritize on use cases. Eso again, Andrea, you've been through this, um, in your prior time at Canadian time. Maybe you can share some thoughts on how you approach that. >>Yeah. So our initial use case was a great launching platform because the merchandizing team had a huge amount across full engagement. So once we had the merchants on board, we started to plan or use case roadmap looking for other areas, and departments were thought spot had already started to spread by word of mouth and we where we felt there was a high strategic importance. As we started to scope these areas, the ease of deployment started to get more complicated. We struggled to get the right people engaged and didn't always have the top down support for resources in the new use case area. We wanted to maintain momentum with the adoption, but it was starting to feel like we were stalling out on the freeway. Then the strategic marketing team reached out and was really excited about getting into thought spot. This was an underserved team where when it came to data, they always had someone else running it for them, and they'd have to request reports and get the information in. Um, and our initial roadmap focused on the biggest impact areas where we could get the most users, and this team was not on the radar. But when we started to engage with them, we realized that this was gonna be an easy deployment. We already had the data and thought spot to support their needs, and it turned into such a great win because as a marketing team, they were so thrilled to have thought spot and to get the data when they needed it and wanted it. They continued to spread the word and let everyone know. But it also gave the project team a quick win to put some gas in the tank and keep us moving. So you want to plan your use case trajectory, but you also need to be willing to adapt to keep the momentum going. >>Yeah, no, that's a That's a really great point. So So Blake is a customer success manager. I'm sure you lived through some integration of this all the time. So any anything you wanted to add that >>Yes. So to Andrew's point, continuous delivery is key for technical folks out there were talking and agile methodology mindset versus a waterfall. So to show value, there's many different factors that air at play. You need to look at the overall business initiatives. We need to look at financial considerations. We need to look at different career objectives and also resource limitations. So when you start thinking about all those different factors, this becomes a mixture of art and science. So, for example, at the beginning of a project when thought spot is has just been purchased or whatever tool has just been purchased. You want to show immediate value to justify that purchase. So in order to show immediate value, you might want to look at a project or a use case that is tightly aligned to a business objective. Therefore, it shows value, and it has data that is ready to go without many different transformations. But as you move forward, you have to come up with a plan that is going to mix together these difficult use cases with the easier use cases and high business values cases versus the lower. So in order to do that, my most successful customers are evaluating those different business factors and putting those into place with an overall use case development plan. >>Really good feedback. That's great. Thank you. Thanks, Blake. Um, I think s a little bit of a reality check here. Right. So I think we all recognize that any technology implementation, um, is gonna have her bumps in the road. It's not gonna be smooth sailing all along the way. You know, we talk about people, process and technology. The technology wrote wrote roadblocks can be infrastructure related there could be some of the data quality issues that you're alluding to there. Like Onda, people in process fall into the sort of the cultural, uh, cultural cultural side of it. Blake, maybe you can spend a couple minutes going through. What? What if some of those bigger roadblocks that people may face on that, um, technical side on how they could both prepare for them and then address them as they come along? >>Yeah. So the most intimidating part of any business intelligence or analytics initiative is that it's going to put the data directly into the hands of the business users. And this is especially true with ocelot. So why this is intimidating is because it's going toe, lay bare and expose any data issues that exist. So this is going to lead to the most common objective that I hear to starting. Any new use case or any FBI initiative overall, which is our data isn't ready. And essentially that is fear of failure. So when data isn't ready and companies aren't ready to start these projects, what happens is to get around those data issues. There's a lot of patchwork that's happening, you know, this patchwork is necessary just to keep the wheels in motion just to keep things going. So what I mean by the patchwork is extracting the data from a source doing some manual manipulation, doing some manipulation directly within the within the database in order to satisfy those business users request. So this keeps things going, but it's not addressing the key issues that are in place now. While it's intimidating to start these initiatives, the beauty of starting these B I initiatives is it's going to force your company to address and fix these issues. And this, to me, is somewhere where thoughts what is a gigantic benefit? It's not something that we talk about necessarily or market, but thought Spot is really good at helping fix these data issues. And I say this for two reasons. One his data quality. So, with thoughts about you can run, searches directly against your most granular level data and find where those data issues exist, and now, especially with embrace, you're running it directly against the source. So thats what is going to really help you figure out those data quality issues. So as you develop a use case, we can uncover those data quality issues and address them accordingly. And second is data governance. So especially again with embrace and our cloud, our cloud structure is you are going to be bringing Companies are going to be bringing data sources from all over the place all into one source and into one logical view. And so traditionally, the problem with that is that your data and source a might be the theoretically the same data and source B. But the numbers are different. And so you have different versions of the truth. So what thoughts about helps you do is when you bring those sources together. Now you're gonna identify those issues, and now you're gonna be forced to address them. You're gonna be forced to address naming convention issues, business logic issues, which business logic translates to the technical logic toe transform that data and then also security and access. Who was actually able to see this data across these different data sources. So overall, the biggest objective eye here is our data isn't ready. But I challenge that. And I say that by taking on this initiative with thought spot, you were going to be directly addressing that issue and thoughts. What's going to help you fix it? >>Yeah, that's Ah, I'd love that observation that, you know, data quality issues. They're not gonna go away by themselves. And if thoughts, thoughts what could be part of the solution, then even better. So that's a That's a really great observation. Eso Andrea, looking at the sort of the cultural side of things the people in process, Um, what are some of the challenges that you've seen there that folks in the audience could that could learn from? >>Yeah. So think about the last time you learned a new system or tool. How long did it take you to get adjusted and get the performance you wanted from it? Maybe you hit the ground running, but maybe you still feel like you're not quite getting the most out of it. Everyone deals with change differently, and sometimes we get stuck in the change curve and never fully adapt. Companies air no different. Ah, lot of the roadblocks you may face are not only from individual struggling to get on board, but can be the result of an organizational culture that may not be used to change or managing it. Their external impacts on how we accept change such as Was there a clear message about the upcoming changes and impacts? Was there a communication channel for questions and concerns? Did individuals feel like their input was sought after and valued? Where there are multiple mediums, toe learn from was their time to learn? Organizational change is hard. And if there isn't a culture that allocates time and resources to training, then realizing success is gonna be an uphill battle. It will be harder to move people forward if they don't have the time to get comfortable and feel acclimated to the new way of doing things. Without the training and change support from the organization, you'll end up running the old and the new simultaneously, which we talked about not in our live supporting users, in both eyes going to negate that value. There were times at Canadian Tire where we really struggled to get key stakeholders engaged or to get leadership by it on the time of the resources that we're gonna be needed and committed Thio to make a use case successful. So gauging where people and the organization are in the change curve is the first step in moving them along the path towards acceptance and integration. So you'll wanna have an action plan to address the concerns and resistance and a way to solicit and channel feedback. >>Yeah, that's Zo great feedback. And I particularly like what you talked about sort of the old and the new because, you know, we've talked about success and measurement on value quite a bit in this session, and ultimately that's that's the goal, right? Is to live a Value s o. This is a framework that we found really helpful visit. Value Team is defining those success criteria really actually falls into two categories on the right hand side. Better decisions. Um, that's ultimately what you're looking to drive with thoughts about right. You're looking to get newer inside faster to be able to drive action and outcomes based on decisions that do. Maybe we're using your gut for previously on the words under that heading. They're going to change by organizations. So you know, those don't get too caught up on those, but it's really around defining, you know, one. Are those better decisions that you're looking to drive, Who what's the persona is gonna be making them one of their actually looking to accomplish when inside. So they're looking to get one of what are the actions they're going to take on those insights? And then how do we measure Thean pact of those actions that then provides us with the the foundation of a business case in our I, um, in parallel to that, it's important to remember that this use case is not just operating in a vacuum, right? Every organization has a Siri's off strategic transformational initiatives move to the cloud democratized data, etcetera. And to the extent that you can tie particular use cases into those key strategic initiatives, really elevates the importance off that use case outside of its own unique business case. In our calculation on Bazzaz several purposes, right, it raises the visibility project. It raises the visibility of the person championing project on. Do you know reality here is that every idea organization has tons of projects have taken invest in, but the ones they're gonna be more likely to invest in other ones that are tied to those strategic initiatives. So it increases the likelihood of getting the support and funding that you need to drive this forward um, that's really around defining the success success criteria upfront. Um, and >>what >>we find is a lot of organizations do that pretty well, and they've got a solid, really solid business case to move forward. But then over time, they kind of forget about that on. Do you know, a year down the line two years down the line, Maybe even, you know, three months, six months down the line. Maybe people have rotated through the business. People have come and gone, and you almost forget the benefit that you're driving, right? And so it's really important to not do that and keep an eye on and track Onda, look back and analyze and realize the value that use cases have driven on. Obviously, the structure of that and what you measure is gonna very significantly by escape. But it's really important there Thio to make sure that you're counting your success and measuring your success. Um, Andrea, I don't any any thoughts on that from from your past experience. >>Yeah, um, success will be different For each use case, 1 may be focused on reducing the time to insights in a fast competitive market, while another may be driven by a need to increase data fluency to reduce risk. The weighting of each of these criterias will shift and and the value perception should as well. Um, but one thing that we don't want to forget is to share your personal successes. So be proud of the work that you've done in the value it's created. Um, if you're a user who has taken advantage of thought spot and managed to grab a competitive edge by having faster in depth access to data, share that in your business reviews. If you're managing the adoption at your company, share your use case winds and user adoption stories. Your customer success team is here to help you articulate the value and leverage the great work being done in and because of thought spot. >>Yeah, long story short here. This benefits everybody. This is something that's easily overlooked and something that it ZZ not to do this to track adoption to define the r o I, but it benefits those benefits. Start spot benefits of customers. Everybody wins. When we do this, >>that's Ah, that's a great point. So, um, so if we talk about you know, as we wrap the session up. You know what can what can folks in the audience dio right now to start making some of this stuff happened? You know, you're Blake again, coming back to you in customer success. How have you and your role help customers take that next step and start executing on some of the things that we've talked about? >>Yeah. So to start off with, I would just say for each use case as much as possible, define the why and to find the success criteria. Just start off with those two, those two elements and over time that that process we'll get more and more refined and our goal within the CSCE or within within thoughts. But overall, not just the C s order is to enable all of our all of our customers to be able to do all these things on their own. And to be a successful, it's possible to be able to pick the right use cases to be able to execute those right use cases as effectively as possible. So we are here to help with that. CS is here to help with that. Your account executives here to help with that, we have use case workshops. We have our professional services team that can get in and help develop use cases. So lots of options available in goal. We all mutually benefit when we try to track towards thes best possible use cases. >>All right, that we're here to help. That's Ah, that's a great way. Thio, wrap up the session there. Thanks, Blake. For all of your thoughts and Andrea to hope everyone in the audience got some valuable insights here on how to choose the right news case and be successful with thoughts about, um, with that being, I'll hand it back over to you. >>Amazing. That was an awesome session. Thank you so much, guys. So our third session is up next, and we're going to be going Global s. Oh, hang on tight as we explore best practices from the extended ecosystem of cloud based analytics. >>Yeah,

>>Hello, everyone, and welcome to track three off beyond. My name is being in Yemen and I am an account executive here at Thought spot based out of our London office. If the accents throwing you off I don't quite sound is British is you're expecting it because the backgrounds Australian so you can look forward to seeing my face. As we go through these next few sessions, I'm gonna be introducing the guests as well as facilitating some of the Q and A. So make sure you come and say hi in the chat with any comments, questions, thoughts that you have eso with that I mean, this whole track, as the title somewhat gives away, is really about everything that you need to know and all the tips and tricks when it comes to adoption and making sure that your thoughts what deployment is really, really successful. We're gonna be taking off everything from user training on boarding new use cases and picking the right use cases, as well as hearing from our customers who have been really successful in during this before. So with that, though, I'm really excited to introduce our first guest, Kathleen Maley. She is a senior analytics executive with over 15 years of experience in the space. And she's going to be talking to us about all her tips and tricks when it comes to making the most out of your center of excellence from obviously an analytics perspective. So with that, I'm going to pass the mic to her. But look forward to continuing the chat with you all in the chat. Come say hi. >>Thank you so much, Bina. And it is really exciting to be here today, thanks to everyone for joining. Um, I'll jump right into it. The topic of evolving your analytics center of excellence is a particular passion of mine on I'm looking forward to sharing some of my best practices with you. I started my career, is a member of an analytic sioe at Bank of America was actually ah, model developer. Um, in my most recent role at a regional bank in the Midwest, I ran an entire analytics center of excellence. Um, but I've also been on the business side running my own P and l. So I think through this combination of experiences, I really developed a unique perspective on how to most effectively establish and work with an analytic CEO. Um, this thing opportunity is really a two sided opportunity creating value from analytics. Uh, and it really requires the analytics group and the line of business Thio come together. Each has a very specific role to play in making that happen. So that's a lot of what I'll talk about today. Um, I started out just like most analysts do formally trained in statistics eso whether your data analyst or a business leader who taps into analytical talent. I want you to leave this talk today, knowing the modern definition of analytics, the purpose of a modern sioe, some best practices for a modern sioe and and then the role that each of you plays in bringing this Kuito life. So with that said, let me start by level, setting on the definition of analytics that aligns with where the discipline is headed. Um, versus where it's been historically, analytics is the discovery, interpretation and communication of meaningful patterns in data, the connective tissue between data and effective decision making within an organization. And this is a definition that I've been working under for the last, you know, 7 to 10 years of my career notice there is nothing in there about getting the data. We're at this amazing intersection of statistics and technology that effectively eliminates getting the data as a competitive advantage on this is just It's true for analysts who are thinking in terms of career progression as it is for business leaders who have to deliver results for clients and shareholders. So the definition is action oriented. It's purposeful. It's not about getting the data. It's about influencing and enabling effective decision making. Now, if you're an analyst, this can be scary because it's likely what you spend a huge amount of your time doing, so much so that it probably feels like getting the data is your job. If that's the case, then the emergence of these new automated tools might feel like your job is at risk of becoming obsolete. If you're a business leader, this should be scary because it means that other companies air shooting out in front of you not because they have better ideas, necessarily, but because they can move so much faster. According to new research from Harvard Business Review, nearly 90% of businesses say the more successful when they equipped those at the front lines with the ability to make decisions in the moment and organizations who are leading their industries and embracing these decision makers are delivering substantial business value nearly 50% reporting increased customer satisfaction, employee engagement, improve product and service quality. So, you know, there there is no doubt that speed matters on it matters more and more. Um, but if you're feeling a little bit nervous, I want you to think of it. I want you think of it a little differently. Um, you think about the movie Hidden figures. The job of the women in hidden figures was to calculate orbital trajectories, uh, to get men into space and then get them home again. And at the start of the movie, they did all the required mathematical calculations by hand. At the end of the movie, when technology eliminated the need to do those calculations by hand, the hidden figures faced essentially the same decision many of you are facing now. Do I become obsolete, or do I develop a new set of, in their case, computer science skills required to keep doing the job of getting them into space and getting them home again. The hidden figures embraced the latter. They stayed relevant on They increase their value because they were able to doom or of what really mattered. So what we're talking about here is how do we embrace the new technology that UN burdens us? And how do we up skill and change our ways of working to create a step function increase in data enabled value and the first step, really In evolving your analytics? Dewey is redefining the role of analytics from getting the data to influencing and enabling effective decision making. So if this is the role of the modern analyst, a strategic thought partner who harnesses the power of data and directs it toward achieving specific business outcomes, then let's talk about how the series in which they operate needs change to support this new purpose. Um, first, historical CEOs have primarily been about fulfilling data requests. In this scenario, C always were often formed primarily as an efficiency measure. This efficiency might have come in the form of consistency funds, ability of resource is breaking down silos, creating and building multipurpose data assets. Um, and under the getting the data scenario that's actually made a lot of sense for modern Sealy's, however, the objective is to create an organization that supports strategic business decision ing for individuals and for the enterprises the whole. So let's talk about how we do that while maintaining the progress made by historical seaweeds. It's about really extending its extending what, what we've already done the progress we've already made. So here I'll cover six primary best practices. None is a silver bullet. Each needs to fit within your own company culture. But these air major areas to consider as you evolve your analytics capabilities first and foremost always agree on the purpose and approach of your Coe. Successfully evolving yourself starts with developing strategic partnerships with the business leaders that your organization will support that the analytics see we will support. Both parties need to explicitly blocked by in to the objective and agree on a set of operating principles on bond. I think the only way to do that is just bringing people to the table, having an open and honest conversation about where you are today, where you wanna be and then agree on how you will move forward together. It's not about your organization or my organization. How do we help the business solve problems that, you know, go beyond what what we've been able to do today? So moving on While there's no single organizational model that works for everyone, I generally favor a hybrid model that includes some level of fully dedicated support. This is where I distinguish between to whom the analyst reports and for whom the analyst works. It's another concept that is important to embrace in spirit because all of the work the analyst does actually comes from the business partner. Not from at least it shouldn't come from the head of the analytic Center of excellence. Andan analysts who are fully dedicated to a line of business, have the time in the practice to develop stronger partnerships to develop domain knowledge and history on those air key ingredients to effectively solving business problems. You, you know, how can you solve a problem when you don't really understand what it is? So is the head of an analytic sioe. I'm responsible for making sure that I hire the right mix of skills that I can effectively manage the quality of my team's work product. I've got a specialized skill set that allows me to do that, Um, that there's career path that matters to analysts on all of the other things that go along with Tele management. But when it comes to doing the work, three analysts who report to me actually work for the business and creating some consistency and stability there will make them much more productive. Um, okay, so getting a bit more, more tactical, um, engagement model answers the question. Who do I go to When? And this is often a question that business partners ask of a centralized analytics function or even the hybrid model. Who do I go to win? Um, my recommendation. Make it easy for them. Create a single primary point of contact whose job is to build relationships with a specific partner set of partners to become deeply embedded in their business and strategies. So they know why the businesses solving the problems they need to solve manage the portfolio of analytical work that's being done on behalf of the partner, Onda Geun. Make it make it easy for the partner to access the entire analytics ecosystem. Think about the growing complexity of of the current analytics ecosystem. We've got automated insights Business Analytics, Predictive modeling machine learning. Um, you Sometimes the AI is emerging. Um, you also then have the functional business questions to contend with. Eso This was a big one for me and my experience in retail banking. Uh, you know, if if I'm if I'm a deposits pricing executive, which was the line of business role that I ran on, I had a question about acquisitions through the digital channel. Do I talk Thio the checking analyst, Or do I talk to the digital analyst? Um, who owns that question? Who do I go to? Eso having dedicated POC s on the flip side also helps the head of the center of excellence actually manage. The team holistically reduces the number of entry points in the complexity coming in so that there is some efficiency. So it really is a It's a win win. It helps on both sides. Significantly. Um, there are several specific operating rhythms. I recommend each acting as a as a different gear in an integrated system, and this is important. It's an integrated decision system. All of these for operating rhythms, serves a specific purpose and work together. So I recommend a business strategy session. First, UM, a portfolio management routine, an internal portfolio review and periodic leadership updates, and I'll say a little bit more about each of those. So the business strategy session is used to set top level priorities on an annual or semiannual basis. I've typically done this by running half day sessions that would include a business led deep dive on their strategy and current priorities. Again, always remembering that if I'm going to try and solve all the business problem, I need to know what the business is trying to achieve. Sometimes new requester added through this process often time, uh, previous requests or de prioritized or dropped from the list entirely. Um, one thing I wanna point out, however, is that it's the partner who decides priorities. The analyst or I can guide and make recommendations, but at the end of the day, it's up to the business leader to decide what his or her short term and long term needs and priorities are. The portfolio management routine Eyes is run by the POC, generally on a biweekly or possibly monthly basis. This is where new requests or prioritize, So it's great if we come together. It's critical if we come together once or twice a year to really think about the big rocks. But then we all go back to work, and every day a new requests are coming up. That pipeline has to be managed in an intelligent way. So this is where the key people, both the analyst and the business partners come together. Thio sort of manage what's coming in, decking it against top priorities, our priorities changing. Um, it's important, uh, Thio recognize that this routine is not a report out. This routine is really for the POC who uses it to clarify questions. Raised risks facilitate decisions, um, from his partners with his or her partner so that the work continues. So, um, it should be exactly as long as it needs to be on. Do you know it's as soon as the POC has the information he or she needs to get back to work? That's what happens. An internal portfolio review Eyes is a little bit different. This this review is internal to the analytics team and has two main functions. First, it's where the analytics team can continue to break down silos for themselves and for their partners by talking to each other about the questions they're getting in the work that they're doing. But it's also the form in which I start to challenge my team to develop a new approach of asking why the request was made. So we're evolving. We're evolving from getting the data thio enabling effective business decision ing. Um, and that's new. That's new for a lot of analysts. So, um, the internal portfolio review is a safe space toe asks toe. Ask the people who work for May who report to May why the partner made this request. What is the partner trying to solve? Okay, senior leadership updates the last of these four routines, um, less important for the day to day, but significantly important for maintaining the overall health of the SIOE. I've usually done this through some combination of email summaries, but also standing agenda items on a leadership routine. Um, for for me, it is always a shared update that my partner and I present together. We both have our names on it. I typically talk about what we learned in the data. Briefly, my partner will talk about what she is going to do with it, and very, very importantly, what it is worth. Okay, a couple more here. Prioritization happens at several levels on Dive. Alluded to this. It happens within a business unit in the Internal Portfolio review. It has to happen at times across business units. It also can and should happen enterprise wide on some frequency. So within business units, that is the easiest. Happens most frequently across business units usually comes up as a need when one leader business leader has a significant opportunity but no available baseline analytical support. For whatever reason. In that case, we might jointly approach another business leader, Havenaar Oi, based discussion about maybe borrowing a resource for some period of time. Again, It's not my decision. I don't in isolation say, Oh, good project is worth more than project. Be so owner of Project Be sorry you lose. I'm taking those. Resource is that's It's not good practice. It's not a good way of building partnerships. Um, you know that that collaboration, what is really best for the business? What is best for the enterprise, um, is an enterprise decision. It's not a me decision. Lastly, enterprise level part ization is the probably the least frequent is aided significantly by the semi annual business strategy sessions. Uh, this is the time to look enterprise wide. It all of the business opportunities that play potential R a y of each and jointly decide where to align. Resource is on a more, uh, permanent basis, if you will, to make sure that the most important, um, initiatives are properly staffed with analytical support. Oxygen funding briefly, Um, I favor a hybrid model, which I don't hear talked about in a lot of other places. So first, I think it's really critical to provide each business unit with some baseline level of analytical support that is centrally funded as part of a shared service center of excellence. And if a business leader needs additional support that can't otherwise be provided, that leader can absolutely choose to fund an incremental resource from her own budget that is fully dedicated to the initiative that is important to her business. Um, there are times when that privatization happens at an enterprise level, and the collective decision is we are not going to staff this potentially worthwhile initiative. Um, even though we know it's worthwhile and a business leader might say, You know what? I get it. I want to do it anyway. And I'm gonna find budget to make that happen, and we create that position, uh, still reporting to the center of excellence for all of the other reasons. The right higher managing the work product. But that resource is, as all resource is, works for the business leader. Um, so, uh, it is very common thinking about again. What's the value of having these resource is reports centrally but work for the business leader. It's very common Thio here. I can't get from a business leader. I can't get what I need from the analytics team. They're too busy. My work falls by the wayside. So I have to hire my own people on. My first response is have we tried putting some of these routines into place on my second is you might be right. So fund a resource that's 100% dedicated to you. But let me use my expertise to help you find the right person and manage that person successfully. Um, so at this point, I I hope you see or starting to see how these routines really work together and how these principles work together to create a higher level of operational partnership. We collectively know the purpose of a centralized Chloe. Everyone knows his or her role in doing the work, managing the work, prioritizing the use of this very valuable analytical talent. And we know where higher ordered trade offs need to be made across the enterprise, and we make sure that those decisions have and those decision makers have the information and connectivity to the work and to each other to make those trade offs. All right, now that we've established the purpose of the modern analyst and the functional framework in which they operate, I want to talk a little bit about the hard part of getting from where many individual analysts and business leaders are today, uh, to where we have the opportunity to grow in order to maintain pain and or regain that competitive advantage. There's no judgment here. It's simply an artifact. How we operate today is simply an artifact of our historical training, the technology constraints we've been under and the overall newness of Applied analytics as a distinct discipline. But now is the time to start breaking away from some of that and and really upping our game. It is hard not because any of these new skills is particularly difficult in and of themselves. But because any time you do something, um, for the first time, it's uncomfortable, and you're probably not gonna be great at it the first time or the second time you try. Keep practicing on again. This is for the analyst and for the business leader to think differently. Um, it gets easier, you know. So as a business leader when you're tempted to say, Hey, so and so I just need this data real quick and you shoot off that email pause. You know it's going to help them, and I'll get the answer quicker if I give him a little context and we have a 10 minute conversation. So if you start practicing these things, I promise you will not look back. It makes a huge difference. Um, for the analyst, become a consultant. This is the new set of skills. Uh, it isn't as simple as using layman's terms. You have to have a different conversation. You have to be willing to meet your business partner as an equal at the table. So when they say, Hey, so and so can you get me this data You're not allowed to say yes. You're definitely not is not to say no. Your reply has to be helped me understand what you're trying to achieve, so I can better meet your needs. Andi, if you don't know what the business is trying to achieve, you will never be able to help them get there. This is a must have developed project management skills. All of a sudden, you're a POC. You're in charge of keeping track of everything that's coming in. You're in charge of understanding why it's happening. You're responsible for making sure that your partner is connected across the rest of the analytics. Um, team and ecosystem that takes some project management skills. Um, be business focused, not data focused. Nobody cares what your algorithm is. I hate to break it to you. We love that stuff on. We love talking about Oh, my gosh. Look, I did this analysis, and I didn't think this is the way I was gonna approach it, and I did. I found this thing. Isn't it amazing? Those are the things you talk about internally with your team because when you're doing that, what you're doing is justifying and sort of proving the the rightness of your answer. It's not valuable to your business partner. They're not going to know what you're talking about anyway. Your job is to tell them what you found. Drawing conclusions. Historically, Analyst spent so much of their time just getting data into a power 0.50 pages of summarized data. Now the job is to study that summarized data and draw a conclusion. Summarized data doesn't explain what's happening. They're just clues to what's happening. And it's your job as the analyst to puzzle out that mystery. If a partner asked you a question stated in words, your answer should be stated in words, not summarized data. That is a new skill for some again takes practice, but it changes your ability to create value. So think about that. Your job is to put the answer on page with supporting evidence. Everything else falls in the cutting room floor, everything. Everything. Everything has to be tied to our oi. Um, you're a cost center and you know, once you become integrated with your business partner, once you're working on business initiatives, all of a sudden, this actually becomes very easy to do because you will know, uh, the business case that was put forth for that business initiative. You're part of that business case. So it becomes actually again with these routines in place with this new way of working with this new way of thinking, it's actually pretty easy to justify and to demonstrate the value that analytic springs to an organization. Andi, I think that's important. Whether or not the organization is is asking for it through formalized reporting routine Now for the business partner, understand that this is a transformation and be prepared to support it. It's ultimately about providing a higher level of support to you, but the analysts can't do it unless you agree to this new way of working. So include your partner as a member of your team. Talk to them about the problems you're trying to sell to solve. Go beyond asking for the data. Be willing and able to tie every request to an overarching business initiative on be poised for action before solution is commissioned. This is about preserving. The precious resource is you have at your disposal and you know often an extra exploratory and let it rip. Often, an exploratory analysis is required to determine the value of a solution, but the solution itself should only be built if there's a plan, staffing and funding in place to implement it. So in closing, transformation is hard. It requires learning new things. It also requires overriding deeply embedded muscle memory. The more you can approach these changes is a team knowing you won't always get it right and that you'll have to hold each other accountable for growth, the better off you'll be and the faster you will make progress together. Thanks. >>Thank you so much, Kathleen, for that great content and thank you all for joining us. Let's take a quick stretch on. Get ready for the next session. Starting in a few minutes, you'll be hearing from thought spots. David Coby, director of Business Value Consulting, and Blake Daniel, customer success manager. As they discuss putting use cases toe work for your business

>>welcome back. And thanks for joining us for our second session. External data, your new leading indicators. We'll be hearing from industry leaders as they share best practices and challenges in leveraging external data. This panel will be a true conversation on the part of the possible. All right, let's get to >>it >>today. We're excited to be joined by thought spots. Chief Data Strategy Officer Cindy Housing Deloitte's chief data officer Manteo, the founder and CEO of Eagle Alfa. And it Kilduff and Snowflakes, VP of data marketplace and customer product strategy. Matt Glickman. Cindy. Without further ado, the floor is yours. >>Thank you, Mallory. And I am thrilled to have this brilliant team joining us from around the world. And they really bring each a very unique perspective. So I'm going to start from further away. Emmett, Welcome. Where you joining us from? >>Thanks for having us, Cindy. I'm joining from Dublin, Ireland, >>great. And and tell us a little bit about Eagle Alfa. What do you dio >>from a company's perspective? Think of Eagle Alfa as an aggregator off all the external data sets on a word I'll use a few times. Today is a big advantage we could bring companies is we have a data concierge service. There's so much data we can help identify the right data sets depending on the specific needs of the company. >>Yeah. And so, Emma, you know, people think I was a little I kind of shocked the industry. Going from gardener to a tech startup. Um, you have had a brave journey as well, Going from financial services to starting this company, really pioneering it with I think the most data sets of any of thes is that right? >>Yes, it was. It was a big jump to go from Morgan Stanley. Uh, leave the comforts of that environment Thio, PowerPoint deck and myself raising funding eight years ago s So it was a big jump on. We were very early in our market. It's in the last few years where there's been real momentum and adoption by various types of verticals. The hedge funds were first, maybe then private equity, but corporate sar are following quite quickly from behind. That will be the biggest users, in our view, by by a significant distance. >>Yeah, great. Thank um, it So we're going to go a little farther a field now, but back to the U. S. So, Juan, where you joining us from? >>Hey, Cindy. Thanks for having me. I'm joining you from Houston, Texas. >>Great. Used to be my home. Yeah, probably see Rice University back there. And you have a distinct perspective serving both Deloitte customers externally, but also internally. Can you tell us about that? >>Yeah, absolutely. So I serve as the Lord consultants, chief data officer, and as a professional service firm, I have the responsibility for overseeing our overall data agenda, which includes both the way we use data and insights to run and operate our own business, but also in how we develop data and insights services that we then take to market and how we serve our dealers and clients. >>Great. Thank you, Juan. And last but not least, Matt Glickman. Kind of in my own backyard in New York. Right, Matt? >>Correct. Joining I haven't been into the city and many months, but yes, um, based in New York. >>Okay. Great. And so, Matt, you and Emmett also, you know, brave pioneers in this space, and I'm remembering a conversation you and I shared when you were still a J. P. Morgan, I believe. And you're Goldman Sachs. Sorry. Sorry. Goldman. Can you Can you share that with us? >>Sure. I made the move back in 2015. Um, when everyone thought, you know, my wife, my wife included that I was crazy. I don't know if I would call it Comfortable was emitted, but particularly had been there for a long time on git suffered in some ways. A lot of the pains we're talking about today, given the number of data, says that the amount of of new data sets that are always demand for having run analytics teams at Goldman, seeing the pain and realizing that this pain was not unique to Goldman Sachs, it was being replicated everywhere across the industry, um, in a mind boggling way and and the fortuitous, um, luck to have one of snowflakes. Founders come to pitch snowflake to Goldman a little bit early. Um, they became a customer later, but a little bit early in 2014. And, you know, I realized that this was clearly, you know, the answer from first principles on bond. If I ever was going to leave, this was a problem. I was acutely aware of. And I also was aware of how much the man that was in financial services for a better solution and how the cloud could really solve this problem in particular the ability to not have to move data in and out of these organizations. And this was something that I saw the future of. Thank you, Andi, that this was, you know, sort of the pain that people just expected to pay. Um, this price if you need a data, there was method you had thio. You had to use you either ftp data in and out. You had data that was being, you know, dropped off and, you know, maybe in in in a new ways and cloud buckets or a P i s You have to suck all this data down and reconstruct it. And God forbid the formats change. It was, you know, a nightmare. And then having issues with data, you had a what you were seeing internally. You look nothing like what the data vendors were seeing because they want a completely different system, maybe model completely differently. Um, but this was just the way things were. Everyone had firewalls. Everyone had their own data centers. There was no other way on git was super costly. And you know this. I won't even share the the details of you know, the errors that would occur in the pain that would come from that, Um what I realized it was confirmed. What I saw it snowflake at the time was once everyone moves to run their actual workloads in this in the cloud right where you're now beyond your firewall, you'll have all this scale. But on top of that, you'll be able to point at data from these vendors were not there the traditional data vendors. Or, you know, this new wave of alternative data vendors, for example, like the ones that eagle out for brings together And bring these all these data sets together with your own internal data without moving it. Yeah, this was a fundamental shift of what you know, it's in some ways, it was a side effect of everyone moving to the cloud for costs and scale and elasticity. But as a side effect of that is what we talked about, You know it snowflake summit, you know, yesterday was this notion of a data cloud that would connect data between regions between cloud vendors between customers in a way where you could now reference data. Just like your reference websites today, I don't download CNN dot com. I point at it, and it points me to something else. I'm always seeing the latest version, obviously, and we can, you know, all collaborate on what I'm seeing on that website. That's the same thing that now can happen with data. So And I saw this as what was possible, and I distinctly asked the question, you know, the CEO of the time Is this possible? And not only was it possible it was a fundamental construct that was built into the way that snowflake was delivered. And then, lastly, this is what we learned. And I think this is what you know. M It also has been touting is that it's all great if data is out there and even if you lower that bar of access where data doesn't have to move, how do I know? Right? If I'm back to sitting at Goldman Sachs, how do I know what data is available to me now in this this you know, connected data network eso we released our data marketplace, which was a very different kind of marketplace than these of the past. Where for us, it was really like a global catalog that would elect a consumer data consumer. Noah data was available, but also level the playing field. Now we're now, you know, Eagle, Alfa, or even, you know, a new alternative data vendor build something in their in their basement can now publish that data set so that the world could see and consume and be aligned to, you know, snowflakes, core business, and not where we wouldn't have to be competing or having to take, um, any kind of custody of that data. So adding that catalog to this now ubiquitous access, um really changed the game and, you know, and then now I seem like a genius for making this move. But back then, like I said, we've seen I seem like instant. I was insane. >>Well, given, given that snowflake was the hottest aipo like ever, you were a genius. Uh, doing this, you know, six years in advance. E think we all agree on that, But, you know, a lot of this is still visionary. Um, you know, some of the most leading companies are already doing this. But one What? What is your take our Are you best in class customers still moving the data? Or is this like they're at least thinking about data monetization? What are you seeing from your perspective? >>Yeah, I mean, I did you know, the overall appreciation and understanding of you know, one. I got to get my house in order around my data, um, has something that has been, you know, understood and acted upon. Andi, I do agree that there is a shift now that says, you know, data silos alone aren't necessarily gonna bring me, you know, new and unique insights on dso enriching that with external third party data is absolutely, you know, sort of the the ship that we're seeing our customers undergo. Um, what I find extremely interesting in this space and what some of the most mature clients are doing is, you know, really taking advantage of these data marketplaces. But building data partnerships right there from what mutually exclusive, where there is a win win scenario for for you know, that organization and that could be, you know, retail customers or life science customers like with pandemic, right the way we saw companies that weren't naturally sharing information are now building these data partnership right that are going are going into mutually benefit, you know, all organizations that are sort of part of that value to Andi. I think that's the sort of really important criteria. And how we're seeing our clients that are extremely successful at this is that partnership has benefits on both sides of that equation, right? Both the data provider and then the consumer of that. And there has to be, you know, some way to ensure that both parties are are are learning right, gaining you insights to support, you know, whatever their business organization going on. >>Yeah, great one. So those data partnerships getting across the full value chain of sharing data and analytics Emmett, you work on both sides of the equation here, helping companies. Let's say let's say data providers maybe, like, you know, cast with human mobility monetize that. But then also people that are new to it. Where you seeing the top use cases? Well, >>interestingly, I agree with one of the supply side. One of the interesting trends is we're seeing a lot more data coming from large Corporates. Whether they're listed are private equity backed, as opposed to maybe data startups that are earning money just through data monetization. I think that's a great trend. I think that means a lot of the best. Data said it data is yet to come, um, in terms off the tough economy and how that's changed. I think the category that's had the most momentum and your references is Geo location data. It's that was the category at our conference in December 2000 and 12 that was pipped as the category to watch in 2019. On it didn't become that at all. Um, there were some regulatory concerns for certain types of geo data, but with with covert 19, it's Bean absolutely critical for governments, ministries of finance, central banks, municipalities, Thio crunch that data to understand what's happening in a real time basis. But from a company perspective, it's obviously critical as well. In terms of planning when customers might be back in the High Street on DSO, fourth traditionally consumer transaction data of all the 26 categories in our taxonomy has been the most popular. But Geo is definitely catching up your slide. Talked about being a tough economy. Just one point to contradict that for certain pockets of our clients, e commerce companies are having a field day, obviously, on they are very data driven and tech literate on day are they are really good client base for us because they're incredibly hungry, firm or data to help drive various, uh, decision making. >>Yeah, So fair enough. Some sectors of the economy e commerce, electron, ICS, healthcare are doing great. Others travel, hospitality, Um, super challenging. So I like your quote. The best is yet to come, >>but >>that's data sets is yet to come. And I do think the cloud is enabling that because we could get rid of some of the messy manual data flows that Matt you talked about, but nonetheless, Still, one of the hardest things is the data map. Things combining internal and external >>when >>you might not even have good master data. Common keys on your internal data. So any advice for this? Anyone who wants to take that? >>Sure I can. I can I can start. That's okay. I do think you know, one of the first problems is just a cataloging of the information that's out there. Um, you know, at least within our organization. When I took on this role, we were, you know, a large buyer of third party data. But our organization as a whole didn't necessarily have full visibility into what was being bought and for what purpose. And so having a catalog that helps us internally navigate what data we have and how we're gonna use it was sort of step number one. Um, so I think that's absolutely important. Um, I would say if we could go from having that catalog, you know, created manually to more automated to me, that's sort of the next step in our evolution, because everyone is saying right, the ongoing, uh, you know, creation of new external data sets. It's only going to get richer on DSO. We wanna be able to take advantage of that, you know, at the at the pacing speed, that data is being created. So going from Emanuel catalog to anonymous >>data >>catalog, I think, is a key capability for us. But then you know, to your second point, Cindy is how doe I then connect that to our own internal data to drive greater greater insights and how we run our business or how we serve our customers. Andi, that one you know really is a It's a tricky is a tricky, uh, question because I think it just depends on what data we're looking toe leverage. You know, we have this concept just around. Not not all data is created equal. And when you think about governance and you think about the management of your master data, your internal nomenclature on how you define and run your business, you know that that entire ecosystem begins to get extremely massive and it gets very broad and very deep on DSO for us. You know, government and master data management is absolutely important. But we took a very sort of prioritized approach on which domains do we really need to get right that drive the greatest results for our organization on dso mapping those domains like client data or employee data to these external third party data sources across this catalog was really the the unlocked for us versus trying to create this, you know, massive connection between all the external data that we're, uh, leveraging as well as all of our own internal data eso for us. I think it was very. It was a very tailored, prioritized approach to connecting internal data to external data based on the domains that matter most to our business. >>So if the domains so customer important domain and maybe that's looking at things, um, you know, whether it's social media data or customer transactions, you prioritized first by that, Is that right? >>That's correct. That's correct. >>And so, then, Matt, I'm going to throw it back to you because snowflake is in a unique position. You actually get to see what are the most popular data sets is is that playing out what one described are you seeing that play out? >>I I'd say Watch this space. Like like you said. I mean this. We've you know, I think we start with the data club. We solve that that movement problem, which I think was really the barrier that you tended to not even have a chance to focus on this mapping problem. Um, this notion of concordance, I think this is where I see the big next momentum in this space is going to be a flurry of traditional and new startups who deliver this concordance or knowledge graph as a service where this is no longer a problem that I have to solve internal to my organization. The notion of mastering which is again when everyone has to do in every organization like they used to have to do with moving data into the organization goes away. And this becomes like, I find the best of breed for the different scopes of data that I have. And it's delivered to me as a, you know, as a cloud service that just takes my data. My internal data maps it to these 2nd and 3rd party data sets. Um, all delivered to me, you know, a service. >>Yeah, well, that would be brilliant concordance as a service or or clean clean master data as a service. Um, using augmented data prep would be brilliant. So let's hope we get there. Um, you know, so 2020 has been a wild ride for everyone. If I could ask each of you imagine what is the art of the possible or looking ahead to the next to your and that you are you already mentioned the best is yet to come. Can you want to drill down on that. What what part of the best is yet to come or what is your already two possible? >>Just just a brief comment on mapping. Just this week we published a white paper on mapping, which is available for for anyone on eagle alfa dot com. It's It's a massive challenge. It's very difficult to solve. Just with technology Onda people have tried to solve it and get a certain level of accuracy, but can't get to 100% which which, which, which makes it difficult to solve it. If if if there is a new service coming out against 100% I'm all ears and that there will be a massive step forward for the entire data industry, even if it comes in a few years time, let alone next year, I think going back to the comment on data Cindy. Yes, I think boards of companies are Mawr and Mawr. Viewing data as an asset as opposed to an expense are a cost center on bond. They are looking therefore to get their internal house in order, as one was saying, but also monetize the data they are sitting on lots of companies. They're sitting on potentially valuable data. It's not all valuable on a lot of cases. They think it's worth a lot more than it is being frank. But in some cases there is valuable data on bond. If monetized, it can drop to the bottom line on. So I think that bodes well right across the world. A lot of the best date is yet to come on. I think a lot of firms like Deloitte are very well positioned to help drive that adoption because they are the trusted advisor to a lot of these Corporates. Um, so that's one thing. I think, from a company perspective. It's still we're still at the first base. It's quite frustrating how slow a lot of companies are to move and adopt, and some of them are haven't hired CDO. Some of them don't have their internal house in order. I think that has to change next year. I think if we have this conference at this time next year, I would expect that would hopefully be close to the tipping point for Corporates to use external data. And the Malcolm Gladwell tipping point on the final point I make is I think, that will hopefully start to see multi department use as opposed to silos again. Parliaments and silos, hopefully will be more coordinated on the company's side. Data could be used by marketing by sales by r and D by strategy by finance holds external data. So it really, hopefully will be coordinated by this time next year. >>Yeah, Thank you. So, to your point, there recently was an article to about one of the airlines that their data actually has more value than the company itself now. So I know, I know. We're counting on, you know, integrators trusted advisers like Deloitte to help us get there. Uh, one what? What do you think? And if I can also drill down, you know, financial services was early toe all of this because they needed the early signals. And and we talk about, you know, is is external data now more valuable than internal? Because we need those early signals in just such a different economy. >>Yeah, I think you know, for me, it's it's the seamless integration of all these external data sources and and the signals that organizations need and how to bring those into, you know, the day to day operations of your organization, right? So how do you bring those into, You know, you're planning process. How do you bring that into your sales process on DSO? I think for me success or or where I see the that the use and adoption of this is it's got to get down to that level off of operations for organizations. For this to continue to move at the pace and deliver the value that you know, we're all describing. I think we're going to get there. But I think until organizations truly get down to that level of operations and how they're using this data, it'll sort of seem like a Bolton, right? So for me, I think it's all about Mawr, the seamless integration. And I think to what Matt mentioned just around services that could help connect external data with internal data. I'll take that one step beyond and say, How can we have the data connect itself? Eso I had references Thio, you know, automation and machine learning. Um, there's significant advances in terms of how we're seeing, you know, mapping to occur in a auto generated fashion. I think this specific space and again the connection between external and internal data is a prime example of where we need to disrupt that, you know, sort of traditional data pipeline on. Try to automate that as much as possible. And let's have the data, you know, connect itself because it then sort of supports. You know, the first concept which waas How do we make it more seamless and integrated into, you know, the business processes of the organization's >>Yeah, great ones. So you two are thinking those automated, more intelligent data pipelines will get us there faster. Matt, you already gave us one. Great, Uh, look ahead, Any more to add to >>it, I'll give you I'll give you two more. One is a bit controversial, but I'll throw that you anyway, um, going back to the point that one made about data partnerships What you were saying Cindy about, you know, the value. These companies, you know, tends to be somehow sometimes more about the data they have than the actual service they provide. I predict you're going to see a wave of mergers and acquisitions. Um, that it's solely about locking down access to data as opposed to having data open up. Um to the broader, you know, economy, if I can, whether that be a retailer or, you know, insurance company was thes prime data assets. Um, you know, they could try to monetize that themselves, But if someone could acquire them and get exclusive access that data, I think that's going to be a wave of, um, in a that is gonna be like, Well, we bought this for this amount of money because of their data assets s. So I think that's gonna be a big wave. And it'll be maybe under the guise of data partnerships. But it really be about, you know, get locking down exclusive access to valuable data as opposed to trying toe monetize it itself number one. And then lastly, you know. Now, did you have this kind of ubiquity of data in this interconnected data network? Well, we're starting to see, and I think going to see a big wave of is hyper personalization of applications where instead of having the application have the data itself Have me Matt at Snowflake. Bring my data graph to applications. Right? This decoupling of we always talk about how you get data out of these applications. It's sort of the reverse was saying Now I want to bring all of my data access that I have 1st, 2nd and 3rd party into my application. Instead of having to think about getting all the data out of these applications, I think about it how when you you know, using a workout app in the consumer space, right? I can connect my Spotify or connect my apple music into that app to personalize the experience and bring my music list to that. Imagine if I could do that, you know, in a in a CRM. Imagine I could do that in a risk management. Imagine I could do that in a marketing app where I can bring my entire data graph with me and personalize that experience for, you know, for given what I have. And I think again, you know, partners like thoughts. But I think in a unique position to help enable that capability, you know, for this next wave of of applications that really take advantage of this decoupling of data. But having data flow into the app tied to me as opposed to having the APP have to know about my data ahead of time, >>Yeah, yeah, So that is very forward thinking. So I'll end with a prediction and a best practice. I am predicting that the organizations that really leverage external data, new data sources, not just whether or what have you and modernize those data flows will outperform the organizations that don't. And as a best practice to getting there, I the CDOs that own this have at least visibility into everything they're purchasing can save millions of dollars in duplicate spend. So, Thio, get their three key takeaways. Identify the leading indicators and market signals The data you need Thio. Better identify that. Consolidate those purchases and please explore the data sets the range of data sets data providers that we have on the thought spot. Atlas Marketplace Mallory over to you. >>Wow. Thank you. That was incredible. Thank you. To all of our Panelists for being here and sharing that wisdom. We really appreciate it. For those of you at home, stay close by. Our third session is coming right up and we'll be joined by our partner AWS and get to see how you can leverage the full power of your data cloud complete with the demo. Make sure to tune in to see you >>then

>>from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>And we're back with the data automation. Siri's. In this episode, we're gonna learn more about what I owe Tahoe is doing in the field of adaptive data governance how it can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin, and I'm joined by a J. Bihar on the CEO of Iot Tahoe and Lester Waters, the CEO of Bio Tahoe. Gentlemen, it's great to have you on the program. >>Thank you. Lisa is good to be back. >>Great. Staley's >>likewise very socially distant. Of course as we are. Listen, we're gonna start with you. What's going on? And I am Tahoe. What's name? Well, >>I've been with Iot Tahoe for a little over the year, and one thing I've learned is every customer needs air just a bit different. So we've been working on our next major release of the I O. Tahoe product. But to really try to address these customer concerns because, you know, we wanna we wanna be flexible enough in order to come in and not just profile the date and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could, uh, extend the product without building a new version of the product. We wanted to be able to have plausible modules. We also focused a lot on performance. That's very important with the bulk of data that we deal with that we're able to pass through that data in a single pass and do the analytics that are needed, whether it's, uh, lineage, data quality or just identifying the underlying data. And we're incorporating all that we've learned. We're tuning up our machine learning we're analyzing on MAWR dimensions than we've ever done before. We're able to do data quality without doing a Nen initial rejects for, for example, just out of the box. So I think it's all of these things were coming together to form our next version of our product. We're really excited by it, >>So it's exciting a J from the CEO's level. What's going on? >>Wow, I think just building on that. But let's still just mentioned there. It's were growing pretty quickly with our partners. And today, here with Oracle are excited. Thio explain how that shaping up lots of collaboration already with Oracle in government, in insurance, on in banking and we're excited because we get to have an impact. It's real satisfying to see how we're able. Thio. Help businesses transform, Redefine what's possible with their data on bond. Having I recall there is a partner, uh, to lean in with is definitely helping. >>Excellent. We're gonna dig into that a little bit later. Let's let's go back over to you. Explain adaptive data governance. Help us understand that >>really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data driven culture and pushing what's traditionally managed in I t out to the business. And to do that, you've got to you've got Thio. You've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concerns itself. But they need to understand what kind of data they have, what shape it's in what's dependent on it upstream and downstream, and so that they could make their educated decisions on on what they need to do to achieve those business outcomes. >>Ah, >>lot of a lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just >>say, you >>know, the start date of alone must always be before the end date of alone and having that generic rule, regardless of the underlying database and applying it even when a new database comes online and having those rules applied. That's what adaptive data governance about I like to think of. It is the intersection of three circles, Really. It's the technical metadata coming together with policies and rules and coming together with the business ontology ease that are that are unique to that particular business. And this all of this. Bringing this all together allows you to enable rapid change in your environment. So it's a mouthful, adaptive data governance. But that's what it kind of comes down to. >>So, Angie, help me understand this. Is this book enterprise companies are doing now? Are they not quite there yet. >>Well, you know, Lisa, I think every organization is is going at its pace. But, you know, markets are changing the economy and the speed at which, um, some of the changes in the economy happening is is compelling more businesses to look at being more digital in how they serve their own customers. Eh? So what we're seeing is a number of trends here from heads of data Chief Data Officers, CEO, stepping back from, ah, one size fits all approach because they've tried that before, and it it just hasn't worked. They've spent millions of dollars on I T programs China Dr Value from that data on Bennett. And they've ended up with large teams of manual processing around data to try and hardwire these policies to fit with the context and each line of business and on that hasn't worked. So the trends that we're seeing emerge really relate. Thio, How do I There's a chief data officer as a CEO. Inject more automation into a lot of these common tax. Andi, you know, we've been able toc that impact. I think the news here is you know, if you're trying to create a knowledge graph a data catalog or Ah, business glossary. And you're trying to do that manually will stop you. You don't have to do that manually anymore. I think best example I can give is Lester and I We we like Chinese food and Japanese food on. If you were sitting there with your chopsticks, you wouldn't eat the bowl of rice with the chopsticks, one grain at a time. What you'd want to do is to find a more productive way to to enjoy that meal before it gets cold. Andi, that's similar to how we're able to help the organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >>And if it was me eating that food with you guys, I would be not using chopsticks. I would be using a fork and probably a spoon. So eso Lester, how then does iota who go about doing this and enabling customers to achieve this? >>Let me, uh, let me show you a little story have here. So if you take a look at the challenges the most customers have, they're very similar, but every customers on a different data journey, so but it all starts with what data do I have? What questions or what shape is that data in? Uh, how is it structured? What's dependent on it? Upstream and downstream. Um, what insights can I derive from that data? And how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Maybe they're doing a migration oracle. Maybe they're doing some data governance changes on bits about enabling this. So if you look at these challenges and I'm gonna take you through a >>story here, E, >>I want to introduce Amanda. Man does not live like, uh, anyone in any large organization. She's looking around and she just sees stacks of data. I mean, different databases, the one she knows about, the one she doesn't know about what should know about various different kinds of databases. And a man is just tasking with understanding all of this so that they can embark on her data journey program. So So a man who goes through and she's great. I've got some handy tools. I can start looking at these databases and getting an idea of what we've got. Well, as she digs into the databases, she starts to see that not everything is as clear as she might have hoped it would be. You know, property names or column names, or have ambiguous names like Attribute one and attribute to or maybe date one and date to s Oh, man is starting to struggle, even though she's get tools to visualize. And look what look at these databases. She still No, she's got a long road ahead. And with 2000 databases in her large enterprise, yes, it's gonna be a long turkey but Amanda Smart. So she pulls out her trusty spreadsheet to track all of her findings on what she doesn't know about. She raises a ticket or maybe tries to track down the owner to find what the data means. And she's tracking all this information. Clearly, this doesn't scale that well for Amanda, you know? So maybe organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well because they're still ambiguities in the data with Iota ho. What we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that attribute. One looks very much like a U. S. Social Security number and attribute to looks like a I c D 10 medical code. And we do this by using anthologies and dictionaries and algorithms to help identify the underlying data and then tag it. Key Thio Doing, uh, this automation is really being able to normalize things across different databases, so that where there's differences in column names, I know that in fact, they contain contain the same data. And by going through this exercise with a Tahoe, not only can we identify the data, but we also could gain insights about the data. So, for example, we can see that 97% of that time that column named Attribute one that's got us Social Security numbers has something that looks like a Social Security number. But 3% of the time, it doesn't quite look right. Maybe there's a dash missing. Maybe there's a digit dropped. Or maybe there's even characters embedded in it. So there may be that may be indicative of a data quality issues, so we try to find those kind of things going a step further. We also try to identify data quality relationships. So, for example, we have two columns, one date, one date to through Ah, observation. We can see that date 1 99% of the time is less than date, too. 1% of the time. It's not probably indicative of a data quality issue, but going a step further, we can also build a business rule that says Day one is less than date to. And so then when it pops up again, we can quickly identify and re mediate that problem. So these are the kinds of things that we could do with with iota going even a step further. You could take your your favorite data science solution production ISAT and incorporated into our next version a zey what we call a worker process to do your own bespoke analytics. >>We spoke analytics. Excellent, Lester. Thank you. So a J talk us through some examples of where you're putting this to use. And also what is some of the feedback from >>some customers? But I think it helped do this Bring it to life a little bit. Lisa is just to talk through a case study way. Pull something together. I know it's available for download, but in ah, well known telecommunications media company, they had a lot of the issues that lasted. You spoke about lots of teams of Amanda's, um, super bright data practitioners, um, on baby looking to to get more productivity out of their day on, deliver a good result for their own customers for cell phone subscribers, Um, on broadband users. So you know that some of the examples that we can see here is how we went about auto generating a lot of that understanding off that data within hours. So Amanda had her data catalog populated automatically. A business class three built up on it. Really? Then start to see. Okay, where do I want Thio? Apply some policies to the data to to set in place some controls where they want to adapt, how different lines of business, maybe tax versus customer operations have different access or permissions to that data on What we've been able to do there is, is to build up that picture to see how does data move across the entire organization across the state. Andi on monitor that overtime for improvement, so have taken it from being a reactive. Let's do something Thio. Fix something. Thio, Now more proactive. We can see what's happening with our data. Who's using it? Who's accessing it, how it's being used, how it's being combined. Um, on from there. Taking a proactive approach is a real smart use of of the talents in in that telco organization Onda folks that worked there with data. >>Okay, Jason, dig into that a little bit deeper. And one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is our ally. How do customers measure are? Why? What are they seeing with iota host >>solution? Yeah, right now that the big ticket item is time to value on. And I think in data, a lot of the upfront investment cause quite expensive. They have been today with a lot of the larger vendors and technologies. So what a CEO and economic bio really needs to be certain of is how quickly can I get that are away. I think we've got something we can show. Just pull up a before and after, and it really comes down to hours, days and weeks. Um, where we've been able Thio have that impact on in this playbook that we pulled together before and after picture really shows. You know, those savings that committed a bit through providing data into some actionable form within hours and days to to drive agility, but at the same time being out and forced the controls to protect the use of that data who has access to it. So these are the number one thing I'd have to say. It's time on. We can see that on the the graphic that we've just pulled up here. >>We talk about achieving adaptive data governance. Lester, you guys talk about automation. You talk about machine learning. How are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? Well, >>Azaz, we see Mitt Emmanuel day. The days of manual effort are so I think you know this >>is a >>multi step process. But the very first step is understanding what you have in normalizing that across your data estate. So you couple this with the ontology, that air unique to your business. There is no algorithms, and you basically go across and you identify and tag tag that data that allows for the next steps toe happen. So now I can write business rules not in terms of columns named columns, but I could write him in terms of the tags being able to automate. That is a huge time saver and the fact that we can suggest that as a rule, rather than waiting for a person to come along and say, Oh, wow. Okay, I need this rule. I need this will thes air steps that increased that are, I should say, decrease that time to value that A. J talked about and then, lastly, a couple of machine learning because even with even with great automation and being able to profile all of your data and getting a good understanding, that brings you to a certain point. But there's still ambiguities in the data. So, for example, I might have to columns date one and date to. I may have even observed the date. One should be less than day two, but I don't really know what date one and date to our other than a date. So this is where it comes in, and I might ask the user said, >>Can >>you help me identify what date? One and date You are in this in this table. Turns out they're a start date and an end date for alone That gets remembered, cycled into the machine learning. So if I start to see this pattern of date one day to elsewhere, I'm going to say, Is it start dating and date? And these Bringing all these things together with this all this automation is really what's key to enabling this This'll data governance. Yeah, >>great. Thanks. Lester and a j wanna wrap things up with something that you mentioned in the beginning about what you guys were doing with Oracle. Take us out by telling us what you're doing there. How are you guys working together? >>Yeah, I think those of us who worked in i t for many years we've We've learned Thio trust articles technology that they're shifting now to ah, hybrid on Prohm Cloud Generation to platform, which is exciting. Andi on their existing customers and new customers moving to article on a journey. So? So Oracle came to us and said, you know, we can see how quickly you're able to help us change mindsets Ondas mindsets are locked in a way of thinking around operating models of I t. That there may be no agile and what siloed on day wanting to break free of that and adopt a more agile A p I at driven approach. A lot of the work that we're doing with our recall no is around, uh, accelerating what customers conduce with understanding their data and to build digital APS by identifying the the underlying data that has value. Onda at the time were able to do that in in in hours, days and weeks. Rather many months. Is opening up the eyes to Chief Data Officers CEO to say, Well, maybe we can do this whole digital transformation this year. Maybe we can bring that forward and and transform who we are as a company on that's driving innovation, which we're excited about it. I know Oracle, a keen Thio to drive through and >>helping businesses transformed digitally is so incredibly important in this time as we look Thio things changing in 2021 a. J. Lester thank you so much for joining me on this segment explaining adaptive data governance, how organizations can use it benefit from it and achieve our Oi. Thanks so much, guys. >>Thank you. Thanks again, Lisa. >>In a moment, we'll look a adaptive data governance in banking. This is the Cube, your global leader in high tech coverage. >>Innovation, impact influence. Welcome to the Cube. Disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader in high tech digital coverage. >>Our next segment here is an interesting panel you're gonna hear from three gentlemen about adaptive data. Governments want to talk a lot about that. Please welcome Yusuf Khan, the global director of data services for Iot Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and good John Vander Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this in this panel. Great >>to be >>tried for me. >>Alright, Santiago, we're going to start with you. Can you talk to the audience a little bit about the first Bank of Nigeria and its scale? This is beyond Nigeria. Talk to us about that. >>Yes, eso First Bank of Nigeria was created 125 years ago. One of the oldest ignored the old in Africa because of the history he grew everywhere in the region on beyond the region. I am calling based in London, where it's kind of the headquarters and it really promotes trade, finance, institutional banking, corporate banking, private banking around the world in particular, in relationship to Africa. We are also in Asia in in the Middle East. >>So, Sanjay, go talk to me about what adaptive data governance means to you. And how does it help the first Bank of Nigeria to be able to innovate faster with the data that you have? >>Yes, I like that concept off adaptive data governor, because it's kind of Ah, I would say an approach that can really happen today with the new technologies before it was much more difficult to implement. So just to give you a little bit of context, I I used to work in consulting for 16, 17 years before joining the president of Nigeria, and I saw many organizations trying to apply different type of approaches in the governance on by the beginning early days was really kind of a year. A Chicago A. A top down approach where data governance was seeing as implement a set of rules, policies and procedures. But really, from the top down on is important. It's important to have the battle off your sea level of your of your director. Whatever I saw, just the way it fails, you really need to have a complimentary approach. You can say bottom are actually as a CEO are really trying to decentralize the governor's. Really, Instead of imposing a framework that some people in the business don't understand or don't care about it, it really needs to come from them. So what I'm trying to say is that data basically support business objectives on what you need to do is every business area needs information on the detector decisions toe actually be able to be more efficient or create value etcetera. Now, depending on the business questions they have to solve, they will need certain data set. So they need actually to be ableto have data quality for their own. For us now, when they understand that they become the stores naturally on their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also empower and be actually, in a way flexible to adapt the different questions that they have in orderto be able to respond to the business needs. Now I cannot impose at the finish for everyone. I need them to adapt and to bring their answers toe their own business questions. That is adaptive data governor and all That is possible because we have. And I was saying at the very beginning just to finalize the point, we have new technologies that allow you to do this method data classifications, uh, in a very sophisticated way that you can actually create analitico of your metadata. You can understand your different data sources in order to be able to create those classifications like nationalities, a way of classifying your customers, your products, etcetera. >>So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. They probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the users so that they can be adaptive. >>More and more business users wants autonomy, and they want to basically be ableto grab the data and answer their own question. Now when you have, that is great, because then you have demand of businesses asking for data. They're asking for the insight. Eso How do you actually support that? I would say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, off course, technology is one of the biggest winners without technology. We couldn't have been working remotely without these technologies where people can actually looking from their homes and still have a market data marketplaces where they self serve their their information. But even beyond that data is a big winner. Data because the pandemic has shown us that crisis happened, that we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore that we need to adapt and we need to be flexible. How do we do that with data. Every single company either saw the revenue going down or the revenue going very up For those companies that are very digital already. Now it changed the reality, so they needed to adapt. But for that they needed information. In order to think on innovate, try toe, create responses So that type of, uh, self service off data Haider for data in order to be able to understand what's happening when the prospect is changing is something that is becoming more, uh, the topic today because off the condemning because of the new abilities, the technologies that allow that and then you then are allowed to basically help your data. Citizens that call them in the organization people that no other business and can actually start playing and an answer their own questions. Eso so these technologies that gives more accessibility to the data that is some cataloging so they can understand where to go or what to find lineage and relationships. All this is is basically the new type of platforms and tools that allow you to create what are called a data marketplace. I think these new tools are really strong because they are now allowing for people that are not technology or I t people to be able to play with data because it comes in the digital world There. Used to a given example without your who You have a very interesting search functionality. Where if you want to find your data you want to sell, Sir, you go there in that search and you actually go on book for your data. Everybody knows how to search in Google, everybody's searching Internet. So this is part of the data culture, the digital culture. They know how to use those schools. Now, similarly, that data marketplace is, uh, in you can, for example, see which data sources they're mostly used >>and enabling that speed that we're all demanding today during these unprecedented times. Goodwin, I wanted to go to you as we talk about in the spirit of evolution, technology is changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >>Yeah, Thank you. Um, well, Oracle Digital is a business unit that Oracle EMEA on. We focus on emerging countries as well as low and enterprises in the mid market, in more developed countries and four years ago. This started with the idea to engage digital with our customers. Fear Central helps across EMEA. That means engaging with video, having conference calls, having a wall, a green wall where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today, and this helps us to engage with our customers in the way we were already doing and then about my team. The focus of my team is to have early stage conversations with our with our customers on digital transformation and innovation. And we also have a team off industry experts who engaged with our customers and share expertise across EMEA, and we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important so we can help the customer and for the customer means that we will help them with our technology and our resource is to achieve their goals. >>It's all about outcomes, right? Good Ron. So in terms of automation, what are some of the things Oracle's doing there to help your clients leverage automation to improve agility? So that they can innovate faster, which in these interesting times it's demanded. >>Yeah, thank you. Well, traditionally, Oracle is known for their databases, which have bean innovated year over year. So here's the first lunch on the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90% with a multi medal converts, database and machine learning based automation for full life cycle management. Our databases self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security, and it's self repairing the automates failure, detection fail over and repair. And then the question is for our customers, What does it mean? It means they can focus on their on their business instead off maintaining their infrastructure and their operations. >>That's absolutely critical use if I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that. But we know that whether we're talking about beta management or digital transformation, a one size fits all approach doesn't work to address the challenges that the business has, um that the i t folks have, as you're looking through the industry with what Santiago told us about first Bank of Nigeria. What are some of the changes that you're seeing that I owe Tahoe seeing throughout the industry? >>Uh, well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data where you have almost a data Policeman who tells you what you can and can't do, just doesn't work anymore. It's too slow. It's too resource intensive. Uh, data management data, governments, digital transformation itself. It has to be collaborative on. There has to be in a personalization to data users. Um, in the environment we find ourselves in. Now, it has to be about enabling self service as well. Um, a one size fits all model when it comes to those things around. Data doesn't work. As Santiago was saying, it needs to be adapted toe how the data is used. Andi, who is using it on in order to do this cos enterprises organizations really need to know their data. They need to understand what data they hold, where it is on what the sensitivity of it is they can then any more agile way apply appropriate controls on access so that people themselves are and groups within businesses are our job and could innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >>Yeah, that one size fits all term just doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do >>before it's it's automatically being able to classify terabytes, terabytes of data or even petabytes of data across different sources to find duplicates, which you can then re mediate on. Deletes now, with the capabilities that iota offers on the Oracle offers, you can do things not just where the five times or 10 times improvement, but it actually enables you to do projects for Stop that otherwise would fail or you would just not be able to dio I mean, uh, classifying multi terrible and multi petabytes states across different sources, formats very large volumes of data in many scenarios. You just can't do that manually. I mean, we've worked with government departments on the issues there is expect are the result of fragmented data. There's a lot of different sources. There's lot of different formats and without these newer technologies to address it with automation on machine learning, the project isn't durable. But now it is on that that could lead to a revolution in some of these businesses organizations >>to enable that revolution that there's got to be the right cultural mindset. And one of the when Santiago was talking about folks really kind of adapted that. The thing I always call that getting comfortably uncomfortable. But that's hard for organizations to. The technology is here to enable that. But well, you're talking with customers use. How do you help them build the trust in the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive the kind of a tech in the culture? >>It's really good question is because it can be quite scary. I think the first thing we'd start with is to say, Look, the technology is here with businesses like I Tahoe. Unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting being agile around it, Andi trying new ways of doing things. Uh, if you don't wanna get less behind that Santiago on the team that fbn are a great example off embracing it, testing it on a small scale on, then scaling up a Toyota, we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with a customer. Picky use case, install the application, uh, analyzed data. Drive out Cem Cem quick winds. So we worked in the last few weeks of a large entity energy supplier, and in about 20 days, we were able to give them an accurate understanding of their critical data. Elements apply. Helping apply data protection policies. Minimize copies of the data on work out what data they needed to delete to reduce their infrastructure. Spend eso. It's about experimenting on that small scale, being agile on, then scaling up in a kind of very modern way. >>Great advice. Uh, Santiago, I'd like to go back to Is we kind of look at again that that topic of culture and the need to get that mindset there to facilitate these rapid changes, I want to understand kind of last question for you about how you're doing that from a digital transformation perspective. We know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges and changes that we're all going through? >>The new technologies allowed us to discover the dating anyway. Toe flawed and see very quickly Information toe. Have new models off over in the data on giving autonomy to our different data units. Now, from that autonomy, they can then compose an innovator own ways. So for me now, we're talking about resilience because in a way, autonomy and flexibility in a organization in a data structure with platform gives you resilience. The organizations and the business units that I have experienced in the pandemic are working well. Are those that actually because they're not physically present during more in the office, you need to give them their autonomy and let them actually engaged on their own side that do their own job and trust them in a way on as you give them, that they start innovating and they start having a really interesting ideas. So autonomy and flexibility. I think this is a key component off the new infrastructure. But even the new reality that on then it show us that, yes, we used to be very kind off structure, policies, procedures as very important. But now we learn flexibility and adaptability of the same side. Now, when you have that a key, other components of resiliency speed, because people want, you know, to access the data and access it fast and on the site fast, especially changes are changing so quickly nowadays that you need to be ableto do you know, interact. Reiterate with your information to answer your questions. Pretty, um, so technology that allows you toe be flexible iterating on in a very fast job way continue will allow you toe actually be resilient in that way, because you are flexible, you adapt your job and you continue answering questions as they come without having everything, setting a structure that is too hard. We also are a partner off Oracle and Oracle. Embodies is great. They have embedded within the transactional system many algorithms that are allowing us to calculate as the transactions happened. What happened there is that when our customers engaged with algorithms and again without your powers, well, the machine learning that is there for for speeding the automation of how you find your data allows you to create a new alliance with the machine. The machine is their toe, actually, in a way to your best friend to actually have more volume of data calculated faster. In a way, it's cover more variety. I mean, we couldn't hope without being connected to this algorithm on >>that engagement is absolutely critical. Santiago. Thank you for sharing that. I do wanna rap really quickly. Good On one last question for you, Santiago talked about Oracle. You've talked about a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle. What you guys were doing there to help your customers get the resilience that they have toe have to be not just survive but thrive. >>Yeah. Oracle has a cloud offering for infrastructure, database, platform service and a complete solutions offered a South on Daz. As Santiago also mentioned, We are using AI across our entire portfolio and by this will help our customers to focus on their business innovation and capitalize on data by enabling new business models. Um, and Oracle has a global conference with our cloud regions. It's massively investing and innovating and expanding their clouds. And by offering clouds as public cloud in our data centers and also as private cloud with clouded customer, we can meet every sovereignty and security requirements. And in this way we help people to see data in new ways. We discover insights and unlock endless possibilities. And and maybe 11 of my takeaways is if I If I speak with customers, I always tell them you better start collecting your data. Now we enable this partners like Iota help us as well. If you collect your data now, you are ready for tomorrow. You can never collect your data backwards, So that is my take away for today. >>You can't collect your data backwards. Excellently, John. Gentlemen, thank you for sharing all of your insights. Very informative conversation in a moment, we'll address the question. Do you know your data? >>Are you interested in test driving the iota Ho platform kick Start the benefits of data automation for your business through the Iota Ho Data Health check program. Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iota ho. Look time with a data engineer to learn more and see Io Tahoe in action from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs to be to Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you could get to know your data and quickly on. We also want to encourage you to engage with the media and Patrick, use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Savita, take it away. Alright. >>Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. I said my name is Patrick Samit. I'm the enterprise data engineer here in Ohio Tahoe. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>So, guys, what patent I got? I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off to being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted to walk you guys through some of those client questions, slash pain points that we're hearing from different industries and different rules and demo how our platform here, like Tahoe, is used for automating Dozier related tasks. So with that said are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one. So I'm a data practitioner. I just started my job. ABC Bank. I have, like, over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I saw who help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of excel and something similar to video which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing, you can see here visualization of the data relationships created by the I. O. Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um so is the data catalog automatically populated? Correct. Okay, so So what I'm using Iota hope at what I'm getting is this complete, unified automated platform without the added cost? Of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column underscore ones and custom variable underscore tents. They're always such a joy to deal with. Now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Uh, personally, I'm a big fan of this view, as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought, Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. >>Now you >>notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships on. You can leverage to try and make new and powerful relationships within your data. >>Eso So this is really cool, and I can see how this could be leverage quickly now. What if I added new data sources or your multiple data sources and need toe identify what data sensitive can iota who detect that? >>Yeah, definitely. Within the hotel platform. There, already over 300 pre defined policies such as hip for C, C, P. A and the like one can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And it's something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface. Someone can work these into the action items within your project management systems, and I think this lends to the collaboration as a team can work through the discovery simultaneously, and as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota hope, you can be sure you're in compliance. >>So I'm glad you mentioned compliance because that's extremely important to my organization. So what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely the collaboration and documentation that the Iot Tahoe interface lends itself to really help you build that confidence that your compliance is sound. >>So we're planning a migration. Andi, I have a set of reports I need to migrate. But what I need to know is, uh well, what what data sources? Those report those reports are dependent on. And what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>Eso So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>Let's say I add another data source. I can still see that unified 3 60 view. >>Yeah, One future that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished alone for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for things. Visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh, can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. This also provides tabular output in case you needed for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions, allowing to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust >>it? So >>what I'm interested in knowing, really is is it in a fit state for me to use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. And I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. Another service that I owe Tahoe provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, eso >>you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. >>So I get now the value of IATA who brings by automatically capturing all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed, one can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions. Allowing insight into the strength of these business rules is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, >>so those custom rules can I apply that across data sources? >>Yeah, you could bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out to us. we are Website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Your Honor, >>if I could ask you one quick question, how do you advise customers? You just walk in this great example this banking example that you instantly to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules. A swell is identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>I'm no, I think actually passed something that pretty well, I mean, just just by automating all those manual task. I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation >>started. Excellent. So, Pete and Pat, thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality, something you can maximize the value of it. Thanks >>for watching. Thanks again, Lisa, for that very insightful and useful deep dive into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria This is Dave a lot You won't wanna mess Iota, whose fifth episode in the data automation Siri's in that we'll talk to experts from Red Hat and Happiest Minds about their best practices for managing data across hybrid cloud Inter Cloud multi Cloud I T environment So market calendar for Wednesday, January 27th That's Episode five. You're watching the Cube Global Leader digital event technique

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Worldwide Public sector. >>Right. Hello and welcome to the Cube. Virtual our coverage of aws reinvent 2020 with special coverage of the public sector experience. This is the day when we go through all the great conversations around public sector in context to reinvent great guest will for Justin, head of A W s ai and machine learning enablement and partnership with AWS Wilfred. Thanks for joining us. >>Thanks, John. Thanks for having me on. I'm pretty excited to be part of this cube interview. >>Well, I wish we could be in person, but with the pandemic, we gotta do the remote. But I want to get into some of the things you're working on. The A I m l Rapid Adoption Assistance Initiative eyes a big story. What is? What is it described what it is. >>So we launched this artificial intelligence slash machine learning rapid adoption assistance for all public sector partners who are part of the AP in network in September 2020. Onda. We launched this in response to the president's Executive water called the American Year Initiative. So the rapid adoption assistant what it provides us. It provides a direct scalable on automated mechanism for all the public sector partners to reach out to AWS experts within our team for assistance in building and deploying machine learning workloads on behalf of the agencies. So for all all the partners who are part off, this rapid adoption assistance will go through a journey with AWS with my team and they will go through three different faces. The first face will be the envisioning face. The second phase would be the enablement face on the third would be the bill face, as you know, in the envisioning face will dive deeply The use case, the problem that they're trying to solve. This is where we will talk about the algorithms and framework on. We will solidify the architecture er on validate the architecture er on following that will be an enablement face where we engage with the partners trained their technical team, meaning that it will be a hands on approach hands on on keyboard kind of approach where we trained them on machine learning stack On the third phase would be the bill face on the partners leverage the knowledge that they have gained through the enablement and envisioning face, and they start building on rolling out workloads on behalf of the agencies. So we will stay with them throughout the journey on We will doom or any kind of blockers be technical or business, so that's a quick overview off a more rapid adoption assistance program. >>It's funny talking to Swami over the years and watching every year at reinvent the A I. M L Portfolio. Dr Matt Wood is always doing something new. This year is no exception. Even Mawr Machine Learning and AI in the In the News on this rapid adoption assistant initiative sounds like it's an accelerant. Um, so I get all that, But I want to ask you, what problem does it solve for the customer? Or Amazon is because there's demand. There's too much demand. People wanna go faster. What problem does this initiative this rapid adoption of a I machine learning initiative solved? >>So as you know, John, artificial intelligence and related technologies like deep learning and machine learning can literally transform the way agencies operate. They can enable them to provide better services, quicker services and more secure services to the citizens of this country. And that's the reason the president released an executive water called American Initiative on it drives all the government agencies, specifically federal agencies, to promote artificial intelligence to protect and improve the security and economy of the nation. So if you think about it, the best way to achieve the goal is to enable the partners toe build workloads on behalf of agencies, because when it comes to public sector, most of the workloads are delivered by partners. So the problem that we face based on our interaction with the partners is that though the partners have been building a lot off applications with AWS for more than a decade, when it comes to artificial intelligence, they have very limited resources when it comes to deep learning and machine learning, right, like speech recognition, cognitive computing, national language frosting. So we wanted exactly address that. And that's the problem you're trying to solve by launching this rapid adoption assistance, which is nothing but a dry direct mechanism for partners to reach our creative, these experts to help them to build those kind of solutions for the government. >>You know, it's interesting because AI and machine learning it's a secret sauce for workload, especially modern workloads. You mentioned agencies and also public sector. You know, we've seen Certainly there's been pandemic a ton of focus on moving faster, right? So getting those APS out quickly ai drives a lot of that, so totally get it. Um, I think it's an accelerant great program. It just makes a lot of sense. And I know you guys have been going in tow by vertical and kind of having stage making all these other tools kind of be specialized within those verticals. So it makes a ton of sense. I get it, and it is a great, great initiative and solve the problem. The question I have is who gets access to this, right? Is it just agencies you mentioned? Is it all public sector? Could you just clarify who can apply to this program? >>Yes, it is a partner focused program. So all the existing partners, though it is going to affect the end agencies, were trying to help the agency's through the partners. So all the existing AP in partners who are part of the PSP program, we call it the public sector partner program can apply for this rapid adoption assistance. So you have been following John, you have been following AWS and AWS partners on a lot of partners have different kind of expertise on they. They show that by achieving a lot of competencies, right, it could be technical competencies like big data storage and security. Or it could be domain specific competencies like public safety education on government competency. But for a playing this program, the partners don't need to have any kind of competency, and all they have to have is they have to be part of the Amazon Partner Network on they have to be part of the public sector partner program. That is number one Second. It is open toe all partners, meaning that it is open toe. Both technology partners, as well as consulting partners Number three are playing is pretty simple, John, right? You can quickly search for a I M or rapid adoption assistance on a little pop up a page on a P network, the partners have to go on Phil pretty basic information about the workload, the problem that they're trying to solve the machine learning services that they're planning to use on a couple of other information, like contact information, and then our team reaches out to the partner on help them with the journey. >>So real. No other requirements are prerequisites. Just part of the partner program. >>Absolutely. It is meant for partners. And all you have to do is you have to be a part off 18 network, and you have to be a public sector apartment. >>Public sector partner makes sense. I mean, how you're gonna handle the demand. I'm sure the it's gonna be a tsunami of interest, because, I mean, why wouldn't someone take advantage of this? >>Yep. It is open to all kinds of partners because they have some kind of prerequisites, right? So that's what I'm trying to explain. It is open to all partners, but we have since it is open to existing partners, we kind of expect the partners toe understand the best practices off deploying a machine, learning workloads, or for that case, any kind of workload which should be scalable, land secure and resilient. So we're not going to touch? Yeah, >>Well, I wanna ask you what's what's the response been on this launch? Because, you know, I mean to me, it just makes it's just common sense. Why wouldn't someone take advantage of it? E. Whether responses partner or you have domain expertise or in a vertical just makes a lot of sense. You get access to the experts. >>The response has been great. As I said, the once you apply the journey takes six weeks, but already we just launched it. Probably close toe. Two months back in September 2nd week of September, it is almost, uh, almost two months, and we have more than 15 partners as part of this program on dykan name couple of partners say, for example, we worked with delight on We Are. We will be working on number of work clothes for the Indy agencies through delight. And there are other couple of number of other partners were making significant progress using this rapid adoption assistance that includes after associates attained ardent emcee on infinitive. So to answer your question, the response has been great so far. >>So what's the I So I gotta ask, you know, one of things I thought that Teresa Carlson about all the time in Sandy Carter is, you know, trying to get the accelerant get whether it's Fed ramp and getting certifications. I mean, you guys have done a great job of getting partners on board. Is there any kind of paperwork? What's the process? What should a partner expect to take advantage of that? I'm sure they'll be interest beyond just the launch. What's what's involved? What zit Web bases it check a form? Is that a lot of hoops to jump through? Explain what? What? The process >>is. Very interesting question. And it probably is a very important question from a part of perspective, right? So since it is offered for a peon partners, absolutely, they should have already gone through the AP in terms and conditions they should have. Already, a customer agreement or advanced partners might have enterprise agreement. So for utilizing this for leveraging this rapid adoption assistance program, absolutely. There's no paperwork involved. All they have to do is log into the Web form, fill up the basic information. It comes to us way, take it from there. So there is no hard requirements as long as you're part of the AP network. And as long as you're part of the PSP program, >>well, for great insight, congratulations on a great program. I think it's gonna be a smash hit. Who wouldn't wanna take? I know you guys a lot of goodness there with Amazon Cloud higher level services with a I machine learning people could bring it into the table. I know from a cybersecurity standpoint to just education the range of, um, workloads is gonna be phenomenal. Obviously military as well. Eso totally cool. Love it. Congratulations. Like my final question is, um, one about the partner. So I'm a partner. I like this. Say I'm a partner. I jump in Easy to get in. Walk me through What happens? I mean, I signed some paperwork. You check the boxes, I get involved, I get, like, a rep. Do I do things? Do I? What happens to me? Walk me down the path of execution. What's expectation of what will happen? >>I'll explain that in two parts, John. Right? One is from a partner journey perspective and then from AWS perspective. What? What we expect out off partners, right? So, from a experience perspective, as long as they fill out, fill out the web form on, fill out the basic information about the project that they're trying to work. It comes to us. The workflow is automated. All the information is captured on the information comes to my team on. We get back to the partners within three days, but the journey itself can take from 6 to 8 weeks because, as I mentioned during the envisioning case, we try to map the problem to the solution. But the enablement phases the second phase is where it can take anywhere from 2 to 3 weeks because, as I mentioned, we focused on the three layers of the machine learning stack for certain kind of partners. They might be interested in sage maker because they might want to build a custom machine learning model. But for some of the partners, they want the argument that existing applications using S. R or NLP or nL you so we can focus on the high level services. Or we can train them on stage makers so it can take anywhere between 2 to 3 weeks or 3 to 4 weeks. And finally, the build phase varies from partner to partner on the complexity of the work. Lord at that point were still involved with a partner, but the partner will be taking the lead on will be with them to remove any kid of Glaucus being technical or, uh, business couple of Yeah, well, I just >>want to say the word enablement in your title kind of speaks volumes. This isn't about enabling customers. >>It is all about enabling the in customers through partners. So we focus on enabling partners. They could be business big system integrators like Lockheed's or Raytheon's or Delight. Or it could be nimble in small partners. Or it could be a technology partner building an entire pass or SAS service on behalf of the government agencies. Right or that could help the comment agencies in different verticals. So we just enabled the in the agency's through the partners. And the focus of this program is all about partner enablement. >>Well, for just ahead of a does a i machine learning enablement in partnership, part of public sector with a W. S. This is our special coverage. Well, for thanks for coming on being a cube virtual guest. I wish we could be in person, but this year it's remote. This is the cube virtual. I'm John for a year. Host of the Cube. Thanks for watching. >>Thanks a lot, John.

>>from around the globe. It's the >>Cube with digital >>coverage of AWS reinvent 2020 sponsored by Intel, >>AWS and >>our community partners. >>Welcome back to the cubes ongoing coverage of this year's AWS reinvent. You know, normally we'd be in the middle of the San Sands Convention Center. We have two sets and 50,000 of our closest friends. We'd be deking out on cloud. Seems like a long time ago, but the show must go on. And it does. Joe Duffy is here. He's the co founder and CEO of Gloomy, and Justin Fits you is the vice president engineering for Cloud Engineering for snowflake. Welcome, gentlemen. Good to see you. >>It's good to be here, >>Joe. I love what you guys are doing. You know, leading your customers to the cloud and really attacking that I t labor problem that we've dealt with for years and years by playing a role in transforming what I would say is I t ops into cloud ups with programmable infra infrastructure practices. So take >>a >>moment to tell us. Why did you and your co founder start the company how you got it off the ground? People are always interested in how you got it funded. You got a couple of Seattle VCs, Madrona and Tola involved. Any a just got involved. So congrats on that. What's the story of your company? >>Yeah. So my background and my co founder Eric's background. You know, we spent multiple decades at Microsoft just really obsessing over developer platforms and productivity and trying to make you know developers lives as as as as productive as possible. You know, help them harness the power of software >>toe create, >>you know, innovative new applications and really spent time on technologies like Visual Studio and Ahmed. And and, you know, it really struck us that the cloud is changing everything about how we develop software. And yet from our perspective, coming from developer landed had almost changed nothing. You know, most of our customers were still, you know, developing software like they did 15 years ago, where it was a typical enter your application, they'd kind of write the code and then go to their I t team and say, Hey, we need to run this somewhere. Can you provisioned a few virtual machines? Can you prevision You know, maybe a database or two and and And so And then we went and talked Thio, you know, infrastructure teams and found out Hey, you know, folks were really toiling away with tools that air a pale in comparison when it comes to the productivity that we we were accustomed Thio on the developer side. And then frequently we heard from leaders that there were silos between the organizations. They couldn't build things quickly enough. They couldn't move quickly enough in cloud Native and the new public cloud capabilities just really were pushed pushing on that, really, you know. But the most innovative companies we kept hearing were the ones who figured this out, who really figured out how to move faster in the cloud. Companies like Snowflake really are leveraging the cloud toe transform entire businesses. You look at uber lyft Airbnb, these companies that really harnessed the cloud toe not just from a technical productivity standpoint, but really transform the business. Eh? So that was the opportunity that we saw Kalemie was Let's take a step back. We call this cloud engineering. Let's imagine a world where every developers, a cloud developer and infrastructure teams are enabling that new way of building. >>Great. So you mentioned cloud engineering. Now, Justin, you've done a bit a bit of cloud engineering yourself in your day. You know, the Cube has been following Snowflake very closely since it launched really mid last decade. And we've we've covered your novel, architectural approach and your cloud only mantra. Talk about that. And have there been any changes in how you're thinking about cloud adoption and how that's as that's increased and you've seen new use cases emerged. >>Yeah, so I think, you know, obviously Snowflake was was built on the foundation of cloud first, and in fact, cloud Onley are only platform and only infrastructure is is based on the cloud. But, you know, for us, it was absolutely key on. How do you develop a platform and a product that's completely elastic? Lee, scalable on drily, really allows for kind of the paper use and paper consumption model. We didn't really it would be very difficult for us to offer this and Thio offer a product in this way. On def, you start to think about kind of from a cloud engineering perspective. Um, we don't have the typical network engineers. A typical data center engineers that you that you might have seen previously. Instead, we're shifting our model in our what we do include engineering away from kind of an operations model or even devotes model towards the software engineering model. E. I think that's the That's the big shift to cloud engineering is that we're looking to hire and we're building a team of software engineers to build systems and platforms and and tooling Thio have the system self managed as much as possible, and it changes to our infrastructure that we look at any changes in our platform are all through, commits and and deployed via pipelines, as opposed to having Operator's log on and make these changes. And so that's the shift that I think we're seeing. And that's to kind of match the overall stuff like Model of Cloud, first and on and where the product is like just going. >>Like you said in cloud only, Justin, you use Pollux me in your own engineering and also in your product externally. Is that correct? And how so? >>Yeah, we actually use it in, specifically and, um, in our platform, in order to kind of deployed to manage and, uh, just operate a kind of our overall cloud infrastructure. We specifically use it more focused on the good days and and continue ization side of things. But that use cases kind of rapidly expanding across the organization. >>So I'm curious of what do you guys we're seeing in the market place? Joe, you know, thinking about cloud broadly, What's the impact that you're seeing on businesses? Who are the big players that you see out there? Maybe you could talk about some of the differentiation that you've noticed. >>Yeah, I think this notion of plot engineering, you know, even 3.5 years ago when we got started was in its infancy. You know, we definitely saw that. Hey, you know, the world is moving and shifting left, you know, it's just was saying and really, people are looking for new ways to empower developers, but that empowerment has to come with guard rails, right? And so what we're seeing is oftentimes, teams are now modernizing their entire platform infrastructure platform, and they're looking to technologies like kubernetes to do that. But increasingly, you know, aws, Azure gp. You know, when we started, um, there weren't any great managed kubernetes clusters. And now today, fast forward. You know Onley 3.5 years and and many of our customers are using flew me to help them get up and running with the chaos in AWS, for example, you look at a lot of folks transforming on Prem as well again many times, adopting kubernetes is sort of a if they intend to stay on Prem. You know, Thio, at least modernize their approach to application infrastructure delivery. That's where Pollux me really can help. It could be a bridge. Thio hate from on Prem to the public cloud. There's certainly a lot of folks doing great work in the space, you know, I think VM Ware has really kind of emerged as sort of vanguard thought leader in this in this space, especially with, you know, hep dio and now kind of pivotal joining the story. We see other, you know, great companies like hash in court, for we're doing good work in this space. Um, certainly we integrate with a lot of their technologies on you. Combine those with the public cloud providers. There's also a lot of just smaller startups in the space which you know, strikes in my heart. I love I love supporting the startup ecosystem. You know, whether that's for cell or net lif I or server list. You know, really trying to help developers harness more of the cloud. I think that's an emerging trend that we're gonna see accelerating in the coming years. >>Yeah. Thank you. You've mentioned a number of interesting emerging tools companies in the ecosystem. I mean, Justin talked about kubernetes. Are there other tooling that you're using that that might be, you know, some of your customers might like toe to know about. >>Yeah, I think so. So one thing I wanted to actually follow up with what Joe said here is is around kind of the multi cloud nature of what we do is is the tools, like gloomy are critical for us to be able to abstract away specific cloud provider AP ice and such and so given Snowflake operates on all three major public clouds and offers a seamless experience amongst all three of them. We have to have something that abstracts some of that complexity and some of those technical details away. Andi, that's why I kind of blew me, made sense in in this case and has helped us kind of achieved that cloud neutrality piece. Um, in terms of other tools that that you're thinking that we're talking about, I think Bellamy is doing a great job kind of on some of these on some of the kind of that interaction and infrastructure and sensation. But we're looking for tooling to kind of look for the overall workflow automation piece on orchestration. So what sits on top of say, you're using intervals using terra form? You may be using Polonia's well, but what kind of orchestrates all these pieces together? Onda, How do you kind of build workflow automation? And I think there's a lot of companies and technology providers that air starting up in this area to kind of stitch all these pieces together so that you kind of have a seamless kind of work flow across across your infrastructure. >>Got it. So, Joe, I'm kind of curious you talked a little bit about your background at Microsoft, and you're even a TMC where you're helping, you know, people manage Luns. It was a sort of skill set that is not in high demand today. Early. Shouldn't be people really need to transform? I've said that a lot in the queue, but But, you know, maybe talk a little bit about the experiences that you've had in the past that informed the direction that Pollux me is taking and where you see it going specifically. I mean, I've been talking a lot about the next decade of cloud is not gonna be the same as the last decade of the cloud. How did you How do you see it? >>Yeah, I think I recognize a clear trend, you know, in with cloud computing. Uh, you know, back I can't remember 13 years ago, maybe 15 years ago, When, when When the Azure project started. You know Dave Cutler, who actually founded the anti project at Microsoft, Actually, was was one of the first engineers that started Azure. And he called it a cloud operating system. And, you know, I think that vision of hey, the cloud is the new operating system is something that we're still just chipping away at. And that was that was a clear trend, you know, having seen these transformations in the past, you know the shift from, you know, dos to windows from windows to mobile Thio, client server thio now the cloud every step of the way. We always transform the way we build applications. And I think where we're at now is horse, really in the midst of a transition that I think we'll look back. You never know when it's happening right? But you can always look back in hindsight and see that it did happen. And I think the trend that we're going through now with service meshes and just, you know, micro services and service list is really we're building distributed applications. These clouds made of applications, they're distributed applications. And that was the trend that I, I recognized, also recognizes another trend, which is, you know, we spent 30 years building great tools. You know, I d s test frameworks sharing and reuse package managers. We figured out static analysis and how to fix security problems in this in in programming languages that we've got today. Let's not go rebuild all that. Let's leverage that, and and so that's what Eric and I said they want, you know, Let's stand on the shoulders of giants. Let's leverage all this good work that has come before us. Let's just apply that to the infrastructure domain and really try toe smooth things out. Give us a new sort of level playing field to build on. From here is we go forward and I'm excited that Parliament gives us that foundation that we can now build on top of >>Great and Justin, of course, were covered. Aws reinvent you guys. It was kind of your your first platform. It's your largest, the largest component of your business. And I have been saying, Ah lot that, you know the early days of cloud was about infrastructure last 32 throw in some database. But really, there's a new workload that's emerging. And you guys are at the heart of that where people are putting governed data giving access to that data, making it secure, uh, sharing that data across an ecosystem so that new workload is really driving new innovation. I wonder how you see that what you see the next half a decade or decades looking like in terms of innovation? >>Yeah, I think I think it za valid point, which is, um, it's less about infrastructure and more about the services that you're providing with that infrastructure. And what what value are you able to add and So I think that's it, Snowflake. The thing that we're really focused on, which is abstract away, all these tunes and all these knobs and such, and the how much remember you have on a specific and a piece of infrastructure or describes or anything like that. So what's the business value? And how can we present that business value in a uniform way, regardless of kind of the underlying service provider on baby to a different class of business users, someone who wants a low data and just two analysts against that they really don't want to understand what's happening underneath. And I think that's that's where this club engineering piece comes in. Um, and what my team is doing is really focused on How do we abstract away that kind of lower level infrastructure and scalability pieces and allow the application developers to develop this application that is providing business value in a transparent and seamless way and in elastic way such that we can scale up and down we can. We have the ability, obviously, to replicate both within regions and clouds, but also across different clouds. So from a business resiliency and and up time point of view. That's that's something that's been really important. Um, and I think also how do we security is? Becoming is obviously a huge, huge importance, given the classifications type of day that people are putting within our platform. So how are we able Thio ensure that there is a pipeline where developers have reviews and commits of any kind of changes going into the system and their arm's length away, and could be fully audited for various clients and regular regulatory needs? And that's something that kind of this suffer engineering cloud engineering concept has really helped develop and allowed us Thio obviously be successful with various different types of industries. >>Joe, we're almost out of time. I wonder if you could bring us home. I mean, some of the things Justin was talking about I mean, I definitely see a lot of potential disruption coming from the world of developers. Uh, he was talking. He was talking about consumption models different than many of the SAS pricing models. And how do you How do you see it? Developers air kind of the really the new source of innovation. Your final thoughts. >>Yeah. I think we're democratizing access to the cloud for everybody. I think you know it's not just about developers, but it's It's really all engineers of all backgrounds, its developers, its infrastructure engineers, its operations engineers, its security engineers. You know, Justin's mentioning compliance and security. These air really critical elements of how we deliver software into the cloud. So I think you know what you're going to see is you're gonna see a lot of new, compelling experiences built thanks to cloud capabilities. You know, the fact that you've got a I and M l and all these infinitely scalable data services like snowflake and, you know, just an arm's length away that you can use as building blocks in your applications. You know, application developers love that. You know, if we can just empower them to run fast, they will run fast, and we'll build great applications. And infrastructure teams and security engineers will be central to enabling that that new future. I think you also see that you know infrastructure and cloud services will become accessible to an entirely new audience. You know, kids graduating from college, they understand Java script. They understand python now they can really just harness the cloud to build amazing new experiences. So I think we're still, you know, still early days on the transition to the cloud. I know where many years on the journey, but we've got many, many years, you know, in our future. And it's very exciting. >>Well, thank you, guys, Joe and Justin. I really appreciate it. Congratulations on your respective success. I know is Joe said you got a lot more work to do, but I really appreciate you coming on the Cube. >>Awesome. Thank you. You're >>welcome. All right, so we're here covering reinvent 2020. The virtual edition. Keep it right there for more great content. Were unpacking the cloud and looking to the future. You're watching the cube?