>> - From around the globe, it's the cube covering data citizens, 21 brought to you by Collibra. >> Hello, everyone, John Walls here, As we continue our cube conversations here as part of data citizens, 21, the conference ongoing. Collibra at the heart of that, really at the heart of data these days and helping companies and corporations make sense. Although this data chaos that they're dealing with, trying to provide new insights, new analysis being a lot more efficient and effective with your data. That's what Collibra is all about. And their founder and their chief data citizen, if you will, Stan Christiaens joins us today. And Stan, I love that title, chief data citizen. What does that all about? What does that mean? >> Hey John, thanks for having me over. And hopefully we'll get to a point where the chief data citizen Titelist cleaves to you. Thanks by the way, for giving us the opportunity to speak a little bit about what we're doing with our chief data citizen. We started the company about 13 years ago, 2008. And over those years, as a founder I've worn many different hats from product to pre-sales to partnerships and a bunch of obvious things. But ultimately the company reaches a certain point a certain size where systems and processes become absolutely necessary if you want to scale further. And for us, this is the moment in time where we said, okay we probably need a data office right now ourselves, something that we've seen with many of our customers. So we said, okay, let me figure out how to lead our own data office and figured out how we can get value out of data using our own software at Collibra itself. And that's where the chief data citizen role comes in. On Friday evening, we like to call that drinking our own champagne moment morning, either eating our own dog food but, essentially this is what we help our customers do, build out the data offices. So we're doing this ourselves now, when we're very hands-on. So there's a lot of things that we're learning, again just like our customers do. And for me, at Collibra, this means that I'm responsible as a chief data citizen for our overall data strategy, which talks a lot about data products, as well as our data infrastructure, which is needed to power data products. Now, because we're doing this in the company and also doing this in a way that is helpful to our customers. We're also figuring out how do we translate the learnings that we have ourselves and give them back to our customers, to our partners, to the broader ecosystem as a whole. And that's why if you summarize the strategy, I like to sometimes refer to it as data office 2025, it's 2025. What is the data office look like by then? And we recommend to our customers to also have that forward looking view just as well. So if I summarize the, the answer a little bit and it's fairly similar to achieve that officer role but, because it has the external evangelization component, helping other data leaders, we like to refer to it as the chief data citizens. >> Yeah, and that, that kind of, you talked about evangelizing, obviously with that, that you're talking about certain kinds of responsibilities and obligations. And I, when I think of citizenship in general I think about privileges and rights and you know, about national citizenship. You're talking about data citizenship, So I assume that with that you're talking about appropriate behaviors and the most well-defined behaviors, and kind of keeping it between the lanes basically. Is that, is that how you look at being a data citizen or, and if not, how would you describe that to a client about being a data citizen? >> It's a very good point, as a citizen you have rights and responsibilities, and the same is exactly true for a data citizen. For us, starting with what it is, right for us, A data citizen is somebody who uses data to do their job. And we've purposely made that definition very broad because today we believe that everyone in some way uses data to do their job. You know, data is universal. It's critical to business processes and it's importance is only increasing. And we want all the data citizens to have appropriate access to data and the ability to do stuff with data but, also to do that in the right way. And if you think about it this is not just something that applies to you in your job but, also extends beyond the workplace because as a data citizen, you're also a human being, of course. So, the way you do data at home with your friends and family, all of this becomes important as well. And we like to think about it as informed privacy aware, data citizens should think about trust in data all the time, because ultimately everybody's talking today about data as an asset, and data is the new gold, and the new oil, and the new soil, and there is a ton of value in data but, as much as organizations themselves to see this, it's also the bad actors out there. We're reading a lot more about data breaches, for example. So, ultimately there's no value without risk. So, as a data citizen, you can achieve a value but, you also have to think about, how do I avoid these risks, and as an organization, if you manage to combine both of those, that's when you can get the maximum value out of data in a trusted manner. >> Yeah, I think this is pretty, an interesting approach that you've taken here because obviously there there are processes with regard to data, right? I mean, the, you know, that that's pretty clear but, there are also, there's a culture that you're talking about here that, that not only are we going to have an operational plan for how we do this certain activity and how we're going to analyze here, input here, action, or perform action on that, whatever but we're going to have a mindset or an approach mentally that we want our company to embrace. So, if you would walk me through that process a little bit in terms of creating that kind of culture, which is very different than kind of the X's and O's and the technical side of things. >> Yeah. That's I think when organizations face the biggest challenge, because, you know maybe they're hiding the best most unique data scientists in the world but, it's not about what that individual can do, right? It's about what the combination of data citizens across the organization can do. And I think it starts first by thinking as an individual about universal goal, golden rule, treat others as you would want to be treated yourself, right? The way you would ethically use data at your job. Think about that, There's other people at other companies, who you would want to do the same thing. Now, from our experience, in our own data office at Collibra, as well as what we see with our customers. A lot of that personal responsibility which is where culture starts, starts with data literacy. And, you know, we talked a little bit about Plymouth rock and the small statues in Brussels Belgium, where I'm from but, essentially here we speak a couple of languages in Belgium. And for organizations, for individuals data literacy is very similar. You know, you're able to read and write which are pretty essential for any job today. And so we want all data citizens to also be able to speak and read and write data fluently. If I, if I can express it this way. And one of the key ways of getting that done and establishing that culture around data, lies with the one who leads data in the organization, the chief data officer, or however the role is called. They play a very important role in this. In comparison, maybe that I always make there is think about other assets in your organization. You know, you're organized for the money assets, for the talent assets, with HR and a bunch of other assets. So let's talk about the, the money assets for a little bit, right? You have a finance department, you have a chief financial officer, and obviously their responsibility is around managing that money asset. But it's also around making others in the organization think about that money. And they do that through established processes and responsibilities like budgeting and planning but, also ultimately to the individual where, you know, through expense sheets that we all love so much, they make you think about money. So, if the CFO makes everyone in the company thinks about think about money, that data officer, or the data lead, has to think, has to make everyone think in the company about data assets, asset, just as well. And those rights, those responsibilities in that culture, they also change, right? Today, they're set this and this way because of privacy and policy X and Y and Z. But tomorrow, for example, as, as with the European union's new regulation around BI, there's a bunch of new responsibilities you'll have to think about. >> You mentioned security and about value and risk, which is certainly, they are part and parcel, right? If I have something important I've got to protect it because somebody else might want to, to create some damage, some harm and and steal my value, basically when that's, what's happening as you point out in the data world these days. So, so what kind of work are you doing in that regard in terms of reinforcing the importance of security culture, privacy culture, you know, this kind of protective culture within an organization so that everybody fully understands, you know, the risks but, also the huge upsides. If you do enforce this responsibility and these good behaviors that that obviously the company can gain from, and then provide value to their client base. So how do you reinforce that within your clients to spread that culture, if you will, within their organizations? >> Spreading a culture is not always an easy thing, And especially a lot of organizations think about the value around data, but to your point, not always about the risks that come associated with it. Sometimes just because they don't know about it yet, right, there's new architectures that come into play, like the clouds and that comes with a whole bunch of new risks. That, that's why one of the things that we recommend always to our customers and to data officers in our customer's organizations, is that next to establishing that, that data literacy, for example, and working on data products is that they also partner strongly with other leaders in their organization. On the one hand, for example, the legal folks, where typically you find the the aspects around privacy and on the other hand, the information security folks, because if you're building up sort of map of your data, look at it like a castle, right, that you're trying to protect. If you don't have a map of your castle, with the strong points and the weak points, and you know where people can build, dig a hole under your wall or what have you, then it's very hard to defend. So, you have to be able to get a map of your data, a data map if you will, know what data is out there. Who its being used by, and why and how, and then you want to prioritize that data, which is the most important what are the most important uses and put the appropriate protections and controls in place. And it's fundamental that you do that together with your legal and information security partners because you may have as a data lead that you may have the data knowledge, the data expertise but, there's a bunch of other things that come into play when you're trying to protect, not just the data but, really your company on its data as a whole. >> No, you Were talking about 2025 a little bit ago, and I thought good for you, that's quite a crystal ball that you have it, you know looking to, you know, with the headlights that far down the road, but I know you have to be, you know that kind of progressive thinking is very important. What do you see in, in the long-term for number one, your kind of position as a chief data citizen, if you will, and then the role of the chief data officer, which you think is kind of migrating toward that citizenship, if you will. So, maybe put on those long-term vision goggles of yours again, and tell me, what do you see as far as these evolving roles and, and these new responsibilities for people who are CEOs these days? >> Well, 2025 is closer than we think right? Then obviously, my crystal ball is as fuzzy as everyone else's but, there's a few things, that trends that you can easily identify and that we've seen by doing this for so long at Collibra. And one is the, the push around data. I think last year, the years, 2020,` where sort of COVID became the executive director of digitalization. Forced everyone to think more about digital, and I expect that to continue. So, that's an important aspect. The second important aspect that I expect to continue for the next couple of years, easily in 2025 is the whole movement to the cloud. So these cloud native architectures become important, as well as the, you know, preparing your data around it, preparing your policies around it, etc.. I also expect that privacy regulations will continue to increase as well as the needs to protect your data assets. And I expected a lot of key data officers will also be very busy building out those data products. So if you, if you take that that trend then, okay data products are getting more important for key data officer's, then data quality is something that's increasingly important today to get right, otherwise, becomes a garbage in garbage out kind of situation, where your data products are being fed bad foods and ultimately their outcomes aren't very clear. So for us, for the chief data officers, I think it was about one of them in 2002, and then 2019 ish, let's say there were 10,000. So there's plenty of upsides for the chief data officer there's plenty of roles like that needed across the world. And they've also evolved in, in responsibility. And I expect that their position, you know, as it it is really a C-level position today in most organizations. Expect that, that trend will also continue to grow. But ultimately those chief data officers have to think about the business, right? Not just the defensive and offensive positions around data, like almost policies and regulations but, also the support for businesses who are today, shifting very fast and will continue to, to digital. So, those key data officers will be seen as key notes. Especially when they can build out the factory of data products that really supports the business. But at the same time, they have to figure out how to reaching all of the branch to their technical counterparts, because you cannot build a factory of data products in my mind at least, without the proper infrastructure. And that's where your technical teams come in. And then obviously the partnerships with your video and information security folks, of course. >> Well heroes, everybody wants to be the hero. And I know that's a, you painted a pretty clear path right now, as far as the chief data officer's concerned and their importance and the value to companies down the road. Stan, we thank you very much for the time today and for the insight, and wish you continued success at the conference. Thank you very much. >> Thank you very much. Have a nice day. Stay healthy. >> Thank you very much Stan Christiaen's joining us, talking about chief data citizenship, if you will, as part of data citizens, 21 the conference being put on by Collibra. I'm John Walls. Thanks for joining us here on the cube. (upbeat music)

>>It's my pleasure to be one of the hosts of the cube on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years, the cube has been following the trail of data. And with the relentless March of data growth, this idea of a single version of the truth has become more and more elusive. Moreover data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is many sued as the CTO and co-founder of Reltio Maneesh. Welcome to the program. >>Thank you, Dave. It's a pleasure to be here. >>Okay. Let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with, with data as a source of digital innovation. >>They, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011, there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making, uh, compute capabilities available at scale to solve large data problems was becoming real impossible. The second thing that we saw was, uh, this big trend of, uh, you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone. And, uh, we are seeing more of the best of breed application type of a landscape where even if you look within a specific function, let's say sales or marketing, you have more than a dozen applications that any company is using today. >>And that trend was starting to emerge where we knew very well, that the number of systems that we would have to work with would continue to increase. And, uh, that created a problem of where would you get the single source of truth or the single best version of a customer, a supplier, a product that you're trying to sell those types of critical pieces of information that are core to any business that's out there today. And, um, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of a capability and for us to provide this capability in the cloud as a software, as a service, uh, uh, offering. So that's where, uh, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos and create a unified view of the core critical information that these companies run on. >>Yeah. I mean, the cloud is this giant, you know, hyper distributed system data by its very nature is distributed. It's interesting what you were sort of implying about, you know, the days of the monolithic app are gone by my business partner years ago, John furrier and the cube said data is going to become the new development kit. And we've certainly seen that with the, the pandemic, but tell us more about Reltio and how you help customers deal with that notion of data, silo, data silos, data fragmentation, how do you solve that problem? >>So, data fragmentation is what exists today. And, um, you know, with the Reltio, uh, software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented, siloed, uh, applications or data sources that they have within their enterprise at the same time. Um, there's a lot of dependence on the third party data. You know, when you think about, uh, different problems that you're trying to solve, you have, uh, for B2B type of information that in Bradstreet type of data providers in life sciences, you have IQ via type of data providers. Um, you know, as you look at other verticals, there is a specialized third-party data provider for any, and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know, who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. >>Um, and that's where Reltio fits in as the only platform that can help stitch together, this kind of, uh, information and create a 360 degree view that spans all the data silos and provides that for real-time use for BI and analytics to benefit from, for data science to benefit from. And then this emerging notion of, uh, data in itself is a, um, you know, key starting point that is used by us, uh, in order to make any decisions, just like, uh, we go, you know, if I, they wanted to look at information about you, I would go to places like LinkedIn, look up the information. And then our, my next set of decisions with that information, if somebody wanted to look up information on Reltio, they would go to, let's say Crunchbase as an example, and look up, uh, who are the investors? How much money have we raised all those details that are available? It's not a CRM system by itself, but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide, uh, as a part of the Reltio platform capabilities. >>Awesome. Thank you. And I want to get into the, to the tech, but before we do, maybe we just cut to the chase and maybe you can talk about some of the examples of, of Reltio and action. Some of the customers that you can talk about, maybe the industries that are, that are really adopting this. W what can you tell us there, Maneesh, >>Um, we work across a few different verticals, some of the key verticals that we work in our life sciences, um, and travel and hospitality and financial services, insurance, um, S uh, retail, as an example, those are some of the key verticals for us, but, uh, to give you some examples of, uh, the type of problems that customers are solving with Reltio as the data unification platform, um, let's take CarMax as an example, CarMax is a customer who's in the business of, uh, buying used cars, selling used cars, servicing those used cars. And then, um, you know, you as a customer, don't just transact with them. Once you, you know, you've had a car for three years, you go back and look at what can you trade in that car for, but in order for CarMax to provide a service to you that, uh, goes across all the different touch points, whether you are visiting them at their store location, uh, trying to test drive a car or viewing, uh, information about the various vehicles on their website, or just, uh, you know, punching in the registration number of your car, just to see what is the appraisal from them in terms of how much will they pay for your car? >>This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points and the type of information that they use, uh Reltio for aggregating, unifying, and then making available across all these touch points is all of the information about the customers, all of the information about, uh, the, uh, household, uh, you know, the understanding that they're trying to achieve because, uh, life events can, uh, be buying signals, uh, for, uh, consumers like uni, as well as, uh, who was the, um, associate who helped you either in the selling of a car buying of a car, because business is all about building relationships for the longer term lifetime value that they want to capture. And in that process, um, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, uh, there is a lot of information in order to price it, right, that needs to be gathered, uh, from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio, and then made available, uh, through API APIs or through other methods, and means to the various applications can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run end to end. Well, it sounds like >>That's come along. Sorry. >>I was just going to say it that's one example and, uh, you know, across other verticals that are other similar examples of how companies are leveraging, Reltio >>Just say, can come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and, and, you know, happy to dig into some other examples, but, but I wonder how does it work? I mean, what's the magic behind it? What's the, the tech look like, I mean, obviously you leveraging AWS, maybe you could talk about how so, and maybe some of the services there and some of your unique IP. >>Yeah. Um, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, uh, you know, if you think about, uh, the problem itself, uh, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. Um, you know, for example, I have been in this area was, uh, responsible for creating some of the previous generation capabilities and, uh, most of the friction in those previous generation MDM or master data management type of solutions, um, as the, you know, the technical term that is used to refer to this area, uh, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that, uh, customers want to capture, whether it is, uh, you know, about a patient or a product, or let's say a supplier that you're working well. >>Uh, there is always additional information that you can capture and, uh, you know, use to better inform the decisions for the next engagement and, uh, that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use at scale compute capabilities in the cloud, um, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information, just locking it in a data warehouse has been sort of the problem in the past. And you talked about the clickstream analysis, uh, analytics has a place, but most of the analytics is a rear view mirror picture of the, uh, you know, work that you have to do, versus everybody that we talked to, uh, as a potential customer, wanted to solve the problem of what can we do at the point of engagement, how can we influence decisions? >>So, you know, I'll give you an example. I think, uh, everybody's familiar with Quicken loans, um, as the mortgage lender and, uh, in the mortgage lending business, uh, Quicken loans is the customer who's using Reltio as the customer data, um, unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time window, um, you know, anywhere from 10 minutes to about an hour, where if somebody expresses an interest in refinancing or getting a mortgage, they have to close that, uh, business within that, uh, Hart window, the conversion ratios are exponentially better in that hot window versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage, uh, at. And, uh, they've been able to use this notion of real time data, where as soon as you come in through the website, or if you come in through the rocket mortgage app, or you're talking to a broker by calling the one 800 number, they are able to triangulate that it's the same person coming from any of these different channels and respond to that person, whether an offer, uh, ASAP so that, uh, there is no opportunity for the competition to get in and present you with a better offer. >>So those are the types of things where the time to, uh, conversion or the time to action is being looked at. And everybody's trying to shrink that time down, uh, that ability to respond in real time with the capabilities was sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities. And now customers are able to benefit from that. >>That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket, and when you experience that environment, it's totally different than anything you've ever seen before. So it's helpful to hear you explain, like what's behind that because it's, it's truly disruptive. And I, and I'll tell you, the other thing that, that sort of triggered a thought was that we use the word realtime a lot, and we try to develop years ago. We said, what does real-time really mean? And the, the answer we CA we landed on was before you lose the customer, and that's kind of what you just described. Uh, and that is what gives as an example, a quick and a real advantage again, having experienced it firsthand. It's, it's pretty, pretty tremendous. So that's a nice, that's a, that's a nice reference. Um, so, and the other thing that struck me is that what I wanted to ask you, how it's different from sort of legacy master data management solutions, and you sort of described that they've seized to me, they got to take their, their traditional on-prem stack, rip it out, stick it in the cloud is okay, we got our stack in the cloud. >>Now your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a, from an CTO's perspective, what's your, >>Yeah. The clean sheet of paper is the luxury that we have, you know, having seen this movie before having, um, you know, looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, um, you know, across all of our customers, we are today managing, um, uh, about 6.5 billion consolidated profiles of people, organizations, product locations, um, you know, assets, uh, those kinds of details. And these are, these are the types of, uh, crown jewels of the business that every business runs on. You know, for example, if you wanted to, um, let's say you're a large company, like, uh, you know, Ford and you wanted to figure out how much business are you doing, where the, uh, you know, another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. >>It's been a very difficult answer to understand what is the total book of business that they have with that other, um, big, uh, customer and, uh, you know, being able to have the right, uh, unified, uh, relevant, rich clean as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, uh, you know, drive, uh, any kind of, uh, conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. Um, you have to have that foundation of clean data to work with in order to get to those answers. >>Nice. Uh, and then I had questions on just the model is this, it's a SAS model. I presume, how, how is it priced? Do you have a, do you have a freemium? How do I get started? Maybe you could give us some color. >>Yeah, we are a SAS provider. We do everything in the cloud, uh, offer it as a SAS offering, um, for customers to leverage and benefit from our pricing is based on the volume of, uh, uh, consolidated profiles. And the, I use the word profiles because this is not the traditional, uh, data model where you have rows columns, foreign keys. This is a, you know, a profile of a customer, regardless of attribution or any other details that you want to capture. And, um, you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Uh, customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, uh, you know, off these different types of data domains, customer, patient provider, uh, product, uh, asset, those types of details. But, uh, then they grow and some of the customers, uh, HP Inc, as a customer is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use the single source of truth capabilities provided by Reltio. >>And your relationship with AWS you're, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >>Yeah. AWS has been a key partner for us, uh, since the very beginning, uh, we are now on the marketplace. Uh, customers can start with the free version of the product, um, and start to play with the product, understand it better, uh, and then move into the paid tier, um, you know, as they bring in more data, uh, into Reltio. And, uh, you know, we also, uh, have, uh, the partnership with AWS where, uh, you know, customers can benefit from the relationship where they are able to, um, uh, use the, the spend against Reltio to offset the commitment credits that they have for AWS, um, you know, as a cloud provider. So, uh, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >>Nice that love, love, those credits, um, company update, uh, you know, head count funding, revenue trajectory, what kind of metrics are you comfortable sharing? >>So, uh, we are currently, uh, at about, um, you know, slightly North of 300 people, uh, overall at rail queue, we will, uh, grow from 300 to about 400 people this year, uh, itself. Uh, we are, uh, uh, you know, we just put out a press release, uh, where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are, uh, looking at, uh, crossing the a hundred million dollar ARR, um, uh, threshold, uh, later this year. So we're on a great growth trajectory and, uh, the businesses, uh, performing really well. And we are, uh, looking at working with more customers and helping them solve this, uh, uh, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >>That's some impressive growth. Congratulations, w w we're, I'm sure adding a hundred people you're hiring all over the place, but where we get some of your priorities. >>So, um, you know, the, as the business is growing, we are spending equally both on the R and D side of the house, uh, investing more there, but at the same time, also on our go to market, uh, so that we can extend our reach, make sure that, uh, more people know about, uh, Reltio and can start leveraging the benefit of, uh, the technology that we have built on top of, uh, AWS. >>Yeah. I mean, it sounds like you've obviously nailed product market fit, and now you're, you know, scaling and scaling the go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, why, what was prompted that move >>Problems of luxury, uh, you know, as I like to call them, uh, once you know, that you're on a great growth trajectory and, uh, the business is performing well, it's all about, uh, figuring out ways of, uh, you know, making sure that you can drive harder and faster towards that growth, uh, milestones, uh, that you want to achieve. And, uh, you know, for us, uh, the story is no different. Uh, the team has done a wonderful job of, uh, making sure that we can build the right platform, um, you know, work towards this opportunity, that PC, which by the way, um, they just to share with you, uh, MDM or master data management has always been underestimated as a, uh, you know, yes, there is a problem that needs to be solved, but the market sizing was, uh, in a, not as clear, but some of the most recent, uh, estimates from analysts like Gartner, but the, uh, you know, sort of the new incarnation of, uh, data unification and master data management at about a $30 billion, uh, you know, uh, Tam or this market. >>So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, uh, I looked at, uh, you know, how could we scale the business faster and have the right team to work, uh, help us maximize the opportunity. And that's why, uh, you know, we decided, uh, that it was the right point in time for me to bring in somebody who's, uh, worked, uh, at, uh, the stretch of, you know, taking a company from just a a hundred million dollars in ARR to, uh, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, uh, you know, has had that experience and having him take on the CEO role, uh, really puts us on a tremendous, uh, our path to tremendous growth and achieving that, uh, with the right team. >>Yeah. And I think I appreciate your comments on the Tam. I love to look at the Tam and to do a lot of Tam analysis. And I think a lot of times when you define the future Tam based on sort of historical categories, you sometimes under count them. I mean, to me, you guys are in the, the, the digital business business. I mean, the data transformation, the company transformation business, I mean, that could be order of magnitude even bigger. So I think the future is bright for your company. Reltio Maneesh. And thank you so much for coming on the program really appreciate. >>Well, thanks for having me, uh, really enjoyed it. Thank you. >>Okay. Thank you for watching. You're watching the cubes startup showcase. We'll be right back.

(upbeat music) >> It's my pleasure, to be one of the hosts of theCUBE on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years theCUBE has been following the trail of data. And with the relentless match of data growth this idea of a single version of the truth has become more and more elusive. Moreover, data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand, the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is Manish Sood the CTO and co-founder of Reltio. Manish, welcome to the program. >> Thank you, Dave. It's a pleasure to be here. >> Okay, let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement, cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with data as a source of digital innovation. >> Dave, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011 there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making compute capabilities available at scale to solve large data problems was becoming real and possible. The second thing that we saw was this big trend of you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone and we are seeing more of the best of breed application type of a landscape where even if you look within a specific function let's say sales or marketing, you have more than a dozen applications that any company is using today. And that trend was starting to emerge where we knew very well that the number of systems that we would have to work with would continue to increase. And that created a problem of where would you get the single source of truth or the single best origin of a customer, a supplier, a product that you're trying to sell, those types of critical pieces of information that are core to any business that's out there today. And, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of capability and for us to provide this capability in the cloud as a software, as a service offering. So that's where, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos, and create a unified view of the core critical information that these companies run on. >> Yeah, the cloud is this giant, you know hyper distributed system, data by its very nature is distributed. It's interesting what you were sort of implying about you know, the days of the monolithic app are gone, but my business partner years ago John Furrier at theCUBE said, data is going to become the new development kit. And we've certainly seen that with the pandemic but tell us more about Reltio and how you help customers deal with that notion of data silos, data fragmentation, how do you solve that problem? >> So data fragmentation is what exists today. And, with the Reltio software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented siloed applications or data sources that they have within their enterprise. At the same time, there's a lot of dependence on the third party data. You know, when you think about different problems that you're trying to solve, you have for B2B type of information that in Bradstreet type of data providers, in life sciences you have IQVIA type of data providers. You know, as you look at other verticals that is a specialized third party data provider for any and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. And that's where Reltio fits in as the only platform that can help stitch together this kind of information and create a 360 degree view that spans all the data silos and provides that for real-time use, for BI and analytics to benefit from, for data science to benefit from, and then this emerging notion of data in itself is a, you know, key starting point that is used by us in order to make any decisions. Just like we go, you know, if I they wanted to look at information about you, I would go to places like LinkedIn, look up the information, and then on my next set of decisions with that information. If somebody wanted to look up information on Reltio they would go to, let's say crunchbase as an example and look up, who are the investors? How much money have we raised? All those details that are available. It's not a CRM system by itself but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide as a part of the Reltio platform capabilities. >> Awesome, thank you. And I want to get into the tech, but before we do maybe we just cut to the chase and maybe you can talk about some of the examples of Reltio and action, some of the customers that you can talk about, maybe the industries that are really adopting this. What can you tell us there Manish? >> We work across a few different verticals some of the key verticals that we work in are life sciences and travel and hospitality and financial services, insurance retail, as an example. Those are some of the key verticals for us. But to give you some examples of the type of problems that customers are solving with Reltio as the data unification platform, let's take CarMax as an example,. CarMax is a customer who's in the business of buying used cars, selling used cars servicing those used cars. And then, you know, you as a customer don't just transact with them once, you know, you've had a car for three years you go back and look at what can you trade in that car for? But in order for CarMax to provide a service to you that goes across all the different touch points whether you are visiting them at their store location trying to test drive a car or viewing information about the various vehicles on their website, or just you know, punching in the registration number of your car just to see what is the appraisal from them in terms of how much will they pay for your car. This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points. And the type of information that they use relative for aggregating, unifying, and then making available across all these touch points, is all of the information about the customers, all of the information about the household, you know, the understanding that they are trying to achieve because life events can be buying signals for consumers like you and I, as well as who was the associate who helped you either in the selling of a car, buying of a car, because their business is all about building relationships for the longer term, lifetime value that they want to capture. And in that process, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, there is a lot of information in order to price it right, that needs to be gathered from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio and then made available through APIs or through other methods and means to the various applications, can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run and to end. >> Well, sounds like we come along, (indistinct). >> I was just going to say that's one example and, you know across other verticals, that are other similar examples of how companies are leveraging, Reltio >> Yeah, so as you say, we've come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and you know happy to dig into some other examples, but I wonder how does it work? I mean, what's the magic behind it? What's the tech look like? I mean, obviously leveraging AWS, maybe you could talk about how, so, and maybe some of the services there and some of your unique IP. >> Yeah, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, you know, if you think about the problem itself, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. You know, for example, I have been in this area was responsible for creating some of the previous generation capabilities and most of the friction in those previous generation MDM or master data management type of solutions as the you know, the technical term that is used to refer to this area, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that customers want to capture, whether it is, you know, about a patient or a product or let's say a supplier that you're working with, there is always additional information that you can capture and you know use to better inform the decisions for the next engagement. And that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use add scale compute capabilities in the cloud, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information just locking it in a data warehouse has been sort of the problem in the past, and you talked about the clickstream analysis. Analytics has a place, but most of the analytics is a real view mirror picture of the, you know, work that you have to do versus everybody that we talk to as a potential customer wanted to solve the problem of what can we do at the point of engagement? How can we influence decisions? So, you know, I'll give you an example. I think everybody's familiar with Quicken loans as the mortgage lender, and in the mortgage lending business, Quicken loans is the customer who's using Reltio as the customer data unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time vendor, you know anywhere from 10 minutes to about an hour where if somebody expresses an interest in refinancing or getting a mortgage they have to close that business within that hot vendor. The conversion ratios are exponentially better in that hot vendor versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage at? And they've been able to use this notion of real time data where as soon as you come in through the website or if you come in through the rocket mortgage app or you're talking to a broker by calling the 1800 number they are able to triangulate that it's the same person coming from any of these different channels and respond to that person with an offer ASAP so that there is no opportunity for the competition to get in and present you with a better offer. So those are the types of things where the time to conversion or the time to action is being looked at, and everybody's trying to shrink that time down. That ability to respond in real time with the capabilities were sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities, and now customers are able to benefit from that. >> That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket when you experience that environment, it's totally different, than anything you've ever seen before. So it's helpful to hear you explain like what's behind that because, it's truly disruptive and I'll tell you the other thing that sort of triggered a thought was that we use the word realtime a lot and we try to develop years ago. We said, what does real-time really mean? And the answer we landed on was, before you lose the customer, and that's kind of what you just described. And that is what gives as an example a quick and a real advantage again, having experienced it firsthand. It's pretty, pretty tremendous. So that's a nice reference. So, and the other thing that struck me is, I wanted to ask you how it's different from sort of legacy Master Data Management solutions and you sort of described that they've since to me they've got to take their traditional on-prime stack, rip it out, stick it in the iCloud, it's okay we got our stack in the cloud now. Your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a CTO's perspective, what's your take? >> Yeah, the clean sheet of paper is the luxury that we have. You know, having seen this movie before having, you know looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, you know, across all of our customers, we are today managing about 6.5 billion consolidated profiles of people, organizations, product, locations, you know, assets, those kinds of details. And these are the types of crown jewels of the business that every business runs on. You know, for example, if you wanted to let's say you're a large company, like, you know, Ford and you wanted to figure out how much business are you doing, whether, you know another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. It's been a very difficult to answer to understand what is the total book of business that they have with that other big customer. And, you know, being able to have the right, unified, relevant, ready clean information as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, you know drive any kind of conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. You have to have that foundation of clean data to work with in order to get to those answers. >> Nice, and then I had questions on just analysis, it's a SAS model I presume, how is it priced? Do you have a freemium? How do I get started? Maybe you could give us some color on that. >> Yeah, we are a SAS provider. We do everything in the cloud, offer it as a SAS offering for customers to leverage and benefit from. Our pricing is based on the volume of consolidated profiles, and I use the word profiles because this is not the traditional data model, where you have rows, columns, foreign keys. This is a profile of a customer, regardless of attribution or any other details that you want to capture. And you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, you know, off these different types of data domains, customer, patient, provider, product, asset, those types of details, but then they grow and some of the customers HPInc, as a customer, is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use, the single source of truth capabilities provided by Reltio. >> And, and your relationship with AWS, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >> Yeah, AWS has been a key partner for us since the very beginning. We are now on the marketplace. Customers can start with the free version of the product and start to play with the product, understand it better and then move into the paid tier, you know as they bring in more data into Reltio and, you know be also have the partnership with AWS where, you know customers can benefit from the relationship where they are able to use the spend against Reltio to offset the commitment credits that they have for AWS, you know, as a cloud provider. So, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >> Nice, love those credits. Company update, you know, head count, funding, revenue trajectory what kind of metrics are you comfortable sharing? >> So we are currently at about, you know, slightly not at 300 people overall at Reltio. We will grow from 300 to about 400 people this year itself we are, you know, we just put out a press release where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are looking at crossing the hundred million dollar ARR threshold later this year. So we are on a great growth trajectory and the business is performing really well. And we are looking at working with more customers and helping them solve this, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >> That's some impressive growth, congratulations. We're, I'm sure adding hundred people you're hiring all over the place, but where we are some of your priorities? >> So, you know, the, as the business is growing we are spending equally, both on the R and D side of the house investing more there, but at the same time also on our go to market so that we can extend our reach, make sure that more people know about Reltio and can start leveraging the benefit of the technology that we have built on top of AWS. >> Yeah, I mean it sounds like you've obviously nailed product market fit and now you're, you know, scaling the grip, go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, what was prompted that move? >> Problems of luxury, you know, as I like to call them once you know that you're in a great growth trajectory, and the business is performing well, it's all about figuring out ways of, you know making sure that you can drive harder and faster towards that growth milestones that you want to achieve. And, you know, for us, the story is no different. The team has done a wonderful job of making sure that we can build the right platform, you know work towards this opportunity that we see, which by the way they've just to share with you, MDM or Master Data Management has always been underestimated as a, you know, yes there is a problem that needs to be solved but the market sizing was in a, not as clear but some of the most recent estimates from analysts like Gartner, but the, you know, sort of the new incarnation of data unification and Master Data Management at about a $30 billion, yeah, TAM for this market. So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, I looked at, you know how could we scale the business faster and have the right team to work help us maximize the opportunity. And that's why, you know, we decided that it was the right point in time for me to bring in somebody who's worked at the stretch of, you know taking a company from just a hundred million dollars in ARR to, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, you know, has had that experience and having him take on the CEO role really puts us on a tremendous path or path to tremendous growth and achieving that with the right team. >> Yeah, and I think I appreciate your comments on the TAM. I love to look at the TAM and to do a lot of TAM analysis. And I think a lot of times when you define the the future TAM based on sort of historical categories, you sometimes under count them. I mean, to me you guys are in the digital business. I mean, the data transformation the company transformation business, I mean that could be order of magnitude even bigger. So I think the future is bright for your company Reltio, Manish and thank you so much for coming on the program. Really appreciate it. >> Well, thanks for having me, really enjoyed it. Thank you. >> Okay, thank you for watching. You're watching theCUBEs Startup Showcase. We'll be right back. (upbeat music)

live from Orlando Florida it's the cube coverage conf 18 got to you by spunk welcome back to Splunk kampf 18 hashtag Splunk conf 18 you watching the cube the leader in live tech coverage we go out to the events we extract the signal from the noise I'm Dave Volante with my co-host Stu many men we love to talk to the customers too we've had seven out of ten of our interviews today have been with the customers Tony Alessandra was here as the chief architect at the co-operators group limited insurance company up in Canada leader in that field Tony thanks so much for coming on the yeah it's great to be here thanks for having me so we were talking off-camera about some of the innovation that's going on in Toronto and want to get to that innovation is actually in your long title yeah there's the time but tell us about your role as chief architect and then some of the other areas that you touch yes certainly so my primary role at the co-operators group is to serve as chief architect for the group of companies and so it's a fancy term to mean that I influence how we invest in technology and process for our strategy and for our operational imperatives I also have responsibility for information security within our organization so I have a great team led by a C so at the co-operators group and essentially our role is to to protect the data of our clients right we have a million unique clients across Canada that entrust us with a lot of personal and confidential data we have thousands of financial advisers throughout the company and so we have retail outlets throughout the entire geography of Canada and essentially we collect a lot of data and and with respect to policies for commercial businesses for private clients for subscribers etc and I also manage an innovation portfolio for the organization and so it's actually I'll work with our business stakeholders within the organization to figure out how we could accelerate new businesses accelerate new capabilities with the use of technology who's excited that's a big big big role that you have if I want to send the the regime you have for security say the seaso reports to you yes sir and there's a set CIO there right there is yeah so I report to the to the executive vice president and CIO of the co-operators group of companies and and my responsibility within the organization is to report back to our CIO on all the responsibilities that I talked to you about okay so this the C so technically reports up through the CIO and C so reports up through me into the CIO yeah which is that's a whole other interesting discussion maybe if we have time we could talk about that absolutely um so a lot of data I mean we think about insurance company regulated you got your claim systems which are critical you have your agent systems which are also critical different types of data both data on customers but when you talk about the data that you guys collect where's it come from what are you trying to do with with that data yes so so you know I'll start I'll start with the motive right the problem that we're trying to solve and so I'll say first and foremost we're an insurance company we offer assurance and protection to our clients right and so in the process of offering assurance and protection to our clients you know they entrust us with massive amounts of data like you know as we as we mentioned before but we'll also need to set a good example because a lot of the assurance some of the assurance that we offer to our clients is also cyber protection we offer cyber insurance to our clients we need to set a good example we need to demonstrate resilience right Splunk is a primary tool in our Arsenal where we're showing our clients that we have good resilience to be able to detect and respond to security threats when they happen that's part of our mandate right so our responsibility with respect to using Splunk is to collect data from all of our major systems within our organization we use Blonk to monitor we use Blanc to detect and we also use Splunk to respond when something is going on what is this is really interesting you're being proactive about from your you know from an actuarial standpoint you rate your risk you're being very proactive when many if not most insurance companies would do is say ok what what's the history yeah and are there any high-profile breaches and yeah as opposed to what you're doing like sounds like you're really inspecting what the policies and the procedures and the technology of your clients is I think you hit on an important point right and so the important point is that you know the the the art of actuarial science is to rely on a lot of history in the past you know to predict the risks of the future but the reality is that model is falling apart very quickly because there is very little history for cyber threats and the other aspect of it is its inconsistent its evolving and it's changing on a regular basis right and so that's why you use platforms like Splunk use platforms like spunk to detect new threats and to end to in sort of to advance new correlations what should we be concerned about which threats are relevant to us which ones can we ignore and unless you have good platforms to do correlation unless you have good automation you're gonna need a large army of people to chase things that may not be relevant to either you or your clients so Tony your industry usually has quite a bit of M&A as to kind of fund the growth that's going on curious how does Splunk in your data strategy fit into M&A type a quiz yeah yeah and so I think that's one of the biggest potential uses of Splunk for us right and so the way that insurance is evolving right now is insurance companies are all trying to figure out how they get involved in the loss prevention game right in the past it's all been about assurance right it's all been about protection and so when you think about the Internet of Things is one of the biggest untapped opportunities for insurance companies it's all about data right so smart homes smart buildings cars outfitted with telematics so it's every history you wearing wearable devices so in terms of health and you know a health insurance and life insurance protection etc all of this data is meaningful to offer value to clients beyond what we've been able to do in the past one of the things we've looked at I know the industry is looking at is well how do you value that data is that something your company's gotten into yeah absolutely and so you know part of what we need to figure out is how to model that data to give the right level of engagement to the customer so to create that two-way engagement with the customer right how am i doing how am i driving is the weather a threat for me in in the in the foreseeable future in terms of things that I need to protect is there a hailstorm coming you know should I should I you know have alerts and and and you know provide you know ask clients to move some of their valuables indoors I mean all of these are things that will increase that engagement with our clients because face it with insurance your clients engage with you two times a year right two major time policy renewal and if they're unfortunate enough to have a claim right we need to have a but we need to have a better game much more proactive game with them so you're in other ways a risk consultant with your your clients right yeah so describe that so you client comes to you says they're interested or you go to them they're interested in in in in a security you know insurance where does it start do you ask them you have Splunk do you advise them as to what are you going to look at their policies and procedures well how does it work so so I think you know Splunk is one of those valuable assets that enables the capability right insurance you know the game is becoming all about data having massive amounts of data and being able to use that data to help assess the risks for a client properly right because without having good data everything is a great guest these days I mean with climate change with cyber risks evolving with customers preferences changing data is going to be the meaningful difference in terms of understanding what risks a client has what the probability is and how to write a meaningful policy for them where they're engaged and they understand it well enough as well understand it well enough to prevent some of their losses and that's really the issue that we're trying to figure out how do we help clients understand their risks and then prevent losses prevent or minimize losses for them and and what role does Splunk play in that you you know your your your client are you a an advisor or you encourage your customers to use belong counters at all so we're talking about our future roadmap right now and this is what we're trying to figure out what's blanc this is where we see the strategic opportunities with blah right and so when we look at the co-operators the way that co-operators has been using Splunk in the past is for their security sim we were one of the very first large companies in Canada to put our security sim on Splunk we were the very first large company in Canada to put our sim in Splunk clout right and so we we you know we're very proud with being able to work with Splunk for for charting that course right for setting the example our next course is how do we leverage a platform as powerful as Splunk now to give value to our customers we're protecting our customers data assets and now it's about returning valuable insights back to the customers in terms of loss prevention that's our forward-thinking approach in terms of how we stay ahead in terms of leveraging this as a unique asset as a unique capability so your leader you've got street cred you can now extend that to your client base I mean for an insurance company risk you know chaos is just cash as I like to say it's opportunity for you guys and to the extent that you can help clients mitigate that risk to win-win it's essentially for them the reduction in expected loss it can actually hate to say this but could actually pay for the insurance which is let's take attractive it's a massive win and I think you know the other part you know that people need to think differently about is the way that people consume insurance will change dramatically as well in the next tenure so and so where you think now that you know your typical home and auto insurance you will buy an annual policy well the reality is that Home Sharing car sharing ride-sharing insurance will change to what we call episodic oh right and so essentially you'll be consuming insurance for an activity right and the only way that you'll be able to sort of drive that activity in a meaningful way is to have a lot of data on that activity right where are you driving how did you drive you know what what are the risks associated to when you're driving in the geography that you're driving where are you renting out your home what are the rooms to which client and so understanding all of those elements give us the best opportunity at giving you just in time insurance for the right risks surance as a service I love it personalized for me I mean the model generally item as a consumer is broken it's very bespoke my insurance company doesn't know who I am it's just to check a bunch of boxes off and they sent me another form every year and advised some new things and I don't even know what half the time they are that's exactly right right then the and the only way you're able to personalize is to have all of that data on an individual on a company on an event right so we give you insurance for you based on your needs based on your risks Tony we know there's a lot of AI happening up in the Toronto area yeah maybe our audience might not know tell them a little bit about that and how you're thinking about AI and what interest you have and what's Blanc's talking about when they talk about AI yeah you're absolutely right I mean there's a loop there's a massive amount of artificial intelligence activity in the Toronto Kitchener corridor within southern Ontario I would say it's early days for insurance in terms of how we leverage AI I think you know some of the early wins for us have been what we refer to as chat BOTS or virtual assistants right helping clients so this is basically speed and convenience for clients right clients need to know something very quickly very predictive short-tailed answers we're there for customers who choose to do that where it's going next is helping clients assess risk and predict outcomes associated to risks right and so there's a lot of different use cases that we're working there partnerships with startups partnerships with mainstream organizations like Splunk is an important partner for us in this area and of course academic institutions that are investing right this is all part of it for the sales channel for the risk channel for claims processing so imagine being able to submit a claim on a mobile device gathering all that data being able to correlate that data to say we've seen this before right based on the correlation here's your damages we could processes as quickly here's the experts you need to go to here's the restoration facilities that you'll engage those are massive opportunities for client service and for an ability for an insurance company to settle things quickly right we're talking about weather before it's obviously a changing dynamic has a change variable and maybe it's it's model Abel I don't know but but clearly weather incidents are on the rise have caught companies and probably insurance companies you know a little bit off guard you know climate change etc the boiling seas this we've heard yeah what do you guys what's your position on that how do you accommodate that and pass it on to your customers and well I think this is what we're well known for right and so first of all we're not gonna be able to control the weather but what we'd be able to do is prevent it from getting worse right and so when you'll hear the leadership within our organization talk especially our CEO our CEO is very passionate about building resilient communities and that starts with making sure that we're building communities in the right spots not in flood plains not in areas of high risk of forest fires or or other things that you could you know potentially prevent you know within a certain geography and so that's first and foremost right and so we're a leader in this space in Canada how do you become a leader in this area you collect data understand the geography understand the trends associated to the understand the future risks associated to those geographies based on weather trends and then lobby governments builders entrepreneurs everybody land development consortiums to say we need to build communities in better places we need to build more resilient communities and then thereafter it's making sure that you're leveraging data to be able to predict and minimize losses for clients in those areas right and that's what you'll use weather data for right who do I need to alert we have threats on the way what can we prevent how do we minimize these losses for Canadians I think the big risk that we all need to understand if the weather continues to change at the same pace are our you know people will not be able to afford the risks right and so the insurance will rise exponentially and and you know will we we won't have a sustainable model for the future so it's clear for you guys it's really all about the data one of the challenges that a lot of companies in your industry have is the data it's about the data for them to insurance companies you could argue our you know IT companies in many respects they develop products that are put together by technologists but a lot of the data is in silos yeah as Splunk allowed you to break down those silos and and is that yet part while you're a leader well like I could talk about what's where Splunk has been able to to offer us that that that ability is with security right and so we have data we have information security log data associated to our systems and our application everywhere on Prem our partner sites in our agency offices on different endpoint devices in the cloud with our different service providers so what Splunk has been able to do is us to be able to aggregate that data consume that data build valid use cases and to correlate that and raise proper alerts right that's our main priority right now is to build resilience with information security that knowledge will take us to these other areas that we want to do in offering now the value back to our clients right embed that value into our product offerings is our next logical step awesome Tony thanks very much for coming on the cube really appreciate it you're welcome it's good to meet you in the pleasure have the leaves changed in Toronto its Toronto by the way stew no tea it's coming it's coming fast Dave a lot a force to Minutemen thanks for watching we'll be right back after this short break you're watching the cube from Splunk Kampf 18 [Music]

>> Announcer: Live, from Washington, D.C. it's CUBEConversations with John Furrier. >> Hello, everyone, and welcome to special on the ground here with theCUBE in Washington, D.C. I'm John Furrier, the co-host of theCUBE, and co-founder of SiliconANGLE, as we explore the disruption in Washington, D.C. with cloud computing and all the hot stories we have Timothy Kotin who is the founder of SuperFluid Labs. Thanks for joining me today. >> Thanks so much, John. >> So you guys are doing some pretty disruptive stuff, obviously, societal change, and ventures for good. Social change is a big part of the stories we're covering. You're in the middle of it here at PeaceTech Accelerator. We're here at the United States Peace Institute. What's your story? >> Thanks for having me. SuperFluid Labs, my organization, is a data analytics firm working in Africa. What we do is we help small businesses to unlock their potential using the power of data. For some organizations, this means being able to deliver essential services to millions more people, so for some organizations, it means increasing revenues, and for some organizations, it means understanding opportunities for greater efficiency and productivity. >> Y'know, PeaceTech Labs and PeaceTech Accelerator as part of this global movement where people want to apply AI for good, data for good, and in some cases good is just business, right? Economists, economies are thriving with big data and cloud. You guys are are using the cloud to bring new business models to Africa, to start. You're going to land and expand and take over the world. What's the key thing for you? >> Great, thanks. So the key thing for us is really that in the last few years, there's been an explosion in data, globally. 90% of the data in the world was created in just the last two years, and this presents a huge opportunity to unlock impact for businesses, and so some of the clients that we work with, for example, one of our clients is providing off-grid solar systems for households in sub-Saharan Africa, and they innovate, the innovation, the key innovation behind this model is the ability to deliver energy access as a service, where individuals pay on a pay-as-you-go basis. >> It's interesting, you know, helping society is not just donating money, but enabling entrepreneurs to be successful. You're an entrepreneur, you're here at the Accelerator. How do you get off the ground? I mean, what's great about the cloud is you don't need to provision all these servers, you're using the cloud. How are you guys going from a zero-stage start to getting into the market? What technology are you using, what strategy are you deplyong? >> Excellent. I think innovations such as the cloud have really been essential to our business model. A decade ago, it would have been impossible to launch a business similar to ours, so we use several cloud providers. Obviously, Amazon Web Services is one of them and many others, and what these services have allowed us to do is they've allowed us to focus on the innovation that we are delivering, the solutions that we are delivering, and less on infrastructure, provisions, and worrying about power outages, networking and all of that. >> In Africa, what's the conditions there? I mean, obviously, mobile is everywhere, but there's no telephone lines, and you've got mobile RF flying all over the world. >> Mobile is huge in Africa. I'm going to tell you an interesting stat. In the next three years, there are going to be an additional three hundred million smartphones in sub-Saharan Africa. That's more than the population of the U.S. and that's just in the next three years. >> Huge growth market. >> Huge growth market. >> How are businesses adapting, 'cause this is there you're taking your angle, right, using data, and how does that connect to the proliferation of phones, and how do business folks use it? Is that where you want to target in terms of your solution. >> Excellent question. So, the most innovational businesses that we have seen have taken advantage of access to mobile phones to develop innovative business models. So we have banks, for example, in Kenya, that have developed mobile-only lending and savings products, and they've expanded from 40,000 customers in 2012, to over twenty million customers at the end of last year. >> What's the ecosystem like in Africa, and what's the entrepreneurial cross-over when you go outside the borders of Africa? Obviously, you know in other continents, other economies. How does it all working together? Is it Bitcoin, is it blockchain, is it just standard cloud, how is the emerging landscape in tech impacting the emerging growth inside Africa. >> It's really phenomenonal, and what is most exciting, especially for me, given my experience in the U.S. and in the West and also in Africa is that a lot of the patented technologies, whether that is AI or cryptocurrency, or blockchain, is actually being used to good effect, it's actually being used to deliver essential services in Africa, and you'd be shocked. I was telling someone the other day that when you talk about payments, money-transfer innovation, Africa is really the hotbed for this. >> So you see crypto and blockchain hot in Africa right now. >> It is, and it's being applied in many other use cases beyond payment. So, you have some companies are innovating in land title administration, using that for growth tech and many other use cases. >> Great for property, great for store of value. Talk about your journey here at the PeaceTech Accelerator. How is that working, obviously they're helping you guys, with they're providing a lot of services. Tell us about what those guys are doing. >> Great, well the time here, this is actually the third week of our time here, it's really been very interesting. We've been exposed to mentors who have generously given their time to come and share their experience as other previous or experienced entrepreneurs, or executives that run large corporations, and there's mentoring sessions, we're exposed to investors, we're exposed to a cohort of other similarly minded entrepreneurs. >> That's great because you've accelerated. I've got to ask you a question, as the entrepreneur, you're always seeking for, most entrepreneurs are always seeking for that data edge, y'know, trying to understand the market force, there's all that good stuff. What have you learned here at the PeaceTech Accelerator? What was the something that you said, "Wow, that's something that I never would have gotten." >> Very interesting. So one of the things that has really stood out during my time here is really the emphasis on the fact that business, that delivering great business, or delivering business for good can cut across multiple sectors, I mean, for profit businesses like mine, and I think that is very reassuring, to know that there's a growing recognition globally around the impact and the social good that businesses can deliver. >> So you're using mobile as your backbone for your connectivity, how is the Internet of Things, or IOT, and AI going to be part of your plan? You see that consuming most of your IP and lots of property? >> Very much so. So given the stats I gave earlier on around the growth and explosive growth of data, and the explosive growth of mobile access, that is going to be essential to our IP and our patents, and we thing that's what will really give us the edge in this market. >> Great, final question for you, does D.C. get this? I mean, D.C. certainly is trying to be more global, you're actually here in D.C. at Accelerator, what's your assessment of the Washington, D.C. culture here? >> I think D.C. really gets it. I mean I think D.C. is really the hub of a lot of international development, international outreach by the U.S. government and many other international organizations. So, my being here is actually of the fact that D.C. gets it, and I'm originally from Ghana and from Africa, and we have other members of our cohorts who are flying in from all over the world, and that's the true evidence. >> How's the cloud impacting you? The U.S. is helping you to bring that innovation, what kind of edge are you bringing with cloud computing? >> It's providing speed, it's providing cost-effectiveness, and it's also providing scalability, rapid scalability. >> All right, I'm John Furrier on the ground in Washington, D.C. where all the innovation's happening here, in the United States Peace Institute, we're here with PeaceTech Accelerator, I see great stuff happening, entrepreneurship in social sectors are really happening, AI is a big part of that, IOT, cloud, all the trends are helping out a new generation of start-ups. Thanks for watching. (upbeat music)

>> Announcer: From The Computer History Museum in Mountain View, California, it's theCUBE On The Ground with Accenture Labs' 30th anniversary celebration. >> Welcome to a special CUBE On The Ground presentation of our coverage of Accenture Labs' 30th birthday party. They've been in business for 30 years. Accenture is doing some great things from here, 30 years ago, to the future. Future's all about AI, blockchain, you name it, virtual reality, augmented reality. I'm John Furrier with theCUBE. Our next guest is Joe Mikhail, who's the chief revenue officer of a company called Meta. Welcome to the conversation here at the Accenture Labs party. >> Thank you, John, and congratulations to Accenture. >> They have this theme, Magical, but really, it is a magical time. At my age, I've been in this business long enough, it's like I wish I was 20 again, because the technology is really amazing. Augmented reality, you guys do a lot of new stuff. Tell us what your company does, and you guys are doing some really cool stuff. >> Absolutely. We're really pioneering in augmented reality. For those who don't really understand augmented reality, it basically overlays digital data and virtual optics in the real world. With that comes, really, a change in paradigm of what's possible. Our forte is really in being a spatial interface company. We're not only changing the fidelity of the images you see in augmented reality, but how you interface with them, naturally based on neuroscience. >> Joe, first, take a step back, 'cause a lot of folks here in Silicon Valley, they all know what AR is, or augmented reality, something analyst relations work. But augmented reality is the big future. I always say AI stands for, not artificial intelligence, but augmented intelligence. That's what software's doing. What's your definition of augmented reality? >> Augmented reality is the ability to really change how man/machine interface around information, objects outside of 2D panels, and bringing the digital into our world. >> Let's talk about your company, Meta. You guys are doing some pretty cool stuff. Your CTO's not here, which, we'll get him on theCUBE soon. If you're watching, we'll get you on. But there's some cool stuff going on around visualization. I mean, we've covered big data since the day Hadoop was born 2009, 2010 timeframe. Visualization is key, but now, when you go to the next level, 3D, holograms, this is the future. The user interface is going to be augmented at work or at play. What are you guys doing? >> Absolutely, many things when it comes to data visualization. First of all, the third dimension, obviously adds a new way to see data, so, obviously, everything going from a 2D data analysis, you add a dimension, that gives you, obviously, added productivity. But in addition to that, you know, visualizing concepts. Mind-mapping, being able to correlate ideas, and not just data points. And, again, product design cycles and so on, productivity increases. Thirdly, ideation. Taking all that data, getting a 3D model with all its complexity into a simple form that we can collaborate around and design. >> You know, the next generation of users that are coming through the system, if you will, young kids, they're gamers. They love graphics. We're living in kind of a gaming culture, if you will, not to say gaming, literally, but per se, the interface is very rich in graphics, very rich in data. How is that going to impact CIOs? 'Cause they are looking at a old world of IT, put the servers on the racks, move the packets through the network. Now they have an opportunity with mobile, and now with global internet to put things out there like AR, like blockchain, smart contracts, AI. >> I think it's definitely an area that all CIOs should be looking at today, in many aspects. Number one, just like mobile, bring-your-own-device came into the office space. There will be, obviously, an impact from not just productivity solutions in the office, but as we get to consumer and AR, dealing with that and the implications of that. But, a more important, pressing issue for CIOs would be the fact that this is the future of compute. There is not a need anymore for 2D panels, or in the near future for 2D panels and keyboards and mouse interfaces, and how does that change IT support and, again, data sharing, collaboration, and all these-- >> And we see Siri, voice-activated, that's pretty classic. Throw the old movie Minority Report out there, where you're using your hands out there in the 3D space. This is an interface. >> Yes, it truly is. >> How real is that? I mean, come on, tell us! >> It's real, it's here, it's now. You can get a demo today for the audience. Soon, we can definitely invite you and get a demo. It is here. We're able to interact naturally today. We're on second-generation product. We have the widest field of view, which truly gives you immersion. You can walk around a hologram. You can stretch a hologram. You can surround yourselves with unlimited 3D images and panels and windows. >> So, what's the applications? What does this mean for the typical person out in the real world, whether they work in an enterprise, or a business, or a consumer? >> Absolutely. Early adopters right now are in business, enterprises. High-ROI type of applications and product design, so, rapidly iterating on concepts and ideas, getting all the way to sales and marketing, so once you have that design, then, how can you sell it and demonstrate it. All the way to maintenance, training, et cetera. That's the early adopters. Education is next, very close by. In the near future, and then, of course, we're thinking and trending towards consumers. What does shopping look like in the future? >> Check out Meta. It's a cool company. Now, Accenture Labs are having their party, and Accenture's been around for a while. I'm old enough to remember Arthur Andersen, the Big Six accounting firms, Accenture Consulting. These guys are not Johnny-come-latelies. They're doing some cool stuff. What's your role with Accenture Labs? You're on a panel here at this event, it's kind of a celebration. They're bringing the magic to life, talking about the magic of AI and cool things. What are you guys doing here, and what's Accenture Labs doing? >> Yeah, absolutely. We've been in collaboration with Accenture Labs for a little while, and it's been very, very exciting and productive. Number one, we're aligned on vision and strategy, so, currently, it's productivity. We're supporting productivity, we are going to develop a new platform, and so, for example, we've done a study together where we measured basic instructions around a LEGO, this was for the public, around building a LEGO piece used in our headset, using three-dimensional instructions versus 2D instructions, and Accenture brought that magic of quantifying productivity, and it was proved to be 20% faster with respect to instruction and training. >> So, Accenture has some chops, here, technically. >> Absolutely, absolutely. They do. (both laughing) And in the future, I mean, they're a big part of our ecosystem. This is what we're an enabler. We're a spatial interface-- >> What is the ecosystem for AI? That's a good question, 'cause people want to know, like, it's in a new, emerging area. Young kids are going to love this. New software development's coming in. What does the ecosystem look like in this new AR area, and what's the hiring profile? >> Yeah, that's a good question. Let me focus on ecosystem. I would say 50% of our current customers are developers, so the development community is adopting AR and they're building some really interesting and cool things. But the ecosystem comes from developers' content, so there's a lot of content developers, you know, high-fidelity 3D models. Enterprises are consuming all of this, and then channel partners, system integrators such as Accenture that are seeing the opportunity and bridging that gap for a lot of our corporate customers that are still forming their strategies. >> Joe Mikhail here, the chief revenue officer of Meta. I got to ask you, what percentage of your employees and customers are gamers? High amount, medium, low? Got to be a lot of gamers. >> There are some. Obviously, we integrate with Unity. A lot of our developers have come from that world, but our customers, we're a productivity company, and all of our customers are corporates at this time. Of course, we're interested to see what gamers can do on our platform. >> What's the low-hanging fruit for enterprise with respect to AR, because this is the question. No one debates the future. They see some augmentation coming on, obviously wearables, things of that nature, but software's going to power it all. What is the use case for enterprise? What's the low-hanging fruit? >> The lowest-hanging fruit is 3D CAD visualization in the product design cycle. That's just the lowest-hanging fruit right now. And then, training and education. >> You guys excited? >> We are very, very excited. The market's huge. >> All right, final question for you. For the folks that don't know the AR world, what is the future of AR going to be? What's the impact on society, what's the impact on daily lives of people with augmented reality? >> I think there are many, many impacts. One of our core values is technology serving humanity, so for us, it's very important to remove the barriers of devices coming between you and me, and being able to just look up content directly and interact with that. I think that's going to change how we think, how we collaborate, and then, of course, life sciences is huge, so there's a lot of companies starting to look at the future operating system, and the empathy that could come between a doctor and a patient looking at a case instead of just talking, you know? >> Joe, great, thanks for coming on. I'll give you a quick last word, here. What are you guys looking for as a company? You hiring, what's the strategy, what's the plan? Give a quick soundbite for what you guys are doing. >> Absolutely. We're growing. The market demand is huge, and we are hiring. We're looking for engineering, smart engineers that are interested in the space. We are growing on the sales and marketing side. We are absolutely interested in being part of our family, but I would say the biggest interest is in ecosystem partnerships. >> How long are you around for? >> Five years. >> Five years. Congratulations, Accenture Labs, 30 years celebration, where all the magic's happening, that's the theme. They got a magic show. We couldn't get video of that. They wouldn't let us record it. Joe from Meta, chief revenue officer, thanks for sharing your insight here on theCUBE. Appreciate it. >> Thanks, John. >> There'll be more coverage here at Accenture Labs' next 30 years. This is theCUBE coverage. We'll be right back. Thanks for watching. (upbeat music)

I see a number of hands in in Orlando so it will come over there right there yeah I John far is SiliconANGLE thanks for having us again guys appreciate it one of the things and that last question was some of my question about the database and one of things we're finding here in the cube this week is extracting out that there's a misconception and it's not just a database on us there's more to it so the question is and the other thing that we found out is it's not just for large SI p companies that have your stuff it's maybe new business opportunities so can you guys elaborate on those new business opportunities may be getting competitive displacements around say Oracle or and then just greenfield new opportunities because analytics is capturing the world by storm big data is is mainstream you guys have been kind of hiding behind that not putting that out forward enough in my opinion but want to get your take on new opportunities so I think that's a great question and I think the biggest misperception at the beginning was that Hannah is for AP stuff and you just mentioned that as well the first customers using Hana we're using Hannah for data that would never go in an essay p system like DNA data in healthcare or seismic data and oil and gas exploration this is not typical erp stuff and how to proved its value and and these examples we have we have customers who proved a hundred thousand times faster response times on Hannah they are all in the category of non SI p big problems to solve now solvable and i see three applications for this there is the traditional SI p where we can radically accelerate and reduce costs of ownership at the same time then you have these optimization opportunities which is all about business predictive analytics big data and then i think there's a third category chiz about solving problems that so far were unsolvable and we are pursuing all three of them so you're right Hannah is much more than a database I try to argue it's a unified next generation platform for business and can do all these three things yesterday my keynote I had a company by name under armour on the panel and he went from 281 million to you know a few billion because he could expand on a common platform globally and when he adds new categories of business it simply snaps on to a common platform and everybody knows what to do in its scales I had a meeting with the CEO yesterday and this is a very common conversation he grew his business by acquisition and now he's got a Federation of a whole bunch of companies and he feels like a holding company what he wants to do is consolidate these businesses onto a common platform he won't do it overnight because you can't shut down businesses but the vision over the next few years is consolidate everything onto one common SI p platform and take all the databases out and standardize everything on Hana because he loves the vision of not just transactional information that's great but it's the wisdom of the crowds that he's going to get from social and the predictive analytics that's built right into Hana so now he's got a real time business he can get it on a common platform everybody will have a common mobile architecture and the vision is to put it into the Hana Enterprise Cloud and let s ap run it that is a very common conversation that we're having right now and they're very disillusioned out there by the alternatives because they may you know have been best to breed in their day but now they figured out years later they may be best but they never breed it the mclaren story is similar right they start with the business we'd they're running their company but then we do a Formula One Hana based app that's not a typical enterprise application it takes data from 140 sensors on the car and gives you the ability to change outcomes during a one and a half hour race now for that you need real-time pneus and and and the decision they made now is to say okay I'm running my business on SI p a Formula One car changes its bill a material in average every 20 minutes that's how fast they change the engineering of every car otherwise they cannot keep up with competition and so you run that complexity on ASAP on Hannah and now you just extend that Hannah to include all this other data from the cars and you build new apps on top that solve different problems one platform all problems solved for company and by the way they brought that into the Hana Enterprise Cloud right because they don't want to deal with infrastructure they want to deal with cars and competition in Formula One races

>> (announcer) Live from Las Vegas: It's the Cube covering service now knowledge 2018 brought to you by Service Now. >> Welcome back to Las Vegas, everybody. This is the Cube: the leader in live tech coverage. We go out to the events, and, we extract the signal from the noise. This is day 3 of Service Now Knowledge, k18. The hashtag is #Know18. I'm Dave Vellante with my co-host Jeff Frick. Chris Anderson is here she's the managing director of Delloit, running the telecommunications, media, and technology practice. Welcome to the cube, thanks for coming on. >> Thank you so much, glad to be here. >> So, Delloit, awesome company, we had some of your colleagues on earlier. You guys have deep industry expertise. Global scale, leading digital transformations. First of all, what's your role, and let's get into it. >> Sure, so, I work in, as you mentioned, RTMC practice, full of acronyms, right? Mostly focused in the telecom space, and I've been in the telecom space for about 20 years. I'm really driving large scale transformation of the operations: how do we make the business more effective, how do we improve the overall customer experience, right, and how do we make sure that as new technology comes online in tel-cos, that that's seamless to customers, and that they don't fell the disruption, if you will, right, of the large leaps that tel-cos are making. >> Well, so, help us understand the basics of tel-co, um, you've got cost per bit coming down, you got data growing like crazy, you have over the top providers just bogarding the network, tel-co infrastructure is fossilized, um, wow, You must have a lot to do. >> Well we all want to watch the basketball game as we walk from the floor, to our car, into the house right >> 24/7, right, so, major, major challenges, which is great opportunity for you and Delloit. >> Absolutely. >> But give us your perspective on the state of the state in the industry. >> Sure, so I think it's funny you say the basics of tel-co, 'cause I think that's the hard part about tel-co, is it's not really basic, like, everyone expects that communications are there real time, right, and there's always going to be, we'll call it tone, right, but I think now it's at a whole new level, right, I think the challenge now for tel-co is mobility, right, I mean the pace of mobility, right, the massive proliferation of devices right, and sensors that are all connected. And so I think that now, I think the basics of tel-co. the game has changed, right, tel-co used to be it's own vertical, right, and now. it's really its own horizontal, right, enabling smart health, smart cities, right, many other industries, and I think that's the challenge for tel-co, and, it's become the new basic, if you will, it's not just the network for dial tone, right, it's about a true enabler for industry, right, and communications in real time right across the board. >> So, tel-co, that's really interesting, how you positioned that, so, tel-co has a dual agenda. >> Yes. >> The horizontal technology platform, and maintaining the verticle, not getting disrupted, so can it, can tel-co pull off that dual agenda? >> I think it has to, right, because to the point verticle, it used to be that they were the straight line,right, they provided the service and they were directly linked to the end customer, right, and, now, there are lots of other content aggregators and providers in that space, and so it's getting harder and harder for tel-cos to really maintain connectivity to their end customer, right, so they've also got to be an important part of the value chain, right, and other businesses, so I think they have to do both in parallel to stay relevant, but I think that's what makes kind of an, part of our work with servicenow, and how it comes in is the focus on customer service management, right, and really the part about the network, right, is the critical underpinning for tel-co, but if you ask tel-co network people, they say that is the experience, right. That's how I get the experience, right, is the speed of the network, right. I can't have any latency, it's always available, right, for it to enable these mission critical, mission critical things. >> Amazing, and you have these things coming up like, 5G, and industrial internet of things, you know, and we, we did a nice piece with a company that had a remote operation of autonomous vehicle. So, you know, they're driving the car from the office while we're in the car. Business case being take care of the edge cases on autonomous vehicles, so, latency becomes a really important thing with car brakes, and these things, so the opportunity and the challenges are only going to grow with this kind of next big leap that we're going to see built up around the 5G capability. >> Yeah, I think the move to 5G will be transformational, for the industry, right? And, really, 'cause now, you know, you expect your communications to work but you get frustrated, like, if your phone doesn't work, or your internet's not working, you just get frustrated, right, if your autonomous, you know, self driving vehicle is not working, right, or you've got a mission critical device, right, helping your heart beat, right, those are, those are different things, right, in a kind mission criticality that I think 5G introduces the potential for, right, will really change the game, right, but also makes it critical that you understand that full path of the network connectivity, and the services to the customer, right, 'cause if you're not in control of that full path to delivery there's no way to guarantee, right, the mission criticality that 5G` can deliver on. >> Right, so Chris, how does your work, um, what's your focus with the tel-cos? How does it intersect with what you're doing with service now, and how does it ultimately benefit consumers? >> Sure, so my focus, really, in the tel-co space has been in, in what tel-cos call "BSS",right, which are business support systems, or really, the front office. So, from, you know, helping customers from, the time of quoting, right, or ordering services, all the way through to fulfillment and delivery of them, right, I think that's the intersection, really, that is important to us with servicenow, right, our work with servicenow, to date, like many organizations, has been kind of in the IT service management space, HR, more on the enterprise, right, but not truly the heart of the business, right, and where we're really focused is, you know, working with servicenow to bring them into the heart of the business of tel-cos, right, and really change the game, right, I think one of the hot, one of the benefits in what I do, which is large scale transformation, most of these take years, right, two to three years before customers see any benefit of transition from one platform to another, right, and we've already been able to do some work with servicenow right, and our partnership, that you can see the benefit in months, right with a lot less risk, so it's really kind of taking the long term experience that I've had with the traditional industry players, right, and creating agility, right, and transformation from taking that from years to months, right, reducing the risk profile, right, and really creating an amazing experience across the value chain. >> Great benefits Dave: less risk and faster. >> Well, well, so I want to bring that back to sort of what we were talking about earlier: I mentioned the over top, top providers, when I think about my experience with interacting with, Netflix for example, I don't talk to their sales department, or their customer service department or their maintenance. I just interact with Netflix. Is that the vision for where you're trying to take tel-cos? >> I think it's part of it, right? 'Cause to your point, if the service I'm getting, works like it should, I don't want to talk to anybody. Right, like, I think that historically, we think of customer service and customer service management as I call somebody and how do they help me. Right, and I think the next generation of good service is how do I make sure they don't need to call me. >> No calls. >> Right, no calls, right, how does this work, and how do I stay on top of it, and I understand anything that might be degrading the experience and I get my arms around that, and so I think the new generation of customer service management is understanding, right, those things and kind of having a full and immediate view, and being able to take action quickly, and I think the kind of customer service management solution is important. We've been building out what we're calling an end to end service assurance solution ,right, with the servicenow team, and that really lets us look at from the time that an issue is detected, which could be customer degrading, all the way through to resolution. Right, to be able to own that path right to closure right, and really have real time visibility, and the ability to act and the ability to see those metrics and really manage your business real time. >> Well we hear that all the time: going from kind of a historical look at data, and reacting to being a little bit more, um, predictive, but then ultimately being more prescriptive, so you're, you see, you see, the development of the problem before the problem becomes a big problem. >> And I think that that is the future of customer service, and its going to be critical, right, as we pivot to 5G and we've got mission critical services running on that network that we really get this right, so. >> How about the event here, um, what are your takeaways? You're hearing a lot about what I call machine intelligence, AI, um Dev Ops, I mean all kinds of cool tech going around, but what's resonating with you Chris? >> So, probably say the opposite of what everyone's saying so I hear that but like we spent a little bit of time with a client yesterday right and we were talking about machine learning and artificial intelligence, and they say okay that's great so I can, you know, how do I take the emails that come from somebody written in a third language trying to write them in english, and what's the challenge of how do I get artificial intelligence to figure out what that issue is, and go act on it right, and so I think, I think these technologies are exciting, but I think we also have to pay a lot of attention to the basics right and not think that there is a shortcut right to providing the service and the mission criticality so to me I still think in terms of really enabling the front office that they're early days I think its certainly worth the investment but I think part of it is just looking critically at the business remember that the service and the service levels right are really driving right and we keep pushing the technology to catch up but I'm I would not I haven't seen a lot of tel-cos in the front office where experience is concerned be early adopters because that's the least the last risk that you want to take. >> But that's a great example, though, because that's a very specific use case where you would like to see more intelligence applied, and I think that's really the key as well where can we get the value as opposed to a generic dead smart person named thing that kind of exists, right, here is a specific problem, can we use AI and machine learning to help us solve that specific problem. >> Because what we, I think what we know is that if I have a sensor on a device and it picks up an issue I can start acting on that immediately, right, the ones that are much harder to act on are the ones that people report and then have to be translated right to figure out the action that needs to be taken but guess what there's still the same SOA attached to it right so how do I really advance you know artificial intelligence to really be able to move that forward in a much faster and reliable way right to the point where businesses will take a bet on it, so >> Alright we'll give you the last word Chris what should we know about, you know Delloit, kind of a bumper sticker, um, you know, your servicenow practice and tel-co what's your take-aways? >> So, um, I think, I think the magic, right, of the partnership and where we're really trying to take it is the fusion of our truly deep industry experience right and folks that have been in and around for 20 years, and using the servicenow solution in new ways right, and really again bringing it to the core of the value chain right, and, and frankly disrupting a lot of the industry solutions that have been out there that have gotten quite set in their ways like we see so many of our clients that don't have good answers right then they're paralyzed right trying to look at all the solutions that are there, and not finding anything that they like, and I think that's the magic that we're trying to bring to the partnership and really disrupt the game. >> Awesome. Well thanks for coming. Thank you I appreciate it guys. >> Alright keep it right there everybody listen you want to go to a couple of resources I want to give you for some great free content go to theCube.net, you'll see all the videos here, go to youtube.com/siliconangle subscribe to that channel, get notified of all the action we're at all the shows um siliconeangle.com for all the news wikibomb.com is a research site so check those out keep it right there everybody well be back with our next guest right after this short break.