>>well, thank you adam. We're back here at the Q we're live at the feta in Barcelona and we're here in cloud city which is just amazing. I'm really excited to have two guests here from a company called data on tap. Angus axe Tina's is the founder and Ceo and Alex Baumann is also a co founder and C Xo again, data on tap guys, welcome to the cube. Thanks so much for coming on Angus. Let's start with you. Tell us about data on tap is a great name. >>Yeah, thank you for we are designing and building digital attacker brands. Built entirely in public wealth. >>What does that mean? Digital attacker brand. So tell us more about that. >>I I think uh when you want to launch now a new wireless service provider, you have this challenge. We were built from current infrastructure or build something as a green field operation. We think building something a new is provides these new opportunities. So that's that's what we are. >>You guys know when you start a company with a blank sheet of paper, it's an exciting time. Why did you start the company? >>A good question. I think, I think for me, I mean, you know, I'm sure we both had our own reasons, but the biggest one for me was being held back on delivering the types of customer experiences that people were expecting. So, uh, telecom um, is notoriously slow moving, deliver great products, but take time to get there and you see all kinds of over the top products kind of leapfrogging ahead and needing lunch of telecoms in some places and kind of being held back. Uh, in that kind of older, you know, the full sheet of paper really drove us to decide what can we do with the blank sheet. How do we go green field, you know, all this new cloud technology, what types of things does not unlock for us? And that's really the impetus for >>it. So what are you actually selling? What's the service or product that you're selling? >>We started in Canadian market. The Canadian market is may be considered undeserved in, you know, when you compare to other markets. And we started with this full and final concept building out from core network all the way to consumer application, um, including e commerce, including other kind of value added services from the get go. Even before we launched before we launch our wireless service proposition, it's very hard to get into Canadian market. We're still battling out with regulator on on that front, but we're building a tax tax for Canada and for other countries to uh, in the model of the Fintech, in the model of this new business model that's becoming available with public cloud. >>So, public policy is obviously a big part of this where you have to ride on top of the existing infrastructure at least get permission to do that. And that's kind of your business model, right? >>Yeah, exactly. Um the infrastructure exists um very good networks in Canada and I believe elsewhere in the world as well, but this is the age of service innovation. Public cloud kind of brings that service innovation to the front rather than, you know, differentiating on the network technologies, which is kind of commanded commoditize thing. The new way of thinking is about service innovation, about what can you build on existing infrastructure, How can you use elements in the public cloud, the new economy, new business models to create this new new business. >>So let's talk about cloud economics. Specifically public cloud. When we say cloud, we need public cloud. Yeah, not fake cloud. So you've got, you've got cloud, you've got you've got cross cloud, you know, kind of imagining this abstraction layer cutting across clouds are extending to the edge. You talk about the cloud suppliers, they look at the the the edge as this opportunity, they see data centers is just another edge node. So talk about how do you think about public cloud economics as it relates to your business and your custom? >>Sure. So um you know, going with that blank sheet of paper and building out and kind of the entire stack exactly from start to finish everything you need from four to customer to deliver a customer experience to deliver all the tools that are necessary to sell in a completely digital model. Um The economics for us, when you look at the public cloud, allow you to do a kind of a composite application approach of using the api economy, you can just pick exactly what you need from individual pieces that exist out in the market. Um, and typically cloud based products as well. And by building in that model, you can really narrow down a per subscriber economic as a carrier that's kind of wasn't feasible before, you know, and on top of that, that kind of Capex the time to market, all those things are so small compared to what used to have as long as you're building out in that. >>So is your strategy to enable service providers and carriers to move beyond connectivity? Is that, is that even is that feasible? Or is it an ecosystem that gets built around that? On top of that? >>Our vision is that, and this is difficult. A lot of subscription based verticals. You, you need the subscriber but you need to know them on a 1 to 1 basis. You need that person, not just building account number. Uh And then once you've got that and you've got your core business around them, it is about all the other things that you can build a kind of an ecosystem around that customer. So it could be enabling um other verticals within the teletext act. It could just be about making sure that they have kind of our first approaches. You need to be digital, you need to have a digital experience, it needs to be good, needs to be premium, it can't just be a digitization, like the clipboard on the ipad, it needs to be a real rethought Greenfield experience to be competitive in >>the future. Because when you think about the brands and the pandemic, we're all watching movies and viewing on demand. The experience that we have with those services is awesome. Absolutely. The sales, the marketing and service all integrated into one. And you think about the experience that you have with traditional telcos and it's just frustration and so so you're, you're enhancing that experience. That's what it's all about, that user >>experience. Yeah. If you, if you go into our app in Canada right now and go into a marketplace stab you, you would kind of feel like netflix a bit because you know, uh, the subscription plans are just part of the range of products you can be buying from us and it truly depends on the customer segment and type and then on the particular customer, what we would bring up front for them to to consume. You know, if it's a youth customer student or perhaps a new Canadian or new immigrants to a certain place, they might need the banking product and we might have appreciate Mastercard or Visa available for them to to order together with decent is incurred. Or they might, if a university student, they might be buying certain clothing products or or other things from around for that university or or so on. Support. The customization is endless and personalization could be really truly personal and uh machine learned and and so on and so forth. >>And if I could, the most people don't describe themselves in terms of gigabytes, they have other things that they like and other things that make them who they are and being able to to understand who somebody is and deliver things outside of just like here is a plan with gigabytes were here a minute is really the next step. You know, you need to be able to put something other than one GB on a poster. >>It's interesting you say that Alex because you're right, we don't think there's consumers, we don't think in terms of gigabytes, but underneath all this is data, it's all about the data. And when I think about industries that are data intensive like telco financial services is another example. These organizations build data products and the time it takes for them to build data products is too long. The the user experience is oftentimes too cumbersome. And I think I think there's a new metric that's going to emerge in the industry is how long is a business person does it take me to go from idea to monetization as I mean a new industry Kpi you heard it here first in the queue because it's all about building data products in the in the digital world. And so when I think about what you're doing, if I understand it correctly, you're allowing the digital service providers first of all become digital and then build data products very quickly. Configure them very quickly and offer them to their consumers. >>Yeah, I like that idea um idea to monetization I think shortening that time is really important, but it goes beyond just like configuring a data product. Um It's anything that you could pull together within your own ecosystem or combinations of ecosystems or bundles of things. Um You know, as a marketer. Uh That idea comes to you and you want to test it, it's you know, it's idea to test the monetization to monetization. Um So you know, if you can rapidly test things iterate on them uh from an interface that happens in real time and you've got customers that are the data model and the construct around them is customer centric. So your marketing can be customer centric, um That's really the world we're building. >>What's the ecosystem, look how you envisioning and thinking about the ecosystem evolution? >>Well, starting point was obviously look at the retail store and look what's in the store and kind of have all of that as as a starting point, so you have that covered. But you can go you can go outside and and and see who else is selling what to add. Mobile consumer of yours. And trust me, all those ecosystem partners are eager to get in this digital kind of platform because they want they want that access to the consumer and they want a targeted access to that consumer and looking at whatever perhaps opportunities and and values exist outside of it. People pass down the phones to their kids and their senior members of the family. We try to sell their use phones. Um We we we started um monetizing or started developing systems that allow members to sell to members, something that, you know, is maybe part of a different marketplaces. But if you can get that process going and you can be a trusted party that handles these things. That's a really exciting opportunity for certain segments specifically. >>Well, that's the thing. The cloud enables, you can create these marketplaces and you can build your own ecosystems and that's sort of the next phase, last 10 years, we're going to be different than the next 10 years of cloud. And one of the big differences is the pace at which you can develop these ecosystems. I mentioned, uh, financial services, is that, uh, an industry segment? That's right for this wireless transformation. Are there other segments that you guys are looking? >>I think uh Fintech is maybe a good example of what telecom should be, uh, not necessarily mirroring, but at least looking to for inspiration because they've kind of dropped a little bit in terms of being open, opening up architecture, allowing that kind of service level innovation. Um so, you know, one thing is to create some digital transformation or digital green field operation for a network operator, um but kind of the next step is allowing other types of experimentation on top of what you've built. And kind of, Fintech is a good model for that. The cloud absolutely enables it. Um I mean, you know, up until cloud, I don't think we could have a conversation about, you know, a carrier opening up for other people to experiment and their platforms are on their systems, but the cloud really does allow for that. And I think uh you know, smaller groups of very capable minds will come up with things that we can't even dream up right now. Uh and that's the kind of stuff that you want to have happening first on your network and be enabling it and then pull it in and pull those minds into into your teams like attracting talent that can deliver the things we're talking about is also going to be important. >>We talked about in the cube data about the economy all the time and no we can talk about opening up the telcos and it scares people a lot. You know can we replicate the reliability of the network with open A PS and open no rand open systems. But are there examples of sort of open api is the ap economy in this digital service provider world? Oh >>um I think there are I think uh you know if you come from I. P. Void ecosystem there are a lot more open um uh and networks should be in a in a similar place. I think it provides opportunities in short tech. Is there security, home security iot everything can have come to play when you think about it, when when you have an app on each each of your consumers phone we have I think endless opportunities you have to be provide certain stickiness. You have to provide certain engagement. Why would people come back to you um Gamification loyalty? Um other things can come to play uh to provide this wholesome experience on why people would come back to you, not just for you know, service things >>I saw in some of your material private by design. What what is that? >>I think so it's it's a bit of a mindset in the strategy when you're when you're developing everything in your platform um as a as a telecommunications provider, you collect like an absurd amount of information about people, particularly if you are detected in the way that you know, whoever one of those people is. Um, and there's a little bit of a need to respect some of that data, respect some of the privacy that maybe around that um, and building within the cloud and constructing new data models around how that data is, is uh, stored, what things exist in a wallet, what traceability happens, inaudible bility happens on that data is really important. As you consider the future. We're already seeing lots of regulation around privacy and data and data processing. Um, so you can't like build now and think, oh whatever, we'll change it later. You a little bit forward thinking is very important for, for that type of >>Yeah. And I think starting point is important of how easy is it to get in and start of telecom telecommunications provider, you'll see during MWc and have evidence people are trying to re engineer the onboarding experiences. Um, I think that first step has to be very, very easy for users to take uh and uh, getting into ecosystem, so just email, good to go just as any other app and, and that's, and that's a starting point, and then the rest of it is sort of on demand when needed. Uh that's, you know, with the value you grow. So telecoms usually try to run the credit check before you even, you know, before you even know the name. >>Hey guys, we got to leave it there. Thanks so much, congratulations on getting off the ground adam. It's buzzing here, back to you.

>>Yeah, >>from the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Everybody, this is Dave Vellante of the Cube. Welcome back. The continuous coverage that we're running here of the IBM Think Digital 2020 Experience. I'm with Radica Gunnar, who is a longtime Cube alum. She's the vice president for Data and AI. Expert labs and learning Radica. Always a pleasure. I wish we were seeing each other face to face in San Francisco. But, you know, we have to make the best. >>Always a pleasure to be with you, Dave. >>So, listen, um, we last saw each other in Miami Attain IBM data event. You hear a lot of firsts in the industry. You hear about Cloud? First, you hear about data. First hear about AI first. I'm really interested in how you see AI first coming customers. They want to operationalize ai. They want to be data first. They see cloud, you know, is basic infrastructure to get there, but ultimately they want insights out of data. And that's where AI comes in. What's your point of view on this? >>I think any client that's really trying to establish how to be able to develop a AI factory in their organization so that they're embedding AI across the most pervasive problems that they have in their order. They need to be able to start first with the data. That's why we have the AI ladder, where we really think the foundation is about how clients organized there to collect their data, organize their data, analyze it, infuse it in the most important applications and, of course, use that whole capability to be able to modernize what they're doing. So we all know to be able to have good ai, you need a good foundational information, architecture and the US A lot of the first steps we have with our clients is really starting with data doing an analysis of where are you with the data maturity? Once you have that, it becomes easier to start applying AI and then to scale AI across the business. >>So unpack that a little bit and talk about some of the critical factors and the ingredients that are really necessary to be successful. What are you seeing with customers? >>Well, to be successful with, a lot of these AI projects have mentioned. It starts with the data, and when we come to those kind of characteristics, you would often think that the most important thing is the technology. It's not that is a myth. It's not the reality. What we found is some of the most important things start with really understanding and having a sponsor who understands the importance of the AI capabilities that you're trying to be able to drive through business. So do you have the right hunger and curiosity of across your organization from top to bottom to really embark on a lot of these AI project? So that's cultural element. I would say that you have to be able to have that in beds within it, like the skills capabilities that you need to be able to have, not just by having the right data scientists or the right data engineers, but by having every person who is going to be able to touch these new applications and to use these new applications, understand how AI is going to impact them, and then it's really about the process. You know, I always talk about AI is not a thing. It's an ingredient that makes everything else better, and that means that you have to be able to change your processes. Those same applications that had Dev ops process is to be able to put it in production. Need to really consider what it means to have something that's ever changing, like AI as part of that which is also really critical. So I think about it as it is a foundation in the data, the cultural changes that you need to have from top to bottom of the organization, which includes the skills and then the process components that need to be able to change. >>Do you really talking about like Dev ops for AI data ops, I think is a term that's gonna gaining popularity of you guys have applied some of that in internally. Is that right? >>Yeah, it's about the operations of the AI life cycle in, and how you can automate as much of that is possible by AI. They're as much as possible, and that's where a lot of our investments in the Data and AI space are going into. How do you use AI for AI to be able to automate that whole AI life site that you need to be able to have in it? Absolutely >>So I've been talking a lot of C. XO CEO CEOs. We've held some C so and CEO roundtables with our data partner ET are. And one of the things that's that's clear is they're accelerating certain things as a result of code 19. There's certainly much more receptive to cloud. Of course, the first thing you heard from them was a pivot to work from home infrastructure. Many folks weren't ready, so okay, but the other thing that they've said is even in some hard hit industries, we've essentially shut down all spending, with the exception of very, very critical things, including, interestingly, our digital transformation. And so they're still on that journey. They realized the strategic imperative. Uh, and they don't want to lose out. In fact, they want to come out of this stronger AI is a critical part of that. So I'm wondering what you've seen specifically with respect to the pandemic and customers, how they're approaching ai, whether or not you see it accelerating or sort of on the same track. What are you seeing out there with clients? >>You know, this is where, um in pandemics In areas where, you know, we face a lot of uncertainty. I am so proud to be an IBM. Er, um, we actually put out offer when the pandemic started in a March timeframe. Teoh Many of our organizations and communities out there to be able to use our AI technologies to be able to help citizens really understand how Kobe 19 was gonna affect them. What are the symptoms? Where can I get tested? Will there be school tomorrow? We've helped hundreds of organizations, and not only in the public sector in the healthcare sector, across every sector be able to use AI capabilities. Like what we have with Watson assistant to be able to understand how code in 19 is impacting their constituents. As I mentioned, we have hundreds of them. So one example was Children's health care of Atlanta, where they wanted to be able to create an assistant to be able to help parents really understand what symptoms are and how to handle diagnosis is so. We have been leveraging a lot of AI technologies, especially right now, to be able to help, um, not just citizens and other organizations in the public and healthcare sector, but even in the consumer sector, really understand how they can use AI to be able to engage with their constituents a lot more closely. That's one of the areas where we have done quite a bit of work, and we're seeing AI actually being used at a much more rapid rate than ever >>before. Well, I'm excited about this because, you know, we were talking about the recovery, What there's a recovery look like is it v shaped? Nobody really expects that anymore. But maybe a U shaped. But the big concern people have, you know, this w shape recovery. And I'm hopeful that machine intelligence and data can be used to just help us really understand the risks. Uh, and then also getting out good quality information. I think it's critical. Different parts of the country in the world are gonna open at different rates. We're gonna learn from those experiences, and we need to do this in near real time. I mean, things change. Certainly there for a while they were changing daily. They kind of still are. You know, maybe we're on a slower. Maybe it's three or four times a week now, but that pace of change is critical and, you know, machine machines and the only way to keep up with that wonder if you could comment. >>Well, machines are the only way to keep, and not only that, but you want to be able to have the most up to date relevant information that's able to be communicated to the masses and ways that they can actually consume that data. And that's one of the things that AI and one of the assistant technologies that we have right now are able to do. You can continually update and train them such that they can continually engage with that end consumer and that end user and be able to give them the answers they want. And you're absolutely right, Dave. In this world, the answers change every single day and that kind of workload, um, and and the man you can't leave that alone to human laborers. Even human human labors need an assistant to be able to help them answer, because it's hard for them to keep up with what the latest information is. So using AI to be able to do that, it's absolutely critical, >>and I want to stress that I said machines you can't do without machines. And I believe that, but machines or a tool for humans to ultimately make the decisions in a crisis like this because, you see, I mean, I know we have a global audience, but here in the United States, you got you have 50 different governors making decisions about when and how certainly the federal government putting down guidelines. But the governor of Georgia is going to come back differently than the governor of New York, Different from the governor of California. They're gonna make different decisions, and they need data. And AI and Machine intelligence will inform that ultimately their public policy is going to be dictated by a combination of things which obviously includes, you know, machine intelligence. >>Absolutely. I think we're seeing that, by the way, I think many of those governors have made different decisions at different points, and therefore their constituents need to really have a place to be able to understand that as well. >>You know, you're right. I mean, the citizens ultimately have to make the decision while the governor said sick, safe to go out. You know, I'm gonna do some of my own research and you know, just like if you're if you're investing in the stock market, you got to do your own research. It's your health and you have to decide. And to the extent that firms like IBM can provide that data, I think it's critical. Where does the cloud fit in all this? I mentioned the cloud before. I mean, it seems to be critical infrastructure to get information that will talk about >>all of the capabilities that we have. They run on the IBM cloud, and I think this is where you know, when you have data that needs to be secured and needs to be trusted. And you need these AI capabilities. A lot of the solutions that I talked about, the hundreds of implementations that we have done over the past just six weeks. If you kind of take a look at 6 to 8 weeks, all of that on the IBM Public cloud, and so cloud is the thing that facilitates that it facilitates it in a way where it is secure. It is trusted, and it has the AI capabilities that augmented >>critical. There's learning in your title. Where do people go toe? Learn more How can you help them learn about AI And I think it started or keep going? >>Well, you know, we think about a lot of these technologies as it isn't just about the technology. It is about the expertise and the methodologies that we bring to bear. You know, when you talk about data and AI, you want to be able to blend the technology with expertise. Which is why are my title is expert labs that come directly from the labs and we take our learnings through thousands of different clients that we have interacted with, working with the technologies in the lab, understanding those outcomes and use cases and helping our clients be successful with their data and AI projects. So we that's what we do That's our mission. Love doing that every day. >>Well, I think this is important, because I mean, ah company, an organization the size of IBM, a lot of different parts of that organization. So I would I would advise our audience the challenge IBM and say, Okay, you've got that expertise. How are you applying that expertise internally? I mean, I've talked into public Sorry about how you know the data. Science is being applied within IBM. How that's then being brought out to the customers. So you've actually you've got a Petri dish inside this massive organization and it sounds like, you know, through the, you know, the expert labs. And so the Learning Center's you're sort of more than willing to and aggressively actually sharing that with clients. >>Yeah, I think it's important for us to not only eat our own dog food, so you're right. Interpol, The CDO Office Depot office we absolutely use our own technology is to be able to drive the insights we need for our large organization and through the learnings that we have, not only from ourselves but from other clients. We should help clients, our clients and our communities and organizations progress their use of their data and their AI. We really firmly believe this is the only way. Not only these organizations will progress that society as a whole breast, that we feel like it's part of our mission, part of our duty to make sure that it isn't just a discussion on the technology. It is about helping our clients and the community get to the outcomes that they need to using ai. >>Well, guy, I'm glad you invoke the dog food ing because, you know, we use that terminology a lot. A lot of people marketing people stepped back and said, No, no, it's sipping our champagne. Well, to get the champagne takes a lot of work, and the grapes at the early stages don't taste that pain I have to go through. And so that's why I think it's a sort of an honest metaphor, but critical your you've been a friend of the Cube, but we've been on this data journey together for many, many years. Really appreciate you coming on back on the Cube and sharing with the think audience. Great to see you stay safe. And hopefully we'll see you face to face soon. >>All right. Thank you. >>Alright. Take care, my friend. And thank you for watching everybody. This is Dave Volante for the Cube. You're watching IBM think 2020. The digital version of think we'll be right back after this short break. >>Yeah, yeah, yeah.