>> live from San Francisco. It's the Cube covering Google Club Next nineteen Rodeo by Google Cloud and its ecosystem partners. >> Hey, welcome back. Everyone's the live Cube covers here in San Francisco for Google Cloud. Next nineteen. I'm Javert Day Volante here on the ground floor, day two of three days of wall to wall coverage to great guests. We got Kartik lost. Meena Ryan, product management director of Cloud Identity for Google and Kim parent chief security officer for Doctor on Demand. Guys, welcome to the Cube. Appreciated Coming on. >> Great to be here. >> Thank you so honestly Way covering Google Cloud and Google for many, many years. And one of the things that jumps out at me, besides allows the transformation for the enterprise is Google's always had great technology, and last year I did an interview, and we learned a lot about what's going on the chip level with the devices you got. Chrome browser. Always extension. All these security features built into a lot of the edge devices that Google has, so there's definitely a security DNA in there and Google the world. But now, when you start getting into cloud access and permissions yesterday and the Kino, Thomas Kurian and Jennifer Lin said, Hey, let's focus on agility. Not all his access stuff. This is kind of really were identity matters. Kartik talk about what's going on with cloud identity. Where are we? What's the big news? >> Yeah, thank you. So clouded. Entities are solution to manage identity devices and the whole axis management for the clouds. And you must have heard of beyond Corp and the whole zero trust model and access. One thing we know about the cloud if you don't make the access simple and easy and at the same time you don't provide security. You can get it right. So you need security and you need that consumer level simplicity. >> Think it meant explain beyond core. This is important. Just take a minute to refresh for the folks that might not know some of the innovations. They're just start >> awesome. Yeah. So traditional on premises world, the security model was your corporate network. Your trust smaller. Lose The corporate network invested a lot to get to keep the bad people out. You get the right people on and that made ten T applications on premises. Your data was on premises now the Internet being a new network, you work from anywhere. Work is no longer a thing. You work from anywhere. What gets done right? So what is the new access? More look like? That's what people have been struggling with. What Google came up with in two thousand eleven is this model called Beyond Core versus Security Access Model will rely on three things. Who you are is a user authentication the device identity and security question and last but not least, the context off. What are you trying to access in very trying to access from So these things together from how you security and access model And this is all about identity. And this is Bianca. >> And anyone who has a mobile device knows what two factor authentication is. That's when you get a text messages. That's just two factor M. F. A multi factor. Authentication really is where the action is, and you mentioned three of them. There's also other dimensions. This is where you guys are really taking to the next level. Yeah, where are we with FAA and some of the advances around multi factor >> s O. So I think keeping you on the highlight is wear always about customer choice. We meet customers where they are. So customers today have invested in things like one time use passwords and things like that. So we support all of that here in cloud identity. But a technology that we are super excited about the security, Keith. And it's built on the fighter standard. And it's inserted this into your USB slot of that make sense. And we just announced here at next you can now use your android phone as a security key. So this basically means you don't have to enter any codes because all those codes you enter can be fished on way. Have this thing at Google and we talked about it last time. Since we roll our security keys. No Google account, it's >> harder for the hackers. Really Good job, Kim. Let's get the reality. You run a business. You've been involved in a lot of start ups. You've been cloud nated with your company. Now talk about your environment does at the end of the year, the chief security officer, the buck stops with you. You've got to figure this out. How are you dealing with all this? These threats at the same time trying to be innovative with your company. >> So for clarity. So I've been there six years since the very beginning of the company. And we started the company with zero hardware, all cloud and before there was beaten beyond Corp. Where there was it was called de-perimeterization. And that's effectively the posture we took from the very beginning so our users could go anywhere. And our I always say, our corporate network is like your local coffee shop. You know, WiFi like that's the way we view it. We wanted to be just a secure there at the coffee shop, you know, we don't care. Like we always have people assessing us and they're looking at a corporate network saying, You know, where your switches that you're, you know, like where your hardware like, we want to come in and look at all like we don't have anything like, >> there's no force. The scan >> is like way. Just all go to the Starbucks will be the same thing. So that's part of it. And now you know, when we started like way wanted to wrap a lot of our services in the Google, but we had the problem with hip a compliance. So in the early days, Google didn't have six years ago. In our early days, Google didn't have a lot of hip, a compliant services. Now they do. Now we're moving. We're trying to move everything we do almost in the Google. That's not because we just love everything about Google. It's for me. I have assessed Google security are team has assessed their security. We have contracts with them and in health care. It's very hard to take on new vendors and say Hey, is there security? Okay, are their contracts okay? It's like a months long process and then even at the end of the day, you still have another vendor out there that sharing your day, that you're sharing your data with them and it's precarious for me. It just it doubles my threat landscape. When I go from Google toe one more, it's like if I put my data there, >> so you're saying multi vendor the old way. This is actually a problematic situation for you. Both technically and what operate timewise or both are super >> problematic for me in terms of like where we spread our data to like It just means that company every hack against that company is brutal for us, like And you know, the other side of the equation is Google has really good pricing. Comparatively, yes, Today we're talking about Big Query, for example, and they wanted to compare Big Query to some other systems and be crazy. G, c p. And And we looked at the other systems and we couldn't find the pricing online. And, like Google's pricing was right there was completely transparent. Easy to understand. The >> security's been vetted. The security's >> exactly Kim. Can you explain when you said the multi vendor of creates problems for you? Why is this? Is it not so much that one vendor is better? The other assistant? It's different. It's different processes or their discernible differences in the quality of the security. >> There are definitely discernible differences in quality, for sure. Yeah, >> and then add to that different processes. Skill sets. Is that writer? Yes, Double click on that E >> everybody away. There's always some I mean almost every vendor. You know, there's always something that you're not perfectly okay with. On the part of the security is something you don't totally like about it. And the more vendors you add, you have. Okay. This person, they're not too good on their physical security at their data center or they're not too good on their policies. They're not too good on their disaster recovery. Like there's you always give a little bit somewhere. I hate to say it, but it's true. It's like nobody's super >> perfect like it's It's so it's a multiplication effects on the trade offs that you have to make. Yeah, it's necessarily bad, but it's just not the way you want to do it. All right? Okay. >> All the time. So you got to get in an S L A u have meetings. You gotta do something vetting. It's learning curves like on the airport taking your shoes off. Yeah. Yeah. And then there's the >> other part. Beyond the security is also downtime. Like if they suffer downtime. How much is that going to impact our company? >> Karthik, you talked about this This new access mall, this three layer who authentication that is the device trusted in the context. I don't understand how you balance the ratio between sort of false positives versus blocking. I think for authentication and devices pretty clear I can authenticate. You are. I don't trust this device. You're not getting in, but the context is interesting. Is that like a tap on the shoulder with with looking at mail? Hey, be careful. Or how are you balancing that? The context realm? >> Yeah, I think it's all about customer choice. Again, customers have, but they look at their application footprint there, making clear decisions on Hey, this is a parole application is a super sensitive as an example, maybe about based meeting application. Brotherly, not a sensitive. So when they're making decisions about hey, you have a manage device. I will need a manage device in order for you to access the payroll application. But if you have you bring your own device. I'm off perfectly fine if you launch a meeting from that. So those are the levels that people are making decisions on today, and it's super easy to segment and classify your application. >> Talk about the the people that are out there watching might say, You know what? I've been really struggling with identity. I've had, you know, l'd app servers at all this stuff out there, you name it. They've all kinds of access medals over the years, the perimeters now gone. So I got a deal to coffee shop, kind of working experience and multiple devices. All these things are reality. I gotta put a plan together. So the folks that are trying to figure this out, what's that? You guys have both weigh in on on approach to take or certain framework. What's what's? How does someone get the first few steps off to go out towards good cloud identity? >> Sure, I only go first, so I think many ways. That's what we try to simplify it. One solution that we call cloud identity because what people want is I want that model. Seems like a huge mountain in front of me, like how do I figure these things out? I'm getting a lot of these terminologies, so I think the key is to just get started on. We've given them lots of ways. You can take the whole of cloud identity solution back to Kim's point. It can be one license from us, that's it and you're done. It's one unified. You I thinks like that. You can also, if you just want to run state three applications on DCP we have something called identity ofher Proxy. It's very fast. Just load yaps random on disability and experience this beyond >> work Classic enterprise Khun >> Yeah, you run all the applications and dcpd and you can And now they're announcing some things that help you connect back with John Thomas application. That's a great way to get started. >> Karthik painted this picture of Okay, it's no perimeter. You can't just dig a moat. The queen wants to leave the castle. All the security, you know, metaphors that we use. I'm interested in how you're approaching response to these days because you have to make trade us because there are discernible differences with different vendors. Make the assumption that people are going to get in so response becomes increasingly important. What have you changed to respond more quickly? What is Google doing to help? >> Well, yeah, So in a model where we are using, a lot of different vendors were having to like they're not necessarily giving us response and detection. Google. Every service we'd wrap into them automatically gets effectively gets wrapped into our security dashboard. There's a couple of different passwords we can use and weaken. Do reporting. We do it. A tremendous amount of compliance content, compliance controls on our DLP, out of e mail out of Dr and there's detection. There's like it's like we don't have to buy an extra tool for detection for every different type of service we have, it's just built into the Google platform, which is it's It's phenomenal from >> detection baked in, It's just >> baked in. We're not to pay extra for it. In fact, I mean way by the enterprise license because it's completely worth it for us. Um, you know, assumes that came out, the enterprise part of it and all the extra tools. We were just immediately on that because the vault is a big thing for us as well. It's like not only response, but how you dig through your assets toe. Look for evidence of things like, if you have some sort of legal case, you need vault, Tio, you know, make the proper ah, data store for that stuff >> is prioritization to Is it not like, figure it out? Okay, which, which threats to actually go after and step out? And I guess other automation. I mean, I don't know if you're automating your run book and things of that nature. But automation is our friends. Ah, big friend of starting >> on the product measures I What's the roadmap looks like and you share any insight into what your priorities are to go the next level. Aussie Enterprise Focus. For Google Cloud is clear Customs on stage. You guys have got a lot of integration points from Chromebooks G Sweep all the way down through Big Query with Auto ML All the stuff's happening. What's on your plate for road map? What things are you innovating around? >> I mean, it's beyond car vision that we're continuing to roll out. We've just ruled out this bit of a sweet access, for example, but all these conditions come in. Do you want to take that to G et? You're gonna look. We're looking at extending that context framework with all the third party applications that we have even answers Thing called beyond our devices FBI and beyond Corp Alliance, because we know it's not just Google security posture. Customers are made investments and other security companies and you want to make sure all of that interoperate really nicely. So you see a lot more of that coming out >> immigration with other security platform. Certainly, enterprises require that I buy everything on the planet these days to protect themselves >> Like there's another company. Let's say that you're using for securing your devices. That sends a signal thing. I trust this device. It security, passing my checks. You want to make sure that that comes through and >> now we're gonna go. But what's your boss's title? Kim Theo, you report to the CEO. Yeah, Awesome guys. >> Creation. Thank you >> way. We've seen a lot of shifts in where security is usually now pretty much right. Strategic is core for the operations with their own practices. So, guys, thanks for coming on. Thanks for the thing you think of the show so far. What's the What's The takeaway came I'll go to you first. What's your What's the vibe of the >> show? It's a little tough for me because I have one of my senior security engineers here, and he's been going to a lot of the events and he comes to me and just >> look at all >> this stuff that they have like, way were just going over before this. I was like, Oh my God, we want to go back to our r R R office and take it all in right today. You know, if we could So yeah, it's a little tough because >> in the candy store way >> love it because again, it's like it's already paying for it. It's like they're just adding on services that we wanted, that we're gonna pay for it now. It's >> and carted quickly. Just get the last word I know was commenting on our opening this morning around how Google's got all five been falling Google since really the beginning of the company and I know for a fact is a tana big day that secures all spread for the company matter. Just kind of getting it. Yeah, share some inside quickly about what's inside Google. From a security asset standpoint, I p software. >> Absolutely. I mean, security's built from the ground up. We've been seeing that and going back to the candy store analogy. It feels like you've always had this amazing candy, but now there's like a stampede to get it, and it's just built in from the ground up. I love the solution. Focus that you found the keynotes and all the sessions that's happening. >> That's handsome connective tissue like Antos. Maybe the kind of people together. >> Yeah. I don't like >> guys. Thanks for coming on. We appreciate Kartik, Kim. Thanks for coming on. It's accused. Live coverage here on the ground floor were on the floor here. Day two of Google Cloud next here in San Francisco on Jeffrey David Lantz Stevens for more coverage after this short break.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Okay. Welcome back, everyone. He live in San Francisco. Here on Mosconi St for the cubes. Exclusive coverage of IBM. Think twenty nineteen. I'm Jeffrey David Long. Four days of coverage bringing on all the action talking. The top executives, entrepreneurs, ecosystem partners and everyone who can bring the signal from the noise here on the Q and excuses. Rob Thomas, general manager, IBM Data and a I with an IBM Cube Alumni. Great to see you again. >> Great. There you go. >> You read a >> book yet? This year we've written ten books on a data. Your general manager. There's >> too much work. Not enough time >> for that's. Good sign. It means you're working hard. Okay. Give us give us the data here because a I anywhere in the center of the announcements we have a story up on. Slick earnings have been reported on CNBC. John Ford was here earlier talking to Ginny. This is a course centerpiece of it. Aye, aye. On any cloud. This highlights the data conversation you've been part of. Now, I think what seven years seems like more. But this is now happening. Give us your thoughts. >> Go back to basics. I've shared this with you before. There's no AI without IA, meaning you need an information architecture to support what you want to do in AI. We started looking into that. Our thesis became so clients are buying into that idea. The problem is their data is everywhere onpremise, private cloud, multiple public clouds. So our thesis became very simple. If we can bring AI to the data, it will make Watson the leading AI platform. So what we announced wtih Watson Anywhere is you could now have it wherever your data is public, private, any public cloud, build the models, run them where you want. I think it's gonna be amazing >> data everywhere and anywhere. So containers are big role in This is a little bit of a deb ops. The world you've been living in convergence of data cloud. How does that set for clients up? What are they need to know about this announcement? Was the impact of them if any >> way that we enable Multi Cloud and Watson anywhere is through IBM cloud private for data? That's our data Micro services architectural writing on Cooper Netease that gives you the portability so that it can run anywhere because, in addition Teo, I'd say, Aye, aye, ambitions. The other big client ambition is around how we modernize to cloud native architectures. Mohr compose herbal services, so the combination gets delivered. Is part of this. >> So this notion of you can't have a eye without a it's It's obviously a great tagline. You use it a lot, but it's super important because there's a gap between those who sort of have a I chops and those who don't. And if I understand what you're doing is you're closing that gap by allowing you to bring you call that a eye to the data is it's sort of a silo buster in regard. Er yeah, >> the model we use. I called the eye ladder. So they give it as all the levels of sophistication an organization needs to think about. From how you collect data, how you organize data, analyze data and then infused data with a I. That's kind of the model that we used to talk about. Talk to clients about that. What we're able to do here is same. You don't have to move your data. The biggest problem Modi projects is the first task is OK move a bunch of data that takes a lot of time. That takes a lot of money. We say you don't need to do that. Leave your data wherever it is. With Cloud private for data, we can virtualized data from any source. That's kind of the ah ha moment people have when they see that. So we're making that piece really >> easy. What's the impact this year and IBM? Think to the part product portfolio. You You had data products in the past. Now you got a eye products. Any changes? How should people live in the latter schism? A kind of a rubric or a view of where they fit into it? But what's up with the products and he changes? People should know about? >> Well, we've brought together the analytics and I units and IBM into this new organization we call Dayton ay, ay, that's a reflection of us. Seen that as two sides of the same coin. I really couldn't really keep them separate. We've really simplified how we're going to market with the Watson products. It's about how you build run Manager II watching studio Watson Machine Learning Watson Open scale. That's for clients that want to build their own. Aye, aye. For clients that wants something out of the box. They want an application. We've got Watson assistant for customer service. Watson Discovery, Watson Health Outset. So we've made it really easy to consume Watson. Whether you want to build your own or you want an application designed for the line of business and then up and down the data, stack a bunch of different announcements. We're bringing out big sequel on Cloudera as part of our evolving partnership with the new Cloudera Horn Works entity. Virtual Data Pipeline is a partnership that we've built with active fio, so we're doing things at all layers of the last. >> You're simplifying the consumption from a client, your customer perspective. It's all data. It's all Watson's, the umbrella for brand for everything underneath that from a tizzy, right? >> Yeah, Watson is the Aye, aye, brand. It is a technology that's having an impact. We have amazing clients on stage with this this week talking about, Hey, Eyes No longer. I'd like to say I was not magic. It's no longer this mystical thing. We have clients that are getting real outcomes. Who they II today we've got Rollback of Scotland talking about how they've automated and augmented forty percent of their customer service with watching the system. So we've got great clients talking about other using >> I today. You seen any patterns, rob in terms of those customers you mentioned, some customers want to do their own. Aye, aye. Some customers wanted out of the box. What? The patterns that you're seeing in terms of who wants to do their own. Aye. Aye. Why do they want to do their own, eh? I do. They get some kind of competitive advantage. So they have additional skill sets that they need. >> It's a >> It's a maker's mark. It is how I would describe it. There's a lot of people that want to make their own and try their own. Ugh. I think most organizations, they're gonna end up with hundreds of different tools for building for running. This is why we introduced Watson Open Scale at the end of last year. That's How would you manage all of your A II environments? What did they come from? IBM or not? Because you got the and the organization has to have this manageable. Understandable, regardless of which tool they're using. I would say the biggest impact that we see is when we pick a customer problem. That is widespread, and the number one right now is customer service. Every organization, regardless of industry, wants to do a better job of serving clients. That's why Watson assistant is taking off >> this's. Where? Data The value of real time data. Historical data kind of horizontally. Scaleable data, not silo data. We've talked us in the past. How important is to date a quality piece of this? Because you have real time and you have a historical date and everything in between that you had to bring to bear at low ladened psi applications. Now we're gonna have data embedded in them as a feature. Right. How does this change? The workloads? The makeup of you? Major customer services? One piece, the low hanging fruit. I get that. But this is a key thing. The data architecture more than anything, isn't it? >> It is. Now remember, there's there's two rungs at the bottom of the ladder on data collection. We have to build a collect data in any form in any type. That's why you've seen us do relationships with Mongo. D B. Were they ship? Obviously with Claude Era? We've got her own data warehouse, so we integrate all of that through our sequel engine. That thing gets to your point around. Are you gonna organize the data? How are you going to curate it? We've got data catalogue. Every client will have a data catalogue for many dollar data across. Clouds were now doing automated metadata creation using a I and machine learning So the organization peace. Once you've collected it than the organization, peace become most important. Certainly, if you want to get to self service analytics, you want to make data available to data scientists around the organization. You have to have those governance pieces. >> Talk about the ecosystem. One of the things that's been impressive IBM of the years is your partnerships. You've done good partners. Partnership of relationships now in an ecosystem is a lot of building blocks. There's more complexity requires software to distract him away. We get that. What's opportunities for you to create new relationships? Where are the upper opportunities for someone a developer or accompanied to engage with you guys? Where's the white spaces? Where is someone? Take advantage of your momentum and you're you're a vision. >> I am dying for partners that air doing domain specific industry specific applications to come have them run on IBM cloud private for data, which unleashes all the data they need to be a valuable application. We've already got a few of those data mirrors. One sensing is another one that air running now as industry applications on top of IBM Club private for data. I'd like to have a thousand of these. So all comers there. We announced a partnership with Red Hat back in May. Eventually, that became more than just a partnership. But that was about enabling Cloud Private, for data on red had open shift, So we're partnered at all layers of the stack. But the greatest customer need is give me an industry solution, leveraging the best of my data. That's why I'm really looking for Eyes V. Partners to run on Ivan clubs. >> What's your pitch to those guys? Why, why I should be going. >> There is no other data platform that will connect to all your data sources, whether they're on eight of us as your Google Cloud on premise. So if you believe data is important to your application. There's simply no better place to run than IBM. Claude Private for data >> in terms of functionality, breath o r. Everything >> well, integrating with all your data. Normally they have to have the application in five different places. We integrate with all the data we build the data catalogue. So the data's organized. So the ingestion of the data becomes very easy for the Iast V. And by the way, thirdly, IBM has got a pretty good reach. Globally, one hundred seventy countries, business partners, resellers all over the world, sales people all over the world. We will help you get your product to market. That's a pretty good value >> today. We talk about this in the Cube all the time. When the cloud came, one of the best things about the cloud wasn't allowed. People to put applications go there really quickly. Stand them up. Startups did that. But now, in this domain world of of data with the clouds scale, I think you're right. I think domain X expertise is the top of the stack where you need specially special ism expertise and you don't build the bottom half out. What you're getting at is of Europe. If you know how to create innovation in the business model, you could come in and innovate quickly >> and vertical APS don't scale enough for me. So that's why focus on horizontal things like customer service. But if you go talk to a bank, sometimes customer service is not in office. I want to do something in loan origination or you're in insurance company. I want to use their own underwriting those air, the solutions that will get a lot of value out of running on an integrated data start >> a thousand flowers. Bloom is kind of ecosystem opportunity. Looking forward to checking in on that. Thoughts on on gaps. For that you guys want to make you want to do em in a on or areas that you think you want to double down on. That might need some help, either organic innovation or emanate what areas you looking at. Can you share a little bit of direction on that? >> We have, >> ah, a unique benefit. And IBM because we have IBM research. One of their big announcement this week is what we call Auto Way I, which is basically automating the process of feature engineering algorithm selection, bringing that into Watson Studio and Watson Machine learning. I am spending most of my time figure out howto I continue to bring great technology out of IBM research and put in the hand of clients through our products. You guys solve the debaters stuff yesterday. We're just getting started with that. We've got some pretty exciting organic innovation happen in IBM. >> It's awesome. Great news for startups. Final question for you. For the folks watching who aren't here in San Francisco, what's the big story here? And IBM think here in San Francisco. Big event closing down the streets here in Howard Street. It's huge. What's the big story? What's the most important things happening? >> The most important thing to me and the customer stories >> here >> are unbelievable. I think we've gotten past this point of a eyes, some idea for the future we have. Hundreds of clients were talking about how they did an A I project, and here's the outcome they got. It's really encouraging to see what I encourage. All clients, though, is so build your strategy off of one big guy. Project company should be doing hundreds of Aye, aye projects. So in twenty nineteen do one hundred projects. Half of them will probably fail. That's okay. The one's that work will more than make up for the ones that don't work. So we're really encouraging mass experimentation. And I think the clients that air here are, you know, creating an aspirational thing for things >> just anecdotally you mentioned earlier. Customer service is a low hanging fruit. Other use cases that are great low hanging fruit opportunities for a >> data discovery data curation these air really hard manual task. Today you can start to automate some of that. That has a really big impact. >> Rob Thomas, general manager of the data and a I groupie with an IBM now part of a bigger portfolio. Watson Rob. Great to see you conventionally on all your success. But following you from the beginning. Great momentum on the right way. Thanks. Gradually. More cute coverage here. Live in San Francisco from Mosconi North. I'm John for Dave A lot. They stay with us for more coverage after this short break

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Welcome back to the live coverage here in Mosconi North in San Francisco for IBM. Think this. The cubes coverage. I'm Jeffrey David. Launching a too great guest here. Carlos. Gavel, gavel. A chief date. Officer Clara, Columbia and Carlos. See? Good. Engage your manager. IBM data Science elite team a customer of IBM country around data science. Welcome to the Cube. Thanks for joining us. Thanks for having us. So we'll hear the street, the street to shut down a i N E. Where's the big theme? Multi cloud. But it's all about the data everywhere. People trying to put end to end solutions together to solve real business problems. Date is at the heart of all this moving date around from cloud to cloud using. Aye, aye. And technology get insights out of that. So take a minute to explain your situation, but you got to try to do. >> Okay. Okay, Perfect. Right now, we're working out a lot about the business thing because we need to use the machine learning models or all the artificial intelligence toe. Take best decisions for the company. Way. We're working with Carlo in a charming mother in order to know how how come with a boy the customers left the company Because for us it's very important to maintain our our customer toe. Now, how they're how are the cables is from them. There are two facility intelligences is next selling way to do it that way. Have a lot of challenge about that because, you know, we have a lot of data, different systems, that they're running the data way need to put all the information together to run them to run the mother's. The team that Carlo is leaving right now is helping to us a lot because we WeII know how to handle that. We know howto clean the data when you have to do the right governess for the data on the IBM iniquity is very compromised with us in there in order to do that safely. That is one of the union that is very close to us right now. She was working a lot with my team in order to run the models. You saying she was doing a lot of four. I mean, over fight on right now we are trained to do it in over the system, running this park on DH that is they? They Good way that we are. We are thinking that is going to get the gold for us way Need to maintain our customers. >> So years the largest telecommunications piece Claro in Mexico for boys and home services. Is that segments you guys are targeting? Yeah, Yeah. Scope. Size of how big is that? >> Clarisa? Largest company in Colombia For telecommunication. We have maybe fifty million customers in Colombia. More than fifty percent of the market marketer also way have many maybe two point five millions off forms in Colombia. That is more than fifty percent of the customers for from services on. Do you know that it's a big challenge for us because the competitors are all the time. Tryinto take our customers on DH the charm or they'll have toe. How's the boy that and how to I hope to do their artificial intelligence to do it much learning. It's a very good way to do that. >> So classic problem and telecommunications is Charon, right? So it's a date. A problem? Yeah, but So how did it all come about? So these guys came to you? >> Yeah. They help The game does. We got together. We talked about the problem and in turn was at the top right. These guys have a ton of data, so what we did is the team got together. We have really the way to data sensibly team works is we really helped clients in three areas. It's all about the right skills, the right people, the right tools and then the right process. So we put together a team. We put together some agile approaches on what we're going to do on DH. Then we'd get started by spinning up in environment. We took some data and we took there. And there's a lot of data is terabytes of data. We took their user data way, took their use users usage data, which is like how many text, cellphone and then bill on day that we pulled all that together and environment. Then the data scientists alongside what Carlos is team really worked on the problem, and they addressed it with, you know, machine learning, obviously target. In turn, they tried a variety of models, But actually, boost ended up being one of the better approaches on DH. They came up with a pretty good accuracy about nineties ninety two. Percent precision on the model. Predicting unpredictable turn. Yeah. >> So what did you do with that? That >> that that is a very good question because the company is preparing to handle that. I have a funny history. I said today to the business people. Okay, these customers are going to leave the company. Andi, I forget about that on DH. Two months later, I was asking Okay, what happened? They say, Okay, your model is very good. All the customers goes, >> Oh, my God, What >> this company with that they weren't working with a with information. That is the reason that we're thinking that the good ways to fame for on the right toe the left because twist them which is therefore, pulls the purposes toe Montana where our customers And in that case, we lose fifty thousand customers because we didn't do nothing Where we are close in the circle, we are taking care about that prescriptive boys could have tto do it on. OK, maybe that is her name. Voice problem. We need to correct them to fix the problem in orderto avoid that. But the fetus first parties toe predict toe. Get any score for the charm on Tau handled that with people obviously working. Also at the root cause analysis because way need to charm, way, need to fix from their road, >> Carla. So walk us through the scope of, like, just the project, because this is a concern we see in the industry a lot of data. How do I attack it? What's the scoop? You just come in and just into a data lake. How do you get to the value? These insights quickly because, honestly, they're starving for insights would take us through that quick process. >> Well, you know, every every problems with different. We helped hundreds of clients in different ways. But this pig a problem. It was a big data problem because we knew we had a lot of data. They had a new environment, but some of the data wasn't there. So what we did was way spun up a separate environment. We pulled some of the big data in there. We also pulled some of the other data together on DH. We started to do analysis on that kind of separately in the cloud, which is a little different, but we're working now to push that down into their Duke Data Lake, because not all the data is there, but some of the data is there, and we want to use some of that >> computer that almost to audit. Almost figure out what you want, what you want to pull in first, absolutely tie into the business on the business side. What would you guys like waiting for the answers? Or was that some of the on your side of process? How did it go down? >> I'm thinking about our business way. We're talking a little bit about about that about their detective tow hundred that I see before data within. That is a very good solution for that because we need infested toe, have us in orderto get the answers because finally we have a question we have question quite by. The customers are leaving us. Andi. What is data on the data handed in the good in a good way with governor? Dance with data cleaning with the rhyme orders toe. Do that on DH Right now, our concern is Business Section a business offer Because because the solution for the companies that way always, the new problems are coming from the data >> started ten years ago, you probably didn't have a new cluster to solve this problem. Data was maybe maybe isn't a data warehouse that maybe it wasn't And you probably weren't chief data officer back then. You know that roll kind of didn't exist, so a lot has changed in the last ten years. My question is, do you first of all be adjusting your comment on that? But do you see a point in which you could now take remedial action or maybe even automate some of that remedial action using machine intelligence and that data cloud or however else you do it to actually take action on behalf of the brand before humans who are without even human involvement foresee a day? >> Yeah. So just a comment on your thought about the times I've been doing technology for twenty something years, and data science is something has been around, but it's kind of evolved in software development. My thought is, uh, you know, we have these rolls of data scientists, but a lot of the feature engineering Data prep does require traditional people that were devious. And now Dave engineers and variety of skills come together, and that's what we try to do in every project. Just add that comment. A ce faras predicted ahead of time. Like, I think you're trying to say what data? Help me understand >> you. You know, you've got a ninety three percent accuracy. Okay, So I presume you take that, You give it to the business businesses, Okay? Let's maybe, you know, reach out to them, maybe do a little incentive or you know what kind of action in the machines take action on behalf of your brand? Do you foresee a day >> so that my thought is for Clara, Columbia and Carlos? But but obviously this is to me. Remain is the predictive models we build will obviously be deployed. And then it would interact with their digital mobile applications. So in real time, it'll react for the customers. And then obviously, you know, you want to make sure that claro and company trust that and it's making accurate predictions. And that's where a lot more, you know, we have to do some model validation and evaluation of that so they can begin to trust those predictions. I think is where >> I want to get your thoughts on this because you're doing a lot of learnings here. So can you guys each taking minutes playing the key Learnings from this As you go through the process? Certainly in the business side, there's a big imperative to do this. You want to have a business outcome that keeps the users there. But what did you learn? What was some of the learnings? You guys gone from the project? >> They the most important learning front from the company that wass teen in the data that that sound funny, but waiting in an alley, garbage in garbage, out on DH that wass very, very important for other was one of the things that we learn that we need to put cleaning date over the system. Also, the government's many people forget about the governments of the governments of the data on DH. Right now, we're working again with IBM in our government's >> so data quality problem? Yeah, they fight it and you report in to your CEO or the CEO. Seo, your spear of the CIA is OK. That >> is it. That's on another funny history, because because the company the company is right now, I am working for planning. This is saying they were working for planning for the company. >> Business planning? >> Yeah, for business planning. I was coming for an engineer engineering on DH. Right now, I'm working for a planning on trying to make money for the company, and you know that it's an engineer thinking how to get more money for the company I was talking about. So on some kind of analysis ticks, that is us Partial Analytics on I want you seeing that in engineer to know how the network handling how the quality of the network on right now using the same software this acknowledge, to know which is the better point to do sales is is a good combination finally and working. Ralph of planning on my boss, the planning the planet is working for the CEO and I heard about different organizations. Somebody's in Financial City owes in financial or the video for it is different. That depends from the company. Right now, I'm working for planning how to handle things, to make more money for the company, how to tow hundred children. And it is interesting because all the knowledge that I have engineering is perfect to do it >> Well, I would argue that's the job of a CDO is to figure out how to make money with data. Are saying money. Yeah. Absolute number one. Anyway, start there. >> Yeah, The thing we always talked about is really proving value. It starts with that use case. Identify where the real value is and then waken. You know, technology could come in the in the development work after that. So I agree with hundred percent. >> Carlos. Thanks for coming in. Largest telecommunication in Colombia. Great. Great customer reference. Carlo thinking men to explain real quick in a plug in for your data science elite team. What do you guys do? How do you engage? What? Some of the projects you work on Grey >> out. So we were a team of about one hundred data scientists worldwide. We work side by side with clients. In our job is to really understand the problem from end and help in all areas from skills, tools and technique. And we won't prototype in a three agile sprints. We use an agile methodology about six to eight weeks and we tied. It developed a really We call it a proof of value. It's it's not a M v P just yet or or poc But at the end of the day we prove out that we could get a model. We can do some prediction. We get a certain accuracy and it's gonna add value to the >> guys. Just >> It's not a freebie. It actually sorry. I'm sorry. It's not for paint service. It's a freebie is no cough you've got. But I don't like to use >> free way. Don't charge, but >> But it's something that clients could take advantage of if they're interesting problem and maybe eventually going to do some business. >> If you the largest telecommunication provider in the country, to get a freebie and then three keys, You guys dig in because its practitioners, real practitioners with the right skills, working on problems that way. Claro, >> Colombia's team. They were amazing. In Colombia. We had a really good time. Six to eight weeks working on it. You know, a problem on those guys. All loved it, too. They were. They were. Before they knew it. They were coding and python. And are they ready? Knew a lot of this stuff, but they're digging in with the team and became well together. >> This is the secret to modernization of digital transformation, Having sales process is getting co creating together. Absolutely. Guys do a great job, and I think this is a trend will see more of. Of course, the cubes bring you live coverage here in San Francisco at Mosconi. Nor That's where I said it is. They're shutting down the streets for IBM. Think twenty here in San Francisco, more cube coverage after the short break right back.