>> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards brought to you by Amazon web services. >> Hi, and welcome back. I'm Stu Miniman. This is theCUBE coverage of the AWS Public Sector Partner Awards. We going to be talking about the Customer Obsession Mission award winner. So happy to welcome to the program. First of all, welcoming back Joel Lipkin. He is the chief operating officer of Four Points Technologies, which is the winner of the aforementioned award and joining him one of his customers, Ryan Hillard, who is a assistant developer with the United States, Small Business Administration, and of course the SBA, an organization that a lot of people in the United States have gotten more familiar with this year. Joel and Ryan, thanks so much for joining us. >> Hi Stu? >> Hey Stu; Thank you. >> All right, so Ryan, I'm sorry, Joel, as I mentioned, you've been on the program, but maybe just give us a sketch if you would, Four Points, your role, your partnership with AWS. >> Sure, I'm Joel Lipkin. I'm the chief operating officer at Four Points Technology, Four Points is a value added technology reseller focused on the federal government and we've been working with federal customer since 2002. We're a service disabled veteran owned small business, and we've been in a Amazon partner since 2012. >> Wonderful; Ryan, if you could, obviously, as I mentioned, the SBA, a lot of people know for the PPP in 2020, if you could tell us a little bit about your role in your organization and tee up for us, if you would, the project that Four Points was involved with that you worked on. >> Sure; so I worked for the chief information officer and I don't have this official title, but I am the de facto manager of our Amazon Web Services presence. This year, we've had a very exciting time with what's been happening in the world, the Paycheck Protection Program, and the SBA have been kind of leveraged to help the US economy recover in the face of the pandemic. And a key part of that has been using Amazon Web Services and our partnership with Four Points Technology to launch new applications to address those requirements. >> Wonderful; Joel, maybe a connect for us. How long has Four Points been working with the SBA and start to give us a little bit more about the projects that you're working together, which I understand was predated the COVID incidents. >> Sure; we've been with SBA for several years now. And SBA was one of the earlier federal agencies that really saw the value in separating their procurement for cloud capacity, from the development implementation and managed services that they either did internally or use third party contractors for. So, Four Points came in as a true value added reseller of cloud to SBA providing cloud capacity and also Amazon professionals services. >> All right; so Ryan bring us in a little bit, the project that we're talking about here, what was the challenge? What were the goals you were looking to accomplish? Help flush out a little bit, what you're doing there? >> Yeah, so most recently Four Points partnered with us to deliver Lender Gateway. Lender Gateway is an application for small community oriented lenders to submit Paycheck Protection loans. So some of these lenders don't have giant established IT departments like big banks do, and they needed an easier way to help their customers. We built that application in six days and I called the Four Points cloud manager on a Saturday, and I said, help, help, I need two accounts by three o'clock and Four Points was there for us. We got new accounts set up. We were able to build the application and deploy it literally in a week and meet the requirements set for us. And that system has now moved billions of dollars of loans. I don't know the exact amount, but has done an incredible amount of work and it wouldn't have been possible without our partnership with Four Points. So we're really excited about that. >> Yeah, If I could drill in there for a second. Absolutely it's been an unprecedented, how fast that amount of money move through the legislature to out to the end user. Help us understand a little bit, how much were you using AWS technologies and solutions that Four Points had helped you with, and how much of this was kind of a net new, you said you built a new application, you had to activate some things fast, help us understand a little bit more. >> Yeah, that's so that's a great question. So we have five major systems in AWS today. And so we're very comfortable with AWS service offerings. What's interesting about Lender Gateway is that it's the first application we've built from scratch in a totally serverless capacity. So one of the hard technical requirements of the Paycheck Protection Program is that, it has huge amounts of demand. So when we're launching a system, we need to know that that system will not go down no matter how much traffic it receives or how many requests it has to handle. So we leaned on services like AWS Lambda, S3, dynamoDB, all of their serverless offerings to make sure that under no circumstances could this application fail. And it never did. We never even actually saw a performance degradation. So a massive success from my perspective as the program manager. >> well, that's wonderful. Joel, of course, you talk about scalability, you talk about uptime. Those are really the promise the public cloud has brought. Ryan did a good job of teeing out some of the services from AWS, but help us understand architecturally how you help put that together, and, the various pieces underneath. >> Yes Stu, it's interesting. Four Points is really focused on delivering capacity. Our delivery model is very much built around giving our customers like Ryan full control over their cloud environments so that they can use it as transparently as though they were working with Amazon directly. They have access to all of the 200+ services that AWS has. They also have a direct access to billing and usage information that lets them really optimize things. So this is sort of a perfect example of how well that works because SBA and Ryan knew their requirements better than anyone. And they were able to leverage exactly the right AWS tools without having to apply to use them. It was as though they were working directly with AWS and the AWS environment on the technology side. And I will say SBA has been really a leader in using of variety of AWS services beyond standard compute and storage, not just in a tested environment, but in a live very, very robust, really large environment. >> Yeah, right, and I was excited to hear about your Lambda usage, how you're building with the serverless architecture there. Could you just bring us through a little bit, how you ramped up on that, any tools or community solutions that you were leveraging to make sure you understood that and any lessons you learned along the way as you were building that application and rolling it out? >> Yeah, that's a great question. So I think one of the mistakes that I see program managers make all the time is thinking that they can migrate a workload to the cloud and keep it architecturally the same way it was. And what they quickly find out is that their old architecture that ran in their on premise data center might actually be more expensive in the cloud than it was in their data center. And so when you're thinking about migrating a workload, you really need to come in with the assumption that you will actually be redesigning that workload and building the system in cloud native technology. You know, the concept of Lambda is so powerful, but it didn't exist for, you know, it didn't exist 20 years ago when some of these systems and applications were being written and now being able to leverage Lambda to only use exactly the compute you need, means you can literally pay pennies on the dollar. One of the interesting things about the PPP program and everything happening in the world is that our main website, sba.gov is now serving a a hundred or a thousand times more traffic daily than it was used to doing. But because we lean on serverless technology like Lambda, we have scaled non-linearly in terms of costs. So we're only paying like two or three times more than we used to pay per month, but we're doing a hundred or a thousand times more work. That's a win, that's a huge victory for cloud technology, in my opinion. >> Yeah, and on that point, I think the other thing that SBA did really amazingly well was take advantage of first reserved instances. But I think it was the day that Amazon announced savings plans as a cost control mechanism. Ryan and SBA were on them. They were our first customer to use savings plans. And I think there were probably the first customer in the federal space to use them. So it's not just using the technology smart, it's using the cost control tools really well also. >> Yeah, so Stu, I wanted to jump in here just because I'm so glad Joel brought that up. I was describing how workloads need to morph and transform as they move from legacy setups into more cloud native ones. Well, we were the first federal agency to buy savings plans. And for folks who don't know savings plans essentially make your reserved instances fungible across services. So if you had a workload that was running on EC2 before, now instead of buying a reserved instance at a certain instant size, a certain family, you can instead buy a savings plan. And when your workload is ready to be moved from EC2 to something a little bit more containerized or cloud native, like Fargate or Lambda, then you don't actually forego your reserved instance. I see program managers get into this weird spot where they bought reserved instances, so they feel like they need to use them for a whole year. So they don't upgrade their system until their reserved instances expire. And that's really the tail wagging the dog. We were very excited about savings plans. I think we bought them four days after they came out and they have enabled us to do things like, be very ambitious with how we rethink our systems and how we rebuild them. And I'm so glad you brought that up to all because it's been such a key thing over this last year. >> Yeah, it's been a really interesting discussion point I've been having the last few years, is that the role between developers and that, that finance piece. So, Ryan, who is it that advises you on this? Is there somebody on the finance team from the SBA? is it Four Points? You know, being aware of savings plan, it was something that was announced at Reinvent, but it takes a while for that to trickle and oftentimes developers don't need to think about or think that they don't need to think about the financial implications of how they're architecting things. So how, how does that communication and decision making happen? >> That's such a great question. I think it goes back to how Four Points is customer obsessed. One of our favorite things about using a small business reseller like Four Points instead of dealing directly with our cloud service provider is that Four Points provides us a service where every quarter they do an independent assessment of our systems, how much we're spending and what that looks like from a service breakdown. And then we get that perspective and that opinion, and we enrich it with our conversation with our AWS account manager, with our finance people. But having that third party independent person come in and say, "Hey, this is what we think" has been so powerful because Joel and Dana and team have always had observations that nobody else has had. And those kinds of insights are nice to have, when you have people who are suspicious of a vendor telling you to buy more things with them, because they're the vendor >> From the lessons you've learned there, any final advice that you'd give to your peers out there, and how will you take what you've learned working on this project to other things, either in the SBA or in talking with your peers in other organizations. >> So I have two big things. So one is go use a small business reseller. I would be remiss if I didn't use this opportunity to tell you as a member of the US Small Business Administration, that there are some really, really great service providers out there. They are part of our programs like Four Points, and they can help you achieve that balance between trusting your cloud service provider and having that a third party entity that can come in and, call bowl and also call Yahtzee. So recognize good things and recognize bad things. So that would be number one. And then number two is moving to the cloud is so often sold as a technology project. And it's like 20% technology and 80% culture and workforce change. And so be honest with yourselves and your executive teams that this isn't a technology project. This is, we going to change how we do business project, and we going to change the culture of this organization kind of project. >> All right; and Joel, I'll let you have the final word on lessons learned here and also about Four Points and congratulations again, the Customer Obsession Mission award winner. >> Great, thanks Stu, we're so appreciative to Amazon for their recognition and to Ryan and SBA for giving us the opportunity to support such an important program. We are a small business, we are very much focused on delivering what our customers need in the cloud. And it's just such a tremendous feeling to be able to work on a program like this that has such, such payoff for the whole country. >> All right, Well, Joel and Ryan, thank you so much for sharing your updates, such an important project this year. Thanks so much. >> Thank you Stu. >> Thanks >> Stay with us for more covered from the AWS Public Sector Partner awards. I'm Stu Miniman, and thank you for watching theCUBE.

>>from Menlo Park, California In the heart of Silicon Valley, it's the Cube covering cloud now. Awards 2020 Brought to you by Silicon Angle Media. Now here's Sonia category. >>Hi and welcome to the Cube. I'm your host Sonia category, and we're on the ground at Facebook headquarters in Menlo Park, California covering Cloud now's top women entrepreneurs in Cloud Innovation Awards. Joining us today is Tao Johnson, who's the CEO and founder of Kaizen Technology Partners. Now welcome to the Cube. Thank you. Thank you for having me. So give us a brief overview of your background. >>Sure, I actually have a finance degree and have no idea what technology was. I started as a finance analyst at Sun Microsystems and had no idea who they were or what job awas but having the interest to be a CFO one day, our CEO in another company, I figured I'd go into sales and really understand what drives a company growth and revenue. So I was actually trained by Scott McNealy's best of the best program and was in sales class with him and his with his sister in law. And, um, I never left sales after them, >>so um So you mentioned that you have a finance background? How do you think that background has helped you to become a successful CEO versus, say, a technical background? >>And I think having the finance background is very important because your cash flow management is one of the biggest reasons companies fail. You know, before they can get their next round of funding, they run out of their overhead costs, their monthly overhead costs. The other thing is really to understand how to sell in our ally and total cost of ownership to the decision powers that be at the CFO level and CEO CIO. >>Okay, Um, so you're on the cloud now advisory board to tell us, How did you join And how was that experience? Like, I think >>it grew organically having been a participant to a few of the events with Jocelyn and then helping her. Where can I help? How can I get speakers for you or winners? And over time, just like just came to me and said, You know, you have such a network, Why don't you join our board and help us where we can? Hence we have mailing today, um, as our keynote because of our network. >>And speaking of entrepreneurs, you, um, I just want to mention that you are at this program for Harvard, for entrepreneurs. Can you talk more about that? >>Sure, it's an amazing program. I wish that there were more women who applied and were able to invest the money and time into the program. It's, ah, owners and entrepreneurs who have companies around the world. There's 41 countries represented. Unfortunately, only about 17% of women of 151 participants in class. We meet three times once a year, and we go through three weeks of intensive training to discuss marketing finance how to scale operations. But the best thing you get out of it is 1 30% of it is learning this case studies method and Harvard, the other 30% is really the network and the different industry's. You get to meet. We have film. As you know, we've talked about retail and other industries there that you can self reflect on. How does that involve with technology? Um, and then the other 30 self reflection time. A lot of entrepreneurs, especially CEOs, don't have the time to get away from their business, and it really forces you to not be the operator. Walk away and be able to self reflect on Where do you want to take the business >>today >>and speaking about networking? What's your advice on networking within the industry? What are some tips and tricks >>in my belief? You know, we have social media, but the best way to meet people is through other people. So going to events like this and really having an idea of your goals at the event when you're going there, who's going to help you get to that person? Um, and having a focus, not. I want to meet 100 80 people, and I don't know who they're going to be really being able to say, Who do I want to meet at that event who can help me get there and preparing plan as much triple the time that you're gonna be even at the event? >>Yes, the networking can be really difficult. So as an entrepreneur, what do you think makes a great entrepreneur? >>You know, entrepreneurship is very hard because you really have to touch all facets of a company and find the right people to trust to do certain areas, but then be able to understand all the different parts of the company, right, from supply chain to partnerships to sales and finance. So what, you really have to be diverse and ambidextrous, and that makes it very difficult for some people who are only analytical or only sales e to be able to run a company in scale. >>And what advice do you have for female technologists who maybe feel that so it's really difficult to navigate in this male dominated industry? I would >>say to them they're stand out, make your different standout, right? Why make it a negative? The positive is you are female and you stand out so less men get called on by you and you might have a chance to get in the door. But you better have your ideas in line and your resource is and you better be >>kick ass. But use it to your >>advantage that you are different and that they're not used to hearing from women. >>So you've been with carved out for many years now. Where do you hope to see cloud now in the future, I >>would love to see cloud now be more, uh, geographically worldwide as we're doing more work in my non profit for women Rwanda, in Afghanistan as entrepreneurs, Um and I think, you know, we've upped and stepped up so much more with Facebook bringing in investments to us to compared to what we've done before, Um, I think just the awareness and may be doing this on a, um, twice a year basis instead of only once a year to be ableto celebrate these wonderful women. >>Don, thank you so much for being on the Cube. This has been really knowledgeable. Thank you for having me. I'm Sonia Tagaris. Thank you for watching the Cube stay tuned for more. Yeah, yeah, yeah.

>> Narrator: Live from Washington D.C., it's theCUBE! Covering Boomi World 19, brought to you by Boomi. >> Welcome to theCUBE. Lisa Martin, with John Furrier. We are in Washington D.C. at Boomi 19. This is our second day of coverage and John and I are very excited to welcome one of Boomi's customers, we have Olive Perrins, head of In Home Experience at Sky. Olive, it's great to have you here. >> Hi, lovely to be here, it's a fantastic event. >> It is, we saw you onstage yesterday so we're very pleased to have you join us on theCUBE, so I think a lot of folks know about Sky. Everybody, I shouldn't say everybody on the planet, but most of us have an ISP. We have cable services. So, we're all customers of Sky or some of Sky's peers across the globe, so, we all kind of understand that. You guys have built something very cool with Boomi, ‘Future Assurance View’ tool, and when you taught that, when you showed me this before we went live, (exclaims) bring that to the U.S. because whenever there is a problem with our internet, I mean people, we just stop, right? >> Yeah. >> So, talk to us about what Sky has built with Boomi and some of the great things that it is enabling. >> Sure, so I think we always had amazing diagnostic information and we had lots of data. What we never did was connect at that and did data-driven decisioning. So, for us, Boomi was there to connect all of the sources together with the, over six million routers out in the field, and live on demand for a customer, check everything, all of the, telemetry data from their hubs, from their line and make sure that line is connected, it's fast enough, it compares well to their neighbors, it's stable, it's not retraining, it's as good as the line can be, and the wifi to every device in the home is good. If not, it simply decides which engineer it needs to fix this and dispatches the job. >> And you started this initially in a reactive mode to start, okay, there's faults here. Talk to us about that migration, we'll say transformation, since we're here, the transformation from reactive to proactive and then unveiling what you guys are doing with predictive. >> Yeah so, I think when we started, we set ourselves this big game of getting to 69% digital first. We were around 25% before we lunged, and to be honest, most of that 25%, it was to find the telephone number in digital rather than do anything. We're now at 87% and as you can imagine, the amount of data logs that creates, about 300,000 customers a week running the tool, has now led us to know which outcome is most reliable and really optimize our decisions. So, then we started to think, "Okay, well it's great that we're fixing "these issues, but we probably have "a lot of customers in pain." Who we're not getting to because they're not calling us or visiting the tool. Why don't we go proactive and then go predictive. Find who's going to be faulty tomorrow and intervene before it happens. So, we've taken all of the intelligence in Boomi and codified it into an algorithm, and every night, it runs and predicts who'll be healthy or unhealthy a signal tomorrow, and then, anyone who needs an engineer, we dispatch it and it just fixes it free of charge before the customer even knows it's broken. >> And was this, I'm just envisioning of the recent issues I've had with ISPs, ah, I need this. Was this driven by, you said initially, just a couple of years ago, only a quarter of your customers were, only a quarter of them were starting their search digitally and now it's up to 87% in just a two year period. What you've done to be, to go from reactive to proactive to predictive, was that driven by customer demand saying, we want, I don't even want to have to call in. I want to be able to get to you from any channel, or was it more driven by you guys suddenly having a massive increase in data, and saying, "We've got a lot more information. "If we can connect it together and unlock the value, "the services we deliver can become predictive." >> I think it was a blend of both, truthfully. So, once you ultimately master the cost per consumer, you've got a really good data model that says, given this fault, then send this engineer and we know, we'll fix it and they'll be happy. I think at that point, you start to say well, where are the other costs to the business? And ultimately that comes from churn and attracting new customers. So, it just feels right to spend more upfront on engineers to save churn later and keep a really healthy and happy base. >> You know, one of the great things about In Home Experience is obviously wifi 'cause it goes down whenever you're on screens, calls. So, the operational side to totally get the efficiencies and the savings that probably comes with that, but people are working at home more, you've seen virtual, so, there's a real need for reliability at home, but also it brings up the data and the security questions 'cause now you got wifi light-bulbs, you got, everything's wifi. So, you know, the In Home Experience now has people maybe working at home. >> Yeah. >> Home and pleasure, security, malware, all these things are cutting-edge data problems. How do you guys view that? What's the internal thinking around how to protect the home and. >> So, I guess the first thing that we needed to be really clear on is traditionally, in an ISP world, you are risk averse and you said our demarkation is where the line enters the home. That's no longer acceptable in today's age. Every time Facebook goes down, our help contacts increase by 30% and so, we know that our demarkation isn't the device, it's not the application on the device, it's the consumer themselves. It's their understanding and as an ISP, it's our job to educate, support and handhold. So, everything that we can do to make our hub smart enough that they're plug and play, and everything that we can do to predict what customers need in IOT and security, and build that in its source, it's the right thing to do. You'll have healthier happier customers in the longterm. >> And parents also want to turn the wifi off when the kids aren't doing their homework. You know, these policy kind of user experienced things are kind of, I mean, as an example, we have kids, but you know. >> We just launched a remote control for the internet, so you can control what your kids have access to anywhere, in or out of the home on any device. >> And you guys have just in this last couple of years, where mostly it's been going from reactive to proactive, you said predictive was launched recently, but even in that two years, your NPS Net Promoter score has gone up 20%, so, can you imagine in the next year or probably last, the impact that you're going to have because customers are getting what they want, and they probably, some of them don't even know it, if they don't know they have a problem, but Sky has identified it. I can only imagine that the churn numbers will go down and the NPS will even continue to rise. >> Exactly, and that's precisely what this is about, it's the happier the base is, the more stable. In the end, you're going to spend more on engineers and less on churn. That is the perfect balance, it really is. >> And in terms of spend, let's talk about the cost savings, dramatic cost savings. The first year alone, you saved a six million pounds? And the second year? >> Six million pounds and on track for similar this year. >> That's transformative to the business. >> It absolutely is, yeah. I think what it has allowed us to do is really knuckle down to watch at our budget bate, and get stability around that. So, now we've given the business some controls and dials, and they know what they can pull to control costs. >> What's next? What are you guys working on next 'cause obviously, that's good in return, you're reinvesting, it's more data, it's more things to do, it's got remote control internet. What are other things you guys looking at operationally to get into to innovate on? >> So, I think there's a real need for speed, for us it's about investing in fiber. We're putting all of our customers on a high fiber diet right now (laughs). So, it's dark fiber, faster fiber, one gig connections, and then on the wifi side, it's giving guarantees, so, it's no longer acceptable to have a router squirting out wifi. What we're now doing is guaranteeing you will have wifi of the best quality anywhere in your home to support any device, and we're putting our money where our mouth is and sending wifi heat mapping engineers with pods to get your house up and sorted right first time. Beyond that, I think it's very much going into the world of IOT, smart sensors, cameras and with that, of course, data. It means IP storage, backup for your cameras. >> One of the interesting (mumbles) trends we've been covering is automation. You're saying RPA, for instance, is a hot sector, observability on the data side, so this Cloud has, but you've mentioned the demark has changed to the user, so, you got wearables, I mean, if you've got gamers in the house, they're going to look at ping times. The kids know what ping times are. So, you're going to have all the speed issues. So, what's that going to look like for you guys as you think about more speed, more data, more people wanting custom services. Is there automation involved? I mean, where do you guys see the automation low-hanging fruit and where's the vision go? >> So, for me, it's not necessarily about automation, it's about personalization. We already have that data. We already use that data. Is it relevant to every customer? I'm sure my mum wouldn't want to know about ping, she wants to know if it's broken. So, I think for us, it's matching what's your intent and have we serviced that in an outcome, and right now, that's exactly where we're going with conversational AI, and then, really starting to consider, have we achieved your goal? RPA has a place, but I think right now, it's less about the generic quality of service and more about targeting your individual consumer needs in the home. >> I love that personalization angle because I think we sometimes in this digital age, personalization is lost. Sometimes we do that of our own, if we're going you know, on Door Dash or something to, instead of going to a restaurant. We want, I think we want a mix of both, but that personalization where something like wifi comes into play, like you were saying, when Facebook goes down, 38% spike in people calling and going, "Hey, there's a problem here." Whether or not it's Sky's problem or not. So, when we look at this demand for personalization, peoples' levels of frustration with, if there is an issue, you guys have resolved that, obviously, but in terms of what Boomi and Excentra announced yesterday with conversational AI. >> Yes. >> Really really exciting stuff there. You guys said, you and I were chatting before we went live, that there was a purposeful decision at Sky to not start this digital transformation with AI. Now, you're ready to take this on. Tell us about that decision and how you're now, really have the foundation with which to actually do it, conversationally, and make it personal. >> Yeah, and I think so much time goes into training bots and I really think that it needs to be authentic. You don't need to feel like you're talking to a human. It's okay that you know you're talking to a virtual machine, but that first interaction needs to be meaningful and helpful or you'll quickly stop engaging with it. So, I think for us, it was about define what does good quality look like? What might be the things that go wrong with Broadband? Ultimately, it really is only slow, not working at all or dropping lots outside the home or inside the home, and really it's about saying, what might be the problems we know about? Eliminate those and there's only a finite number of alternative problems left that we can really start to train a model on our learnings to date. So, I think having excluded all of the weird wonderful edge cases and dispatches, there's less there to worry about, but it's higher value for the consumer, and I think on the personalization angle, the key for us is understanding, are you tech-avoidant? Are you tech-savvy? Where are you on that scale? And which channel should we serve you up those steps in and how complicated or handholding should those steps be? And I think that's, for us, where conversational AI comes in. It's personalization, the number of steps, the type of steps and the channel that it's best served in. There is no point having Siri guide you through really complicated hands and knees wiring stuff. That's best done with some images sent through WhatsApp, for example. >> So, you guys will have the data to be able to determine, not just maybe knowing, why is this person calling in or why are they engaging with a chat bot? But to understand, what's that persons' preferred method of communication. There's that whole consumerization effect and that demand of the consumer of, you know, your mom and my mom-- >> And my handholding. >> Exactly, would have different levels. So, you're going to have enough of that quality data to really deliver the personalized experience way beyond knowing what boxes I have installed, what routers I have, what version, but also, my level of technology understanding. That's pretty cool. >> Exactly that. Exactly that, that's the destination for this year, absolutely. >> Well, sign me up. Bring this over to the U.S. And before we go, I want to note that that Sky and Boomi together, your design won the Best Enterprise Project at the UK National Technology Awards recently. >> It did, it did. >> Congratulations. >> What an honor. Thank you, it was a great night. >> Exactly, well, Olive, it's been great having you on theCUBE sharing with us what Sky is doing to really deliver a personalized experience going from reactive to proactive to predictive, awesome stuff, thank you. >> Exactly. Thank you, pleasure. >> Ours, too. For John Furrier, I'm Lisa Martin and you're watching theCUBE from Boomi World 19. (electronic upbeat music)

>> Live from San Francisco, it's theCUBE. Covering Google Cloud Next 19. Brought to you by Google Cloud and its eco system partners. >> Hello everyone welcome back here to theCUBE live coverage here in San Francisco, California. We're in the Moscone Center on the ground floor here. Day three of three days of coverage for Google Cloud Next 2019. I'm John Furrier, my co-host, Dave Vellante, Stew Miniman out there getting stories out there He's also been hosting. Dave, great to see you! Evren, Director of Product Management at Google Cloud, doing all the data streaming the data. We're streaming data right now. >> Absolutely, this is it. This is it. >> So let's stream some data. So streaming data has certainly been around for awhile. Dave and I when we first started theCUBE ten years ago, it was part of Silk and Angle Media hadoop was just a small little project. That really kind of was the catalyst moment for around big data that's now evolved to it's own position. Now you have streaming data, you have cloud scale, the Cloud has really changed the game on big data. Changed the nature and dynamics of it and one of the things is streaming data, streaming analytics as a core value proposition for enterprises, and this is fairly new. >> Very true. >> What's your take on it and how does it relate to what's going on with Google Cloud? >> I am glad we're talking about that. This is an exciting time for us. Streaming like you said is growing. Batch is not going away, but streaming is actually overtaking a lot of the applications that we're seeing. Today we're seeing more streaming applications taking place than batch. One of the things that we're seeing is everybody is gathering data from all over the place from your websites, from your mobile phones, from your IoT devices, just like we're doing right now. There's data coming in and people want to make decisions real time whether it's in the banking industry, in your healthcare, retail, it doesn't matter which word cycle you're working with and we're seeing how those messages how those events are coming in and where the decisions are being made real time, milliseconds we're talking about. >> Why is it happening, what's the real catalyst here? Just tsunami of data, nature of the value, all of the above, what's the? >> We believe one of the things is like you mentioned Cloud really changed the game. Where people actually can reach globally data and messages at scale. We're talking about billions of messages coming in and processing capacity is available now we can actually process it and make a decision within milliseconds and get to the results. To me, that was the biggest catalyst. And we're seeing many of us have grown up using batch data, making decisions now everybody is talking about M.L. and A.I. You need that data coming in real time and we can actual process it and make the decision. To me, that's the catalyst. >> First of all we love streaming data, this topic. One we believe streaming where shooting video but data, real time, has been one of the keys you see self driving cars monging of data, mixing and matching of data to get better signal and better machine learning and I got to ask you, because batch is certainly the role for batch is kind of old school it's some old techniques it's been around for awhile, >> It's not going to go away though. >> It's not going to go away it's established it's place but the knee jerk reaction of existing old school people who haven't migrated to the new modern version they go to the batch kind of mind set. I want to get you're reaction. Data lakes, there's nothing flowing in a lake. Okay, so there is a role for a data lake streaming gives me the impression of like an ocean or a river or something moving fast. Talk about the differences because it's not just the data lake okay that's a batch kind of reaction. >> It is a complementary. Actually it's not going away because all of that data that we had in the back is something we're relying on to really augment and see what's changing. So if you're in a retail house you're buying something, you're going to make a decision and your support is actually behind it. OK here's Evren, he's actually shopping around this and he wants this for his son. That's what the models built around it is looking at what is my behavior and in the moment making a decision for me. So that's not going away. The other thing is batch users are able to take advantage of the technology today. If you look at our data flow, same set of codes, same set of capability can be used by the same folks that are used to batch. You don't have to change anything so that actually we help folks to be up skilled using the same set of tools and become much more experienced and experts in the streaming too. That's not going away we help both of the worlds. >> So, complementary. >> Very complementary. >> So data lakes are good for kind of setting the table if you have to store it somewhere but that's not the end game though. >> No. >> Okay. >> I wonder if we could talk about the evolution from batch to real time streaming. And my favorite example, because I think people can relate to it, is fraud detection. Ten years ago, it was up to the user to go through his or her bill, right? And then you started to get inundated with false positives, and now lately, last couple of years it's getting better and better. Fewer false positives, usually when you usually no news is good news. News is usually bad news now, so take that example and use that to describe how things have evolved. >> I am a student of AI I did my Master's and PhD in that and I went through that change in my career because we had to collect the data, batch it and analyze it, and actually make a decision about it and we had a lot of false positives and in some cases some negative misses too which you don't want that either. And what happened is our modeling capabilities became much better. With this rich data, and you actually tap into that data lake, you can go in there the data is there, and this is spread data we can pull in data from different sources and actually remove the outliers and make our decision real time right there. We didn't have the processing capability we didn't have a place like PostUp where globic can scan and bring in data at hundreds of gigabytes of data. That's messaging you want to deal with at scale no matter where it is and process that, that wasn't available for us. Now it's available it's like a candy shelf for technologists, all the technology is in our hands and we wanted all these things. >> You were talking about I think the simplicity of, I'm able to use my batch processes and apply them. One of the complaints I hear from developers sometimes is that the data pipeline is getting so complicated. You were talking about you're grabbing stuff from websites, from financial databases, and so depending on what data store you're using and what streaming tools you're using or other A.I. tools, the pipeline gets very complicated the A.P.Is start to get complicated but I'm hearing a story of simplicity. Can you elaborate on that and add some color? >> Yeah I'm glad you're asking that question you may have heard, yesterday we announced a whole bunch of new things and ease of use is the top of the line for us. Really are trying to make it easy. If you look at this eco pipeline we're building with data flow, it helps you end to end. Data engineered no matter which angle their coming in should be able to use their known skill sets and be able to build their pipelines end to end so that you can achieve your goals around streaming. We aren't really having to go through a lot of the clusters of the pipelines we are going to continue to push that ease of use over and over, we're not going to let it go because make it easier, everyone will adapt it faster. >> You mentioned you got a PhD in A.I., Master's in A.I., A.I. has been around for awhile. A lot of people have been saying that but machine learning certainly has changed the game. Machine learning plus cloud has been a real accelerant in the academic and now commercial aspects of A.I. So I want to get your thoughts on the notion of scale which you talk about, plus the diversity of data. So if you can bring in data at scale get more signaling points more access to data signaling the diversity of data becomes very key. But cleanliness, data cleaning, used to be an old practice of you get a bunch of data, stack it up, put it in a pile corpus, and you kind of go clean it. With streaming, if it's always flowing there's kind of a behavioral characteristic of data cleanliness, data monitoring, talk about that diversity of data clean data and how that feeds machine learning and makes better A.I. >> Good one, so that's where we actually are able to, if you look at PostUp, you're building joint your table set of datas with streaming set of datas you can actually put it into data filter it and make those analyses. And within both, we provide enough of a window for you to be able to go back, hey are there things that I should be looking at, up to seven days we can provide a snapshot because you will always find something you can go back, you know what I'm going to remove this outlier. All worrying about all the processing we do before we bring in the data so there's a lot of cleanliness that takes place but we have the built in tools we have the built in capabilities for everyone to get going. It's ready to scale for you from the moment you open it up. That's the beauty of it, that's the beauty of when you start from PostUp to data flow to streaming engine it's ready for you to run. >> Talk about what's changed though when people hear diversity of data they get scared, oh my god I work, heavy lifting. Now it's a benefit. What's easier now to deal with all of these diverse data sets, what's the easy revolution? >> So do you remember the big V's of big data right? Volume, velocity, variety. People were scared about the variety. Now I can actually bring in my data from different places. Again, let's go back to the shopping example. Where I shop, what I shop for, that actually defines my behavior around it. Those data sit somewhere else. We bring those in to make a decision about okay everyone wants to go buy a scooter or whatever else, that's the diversity of the data. We're now able to deal to with this at scale. That was not available we could actually bring in and render this, now everything is going to do this much more sequential. We're now able to bring all of them together process it at the same time and make the decision. >> What's the key products that will make all of those happen, take us through the portfolio if I want that would you just said which is a great value. It sounds like not a heavy lift all I have to do is point the data sources into this engine, what are the products that make up that capability? >> So if I look at the overall portfolio on Google Cloud from our data analysts point of view, so you actually can bring in your data through PostUp, lots of messaging capability globally and you can actually do it regionally because we have a lot of regional requirements coming from various countries and data flow is where we actually transfer the data. That's where you do the processing. And you use all of these advance analytics capabilities through your streaming engine that we released and you have your B query, you have your OMLs, you have all kinds of things that you can bring in you're big tables and what have you. That's all easily integrated end to end for any analyst to be able to use. >> What is beam? >> Beam ah that's great I'm so glad you asked that question I almost forgot! Beam is one of our open sources we donated the same set, just like we did with Koppernes few years ago, we donated to the open source it's growing. This year actually it won The Technology Awards. So the source is open the community really took it upon, they use that toolkit to build their pipelines you can use any kind of a code that you want Java, Gold, whatever you want to do it and they contribute. We use it internally and externally. It's one of those things that's going to grow. We have a lot of community events coming up this year. We might, and I've seen the increase, I'm really really proud of that community. >> Evren, I love the A.I. can't get my mind off your background and academic because I studied A.I. as well in the 80s and 90s all that good stuff. Young kids are flocking to computer science now because A.I. is very sexy, it's very intoxicating and it's so easy to deal with now. You guys had a hack-a-thon here with NCAA using data really kind of real time and kind of cool things are happening. So it's a moment now for A.I. this is the moment. What's your advice, you've been through the wars you've done your chore duty all those years now it's actually happening. What's your advice for young people who want to come in, get their hands dirty, build things, use A.I., what's your advice, how they should tackle that? >> I am living it, both of my sons one is finishing junior high, the other one is a senior in high school, their both in it. So when I hear my young kids come and say, "hey bubba we just built this using transfer flow." Like it is making me really proud. At the middle school level they were doing it. So the good news is we have all of this publicly available data for them. I encourage every one of them. If you look at what we provide from Google Cloud, you come in there, we have the data for them, we have the tools for them, it's all ready for them to play so schools get free access to it too. >> It's a major culture but how do they get someone who's interested but never coded before, how do they jump right in and get ingratiated and immersed into the code, what do they do? >> We have some community reaches that we're actually doing as Google. We go out to them and we're actually establishing centers to really build community events for them to really learn some new skills. And we're making this easy for them. And I'm happy to hear more and do it, but I'm an advocate I go to middle schools, I go to high schools, I go to colleges. Colleges are a different story. We provide school classes and we provide our technologies at the universities because enterprises need that talent, need that skill, when they graduate, their going to hire them just like I'm going to hire them into my organization. >> So my number one complaint my kids have about school, they're talking about kids that, oh school's going to be a waste it's so linear I can learn everything on YouTube and Google.com. All the stuff I learned in school I'm never going to use in the real world. So the question is, what skill should kids learn that could be applied to machine learning, thinking, the kind of constructs, data structures, or methodologies, what are some of the skills and classes that can tease out and be natural lead into computer science and machine learning A.I.? >> You know, actually their going to build up the skills. The languages will evolve and so forth. As long as they have that inner curiosity asking new questions, how can I find the answer a little faster, that will push them towards different sets of tools, different sets of areas. If you go to Berkeley in here, you will see a whole bunch of high school kids working side by side with graduate students asking those questions, developing those skill sets, but it's all coming down to their curiosity. >> And I think that applies for business too. I mean there's a big gap between the A.I. haves and have-nots I always say. And the good news here that my take away is, you're going to buy A.I, you're going to buy it from people like Google and you're going to build it and apply it, you're going to spend time applying it, and that's how these incumbents can close the gap and that's the good news here. >> Very true if you look at it, look at all the A.P.Is that we have. From text recognition to image recognition to whatever it is, those are all built models and I've seen some customers build some fantastic applications starting from there and they use their own data, bring it in, they update their model for their own businesses cases. >> It's composition it's composing. It's not coding it's composing. >> Exactly, it's composing. We are taking it to the next level. That abstraction is going to actually help others come into the field because they know their field of expertise, they can ask direct questions. You and I may not know it but, they will ask direct questions. And they will go with the tools available for them for the curiosity that they reach. >> Okay what's the coolest thing you're working on right now? >> Coolest thing, I just y'know streaming is my baby. We are working on, I want to solve all the streaming challenges, whatever the industry is. I really want to welcome everyone, bring you to us. I think, if I look at it, one of the things we discussed today was Antos was fantastic right? I mean we're really going to change the game for all enterprises to be able to provide those capabilities at the infrastructure. But imagine what we can do with all the data analytics capabilities we have on top of it. I think this is the next five years is going to be fantastic for us. >> What's the coolest use case thing you see emerging out of streaming? >> Ah you know, yesterday I actually had one of my clients with me onstage, AB Tasty. They had a fantastic capability that they built. They tried everything. And we were not their first choice, I'll be very open. They said the same thing to everybody, you guys were not our first choice. They went around, they looked at all the tool kits, everything. They came they used PostUp, they used data flow, they used engine, streaming engine. And they AB testing for marketing. And they do that at scale, billions of messages every minute, and they do it within seconds, milliseconds, 32 milliseconds at most. Because they have to make the decision. That was awesome, go check. I don't know if you're familiar with that. One of our customers, they provide these real time delivery. In India, imagine where things are. In global leaders, you can actually ask for a food to be delivered and they have to optimize, depending on what the traffic is and go with their scooters, and provide you this delivery. They aren't doing it as well. Okato, they believe, provide food in UK 70% of the population use our technologies for real time delivery. Those are some great examples. >> Evren, great insight, great to have you on. Just a final word here, next couple years, how do you see the trajectory of machine learning A.I. Analytics feeding into the value of making life easier society better, and businesses more productive? >> We are seeing really good pull from enterprises from every archival that you can think of. Regulated, retail, what have you. And we're going to solve some really hard problems whether it's in health care industry, financial industry, retail industry, we're going to make lives of people much easier. And their going to benefit from it at scale. And I believe we're just scratching the tip of it and you're seeing this energy in here. Year over year this has gotten better and better. I can't wait to see what's going to happen next year. >> Evren Eryurek great energy, expert at A.Is, streaming analytics, again this is early days of a brand new shift that's happening. You get on the right side of history it's A.I. machine learning, streaming analysts. Thanks for coming, I appreciate it. >> Thank you so much, take care guys. >> More live coverage here in theCUBE in San Francisco at Google next Cloud 2019. We'll be back after this short break.

(clicking) >> I am Lisa Martin with theCUBE on the ground at Google for the sixth annual Top Women in Cloud Awards event with CloudNOW. Very excited to be joined by next guest, Ajit George, the Managing Director of the Shanti Bhavan Children's Project. Welcome to the cube. >> Hi Lisa, it's great to be here. >> So, I was so excited to have a chat with you. The Shanti Bhavan Children's Project is incredible. Tell us about it, 20 years now, tell us about what that is, how your family is involved, and what it's helping to do for these young children in Bangelore, India? >> Sure, Shanti Bhavan was founded by my father, Dr. Abraham George, 20 years ago, and its goal is to educate children, but also to eliminate poverty and change entire systems of communities and governments. It, the way we achieve this goal is by taking children from the poorest communities in India, giving them a high-quality, boarding school education, from the age of four until they graduate from 12th grade, and we cover everything during that period. So, their healthcare, their clothing, their boarding, food, all of that is taken care of, as well as training in soft skills. So, debate, interpersonal and interview skills, leadership skills, and the whole nine yards. While we educate them in the highest curriculum, the toughest standards in India, and then we pay for their entire college degree afterwards. So, that is 17 years of a high-quality intervention per child from the very first day they start school to the very first day of work. >> That's incredible and you have a very high college graduation rate, isn't that correct? Yeah, that is correct. If they pass out of high school, their high school graduation rate is about 77%, University graduation rate is 98% and so- >> Wow, 98%. >> It's been pretty exciting and they go on from those, from college to multinational companies, like Mercedes-Benz or Amazon, or Goldman Sachs. So, our kids who come from urban slums or rural villages with huts with no running water or electricity are making more in their first five years, than their parents make in a lifetime. So, it's a quantum leap, it is a genuine breaking the cycle of poverty, and the ability to become both, either the primary or the sole breadwinner for their entire family. So, four or five other people are dependent on them at the age of 21. >> And that's incredible, I was watching, there is a Daughters of Destiny, Netflix Original Docuseries. I saw the trailer of it today, incredibly profound. One of the things that, a couple things that really stuck out to me was, this is taking children from poverty to possibility. And also, one of the young girls that was in that trailer had said, "I've got a lot to lose, it's now or never for me." These children seem to really understand the gravity of their situation, and genuinely recognize the opportunity that they've been given. >> Yeah, sure, every single Shanti Bhavan child understands, it's almost like they've won the lottery, they've had an opportunity that no one in their families have ever had, but no one from their communities have had either. They're the first person in their family for generations to get any kind of education, and so that's a powerful opportunity, but it's also an important obligation or duty to give back to the family and to make an impact for the community because they are given this golden ticket, and they want to do something important with it. If they don't succeed, nobody gives them a second chance. Kids from that kind of community, and from that kind of circumstance, don't really have a second chance if they aren't able to make the most of it. So when you hear those stories they're talking about, "hey, I really need to seize this moment." "I need to seize this opportunity," maybe, "my mother's back at home and she needs my help," maybe, "my father's bedridden." A lot of these kids have generational debt, so they owe money to, like a money lender, which is an illegal lender and that's a couple generations back. Maybe their grandparents have taken out this debt, so they have all these debts piled up on them, and they have healthcare bills piled up on them, and they've got housing and all of these other problems. Then they have to educate their younger brothers and sisters and pay for dowries for their family members. It's the enormous responsibilities on one child is huge, but they're able to step up because they're given this powerful education, this great opportunity, so there's a lot of pressure, but there's also this great knowledge that they have a horizon out there that no one in their family has ever had before. >> That's incredible and so in the last couple minutes here, CloudNOW, where we are at the awards event tonight, they've teamed up with Intel, Apcera, and CB Technologies, to launch the Daughters of Destiny STEM scholarship. So exciting, what's that going to mean for current students, at Shanti Bhavan or the future students? >> Right, I think I'm really, really thankful, first of all to CB Technologies, Intel, and Apcera, as well as the CloudNOW. This scholarship is the first of its kind within our program and it allows these three young ladies, who are the first recipients of the scholarship, and hopefully there'll be many more recipients, but these young ladies to get a high-quality college education in the STEM fields, which is their passion. So, it opens doors for them for their education, potentially for internships and maybe job opportunities after college. So, I think this is a gateway to something bright and beautiful. >> Oh, I love that and how you described it for these children as a quantum leap, is as profound as what's been shown in the Netflix series. So, Ajit, thank you so much for joining. I wish we had more time, this is such an incredible project that you're working on, but we thank you for stopping by theCUBE and sharing it with us. >> Thank you so much, Lisa, it's great to be here. >> We want to thank you for watching theCUBE. I'm Lisa Martin on the ground at Google for the CloudNOW, Top Women in Technology Awards. Bye for now. (closing music)