(Gentle music) >> Hello and welcome to the Cube here in Palo Alto, California. I'm John Furrier here, joined by Platform nine, Amelia Bell the Chief Revenue Officer, really digging into the conversation around Kubernetes Cloud native and the journey this next generation cloud. Amelia, thanks for coming in and joining me today. >> Thank you, thank you. Great pleasure to be here. >> So, CRO, chief Revenue Officer. So you're mainly in charge of serving the customers, making sure they're they're happy with the solution you guys have. >> That's right. >> And this market must be pretty exciting. >> Oh, it's very exciting and we are seeing a lot of new use cases coming up all the time. So part of my job is to obtain new customers but then of course, service our existing customers and then there's a constant evolution. Nothing is standing still right now. >> We've had all your co-founders on, on the show here and we've kind of talked about the trends and where you guys have come from, where you guys are going now. And it's interesting, if you look at the cloud native market, the scale is still huge. You seeing now this next wave of AI coming on, which I call that's the real web three in my mind in terms of like the next experiences really still points to data infrastructure scale. These next gen apps are coming. And so that's being built on the previous generation of DevSecOps. >> Right >> And so a lot of enterprises are having to grow up really, really fast >> Right. >> And figure out, okay, I got to have scale I got large scale data, I got horizontal scalability I got to apply machine learning now the new software engineering practice. And then, oh, by the way I got the Kubernetes clusters I got to manage >> Right. >> I got what's containers weather, the security problems. This is a really complicated but important area of build out right now in the marketplace. >> Right. What are you seeing? >> So it's, it's really important that the infrastructure is not the hindrance in these cases. And we, one of our customers is in fact a large AI company and we, I met with them yesterday and asked them, you know, why are you giving that to us? You've got really smart engineers. They can run and create the infrastructure, you know in a custom way that you want it. And they said, we've got to be core to our business. There's plenty of work to do just on delivering the AI capabilities, and there's plenty of work to do. We can't get bogged down in the infrastructure. We don't want to have people running the engine we want them driving the car. We want them creating value on top of that. so they can't have the infrastructure being the bottleneck for them. >> It's interesting, the AI companies, that's their value proposition to their customers is that they don't want the technical talent. >> Right. >> Working on, you know, non-differentiated heavy lifting things. >> Right. >> And automate those and scale it up. Can you talk about the problem that you guys are solving? Because there's a lot going on here. >> Yeah. >> You can look at all aspects of the DevOps scale. There's a lot of little problems, some big problems. What are you guys focusing on? What's the bullseye for Platform known? >> Okay, so the bullseye is that Kubernetes infrastructure is really hard, right? It's really hard to create and run. So we introduce a time to market efficiency, let's get this up and running and let's get you into production and and producing results for your customers fast. But at the same time, let's reduce your cost and complexity and increase reliability. So, >> And what are some of the things that they're having problems with that are breaking? Is it more of updates on code? Is it size of the, I mean clusters they have, what what is it more operational? What are the, what are some of the things that are that kind of get them to call you guys up? What's the main thing? >> It's the operations. It's all operations. So what, what happens is that if you have a look at Kubernetes platform it's made up of many, many components. And that's where it gets complex. It's not just Kubernetes. There's load balances, networking, there's observability. All these things have to operate together. And all the piece parts have to be upgraded and maintained. The integrations need to work, you need to have probes into the system to predict where problems can be coming. So the operational part of it is complex. So you need to be observing not only your clusters in the health of the clusters and the nodes and so on but the health of the platform itself. >> We're going to get Peter Frey in on here after I talk about some of the technical issues on deployments. But what's the, what's the big decision for the customer? Because there's kind of, there's two schools of thought. One is, I'm going to build my own and have my team build it or I'm going to go with a partner >> Right. >> Say platform nine, what's the trade offs there? Because it seems to me that, that there's a there's a certain area of where it's core competency but I can outsource it or partner with it and, and work with platform nine versus trying to take it all on internally >> Right. >> Of which requires more costs. So there's a, there's a line where you kind of like figure out that customers have to figure out that, that piece >> Right >> What do, what's your view on that? Because I'm hearing that more people are saying, hey I want to, I want to focus my people on solutions. The app side, not so much the ops >> Right. >> What's the trade off? How do you talk about? >> It's a really interesting question because most companies think they have two options. It's either a DIY option and they love that engineers love playing with the new and on the latest. And then they think the other option is going to cloud, public cloud and have it semi managed by them. And you get very different out of those. So in the DIY you get flexibility coz you get to choose your infrastructure but then you've got all the complexities of the DIY piece. You've got to not only choose all your components but you've got to keep them working. Now if you go to public cloud option, you lose flexibility because a lot of those choices are made for you but you gain agility because quite frankly it's really easy to spin up clusters. So what we are, is that in the middle we bring the agility and the flexibility because we bring the control plane that allows you to spin up clusters and and lifecycle manage them very quickly. So the agility's there but you can do it on the infrastructure of your choice. And in the DIY culture, one of the hardest things to do actually is to convince them they don't have to do it themselves. They can focus on higher value activities, which are more focused on delivering outcomes to their customers. >> So you provide the solution that allows them to feel like they're billing it themselves. >> Correct. >> And get these scale and speed and the efficiencies of the op side. So it's kind of the best of both worlds. It's not a full outsource. >> Right, right. >> You're bringing them in to make their jobs easier >> Right, That's right. So they get choices. >> Yeah. >> We, we, they get choices on how they build it and then we run and operate it for them. But they, they have all the observability. The benefit is that if we are managing their operations and most of our customers choose the managed operations piece of it, then they don't. If something goes wrong, we fix that and they, they they get told, oh, by the way, you had a problem. We've dealt with it. But in the other model is they've got to create all that observability themselves and they've got to get ahead of the issues themselves, and then they've got to raise tickets to whoever they need to raise tickets to. Whereas we have things like auto ticket generation and so on where, look, just drive the car let us worry about the engine and all of that. Let us deal with that. And you can choose whatever you want about the engine but let us manage it for you. So >> What do you, what do you say to folks out there that are may have a need for platform nine? What's the signals inside their company that they should be calling you guys up and, and leaning in with platform nine? >> Right. >> Is it more sprawl on on clusters? Is it more errors? Is it more tickets? Is it more hassle? What are some of the signs? If someone's watching this say, hey I have, I have an issue with this. >> I would say, if there's operational inefficiencies you can't get things to market fast enough because you are building this and it's just taking too long you're spending way too much time operationally on the infrastructure, then you are, you are not using your resources where they should best be used. And, and that is delivering services to the customer. >> Ed me Hora on for International Women's Day. And she was talking about how they love to solve complex problems on the engineering team at Platform nine. It's going to get pretty complex with the edge emerging >> Indeed >> and cloud native on-premises distributed computing. >> Indeed. >> essentially is what it is. That's kind of the core DNA of the team. >> Yeah. >> What, how does that translate to the customers? Because IT seems to be, okay, I have virtual machines were great, now I got to scale up and and convert over a transform to containers, Kubernetes >> Right. >> And then large scale app, app applications. >> Right, so when it comes to Edge it gets complex pretty fast because it's highly distributed. So how do you have standardization and governance across all the different edge locations? So what we bring into play is an ability to, um, at each edge, location eh, provision from bare metal up all the way up to the application. So let's say you have thousands of stores and you want to modernize those stores, you know rather than having a server being sent somewhere to have an image loaded up and then sent that and then you've got to send a technical guide to the store and you've got to implement it all there. Forget all that. That's just, that's just a ridiculous waste of time. So what we've done is we've created the ability where the server can just be sent to the store. You can get your barista or your chef just to plug it in, right? You don't need to send any technical person over there. As long as we have access to it, we get access to it and we provision the whole thing from bare metal up and then we can maintain it according to the standards that are needed and upgrade accordingly. And that gives standardization across all your stores or edge locations or 5G towers or whatever it is, distribution centers. And we can create nice governance and good standardization which allows them to innovate fast as well. >> So this is a real opportunity for you guys. >> Yeah. >> This is an advantage from your expertise. >> Yes. >> The edge piece, dropping in a box, self-provisioning. >> That's right. So yeah. >> Can people do that? What's the, >> No, actually it, it's, it's very difficult to do. I I, from my understanding, we're the only people that can provision it from bare metal up, right? So if anyone has a different story, I'd love to hear about that. But that's my understanding today. >> That's a good value purpose. So talk about the value of the customer. What kind of scope do you got? Can you scope some of the customer environments you have from >> Sure. >> From, you know, small to the large, how give us an idea of the order of magnitude of the >> Yeah, so, so small customers may have 20 clusters or something like that. 20 nodes, I beg your pardon. Our large customers, like we're we are scaling one particular distributed environment from 2200 nodes to 10,000 nodes by the end of this year and 26,000 nodes next year. We have another customer that's scaling up to 10,000 nodes this year as well. So we have some very large scale, but some smaller ones too. And we're, we're happy to work with either end. >> Okay, so pretend I'm a customer. I'm really, I got pain and Kubernetes like I want to, I can't hire enough people. I want to have my all focus. What's the pitch? >> Okay. So skill shortage is something that that everyone is facing right now. And if, if you've got skill shortage it's going to be really hard to hire if you are competing against really, you know, high salary you know, offering companies that are out there. So the pitch is, let us do it for you. We have, we have a team of excellent probably the best Kubernetes engineers on the planet. We will create your environment for you. We will get it up and running. We will allow you to, you know, run your applica, just consume the platform, we'll run it for you. We'll have SLAs and up times guaranteed and you can just focus on delivering the software and the value needed to your customers. >> What are some of the testimonials that you get from people? Just anecdotally, what do they say? Oh my god, you guys save. >> Yeah. >> Our butts. >> Yeah. >> This is amazing. We just shipped our code out much faster. >> Yeah. >> What are some of the things that you hear? >> So, so the number one thing I hear is it just works right? It's, we don't have to worry about it, it just works. So that, that's a really great feedback that we get. The other thing I hear is if we do have issues that your team are amazing, they they fix things, they're proactive, you know, they're we really enjoy working with you. So from, from that perspective, that's great. But the other side of it is we hear things like if we were to do that ourselves we would've taken six to 12 months to build that. And you guys have just saved us six to 12 months. The other thing that we hear is with the same two engineers we started on, you know, a hundred nodes we're now running thousands of nodes. We have not had to increase the size of the team and expand and scale exponentially. >> Awesome. What's next for you guys? What's on your, your plate? >> Yeah. >> With CRO, what's some of the goals you have? >> Yeah, so growth of course as a CRO, you don't get away from that. We've got some very exciting, actually, initiatives coming up. One of the things that we are seeing a lot of demand for and is, is in the area of virtualization bringing virtual machine, virtual virtual containers, sorry I'm saying that all wrong. Bringing virtual machine, the virtual machines onto the cloud native infrastructure using Kubernetes technology. So that provides a, an excellent stepping stone for those guys who are in the virtualization world. And they can't move to containers, they can't refactor their applications and workloads fast enough. So just bring your virtual machine and put it onto the container infrastructure. So we're seeing a lot of demand for that, because it provides an excellent stepping stone. Why not use Kubernetes to orchestrate virtual the virtual world? And then we've got some really interesting cost optimization. >> So a lot of migration kind of thinking around VMs and >> Oh, tremendous. The, the VM world is just massively bigger than the container world right now. So you can't ignore that. So we are providing basically the evolution, the the journey for the customers to utilize the greatest of technologies without having to do that in a, in a in a way that just breaks the bank and they can't get there fast enough. So we provide those stepping stones for them. Yeah. >> Amelia thank you for coming on. Sharing. >> Thank you. >> The update on platform nine. Congratulations on your big accounts you have and >> thank you. >> And the world could get more complex, which Means >> indeed >> have more customers. >> Thank you, thank you John. Appreciate that. Thank you. >> I'm John Furry. You're watching Platform nine and the Cube Conversations here. Thanks for watching. (gentle music)

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world, and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to the Cube's presentation of "Democratizing Analytics Across the Enterprise," made possible by Alteryx. An Alteryx-commissioned IDC InfoBrief entitled, Four Ways to Unlock Transformative Business Outcomes From Analytics Investments, found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special Cube presentation, Jason Klein, Product Marketing Director of Alteryx, will join me to share key findings from the new Alteryx-commissioned IDC Brief, and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then, in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jacqui Van der Leij-Greyling, who is the Global Head of Tax Technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research which spoke with about 1500 leaders? What nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees. And this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. >> So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? >> Sure, well, first, there's more data than ever before. The data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> Yet not all analytics spending is resulting in the same ROI. So, what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead, they're relying on outdated spreadsheet technology. Nine out of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value >> from their data and analytics and achieved more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics, across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources compared to only 67% among the ROI laggards. >> So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also, among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively, and letting them do so cross-functionally >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side, and is expected to spend more on analytics than other IT. What risks does this present to the overall organization? If IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance, which ultimately impedes democratization and hence, ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more, you know, on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up an Alteryx environment. But also to take a look at your analytics stack, and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process and technologies. Jason, thank you so much for joining me today, unpacking the IDC InfoBrief and the great nuggets in there. Lots that organizations can learn, and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you. It's been a pleasure. >> In a moment, Alan Jacobson, who's the Chief Data and Analytics Officer at Alteryx, is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching the Cube, the leader in tech enterprise coverage. (gentle music)

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world, and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to the Cube's presentation of "Democratizing Analytics Across the Enterprise," made possible by Alteryx. An Alteryx-commissioned IDC InfoBrief entitled, Four Ways to Unlock Transformative Business Outcomes From Analytics Investments, found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special Cube presentation, Jason Klein, Product Marketing Director of Alteryx, will join me to share key findings from the new Alteryx-commissioned IDC Brief, and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then, in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jacqui Van der Leij-Greyling, who is the Global Head of Tax Technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research which spoke with about 1500 leaders? What nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees. And this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. >> So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? >> Sure, well, first, there's more data than ever before. The data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the InfoBrief uncovered with respect to the the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy, as compared to the technology itself. And next, while data is everywhere, most organizations, 63%, from our survey, are still not using the full breadth of data types available. Yet, data's never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytics tools to help everyone unlock the power of data. They instead rely on outdated spreadsheet technology. In our survey, 9 out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely, you can do so. Yep, we'll go back to Lisa's question. Let's retake the question and the answer. >> That'll be not all analog spending results in the same ROI. What are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we can get that clean question and answer. >> Okay. >> Thank you for that. on your ISO, we're still speeding, Lisa. So give it a beat in your head, and then on you. >> Yet not all analytics spending is resulting in the same ROI. So, what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead, they're relying on outdated spreadsheet technology. Nine out of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieved more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics, across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did. It did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads. Can I start that one over? Can I redo this one? >> Sure. >> Yeah >> Of course. Stand by. >> Tongue tied. >> Yep. No worries. >> One second. >> If we could get, if we could do the same, Lisa, just have a clean break. We'll go to your question. Yep. >> Yeah. >> On you Lisa. Just give that a count and whenever you're ready, here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources compared to only 67% among the ROI laggards. >> So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also, among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively, and letting them do so cross-functionally >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side, and is expected to spend more on analytics than other IT. What risks does this present to the overall organization? If IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance, which ultimately impedes democratization and hence, ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more, you know, on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up an Alteryx environment. But also to take a look at your analytics stack, and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process and technologies. Jason, thank you so much for joining me today, unpacking the IDC InfoBrief and the great nuggets in there. Lots that organizations can learn, and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you. It's been a pleasure. >> In a moment, Alan Jacobson, who's the Chief Data and Analytics Officer at Alteryx, is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching the Cube, the leader in tech enterprise coverage. (gentle music)

>> Live from Las Vegas. It's theCUBE. Covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome to theCUBE. We are live at VMworld 2018. Day one, VMware's 20th anniversary. I am Lisa Martin, very excited to be joined by Dave Vellante. Hey, Dave! >> Hey, Lisa, good to see you again. >> Good to see you, too. We are welcoming back to theCUBE, an alumni, Geoff Waters, the VP of Global Cloud Sales for Vmware, hi, Geoff. >> Hi, great to be here, guys. Last year, we talked about the buzz, VMware getting the buzz back. Boy, this is a sonic boom this year. >> Yeah, it's a lot of buzz. >> Superpower infused. And we've also got David Wigglesworth, the Chief Revenue Officer for OVH. David, welcome to theCUBE. >> Thank you very much, both of you, Dave and Lisa. >> So, I have to ask first, do you have the VMware tattoo that Pat Gelsinger sported this morning? >> I don't have VMware, but I do have OVHcloud. Okay, so, speaking of OVH, David give our viewers an overview of what you guys are doing and what momentum you have created with VMware. >> Yeah, you know, it's an exciting time for us, especially to be here, as a Global Diamond sponsor, right? This is our second year, as OVHcloud, to be here. Last year, when we came, it was right after the vCloud Air acquisition of the asset from Vmware. Which is where our partnership just continued to grow more and more. And, so, for the last year, what we've been doing is we've really been focusing on deploying our data centers here, as well as getting our products ready to go to market. I always joke that OVHcloud is, probably, the best-kept secret in the US because that, when we acquired vCloud Air's assets, is when we kind of launched in the US. But, as Geoff can tell you in a few minutes, we've been a partner with VMware for years, right? And it's been really exciting. >> Yeah, I wonder if you could talk about that, Geoff, a little bit, I mean, the signal on vCloud Air early on, you guys kept having to tune the radio station, so to speak. >> Yep. >> Yep. >> And then, boom, finally it hit the OVH acquisition and then AWS deal, of course, IBM and other cloud service providers. Talk about how that all came about, and the track that you're on now. >> Yes, so, I mean, we've been partnering with OVH for actually nine years, I went back and I researched it. >> Did you? >> Yeah, back in Europe. So, they've actually been a seven-time Service Provider of the Year award winner. So, our relationship with OVH is nothing new. And we've been working with them for years. The other thing is the breadth of the portfolio adoption, the full SDDC stack, so not just vSphere, NSX, vSAN, the entire stack. So, you know, OVH is right in the forefront of our overall cloud strategy, and it has been for years. >> Yeah, and as a global infrastructure provider, we have almost a million 500 thousand customers, in 138 different countries. We have 28 data centers, three here in North America. We've got the breadth to go to the market in a big way. So, it's exciting to be here. >> So, lay out the options that you have for OVH customers. What services can they get from you? What are the platforms? >> No, it's a great question. So, obviously, have a very purpose-felt solution built on VMware, right, with our Hybrid Private Cloud. It's all built on the SDDC stack. So vSphere, vSAN, NSX, everything that Geoff mentioned. We also offer a bare metal solution. And then we also have a public cloud offering that's built on our relationship that we have with OpenStack. So, we give our customers three different choices on what they want to go to the market with. >> So, what do you make of, what's the AWS-VMware partnership mean for OVH? How do you guys take advantage of that? >> Well, I mean, you know, look. I think Pat, in his keynote this morning, talked about that eight out of every 10 customers is using cloud today, multi-cloud strategy. The average large customer is using, what did he say, eight clouds? >> Yep. >> He said that they're forecasting that there would be 10 clouds by the end of 2019. I'd like to take one of those two spots, if you don't mind. So, no, we think there's huge opportunity. I mean, Amazon's built a business on, and has created kind of the standard. We think there's plenty of room to play in a very large market. >> Well, the services market has always been highly fragmented. >> Yep. >> And it's always been local in nature. Maybe not as to the degree and scale, but, so, you've got, what did you say, a million and a half customers? >> Globally. >> So what are they telling you about their cloud strategy? >> Well, what our customers are asking for is they're asking for agility. They're looking for low cost. You know, we announced a partner program earlier this morning, where we're launching that. And our partners are coming to us saying, David, give us choice, give us flexibility, and help us save a little bit of money. I mean, all of our partners are dealing with margin erosion, as well as everybody else in the industry. So, if we can come to market and actually help them go acquire a customer, and help them do that in a way that's cost-effective, they're very excited about that. >> So, what's the conversation that you're having with customers? You know, we were, a lot of press, a lot of news came out this morning. A lot of great announcements made by Pat and team on stage. Customers talking about migrating from on-prem to the cloud, from public back to on-premises, for security compliance reasons. What are some of the things that you guys are hearing from customers, when you're having those business-level discussions about being able to execute a successful cloud strategy? >> You want to hit that first, and I'll come over. >> Go ahead. Well, I can. So, what our customers are talking about is simplicity. One of the things that we're excited to work about, to work with VMware on, is that our customers, when they move their solution on-prem to our hybrid cloud, they use the exact same resources that they use on-prem today. They don't have to go hire new people. It's all of the exact same economics that they've built to an on-prem solution, is in their off-prem solution with OVHcloud. That's what makes this so unique, right? I mean, look, part of the vCloud Air acquisition, what are we doing? We're migrating VMware customers, right, that are using VMware technology, that we're setting on vCloud Air into OVH data centers, using VMware technology to do it. And, so, it's. >> Just to add to that, the beauty is reducing day two complexity onto the operations, day two operations. So, instead of customers having to build out all themselves and integrating it, OVH is doing that already. Right out of the gate, in a hosted managed environment. >> That's because it is a like to like homogeneous, and you guys have laid that vision out years ago. >> Yep, yep. >> We sure did. >> When Maritz was running the company. But how does that actually manifest itself? So, a customer says, look, I'm sick of the heavy lifting, I want to get to the cloud. Alright, so they come to you guys, what are the steps that they take to get there? >> Well, there's, you know, the first thing you'll do is you'll sit down with the client. And some clients know exactly what they want to do and how they want to do it. And some customers say, hey, I think I need to be in the cloud, please help me. So we'll have that conversation, right, first of all. Yeah, exactly, it's from A to Z, soup to nuts, whatever you want to say. So, you know, a lot times we'll sit down and we'll walk them through that journey to the cloud. And then, once we determine what applications or workloads we want to move, then we'll back into, okay, well here's the best way to move that, right, and whatever technologies we then decide to do. And if it's vSphere based, it makes it real simple, right? >> And you hit the nail on the head. It starts with the application. It's always about the application. What is the end goal? Right, once you identify that, you start looking at the use cases, a lot of it's app migration, a lot of data center evacuation. A lot of these data centers, as the different leases are coming up, they want to get out of there. Right, and that's the opportunity to then have the discussion. There's also tools that we got. HDX, which allows for bulk migration of workloads and it reduces, you know, the complexity of going to another cloud and another hypervisor from, like, years down to months and weeks. We've had some customers that have done that, migrated hundreds of VMs over a weekend. >> Oh sure. And we're in the process of that right now. >> So, go ahead, please. >> Oh, thank you, I was going to say, could you give us an example of a customer, whether they're in Europe, where you guys have really had a lot success, or here in the Americas, that have really demonstrated substantial business outcomes, revenue, et cetera, leveraging the joint service? >> Well, sure, I mean, you know, we've got customers both in the U.S. and in EMEA, but, you know, I'm thinking about a customer in particular that's based in the U.K.. That, they're a MNA company, right? And, at one time, they had 97 data centers that they were trying to manage. The complexity of that. And, so, they originally went to vCloud Air because they were like, help us with this complexity, we're built on VMware, but we've got to close these data centers, right, we need to go to more of an asset-like model, and we need to be able to manage it effectively with the staff that I have that's already overworked. So that's how we won them as a client with vCloud Air. What's exciting is, is when we come in and we start talking about what we're doing with OVH, and some of the new technology that we're building, on the VMware stack, right, plus the fact that we own our own network. I don't charge ingress and egress charges, right. A lot of the things that we do, We've got 33 points of presence, you know, globally. Then we start having a conversation and they're like, listen I already had a great solution in vCloud Air on VMware, now I've got that on steroids. I've got the benefit of both companies coming together for a solution for my client. >> So how do you get the data from point A to point B? Do you back up the Chevy truck and load it on? >> You can do it that way. >> You talked about your network. What's the kind of best practice? >> Yeah, so the best practice is to come in and understand the actual environment we're working with. What is the tolerance to take that workload up or down? But, if we use technology like HDX, I don't have to take that workload down at all. I'm able to basically, essentially, and don't let me get over my skis, VMware guy, but I am going to essentially do a Vmotion over my network, right, no cost to the customer, into my data center, and the customer can continue to use the app while that's happening. >> And the time that takes is a function of, obviously, the volume of the data, >> Sure, of course. The bandwidth. >> The number of VMs, the complexity of that. >> So you'll schedule that out over a period of, what, days, weeks, months? >> Exactly Years, even, I mean, maybe not years but, maybe I have a multi-year strategy, right? So that's how you're seeing people do it? It's sort of a planned approach. >> Weeks and months is sort of. >> I would say, typically. >> It's project based, yeah. >> So, within months, I can get an entire data center from my on-premises into your platform. Is that a fair statement? >> And if you ever wanted to bring it back, we can do that real easy too. >> You see that happening? >> We see customers moving workloads back and forth, it depends on seasonality. I mean, you take the retail industry, right? There's a lot of times where, during the retail industry, they'll send things to us, they'll flip it around, and, after the holidays are over, they'll bring there on-prem or what have you. >> And, more importantly, I think having network access back into the on-prem data center, with HDX, allows you to have a network connection. So it does need a talk back. The whole workload may not move back, but you need to have communications back into the network. And that's what HDX, their technology, allows. >> Right. >> So it allows me to leave whatever component of my workload I want to keep there. >> Yep, that's right. >> When I'm talking to each other. >> That's right. >> Okay, so for years at VMware, we heard this theme, any app, any workload, really anywhere in the world. >> Exactly. >> Now, you guys, right, you guys have an open source based public cloud. Vmware, obviously, like, hey, some of these cloud native apps, we'd like a piece of that action. You hear Pat talking about Kubernetes and containers. So what's that conversation like, between you guys, I mean you want some of that, right? Are you talking about Edge? Is that more integration? You guys got some work to do there to really compete in the that space? >> Well, I mean, it's your solution. But I'll start off of on the Edge. So, the announcement on Edge today, I don't know if you guys have heard it yet, but really exciting. We've actually announced a lot of different solutions around automation of the data center. I mean, this whole cloud operations is becoming sort of a major problem, as we have eight to 10 global service providers in most enterprises. So, reducing the complexity of that down is incredibly important. All the pieces that we're announcing, a VMware as a service, we're going to roll to our service providers in a managed service environment. So all these new technologies that we just announced, right, David and OVH are going to get access to that and have the same capability. >> That's right. >> I'll let you guys speak, specifically on your OpenStack. >> Well, I mean, listen, the beautiful thing about OpenStack is it's open, right, so, I mean, it doesn't really matter what cloud's out there, we can interface with it, right? So, that's the beauty of it, right? And it doesn't change at all the way that we go to market. It's just, really, we're giving the customers choice. What do you want? And it depends on the app, right? That's what's beautiful about it, is when we've sit down and meet with customers or partners, it's, like, what do you want to do, what workload would you want to move? And we've got choice for you. >> Yeah, I remember when we talked to Pat about this, years ago, when OpenStack was kind of the hot new toy, and he said, OpenStack, we like OpenStack, that's cool, we'll embrace it, no problem, and we're like, really? Yeah, I mean, that's kind of exactly what's happened. I mean, you're seeing the same thing with Kubernetes, and containers, and the like. But, again, you guys still got some work to do to really earn their business for those types of workloads, and I presume you're hard at work. >> We are. I don't know if you wanted to hit on some of the announcements that you. >> Yeah, I'd love to. >> Yeah, let's do that. >> So, the real thing I'm excited about is this morning we announced the announcement of our partner program at OVHcloud. It's an exciting day for us on that because, if you'll remember a few minutes ago, I was talking about all of the things we've been doing for the last year, right, getting our data centers ready, and, also, building out our product stack to be able to go to market, and migrating our customers. Well, the fourth thing we were doing, for the last nine to 12 months, is we've been meeting with partners. And I'm fortunate, from my years at EMC-Vmware, and my team, we have a lot of relationships out there. And so we were able to go meet with these partners and say, listen, here's what we're thinking, what do you guys think, what are you looking for, right? We've got all these big players out there, obviously we know all the names, but what differentiation could we bring to your business to help you go grow revenue? And, you know, they came back to us and they said, Wiggs, what we really want to be able to do is we want to be able to come in slowly, expand that as much as we can, make big commitments, make small commitments, we want the ability to be agile, we want to be able to, help us figure out a way that we can save money and worry about that. Help us resolve that issue of that margin erosion. That's a big thing that a lot of the channel's dealing with today. And, so, that's what we did. We came up with a program of four different levels, right? You can dip your toe in, and with a very minimum commitment, the higher commitment you make, not only do you get a better price, but you also get a ton of support on the backend. So, I actually come in and work with you on your messaging. I have sales teams that can actually go out and help them sell the solution, with us as the infrastructure layer in the underpinning, right, and, so far, it's been really good. >> So these are, don't hate me for saying this, these are sort of traditional box sellers, now trying to transform their business, right, and add more value, or their value added supply. Maybe they're SAP. >> Well, you've got manage service providers. You've got manage service providers. >> Okay, so hosting. >> You've got the SI's and the OS's, right? So, you know, some of these guys they either want a private label, right? Or white label your solution? Some guys just want to go to mark up their solution and they just need an asset like model, right? They're just exhausted with, you know, investing in infrastructure, right? So, they're like, "Listen >> And bodies. >> And body, you take that over and let us worry about that. >> You see, from VMware's perspective, that's exactly what we're seeing. We've got an ecosystem of 42 hundred global service providers. They build their own data centers, have a VMwares based hosted solution of some type. A lot of different flavors. They want to get out of the hardware space and out of the data center management space. This is why it's a great solution for OVH, they want to focus on, and, again, we call this asset light, they want to focus on high margin trusted value. Things that they're good at, where they can make a lot of money. >> Which is what? Like, I always see there's a consulting piece up front, security. >> It could be security specialist. >> Yep, security security services. >> Patching monitor, you know, automation, migration services, I mean, the exact discussion we just talked about, right? Customers need that journey. So OVH abstracts a way, the need to do hardware, and that allows them to go focus on the rich or higher margin services that they offer. >> And how are they making it sticky? Because, obviously, they want that, right? So what do you see there and how are you helping them? >> I think anytime you're adding a value added service, if you add that value it is sticky, right? >> Yeah. >> I mean, for an example, to help our relationship with Vmware, and just how strong it is, you know, FusionStormers was one of the partners that we had announced today, right? And they had a quote in there. And I was just sitting in Pat's keynote, next to our customer. You know, and I'm like, so, you know, I get this, it makes sense, you're looking for this, you know, infrastructure as a service play. He's like, David, what we're trying to do is help our customers that love the VMware stack, we're trying to help them to get to the Cloud, right? They don't care about the infrastructure, all they want is great service, right, and great support. And he said, that's my secret sauce, that I am able to offer that. And he goes, you guys handle the infrastructure. He said, it's perfect. >> Last question, David, for you. What are people going to be able to see and feel and touch at the OVH booth here at VMWorld? >> Oh, that's a great question. So, you're going to be able to go over, and you're going to be able to learn about some of our other announcements, with VMwares. Specifically, around what we're doing on the whole SCDC as a stack, right? In the VMware Cloud foundation, and the announcement we had on that this morning. Or, actually, I think that was Friday. You're actually going to be able to go over and they'll pull up and they'll show you some demos, and be able to see the technology live. I think they have a show every hour, and you go over there. And if you go over, you might win a Yeti mug. I think they're giving a Yeti mug to whoever pays the most attention. (Lisa and Dave ooh) So, go over there and learn about that. >> Can always use another Yeti, yeah, I love the Yeti. >> Yeah >> You can't have too many Yeti's. >> Does it come with caffeine? Because that, I'm all over it. >> No, well, we'll leave it clean, yes, maybe caffeine. >> Okay, awesome. David, Geoff, thanks so much for joining Dave and me this morning. >> Thank you so much, we really enjoyed it. >> You're watching theCUBE, live from VMWorld 2018. Day one, Lisa Martin for Dave Vellante, stick around, we'll be right back. (electronic music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering IBM Think 2018. Brought to you by IBM. >> Welcome back to theCUBE. We are live at the inaugural IBM Think 2018 event. I'm Lisa Martin with Dave Vellante. And our first guest, on day one of our coverage, is Jerry Thompson, the Chief Revenue Officer of Identity Guard. Hey Jerry, welcome to theCUBE. >> Thank you, well, it's a pleasure to be here. >> So tell us about Identity Guard. What are you guys, what do you do and how are you working with IBM? >> Yeah, Identity Guard is a, is a subsidiary of Intersections. We are a publicly-traded company and we're only in the identity and privacy space. So we, today, protect about 1.4 million people's identities. They, it's a subscription-based service. And two and a half years ago, we made the decision to, to basically invent identity 2.0 and the only way to do that was to use artificial intelligence technology, so we went to Watson to do that. >> This is a giant leap that you mentioned. >> Huge. >> So let's kind of, maybe, break that down a little bit and really talk about what you're doing here that was really transformative. >> Yeah, so, identity protection companies today only look at structured data. And, basically, we look at structured data and we look at it in arrears, so we can't do anything proactive or preventive. We knew if we used Watson in an AI technology, we could monitor unstructured data, which is probably 90% of all the data out there about any of us. And in order, in doing so, we could do preventive and predictive analysis of your personal information, privacy and your identity. So there was a quantum leap to go from just reacting to actually proactively protecting people's identity and privacy. >> So could you take us through, sort of, the journey that you went on to go from, sort of, where you were to where you are now and where you're headed? >> Yeah so, I mean, it starts like every other company with Watson. We took the tour of the Watson building. Went upstairs to the glass conference rooms and in that conference room, waiting for us, was the CIO of Watson. >> Dave: When was this? >> Two and a half years ago. >> Okay. >> And we explained the problem we were trying to solve. And from that day forward, IBM has been an amazing partner for us, amazing partner. So we did all of the things. We went through a Scrum, we wrote some product code, we did, you know, proof of concept, and when we were convinced that we could actually reinvent this industry, we went all-in. >> Keep going. >> And that was two and a half years ago. >> So, so, so a lot of people would say "Okay, Watson's a heavy lift, "you got to have a lot of services." It sounds like you did but the outcome is really what you're driving toward. So what was the outcome you were looking for and what'd you have to do to get there? >> Yeah so, I mean, at the highest level, we wanted to protect not only your financial and credit data, but all of the data that's out there about you and your partner, spouse, wife and kids. And in order to do that you need a processing engine that actually is intelligent. So that was the journey in Watson. We have found it to be not a big, heavy lift. We had the right kind of data scientists and we knew the problems we were trying to solve. Not in the abstract, in the particular. We defined the stories and the categories that we wanted to play in. We defined the product as we wanted to launch it. We knew it was going to be a one to two year run because you have to invent it, create it, then you have to play with it, right? You have to run it through the machine, so, >> Iterate. >> Right, and iterate. So, in order to do that, we knew the timeframe so we were never frustrated. And, along that journey, we came up with other things that we thought would be amazing to include in the service so, like cyberbullying technology, geolocation technology. All kinds of other things where only Watson would help us do that. >> And, and the data scientists were on your team >> Our team, yeah. or IBM brought those to the table? Okay, so you >> Yeah, no, IBM always let us reference their, but we have a handful in Virginia and some more in California in our development center. >> So you're one of the lucky ones who had a team, a bench, of data scientists >> Yes. >> at your disposal to go, is that right? >> Yeah, I wouldn't say a deep bench, but we've added to it over time, as you, as you get into the way you want to solve this problem. >> And, and how, specifically, are you using Watson? Can you give us, add some color on the APIs that you're using >> Sure. >> and how you're applying them? >> So we use natural-language processing because we pour amazing amount of data through the Watson funnel. Social media data, geolocation, Alchemy News. And we need the natural-language to actually jump and, and search for key words and key intimates. We use emotion analysis API, sentiment analysis API for context. So we're reading social media posts, your kids' posts. Your kid might say "Boy, I killed it "on the soccer field today." That's not a threat, right, that's just a statement. You have to add context to the statement. In order to do that, we use emotion and sentiment APIs. We use visual image recognition for inappropriate things that might be coming through. We use Alchemy News, which I believe is Discovery today. We're in the process, with the help of IBM, to create a library, a language, around emojis. Some emojis can be very threatening in the way they're used and the context they're used. You have to be able to read it, intelligently read it, and then put it in context to the string of texts or Instagram posts or whatever, that are going back and forth. So we, we've really taken this holistic view of what Watson can do, help us do for unstructured data and, in that process, it made our ability to monitor structured data better. We learned a lot. So we actually got benefits on both sides of our business. >> So you talked about this quantum leap that, that you made to identity 2.0. Also, what you're doing, in your space is quite pioneering in that, you're >> Yes. >> the only, first and only company, in the space that's using AI. Cyberbullying is such a hot, very challenging topic and, and sadly one that's very much needed in terms of identity. >> Right. >> But why do you think it is that, that Identity Guard is, is so pioneering in this space? >> Yeah, you know, we've always been, we, first of all, Identity Guard invented the identity business 23 years ago. We're the first ones to ever do it, first ones to do credit scores, reports. So we've always innovated in this space. The, the challenge for us as a public company, our biggest competitor is the credit bureaus, right? And the credit bureaus are low-cost providers and, and, candidly, I think they stamp out innovation in our field because they just want it to be about credit data. They don't want it to be about other things. So it was time for somebody to take this leap to predictive and preventive technologies, not just reactive. The rear view mirror can tell you a lot but it can't help you protect today, and that's what we've been doing in our space. >> Well the dossier from a credit bureau is so limited. >> Right. >> It doesn't provide context. You know, your score goes up or down for weird reasons. 'Cause people are doing credit pulls or whatever it is. You don't really have a context of what's going on there. So, so my question to you, Jerry, is where do you see innovation going in this space? Obviously data is involved and the credit bureaus have data but where is innovation going to come from in the next five to 10 years? >> Yeah, you know, I think it's the, we're going to figure out how to harvest data that's out there and then score that data so that we can help you and your family stay safe. Nobody today wants to have no internet, right? The internet's opened up an amazing amount of capability for people. But, but you have to have a way to play in it without it being too dangerous. And I believe we can use Watson. That's our, it's been our theory from day one. We can use Watson to level the playing field, right? Not, not really get an advantage, but to level the playing field, especially for families where not everybody is aware of all of the malfeasance that's out there on the internet, right? >> Right. >> People are always looking to harvest our data and to use it in a malicious way. Especially kids and minors, right? They're at risk for cyber, you know, predation and stalking and cyberbullying and, and parents today know it's a big issue. >> Okay, go ahead please Lisa. >> I was just going to say, in terms of expectations, you're saying it's to level the playing field with the cyber criminals, the stalkers, in the next, you know, can we look at timeframe? Think that you'll get ahead of that to start actually preventing some of this cyberbullying going on? >> You know, I, that's a good question. I will tell you right now, our ambition is to level the playing field. It's tilted this way today. I think what will happen is technology's like geolocation. It seems, first of all geolocation is not really relevant without Watson Discovery, right? You need all of this massive data going on in the locations that you're relevant in to help us protect you. But I believe, based on the early science that we're doing with IBM, that we can actually help a kid, somebody's stalking them from, you know, four states away but it says it's the little boy across town, we can actually stop things like that happening using the processing and the algorithms that we're doing using Watson. So there are, there are relevant areas that I think we can have a massive impact on the privacy and the protection of people and their families. >> I want to come back to innovation, so data is clearly a key component of that. You're extending the data model into unstructured data. I'm hearing that, correct? >> Yes. >> Also, AI, machine intelligence is another part of that. What about scale? Scale and network effects >> Yeah. >> and that sort of component of innovation. >> That had to be >> Does that come from cloud, is that where it's coming from? >> That had to be part of this. So we, along with all of our competitors in the existing 1.0 business, we use a hard-coded platform. >> Right. >> Right, I mean, if you want to change something, you have to get out a sledgehammer and a chisel and it takes a year. We built Watson using AWS, so we've used all the best tools, the fastest tools. We've run scale testing, you know, and, and the beautiful thing about our business, we're a digital business, right, so our factory's open 24 hours a day, 365 days a year. Our shopping carts never close. You can always, you know, subscribe to the Identity Guard With Watson service. So we needed the cloud to give us the scale. We also needed the platform to be able to plug in and unplug the APIs. Some partners may not want social media monitoring. Some partners may not want this, so we didn't have to hard-code our product. We actually built three services and we can unplug any of the services. >> So, when you say you're a digital business, it strikes me that your data model is not in a bunch of silos. >> Correct. >> You've got a data model that's accessible, maybe through sets of APIs, et cetera, that your human experts can go attack. >> Correct. >> Is that a fair assertion? >> Yeah, that's fair. One other thing about Watson. We were going to use Watson from day one, I was convinced. And I was the one that took the company on this journey. But the other thing I like about Watson is that you don't, Watson doesn't keep the data, right? We talked to the other big players in this field and one of their mandates is, they always keep the data. All of it. And, and Watson shreds the data and we don't keep all the data. So think of all the social media and other data that flows through this funnel. People out there want to keep it so then they can reverse profile consumers or cohorts or, Watson shreds the data. You're not in the, you're not in the spoofing or spying business, nor are we. So that was also a really important consideration. >> Yeah, I said that at the top, that you're, you're going to hear this from Ginni tomorrow. I can almost guarantee ya, she's going to say that we're not in the business of trying to re-mine your data and re-target. >> Right. >> But, so that was, I was going to ask you why Watson. That was one reason. What about the quality of the, of the machine intelligence? >> Yeah. >> You hear a lot, you know, you hang around Silicon Valley, "Oh yeah, Watson." How does it compare, in your view? >> Yeah. >> You're a practitioner who's, you know, you're familiar with all this. >> So they have more refined, first of all, more APIs, right? More, some of them not relevant to us, the medical ones, which are amazing and fascinating, >> Yeah, but, yeah. >> but they had more structured APIs and a better road map on where they were going. And what we found from day one is that, if we defined something, they would say "We'll jump in and help", right? It's really important when you're the first one, you know, the tip of the spear, you don't know, you don't know what you don't know. And we found from day one, the IBM team has treated us like we're General Electric, right? Or General Motors, right? We're just, you know, a couple of hundred million dollar company trying to make a big difference in a important space. And they have treated us like a Fortune 100 company from day one and really appreciate it. >> So as >> And their science is so good. >> Sorry there, as the CRO, going from identity 1.0 to 2.0, this journey that you're on. You mentioned competition. How many, talk to us about the actual financial impact to the company that you can say that you've been able to achieve on this journey to identity 2.0. Presumably, leaving some of your competition back in the 1.0 land. >> Yeah, yeah, actually, our competition will be behind us for at least a couple years 'cause it takes a couple years. You know, you don't do this quickly. So we are out, we launched, we launched Watson in December. We actually launched, we distribute our product through partners, most of it, 90%. 10%, people come to our site and sign up online but we launched 21 partners in January, 11 in February, 13 in March we'll launch. So by the end of the year, we predict we'll have about 200 Watson partners distributing our product, which would give us a huge head start and advantage over anybody else. Once you see what we're doing and you see what else, the 1.0 version, it's almost impossible to pick 1.0. It's impossible, right? So our job is to get more, create more awareness in the distribution channels so that people are, are understand that Watson is out there and available. >> And, and this is a subscription service, I think you said, upfront? >> Yeah. >> And you've got different tiers, etc? >> Yes, yes. >> And you guys have a couple of, of sessions >> that you're participating in at the event? >> We do. >> Yeah, I know that we're on tomorrow afternoon and I believe Wednesday morning. >> Great. >> So, yeah. >> Well Jerry, thanks so much for stopping by theCUBE >> You're welcome. >> and sharing what you guys at Identity Guard are doing with data, >> Thank you. >> I mean, it's fascinating. >> Appreciate you talking to us. >> Dave: Thanks for coming on. >> Yeah, thanks, pleasure. >> And we want to thank you for watching theCUBE. I'm Lisa Martin with Dave Vellante again. This is day one of theCUBE's three days of coverage at the inaugural IBM Think 2018. Stick around, we'll be right back with our next guest after a short break. (bright music)