(upbeat techno music) >> Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions, and they were largely confined to regulated industries that had to comply with public policy mandates. But as the cloud went mainstream the tech giants showed us how valuable data could become, and the value proposition for data quality and trust, it evolved from primarily a compliance driven issue, to becoming a linchpin of competitive advantage. But, data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper-specialized skills, to develop data architectures and processes, to serve the myriad data needs of organizations. And it resulted in a lot of frustration, with data initiatives for most organizations, that didn't have the resources of the cloud guys and the social media giants, to really attack their data problems and turn data into gold. This is why today, for example, there's quite a bit of momentum to re-thinking monolithic data architectures. You see, you hear about initiatives like Data Mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business users. You hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver, like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that but also, how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. In other words, while it's enticing to experiment, and run fast and loose with data initiatives, kind of like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated and intelligent. Governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is going to use data that is entrusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. Hello and welcome to theCUBE's coverage of Data Citizens made possible by Collibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Vellante and I'm one of the hosts of our program which is running in parallel to Data Citizens. Now at theCUBE we like to say we extract the signal from the noise, and over the next couple of days we're going to feature some of the themes from the keynote speakers at Data Citizens, and we'll hear from several of the executives. Felix Van de Maele, who is the co-founder and CEO of Collibra, will join us. Along with one of the other founders of Collibra, Stan Christiaens, who's going to join my colleague Lisa Martin. I'm going to also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Haslbeck. He's the Vice President of Data Quality at Collibra. He's an amazingly smart dude who founded Owl DQ, a company that he sold to Collibra last year. Now, many companies they didn't make it through the Hadoop era, you know they missed the industry waves and they became driftwood. Collibra, on the other hand, has evolved its business, they've leveraged the cloud, expanded its product portfolio and leaned in heavily to some major partnerships with cloud providers as well as receiving a strategic investment from Snowflake, earlier this year. So, it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. (upbeat rock music) Last year theCUBE covered Data Citizens, Collibra's customer event, and the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know starting with the Hadoop movement, we had Data lakes, we had Spark, the ascendancy of programming languages like Python, the introduction of frameworks like Tensorflow, the rise of AI, Low Code, No Code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives, and we said at the time, you know maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation. Meaning, making it easier for domain experts to both gain insights from data, trust the data, and begin to use that data in new ways, fueling data products, monetization, and insights. Data Citizens 2022 is back and we're pleased to have Felix Van de Maele who is the founder and CEO of Collibra. He's on theCUBE. We're excited to have you Felix. Good to see you again. >> Likewise Dave. Thanks for having me again. >> You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it why data intelligence is more important now than ever, and get current on what Collibra has been up to over the past year, and what's changed since Data citizens 2021, and we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends and we're not just snapping back to the 2010s, that's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s, from the previous decade, and what challenges does that bring for your customers? >> Yeah, absolutely, and and I think you said it well, Dave and the intro that, that rising complexity and fragmentation, in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use, has only gotten more more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under, respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity, and fragmentation. So, it's become much more acute. And to your earlier point, we do live in a different world and and the past couple of years we could probably just kind of brute force it, right? We could focus on, on the top line, there was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, how do we truly get the value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale with data, not just from a a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? You said at the, the people and process, how do we do that at scale? And that's only, only, only becoming much more important, and we do believe that the, the economic environment that we find ourselves in today is going to be catalyst for organizations to really take that more seriously if, if, if you will, than they maybe have in the have in the past. >> You know, I don't know when you guys founded Collibra, if you had a sense as to how complicated it was going to get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >> Yeah, absolutely. We, we started Collibra in 2008. So, in some sense and the, the last kind of financial crisis and that was really the, the start of Collibra, where we found product market fit, working with large financial institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis. And kind of here we are again, in a very different environment of course 15 years, almost 15 years later, but data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So, what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it Data Citizens, we truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we still relatively early in that, in that journey. >> Well that's interesting, because you know, in my observation it takes 7 to 10 years to actually build a company, and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your current momentum? >> Yeah, absolutely. Again, there's a lot of tailwind organizations that are only maturing their data practices and we've seen that kind of transform or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world with its Adobe, Heineken, Bank of America and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in the, in the market with some of the cloud partners like Google, Amazon, Snowflake, Data Breaks, and and others, right? As those kind of new modern data infrastructures, modern data architectures, are definitely all moving to the cloud. A great opportunity for us, our partners, and of course our customers, to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course data quality isn't new but I think there's a lot of reasons why we're so excited about quality and observability now. One, is around leveraging AI machine learning again to drive more automation. And a second is that those data pipelines, that are now being created in the cloud, in these modern data architecture, architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously, has become absolutely critical so that they're really excited about, about that as well. And on the organizational side, I'm sure you've heard the term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believed in. Federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations, and so that aligns really well with our vision and from a product perspective, we've seen a lot of momentum with our customers there as well. >> Yeah, you know, a couple things there. I mean, the acquisition of OwlDQ, you know Kirk Haslbeck and, and their team. It's interesting, you know the whole data quality used to be this back office function and and really confined to highly regulated industries. It's come to the front office, it's top of mind for Chief Data Officers. Data mesh, you mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So, let's chat a little bit about the, the products. We're going to go deeper into products later on, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes, as you talked about earlier. Tell us a little bit about what you're introducing. >> Yeah, absolutely. We we're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission. Either customers are still start, are just starting on that, on that journey. We want to make it as easy as possible for the, for organization to actually get started, because we know that's important that they do. And for our organization and customers, that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again to make it easier for, really to, to accomplish that mission and vision around that Data Citizen, that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then, how do we make sure that, as clear becomes this kind of mission critical enterprise platform, from a security performance, architecture scale supportability, that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme. From an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One, is around data marketplace. Again, a lot of our customers have plans in that direction, How to make it easy? How do we make How do we make available to true kind of shopping experience? So that anybody in the organization can, in a very easy search first way, find the right data product, find the right dataset, that they can then consume. Usage analytics, how do you, how do we help organizations drive adoption? Tell them where they're working really well and where they have opportunities. Homepages again to, to make things easy for, for people, for anyone in your organization, to kind of get started with Collibra. You mentioned Workflow Designer, again, we have a very powerful enterprise platform, one of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a, a new Low-Code, No-Code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around Collibra protect, which in partnership with Snowflake, which has been a strategic investor in Collibra, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PIA data, is managed as a much more effective, effective rate. Really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily, and quickly, and widely as we can? Moving that to the cloud has been a big part of our strategy. So, we launch our data quality cloud product, as well as making use of those, those native compute capabilities and platforms, like Snowflake, Databricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down, so we're actually pushing down the computer and data quality, to monitoring into the underlying platform, which again from a scale performance and ease of use perspective, is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical, and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So that's a lot coming out, the team has been work, at work really hard, and we are really really excited about what we are coming, what we're bringing to market. >> Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you you talked about, you know, the marketplace, you know you think about Data Mesh, you think of data as product, one of the key principles, you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been, been so hard. So, how do you see sort of the future and, you know give us the, your closing thoughts please? >> Yeah, absolutely. And, and I think we we're really at a pivotal moment and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not going to fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to, deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can, as kind of our, as our mission. And so I'm really, really excited to see what we, what we are going to, how the marks are going to evolve over the next, next few quarters and years. I think the trend is clearly there. We talked about Data Mesh, this kind of federated approach focus on data products, is just another signal that we believe, that a lot of our organization are now at the time, they're understanding need to go beyond just the technology. I really, really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now is the time, given the economic environment that we are in, much more focus on control, much more focus on productivity, efficiency, and now is the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >> Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much. Good luck in, in San Diego. I know you're going to crush it out there. >> Thank you Dave. >> Yeah, it's a great spot for an in-person event and and of course the content post-event is going to be available at collibra.com and you can of course catch theCUBE coverage at theCUBE.net and all the news at siliconangle.com. This is Dave Vellante for theCUBE, your leader in enterprise and emerging tech coverage. (upbeat techno music)

(upbeat music) >> Last year, the Cube covered Data Citizens, Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hadoop movement. We had data lakes, we had Spark, the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of AI, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights from data, trust the data, and begin to use that data in new ways, fueling data products, monetization, and insights. Data Citizens 2022 is back, and we're pleased to have Felix Van de Maele, who is the founder and CEO of Collibra. He's on the Cube. We're excited to have you, Felix. Good to see you again. >> Likewise Dave. Thanks for having me again. >> You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever, and get current on what Collibra has been up to over the past year, and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear. And that's really true, as well, in the world of data. So what's different in your mind in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >> Yeah, absolutely. And I think you said it well, Dave, in the intro that rising complexity and fragmentation in the broader data landscape that hasn't gotten any better over the last couple of years. When we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use, has only gotten kind of more difficult. So that trend is continuing. I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under with respect to data, as data becomes more mission critical, as data becomes more impactful and important, the level of scrutiny with respect to privacy, security, regulatory compliance, is only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. So it's become much more acute. And to your earlier point, we do live in a different world, and the past couple of years, we could probably just kind of brute force it, right? We could focus on the top line. There was enough kind of investments to be had. I think nowadays organizations are focused, or are in a very different environment where there's much more focus on cost control, productivity, efficiency. How do we truly get value from that data? So again, I think it's just another incentive for organizations to now truly look at that data and to scale that data, not just from a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? Like you said, the people and process, how do we do that at scale? And that's only becoming much more important. And we do believe that the economic environment that we find ourselves in today is going to be a catalyst for organizations to really take that more seriously if you will than they maybe have in the past. >> You know, I don't know when you guys founded Collibra, if you had a sense as to how complicated it was going to get, but you've been on a mission to really address these problems from the beginning. How would you describe your mission, and what are you doing to address these challenges? >> Yeah, absolutely. We started Collibra in 2008. So in some sense in the last kind of financial crisis. And that was really the start of Collibra, where we found product market fit working with large financial institutions to help them cope with the increasing compliance requirements that they were faced with because of the financial crisis, and kind of here we are again in a very different environment of course, 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case, and across every source, frankly has only become more important. So while it's been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to, again, be able to provide everyone, and that's why we call it Data Citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy manner. That mission is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we're still relatively early in that journey. >> Well, that's interesting because, you know, in my observation, it takes seven to 10 years to actually build a company, and then the fact that you're still in the early days is kind of interesting. I mean, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your your current momentum? >> Yeah, absolutely. Again, there's a lot of tailwinds, organizations are only maturing their data practices, and we've seen it kind of transform, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world, whether it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the market with some of the cloud partners like Google, Amazon, Snowflake, Databricks, and others, right? As those kind of new modern data infrastructures, modern data architectures, are definitely all moving to the cloud. A great opportunity for us, our partners, and of course our customers, to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging AI, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical. So we're really excited about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believed in. Federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale the data organizations, and so that aligns really well with our vision, and from a product perspective, we've seen a lot of momentum with our customers there as well. >> Yeah, you know, a couple things there. I mean, the acquisition of OwlDQ, you know, Kirk Haslbeck and their team, it's interesting, you know, the whole data quality used to be this back office function and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh, you mentioned. You guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're a critical part of many ecosystems, and you're developing your own ecosystem. So let's chat a little bit about the products. We're going to go deeper into products later on at Data Citizens '22, but we know you're debuting some new innovations, you know, whether it's, you know, the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >> Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme, and like I said, we're still relatively early in this journey towards kind of that mission of data intelligence, that really bold and compelling mission. Either customers are just starting on that journey, and we want to make it as easy as possible for the organization to actually get started, because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for, really to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then, how do we make sure that as Collibra becomes this kind of mission critical enterprise platform from a security performance architecture scale, supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme. From an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction. How do we make it easy? How do we make available a true kind of shopping experience so that anybody in your organization can, in a very easy search first way, find the right data product, find the right data set that data can then consume, use its analytics. How do we help organizations drive adoption, tell them where they're working really well, and where they have opportunities. Home pages, again, to make things easy for people, for anyone in your organization, to kind of get started with Collibra. You mentioned workflow designer, again, we have a very powerful enterprise platform. One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code, kind of workflow designer experience. So really customers can take it to the next level. There's a lot more new product around Collibra Protect, which in partnership with Snowflake, which has been a strategic investor in Collibra, focused on how do we make access governance easier? How do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data, is managed in a much more effective way. Really excited about that product. There's more around data quality. Again, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. So we launched our data quality cloud product as well as making use of those native compute capabilities in platforms like Snowflake, Databricks, Google, Amazon, and others. And so we are bettering a capability that we call push down. So we're actually pushing down the computer and data quality, the monitoring, into the underlying platform, which again, from a scale performance and ease of use perspective is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations that we talk about, being able to connect to every source. Integrations are absolutely critical, and we're really excited to deliver new integrations with Snowflake, Azure, and Google Cloud Storage as well. So there's a lot coming out. The team has been at work really hard, and we are really, really excited about what we are coming, what we're bringing to markets. >> Yeah, a lot going on there. I wonder if you could give us your closing thoughts. I mean, you talked about the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles. You think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard, so how do you see sort of the future? And, you know, give us your closing thoughts please. >> Yeah, absolutely. And I think we're really at this pivotal moment, and I think you said it well. We all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not going to fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, the data intelligence platform. We are still early, making it as easy as we can. It's kind of our, as our mission. And so I'm really, really excited to see what we are going to, how the markets are going to evolve over the next few quarters and years. I think the trend is clearly there, when we talk about data mesh, this kind of federated approach, focus on data products is just another signal that we believe that a lot of our organizations are now at the time, they understand the need to go beyond just the technology, how to really, really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now's the time given the economic environment that we are in, much more focus on control, much more focus on productivity, efficiency, and now's the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >> Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much, and good luck in San Diego. I know you're going to crush it out there. >> Thank you Dave. >> Yeah, it's a great spot for an in person event, and of course, the content post event is going to be available at collibra.com, and you can of course catch the Cube coverage at thecube.net, and all the news at siliconangle.com. This is Dave Vellante for the Cube, your leader in enterprise and emerging tech coverage. (light music)

(light upbeat music) (mouse clicks) >> Hey, everyone. Welcome back to the program. Lisa Martin here. I've got two guests joining me. Please welcome back to The Cube, Paula Hansen, the chief revenue officer and president at Alteryx. And Jacqui Van der Leij - Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the program. >> Thank you, Lisa. >> Thank you, Lisa. >> It's great to be here. >> Yeah, Paula. We're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation. With analytics as they talked about at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform but ultimately, we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >> Excellent. Sounds like a very strategic program. We're going to unpack that. Jacqui let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How, Jacqui, did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is just when we started out was, is that, you know, our, especially in finance they became spreadsheet professionals, instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no, we're not independent. You couldn't move forward. You would've been dependent on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. And finally, we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks because you always have, not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's our people that need to actually really embrace it and making that accessible for them, I would say is definitely not per se, a roadblock but basically some, a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula will start with you, and then Jacqui will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven? Paula? >> Yes. Well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting, all of our key performance metrics for business planning across our audit function to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter so it's really remained across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases. And so one of the other things that we've seen many companies do is to gamify that process to build a game that brings users into the experience for training and to work with each other, to problem solve, and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of you know, getting people excited about it but it's also understanding that this is a journey. And everybody is the different place in their journey. You have folks that's already really advanced who has done this every day, and then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the initial destination. I say initially, because I believe the journey is never really complete. What we have done is that we decided to invest in a... We build a proof of concepts and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom. And we told people, "Listen, we're going to teach you this tool, super easy. And let's just see what you can do." We ended up having 70 entries. We had only three weeks. So, and these are people that has... They do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon. From the 70 entries with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was people had a proof of concept, they knew that it worked, and they overcame that initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula will start with you. >> Absolutely. And Jacqui says it so well, which is that it really is a journey that organizations are on. And we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay, and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED, we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED just made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kicked that momentum from the hackathon. Like we don't lose that excitement, right? So we just launched a program called eBay Masterminds. And what it basically is, it's an inclusive innovation initiative, where we firmly believe that innovation is for upscaling for all analytics role. So it doesn't matter your background, doesn't matter which function you are in, come and participate in this, where we really focus on innovation, introducing new technologies and upscaling our people. We are... Apart from that, we also said... Well, we should just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter Alteryx. And we're working with actually, we're working with SparkED and they're helping us develop that program. And we really hope that, let us say, by the end of the year have a pilot and then also next, was hoping to roll it out in multiple locations, in multiple countries, and really, really focus on that whole concept of analytics role. >> Analytics role, sounds like Alteryx and eBay have a great synergistic relationship there, that is jointly aimed at, especially, kind of, going down the stuff and getting people when they're younger interested and understanding how they can be empowered with data across any industry. Paula let's go back to you. You were recently on The Cube's Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world? How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last, I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. (Paula clears throat) So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud, is to empower all of those people in every job function regardless of their skillset. As Jacqui pointed out from people that would, you know are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud and it operates in a multi-cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skills gap as you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues. And what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we started about getting excited about things when it comes to analytics, I can go on all day but I'll keep it short and sweet for you. I do think we are on the topic full of data scientists. And I really feel that that is your next step, for us anyways, it's just that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx would just release the AI/ML solution, allowing, you know, folks to not have a data scientist program but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses quite a few. And right now, through our mastermind program we're actually running a four-months program for all skill levels. Teaching them AI/ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services, we have even some of our engineers, are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all was able to develop a solution where, you know, there is a checkout feedback, checkout functionality on the eBay site, where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in. And now instead of us or somebody going to the bay to try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. And it's a beautiful tool, and I'm very impressed when you saw the demo and they've been developing that further. >> That sounds fantastic. And I think just the one word that keeps coming to mind and we've said this a number of times in the program today is, empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you >> Thank you, Lisa. >> Thank you so much. (light upbeat music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four E's that's, everyone, everything, everywhere and easy analytics. Those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics. Not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com, and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring The Cube. For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (light upbeat music)

>>Hey everyone. Welcome back to the program. Lisa Martin here, I've got two guests joining me, please. Welcome back to the cube. Paula Hansen, the chief revenue officer and president at Al alters and Jackie Vander lake grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an alter Ricks is helping eBay innovate with analytics. Ladies. Welcome. It's great to have you both on the program. >>Thank you, Lisa. It's great to be here. >>Yeah, Paula, we're gonna start with you in this program. We've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation with analytics. As they talked about at the forefront of software investments, how's alters helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course, with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills, assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics, maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic program. We're gonna unpack that Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jackie did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >>So I think the main thing for us is just when we started out was is that, you know, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes, >>Starting with people is really critical. Jackie, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and, and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that, you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And we, there was no, we're not independent. You couldn't move forward. You would've opinion on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. >>And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy? And that is not so daunting on somebody who's brand new to the field. And I would, I would call those out as your, as your major roadblocks, because you always have not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's, it's our people that need to actually really embrace it and, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically some, a block you wanna be able to move. >>It's really all about putting people. First question for both of you and Paula will start with you. And then Jackie will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven Paula. >>Yes. Well, we leverage our platform across all of our business functions here at Altrix and just like Jackie explained it, eBay finances is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a, a key sponsor for using our own technology. We use Altrix for forecasting, all of our key performance metrics for business planning across our audit function, to help with compliance and regulatory requirements tax, and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? >>And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>Yeah, I think it means to what Paula has said in terms of, you know, you know, getting people excited about it, but it's also understanding that this is a journey and everybody's the different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you put, get everybody in their different phases to get to the, the initial destination. I say initially, because I believe the journey is never really complete. What we have done is, is that we decided to invest in an Ebola group of concept. And we got our CFO to sponsor a hackathon. We opened it up to everybody in finance, in the middle of the pandemic. So everybody was on zoom and we had, and we told people, listen, we're gonna teach you this tool super easy. >>And let's just see what you can do. We ended up having 70 entries. We had only three weeks. So, and these are people that has N that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 inches with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was, people had a proof of concept. They, they knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up. Now >>That's fantastic. And the, the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome. Sometimes the, the cultural barriers is key. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you are empowering the next generation of data workers, Paula will start with you? >>Absolutely. And, and Jackie says it so well, which is that it really is a journey that organizations are on. And, and we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Altrix to help address this skillset gap on a global level is through a program that we call sparked, which is essentially a, no-cost a no cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to, to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked. We started last may, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're gonna continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people within necessary analytics skills to solve all the problems that data can help solve. >>So spark has made a really big impact in such a short time period. And it's gonna be fun to watch the progress of that. Jackie, let's go over to you now talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we basically wanted to make sure that we keep that momentum from the hackathon that we don't lose that excitement, right? So we just launched a program called Ebo masterminds. And what it basically is, it's an inclusive innovation initiative where we firmly believe that innovation is all up scaling for all analytics for. So it doesn't matter. Your background doesn't matter which function you are in, come and participate in, in this where we really focus on innovation, introducing new technologies and upskilling our people. We are apart from that, we also say, well, we should just keep it to inside eBay. We, we have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter alter. And we're working with actually, we're working with spark and they're helping us develop that program. And we really hope that as a say, by the end of the year, have a pilot and then also make you, so we roll it out in multiple locations in multiple countries and really, really focus on, on that whole concept of analytics, role >>Analytics for all sounds like ultra and eBay have a great synergistic relationship there that is jointly aimed at, especially kind of going down the staff and getting people when they're younger, interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the Cube's super cloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating. What is by default a multi-cloud world? How does the alters analytics cloud platform enable CIOs to democratize analytics across their organization? >>Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs with business leaders is that they're integrating data analysis and the skill of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Altrics analytics cloud is to empower all of those people in every job function, regardless of their skillset. As Jackie pointed out from people that would, you know, are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Altrics analytics cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and drive real business outcomes. As a result of unlocking the potential of data, >>As well as really re lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the, the beauty of what Altrics is enabling. And, and eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where alters fits in on as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >>When we start about getting excited about things, when it comes to analytics, I can go on all day, but I I'll keep it short and sweet for you. I do think we are on the topic full of, of, of data scientists. And I really feel that that is your next step for us anyways, is that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's, it's something completely different. And it's something that, that is in everybody to a certain extent. So again, partner with three X would just released the AI ML solution, allowing, you know, folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with alters and we, we purchased a license, this quite a few. And right now through our mastermind program, we're actually running a four months program for all skill levels, teaching, teaching them AI ML and machine learning and how they can build their own models. >>We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I wanna give you a quick example of, of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where, you know, there is a checkout feedback checkout functionality on the eBay site where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. >>And it's a beautiful tool and very impressed. You saw the demo and they developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with, with varying degrees of skill level, going down to the high school level, really exciting, we'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I wanna thank you so much for joining me on the program today and talking about how alters and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>As you heard over the course of our program organizations, where more people are using analytics who have the deeper capabilities in each of the four E's, that's, everyone, everything everywhere and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We wanna thank you so much for watching the program today. Remember you can find all of the content on the cue.net. You can find all of the news from today on Silicon angle.com and of course, alter.com. We also wanna thank alt alters for making this program possible and for sponsored in the queue for all of my guests. I'm Lisa Martin. We wanna thank you for watching and bye for now.

>>Hey, everyone, welcome back to the programme. Lisa Martin here. I've got two guests joining me. Please welcome back to the Q. Paula Hanson, the chief Revenue officer and president at all tricks. And Jackie Vanderlei Grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an all tricks is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the programme. >>Thank you, Lisa. Not great to be >>here. >>Yeah, Paula, we're gonna start with you in this programme. We've heard from Jason Klein. We've heard from Allan Jacobsen. They talked about the need to democratise analytics across any organisation to really drive innovation with analytics as they talked about at the forefront of software investments. House all tricks, helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. Absolutely is about our customers success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform. But ultimately we help our customers to create a culture of data literacy and analytics from the top of the organisation starting with the C suite and we partner with our customers to build their road maps for scaling that culture of analytics through things like enablement programmes, skills assessments, hackathons, uh, setting up centres of excellence to help their organisation scale and drive governance of this, uh, analytics capability across the Enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practises so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic programme. We're gonna unpack that, Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the I. D. C report that showed that 93% of organisations are not utilising the analytic skills of their employees. But then there's eBay. How Jackie did eBay become one of the 7% of organisations who's really maturing and how are you using analytics across the organisation at bay? >>So I think the main thing for us is when we started out was is that you know our especially in finance. They became spreadsheet professionals instead of the things that we really want our influence to add value to. And we realised we have to address that. And we also knew we couldn't wait for all our data to be centralised until we actually start using the data or start automating and be more effective. Um, so ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >>Starting with people is really critical jacket continuing with you. What was in the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think you know, Eva is a very data driven company. We have a lot of data. I think we are 27 years around this year. So we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them, um, to move forward. The other thing is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no we're not independent. You couldn't move forward. You're dependent on somebody else's roadmap to get to data to get the information you want it. So really finding something that everybody could access analytics or access data. And finally we have to realise, is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would I would call those out as your as your major roadblocks, because you always have always. But most of the times you have support from the top. In our case we have. But in the end of the day, it's it's our people that need to actually really embrace it and making that accessible for them. I would say it's not to say a road block a block you want to be able to do. >>It's really all about putting people first question for both of you and Paula will start with you and then Jackie will go to you. I think the message in this programme that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organisations are empowering people, those in the organisation that may not have technical expertise to be able to leverage data so that they can actually be data driven colour. >>Yes, well, we leverage our platform across all of our business functions here at all tricks. And just like Jackie explained that eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data, uh, flowing through our enterprise, and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Ruben has been a key sponsor for using our own technology. We use all tricks for forecasting all of our key performance metrics for business planning across our audit function, uh, to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to How do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other to problem solve and, along the way, maybe earn badges, depending on the capabilities and trainings that they take and just have a little healthy competition, Uh, as an employee based around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable that they feel supportive, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>I think it means to what Paula has said in terms of, you know, getting people excited about it. But it's also understanding that this is a journey and everybody is the different place in their journey. You have folks that's already really advanced. Who's done this every day. And then you have really some folks that this is brand new and, um, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the the initial destination. And I say initial because I believe the journey is never really complete. Um, what we have done is that we decided to invest in a group of concept when we got our CFO to sponsor a hackathon. Um, we open it up to everybody in finance, um, in the middle of the pandemic. So everybody was on Zoom, um, and we had and we told people, Listen, we're gonna teach you this tool. It's super easy, and let's just see what you can do. We ended up having 70 injuries. We had only three weeks. So these are people that that do not have a background. They are not engineers and not data scientists and we ended up with 25,000 our savings at the end of the hackathon. Um, from the 70 countries with people that I've never, ever done anything like this before. And there you have the results. And they just went from there because people had a proof of concept. They knew that it worked and they overcame the initial barrier of change. Um, and that's what we are seeing things really, really picking up now >>that's fantastic. And the business outcome that you mentioned that the business impact is massive, helping folks get that confidence to be able to overcome. Sometimes the cultural barriers is key there. I think another thing that this programme has really highlighted is there is a clear demand for data literacy in the job market, regardless of organisation. Can each of you share more about how your empowering the next generation of data workers Paula will start with you? >>Absolutely. And Jackie says it so well, which is that it really is a journey that organisations are on and we, as people in society, are on in terms of up skilling our capabilities. Uh, so one of the things that we're doing here at all tricks to help address the skill set gap on a global level is through a programme that we call Sparked, which is essentially a no cost analyst education programme that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this programme is really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises when we close gap and empower more people with the necessary analytic skills to solve all the problems that data can help solve. >>So >>I just made a really big impact in such a short time period is gonna be fun to watch the progress of that. Jackie, let's go over to you now Talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we definitely wanted to make sure that we kept implemented from the hackathon that we don't lose that excitement life. So we just launched a programme for evil masterminds and what it basically is. It's an inclusive innovation initiative where we firmly believe that innovation is all upscaling for all analytics role. So it doesn't matter. Your background doesn't matter which function you are in. Come and participate in this where we really focus on innovation, introducing these technologies and upscaling of people. Um, we are apart from that. We also said, Well, we should just keep it to inside the way we have to share this innovation with the community. So we are actually working on developing an analytics high school programme which we hope to pilot by the end of this year. We will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, But also, um, how to use all tricks and we're working with Actually, we're working with spark and they're helping us develop that programme. And we really hope that it is said by the end of the year, have a pilot and then also makes you must have been rolled out in multiple locations in multiple countries and really, really, uh, focused on that whole concept of analytic school >>analytics. Girl sounds like ultra and everybody have a great synergistic relationship there that is jointly aimed at especially kind of going down the stock and getting people when they're younger, interested and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the cubes Super Cloud event just a couple of weeks ago and you talked about the challenges the companies are facing as they are navigating what is by default, a multi cloud world. How does the all tricks analytics cloud platform enable CEO s to democratise analytics across their organisation? >>Yes, business leaders and CEO s across all industries are realising that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organisations. Last I checked, there was two million data scientists in the world. So that's, uh, woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CEO s with business leaders is that they are integrating data analysis and the skill set of data analysis into virtually every job function. Uh, and that is what we think of when we think of analytics for all. And so our mission with all tricks analytics cloud is to empower all of those people in every job function, regardless of their skill set, as Jackie pointed out, from people that would are just getting started all the way to the most sophisticated of technical users. Um, every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organisations. So that's our goal with all tricks, analytics cloud and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyse and report out so that we can break down data silos across the Enterprise and Dr Real Business Outcomes. As a result, of unlocking the potential of data >>as well as really listening that skills gap. As you were saying, There's only two million data scientists. You don't need to be a data scientist. That's the beauty of what all tricks is enabling. And eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where all tricks fits in as that analytics maturity journey continues. And what are some of the things that you're most excited about as analytics truly gets democratised across eBay >>when we start about getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. Um, I do think we're on the topic full of data scientists, and I really feel that that is your next step for us, anyway. Is that how do we get folks to not see data scientist as this big thing like a rocket scientist it's something completely different and it's something that is in everybody in a certain extent. So, um, game partnering with all tricks to just release uh, ai ml um, solution allowing. You know, folks do not have a data scientist programme but actually build models and be able to solve problems that way. So we have engaged with all turrets and we purchase the licence is quite a few. And right now, through our masterminds programme, we're actually running a four months programme. Um, for all skill levels, um, teaching them ai ml and machine learning and how they can build their own models. Um, we are really excited about that. We have over 50 participants without the background from all over the organisation. We have members from our customer services. We have even some of our engineers are actually participating in the programme will just kick it off. And I really believe that that is our next step. Um, I want to give you a quick example of the beauty of this is where we actually, um, just allow people to go out and think about ideas and come up with things and one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution. Where, um, you know there is a checkout feedback checkout functionality on the eBay side, There's sellers or buyers can pervade them at information. And she built a model to be able to determine what relates to tax specific what is the type of problem and even predict how that problem can be solved before we as human, even stepped in. And now, instead of us or somebody going to debate and try to figure out what's going on there, we can focus on fixing their versus, um, actually just reading through things and not adding any value and its a beautiful tool. And I'm very impressed when we saw the demo and they've been developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind. And we've said this a number of times in the programme. Today's empowerment, what you're actually really doing to truly empower people across the organisation with with varying degrees of skill level, going down to the high school level really exciting. We'll have so stay tuned to see what some of the great things are that come from this continued partnership? Ladies, I wanna thank you so much for joining me on the programme today and talking about how all tricks and eBay are really partnering together to democratise analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>Thank you so much.

>> Narrator: theCUBE presents KubeCon and CloudNativeCon Europe 2022, brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain, KubeCon, CloudNativeCon Europe 2022. I'm Keith Townsend, your host. And we're continuing the conversations around ecosystem cloud native, 7,500 people here, 170 plus show for sponsors. It is for open source conference, I think the destination. I might even premise that this may be, this may eventually roll to the biggest tech conference in the industry, maybe outside of AWS re:Invent. My next guest is Nick van Wiggeren. >> Wiggeren. >> VP engineering of PlanetScale. Nick, I'm going to start off the conversation right off the bat PlanetScale cloud native database, why do we need another database? >> Well, why don't you need another database? I mean, are you happy with yours? Is anyone happy with theirs? >> That's a good question. I don't think anyone is quite happy with, I don't know, I've never seen a excited database user, except for guys with really (murmurs) guys with great beards. >> Yeah. >> Keith: Or guys with gray hair maybe. >> Yeah. Outside of the dungeon I think... >> Keith: Right. >> No one is really is happy with their database, and that's what we're here to change. We're not just building the database, we're actually building the whole kind of start to finish experience, so that people can get more done. >> So what do you mean by getting more done? Because MySQL has been the underpinnings of like massive cloud database deployments. >> 100% >> It has been the de-facto standard. >> Nick: Yep. >> For cloud databases. >> Nick: Yep. >> What is PlanetScale doing in enabling us to do that I can't do with something like a MySQL or a SQL server? >> Great question. So we are MySQL compatible. So under the hood it's a lot of the MySQL you know and love. But on top of that we've layered workflows, we've layered scalability, we've layered serverless. So that you can get all of the the parts of the MySQL, that dependability, the thing that people have used for 20, 30 years, right? People don't even know a world before MySQL. But then you also get this ability to make schema changes faster. So you can kind of do your work quicker get to the business objectives faster. You can scale farther. So when you get to your MySQL and you say, well, can we handle adding this one feature on top? Can we handle the user growth we've got? You don't have to worry about that either. So it's kind of the best of both worlds. We've got one foot in history and we've got one foot in the new kind of cloud native database world. We want to give everyone the best of both. >> So when I think of serverless because that's the buzzy world. >> Yeah. >> But when I think of serverless I think about developers being able to write code. >> Yep. >> Deploy the code, not worry about VM sizes. >> Yep. >> Amount of disk space. >> Yep. >> CPU, et cetera. But we're talking about databases. >> Yep. >> I got to describe what type of disk I want to use. I got to describe the performance levels. >> Yep. >> I got all the descriptive stuff that I have to do about infrastructures. Databases are not... >> Yep. >> Keith: Serverless. >> Yep. >> They're the furthest thing from it. >> So despite what the name may say, I can guarantee you PlanetScale, your PlanetScale database does run on at least one server, usually more than one. But the idea is exactly what you said. So especially when you're starting off, when you're first beginning your, let's say database journey. That's a word I use a lot. The furthest thing from your mind is, how many CPUs do I need? How many disk iOS do I need? How much memory do I need? What we want you to be able to do is get started on focusing on shipping your code, right? The same way that Lambda, the same way that Kubernetes, and all of these other cloud native technologies just help people get done what they want to get done. PlanetScale is the same way, you want a database, you sign up, you click two buttons, you've got a database. We'll handle scaling the disk as you grow, we'll handle giving you more resources. And when you get to a spot where you're really starting to think about, my database has got hundreds of gigabytes or petabytes, terabytes, that's when we'll start to talk to you a little bit more about, hey, you know it really does run on a server, we ain't got to help you with the capacity planning, but there's no reason people should have to do that up front. I mean, that stinks. When you want to use a database you want to use a database. You don't want to use, 747 with 27 different knobs. You just want to get going. >> So, also when I think of serverless and cloud native, I think of stateless. >> Yep. >> Now there's stateless with databases, help me reconcile like, when you say it's cloud native. >> Nick: Yep. >> How is it cloud native when I think of cloud native as stateless? >> Yeah. So it's cloud native because it exists where you want it in the cloud, right? No matter where you've deployed your application on your own cloud, on a public cloud, or something like that, our job is to meet you and match the same level of velocity and the same level of change that you've got on your kind of cloud native setup. So there's a lot of state, right? We are your state and that's a big responsibility. And so what we want to do is, we want to let you experiment with the rest of the stateless workloads, and be right there next to you so that you can kind of get done what you need to get done. >> All right. So this concept of clicking two buttons... >> Nick: Yeah. >> And deploying, it's a database. >> Nick: Yep. >> It has to run somewhere. So let's say that I'm in AWS. >> Nick: Yep. >> And I have AWS VPC. What does it look like from a developer's perspective to consume the service? >> Yeah. So we've got a couple of different offerings, and AWS is a great example. So at the very kind of the most basic database unit you click, you get an endpoint, a host name, a password, and the username. You feed that right into your application and it's TLS secure and stuff like that, goes right into the database no problem. As you grow larger and larger, we can use things like AWS PrivateLink and stuff like that, to actually start to integrate more with your AWS environment, all the way over to what we call PlanetScale Managed. Which is where we actually deploy your data plan in your AWS account. So you give us some permissions and we kind of create a sub-account and stuff like that. And we can actually start sending pods, and hold clusters and stuff like that into your AWS account, give you a PrivateLink, so that everything looks like it's kind of wrapped up in your ownership but you still get the same kind of PlanetScale cloud experience, cloud native experience. >> So how do I make calls to the database? I mean, do I have to install a new... >> Nick: Great question. >> Like agent, or do some weird SQL configuration on my end? Or like what's the experience? >> Nope, we just need MySQL. Same way you'd go, install MySQL if you're on a Mac or app store to install MySQL on analytics PC, you just username, password, database name, and stuff like that, you feed that into your app and it just works. >> All right. So databases are typically security. >> Nick: Yep. >> When my security person. >> Nick: Yep. >> Sees a new database. >> Nick: Yep. >> Oh, they get excited. They're like, oh my job... >> Nick: I bet they do. >> My job just got real easy. I can find like eight or nine different findings. >> Right. >> How do you help me with compliance? >> Yeah. >> And answering these tough security questions from security? >> Great question. So security's at the core of what we do, right? We've got security people ourselves. We do the same thing for all the new vendors that we onboard. So we invest a lot. For example, the only way you can connect to a PlanetScale database even if you're using PrivateLink, even if you're not touching the public internet at all, is over TLS secured endpoint, right? From the very first day, the very first beta that we had we knew not a single byte goes over the internet that's not encrypted. It's encrypted at rest, we have audit logging, we do a ton internally as well to make sure that, what's happening to your database is something you can find out. The favorite thing that I think though is all your schema changes are tracked on PlanetScale, because we provide an entire workflow for your schema changes. We actually have like a GitHub Polar Request style thing, your security folks can actually look and say, what changes were made to the database day in and day out. They can go back and there's a full history of that log. So you actually have, I think better security than a lot of other databases where you've got to build all these tools and stuff like that, it's all built into PlanetScale. >> So, we started out the conversation with two clicks but I'm a developer. >> Nick: Yeah. >> And I'm developing a service at scale. >> Yep. >> I want to have a SaaS offering. How do I automate the deployment of the database and the management of the database across multiple customers? >> Yeah, so everything is API driven. We've got an API that you can use supervision databases to make schema changes, to make whatever changes you want to that database. We have an API that powers our website, the same API that customers can use to kind of automate any part of the workflow that they want. There's actually someone who did talk earlier using, I think, wwww.crossplane.io, or they can use Kubernetes custom resource definitions to provision PlanetScale databases completely automatically. So you can even do it as part of your standard deployment workflow. Just create a PlanetScale database, create a password, inject it in your app, all automatically. >> So Nick, as I'm thinking about scale. >> Yep. >> I'm thinking about multiple customers. >> Nick: Yep. >> I have a successful product. >> Nick: Yep. >> And now these customers are coming to me with different requirements. One customer wants to upgrade once every 1/4, another one, it's like, you know what? Just bring it on. Like bring the schema changes on. >> Yep. >> I want the latest features, et cetera. >> Nick: Right. >> How do I manage that with PlanetScale? When I'm thinking about MySQL it's a little, that can be a little difficult. >> Nick: Yeah. >> But how does PlanetScale help me solve that problem? >> Yeah. So, again I think it's that same workflow engine that we've built. So every database has its own kind of deploy queue, its own migration system. So you can automate all these processes and say, on this database, I want to change this schema this way, on this database I'm going to hold off. You can use our API to drive a view into like, well, what's the schema on this database? What's schema on this database? What version am I running on this database? And you can actually bring all that in. And if you were really successful you'd have this single plane of glass where you can see what's the status of all my databases and how are they doing, all powered by kind of the PlanetScale API. >> So we can't talk about databases without talking about backup. >> Nick: Yep. >> And recovery. >> Yep. >> How do I back this thing up and make sure that I can fall back? If someone deleted a table. >> Nick: Yep. >> It happens all the time in production. >> Nick: Yeah, 100%. >> How do I recover from it? >> So there's two pieces to this, and I'm going to talk about two different ways that we can help you solve this problem. One of them is, every PlanetScale database comes with backups built in and we test them fairly often, right? We use these backups. We actually give you a free daily backup on every database 'cause it's important to us as well. We want to be able to restore from backup, we want to be able to do failovers and stuff like that, all that is handled automatically. The other thing though is this feature that we launched in March called the PlanetScale Rewind. And what Rewind is, is actually a schema migration undo button. So let's say, you're a developer you're dropping a table or a column, you mean to drop this, but you drop the other one on accident, or you thought this column was unused but it wasn't. You know when you do something wrong, you cause an incident and you get that sick feeling in your stomach. >> Oh, I'm sorry. I've pulled a drive that was written not ready file and it was horrible. >> Exactly. And you kind of start to go, oh man, what am I going to do next? Everyone watching this right now is probably squirming in their seat a bit, you know the feeling. >> Yeah, I know the feeling >> Well, PlanetScale gives you an undo button. So you can click, undo migration, for 30 minutes after you do the migration and we'll revert your schema with all the data in it back to what your database looked like before you did that migration. Drop a column on accident, drop a table on accident, click the Rewind button, there's all the data there. And, the new rights that you've taken while that's happened are there as well. So it's not just a restore to a point in time backup. It's actually that we've replicated your rights sent them to both the old and the new schema, and we can get you right back to where you started, downtime solved. >> Both: So. >> Nick: Go ahead. >> DBAs are DBAs, whether they've become now reformed DBAs that are cloud architects, but they're DBAs. So there's a couple of things that they're going to want to know, one, how do I get my zero back up in my hands? >> Yeah. >> I want my, it's MySQL data. >> Nick: Yeah. >> I want my MySQL backup. >> Yeah. So you can just take backups off the database yourself the same way that you're doing today, right? MySQL dump, MySQL backup, and all those kinds of things. If you don't trust PlanetScale, and look, I'm all about backups, right? You want them in two different data centers on different mediums, you can just add on your own backup tools that you have right now and also use that. I'd like you to trust that PlanetScale has the backups as well. But if you want to keep doing that and run your own system, we're totally cool with that as well. In fact, I'd go as far as to say, I recommend it. You never have too many backups. >> So in a moment we're going to run Kube clock. So get your... >> Okay, all right. >> You know, stand tall. >> All right. >> I'll get ready. I'm going to... >> Nick: I'm tall, I'm tall. >> We're both tall. The last question before Kube clock. >> Nick: Yeah. >> It is, let's talk a little nerve knobs. >> Nick: Okay. >> The reform DBA. >> Nick: Yeah. >> They want, they're like, oh, this query ran a little bit slow. I know I can squeeze a little bit more out of that. >> Nick: Yeah. >> Who do they talk to? >> Yeah. So that's a great question. So we provide you some insights on the product itself, right? So you can take a look and see how are my queries performing and stuff like that. Our goal, our job is to surface to you all the metrics that you need to make that decision. 'Cause at the end of the day, a reform DBA or not it is still a skill to analyze the performance of a MySQL query, run and explain, kind of figure all that out. We can't do all of that for you. So we want to give you the information you need either knowledge or you know, stuff to learn whatever it is because some of it does have to come back to, what's my schema? What's my query? And how can I optimize it? I'm missing an index and stuff like that. >> All right. So, you're early adopter of the Kube clock. >> Okay. >> I have to, people say they're ready. >> Nick: Ooh, okay. >> All the time people say they're ready. >> Nick: Woo. >> But I'm not quite sure that they're ready. >> Nick: Well, now I'm nervous. >> So are you ready? >> Do I have any other choice? >> No, you don't. >> Nick: Then I am. >> But are you ready? >> Sure, let's go. >> All right. Start the Kube clock. (upbeat music) >> Nick: All right, what do you want me to do? >> Go. >> All right. >> You said you were ready. >> I'm ready, all right, I'm ready. All right. >> Okay, I'll reset. I'll give you, I'll give, see people say they're ready. >> All right. You're right. You're right. >> Start the Kube clock, go. >> Okay. Are you happy with how your database works? Are you happy with the velocity? Are you happy with what your engineers and what your teams can do with their database? >> Follow the dream not the... Well, follow the green... >> You got to be. >> Not the dream. >> You got to be able to deliver. At the end of the day you got to deliver what the business wants. It's not about performance. >> You got to crawl before you go. You got to crawl, you got to crawl. >> It's not just about is my query fast, it's not just about is my query right, it's about, are my customers getting what they want? >> You're here, you deserve a seat at the table. >> And that's what PlanetScale provides, right? PlanetScale... >> Keith: Ten more seconds. >> PlanetScale is a tool for getting done what you need to get done as a business. That's what we're here for. Ultimately, we want to be the best database for developing software. >> Keith: Two, one. >> That's it. End it there. >> Nick, you took a shot, I'm buying it. Great job. You know, this is fun. Our jobs are complex. >> Yep. >> Databases are hard. >> Yep. >> It is the, where your organization keeps the most valuable assets that you have. >> Nick: A 100%. >> And we are having these tough conversations. >> Nick: Yep. >> Here in Valencia, you're talking to the leader in tech coverage. From Valencia, Spain, I'm Keith Townsend, and you're watching theCUBE, the leader in high tech coverage. (upbeat music)

>>Mm. Joining us now is Mark Van Name, co founder of Principled Technologies. Welcome, Mark. >>Thanks, Dave. It's great to be here. >>It's great to have you here. Uh, we'd like to hear the principled technologies story. We know that you are an independent testing lab, but but tell us. Tell us the story. >>Sure. Here's the short form we're in our 20th year. We created the company with the idea that the best way to sell products was to tell the truth, which may not seem radical, but often is. And so we started out trying to prove the advantages of products. We work primarily in the technical space. We work with most of the big tech companies, and over the years, what we learned was that although we were coming up with great facts that people could use for buying decisions and they were very successful for companies, companies were then having to turn them into marketing materials. So we created a studio team and we started enlarging the range of collateral we delivered so that today we do the testing and research and in some cases, even software development necessary to prove competitive advantages. And then we package that up into compelling collateral that helps companies win in the attention economy and sell their products. All telling the truth. >>Talk to me about the numbers of customers that you work with. The numbers of projects that you do give me, Give me, Give me a sense of the kind of scale we're talking about. >>Sure, we, as I said, I've been in business for 20 years. This our 20th year. We've done at this point, I believe, several 1000 engagements in it. Typical year, we will do more than 100 engagements, each of which will typically have many components and many different tests, different pieces of collateral and so on. We've worked with more than 50 tech leading companies, as well as about as many people in non tech areas with our e learning practise. But for this purpose here, the main audience is 50 plus tech companies. So it's it's many dozen tech companies over the years. >>Have you had challenges over the years maintaining that independence? Uh, what? What do those conversations look like when maybe someone is trying to nudge you? How do you deal with that? >>So this is obviously a key question about our business model and one that we considered when we started the company. The first thing to note is that anybody looking at our results, looking at any report or looking at any company that is paid to do work has the very reasonable question that could come to them, which is why should I trust you? And our answer from the beginning is don't trust us. Verify. So unlike just about anybody else in the industry from the beginning, we give away the entire methodology what we now call the science behind the report for every engagement we do. So we don't say, Hey, we just tested this. If you go to most review sites, they'll tell you a little tiny bit about what they did, and then they'll give you their conclusions. We make available in a separate document attached to the report, the complete methodology, the system, information, software, information, um, everything about what we did, the detailed steps so that if you have the right hardware, software and expertise, you can reproduce what we did. This means you don't have to trust us. You can verify it, and it puts our work out on display for everybody. >>Mark, Thank you so much for spending time with us and telling us a little about what your company does and how you do it. Well, thanks >>for having me. Mm.

(electronic music) >> Welcome to theCUBE. This is the AWS Executive Summit presented by Accenture and our coverage of this great event continues. Lisa Martin here, I've got two guests with me here to talk about Amazon Connect. Please welcome from Hawaiian Airlines, Will Van Devender, Senior Director of IT Engineering. Will, welcome to the program. >> Thanks for having me here. >> And from Accenture, Erich Chen is here as well, the Hawaii Regional Lead at Accenture. Erich, it's great to have you on the program. >> It's great to be here. >> I feel very overdressed. You can tell I'm on the mainland with my turtleneck and you guys are on Oahu, which is fantastic. And I'm excited that I have a seat on Hawaiian Airlines in just a few weeks. So you guys, let's talk about this technology solution that you put together. Will, I want to start with you. Talk to me about some of the challenges that Hawaiian Airlines was having prior to working with Accenture and Amazon. >> Well, nothing really unique to us. We had the challenges that everybody had with the pandemic and scaling out to work from home, as well as an old legacy stack that had been around for a long, long time. The specific ones that drove us to launch this particular project was we had been running into some talent acquisition issues. We're not of size where we have a huge telecom team that can specialize in IDRs and other things like that. So we need folks that can play a lot of different spaces. And in this particular case, we had a situation where we had really old technology and the people we were bringing in were a lot more savvy on Cloud and those kinds of things. And so AWS Connect was a way for us to take talent that traditionally wasn't inside the telephony space and use them and bring them to bear for that business need. So it kept us from having to scale up to do this. The other thing we had was a big issue with work from home that actually predated COVID. So we had been, we're in a hurricane zone, we had been doing hurricane preparedness exercises and we realized that we had a difficult time scaling our environment to large scale work from home. So even prior to COVID, we had been started looking at the technologies that we had, which ones worked well outside of an office for a distributed workforce. And we had been moving technology in that direction. And so telephony was one of the ones that we had to beef up. And so it was nice to have a good leg up on it when the pandemic hit us. >> Absolutely. I can't imagine how advantageous that was when it struck. And of course we all know how much the airlines were affected. Talk to me about an interesting catalyst for this solution in terms of challenge with talent acquisition and work from home. Interesting impetus for this solution. Talk to me about, are you long time partners, Hawaiian Airlines with Accenture? Talk to me about how you went about looking for the right solution with them as a partner. >> Ah, okay. So Hawaiian Airlines and Accenture had been partnering for many years, but in a much bigger way in 2019, when we solidified a new managed services deal. So Accenture came in to help us out with our day to day operations. And one of the big reasons for that was actually cloud adoption. So we needed a partner that was much more up to date technology wise. And as we started ramping up our engineering and architecture designs and releasing things on new stacks, we needed folks in the operation side that could keep up with that. And not only that, actually enable and push us in those directions. And so when we went out to RFP, Accenture kind of stood out in that area and that's been a good thing. We've had very little friction as we've been going out and acquiring new technology with being able to bring that out to our run and operation space. >> That's critical, especially given the tumultuous times in which we are still living. Erich, let's go ahead and bring you into the conversation. Now, talk to me about you guys at Accenture developed and deployed this solution quickly. We're talking an eight week timeframe. Talk to me about the solution that you architected, about that delivery, and what some of the challenges were along the way that you tackled and mitigated. >> Yeah. Thanks Lisa. I mean, it was, you know, eight weeks when you look back on it, it's hard to believe we did complete it in that timeframe, but, you know, we were able to do it with some strong experts from our side. Some of the challenges we ran into along the way were probably at the very beginning, just securing the right team for Hawaiian to deliver the kind of the proper designs and development upfront, and then helping to kind of manage through the delivery process itself. You know, they were great. They had some great people with some deep expertise, kind of from a business process side of things, kind of paired with our technical and then also industry knowledge of the airlines as well. It made for a really nice, you know, strong partnership where we could get it through in eight weeks. So it was pretty amazing. >> And then walk me through the actual, oh Will, sorry. Did you want to say something? >> Yeah, I was actually going to comment on that, that was exactly what we were looking for was that sort of wholesale partner. So when we went out to modernize our entire telephony stack, it wasn't just call centers. It was the conference rooms, it was the telephony, we went to new phone providers and circuit providers, we moved everyone off of Skype over on to Teams, all the desk phones. And so there was this scope of work that was simply larger than our team. And so what we were looking for from a partner was one, who's done this before, and then two, could you manage the whole piece of work? And so what was nice for Accenture, because they owned our existing operation space, they not only did the AWS Connect piece, they got on the old systems and they brought up all the specs of how the call queues worked, how the call flows worked, they found the old voice talent, they brought those, imported them without us having to do anything over onto the new stack, and then brought it over for testing. So it was just a very minimal lift from the Hawaiian Airlines side. And since they ran our operations, they then moved it over to the run space. And it was just very few man hours on the Hawaiian Airlines side expended for that outcome. >> Wow. It sounds fairly seamless. Erich, how did you guys accomplish that? >> I mean, that's a type of experience and partnership we like to have with our clients, more of an all-inclusive type service. But we're sometimes accused of not having the cheapest prices on the block, but you know, you do get a great, you know, a pretty holistic experience with us and we do try to make it as easy as possible for our clients and bring kind of the full breadth of Accenture to fill in a lot of gaps. >> Well, one of the things, Will, that you mentioned is we were looking for a partner that had done this before, where there's actual proof in the pudding, especially given the, like I mentioned before, the tumultuous market. Erich talk to me about, if we look at Hawaiian Airlines as an example, as a template here, how common or how often are you seeing these same challenges with respect to talent acquisition and work from home? Is that something that really skyrocketed in the last year and a half? >> Sure. I mean, it's maybe a blessing in the type of business that we're in, right. But whenever there are, you know, big, you know, kind of market issues and kind of pandemics as an example, right. Our clients do turn to us for, you know, support to help them through, you know, smaller times of need. And, you know, maybe very compressed issues. So we're very happy to, you know, reach into our larger organization to make sure that we can bring the best of Accenture to them and help them get through these tough times. >> Will, let's talk about how this solution is helping employees, agents get through these tough times. As we know, Hawaii had some really strict travel restrictions on COVID. And of course, one of the things that a lot of people lost during this time, was patience. Talk to me about how the workforce is improving, the employees, the agents, now that you have this solution implemented and a leg up probably on your competitors. >> Yeah, the whole pandemic hit us in a hard way. So we found ourselves, you know, all of a sudden one day waking up and finding that our customer facing support desks couldn't be staffed. People couldn't get into the office and actually get there. At the same time, as you and everyone else knows, flights were getting canceled and customers were calling at a level we'd never seen before trying to reschedule their flights or get credit back or get money back. And so AWS Connect was interesting in that it was one of the things we could ramp up new call centers very quickly. And so we knew we wanted something that was consumption-based because we didn't know how long it was going to last. And we wanted to be able to spin it up, get new agents going, respond to our customers, scale up to the volume, and then be able to decrease it out. So it was a good win there. What wasn't talked about much was the reliability aspect of it. Being on a really old system, our telephony was pretty stable, but our call center internal business facing ones were not. We had a series of outages out there and those outages directly impact our ability to get planes out in the air. There's the sort of customers calling about tickets and about help with flights, but there's also things like cruise, trying to get cruise scheduling done, trying to get staffing to a plane, trying to get things moved around in an airport. And there's a lot of internal desks that deal with those kinds of things. And having that on an incredibly stable technology and stack is key for us. And so we were able to get Connect deployed, and we were also able to front that with a number of other technologies that allowed us to have DR plans. So even if we lost that desk, how can we quickly move that over to manual calls and desk phones and those kinds of things. And so that's been, that part has been very well received. That has helped us out a lot. Our confidence, knowing that if anything should happen, our ability to recover and get back into full operations now is just night and day from where it was 12 months ago. And so thank you all very much for your assistance in getting us to this point. >> Getting that stability and that reliability during a time of chaos that's, and also in a time that can really affect brand reputation, it sounds to me like IT is really helping drive the business forward. This is something that you did in partnership with the business side, because of course during the last year and a half, so many brands have had challenges with reputation and the ability to not do things. Talk to me about that business IT relationship. And was this a facilitator of making that even better? >> Well, it's certainly better. Yeah, we have far better conversations internally than I can ever remember in my time here in Hawaiian Airlines. But you know, when these kinds of emergencies hit, I don't think about it as IT or business. I mean, there's a problem and you got to go fix it. And so we're all in there and IT is one piece of that. How do we get a solution stood up almost overnight in this, you know, very, very difficult pandemic business time? But you know, the business is trying to get talent together and trying to get agents trained and being able to do things like handle these customer calls is very, very skill intensive. So there's a lot of partnership coming in and getting solutions, demoing with the business, dialing them in back and forth, and a lot of collaboration there. And so that builds stronger teams. And that's one of the outcomes I like more than anything else, is we're working together and dialing in the IT and the business needs very much in unison. >> That's probably one of the best outcomes you can hope for. Erich, talk to me about, are you seeing similar things with customers in other industries? Are you seeing that business IT coming together, especially during these challenging times we've been living through? >> Yeah, to varying degrees, you know, that's always the crux of, you know, a successful IT department, right. You know, you're there to serve and support the business side of things, right. We don't do technology for technology sake. But yeah, I think the better ones are getting better, better at, you know, being more fully integrated and it's not a business or IT decision, right, it's a collective kind of team decision. And I think as long as you have people who respect and understand the other side of the coin sometimes, easier the conversation will go. And I think that's what our team was able to do is express, you know, very clearly and concisely kind of what the decisions they had to make were and they could make a decision a little bit easier that way. >> And talk to me, Erich, about the solution, what impressed you? What are you most excited about in terms of what Accenture has helped to accomplish for Hawaiian Airlines? >> Yeah, I was really happy that even, you know, within a short eight week period itself, you know, things always come up as you go throughout a project. And I think the business team was getting excited about the possibilities once they saw kind of the potential of the platform. And so some, you know, requests came up in the middle of the way, you know, in flight. And, you know, our team was able to accommodate a number of the kind of minor enhancements or tweaks to the system to make it even better and serve the business in a better fashion there. >> Gotcha. Will, what is next for Hawaiian Airlines, besides my flight on it in a few weeks? Talk to me about where you guys are going from an IT perspective. >> Well we've rolled out a solution quickly 'cause we needed to, but there's a lot still to be done to dial it in for the business. Where reliability and speed were key, we got those done, but there was some aspects of the old system that were still a little easier. For those call centers where people needed to dial in, get ahold of an agent, and then pass it onto an internal employee, there's still a disconnect between our call center technology, AWS Connect, and the internal collaboration, Microsoft Teams. And that's because Teams really wasn't up to all of the call center technology needs at the time we started this. Things like call recording and things like that just weren't there at the time. So we've got some of our internal desks that still need to be tweaked and integrated more seamlessly between the two platforms or maybe as Teams gets ready, moved back over onto that. So that's, again, the part of it, being able to have this deep conversation with the business, understand their needs, having a partner where you can quickly go respond and go dial it in. And so we don't look at it as our telephony migration is complete. We look at it as we got our first big hurdle done, moving off decades old tech onto our modern stack. And now we're looking at refining it with our partners over the future. >> Right. Phase one, it's always that journey that we talk about. Erich, last question for you. What are some of the things that are coming up next as you help Hawaiian Airlines to continue on this modernization journey? >> Yeah, so more broadly we're really excited because this effort was one of the first or probably more platform centric system integration type projects we've done for Hawaiian. We've been on the operation side, we've done some business consulting worked with them for various business functions already, but this was really more on the application modernization side of things. And, you know, we see that Hawaiian has a number of areas that they're looking to kind of modernize and improve along the way. And we're very excited about, you know, being a strong partner for them in that journey coming up. >> Awesome guys, great work. Congratulations on a huge transformation accomplished during a very chaotic world time period and done so quickly. We appreciate your comments, your feedback, and look forward to seeing what you dial in next. Thanks for joining me today. >> Thank you. >> Thanks very much. >> For Will Van Devender and Erich Chen, I'm Lisa Martin. You're watching theCUBE's coverage of the AWS Executive Summit presented by Accenture. (soft music)

>>At the beginning of the last decade, the technology industry was a buzzing because we were on the cusp of a new era of data. The promise of so-called big data was that it would enable data-driven organizations to tap a new form of competitive advantage. Namely insights from data at a much lower cost. The problem was data became plentiful, but insights. They remained scarce, a rash of technical complexity combined with a lack of trust due to conflicting data sources and inconsistent definitions led to the same story that we've heard for decades. We spent a ton of time and money to create a single version of the truth. And we're further away than we've ever been before. Maybe as an industry, we should be approaching this problem differently. Perhaps it should start with the idea that we have to change the way we serve business users. I E those who understand data context, and with me to discuss the evolving data space, his company, and the upcoming data citizens conference is Felix van de Mala, the CEO and founder of Collibra. Felix. Welcome. Great to see you. >>Great to see you. Great to be here. >>So tell us a little bit about Collibra and the problem that you're solving. Maybe you could double click on my upfront narrative. >>Yeah, I think you said it really well. Uh, we've seen so much innovation over the last couple of years in data, the exploding volume complexity of data. We've seen a lot of innovation of how to store and process that data, that, that volume of data more effectively or more cost-effectively, but fundamentally the source of the problem as being able to really derive insights from that data effectively when it's for an AI model or for reporting, it's still as difficult as it was, let's say 10 years ago. And if only in a way it's only become more, uh, more difficult. And so what we fundamentally believe is that next to that innovation on the infrastructure side of data, you really need to look at the people on process side of data. There's so many more people that today consume and produce data to do their job. >>That's why we talk about data citizens. They have to make it easier for them to find the right data in a way that they can trust that there's confidence in that data to be able to make decisions and to be able to trust the output of that, uh, of that model. And that's really what is focused on initially around governance. Uh, how do you make sure people actually are companies know what data they have and make sure they can trust it and they can use it in a compliant way. And now we've extended that into the only data intelligence platform today in the industry where we just make it easier for organizations to truly unite around the data across the whole organization, wherever that data is stored on premise and the cloud, whoever is actually using or consuming data. Uh, that's why we talk about data citizens. I >>Think you're right. I think it is more complex. There's just more of it. And there's more pressure on individuals to get advantage from it. But I, to ask you what sets Culebra apart, because I'd like you to explain why you're not just another data company chasing a problem with w it's going to be an incremental solution. It's really not going to change anything. What, what sets Collibra apart? >>Yeah, that's a really good question. And I think what's fundamentally sets us apart. What makes us unique is that we look at data or the problem around data as truly a business problem and a business function. So we fundamentally believe that if you believe that data is an asset, you really have to run it as a, as a, as a strategic business functions, just like your, um, uh, your HR function, your people function, your it functioning says a marketing function. You have a system to run that function. Now you have Salesforce to run sales and marketing. You have service now to run your, it function. You have Workday to run your people function, but you need the same system to really run your data from. And that's really how we think about GDPR. So we not another kind of faster, better database we know than other data management tool that makes the life of a single individual easier, which really a business application that focuses on how do we bring people together and effective rate so that they can collaborate around the data. It creates efficiency. So you don't have to do things ad hoc. You can easily find the right information. You can collaborate effectively. And it creates the confidence to actually be able to do something with the outcomes of it, the results of all of that work. And so fundamentally I'm looking at the problem as a, as a business function that needs a business system. We call it the system of record or system of engagement for the, for the data function, I think is absolutely critical and, and really unique in the, in our approach. So >>Data citizens are big user conference, data citizens, 21, it's coming up June 16th and 17th, the cubes stoked because we love talking about data. This is the first time we're bringing the cube to that event. So we're really gearing up for it. And I wonder if it could tell us a little bit about the history and the evolution of the data citizens conference? >>Absolutely. I think the first one is set at six years ago where we had a small event at a hotel downtown New York. Uh, most of the customers as their user conference, a lot of the banks, which are at the time of the main customers at 60 people. So very small events, and it exploded ever since, uh, this year we expect over 5,000 people. So it's really expanded beyond just the user conference to really become more of almost the community conference and the industry, um, the conference. So we're really excited, a big part of what we do, why we care so much about the conference. That's an opportunity to build that data citizens community. That's what we hear from our customers, from all attendees that come to the conference, uh, bring those people to get us all care about the same topic and are passionate about doing more at data, uh, being able to connect, uh, connect people together as a big part of that. So we've always, uh, we're always looking forwards, uh, through the event, uh, from that perspective >>Competition, of course, for virtual events these days with them, what's in it for me, what, who should attend and what can attendees expect from data citizens? 21. >>Yeah, absolutely. The good thing about the virtual event, uh, event is that everybody can attend. It's free, it's open from across the road, of course, but what we want for people to take away as attendees is that you learn something at pragmatics or the next day on the job, you can do something. You've learned something very specific. We've also been, um, um, excited and looked at what is possible from an innovation perspective. And so that's how we look at the events. We bring a lot of, um, uh, customers on my realization that they're going to share their best practices, very specifically, how they are, how they are handling data governance, how they're doing data, data, cataloging, how they're doing data privacy. So very specific best practices and tips on how to be successful, but then also industry experts that can paint the picture of where we going as an industry, what are the best practices? >>What do we need to think about today to be ready for what's going to come tomorrow? So that's a big focus. We, of course, we're going to talk about and our product. What are we, what do we have in store from a product roadmap and innovation perspective? How are we helping these organizations get their foster and not aspect as we were being in a lot of partners as well? Um, and so that's a big part of that broader ecosystem, uh, which is, which is really interesting. And I finally, like I said, it's really around the community, right? And that's what we hear continuously from the attendees. Just being able to make these connections, learn new people, learn what they're doing, how they've, uh, kind of, um, solved certain challenges. We hear that's a really big part of, uh, of the value proposition. So as an attendee, uh, the good thing is you can, you can join from anywhere. Uh, all of the content is going to be available on demand. So later it's going to be available for you to have to look at as well. Plus you're going to be farther out. You're going to become part of that data, citizens community, which has a really thriving and growing community where you're going to find a lot of like-minded people with the same passion, the same interest that McConnell learned the most from, well, I'd rather >>Like the term data citizen. I consider myself a data citizen, and it has implications just in terms of putting data in the hands of, of business users. So it's sort of central to this event, obviously. W what is a data citizen to Collibra? >>Yeah, it's, it's a really core part of our mission and our vision that we believe that today everyone needs data to do their job. Everyone in that sense has become a data citizen in the sense that they need to be able to easily access trustworthy data. We have to make it easy for people to easily find the right data that they can trust that they can understand. And I can do something like with and make their job easier. On the other hand, like a citizen, you have rights and you have responsibilities as a data citizen. You also have the responsibility to treat that data in the right way to make sure from a privacy and security perspective, that data is a as again, like I said, treated in the right way. And so that combination of making it easy, making it accessible, democratizing it, uh, but also making sure we treat data in the right way is really important. And that's a core part of what we believe that everyone is going to become a data citizen. And so, um, that's a big part of our mission. I like that >>We're to enter into a contract, I'll do my part and you'll give me access to that data. I think that's a great philosophy. So the call to action here, June 16th and 17th, go register@citizensdotcollibra.com go register because it's not just the normal mumbo jumbo. You're going to get some really interesting data. Felix, I'll give you the last word. >>No, like I said, it's like you said, go register. It's a great event. It's a great community to be part of June 16 at 17, you can block it in your calendar. So go to citizens up pretty bad outcome. It's going to be a, it's going to be a great event. Thanks for helping >>Us preview. Uh, this event is going to be a great event that really excited about Felix. Great to see you. And we'll see you on June 16th and 17th. Absolutely. All right. Thanks for watching everybody. This is Dave Volante for the cube. We'll see you next time.

(upbeat music) >> At the beginning of last decade technology industry was a buzzing because we were on the cusp of a new era of data. The promise of so-called big data was that it would enable data-driven organizations to tap a new form of competitive advantage. Namely insights from data at a much lower cost. The problem was data became plentiful, but insights, they remain scarce. A rash of technical complexity combined with a lack of trust due to conflicting data sources and inconsistent definitions led to the same story that we've heard for decades. We spent a ton of time and money to create a single version of the truth. And we're further away than we've ever been before. Maybe as an industry, we should be approaching this problem differently. Perhaps it should start with the idea that we have to change the way we serve business users i.e. those who understand data context. And with me, to discuss the evolving data space, his company and the upcoming Data Citizens Conference is Felix Van De Maele, the CEO and Founder, of Collibra. Felix, welcome. Great to see you. >> Great to see you. Great to be here. >> So tell us a little bit about Collibra and the problem that you're solving. Maybe you could double click on my upfront narrative. >> Yeah, I think you said it really well. We've seen so much innovation over the last couple of years in data, the exploding volume complexity of data. We've seen a lot of innovation of how to store and process that data, that volume of data more effectively, more cost-effectively. But fundamentally the source of the problem as being able to really derive insights from that data effectively when it's for an AI model or for reporting is still as difficult as it was let's say 10 years ago. And it only... In a way it's only become more difficult. And so what we fundamentally believe is that next to that innovation on the infrastructure side of data you really need to look at the people on process side of data. There are so many more people that today consume and produce data to do their job. That's why we talk about data citizens. They have to make it easier for them to find the right data in a way that they can trust that there's confidence in that data to be able to make decisions and to be able to trust the algorithm of that model. And that's really what Collibra is focused on. Initially, around governance. How do you make sure people actually or companies know what data they have and make sure they can trust it and they can use it in a compliant way. And now we've extended that into the only data intelligence platform today in the industry where we just make it easier for organizations to truly unite around the data across the whole organization. wherever that data stored on premise and the cloud whoever is actually using or consuming that data. That's why we talk about data citizens. >> I think you're right. I think yours is more complex. There's more of it. And there's more pressure on individuals to get advantage from it. But I want to ask you, what sets Collibra apart because I'd like you to explain why you're not just another data company chasing a problem with it's going to be an incremental solution, it's really not going to change anything. What sets Collibra apart? >> Yeah, that's a really good question. And what fundamentally sets us apart, or makes us unique is that we look at data or the problem around data as truly a business owner and a business function. So we fundamentally believe that if you believe that data is an asset, you really have to run it as a strategic business function. Just like you run your HR function, your people function, your IT function your sales and marketing function. You have a system to run that function. And you have Salesforce to run sales and marketing. You have service now to run your IT function. You have word day to run your people function. Like you need the same system to really run your data function. And that's really how we think about Collibra. So we're not another kind of faster better database. We're not another data management tool that makes the life of a single individual easier. We're truly a business application that focuses on how do we bring people together and effective rates so that they can collaborate around the data. It creates efficiency. So you don't have to do things ad hoc. You can easily find the right information. You can collaborate effectively. And it creates the confidence to actually be able to do something with the outcomes or with the results of all of that work. And so fundamentally, looking at the problem as a business function that needs a business system. We call it the system of record or system of engagement. For the data function, I think it's absolutely a critical and really unique in our approach. >> So Data Citizens your big user conference. Data Citizens '21 it's coming up June 16th and 17th cubes stoked because we love talking about data. This is the first time we're bringing theCUBE to that event. And so we're really gearing up for it. And I wonder if you can tell us a little bit about the history and the evolution of the Data Citizens conference? >> Absolutely. I think the first one it started six years ago where we had a small event at a hotel downtown New York mostly customers as their user conference, a lot of the banks, which are at the time are the main customers at 60 people. So very small events. And it's exploded ever since this year, we expect over 5,000 people. So it's really expanded beyond just a user conference to really become more of almost a community conference and an industry conference. So we're really excited. A big part of what we do, why we care so much about the conference. That's an opportunity to build that data citizens community. That's where we hear from our customers, from all attendees that come to the conference, bring those people together that all care about the same topic and are passionate about doing more with data, being able to connect people together as a big part of that. So we've always... We're always looking forward to event from that perspective. >> Well, a lot of competition of course, for virtual events these days with them. What's in it for me? Who should attend? And what can attendees expect from Data Citizens '21? >> Yeah, absolutely. The good thing about the virtual event is that everybody can attend. It's free, it's open from across the world, of course. But what we want for people to take away as attendees is that you learn something pragmatic. So the next day on the job, you can do something. You've learned something very specific. We've also been excited and looked at what is possible from an innovation perspective? And so that's how we look at the event. We bring a lot of customers and organization that are going to share their best practices. Very specifically, how they're handling data governance. How they're doing data cataloging. How they're doing data privacy. So very specific best practices and tips on how to be successful, but then also industry experts that can paint a picture of where we're going as an industry, what are the best practices? What do we need to think about today to be ready for what's going to come tomorrow? So that's a big focus. We, of course, we're going to talk about Collibra and our product. What do we have in store from a product roadmap. And innovation perspective, how we're helping these organizations get there faster and all that aspect as we bring in a lot of partners as well. And so that's a big part of that broader ecosystem which is really interesting. And I finally, like I said it's really around the community. That's what we hear continuously from the attendees. Just being able to make these connections, learn new people, learn what they're doing how they've kind of solved certain challenges. We hear that's a really big part of the value proposition. So as an attendee, the good thing is you can join from anywhere. All of the content is going to be available on demand. So later it's going to be available for you to have to look at as well. Plus you're going to be part, or you're going to become part of that data citizens community. Which is a really thriving and growing community where you're going to find a lot of like-minded people with the same passion, the same interest, that we can all learn a lot from. >> I rather like the term data citizen. I consider myself a data citizen and it has implications just in terms of putting data in the hands of business users. So it's just sort of central to this event, obviously. What is a data citizen to Collibra? >> Yeah. It's a really core part of our mission and our vision that we believe that today everyone needs data to do their job. Everyone in that sense has become a data citizen in the sense that they need to be able to easily access trustworthy data. We have to make it easy for people to easily find the right data that they can trust, that they can understand and they can do something with and make their job easier. On the other hand, like a citizen, you have rights and you have responsibilities. As a data citizen, you also have the responsibility to treat that data in the right way. To make sure from a privacy and security perspective, that data is as again like I said, treated in the right way. And so that combination of making it easy, making it accessible, democratizing it but also making sure we treat data in the right way is really important. And it's a core part of what we believe that everyone is going to become a data citizen. And so that's a big part of our mission. >> I like that. We're going to enter into a contract. I'll do my part and you'll give me access to that data. I think that's a great philosophy. So the call to action here, June 16th and 17th go register at citizens.collibra.com go register because it's not just the normal mumbo jumbo. You're going to get some really interesting data. Felix, I'll give you the last word. >> No, like I said, like you said, go register. It's a great event. It's a great community to be part of at June 16th and 17th you can block it in your calendar. So go to citizens.collibra.com. It's going to be a great event. >> Well, thanks for helping us preview this event. It's going to be a great event that we're really excited about. Felix, great to see you. And we'll see you on June 16th and 17th. >> Absolutely. >> All right. Thanks for watching everyone. This is Dave Vellante for theCUBE. We'll see you next time. (upbeat music)

>> Presenter: From around the globe, it's theCUBE. Presenting Adaptive Data Governance, brought to you by Io-Tahoe. >> Our next segment here is an interesting panel, you're going to hear from three gentlemen, about Adaptive Data Governance. We're going to talk a lot about that. Please welcome Yusef Khan, the global director of data services for Io-Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and Gudron Van Der Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this panel. (indistinct) >> All right, Santiago, we're going to start with you. Can you talk to the audience a little bit about the First Bank of Nigeria and its scale? This is beyond Nigeria, talk to us about that. >> Yes. So First Bank of Nigeria was created 125 years ago, it's one of the oldest, if not the oldest bank in Africa. And because of the history, it grew, everywhere in the region, and beyond the region. I'm currently based in London, where it's kind of the European headquarters. And it really promotes trade finance, institutional banking, corporate banking, private banking around the world, in particular in relationship to Africa. We are also in Asia, in the Middle East. And yes, and is a very kind of active bank in all these regions. >> So Santiago, talk to me about what adaptive data governance means to you, and how does it helps the First Bank of Nigeria to be able to innovate faster with the data that you have. >> Yes I like that concept of adaptive data governance, because it's kind of, I would say, an approach that can really happen today with the new technology before it was much more difficult to implement. So just to give you a little bit of context, I used to work in consulting for 16-17 years before joining the First Bank of Nigeria. And I saw many organizations trying to apply different type of approaches in data governance. And the beginning, early days was really kind of (indistinct), where you top down approach, where data governance was seen as implement a set of rules, policies and procedures, but really from the top down. And is important, it's important to have the battle of your sea level, of your director, whatever is, so just that way it fails, you really need to have a complimentary approach, I often say both amount, and actually, as a CEO I'm really trying to decentralized data governance, really instead of imposing a framework that some people in the business don't understand or don't care about it. It really needs to come from them. So what I'm trying to say is that, data basically support business objectives. And what you need to do is every business area needs information on particular decisions to actually be able to be more efficient, create value, et cetera. Now, depending on the business questions they have to show, they will need certain data sets. So they need actually to be able to have data quality for their own, 'çause now when they understand that, they become the stewards naturally of their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also in power and be actually in a way flexible to adapt the different questions that they have in order to be able to respond to the business needs. And I think that is where these adaptive data governance starts. Because if you want, I'll give you an example. In the bank, we work, imagine a Venn diagram. So we have information that is provided to finance, and all information to risk, or information for business development. And in this Venn diagram, there is going to be part of that every circle that are going to kind of intersect with each other. So what you want as a data governance is to help providing what is in common, and then let them do their own analysis to what is really related to their own area as an example, nationality. You will say in a bank that will open an account is the nationality of your customer, that's fine for final when they want to do a balance sheet an accounting or a P&L, but for risk, they want that type of analysis plus the net nationality of exposure, meaning where you are actually exposed as a risk, you can have a customer that are on hold in the UK, but then trade with Africa, and in Africa they're exposing their credit. So what I'm trying to say is they have these pieces in common and pieces that are different. Now I cannot impose a definition for everyone. I need them to adapt and to bring their answers to their own business questions. That is adaptive data governance. And all that is possible because we have and I was saying at the very beginning, just to finalize the point, we have new technologies that allow you to do these metadata classification in a very sophisticated way that you can actually create analytics of your metadata. You can understand your different data sources, in order to be able to create those classifications like nationalities and way of classifying your customers, your products, et cetera. But you will need to understand which areas need, what type nationality or classification, which others will mean that all the time. And the more you create that understanding, that intelligence about how your people are using your data you create in a way building blocks like a label, if you want. Where you provide them with those definitions, those catalogs you understand how they are used or you let them compose like Lego. They would play their way to build their analysis. And they will be adaptive. And I think the new technologies are allowing that. And this is a real game changer. I will say that over and over. >> So one of the things that you just said Santiago kind of struck me in to enable the users to be adaptive, they probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the user so that they can be adaptive? >> Yeah, that's a really good question. And that goes along with that type of approach. I was saying in a way more and more business users want autonomy, and they want to basically be able to grab the data and answers their question. Now, when you have that, that's great, because then you have demand. The business is asking for data. They're asking for the insight. So how do you actually support that? I will say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, of course, technology is one of the biggest winners without technology we couldn't have been working remotely. Without this technology, where people can actually log in from their homes and still have a market data marketplaces where they self serve their information. But even beyond that, data is a big winner. Data because the pandemic has shown us that crisis happened, but we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore and we need to adapt and we need to be flexible. How do we do that? With data. As a good example this, every country, every government, is publishing everyday data stats of what's happening in the countries with the COVID and the pandemic so they can understand how to react because this is new. So you need facts in order to learn and adapt. Now, the companies that are the same. Every single company either saw the revenue going down, or the revenue going very up for those companies that are very digital already now, it changed the reality. So they needed to adapt, but for that they needed information in order to think and innovate and try to create responses. So that type of self service of data, (indistinct) for data in order to be able to understand what's happening when the construct is changing, is something that is becoming more of the topic today because of the pandemic, because of the new capabilities of technologies that allow that. And then, you then are allowed to basically help, your data citizens, I call them in organization. People that know their business and can actually start playing and answer their own questions. So these technologies that gives more accessibility to the data, that gives some cataloging so we can understand where to go or where to find lineage and relationships. All this is basically the new type of platforms or tools that allow you to create what I call a data marketplace. So once you create that marketplace, they can play with it. And I was talking about new culture. And I'm going to finish with that idea. I think these new tools are really strong because they are now allowing for people that are not technology or IT people to be able to play with data because it comes in the digital world they are useful. I'll give you an example with all your stuff where you have a very interesting search functionality, where you want to find your data and you want to self serve, you go there in that search, and you actually go and look for your data. Everybody knows how to search in Google, everybody searching the internet. So this is part of the data culture, the digital culture, they know how to use those tools. Now similarly, that data marketplace is in Io-Tahoe, you can for example, see which data sources are mostly used. So when I'm doing an analysis, I see that police in my area are also using these sources so I trust those sources. We are a little bit like Amazon, when you might suggest you what next to buy, again this is the digital kind of culture where people very easily will understand. Similarly, you can actually like some type of data sets that are working, that's Facebook. So what I'm trying to say is you have some very easy user friendly technologies that allows you to understand how to interact with them. And then within the type of digital knowledge that you have, be able to self serve, play, collaborate with your peers, collaborate with the data query analysis. So its really enabling very easily that transition to become a data savvy without actually needing too much knowledge of IT, or coding, et cetera, et cetera. And I think that is a game changer as well. >> And enabling that speed that we're all demanding today during these unprecedented times. Gudron I wanted to go to you, as we talk about in the spirit of evolution, technology's changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >> Yeah, thank you. Well, Oracle Digital is a business unit at Oracle EMEA. And we focus on emerging countries, as well as low end enterprises in the mid market in more developed countries. And four years ago, they started with the idea to engage digital with our customers via central hubs across EMEA. That means engaging with video having conference calls, having a wall, agreeing wall, where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today. And this helps us to engage with our customers in the way we're already doing. And then about my team. The focus of my team is to have early stage conversations with our customers on digital transformation and innovation. And we also have a team of industry experts who engage with our customers and share expertise across EMEA. And we we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important. So we can help the customer and for the customer means that we will help them with our technology and our resources to achieve their goals. >> It's all about outcomes. Right Gudron? So in terms of automation, what are some of the things Oracle is doing there to help your clients leverage automation to improve agility so that they can innovate faster? Which on these interesting times it's demanding. >> Yeah. Thank you. Well, traditionally, Oracle is known for their databases, which has been innovated year over year since the first launch. And the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90%, with a multimodal converged database, and machine learning based automation for full lifecycle management. Our database is self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security and itself repairing the ultimate failure detection, failover and repair. And the question is for our customers, what does it mean? It means they can focus on their business instead of maintaining their infrastructure and their operations. >> That's absolutely critical. Yusef, I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that, but we know that whether we're talking about data management, or digital transformation. A one size fits all approach doesn't work to address the challenges that the business has. That the IT folks have. As you are looking to the industry, with what Santiago told us about First Bank of Nigeria, what are some of the changes that you're seeing that Io-Tahoe has seen throughout the industry? >> Well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data, where you have almost a data policeman who tells you what you can and cannot do just doesn't work anymore. It's too slow, it's too result intensive. Data Management, data governance, digital transformation itself, it has to be collaborative. And it has to be an element of personalization today to users. In the environment we find ourselves in now, it has to be about enabling self service as well. A one size fits all model when it comes to those things around data doesn't work. As Santiago was saying, it needs to be adaptive to how the data is used and who is using it. And in order to do this, companies, enterprises, organizations really need to know their data. They need to understand what data they hold, where it is, and what the sensitivity of it is. They can then in a more agile way, apply appropriate controls and access so that people themselves are in groups within businesses are agile and can innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >> Yet a one size fits all terms doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Yusef, talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do before. >> I guess one of the key ones is around. Just it's automatically being able to classify terabytes of data or even petabytes of data across different sources to find duplicates, which you can then remediate and delete. Now, with the capabilities that Io-Tahoe offers, and Oracle offers, you can do things not just with a five times or 10 times improvement, but it actually enables you to do project for stock that otherwise would fail, or you would just not be able to do. Classifying multi terabyte and multi petabyte estates across different sources, formats, very large volumes of data. In many scenarios, you just can't do that manually. We've worked with government departments. And the issues there as you'd expect are the result of fragmented data. There's a lot of different sources, there's a lot of different formats. And without these newer technologies to address it, with automation and machine learning, the project isn't doable. But now it is. And that could lead to a revolution in some of these businesses organizations. >> To enable that revolution now, there's got to be the right cultural mindset. And one, when Santiago was talking about those really kind of adopting that and I think, I always call that getting comfortably uncomfortable. But that's hard for organizations to do. The technology is here to enable that. But when you're talking with customers, how do you help them build the trust and the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive that kind of attack in the culture? >> It's really good question, because it can be quite scary. I think the first thing we'd start with is to say, look, the technology is here, with businesses like Io-Tahoe, unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting, being agile around it and trying new ways of doing things. If you don't want to get left behind. And Santiago, and the team at FBN, are a great example of embracing it, testing it on a small scale and then scaling up. At Io-Tahoe we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with the customer, pick a use case, install the application, analyze data, drive out some some quick wins. So we worked in the last few weeks of a large energy supplier. And in about 20 days, we were able to give them an accurate understanding of their critical data elements, help them apply data protection policies, minimize copies of the data, and work out what data they needed to delete to reduce their infrastructure spend. So it's about experimenting on that small scale, being agile, and then scaling up in a in a kind of very modern way. >> Great advice. Santiago, I'd like to go back to you. Is we kind of look at, again, that topic of culture, and the need to get that mindset there to facilitate these rapid changes. I want to understand kind of last question for you about how you're doing that. From a digital transformation perspective, we know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges that we're all going through? >> That's a really interesting transition, I would say. I was mentioning, just going back to some of the points before to transition these I said that the new technologies allowed us to discover the data in a new way to blog and see very quickly information, to have new models of (indistinct) data, we are talking about data (indistinct), and giving autonomy to our different data units. Well, from that autonomy, they can then compose and innovate their own ways. So for me now we're talking about resilience. Because, in a way autonomy and flexibility in our organization, in our data structure, we platform gives you resilience. The organizations and the business units that I have experienced in the pandemic, are working well, are those that actually, because they're not physically present anymore in the office, you need to give them their autonomy and let them actually engage on their own side and do their own job and trust them in a away. And as you give them that they start innovating, and they start having a really interesting idea. So autonomy and flexibility, I think, is a key component of the new infrastructure where you get the new reality that pandemic shows that yes, we used to be very kind of structure, policies, procedures, as they're important, but now we learn flexibility and adaptability at the same site. Now, when you have that, a key other components of resiliency is speed, of course, people want to access the data and access it fast and decide fast, especially changes are changing so quickly nowadays, that you need to be able to, interact and iterate with your information to answer your questions quickly. And coming back maybe to where Yusef was saying, I completely agree is about experimenting, and iterate. You will not get it right the first time, especially that the world is changing too fast. And we don't have answers already set for everything. So we need to just go play and have ideas fail, fail fast, and then learn and then go for the next. So, technology that allows you to be flexible, iterate, and in a very fast agile way continue will allow you to actually be resilient in the way because you're flexible, you adapt, you are agile and you continue answering questions as they come without having everything said in a stroke that is too hard. Now coming back to your idea about the culture is changing in employees and in customers. Our employees, our customers are more and more digital service. And in a way the pandemic has accelerated that. We had many branches of the bank that people used to go to ask for things now they cannot go. You need to, here in Europe with the lockdown you physically cannot be going to the branches and the shops that have been closed. So they had to use our mobile apps. And we have to go into the internet banking, which is great, because that was the acceleration we wanted. Similarly, our employees needed to work remotely. So they needed to engage with a digital platform. Now what that means, and this is, I think the really strong point for the cultural change for resilience is that more and more we have two type of connectivity that is happening with data. And I call it employees connecting to data. The session we're talking about, employees connecting with each other, the collaboration that Yusef was talking about, which is allowing people to share ideas, learn and innovate. Because the more you have platforms where people can actually find themselves and play with the data, they can bring ideas to the analysis. And then employees actually connecting to algorithms. And this is the other part that is really interesting. We also are a partner of Oracle. And Oracle (indistinct) is great, they have embedded within the transactional system, many algorithms that are allowing us to calculate as the transactions happen. What happened there is that when our customers engage with algorithms, and again, with Io-Tahoe as well, the machine learning that is there for speeding the automation of how you find your data allows you to create an alliance with the machine. The machine is there to actually in a way be your best friend, to actually have more volume of data calculated faster in a way to discover more variety. And then, we couldn't cope without being connected to these algorithms. And then, we'll finally get to the last connection I was saying is, the customers themselves engaging with the connecting with the data. I was saying they're more and more engaging with our app and our website and they're digitally serving. The expectation of the customer has changed. I work in a bank where the industry is completely challenged. You used to have people going to a branch, as I was saying, they cannot not only not go there, but they're even going from branch to digital to ask to now even wanting to have business services actually in every single app that they are using. So the data becomes a service for them. The data they want to see how they spend their money and the data of their transactions will tell them what is actually their spending is going well with their lifestyle. For example, we talk about a normal healthy person. I want to see that I'm standing, eating good food and the right handle, healthy environment where I'm mentally engaged. Now all these is metadata is knowing how to classify your data according to my values, my lifestyle, is algorithms I'm coming back to my three connections, is the algorithms that allow me to very quickly analyze that metadata. And actually my staff in the background, creating those understanding of the customer journey to give them service that they expect on a digital channel, which is actually allowing them to understand how they are engaging with financial services. >> Engagement is absolutely critical Santiago. Thank you for sharing that. I do want to wrap really quickly. Gudron one last question for you. Santiago talked about Oracle, you've talked about it a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle, what you guys are doing there to help your customers get the resilience that they have to have to be. To not just survive, but thrive. >> Yeah. Well, Oracle has a cloud offering for infrastructure, database, platform service, and the complete solutions offered at SaaS. And as Santiago also mentioned, we are using AI across our entire portfolio, and by this will help our customers to focus on their business innovation and capitalize on data by enabling your business models. And Oracle has a global coverage with our cloud regions. It's massively investing in innovating and expanding their cloud. And by offering cloud as public cloud in our data centers, and also as private clouds with clouded customer, we can meet every sovereignty and security requirement. And then this way, we help people to see data in new ways. We discover insights and unlock endless possibilities. And maybe one one of my takeaways is, if I speak with customers, I always tell them, you better start collecting your data now. We enable this by this like Io-Tahoe help us as well. If you collect your data now you are ready for tomorrow. You can never collect your data backwards. So that is my takeaway for today. >> You can't collect your data backwards. Excellent Gudron. Gentlemen, thank you for sharing all of your insights, very informative conversation. All right. This is theCUBE, the leader in live digital tech coverage. (upbeat music)

>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cube conversation. >>Hey, welcome back. You're ready, Jeffrey here with the Cuban Apollo Alto studios today, and we're excited. You know, we're slowly coming out of the, uh, out of the summer season. We're getting ready to jump back into the fall. Season, of course, is still covet. Everything is still digital. But you know, what we're seeing is a digital events allow a lot of things that you couldn't do in the physical space. Mainly get a lot more people to attend that don't have to get in airplanes and file over the country. So to preview this brand new inaugural event that's coming up in about a month, we have We have a new guest. He's Dave and Everen. He is the senior vice president of marketing. Former ran tous. Dave. Great to see you. >>Happy to be here today. Thank you. >>Yeah. So tell us about this inaugural event. You know, we did an event with Miranda's years ago. I had to look it up like 2014. 15. Open stack was hot and you guys sponsored a community event in the Bay Area because the open stack events used to move all over the country each and every year. But you guys said, and the top one here in the Bay Area. But now you're launching something brand new based on some new activity that you guys have been up to over the last several months. So let us give us give us the word. >>Yeah, absolutely. So we definitely have been organizing community events in a variety of open source communities over the years. And, you know, we saw really, really good success with with the Cube And are those events in opens tax Silicon Valley days? And, you know, with the way things have gone this year, we've really seen that virtual events could be very successful and provide a new, maybe slightly different form of engagement but still very high level of engagement for our guests and eso. We're excited to put this together and invite the entire cloud native industry to join us and learn about some of the things that Mantis has been working on in recent months. A zwelling as some of the interesting things that are going on in the Cloud native and kubernetes community >>Great. So it's the inaugural event is called Moran Sous launchpad 2020. The Wares and the Winds in September 16th. So we're about a month away and it's all online is their registration. Costars is free for the community. >>It's absolutely free. Eso everyone is welcome to attend You. Just visit Miranda's dot com and you'll see the info for registering for the event and we'd love it. We love to see you there. It's gonna be a fantastic event. We have multiple tracks catering to developers, operators, general industry. Um, you know, participants in the community and eso we'd be happy to see you on join us on and learn about some of the some of the things we're working on. >>That's awesome. So let's back up a step for people that have been paying as close attention as they might have. Right? So you guys purchase, um, assets from Docker at the end of last year, really taken over there, they're they're kind of enterprise solutions, and you've been doing some work with that. Now, what's interesting is we we cover docker con, um, A couple of months ago, a couple three months ago. Time time moves fast. They had a tremendously successful digital event. 70,000 registrants, people coming from all over the world. I think they're physical. Event used to be like four or 5000 people at the peak, maybe 6000 Really tremendous success. But a lot of that success was driven, really by the by the strength of the community. The docker community is so passionate. And what struck me about that event is this is not the first time these people get together. You know, this is not ah, once a year, kind of sharing of information and sharing ideas, but kind of the passion and and the friendships and the sharing of information is so, so good. You know, it's a super or, um, rich development community. You guys have really now taken advantage of that. But you're doing your Miranda's thing. You're bringing your own technology to it and really taking it to more of an enterprise solution. So I wonder if you can kind of walk people through the process of, you know, you have the acquisition late last year. You guys been hard at work. What are we gonna see on September 16. >>Sure, absolutely. And, you know, just thio Give credit Thio Docker for putting on an amazing event with Dr Khan this year. Uh, you know, you mentioned 70,000 registrants. That's an astounding number. And you know, it really is a testament thio. You know, the community that they've built over the years and continue to serve eso We're really, really happy for Docker as they kind of move into, you know, the next the next path in their journey and, you know, focus more on the developer oriented, um, solution and go to market. So, uh, they did a fantastic job with the event. And, you know, I think that they continue toe connect with their community throughout the year on That's part of what drives What drove so many attendees to the event assed faras our our history and progress with with Dr Enterprise eso. As you mentioned mid November last year, we did acquire Doctor Enterprise assets from Docker Inc and, um, right away we noticed tremendous synergy in our product road maps and even in the in the team's eso that came together really, really quickly and we started executing on a Siris of releases. Um that are starting Thio, you know, be introduced into the market. Um, you know, one was introduced in late May and that was the first major release of Dr Enterprise produced exclusively by more antis. And we're going to announce at the launch pad 2020 event. Our next major release of the Doctor Enterprise Technology, which will for the first time include kubernetes related in life cycle management related technology from Mirant is eso. It's a huge milestone for our company. Huge benefit Thio our customers on and the broader user community around Dr Enterprise. We're super excited. Thio provide a lot of a lot of compelling and detailed content around the new technology that will be announcing at the event. >>So I'm looking at the at the website with with the agenda and there's a little teaser here right in the middle of the spaceship Docker Enterprise Container Cloud. So, um, and I glanced into you got a great little layout, five tracks, keynote track D container track operations and I t developer track and keep track. But I did. I went ahead and clicked on the keynote track and I see the big reveal so I love the opening keynote at at 8 a.m. On the 76 on the September 16th is right. Um, I, Enel CEO who have had on many, many times, has the big reveal Docker Enterprise Container Cloud. So without stealing any thunder, uh, can you give us any any little inside inside baseball on on what people should expect or what they can get excited about for that big announcement? >>Sure, absolutely so I definitely don't want to steal any thunder from Adrian, our CEO. But you know, we did include a few Easter eggs, so to speak, in the website on Dr Enterprise. Container Cloud is absolutely the biggest story out of the bunch eso that's visible on the on the rocket ship as you noticed, and in the agenda it will be revealed during Adrian's keynote, and every every word in the product name is important, right? So Dr Enterprise, based on Dr Enterprise Platform Container Cloud and there's the new word in there really is Cloud eso. I think, um, people are going to be surprised at the groundbreaking territory that were forging with with this release along the lines of a cloud experience and what we are going to provide to not only I t operations and the Op Graders and Dev ops for cloud environment, but also for the developers and the experience that we could bring to developers As they become more dependent on kubernetes and get more hands on with kubernetes. We think that we're going thio provide ah lot of ways for them to be more empowered with kubernetes while at the same time lowering the bar, the bar or the barrier of entry for kubernetes. As many enterprises have have told us that you know kubernetes can be difficult for the broader developer community inside the organization Thio interact with right? So this is, uh, you know, a strategic underpinning of our our product strategy. And this is really the first step in a non going launch of technologies that we're going to make bigger netease easier for developing. >>I was gonna say the other Easter egg that's all over the agenda, as I'm just kind of looking through the agenda. It's kubernetes on 80 infrastructure multi cloud kubernetes Miranda's open stack on kubernetes. So Goober Netease plays a huge part and you know, we talk a lot about kubernetes at all the events that we cover. But as you said, kind of the new theme that we're hearing a little bit more Morris is the difficulty and actually managing it so looking, kind of beyond the actual technology to the operations and the execution in production. And it sounds like you guys might have a few things up your sleeve to help people be more successful in in and actually kubernetes in production. >>Yeah, absolutely. So, uh, kubernetes is the focus of most of the companies in our space. Obviously, we think that we have some ideas for how we can, you know, really begin thio enable enable it to fulfill its promise as the operating system for the cloud eso. If we think about the ecosystem that's formed around kubernetes, uh, you know, it's it's now really being held back on Lee by adoption user adoption. And so that's where our focus in our product strategy really lives is around. How can we accelerate the move to kubernetes and accelerate the move to cloud native applications on? But in order to provide that acceleration catalyst, you need to be able to address the needs of not only the operators and make their lives easier while still giving them the tools they need for things like policy enforcement and operational insights. At the same time, Foster, you know, a grassroots, um, upswell of developer adoption within their company on bond Really help the I t. Operations team serve their customers the developers more effectively. >>Well, Dave, it sounds like a great event. We we had a great time covering those open stack events with you guys. We've covered the doctor events for years and years and years. Eso super engaged community and and thanks for, you know, inviting us back Thio to cover this inaugural event as well. So it should be terrific. Everyone just go to Miranda's dot com. The big pop up Will will jump up. You just click on the button and you can see the full agenda on get ready for about a month from now. When when the big reveal, September 16th will happen. Well, Dave, thanks for sharing this quick update with us. And I'm sure we're talking a lot more between now in, uh, in the 16 because I know there's a cube track in there, so we look forward to interview in our are our guests is part of the part of the program. >>Absolutely. Eso welcome everyone. Join us at the event and, uh, you know, stay tuned for the big reveal. >>Everybody loves a big reveal. All right, well, thanks a lot, Dave. So he's Dave. I'm Jeff. You're watching the Cube. Thanks for watching. We'll see you next time.

>>live from Atlanta, Georgia. It's the Q covering answerable best 2019. Brought to you by Red hat. >>Hey, welcome back to the Cuban Live coverage in simple fest. Two days of coverage. Day one, wrapping up. I'm John forwards. Accused Too many men. My guest co host today, our next two guests at his van. Van Velzen. Okay, welcome to the Cube. You're an engineer at I n G Bank and Robert de Bock, product owner, engineer I n g. Bank. Hey, guys, Thanks for coming on. Thank you. Have the practitioner on. Well, first of all, we have a lot of great feedback from the practitioners here. And also people in deploying answerable and other other cool Dev ops Tools on automation is at the top of the list. Yes, More efficient. Getting things done. Focus. You got satisfaction in job because things go awaiting time savings. I'm saving security drives a conversation and re skilling opportunities. Love. These are cutting edge. Things you got to do is take a minute to explain what you guys do. What a night. What a night. Angie bank. >>Yeah. I work in a team that provides redhead images for other teams. in 90 to consume to use two insane she ate way. Also live from playbooks, amendable code and rolls to manage those things. And he's very scattered, which sort of decentralized, which is a good thing. In my opinion, it's ready for scaling. In that case, I used to work with Dennis are lots in the tower team, so take it away. >>Okay, so I still work at the answer, built our squad What we do, it's ah, We make sure that the instable tower service keeps running 24 7 and we also ensure that we, uh, provide updates next to all this. We also have unanswerable community where we basically support our end users, which are their love. So, uh, from some numbers, I heard we have 1200 applications teams that are using our service. Um, and they all have, like, answerable playbook, sensible rolls, questions, difficulties with, uh, with anything. And we're basically there to support them as well. >>So 1200 teams are using answerable, Yes, inside the bank. Yes. Yeah, like >>it's set up very decentralized. And I think what I hear from instable fest that is not very common. I still think it's very good thing to do. We try to basically give these teams all the tools they need to do their stuff on. What I hear hear mostly is that there's essential team off administrators pushing the buttons for them. Towers. Great answer was great in that case, I think, for our case is really it's a perfect fit. >>E guess help Explain. Is this do you provide? You know, he said it's not centralized, but is this you know, here's best practices here. Some play boat out. How do you end? You support them? Because they're a little bit those relationships. >>Okay. Okay. Um so what we do is we basically all the rules and get ah ah, good lap. So it's an own premise. Get environment. You can search in this. Get for rules. Uh, not like all rules are easily to be found when searching for them. So that's why there are these communities to share what you have made. Um, >>plus these teams, they can themselves pick and choose. Some will try to rewrite everything That's fine. Others can can benefit from existing coat, so it's just a good trick. Thio enable these team to participate on it really different. Some people make it all themselves another >>next to this. So we basically have these 12 on the teams do their own thing. But next to this, we also have a self service portal where they can choose, like from, uh, generic finks like us. But your machine at new disc. So New capacity Cp use memory. That's all being done through a portal s so they don't need to do anything on their own for this they can, but most of them choose the easy way off using this portal. This portal basically doesn't a vehicle to instable tower, which executes a sensible playbook and some other stuffs. Maybe some AP eyes. And this is one of the things you guys create A manage these books. So, um >>and if you go back in time so the alternative way, which we happily got rid off, is to do it ourselves. I think it was before we we work together. Way had batch weekends, for example, and it >>was no very different. No life. Oh, that's working on weekends, >>weekends and, for example, he used to patch machine some 10,000 or so, and we were not aware what was important. What? Not so you you'd stop the whole pitch. Oh, this machine has a problem. Let's stop everything in focus and that's >>not important. Was like a complete order. >>And the other way around Also this machine. I guess it's not that important. Let's just >>continue this >>Sunday morning. Oh, my God. Everything's broken. >>Can you give us a little flavor of kind of the spectrum of solutions that you leverage answerable on >>tap? Yeah. We, uh I think what we see Moses for Lennox machines, eso fetching is a big one. We got a second operation, so there's a few of them. The deployment also depends on and small. So if you order a new machine, answer was involved somewhere to do to make it happen on network on board and the Windows teams are very interested. I'm not sure if we notice on board yet. To >>be honest, I know we did some book in the boss so a couple of months ago, using wind around when you needed set on policies there, But you can see that the networking teams were getting more momentum. Uh, five. There's some suffer suffer to find switches Bob. I don't know. The, uh Never mind the name, but ah, you can see some momentum in the in the networking. Uh, it's not Morgan departments >>configuration network networking with the activists. So that's where the action is in the >>network. Um, there were some cool talks also here on five workshops. So you can see there is, um, that there is some attention on these modules and integrations as well. >>What's your guy's goal here for the show? What brought you here? I'll see Big user. >>Yeah. So what do you think was like sharing our own thing? We did. They talk this morning. Ah, regarding and programming A really cool we wanted to share. It is this behavioral thing, and and >>we'll talk about take a minute and programming. >>So, um, basically, it's, ah programming with the whole team and making sure that you get something done with all the knowledge in the team. So you don't have to align off the words or if some other if you're Kulik says from basically session, you can do better using this staying. It's all, um it's It's all done during the decision >>as basically a good way to get a team up to speed. So in a team that's probably a few few people that are very quick and understand the concept and few starters or so So >>you guys decentralized, which makes sense for scale. I get that. So this sounds like you can operate decentralized, but where danceable. You can still have that common a book Switch >>teams, for example. So it used to be very specific. H team would have their own type of coat. Now that more answers used people can switch a little easier to to another product of surface because the languages have lied, shared, steal it, steal. It's quite >>well happy with this, right? I am. I really, really have to work on the weekend. That's good. I think >>the good thing is that you have one generic way of working. So his playbook is readable by all engineers. And if you want to learn this thing, you just do the inevitable course. So you know what this thing is? A mosque and roll, and it's all like >>way. We do see horrible >>koto. Come on, don't throw your college under the bus. But here's the international tough question can see is what we have been here. I want you guys to test this. We hear that there's a lot of time savings involved. Yes, with answer. True or false. That's true order of magnitude. What? What kind of saving way talking about? I >>think it depends on the thing because we saw a huge I don't know, except numbers. But this this os patching that Really? Really Uh, >>yes. Now, especially waas. Two people working a full time basically collecting, who needs to do what? The win. And then for a weekend, 10 15 people or so. So, uh, that's reduced now to sort of nothing. Yes, some maintenance to that playbook and roll. But I mean, yeah, it's difficult to express what message? So >>no one's getting phone call? Hey, come in on the weekend. So 15 people on the weekend jam and then to Fulton will just managing it all Go away. >>Yeah, not needed, but not needed. But they basically they can do something else, so those people are still there. But now they're not doing Os patching and doing all the excel sheets and keeping order off. The systems are important, and this shall be the first, and then they because way are basically doing the thing they know better. This application team knows their dependency, so they know they. But first I need to patch the database machine and then there during the front end or Andi. It's difficult to do this so they do it themselves. >>That's Dev Ops. That's that's the way it's supposed to be, right? >>So you've matured this thes deployments over time. As you look back, What key learnings do you have that maybe you'd recommend to your peers toe? You know how things could run a little bit smoother >>next time, a good amount of time. So they're stools. That's not the problem, So answer is great, but there's others to their great Give it time to sink in with the people. So you start something and you have to have a pretty strong team to do the long the long stretch with it and give it some time, maybe a year or so before everyone's on board it. In our case, in the beginning, we spend lots of time on this community model where we basically organized small meet ups or get together, too, show things or to hear problems and try to express them. That really helped a lot. And by now it's starting to get normal, more normal. So all the teams do sensible, basically. And problem starts slowly disappearing. Also. So So >>one of the things, um, that will be better. Probably in our scenario. Housekeeping metrics. So what are the improvements over time? I don't know how to measure this. No, no, no aspect. But it will be better if you had, like, better numbers like we did hair Very good. Or this is something like, what did the community thing bring way indirectly what the results are Because the engineers are doing things really, really things. They're really patching the replication. And they're really, um, restarting their own machines, for example, when there is something wrong. Whatever. Um, but our days related to our community thing or all that's really related to Sensible Tower >>last. I think we we are very technical focus. So So we like it as a nerd, so to say, to do things but what the business value is, for example, I'm not so interested or less interested so way typically, like the technology, so it could be good to have some someone onboard and your team that says, Yeah, but this is the problem. It's crossed. This amount of money and that solved now are improved. >>Well, they assume the applications are doing a good job. So you guys helped those guys out. They get to do their own thing. They do the heavy lifting. They're doing the coding anyway for those guys that were coming in managing full time on the 15 or so on the weekend. What are they doing now? >>Most are spread across. All the application teams go back. But the other side there is now it's our team that was not there s. So that's the price you have to pay. And that's a serious team. I mean, it's far six people now 86 people and 100 machines or so. So it is a serious amount of time, but it makes it at least much more constant. So people are not surprised by machines being patched, and Monday they come back into the half broken or so. So it's a lot more control now, so I don't know if you can express it in price, but at least it's more stable >>more consistent. >>Well, one of the things that we hear here and I want to get your thoughts as we wrap up is as you go forward, you got answerable 1200 teams using it. You got a lot of collaboration. The work cultures change. Sounds like a shower. Team steps service everything else. So some scale building out what's next? Because as it becomes a platform. Okay, you have to enable something. There has value there. Okay, technical nerd value and then business value >>scaling, uh, because we continuously see this thing growing like more application teams are adapting answerable, invincible tower. So, um, right now we have, like, a cluster. We have different clusters running. Go into much detail, but we can see that the load is getting higher and higher, so we need to skill. Um, and this is sort of difficult, but red. That is really supporting in this because they're going to change some things at the application level two to allow scaling even better. Um, >>plus, also, for most teams, they're starting their configuration. Everything is coat process. They're not there yet. As soon as they discover the power of it, I'm sure that's being used a lot. A lot more. And plus, there's other countries that are going to be connected. So you have a lot of work >>because your engineering doing some getting down and dirty with the code, automating everything. >>Yeah. Yeah. So, um, what else do we >>Oh, what's the coolest thing you've done that you've automated? >>Uh >>uh, Pick your favorite. >>So but the child during Encircle Tower and with answerable, um, let me think about this. >>I I really like the patching that saved us so much work. And, uh, I think also one of the next goes to make much more simpler. So we as a company, we're complex and the people also like complexity. That's wrong. We should change >>that. Patching up our >>offense, Melissa Simplicity. So we should really use that. >>You don't want any open holes in the network housely and assistance >>about your previous question. Like I have sort of a finger and all these small things. So it's sort of what I did. It's more like an A team thing. We created the OS patch playbooks, the configure stuff, the second day offs. So we did this as a team >>like sports but the playbooks together run the play. Some defense on security >>and programming. So you're doing >>this as a team, which is very cool. Has a scoreboard look good? Winning? >>Yeah, Yeah, yeah, yeah. We're looking at the graphite. Uh, it's girl. >>Final question. How you enjoying the show here? Having a good time? What's the vibe here? What's it like here? Share for the people who aren't here. What's going on? What's the vibe with >>a conversation? It's great. We went to some sessions yesterday really technical stuff with developers. And this was really amazing because you heard details that that are not in the India in the talks today and tomorrow. Um, yeah, it's great. It's great community. It's just I really I really enjoy it because you can. It's You can have, like one on one conversations go into depth. I was showing something I created, and this guy's we'll hold. This is really great in the It's cool. It's just if you it's really great. It's really >>cool. Really? Yeah, for me also, it feels like coming home, So I know these people and I think the first day, the collaboration day, what's it called and I'm not sure you community, that's it's great because it's been a bit rough and unpolished in today's more polished and more presented and prepared to, uh, both are great. >>Good. Give the hard feedback. >>Yeah, you meet all the people. So, for example, I used instable a lot, and then I'm getting up. I see all these names. Like, who would that be there walking here and shake hands like, Oh, that's >>why guys like your code looking good. Yeah. Looks good. A contributor. Summit contributed. Okay. Sorry. After it for >>anyone that goes to visit that day, too. That's just great. >>It's great to see people face to face that, you know, online for their digital identity or the code >>you can You can't complain about stuff out on. Do you know that you don't hurt them or something with just commenting on get like after this issue and this issue and this issue. Then you can see them in person. And then you >>him a high five assault, you know? Hey, >>it's really very cool. >>Guys. Great conversations were coming on cue. Thanks, Dennis. Appreciate Robert. Thanks for coming on. Skew coverage here Day one of two days of live coverage here inside the Cube here in Atlanta, Georgia for Ansel Fest is the cute I'm John 1st 2 minute. Thanks for watching.

>> Announcer: From the Cosmopolitan Hotel in Las Vegas, Nevada, it's theCUBE. Covering Coupa Inspire 2019, brought to you by Coupa. >> Welcome to theCUBE, at Coupa Inspire '19. I'm Lisa Martin on the ground, at the Cosmopolitan in Las Vegas, and we're pleased to welcome to theCUBE Michael Van Keulen, Global Procurement Director of Lululemon Athletica. Michael, welcome to theCUBE. >> Thank you. >> I'm a big Lulu fan, have been for many, many years. If anybody doesn't know Lululemon, this is a three plus billion dollar designer, distributor, and retailer of really cool technical athletic apparel. You've been there for a few years now, came from a finance background. One of the things that I love about Lululemon is the inspirational messages on the bags. Anytime I'm in a grocery store and you have to bring your own bags, and I'm nearsighted and I can spot a Lululemon bag from a mile away. Talk to us about just one of the examples of this procurement transformation that you helped initiate, when you came in and found something really interesting about this iconic bag. >> Sure, yeah, so when I joined the company you start to do your basic spend cube analysis and trying to figure out where the big spend items are. And given that the bag is so visible for everybody, I figured that's really a big volume, lots of spend, very visible, and very important to our business. So I started to dig in to our shopping bag as a category. And I uncovered that it was single-sourced with one factory in Cambodia, with a nine month lead time. But nobody in the company really knew that. So when I was put in front of our senior executives to talk about where do I feel there's opportunity, there was some pushback on me digging into our shopper and there was even perspective in the senior executive teams that I didn't really understand how important our shopper is. And then when I asked the question, where does the shopper come from? Where is it made? How is it made? What's the lead time? What's the cost? There were lots of unknowns, and when I threw that on the table and said, "Well, it's single-sourced, "one factory, in Cambodia", you could immediately see a lot of people going like, "Wow, that's very interesting." And they started to realize that procurement is not just about saving money, which we also did, but it's also about de-risking our supply chain, being more nimble and more agile. >> Yes, I was going to say that what you discovered was a massive risk to the brand. I think the bag, is the number one brand asset? >> Michael: Totally. >> It's very visible. But that was really the tip of the iceberg of some of the things you came in saying, "You know, as procurement, "there is a massive, massive, many massive, "impact elements that it can have on the business." >> Michael: Right. >> So going from sort of a tactical to a strategic approach. How was the bag, as an example, able to start helping you transform the culture of Lulu to be more strategic and start looking at all of the other ways in which this business can derive value from a number of the other elements besides the bag. >> Yeah, so we started to identify, what are some of our core principles when it comes to how we source, and how we procure. Those are things to me, like fact-based decision making, analytics, knowing what you buy, how you buy, where you buy, competitive pressure, making sure the suppliers realize that we have options in the marketplace. I mean, those are some of the key components of running a competitive department that drives a competitive advantage. And that's really what we focus on at Lululemon in procurement. >> Some of the disruptors that we see in procurement and finance today are consumerization. Rob Bernstein talked about it this morning with some of the things that Coupa is now doing with the Amazon Marketplace. But as consumers, whether we're consuming Lululemon products or software, we have choice. We also have this expectation that we can go somewhere and find anybody that's selling this particular product, I can see the prices, I can see, the pricing pressures put on, I can see all the different suppliers. So the consumerization sort of disruptor, is really interesting to every industry. How are you leveraging that to, to really drive much more value. Not just saving costs, but even things like impacting shareholder value for Lulu? >> Yeah, I think table stakes today is just managing spend, right? Knowing where your money goes, and trying to make sure that we stretch the dollars as much as we can, I think is what every procurement function does. I think what distinguishes the world class from the let's say, the middle of the pack, is are you able to contribute to top-line growth? How are you able to innovate? Are you able to innovate through your suppliers? And so one example, this is how we implemented third-party gift cards at many grocers across North America. That was an idea generating from procurement, tying into gift cards that we already source and that we now have third-party gift cards at the Kroeger's and the likes. That just drive more traffic to our stores. And that's just through a really exciting, cool idea, that wouldn't necessarily come from a procurement, traditional procurement function, but one that really wants to contribute to future growth. >> One that wants to contribute to future growth, that has a strategic vision. When we look at the Coupa community, there's now $1.2 trillion of transactions going through that. There's a tremendous amount of data, and we go to so many conferences at theCUBE every year, and we hear very commonly, data is the new oil. >> Michael: Totally. >> Data is gold. It is those things if you have the right, if you have visibility and the opportunity to extract value from it and act on it immediately. Talk to me a little bit more about the third-party gift card approach, and was that something that you said we have so much more visibility, into our data, into our consumers, into our suppliers. There's an obvious low-hanging fruit opportunity here. How did that data help you make that decision? >> Yeah, no this was more an idea where you start to look at what value can procurement drive other than just managing and reducing cost? And every other big apparel retailer is already in this third-party space and Lululemon is not. And the power of our company is we are vertically integrated. You can only buy our product at Lululemon, and some select strategic partners. But opening up the doors for people to be experiencing our brand in a different way, through purchasing a gift card or being gifted a gift card, I should say, and that audience then now comes into our store. It just could potentially be a completely new guest. And that is what is super exciting. >> So let's talk about some of the business impact of that. So, I would like to be on the receiving end of the Lulu gift card, for anybody who's watching my birthday's in March. (Michael laughing) But in terms of what are some of the things that you've seen map back to top line impact from that. Increase in new customers acquired, increase in customer lifetime value, what are some of those big impacts that procurement has made with what seems like an, aha, this is a simple idea, we should be doing this too. >> I think what Lululemon does better than any retailer on the planet is our educators. Right, our educators in our stores. And so, it's my job is how do I set these guys up for success? So I think one way we're now doing and leveraging the Coupa platform, is taking away administrative complexity. So the lesser the administrative burden is on our stores and our educators, the better they are with engaging with our guests. And educating them on our product, why we make it, what it does, so that our consumers that we call guests, ultimately, not just make the transaction, but also buy the right product, they know what the product is supposed to do for them. And how it's supposed to fit and how it's supposed to help them in their daily lives. And so what procurement really does is just take away that complexity that they have today, so that they can focus on what they do best. >> So walk me through who within, so one of the things that Coupa does, is more than I think any of their competitors, is it's procurement, it's invoices, expenses, payments. Tell me about all the different ways in which Lululemon is leveraging Coupa and walk me through kind of an average user experience. This is somebody, like an individual contributor in marketing or finance. Give me a little bit of a taste of that. >> Yeah, so we use Coupa for sourcing, contracting, requisitioning, purchase orders, and then flip that PO into pay, so we use the full suite of solution. The biggest focus for us is on the downstream, as we call, Procure to Pay. So it's a lot of people placing requisitions, and that can be in marketing, it could be in the store, it could be in any part of our business, really. And the downstream is the most important element, because that's where the visibility comes. And then from a procurement standpoint, we use the Sourcing and the CLM platform. But the downstream is where the magic happens. >> So is every business unit within Lululemon on the Coupa platform? >> So we launched North America on February 4th, we're live in 18 stores as a pilot, and we're going to roll out all of North America, the entire fleet, in August. >> So just February of 2019, so just what, five months or so ago. And the impact to the business that you've seen with just these first 18 stores? >> Yeah, it's not just the 18 stores, it's inclusive of our head office and our distribution centers in North America. We just now focus on supplier enablement, more suppliers on the platform, more spend through the portal, and with the stores it's a pilot. It's going really well and if the stores are going to get it I'm pretty sure they will be very pleased. >> So, we talked about kind of the consumer, the guest experience, supplier centricity. What have you achieved with respect to supplier centricity, using Coupa, and how is that affecting everybody up to the C-suite in your organization in terms of, wow, procurement is really a business engine, here we do invest in. >> Yeah I think our, if you look at our journey when we started three years ago where we literally had no real procurement as it is described today, we're still in that journey of maximizing our supplier relationships. And through our supplier relationships, really drive innovation. I think we're not entirely there yet, I think that is one of the next iterations, is how do we take procurement to the next level. >> And if you look back at the last few years, what surprises you about coming from a finance background, now being in charge of procurement for a major global brand. What are some of the things that surprise you about this future of procurement and where Lululemon is setup to be successful? >> I think the biggest surprise is that people never intentionally do business with a company that we may or we should be doing business with. People never intentionally do that, it's just because they don't ask the right questions around ownership structure and risk and sustainability, and reputational risk and environmental risk, and just cost aside. And what I think what procurement helps to do is to actually ask all those questions. So that we end up with the right company, with the right pricing, the right quality, the right specs, the right everything. I think that's what surprised me, is that missing link that procurement brings to the table. >> So if you had to give your peers, in any industry, some advice would it be first of all, help establish a culture that is willing to ask questions. 'Cause there's that whole thing too, right? We always think, well maybe it's a dumb question. Have that culture that is, no question is a dumb question, ask, ask, ask. >> Yeah and Lulu is, fortunately enough, such a young company so I had a lot of great stakeholders, I still have them today, that are highly supportive. It's never just me or my team, it is collaboration, it's cross-functional. Everybody has to have something in it, right? So Lulu's a very young company. So if you're a very, maybe mature organization where people are set in their ways it just becomes a little. So I used to work for VF Corps, which is a slightly more mature, been around for 100 years. There it required more convincing than maybe at Lululemon where, again, people are just, the population is much younger. And we needed more structure and people recognized that. >> The appetite was there. >> The appetite was there, for sure. >> Last question for you, Michael. Some of the things that are being announced this week at Inspire, we heard this morning about, we mentioned a minute ago about the size of the Coupa community. The amount of data, the value that it's driving for customers and for suppliers. Also they talked about this Amazon Marketplace that they're expanding this relationship so that IT folks can have this full suite of visibility. What excites you most about the direction that Coupa is going in? >> I mean, it's the data, it's the native integrations with Amazon and the likes, absolutely. What excites me the most in terms of the different modules is Coupa Pay. I've been wanting to go after dynamic discounting, that's what Coupa Pay is going to enable us to do. Virtual pay is another big opportunity where we can start flowing a lot of our payments through a virtual payment system, our payment cards, that excites me. But it's the data, and it's how do we as a community start to leverage our spend, I think will be absolutely awesome. I look forward to that. >> Yes and that collaborative spirit this morning was really palpable. Well, Michael it's been a pleasure to have you on theCUBE today. >> Thank you. >> Congratulations on what you've done at Lulu, and for Lulu being a Coupa Spendsetter. >> Thank you. >> For Michael Van Keulen, I'm Lisa Martin, you're watching theCUBE from Coupa Inspire '19, thanks for watching. (upbeat techno music)

>> Female Voice: From San Francisco, it's theCUBE, covering VMware RADIO 2019, brought to you by VMware. >> Welcome to theCUBE's exclusive coverage of VMware RADIO 2019, Lisa Martin with John Furrier in San Francisco, talking all sorts of innovation in this innovation long history culture at VMware, welcoming back to theCUBE, Mornay Van Der Walt, VP of R&D in the Explorer Group. Mornay, thank you for joining John and me on theCUBE today. >> Thank you for having me. >> So, I got to start with Explorer Group. Super cool name. >> Yeah. >> What is that within R&D? >> So the origins of the Explorer Group. I've had many roles at VMware, and I've been fortunate enough to do a little bit of everything. Technical marketing; product development; business development; one of the big things I did before the Explorer group was created was actually EVO:RAIL. I was the founder of that, pitched that idea. Raghu and Ray and Pat were very supportive. We took that to market, took it to (inaudible), handed that off to Dell EMC, the rest is history, right? And then was, "what's next?" So Ray and me look at some special projects, go and look at IoT, go and look at Telemetry, and did some orders for them, and then said "Alright, why don't you look at all our innovation programs." Because beyond RADIO, we actually have four other programs. And everyone, was -- RADIO gets a lot of airtime and press, but it's really the collective. It's the power of those other four programs that support RADIO that allow us to take an idea from inception to an impactful outcome. So hence the name, the Explorer Group. We're going out there, we're exploring for new ideas, new technologies, what's happening in the market. >> Talk about the R&D management style. You've actually got all these-- RADIO's one-- kind of a celebration, it's kind of the best of the best come together, with papers and submissions. Kind of a symposium meets kind of a, you know, successive end for all the top engineers. There's more, as you've mentioned. How does all of it work? Because, in this modern era of distributed teams, decentralization, decisions around business, decisions on allocating to the portfolio, what gets invested, money, spend, how do you organize? Give a quick minute to explain how R&D is structured. >> So, obviously, we have the BUs structured-- well there's PCS, Raghu and Rajeev head that up. And then we've got the OCTO organization, which Ray O'Farrell heads up. And the business, you know, it's innovating every day to get products out the door, right, and that's something that we've got to be mindful of because, I mean, that's ultimately what's allowing us to get products into the hands of our customers, solving tough problems. But then in addition to that, we want to give our engineers an avenue to go and explore, and, you know, tinker on something that's maybe related to their day job, or completely off, unrelated to their day job. The other thing that's important is, we also want to give, because we're such a global R&D, you know, our setup globally, we want to give teams the opportunity to work together, collaborate together, get that diversity of thought going, and so a lot of times, if we do a Hackathon, which we call a Borathon, we actually give bonus points if teams pull from outside of their business units. So you've got an idea, well, let's make it a diverse idea in terms of thought and perspective. If you're from the storage business unit, bring in folks from the network business unit. Bring in folks from the cloud business unit. Maybe you've partnered with some folks that are in IT. It's very, you know, sometimes engineers will go, "Ah, it's just R&D that's innovating." But in reality, there's great innovation coming out of our IT department. There's great innovation coming out of our global support organization. Our SEs that are on the front lines, sometimes are seeing the customers' pain points firsthand, and then they bring that back, and some of that makes it into the product. >> How much of R&D is applied R&D, which is kind of business unit aligned, or somewhat aligned, versus the wacky, crazy ideas: "Go solve a big, hairy problem", that's out there, that's not, kind of, related to the current product sets? >> Ah, that's tough to put an actual number on it, >> John: Well ballpark, I mean. >> But if I just say, like, if I had to just think about budgets and that, it's probably ten to fifteen percent is the wacky stuff, that's, you know, not tied to a roadmap, that's why we call it "off-road innovation", and the five programs that my Explorer Group ultimately leads is all about driving that off-road innovation. And eventually you want to find an on-ramp, >> Yeah. >> to a roadmap, you know, that's aligned to a business unit, or a new emerging, you know, technology. >> How does someone come up with an idea and say, "Hey, you know, I want to do this"? Do they submit, like, a form? Is there a proposal? Who approves it? I mean, do you get involved? How does that process work? >> So that's a good question. It really depends on the engineer, right? You take someone who's just a new college grad, straight out of, you know, college. That's why we have these five programs. Because some of these folks, they've got a good idea, but they don't really know how to frame it, pitch it. And so if you've got a good idea, and let's say, this is your first rodeo, so to speak, We have a program called TechTalks where it allows you to actually go and pitch your idea; get some feedback. And that's sometimes where you get the best feedback, because you go and, you know, present your idea, and somebody will come back and say, "Well, you know, have you met, you know, Johnny and Sue over there, in this group? They're actually working on something similar. You should go and talk to them, maybe you guys can bring your ideas together." Folks that are, you know, more seasoned, you know, longer tenure, sometimes they just come up, and-- "I'm going to pitch an idea to xLabs," and for xLabs, for example --that's an internal incubator-- there is, like, a submissions process. We want to obviously make sure, that, you know, your idea's timing in the market's correct, we've got limited funding there so we're going to make sure we're really investing on the right, you know, type of ideas. But if you don't want to go and pitch your idea and get feedback, go and do a Borathon. Turn an idea into a little prototype. And we see a lot of that happening, and some of the greatest ideas are coming from our Borathons, you know? And it's also about tracking the journey. So, we have RADIO here today, we have mentioned xLabs, TechTalks, we have another program called Flings. Some of our engineers are shipping product, and they've got an idea to augment the product. They put it out as a Fling, and our customers and the ecosystem download these, and it augments the product. And then we get great feedback. And then that makes it back into the product roadmap. So there's a lot of different ways to do it, and RADIO, the process for RADIO, there's a lot of rigor in it. It's, like, it's run as a research program. >> Lisa: It's a call for papers, right? >> Call for papers, you know, there's a strict format, it's got to be, you know, this many pages; if you go over about one line, you're sort of, disqualified, so to speak. And then once you've got those papers, like this year we had 560 papers be submitted, out of those 560, 31 made it onto mainstage, and another 61 made it as posters, as you can see in the room we're sitting in. >> I have an idea. Machine learning should get all those papers. (laughs) I mean, that's-- >> Funny you say that. We actually have, one of our engineers, Josh Simons, is actually using machine learning to go back in time and look at all the submissions. So idea harvesting is something we're paying a lot of attention to, because you submit an idea, >> Interesting. >> the market may not be right for it, or reality is, I just don't have a budget to fund it if it's an xLab. >> John: So it's like a Google search for your, kind of, the indexing all those workers. >> Internally, yeah, and sometimes it's-- there's a great idea here, you merge that with another idea from another group or another geo, and then you can actually go and fund something. >> Well, that's important because timing is critical, in these early-- most stuff can be early in just incubation, gestation period for that tech or concept, could be in play because the computer-- all the new things, right? >> Correct. And, do you actually have the time? You're an engineer working on a release, the priority is getting that release out the door, right? >> (laughs) >> So, put the idea on the back burner, come off the release, and then, you know, get a couple of colleagues together and maybe there's a Borathon being held and you go and move that idea forward that way. Or, it's time for RADIO submissions, get a couple of colleagues together and submit a RADIO paper. So we want to have different platforms for our engineers to submit ideas outside of their day job. >> And it sounds like, the different programs that you're talking about: Flings, xLab, Borathon, RADIO, what it sounds like is, there isn't necessarily a hierarchy that ideas have to go through. It really depends on the teams that have the ideas, that are collaborating, and they can put them forward to any of these programs, >> Correct, yeah. >> and one might get, say, rejected for RADIO, but might be great for a Borathon or a Fling? >> Correct. >> So they've got options there, and there's multiple committees, I imagine? Is that spearheaded out of Ray's OCTO group, >> Yep. >> that's helping to make the selections? Tell us a little bit about that process. >> Sure, so. That's a great point, right? To get an idea out the door, you don't always have to take the same pathway. And so one thing we started tracking was these innovation journeys that all take different pathways. We just published an impact report on innovation for FY19, and we've got the vSAN story in there, right? It was an idea. A group of engineers had an idea, like, in 2009, and they worked on their idea a little bit-- it first made it to RADIO in 2011. And then they came back in 2013, and, sort of, the rest is history, you know. vSAN launched in 2014. We had a press release this week for Carbon Avoidance Meter. It was an idea that actually started as a calculator many years ago. Was used, and then sort of died on the vine, so to speak? One of our SEs said, "You know, this is a good idea. I want to evolve this a little bit further." Came and pitched an xLabs idea, and we said, "Alright, we're going to fund this as an xLabs Lite. Three to six months project, limited funding, work on one objective --you're still doing your day job-- move the project forward a little bit." Then Nicola Acutt, our Sustainability VP, got involved, wanted to move the idea a little bit further along, came back for another round of funding through an xLabs Lite, and then GSS, with their Skyline platform, picked it up, and that's going to be integrated in the coming months into Skyline, and we're going to be able to give our customers a carbon, sort of, readout of their data center. And then they'll be able to, you know, map that, and get a bigger picture, because obviously, it's not just the servers that are virtualized, there's cooling in the data center plants, and all these other factors that you've got to, you know, take into account when you want to look at your carbon footprint for your facility. So, we have lots of examples of how these innovation pathways take different turns, and sometimes it's Team A starting with an idea, Team B joins in, and then there's this convergence at a particular point, and then it goes nowhere for a couple of months, and then, a business unit picks it up. >> One of the things that's come out-- Pat Gelsinger mentioned that a theme outside of the normal product stuff is how people do work. There's been some actual R&D around it, because you guys have a lot of distributed, decentralized operations in R&D because of the global nature. >> Yeah. >> How should companies and R&D be run when the reality is that developers could be anywhere? They could be at a coffee shop, they could be overseas, they could be in any geography, how do you create an environment where you have that kind of innovation? Can you just share some of the best practices that you guys have found? >> I'm not sure if there's 'best practices', per se, but to make sure that the programs are open and inclusive to everybody on the planet. So, I'll give you some stats. For example, when RADIO started in the early days, we were founded in Palo Alto. It was a very Palo Alto-centric company. And for the first few years, if you looked at the percentage of attendees, it was probably over 75% were coming from Palo Alto. We've now over the years shifted that, to where Palo Alto probably represents about 44%, 16% is the rest of North America, and then the balance is from across the globe. And so that shift has been deliberate, obviously that impacts the budget a little bit, but in our programs, like a Borathon, you can hack from anywhere. We've got a lot of folks that are remote office workers, using, you know, collaborative tools, they can be part of a team. If the Borathon's happening in China, it doesn't stop somebody in Palo Alto or in Israel or in Bulgaria, participating. And, you know, that's the beautiful nature of being global, right? If you think about how products get out of the door, sometimes you've got teams and you are literally following the sun, and you're doing handoff, you know, from Team A to B to C, but at the end of the day you're delivering one product. And so that's just part of our culture, I mean, everybody's open to that, we don't say, "Oh, we can't work with those guys because they're in that geo-location." It's pretty open. >> This is also, really, an essential driver, and I think I saw last year's RADIO, there were participants from 25+ countries. But this is an essential-- not only is VMware a global company, but many of your customers are as well, and they have very similar operating models. So that thought diversity, to be able to build that into the R&D process is critical. >> Absolutely. And also, think about, you know, when you're going to Europe. Smaller borders, countries, you deploy technology differently. And so, you want to have that diversity in thought as well, because you don't just want to be thinking, "Alright, we're going to deploy a disaster recovery product in North America where they can fail over from, you know, East Coast to West Coast. You go to Europe, and typically you're failing over from, you know, site A to site B, and they're literally three or four miles apart. And so, just having that perspective as well, is very important. And we see that, you know, when we release certain products, you'll get, you know, better uptick in a certain geo, and then, "Why is it stalling over here?" well it's, sometimes it's cultural, right? How do you deploy that technology? Just because it works in the US, doesn't mean it's going to work in Europe or in APJ. >> How was your team involved in the commercialization? You mentioned vSAN and the history of that, but I'm just wondering, looking at it from an investment standpoint of deciding which projects to invest in, and then there's also the-- if they're ready to go to market, the balance of "How much do we need to invest in sales and marketing to be able to get this great idea-- because if we can't market it and sell it, you know, then there's obviously no point." So what's that balance like, within your organization, about, "how do we commercialize this effectively, at scale"? >> So that is ultimately not the responsibility of my group. We'll incubate ideas, like, for example, through an xLabs project. And, you know, sometimes we'll get to a point and we'll work, collaborate with a business unit, and we'll say, "Alright, we feel this project's probably a 24 months project", if it's an xLabs Full. So these folks are truly giving up their day job. But at the end of the day, you want to have an exit and when we say exit, what does that exit mean? Is that an exit into a business unit? Are you exiting the xLabs project because we're now out of funding? You know, think about a VC, I'm going to fund you to, you know, to a particular point; if there is no market traction, >> Right. >> we may, you know, sunset the project. And, you know, so our goal is to get these ideas, select which ones we want to invest in, and then find a sort of off-ramp into a business unit. And sometimes there'll be an off-ramp into a business unit, and the project goes on for a couple of months, and then we make a decision, right? And it's not a personal decision, it's like, "Well we funded that as an xLabs; we're now going to shut it down because, you know, we're going to go and make an acquisition in this space. And with the talent that's going to come onboard, the talent that was working on this xLab project, we can push the agenda forward." >> John: You have a lot of action going on so you move people around. >> Exactly. >> Kind of like the cloud, elastic resource, yeah? (laughs) >> So, then, some of these things, because xLabs is only a two-year-old, you know, we haven't had things exit yet that are, you know, running within a business unit that we're seeing this material impact. You know, from a revenue point of view. So that's why tracking the journeys is very important. And, you know, stay tuned, maybe in about three or four years we'll have this, similar, you know, interview, and I'll be able to say, "Yeah, you know, that started as an xLab, and now it's three years into the market, and look at the run rate. >> So there's 31-- last question for you-- there's 31 projects that were presented on mainstage. Are there any that you could kind of see, early on, "ooh", you know, those top five? Anything that really kind of sticks out-- you don't have to explain it in detail, but I'm just curious, can you see some of that opportunity in advance? >> Absolutely. There's been some great papers up on mainstage. And covering, you know, things on the networking side, there's a lot of innovation going in on the storage side. If you think about data, right, the explosion of data because of edge computing, how are you going to manage that data? How are you going to take, you know, make informed decisions on that data? How can you manipulate that data? What are you going to have to do from a dedupe point of view, or a replication point of view, because you want to get that to many locations, quickly? So, I saw some really good papers on data orchestration, manipulation, get it out to many places, it can take an informed decision. I saw great-- there was a great paper on, you know, you want to go and put something in AWS. There's a bull that you get at the end of the month, right? Sometimes those bulls can be a little bit frightening, right? You know, what can you do to make sure that you manage those bulls correctly? And sometimes, the innovation has got nothing to do with the product per se, but it has to do with how we're going to develop. So we have some innovation on the floor here where an engineer has looked at a different way of, basically, creating an application. And so, there's a ton of these ideas, so after RADIO, it doesn't stop there. Now the idea harvesting starts, right? So yes, there were 31 papers that made it onto mainstage, 61 that are posters here. During that review process, and you asked that question earlier and I apologize, I didn't answer it-- you know, when we look at the papers, there's a team of over 100 folks from across the globe that are reviewing these papers. During that review process, they'll flag things like "This is not going to make it onto mainstage, but the idea here is very novel; we should send this off to our IP team," you know. So this year at RADIO, there were 250 papers that were flagged for further followup with our IP team, so, do we go and then file an IDF, Invention Disclosure Form, do those then become patents, you know? So if we look at the data last year, it was 210. Out of those 210, 74 patents were filed. So there's a lot of work that now will happen post-RADIO. Some of these papers come in, they don't make it onto mainstage; they might become a poster. But at the same time they're getting flagged for a business unit. So from last year, there were 39 ideas that were submitted that are now being mapped to roadmap across the BUs. Some of these papers are great for academic research programs, so David Tennenhouse's research group will take these papers and then, you know, evolve them a little bit more, and then go and present them at academic conferences around the world. So there's a lot of, like, the "what's next?" aspect of RADIO has become a really big deal for us. >> The potential is massive. Well, Mornay, thank you so much for joining John and me, >> Thank you. >> and I've got to follow xLabs, there's just a lot of >> (laughs) >> really, really, innovative things that are so collaborative, coming forward. We thank you for your time. >> Thank you. >> For John Furrier, I'm Lisa Martin; you're watching theCUBE, exclusive coverage of VMware RADIO 2019, from San Francisco. Thanks for watching.

live from Las Vegas it's the queue covering Adobe summit 2019 brought to you by Adobe welcome back everyone live cube coverage here in Las Vegas for Adobe summit 2019 I'm John fry with Jeff Frick two days of wall-to-wall coverage our next guest is Josh Van Tonder group product marketing manager to Dobby thanks for joining us thanks pleasure you're managing the marketing of the products of experienced manager within the platform great event here really the keynote we have agreed a good view good review this morning it's a great platform a lot of elements to it journey it's the Holy Grail that's super interesting and I mean I think you can see the Holy Grail you know it's it's just great actually hearing from the customers right I think it comes to life when you hear the stories they're telling kind of the solutions they're bringing a market on top of it it's it's it's very exhilarating for the product teams to see it all in action and coming to life through the customers you know we cover hundreds of events a year we hear all the stories everyone talks about innovation it's really happening here is gadot bees transform to cloud years ago so now you start to see Marketo Magento coming through the mix full platform architecture open API is open data this is the beginning of a sea change we started to seeing customers having the end-to-end experience where each functional element can do its job and connect with the data this is progressive that's great stuff it's great stuff so so where where are we what's going on with the product what's what's going on how our customers dealing with this because you got Best Buy up there forty million emails personalized yep personalization at scale yep I mean I think the the crux of what's going on is I think a lot of the organizations I mean essentially the name of the game is delivering personalized experiences right I mean how do you how do you get someone to have that moment that moment of truth where they they get to see and interact with the brand in a way that's relevant to that right I mean I think we all we all respond that way I think you know even statistics show that our own statistics show that so we've done some surveys of other consumers um it's 51 percent say I'm much more likely to buy something from a if it's personalized and 49 1% are gonna say look I'm gonna be more loyal to you because it is relevant to me which makes sense I think you and I would probably agree that if it's it's the nail on the head I want to bring up a point that the in the keynote the CEO said he said people don't buy products they buy experiences okay and this is now kind of become the the kind of the mission of all companies just seeing a big frame with direct-to-consumer yeah in all verticals not just B to B to C directly consumer so now companies can go direct to the consumer so how does that change like the ite equation because the old days were you know Bill stack and rack servers load some soft yeah sell it to a customer but now you're dealing with a user experience model that's everywhere yeah that's an interesting basis I mean a the crux of the issue is under the underneath that is it takes contents and data together to kind of deliver the great experience and at the end of the day IT is front and center as the enabler strategically for how that gets delivered I think what we've been seeing is they're they're sort of I would say four key pillars elements that that they've been using to turn their portfolio to be a strategic advantage so one is how do you manage omni-channel right I mean I guess it's getting further with your message so it's if that's essentially an omni-channel thing the other is being faster about getting to market with that message so you know maybe how does cloud play into that how does how do you enable the marketing teams and then I think the last thing and this is this is one that's been a hot topic is where does where does AI simultaneously help drive that better experience so I think those are sort of the pieces we're seeing coming into play from an IT standpoint where they they have a lot of a lot of influence to advance the overall business mission you know Jeff and I were talking about our intro about how the cloud has really in changed the game with Adobe and the customer base you know the old cloud conversation around DevOps and around the building applications work waterfall processes are gonna be dismantled by agility process based processes you started to see that now with content and creative yet we're agility and feed and data are now the new thing so a Content developer is kind of like a software developer for software you guys are providing cloud tech capabilities for content developers yeah creative developers that's right kind of metaphor there what's how do you view that how do customers react to that that's interesting I mean I think you you know usually you bring up the one side is cloud agility and the corollary to that it's just overall content velocity if you will right so I think from a cloud standpoint the the model would be you know how do i how do I get to market faster and in more geographies how to get to more geographies how do I you know support rolling out new infrastructure or new products more more quickly on the cloud infrastructure and then how do I deal with growth right how do i ami system if you look at it from the content lens which i think is what you're getting at there's a similar paradigm in terms of this agility so from an IT standpoint how do you enable someone that's on the marketing team to discover their content to reuse it more effectively and then deploy it more effectively and there are many pieces to the ité equation that fundamentally empower if you will let that velocity in terms of being able to manage discover and and frankly optimize that content as you get it out there so it's an interesting thing that I think we've been doing a lot of looking at a lot of product innovation specifically from an Adobe standpoint in terms of actually enabling that that product velocity which I mean the platform out there basically is the architecture for the platform to do that yes elements so this is just a perfect storm that's come together finally in terms of capability because we've talked about 360 view of the customer ad nauseam and and we've talked about omni-channel for many many many years but I think the execution on those was was was certainly lagging behind the vision but is it now because of the integration of the platform is it because the Big Data architectures is it because now you know it's it's it's you're reading real-time data on ingest you're not going back this normal data what is it this now and abling just actually execute on the vision that we've been talking about for years yeah I mean I think there there are multiple pieces kind of coming together that are helping so I think you know as you said I think in some sense what you're getting at is there there were historically many silos of how these things have historically been managed and what we're seeing is is a trend towards centralizing that information because ultimately you can drive more insights by looking at it and it's just you get more velocity for reusing it so you know to look at it from let's just take an example of the V omni-channel so if we look at it purely from delivering content what we as say an IOT device comes to market or you have these more advanced single page apps on the web page or an Alexa right what we saw is a rise of separate systems in some sense to manage those but now we're seeing a trend where gosh if we were to have all that content in one place if we had all the analytics behind that in one place we can more effectively personalize the customer journey across each of those and that's effectively what you're hearing a lot of today is can I have sort of a centralized but hybrid model that supports through api's getting that information to different touch points and then the data engine that will allow the personalization across each of that those touch points and that I think is the fundamentally the part that's unlocking a lot of value and is it the acceptance of the of the AI and and kind of the machine learning that's going to help you do it because you can't you can create 40 million emails with the people right you mean you have to have automation and you have to have some intelligence behind that you just can't do it manually so is that where we finally kind of broken through so that I can send 40 million different emails in one campaign with some intelligence and some logic behind who's got what yeah I think you hit the nail and I had that right I mean I think if personalization is the name of the game and you're interacting on more touch points with more pieces of contents how do you get it right for each audience and so that's where AI is it's just adds tremendous a tremendous velocity and help for businesses to get that right so I think you can think of it almost this pipeline to deliver the experience so on one hand how do you create that experience hey I can play a role how do you manage it internally hey I can play a role in terms of discovering the assets and we're using it delivering it it can play a role and actually getting the right content out there I'll give you some examples of that in a second but and then the final piece is it has you know the actual optimization of that right so to give you some examples what we've seen happening is you can literally use the AI the the data on interactions of how people interacting across your system and actually create interfaces on-the-fly for specific segments of audiences right so instead of say I as a marketer creating that interface you know using web development or tooling why not have the system actually recompose what is being served up you know maybe a certain layout with multiple columns works for some audiences maybe it just needs to be one banner with a certain type of image a I can actually do that for you by looking at the analytics of you know how do you react to certain things versus me and drawing corollaries so there's a lot of police places along that chain where AI is the impact is productivity obviously because you know the right to queries or figure out what's come in that's presented to you that's good that's kind of the impact of the marketer right it's about yeah it's about scaling the market or right I mean I think that's one of the big challenges from a business standpoint is you know your team's never big enough to serve every person every single customer as a marketer so that's where a I essentially unlocks that that scale it gives you a marketing team of thousands where you may only have a team of a hundred or twenty depending on the size of the order to tune that up in terms of a customer I've got an Adobe I'm Adobe customer I go the Adobe cloud experience cloud how do I tune this up I mean is there a way that you guys have figured out that allows them to kind of get it up and running fast without a lot of complexity yeah that's like that's a good question it's I mean that's actually it's really critical because that from a marketing standpoint you know IT can bring to bear a number of different technologies but unless they're easy to adopt you're not gonna go anywhere so I think the trick is almost giving marketers the easy button so I think that's that's where a lot of the magic and AI happens is you pick one specific problem you know in Adobe's case we pick a problem where we know we have a lot of intelligence about creative assets and we have visibility and how those are being used so if we bring those together we can solve specific problems about discovering content or how we deliver that optimally but the wit to answer your specific question it's almost as though we try to give an easy button for the marketer right so I feed you a bunch of say audience segments and then I plug you into my my analytics data press a button and I ideally it's gonna just figure it out for me write it and and then test if it works that's the key thing is once you get in a market test it right and and it can do that for you and I don't think there's enough you know kind of highlight on that where you know those dramatic before to do a/b testing now you can test everything you know at such scale it's such detail into your point you think you know your segments and you can create your own segments but you can actually let the Machine create segments based on actual behavior of people which I guess really is enabled by most you know so many of your interactions now with brands is digital so give you that opportunity to grab a piece of that exhaust do the analytics and get some insight out of it yeah that's exactly right I mean I you know data the scale of data I mean everybody's flooded with data right now but it's really where's the needle in the haystack and I think that's that's where AI plays a crucial role I mean it it can do things like figure out anomalies on on your interactions across a large swath of users right if something something you see in the data is it's statistically normal or not and should I pay attention to it and what should i do from it so AI starts to play a role in that it can even do simple things like we all have mobile phones we all want to watch more video on mobile phones the problem is as a business as a marketing team and and I'm sure even you know you folks have the same situation is the content that you create may not be ready to be consumed appropriately on each device right so if I pick up my mol device has it been optimized properly so you can do things like have a I pick the focal points in a video and crop out the rest and follow the focal point and only show that on the phone so well certainly gonna call you up because we have a lot of video we don't have twenty videos here today so a lot of luck but this is the norm people gonna have more velocity of videos that's that's podcasts yep blog posts so the waterfalls I was getting earlier this waterfall thing is over it's more of an agile environment so I got to ask the customer question is that reality yet grounded in the customer base or is it still early adopters or I guess the question is what's the pattern that you're seeing in customers Bart what makes a good market or what makes a good organization to embrace the kind of change that's on our doorstep right now it's a good that's a good question and it I think it takes two to tango I think there's a an IT elements and a marketing elements and I think we're seeing an evolution and how how the two work together in this new model so from an IT standpoint they are the enabler for example to get content onto multiple multiple different channels from a from our marketers standpoint they ultimately are the ones that define and help articulate the right message and type of content if IT and marketers are working well together the more the the IT team is going to enable that market or T marketing team to essentially iterate quickly in content so there's a whole set of things that can be done to enable the marketing team to be agile and getting that content out there so I think you know the evolution I would say is is in in how the two teams are working so I think your waterfall model and past I'd say it's entirely gone but it has been reframed in a ways exploring it that's a good way to test to see if if IT and CM a CIO and the CMO working together yeah probably aligned to four change right they're not maybe not it's so I mean I'll give you a very specific example so one thing that we've been seeing in our world is so for example on cloud you know there's a lot of things you can do more quickly traditionally there have been some waterfall development models what we've seen is IT now has a DevOps process where they're very fast and rolling out application updates but if you can actually standardize that if you can create a pipeline for Creek getting code onto the onto the different environments if you test it and roll it out faster what that means for marketing and business is the time to market goes down so for example we've actually been baking that into our products can we literally here's a best-in-class pipeline for doing an agile development model it's already pre-built into the the infrastructure to enable IT to kind of go faster on the behalf of so here's a question for you put you on the spot sure in all the stores major shifts is always gaps there's always gaps in new markets or white spaces so there's three areas technology gaps skills gaps and culture gaps yep can you talk about what you see as the key gaps that people are starting to get over on figure out how to fill those gaps because they can become direct walkers if they're not resolved so tech gap skills gap and culture gap so just because we talking tech a lot let's reverse it and talk you know sort of the the team and organization elements I mean you think one thing that we've we've definitely been seeing is is if you will the the alignment of what was traditionally a channel management is now moving more closely into the CDO or CMO arm which I think is a good thing right I think what we see as some of our leading customers is the marketing and and chief digital officer x' have increasingly more alignment and a seat at the table of how the individual channel line of businesses are operating and that's a very good thing because it does help close the loop on the customer journey across those channels which I think it's traditionally been a bit of a dilemma so I would say that's one thing we're seeing much more is that the channels the channel management actually going under directly or more alignment with the marketing arm or something like a CDO so on the org side that's one area and that helps with the velocity right and they're rearranging the org structures to align with how does content me to be shared across these teams do you really own that channel is it is it do we do we have a customer journey that is owned across all channels right and I think that's an important conversation that these companies have been struggling with in our and I've evolved a lot in the last few years and we talked about the tech gap already but skills gap what skills are out there that are needed obviously day the machine learning yeah a big one date the machine learning stuff I mean I think Adobe's fuel horse on the races I think we're trying to democratize some of that so as I said earlier the hope is for the marketing team we we give them a neat easy path to to unlock that there are areas where there's been big growth like so for example the front and frameworks and development for single page applications that's an area from an IT standpoint where we've seen a tremendous growth in that technology set and and how that plays a role with the rest of the infrastructure yeah and and and simply how does that actually align with the traditional tools they've been using for managing their websites I think what we've seen is that they're now skill wise and technology wise actually taking of you that you you still have one centralized platform but ultimately you'll have IT developer resources that plug in to say one central hybrid content management system for example any new personas popping out of this just shift that's going on with cloud and and creativity experience cloud any new roles that are emerging that you see popping out yeah I mean I so I mean one example we've seen and it's it's it's been an evolution but you know for example we've seen the rise of something called journey managers right which just goes back to what I was mentioning earlier which are our people that their business and tack align but they're interested in understanding how does a customer actually move across a specific journey so they're mapped to if you will a task a customer's trying to do and how do i optimize that you know assuming and knowing that you know if Josh is going to try and get some customer support he's not just always going to call the support line he's going to try other things and how do I simplify that for him and taking a very holistic view so I think that's that's one thing we've seen more of and it's it's a you know a great way to approach it fascinating insights Josh thanks for coming on I'll give you the final word I put a plug in for what you're working on experience manager what's new what's happening yeah absolutely so we're I'm part of the experience manager team so we're part of the organization that that helps our brands deliver and manage digital experiences so essentially we're enabling if you will omni channel delivery and management of those experiences and a key thrusts for us are around enabling IT to get content effectively across channels and also experience intelligence how do we how do we deliver AI and machine learning innovation to make the marketers job easier for getting personalized experiences to market and enabling IT to support them more efficiently so there's a number of innovations and exciting things that we're very excited about it someone for the congratulations Josh van Tonder group product marketing manager at adobe experience manager his product breaking down what's going on here at Adobe summit and in the industry I'm Jennifer Jeff rick stay with us for more coverage here at adobe summit after this short break

(energetic music) >> [Narrator] From San Francisco, it's theCUBE, covering Radio 2018. Brought to you by VMware. >> Hello everyone. Welcome to the special CUBE coverage here in San Francisco, California for VMware's Radio 2018 event. This is their R&D big event kickoff. It's like a sales kickoff for engineers, as Steve Herrod said on stage. Out next guest is Mornay Van Der Walt, VP of the Explore Group, Office of the CTO. Also, program chair of the Event Today Conference, working for the collective of people within VMware on a rigorous selection committee for a high bar here at your event. Welcome to theCUBE. Thanks for joining me. >> Thank you. >> Talk about the event, because I know a lot of work went into it. Congratulations, the talks were amazing. I see the schedule. We have Pat Gelsinger coming on later today. We just had Ray O'Farrell on. This is like the, I don't want to say, Burning Man of Vmware, but this is really a recognition, but also really important innovation. Take a minute to talk about the process that you go through to put this together. It's a fantastic event. The smartest minds, the cream rises to the top. It's hard, it's challenging, it's a team effort, but yet you gotta ride the right waves. >> Right. So, RADIO: R&D Innovation Offsite. And as you said, it is tough because we've got this huge R&D community and they've all got amazing ideas. So they get the opportunity to submit ideas. I think this this year we have over 1,700 ideas submitted, and at the end of the day we're only going to showcase 226 of those ideas across research programs, posters, breakout sessions, Just-In-Time BOFs, Birds Of a Feather. You know, so, the bar is high. we've got a finite amount of time, but what's amazing is we take these ideas, and we don't just showcase them at RADIO. We have four other programs that give us the ability to take those ideas to the next level. So when we think about the innovation programs that come out of OCTO, this is really to drive what we call "Off-Road Map Innovation." So Raghu and Rajiv, with our Product Cloud Services Division, are driving road map, zero to three years out the stuff that you can buy from sales, >> [Furrier] Customer centric? >> Customer centric, yeah. OCTO is providing an innovation program structure, these five programs: Tech Talks, Flings, Borathons, RADIO, and xLabs, and as a collective, they are focused on off-road map innovation. Maybe something that's-- >> Give me an example of what that means, Off-Road Map. >> Sure. So last year at RADIO we did a paper that was showcased on functions as a service. So you think of AWS Lambda, right. [Furrier] Yep, yep >> VM was uniquely positioned, with the substrate, to manage and orchestrate VM's containers and whynot functions. So this radio paper was submitted, I then, as the xLabs group, said we're going to fund this, but given where we are in this market, we said, "Alright, we'll fund this for 12 months." So, we're incubating functions as a service. In July/August time frame, that'll actually exit xLabs into the Cloud Native business. >> It's a real rapid innovation. >> Very rapid. >> Within a 12 month period, we're gonna get something into a BU that they can take it to market. >> Yeah, and also I would say that this also I've seen from the talks here, there's also off-road map hard problems that need to kind of get the concepts, building blocks, or architecture... >> [Van Der Walt] Correct. >> With the confluence of hitting, whatever, its IOT or whatever, blockchains, seeing things like that. >> [Van Der Walt] Yeah. Correct. >> Is that also accurate too? >> Very true. And, you know, Ray had a great slide in his keynote this morning, you know, we spoke about how we started in 2003, when he joined the company, it was all about computer virtualization. Fast-forward 15 years, and you look at our strategy today, it's any Cloud, any device, any app, right? Then, you gotta look to the future, beyond there, what we're doing today, what are the next twenty years going to look like? Obviously, there's things like, you know, blockchain, VR, edge computing, you know, AIML... >> [Furrier] Service meshes? >> Services meshes, adaptive security. And, you know, people say, "Oh, AIML, that's a hot topic right now, but if you look back at VM ware, we've been doing that since 2006. Distributed resource scheduler: a great example of something that, at the core of the product, was already using ML techniques, you know, to load-balance a data center. And now, you can load-balance across Clouds. >> It's interesting how buzzwords can become industry verticals. We saw that with Hadoop; it didn't really happen, although it became important in big data as it integrates in. I mean, I find that you guys, really from the ecosystem we look at, you guys have a really interesting challenge. You started out as "inside the box," if you will. I saw your old t-shirt there from the 14 year history you guys have been doing this event. Great collection of t-shirts behind me if you can't see it. It's really cool. But infrastructures, on premise, you buy, it's data center, growth, all that stuff happened. Cloud comes in. Big data comes in. Now you got blockchain. These are big markers now, but the intersection of all these are all kind of touching each other. >> [Van Der Walt] Correct. >> IOT...so it's really that integration. I also find that you guys do a great job of fostering innovation, and always amazed at the VM world with some great either bechmarks or labs that show the good stuff. How do you do it? Walk me through the steps because you have this Explorer program, which is working. >> [Van Der Walt] Yeah >> It's almost a ladder, or a reverse ladder. Start with tech talks, get it out to the marketplace... >> [Van Der Walt] Do a hackathon. >> Hackathon. Take us through the process. So there's four things: tech talks, borathons, which is the meaning behind the name, flings, and xLabs. >> Correct >> Take us through that progression. >> ... and RADIO, of course. >> And RADIO, of course, the big tent event. Bring it all together. >> So, I'm an engineer. I have a great idea. I wanna socialize it; I wanna get some feedback. So, at VMWare, we offer a tech talk platform. You come, you present your idea. It's live. There'll be engineers in the audience. We also record those, and then those get replayed, and engineers will say, "You know, have you thought about this?" or "Have you met up with Johnny and Mary?" They're actually working on something very similar. Why don't you go and, you know, compare ideas? I can actually make that very real. I was in India in November, and we were doing a shark tank for our xLabs incubator, and this one team presented an idea on an augmented reality desktop. We went over to another office, actually the air watch office, and we did another shark tank there. Another team pitched the exact same idea, so I looked at my host, and I said, "Do these two teams know each other?" and the guy goes, "Absolutely not," so what did we do? We made the connection point. Their ideas were virtually identical. They were 25 kilometers apart. Never met. >> [Furrier] Wow. >> You know, so when, that's one of the challenges when your company becomes so big, you've got this vast R&D organization that's truly global, in one country 25 kilometers apart, you had two teams with the same idea that had never met. So part of the challenge is also bringing these ideas together because, you know, the sum of the parts makes for a greater whole. >> And they can then collectively come together then present to RADIO one single paper or idea. >> [Van Der Walt] Absolutely, or go ahead and say, you know what, let's take this to the next step, which would be a borathon, so borathons are heckathons. >> Explain the name because borathon sounds like heckathon, so it is, but there's a meaning behind the name borathon. What is the meaning? >> Sure. So, our very first build repository was named after Bora Bora, and so we paid homage to that, and so, instead of saying a heckathon, we called it a borathon. And one of our senior engineers apparently came up with that name, and it stuck, and it's great. >> So it's got history, okay. So, borathons is like ... okay, so you do tech talks, you collaborate, you socialize the idea via verbal or presentation that gets the seeds of innovation kinda planted. Borathon is okay, lets attack it. >> Turn it into a prototype. >> Prototype. >> And it gets judged, so then you get even more feedback from your most senior engineers. In fact ... >> And there's a process for all this that you guys run? >> Yeah, so the Explorer groups run these five innovation programs. We just recently, in Palo Alto, did a theme borathon. Our fellows and PE's came together. Decided the theme should be sustainability, and we mixed it up a little bit. So, normally, at a borathon, teams come with ideas that they've already been developing. For this one, the teams had no idea what the theme was going to be, so we announced the theme. Then, they showed up on the day to learn what the five challenges were going to be, and some of those challenges, one of them was quite interesting. It was using distributed ledger to manage microgrids, and that's a ... >> A blockchain limitation >> Well, it's a project that's, you know, is near and dear to us at VMWare. We're actually going to be setting up a microgrid on campus, and if you think about microgrids, and Nicola Acutt can talk more to this, we're gonna be looking at, you know, how can we give power back to the city of Palo Alto? Well, imagine that becoming a mesh network. >> [Furrier] With token economics. >> How do you start tracking this, right? A blockchain would be a perfect way to do this, right? So, then, you take your ideas at a borathon, get them into a prototype, get some more feedback, and now you might have enough critical mass to say, "Alright, I'm going to present a RADIO paper next year." So, then, you work as a team; get that into the system. >> [Furrier] And, certainly, in India and these third-world countries now becoming large, growing middle-class, these are important technologies to build on top of, say, mobile... >> [Van Der Walt] Absolutely. >> And with solar and power coming in, it's a natural evolution, so that's good use case. Okay, so, now I do the borathon. I've got a product. Flings? >> It's a prototype, right, so now ... >> You can socialize it, you have a fling, you throw it out there, you fling it out there What happens? >> Yeah, so, I've done something at a borathon. It's like, I want to get some actual feedback from the ecosystem: our customers and partners. That example I used with vSAN. You know, vSAN launched. We wanted to get some health analytics. The release managers were doing their job. The products got a ship on the state. Senior engineers on the team got a health analytics tool out as a fling. It got incredible feedback from the community. Made it into the next release. We did the same with the HTML clients, right? And that's been in the press lately because, you know, we've got Rotoflex. Now, there's HTML, but that actually started - two teams started working on that. One team just did HTML >> a very small portion of the HTML client, presented a RADIO paper. Two years later, another team, started the work, and now we have a full-fledged HTML client that's embedded into the VIS via product. >> [Furrier] So, the fling brings in a community dynamic, it brings in new ideas, or diversity, if you will. All kinds of diverse ideas melting together. Now, xLabs, I'm assuming that's an incubator. That brings it together. What is xLabs? Is that an incubator? You fund it? What happens there? >> So with an xLabs, the real way to think about it, it's truly an incubator. I don't want to use the word "start-up" there because you've clearly got the protection of the larger VMware organization, so you're not being a scrappy start-up, but you've got a great idea, we see there's merit ... >> [Furrier] Go build a real product. >> We see it more being on the disruptive side, and so we offer two tracks in the xLabs. There's a light track, which typically runs three to six months, and you're still doing your day job. You know, so you're basically doing two jobs. You know, we fund you with a level of funding that allows you to bring on extra contracting, resources, developers, etc., and you're typically delivering one objective. The larger xLab is the full-track, so functions as a service. Full-track, we showcased it as a RADIO paper last year. We said, "Alright, we're going to fund this. We're going to give it 12 months worth of funding, and then it needs to exit into a business unit," and we got lucky with that one because we were already doing a lot of work with containers, the PKS, the pivotal. >> [Furrier] Do the people have to quit their day job, not quit their day job, but move their resource over? >> [Van Der Walt] Absolutely. >> The full-track is go for it, green light >> Yep >> Run as fast as you can, take it to this business unit. Is the business unit known as the end point in time? Is it kind of tracked there, or is it more flexible still. >> Not all the time. You know so sometimes, with functions it was easier, right? So, we know we've got pull for zone heading up Cloud native apps. The Cloud native business unit is doing all the partnerships with PKS. That one makes sense. >> [Furrier] Yeah. >> We're actually doing one right now, another xLabs full, called network slicing, and it's going to play into the Telco space. We've obviously got NFV being led by Shekar and team, but we don't know if network slicing, when it exits, and this one is probably going to have a longer time arise and probably 24-36 months. Does it go into the NFV business unit, or does it become its own business unit. >> [Furrier] That's awesome. So, you got great tracks, end to end, so you have a good process. I gotta ask you the question that's on my mind. I think everyone would look at this, and some people might look at Vmware as, and most people do, at least I do, as kind of a cutting-edge tier one company. You guys always are a great place to work. Voted as, get awards for that, but you take seriously innovation and organic growth in community and engineering. Engineering and community are two really important things. How do you bring the foster culture because engineers can be really pissed off. "Oh my god! They're idiots that make the selection!" because you don't want engineers to be pissed cuz they're proud, and they're inventing. >> Yep, yep. >> So, how to manage the team approach? What's the cultural secret in the DNA that makes this so successful over 14 years? >> So, before I answer that question, I think it's important to take a step back. So, when we think about innovation, we call this thing the Vmware "innovation engine." It's really three parts to it, right? If you think about innovation at its core: sustaining, disruptive, internal, external, And, so, we've got product Cloud Services group, Raghu and Rajiv, we've got OCTO, headed up by Ray, we've got corp dev headed up by Shekar. Think of it as it's a three-legged stool. You take one of those legs away, the stool falls over. So, it's a balancing act, right? And we need to be collaborating. >> [Furrier] And they're talking to each other all the time. >> We're talking to each other all the time, right? Build or buy? Are we gonna do something internal, or we gonna go external, right? You think something about acquisitions like Nicira, right? We didn't build that; we bought it. You think about Airwatch, right? Airwatch put us into the top right quadrant from Gartner, right? So, these are very strategic decision that get made. Petchist presented at Dell emc world, Dell Technologies world. He had a slide on there that showed, it was the Nicira acquisition, and then it sort of was this arc leading all the way up to VeloCloud, and when you saw it on one slide, it made perfect sense. As an outsider looking in, you might have thought, "Why were they doing all these things? Why was that acquisition made? But there's always a plan, and that plan involves us all talking across. >> [Furrier] Strategic plan around what to move faster on. >> Correct >> Because there's always the challenge on M&A, if they're not talking to each other, is the buy/build is, you kinda, may miss a core competency. They always ... what's the core competency of the company? And should you outsource a core competency, or should you build it internally? Sometimes, you might even accelerate that, so I think Airwatch and Nicira, I would say, was kinda on the edges of core competency, but together with the synergies ... >> [Van Der Walt] Helped us accelerate. >> And I think that's your message. >> [Van Der Walt] Yep. >> Okay, so that's the culture. How do you make, what's the secret sauce of making all this work? I mean, cuz you have to kinda create an open, collaborative, but it's competitive. >> [Van Der Walt] Absolutely. >> So how do you balance that? >> You know, so clearly, there's a ton of innovation going on within the prior Cloud services division. The stuff that's on the truck that our customers can buy today, alright? We also know we gotta look ahead, and we gotta start looking at solving problems that aren't on the truck today, alright? And, so, having these five programs and the collective is really what allows us to do that. But at the same time, we need to have open channels of communication back into corp dev as well. I can give you examples of, you know, Shekar and his team might be looking at Company X. We're doing some exploratory work, IOT, I did an ordered foray. IOT is gonna be massive; everybody knows that, but you know what's going to be even more massive is all the data at the edge, and what do you do with that data? How do you turn that data into something actionable, right? So, if you think about a jet engine on a big plane, right? When it's operating correctly, you know what all the good levels are, the metrics, the telemetry coming off it. Why do I need to collect that and throw it away? You're interested in the anomalies, right? As we start thinking about IOT, and we start thinking all this data at the edge, we're going to need a different type of analytics engine that can do real-time analytics but not looking at the norm, looking at the deviations, and report back on that, so you can take action on that, you know? So, we started identifying some companies like PubNub, Mulesoft, too, just got acquired, right? Shekar and his team were looking at the same companies, and was like, "These companies are interesting because they're starting to attack the problem in a different way. We do that at Vmware all the time. You think about Appdefense. We've taken a completely different approach to security. You know what the good state is, but if you have a deviation, attack that, you know? And then you can use things like ... >> It's re-imagining, almost flipping everything upside-down. >> Yeah, challenging the status quo. >> Yeah, great stuff, great program. I gotta ask you a final question since it's your show here. Great content program, by the way. Got the competition, got the papers, which is deep, technical coolness, but the show is great content, great event. Thanks for inviting us. What's trending? What's rising up? Have you heard or kind of point at something you see getting some buzz, that you thought might get buzz, or it didn't get buzz? What's rising of the topics of interest here? What's kind of popping out for you; what's trending if I had to a Twitter feed, not Twitter feed, but like top three trending items here. >> Well, I'll take it back to that last borathon that we did on sustainability. We set out the five challenges. The challenge that got the most attention was the blockchain microgrid. So, blockchain is definitely trending, and, you know, the challenge we have with blockchain today is it's not ready for the enterprise. So, David Tennenhouse and his research group is actually looking at how do you make blockchain enterprise ready? And that is a difficult problem to solve. So, there's a ton of interest in watching ... >> [Furrier] Well, we have an opinion. Don't use the public block chain. (both laugh) >> So, you know, that's one that's definitely trending. We have a great program called Propel, where we basically attract the brightest of the brightest, you know, new college grads coming into the company, and they actually come through OCTO first and do a sort of onboarding process. What are they interested in? They're not really interested in working for a particular BU, but, you know, when we share with them, "You're gonna have the ability to work on blockchain, AI, VR, augmented reality, distributed systems, new ways of doing analytics >> that's what attracts them. >> [Furrier] And they have the options to go test and put the toe in the water or jump in deep with xLabs. >> Absolutely >> So, I mean, this is like catnip for engineers. It draws a lot of people in. >> Absolutely, and, you know, we need to do that to be competitive in the valley. I mean, it's a very hard marketplace. >> Great place to work. >> You guys have a great engineering team. >> Congratulations for a great event, Mornay, and thanks for coming on theCUBE. We're here in San Francisco for theCUBE coverage of RADIO 2018. I'm John Furrier. Be back with more coverage after this break. Thanks for watching. (upbeat techno music)