(upbeat music), (logo pop up) >> Narrator: From around the globe it's theCUBE. Presenting active DQ intelligent automation for data quality brought to you by IO-Tahoe. >> Are you ready to see active DQ on Snowflake in action? Let's get into the show and tell him, do the demo. With me or Tiji Matthew, the Data Solutions Engineer at IO-Tahoe. Also joining us is Patrick Zeimet Data Solutions Engineer at IO-Tahoe and Senthilnathan Karuppaiah, who's the Head of Production Engineering at IO-Tahoe. Patrick, over to you let's see it. >> Hey Dave, thank you so much. Yeah, we've seen a huge increase in the number of organizations interested in Snowflake implementation. Were looking for an innovative, precise and timely method to ingest their data into Snowflake. And where we are seeing a lot of success is a ground up method utilizing both IO-Tahoe and Snowflake. To start you define your as is model. By leveraging IO-Tahoe to profile your various data sources and push the metadata to Snowflake. Meaning we create a data catalog within Snowflake for a centralized location to document items such as source system owners allowing you to have those key conversations and understand the data's lineage, potential blockers and what data is readily available for ingestion. Once the data catalog is built you have a much more dynamic strategies surrounding your Snowflake ingestion. And what's great is that while you're working through those key conversations IO-Tahoe will maintain that metadata push and partnered with Snowflake ability to version the data. You can easily incorporate potential scheme changes along the way. Making sure that the information that you're working on stays as current as the systems that you're hoping to integrate with Snowflake. >> Nice, Patrick I wonder if you could address how you IO-Tahoe Platform Scales and maybe in what way it provides a competitive advantage for customers. >> Great question where IO-Tahoe shines is through its active DQ or the ability to monitor your data's quality in real time. Marking which roads need remediation. According to the customized business rules that you can set. Ensuring that the data quality standards meet the requirements of your organizations. What's great is through our use of RPA. We can scale with an organization. So as you ingest more data sources we can allocate more robotic workers meaning the results will continue to be delivered in the same timely fashion you've grown used to. What's Morrisons IO-Tahoe is doing the heavy lifting on monitoring data quality. That's frees up your data experts to focus on the more strategic tasks such as remediation that augmentations and analytics developments. >> Okay, maybe Tiji, you could address this. I mean, how does all this automation change the operating model that we were talking to to Aj and Dunkin before about that? I mean, if it involves less people and more automation what else can I do in parallel? >> I'm sure the participants today will also be asking the same question. Let me start with the strategic tasks Patrick mentioned, Io-Tahoe does the heavy lifting. Freeing up data experts to act upon the data events generated by IO-Tahoe. Companies that have teams focused on manually building their inventory of the data landscape. Leads to longer turnaround times in producing actionable insights from their own data assets. Thus, diminishing the value realized by traditional methods. However, our operating model involves profiling and remediating at the same time creating a catalog data estate that can be used by business or IT accordingly. With increased automation and fewer people. Our machine learning algorithms augment the data pipeline to tag and capture the data elements into a comprehensive data catalog. As IO-Tahoe automatically catalogs the data estate in a centralized view, the data experts can partly focus on remediating the data events generated from validating against business rules. We envision that data events coupled with this drillable and searchable view will be a comprehensive one to assess the impact of bad quality data. Let's briefly look at the image on screen. For example, the view indicates that bad quality zip code data impacts the contact data which in turn impacts other related entities in systems. Now contrast that with a manually maintained spreadsheet that drowns out the main focus of your analysis. >> Tiji, how do you tag and capture bad quality data and stop that from you've mentioned these printed dependencies. How do you stop that from flowing downstream into the processes within the applications or reports? >> As IO-Tahoe builds the data catalog across source systems. We tag the elements that meet the business rule criteria while segregating the failed data examples associated with the elements that fall below a certain threshold. The elements that meet the business rule criteria are tagged to be searchable. Thus, providing an easy way to identify data elements that may flow through the system. The segregated data examples on the other hand are used by data experts to triage for the root cause. Based on the root cause potential outcomes could be one, changes in the source system to prevent that data from entering the system in the first place. Two, add data pipeline logic, to sanitize bad data from being consumed by downstream applications and reports or just accept the risk of storing bad data and address it when it meets a certain threshold. However, Dave as for your question about preventing bad quality data from flowing into the system? IO-Tahoe will not prevent it because the controls of data flowing between systems is managed outside of IO-Tahoe. Although, IO-Tahoe will alert and notify the data experts to events that indicate bad data has entered the monitored assets. Also we have redesigned our product to be modular and extensible. This allows data events generated by IO-Tahoe to be consumed by any system that wants to control the targets from bad data. Does IO-Tahoe empowers the data experts to control the bad data from flowing into their system. >> Thank you for that. So, one of the things that we've noticed, we've written about is that you've got these hyper specialized roles within the data, the centralized data organization. And wonder how do the data folks get involved here if at all, and how frequently do they get involved? Maybe Senthilnathan you could take that. >> Thank you, Dave for having me here. Well, based on whether the data element in question is in data cataloging or monitoring phase. Different data folks gets involved. When it isn't in the data cataloging stage. The data governance team, along with enterprise architecture or IT involved in setting up the data catalog. Which includes identifying the critical data elements business term identification, definition, documentation data quality rules, and data even set up data domain and business line mapping, lineage PA tracking source of truth. So on and so forth. It's typically in one time set up review certify then govern and monitor. But while when it is in the monitoring phase during any data incident or data issues IO-Tahoe broadcast data signals to the relevant data folks to act and remedy it as quick as possible. And alerts the consumption team it could be the data science, analytics, business opts are both a potential issue so that they are aware and take necessary preventative measure. Let me show you an example, critical data element from data quality dashboard view to lineage view to data 360 degree view for a zip code for conformity check. So in this case the zip code did not meet the past threshold during the technical data quality check and was identified as non-compliant item and notification was sent to the ID folks. So clicking on the zip code. Will take to the lineage view to visualize the dependent system, says that who are producers and who are the consumers. And further drilling down will take us to the detailed view, that a lot of other information's are presented to facilitate for a root cause analysis and not to take it to a final closure. >> Thank you for that. So Tiji? Patrick was talking about the as is to be. So I'm interested in how it's done now versus before. Do you need a data governance operating model for example? >> Typically a company that decides to make an inventory of the data assets would start out by manually building a spreadsheet managed by data experts of the company. What started as a draft now get break into the model of a company. This leads to loss of collaboration as each department makes a copy of their catalog for their specific needs. This decentralized approach leads to loss of uniformity which each department having different definitions which ironically needs a governance model for the data catalog itself. And as the spreadsheet grows in complexity the skill level needed to maintain. It also increases thus leading to fewer and fewer people knowing how to maintain it. About all the content that took so much time and effort to build is not searchable outside of that spreadsheet document. >> Yeah, I think you really hit the nail on my head Tiji. Now companies want to move away from the spreadsheet approach. IO-Tahoe addresses the shortcoming of the traditional approach enabling companies to achieve more with less. >> Yeah, what the customer reaction has been. We had Webster Bank, on one of the early episodes for example, I mean could they have achieved. What they did without something like active data quality and automation maybe Senthilnathan you could address that? >> Sure, It is impossible to achieve full data quality monitoring and remediation without automation or digital workers in place reality that introverts they don't have the time to do the remediation manually because they have to do an analysis conform fix on any data quality issues, as fast as possible before it gets bigger and no exception to Webster. That's why Webster implemented IO-Tahoe's active DQ to set up the business, metadata management and data quality monitoring and remediation in the Snowflake cloud data Lake. We help and building the center of excellence in the data governance, which is managing the data catalog schedule on demand and in-flight data quality checks, but Snowflake, no pipe on stream are super beneficial to achieve in flight quality checks. Then the data assumption monitoring and reporting last but not the least the time saver is persisting the non-compliant records for every data quality run within the Snowflake cloud, along with remediation script. So that during any exceptions the respect to team members is not only alerted. But also supplied with necessary scripts and tools to perform remediation right from the IO-Tahoe's Active DQ. >> Very nice. Okay guys, thanks for the demo. Great stuff. Now, if you want to learn more about the IO-Tahoe platform and how you can accelerate your adoption of Snowflake book some time with a data RPA expert all you got to do is click on the demo icon on the right of your screen and set a meeting. We appreciate you attending this latest episode of the IO-Tahoe data automation series. Look, if you missed any of the content that's all available on demand. This is Dave Vellante theCUBE. Thanks for watching. (upbeat music)

(upbeat music), (logo pop up) >> Narrator: From around the globe it's theCUBE. Presenting active DQ intelligent automation for data quality brought to you by IO-Tahoe. >> Are you ready to see active DQ on Snowflake in action? Let's get into the show and tell him, do the demo. With me or Tiji Matthew, the Data Solutions Engineer at IO-Tahoe. Also joining us is Patrick Zeimet Data Solutions Engineer at IO-Tahoe and Senthilnathan Karuppaiah, who's the Head of Production Engineering at IO-Tahoe. Patrick, over to you let's see it. >> Hey Dave, thank you so much. Yeah, we've seen a huge increase in the number of organizations interested in Snowflake implementation. Were looking for an innovative, precise and timely method to ingest their data into Snowflake. And where we are seeing a lot of success is a ground up method utilizing both IO-Tahoe and Snowflake. To start you define your as is model. By leveraging IO-Tahoe to profile your various data sources and push the metadata to Snowflake. Meaning we create a data catalog within Snowflake for a centralized location to document items such as source system owners allowing you to have those key conversations and understand the data's lineage, potential blockers and what data is readily available for ingestion. Once the data catalog is built you have a much more dynamic strategies surrounding your Snowflake ingestion. And what's great is that while you're working through those key conversations IO-Tahoe will maintain that metadata push and partnered with Snowflake ability to version the data. You can easily incorporate potential scheme changes along the way. Making sure that the information that you're working on stays as current as the systems that you're hoping to integrate with Snowflake. >> Nice, Patrick I wonder if you could address how you IO-Tahoe Platform Scales and maybe in what way it provides a competitive advantage for customers. >> Great question where IO-Tahoe shines is through its active DQ or the ability to monitor your data's quality in real time. Marking which roads need remediation. According to the customized business rules that you can set. Ensuring that the data quality standards meet the requirements of your organizations. What's great is through our use of RPA. We can scale with an organization. So as you ingest more data sources we can allocate more robotic workers meaning the results will continue to be delivered in the same timely fashion you've grown used to. What's Morrisons IO-Tahoe is doing the heavy lifting on monitoring data quality. That's frees up your data experts to focus on the more strategic tasks such as remediation that augmentations and analytics developments. >> Okay, maybe Tiji, you could address this. I mean, how does all this automation change the operating model that we were talking to to Aj and Dunkin before about that? I mean, if it involves less people and more automation what else can I do in parallel? >> I'm sure the participants today will also be asking the same question. Let me start with the strategic task. Patrick mentioned IO-Tahoe does the heavy lifting. Freeing up data experts to act upon the data events generated by IO-Tahoe. Companies that have teams focused on manually building their inventory of the data landscape. Leads to longer turnaround times in producing actionable insights from their own data assets. Thus, diminishing the value realized by traditional methods. However, our operating model involves profiling and remediating at the same time creating a catalog data estate that can be used by business or IT accordingly. With increased automation and fewer people. Our machine learning algorithms augment the data pipeline to tag and capture the data elements into a comprehensive data catalog. As IO-Tahoe automatically catalogs the data estate in a centralized view, the data experts can partly focus on remediating the data events generated from validating against business rules. We envision that data events coupled with this drillable and searchable view will be a comprehensive one to assess the impact of bad quality data. Let's briefly look at the image on screen. For example, the view indicates that bad quality zip code data impacts the contact data which in turn impacts other related entities in systems. Now contrast that with a manually maintained spreadsheet that drowns out the main focus of your analysis. >> Tiji, how do you tag and capture bad quality data and stop that from you've mentioned these printed dependencies. How do you stop that from flowing downstream into the processes within the applications or reports? >> As IO-Tahoe builds the data catalog across source systems. We tag the elements that meet the business rule criteria while segregating the failed data examples associated with the elements that fall below a certain threshold. The elements that meet the business rule criteria are tagged to be searchable. Thus, providing an easy way to identify data elements that may flow through the system. The segregated data examples on the other hand are used by data experts to triage for the root cause. Based on the root cause potential outcomes could be one, changes in the source system to prevent that data from entering the system in the first place. Two, add data pipeline logic, to sanitize bad data from being consumed by downstream applications and reports or just accept the risk of storing bad data and address it when it meets a certain threshold. However, Dave as for your question about preventing bad quality data from flowing into the system? IO-Tahoe will not prevent it because the controls of data flowing between systems is managed outside of IO-Tahoe. Although, IO-Tahoe will alert and notify the data experts to events that indicate bad data has entered the monitored assets. Also we have redesigned our product to be modular and extensible. This allows data events generated by IO-Tahoe to be consumed by any system that wants to control the targets from bad data. Does IO-Tahoe empowers the data experts to control the bad data from flowing into their system. >> Thank you for that. So, one of the things that we've noticed, we've written about is that you've got these hyper specialized roles within the data, the centralized data organization. And wonder how do the data folks get involved here if at all, and how frequently do they get involved? Maybe Senthilnathan you could take that. >> Thank you, Dave for having me here. Well, based on whether the data element in question is in data cataloging or monitoring phase. Different data folks gets involved. When it doesn't the data cataloging stage. The data governance team, along with enterprise architecture or IT involved in setting up the data catalog. Which includes identifying the critical data elements business term identification, definition, documentation data quality rules, and data even set up data domain and business line mapping, lineage PA tracking source of truth. So on and so forth. It's typically in one time set up review certify then govern and monitor. But while when it is in the monitoring phase during any data incident or data issues IO-Tahoe broadcast data signals to the relevant data folks to act and remedy it as quick as possible. And alerts the consumption team it could be the data science, analytics, business opts are both a potential issue so that they are aware and take necessary preventative measure. Let me show you an example, critical data element from data quality dashboard view to lineage view to data 360 degree view for a zip code for conformity check. So in this case the zip code did not meet the past threshold during the technical data quality check and was identified as non-compliant item and notification was sent to the ID folks. So clicking on the zip code. Will take to the lineage view to visualize the dependent system, says that who are producers and who are the consumers. And further drilling down will take us to the detailed view, that a lot of other information's are presented to facilitate for a root cause analysis and not to take it to a final closure. >> Thank you for that. So Tiji? Patrick was talking about the as is to be. So I'm interested in how it's done now versus before. Do you need a data governance operating model for example? >> Typically a company that decides to make an inventory of the data assets would start out by manually building a spreadsheet managed by data experts of the company. What started as a draft now get break into the model of a company. This leads to loss of collaboration as each department makes a copy of their catalog for their specific needs. This decentralized approach leads to loss of uniformity which each department having different definitions which ironically needs a governance model for the data catalog itself. And as the spreadsheet grows in complexity the skill level needed to maintain. It also increases thus leading to fewer and fewer people knowing how to maintain it. About all the content that took so much time and effort to build is not searchable outside of that spreadsheet document. >> Yeah, I think you really hit the nail on my head Tiji. Now companies want to move away from the spreadsheet approach. IO-Tahoe addresses the shortcoming of the traditional approach enabling companies to achieve more with less. >> Yeah, what the customer reaction has been. We had Webster Bank, on one of the early episodes for example, I mean could they have achieved. What they did without something like active data quality and automation maybe Senthilnathan you could address that? >> Sure, It is impossible to achieve full data quality monitoring and remediation without automation or digital workers in place reality that introverts they don't have the time to do the remediation manually because they have to do an analysis conform fix on any data quality issues, as fast as possible before it gets bigger and no exception to Webster. That's why Webster implemented IO-Tahoe's active DQ to set up the business, metadata management and data quality monitoring and remediation in the Snowflake cloud data Lake. We help and building the center of excellence in the data governance, which is managing the data catalog schedule on demand and in-flight data quality checks, but Snowflake, no pipe on stream are super beneficial to achieve in flight quality checks. Then the data assumption monitoring and reporting last but not the least the time saver is persisting the non-compliant records for every data quality run within the Snowflake cloud, along with remediation script. So that during any exceptions the respect to team members is not only alerted. But also supplied with necessary scripts and tools to perform remediation right from the IO-Tahoe's Active DQ. >> Very nice. Okay guys, thanks for the demo. Great stuff. Now, if you want to learn more about the IO-Tahoe platform and how you can accelerate your adoption of Snowflake book some time with a data RPA expert all you got to do is click on the demo icon on the right of your screen and set a meeting. We appreciate you attending this latest episode of the IO-Tahoe data automation series. Look, if you missed any of the content that's all available on demand. This is Dave Vellante theCUBE. Thanks for watching. (upbeat music)

>> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon North America 2020 virtual brought to you by Red Hat, the Cloud Native Computing Foundation and ecosystem partners. >> Hi, and welcome back to theCUBE. I'm Joep Piscaer, I'm covering KubeCon CloudNativeCon here remotely from the Netherlands. And I'm joined by Commvault, Mathew Pearson, he's a Senior Product Manager, as well as David Ngo, Vice President of Metallic Products and Engineering to talk about the cloud native space and data protection in the Cloud Native space. So both, welcome to the show. And I want to start off with kind of the why question, right? Why are we here obviously, but also why are we talking about data protection? I thought we had that figured out. So David, can you shed some light on how, data protection is totally different in the cloud native container space? >> Sure, absolutely, thank you. I think the thing to keep in mind is that, containers are an evolution and a revolution actually in the virtualization space in the cloud space. What we're seeing is that customers are turning more and more to SaaS based applications and infrastructure in order to modernize their data centers and their data state in their compute environments. And when they do that, they're looking for solutions that match how they deploy their applications. And SaaS for us is an important area of that space. So, Metallic is Commvault portfolio of SaaS delivered and SaaS native data protection capabilities and offerings to allow customers to take the advantage of the best SaaS that is easy to try, easy to buy, easy to deploy, no infrastructure required and combine that with the technology and experience of Commvault. It'll build over last 20 years to deliver an enterprise grade data protection solution delivered as SaaS. And so, with Kubernetes and deploying in the cloud and modernizing applications I think that's very appealing to customers to also be able to modernize their data protection. >> Yeah, so I get the SaaS part. I mean, SaaS is an important way of delivering services. It is especially in the mid-market, something customers prefer, they want to have that simplicity, that easy onboarding as well as the OPEX of paying a subscription fee instead of longer term fees. So, the delivery model makes sense that fits into, the paradigm of making it simple, getting started easily. I get that, but Metallic isn't a traditional backup solution in that sense, right? It's not backing up necessarily just physical machines or just virtual machines. It has a relevance in the cloud native space. And the way I understand it, and please, if you can shed some light on that, Matt, is how is it different? What does it do that kind of makes it stand apart? >> Yeah, look, what we've found is the application developers can be in control now. So it's not like a traditional backup, that's what's changed. At this point, the application developer is free to create the infrastructure that he or she needs. And that freedom has meant that a bunch of stateful applications, the apps that we didn't think were going to live in Kubernetes have made their way to Kubernetes and they're making their way fast. So why is Metallic different? Because it's taking its lead from the developer. So it's using things like namespaces and label selectors. So basically take input from the developer on what information is important and needs to be protected and then protecting it. So it's your easy button to keep that Kubernetes development protected while you keep pace with the innovation within the organization. >> So you raise a valid point, cloud native has many advantages. It also has an extra challenge to account for which is fragmentation, right? In the olden days, let's call it that. We had a virtual machine, maybe a couple dozen that made up an application. And it was fairly easy to pinpoint the kind of the sort of conference of an application. This is my application. But now with cloud native, applications data can basically live anywhere. In a single cloud vendor, in many different cloud accounts, across different services, even across the public clouds themselves, like in a true multi-cloud scenario and figuring out what is part of an application in that enormous fragmentation is a challenge I think is understated and underestimated in a lot of operational environments with customers, with their applications in production. And that's where I think a product needs to figure out how to make sure an application is still backed up, is still protected in the way that is necessary for that given application. So I wonder how that works with Metallic. How do you kind of figure out what part of that enormous fragmentation is part of a single application? >> Yeah, so Metallic effectively integrates and speaks natively with the kube-apiserver. So it's taking its lead from the system of truth which is the orchestrator, which is Kubernetes itself. So for example, if you say everything in your production namespace needs protection, every night or every four hours, whatever that may be, it steps out and asks Kubernetes what applications exist there. It then maps all of the associated API resources associated with that application including the persistent volumes and persistent volume claims, man throws up and grabs the data from them as well. And that allows us to then reapply or reschedule that application either back to that original cluster or to another one for application mobility, where they are. >> So how do you make sure you, it kind of, what's the central point where everything comes together for that given application? Is that something the developer does as part of their release process or as part of their CICD? How do you figure out what components are part of an application? >> That is definitely a big challenge in the industry today? So, today we use label selectors predominantly. We find developers have been educating us on what works for them. And they've said, "Our CICD system is going "to label everything associated with this app, "as namespaced, then non-named space resources. 'So just here, take my label, grab everything under that, "and you will be good." The reality is that doesn't work for every business. Some businesses drop things into a specific namespace. And then you've got the added challenge that all of your data doesn't actually just live in Kubernetes. What about your image registries? What about it HCD? What about your Source Code Control and CICD systems? So we're finding that even VMs as well are playing a part in this ecosystem right now until applications can fully migrate. >> Yeah, and then let's zoom out on that a little bit. I mean, I think it's great that developers now kind of have flipped the paradigm where backup and data protection used to be something squarely in the OPS domain. It's now made its way into the .dev domain where it's become fairly easy to tag resources as application X, application Y, and then it automatically gets pulled into the backup based on policies. I mean, that's great, but let's zoom out a little bit and figure out, why is this happening? Why are developers even being put in a position of backing up their applications? So David, do you want to shed some light on that for me? >> Sure, I think data protection is always going to be a requirement and you'll have persistent data, right? There are other elements of applications that will always need to be protected and data protection is often something that is an afterthought, but it's something that needs to be considered from the beginning. And Metallic in being able to support deployments, not just in the cloud, but on-premises as well. We support any number of certified distributions of Kubernetes, gives you the flexibility to make sure that there was apps and that data is protected no matter where it lives. Being able to do that from a single pane of glass, being able to manage your Kubernetes deployments in different environments is very important there. >> So let's dive into that a little bit. I hear you say, Certified Kubernetes Distributions. So what's kind of the common denominator we need to use Metallic in an environment? Because I hear On-Prem, I hear public cloud. So it seems to me like this is a pretty broad product in terms of what it supports in its scope. But what's the lowest common denominator for instance, in the On-Prem environment? >> Sure, so we support all CNCF certified distributions of Kubernetes today. And in the cloud, we support Azure with AKS and AWS with EKS. So you can really use the one Metallic environment, the one interface to be able to manage all of those environments. >> And so what about that storage underneath? Is that all through CSI? >> Yes. So we support CSI on the backend of the Kubernetes applications, and we can then protect all the data stored there. >> And so how does this, I mean, you acquired Hedvig about a year ago, I want to say. Not sure on the exact date, but you acquired Hedvig a little while ago. So how does that come into play in Metallic offering? >> Sure, the Hedvig distributed storage platform is a fantastic platform on which to provision and scale Kubernates's applications and clusters. And that having full integration with Kubernetes on the storage side, we support that natively and really builds on the value that Commvault can bring as a whole with all of its offerings as a platform to Kubernetes. >> All right. So, zooming out just a little more, I want to get a feel for the cover of the portfolio of Commvault, as we're ushering into this cloud native era, as we're helping customers make that move and make that transition. What's the positioning of Metallic basically in the transformation customers are going through from On-Prem kind of lift and shift cloud into the cloud native space? >> Yeah, so with today's announcements, our hybrid cloud support and our hybrid cloud initiatives really help customers manage data wherever it lives as I've mentioned earlier. Customers can start with workloads On-Prem and start protecting workloads that they either have migrated or starting to build in the cloud natively and really cover the gamut of infrastructure and hypervisors and file systems and storage locations amongst all of these locations. So from our perspective, we think that hybrid is here to stay, right? There are very few customers who are either going to be all on-premises or all in the cloud. Most customers have some requirement that keeps them in a hybrid configuration, and we see that being prevalent for quite some time. So supporting customers in their transformation, right? Where they are moving applications from on-premises to the cloud, either refactoring or lift and shift, or what have you. It's very important to them, it's very important for us to be able to support that motion. And we look forward to helping them along the way. >> Awesome, so one last question for Matt. I mean, Metallic is a set of servers, right? That means you run it, you operate it, you build it. So I wonder, is Metallic itself cloud native? How does it scale? What are kind of the big components that Metallic has made up of? >> So Metallic itself is absolutely cloud native. It is sitting inside Azure today. I won't go into all the details. In fact, David could probably provide far more detail there. But I think Metallic is cloud native with respect to the fact that it's speaking natively to your applications, your cloud instances, your Vms. And then it's giving you the agility and the ability to move them where you need them to be. And that's assisting people in that migration. So in the past, we helped people get from P to V. Now that there are virtualized, applications like Metallic can protect you wherever you are and get you to wherever you need to be, especially into your next cloud of choice. And there's always another cloud. What I'm interested to see and what I'm hoping to see out of KubeCon is how are we doing with KubeVirt and Kubernetes becoming the orchestrator of the data center. And how are we doing with some of these other projects like application CRDs and hierarchical namespaces that are truly going to build a multi-tenanted software defined, distributed application ecosystem, that Metallic I can speak natively to via Kubernetes. >> Awesome. Well, thank you both for being with me here today. I certainly learned a ton about Metallic. I learned a lot about the challenges in cloud native that'll certainly be an area of development in the next couple of years. As you know, that the CNCF will continue to support projects in this space and vendors to work with us in that space as well. So that's it for now. I'm Joep Piscaer, I'm covering for KubeCon here remotely from the Netherlands. I will see you next time, thanks. (bright upbeat music)

>> Live, from Bahrain it's theCUBE. Covering AWS Summit Bahrain. Brought to you by Amazon Web Services. >> Okay, welcome back everyone. It's the theCUBE's coverage here, in Bahrain, in the Middle East, for our coverage of AWS Summit and the announcement, and now soon to be up-and-running in 2019 in Q1, Amazon Web Services, full region here in the Middle East. Should have a massive impact to the ecosystem, and companies and entrepreneurs from around the borders. We've got great conversations all day. And today we've got to great guests here, Emilio Valdes, VP of EMEA South and Latin America for Informatica. Thank you for theCUBE sponsorships over the years. We've covered Informatica shows all over the world. Mathew Joseph, business head of Data Analytics for Wipro. Good to see you, thanks for joining us. >> It's a pleasure. >> Same >> Great to be here. >> So, Informatica, we know a lot about you. We cover all of your big events in North America, I interviewed your CEO, I've been following the value proposition, growing really well, you've got a good product offering. But we're in the Middle East, okay? And what I've learned here is that there's a thirst for entrepreneurship. There's a thirst for cloud. But everyone's talking about data. And if data's the new oil, no better place to be than in the Middle East. They know the value of oil. What's going on in town here? What's happening in the Middle East? >> Right, so, as I cover a pretty big area within Informatica, I used to travel the world and meet many customers, in many places, many customers and many industries here in the Middle East. And I can tell you that, you know, the story, the messages are very consistent, you know? Every company, every industry, is going through a massive period of change, and companies are reacting to this change very differently. What we've seen is that the disrupters are going to be the ones that will, you know, implement digital transformation consistently, and we believe that data is the key driver for intelligent digital transformation. Here in the Middle East is no different. We've been seeing this across the different countries, in Dubai, in Bahrain, in Kuwait, in Saudi Arabia, exactly the same as everywhere else in the world. >> And cloud's now coming in full throttle at Amazon, You guys are not new to Amazon. I know you guys do a ton of work with Amazon integrating and putting all this together, what do you think is going to happen, here? Now Amazon gets up and running, they're already using a cloud now, so Bahrain's clear, cloud first. Saudi's got the cloud bug too, they're doing great things. So when an actual region comes here, what do you think is going to happen? An explosion of innovation and more business? What's going to be the impact? >> Well I think, I think the market knows what the benefits they can get out of the AWS platform, and I believe the challenges are related to get the most out of this AWS platform. At Informatica, we are going to help customers to move their data to the cloud in a consistent manner that is connected, articulated, properly governed, and not only this, but also we believe that the key value is in the hybrid world. The world hasn't moved to the cloud yet, entirely, so most companies continue to have some on-premise applications, as well as their cloud applications. So I believe that Informatica can help customers here in the Middle East, by connecting the on-premise world with the cloud world. And at the same time, the value they can get from our platform is by making AWS easy to operate, and, you know, move data to the cloud in a consistent, quick, and sustainable manner. >> So Matthew Joseph, you're with Wipro, why are you guys together, what's the relationship? Obviously we know what you guys do, you guys do great work, global, around the world. We see you at all the events. From SAP Sapphire, EMC World, now Dell World, Reinvent, you guys are everywhere. So here, what's going on here? I mean, analytics, you need analytics. You're good at analytics >> First of all, John, thanks a lot. A couple of thoughts. One, Wipro has been a global partner of AWS. Wipro's a global partner of Informatica. And the region is going through massive change of innovation, of using, consuming data. And at this point we really feel that both the expertises should come together to manage the change. And that's the simple reason why Informatica and Wipro are together, along with AWS and this, I would say a historical movement of this part of the world, to actually consume this rate and transfer the data for all of us. >> So if I asked you a question that said, hey, tell me about your relationship with Informatica. What's in it for me? What do you do for me? Are you, are you bringing it together? Are you guys going to market together? How do you, how do I win with you and Informatica? >> So what we have done is, as I told, the global partnership, across the globe, the best practices we're bringing back to this part of the world, to make sure that we have a similar set of stories across the global sphere. This certainly means more repeatability, less risk, and for the entire government to go through a small transition of going to the cloud. >> And data disruption is huge. You guys have Informatica 3.0, and you guys have your practice. When you put that together, what's the go to market? What's the value proposition? What's the pitch to the customer? >> So the key part is the IPaas method, the platform as a service message, right? With the platform as a service, it's a market that Gartner has identified as a $12.5 billion market. And it's growing very rapidly. Just to give you an idea, we process three trillion transactions per month, and this number is being multiplied by three every three to four months, right? So the iPaaS platform is what is going to help customers to move from the on-premise world, to the cloud. And this is where the key value Informatica, and Wipro, can put together to facilitate and to help enable customers in their journey to the cloud. >> So talk about the Amazon impact, obviously you guys do work with Amazon. What, specifically, does Amazon have that you guys like? That you work with the most with customers? Obviously they want to know, obviously you know, I got data, a ton of data. I've got to manage it. I mean, analytics are pretty good. You've got Sagemakers, Hotrock, on fire. Redshift everyone knows is doing well. Kinesis, with streaming. What's some of the Amazon tools you guys are working with around some of these day-to-day opportunities? >> Yeah, so there are multiple of them. In fact today's the day when the big data is pouring in, for example, right? So how do I really bring in all the data into a common platform? And today the customer is also talking about how do they really consume it? So consumption is a major attraction for AWS and how they really consume this data. The extraction, making sure the data is available, furthers decision making in the second part. The way Wipro and Informatica positions this entire journey is not just about putting the data into a common place and building up a transformation, right? What you're looking at is how do I really change the way the business works? And elements of design principal come in on it. And what Wipro has literally done is, we've done a lot of investments around how to I really make this transformation from a design-thinking point of view? How do I make sure the best practices of data science, and governance comes into it? How do I make sure that the press points for the customer are so clear and so vivid that decisions are made based on that? And I feel AWS, out in the region, is doing a great work on that. And that's the simple reason why all of us are together with that. >> That's great. And cloud, you guys are no stranger to Amazon. >> We are partner of Amazon. And we've been a partner of Amazon AWS for awhile. As well as Wipro is a partner of Amazon. And Informatica and Wipro are global partners as well. We're quite excited about bringing this partnership to the region. >> What sort of things that you guys have done together, can you share some examples of some awesome implementation and use cases? >> A few of them. So to me, what is happening, as I was earlier telling is that most of the government entities are talking about how do I really consume this data. How do I really think of it as an experience? So what we have really done is pull up this data, look at various models on how I can do revenue generation for the customer. How can I bring in more customers' recommendation? How do I make impactful decisions based on those data? And the ample amount of programs use cases that you have already implemented in this part of the world, and certainly Informatica has been a great help in this journey of ours. So the teams around which we look out, is data monetization, customizability, researching degree of the customer, operating efficiency, and this is true across industries. Government is doing a fabulous job of going on this journey but certainly we do a lot of work in the oil and gas sector, in the healthcare, and similar things like that. >> Awesome, and what's core value proposition that you guys are offering customers out here? >> I believe it's the messages we discussed earlier. It's having a consistent platform where data gets together and can be used across different applications, business units, et cetera. At the end of the day, end users will need to use data and they don't care where this data is stored. It could be in the cloud, it could on premise, it could be in a big data application, it doesn't really matter, you know? >> It could be addressable. >> Exactly >> In real time too in low latency. It can't be some data warehousing thing that takes, you know, real time application like a car needs data. IoT, a huge growth area. I mean these are new cloud architectural opportunities. You can't be having the old way. >> The data has to be connected, and secure, and clean, and available, and consistent. This is what we do for a business. >> Yeah you guys have got some good story there. Good luck with everything. I want to get your final questions as we kind of round down the day here. The day's kind of cleaning out here behind us. You can see it's getting quieter. What do you think about what's happening here? Amazon Web Services Summit, mix a little public sector, you've got some commercial, but this region pulsing with cloud demand. What do you think, guys? What's your thoughts? >> I think we're going to help the government to move to the cloud. We're very excited about the announcement that we heard this morning. The cloud-first policy. I think that Wipro and Informatica are uniquely positioned to give the government what they need to be successful in their cloud-first policy >> Thoughts? >> Same here, I think the last 24 months we have seen a lot of initiative from the government. Both across the artificial and then about data being the center of all things. And cloud is going to be a very pivotal role in this. And I think we are geared very well to take care of it. >> I think you guys are well positioned enough, you know. My translation is you see their cloud-first policy, they want to be involved in FinTech in the future, you got to have a data strategy to center the value proposition everything's got to be built around how that data's going to move, how it's going to be addressed, how it's going to be consumed, shared, connected. Across the board, IoT, on premises, real-time mobile, everything. >> And John, one more point, to close, would be what we see is the hybrid architecture coming up, alright? So cloud being one of them, the customers still want data inside the premises as well, so how do you really look at the hybrid architecture, and the challenges around it. I don't think there are many companies in this part of the world who are geared up to that. Wipro has done it multiple times, Informatica has been a leader in that. And I think that is going to be a game changer for all of us. >> You know Mathew you made me smile because, thank you for making me smile, because we always joke, and I always talk on theCUBE, and usually Dave Vellante's here and we kind of argue about it, because I say data is the new oil, he says it's not the new oil because oil can only be used in the car I guess, we can always go back and forth. But I've been saying that cloud is the future, I've been saying it for many years. Amazon certainly is more hardcore, Andy Jassy, all data systems moved to the cloud, What does that mean? Just announced RDS on VMware on premises, so it kind of like, takes that window, but I say that the cloud, operationally, is what's going on. People are moving to operations that are cloud-linked. So if everything is running cloud operations, DevOps, infrastructure as code, AI, all the things that you guys are working on, that means that the data center and on-premises, is an edge device. Or is it? It's a big fat edge. Or what's the difference between a windmill and an on-premise campus? I mean, edges? So, this is the debate we've been having. What is an edge? >> The way we see it is customers having a journey, in a journey to the cloud. And the state of the art is very different. We're happy to help customers to go through this journey efficiently, quickly, and in a consistent manner. >> And all serious, putting the fun kind of comment aside about the argument we had about the edge, is that the architecture that we see people are going to is, don't let some pre-defined thing define where the data has to go. So this data out there, it's got to move around. And if you don't want it to move around, then you put Compute to it. So there's all kinds of things going on where you don't have to get dogmatic about it. >> Absolutely >> What the definition is. It's all running cloud operations, then it's cloud, right? I mean it's not on-premises operations, no one says that. Anyway thanks for coming on theCUBE, thanks for sharing. Great to see Informatica here, great to see Wipro. We've got to get more of these use cases, if we had more time we would. This is theCUBE coverage, here, in Bahrain for Amazon Web Services Summit. Stay with us for more coverage after this break. (electronic music)

(upbeat music) >> Hey, welcome back everybody Jeff Frick here with theCUBE. We're in our Palo Alto studios, the conference season is getting ready to ramp up, it hasn't really hit full speed yet, so, it gives us the opportunity to have CUBE Conversations, and we're really excited to have our next guest, we haven't had him on for quite a while, George Mathew. He's the chairman and CEO of Kespry. George great to see you. >> Jeff, great to be here. Thanks for having me. >> So, you used to be big time in the data analytics world we used to see you at all the big data shows, and now you've made the move to autonomous flying machines. >> I did, I did, and there's a very strong relationship between the two, right? When you look at the lot worth that I was doing in the horizontal data analytic space, there was really a need to be able to accumulate data and process and understand that, and make better decisions off of it. Well, when you look at the industrial world that Kespry serves today, the ability to drive a full, complete application, where sensor based data is now being processed in our cloud infrastructure, and packaged up as complete applications, is exactly the market that we're focused on. >> So, George also a lot of big words. Let's talk about the fun words. >> Sure. >> You have drones, you have cool industrial drones. >> That's right. >> So, but what you've done is different than some the more popular drones that people know, some of the big names. You guy are really kind of single purpose, industrial only, totally integrated solution, sold as a service. >> Is that accurate? >> That's right. When you look at the drone space today, it's a big market. Its actually a 100 billion dollar market overall for drones. just in the commercial aspect of the drone space, it's a 15, 16 billion dollar market. Industrial use cases are proliferating everywhere. Kespry actually started in the mining aggregate space, where we were able to take our industrial grade drone, be able to do volumetric stock pile measurement to a level of accuracy that was literally down to one, two percent forecast accuracy, because we can now take imagery and convert that to super accurate three dimensional models of a mine site, of a query, and be able to make better decisions on how much inventory you had on that work site. >> Now, let's dive into that a little bit, cus most people when they think of drones, they think of, aerial photography at their wedding, and sweeping shots at the beach of their Maui vacation. But the industrial applications are real, and these are huge pieces of real estate that you're operating over. Huge masses of material, and men, and machines. So, the impacts, of small incremental impacts in being able to measure, and make decisions on that, have huge financial impact. >> So, what's amazing with drone tech that's available today, think about it as the new sensor network Jeff, so it's not just the fact that we can take images off a drone. It's the fact that we can take those images, and combine that with additional sensor based input. One of the key elements that Kespry introduced into the market, is taking imagery, and being able to augment the ability to have precision GPS along with that images. So, you can now have images that are processed in our cloud that are converted into full three dimensional models, and each one of those models are hyper accurate within three centimeters of real space. So, when you want to apply that for a full topological assessment of what a construction site looks like. If you wanted to measure the amount of volumetric stock pile of material that might be on 250 acres, you can fly a drone overhead in 30 minutes, be able to collect all that sensor based input, and process that in the cloud and have very accurate answers in terms of what's happening on an industrial work site without the danger and the challenges of manually collecting that information. >> Cus how did they do it before? >> Yup >> What was state of the art three years ago? >> The status quo in the market was being able to collect that data using a GPS backpack or laser guided precision equipment, but you still needed to have someone manually be able to bring that equipment to the work site. Often times, the data that you were collecting, you know, on a volumetric measurement of a stock pile, might be 20, 30, 40 points of measurement. When you're flying a drone overhead, and converting the imagery into a point cloud, you're creating five, six hundred thousand points of measurement. >> Right. >> And so the accuracy of what you're able to now accomplish with a level of safety, is unprecedented. >> Well, it's interesting, one of the Kespry tag lines is no joysticks, which I think is kind of funny. >> That's right. >> But the fact that it's really an automated system. You're selling us solutions. I'm teasing you about having fun with drones and flying with vacation, but that's not what it is. Basically it's a platform in which to deploy sensors. Which could be visual sensors, could be infrared sensors, could be GPS, could be all kinds of stuff, so it really opens up a huge opportunity to put different types of payloads, for different use cases into use. >> That's right, when you think about where Kespry's differentiation in the market is. We've introduced that capability to have different payloads, and be able to fuse those sensors together in a meaningful way, and combine that with a fully autonomous solution for flight control. So, now you don't have to have specialist piloting skills to be able to collect that information. The sensor based input is fused in a way where we can process that in our cloud infrastructure. We add a series of artificial intelligence machine learning algorithms to augment what's coming off of these sensors, and then package them as industrial grade applications. Good examples: inventory management in the mining aggregate space. Being able to do full earth works topological assessment in construction projects. Being able to do claims management for what the dimensionality, and their current state of a roof might be after a weather event has occurred. To be able to understand the number of missing shingles. The amount of hail damage that's occurred, and so all of these applications are packaged in an end to end manner, so that, you as a decision maker, and you as a user, don't have to be, you know, basically, playing with broken toys, to be able to get very clean answers in terms of what's happening in physical space. >> The roof story is so fascinating to me, 'cause people just think "oh it's a roof," they have no idea to really think through the impact of roofing in commercial real estate, and in industrial real estate. You know, roofs are where buildings fail, and so roofs, roof inspections is a really really important piece of title processes, and operational processes, so to be able now to automate that. It's classic right, automated, data driven, software driven, processes, really is a game changer versus having to send somebody up on a roof to physically inspect, I mean the accuracy's got to just be ore's of magnitude better. >> So, a few facts there, right. First of all, it's a multi billion dollar industry. You won't believe that just hail alone as far as damage that occurs on an annualized basis, is a 2.4 billion dollar challenge. It's also, the third most-- >> Is that in the U.S only? >> In the US, it's the third most occupationally hazardous job in the country, where people fall off roofs all the time when they're doing this kind of inspection. So, when you're able to now apply a drone to fly over that roof autonomously, collect that data, do the dimensional analysis, as well as being able to create the hail damage model, or the missing shingle model. You're now effectively enabling that claim process, for instance for the insurance carrier to adjudicate a claim to effectively happen within hours, right, after you know, you're on site. What we're seeing today in the market, is, if you're effectively looking at a claims assessment process, a claims adjuster would usually take about a day to cover three homes. With the use of a Kespry drone, we're seeing that same claims adjuster cover three homes in an hour. It's a massive productivity gain for this industrial use case. >> So, that brings up another topic. We've gone to a couple commercial drone shows and obviously it's a cool space, it's a fun space, but it's also really important space. I just think back to the end of World War I, when suddenly there were these things called airplanes, and the military trying to figure out, what do we do with this new asset, and those people maybe don't know that the Air Force was actually, the Army Air Force at the beginning. They didn't think that they needed a different branch, with different tactics, strategy, training, governance, et cetera. So, as we look at kind of, commercial drones entering into the business space, and I'm sure you've seen it, in some of these aggregate examples, construction. How having an air force, as a company, as a resource, you know, air deployed assets is such a big game changer. It's going to people a long time to figure out how to use it beyond the obvious in the short term, but it's a completely different tool, to apply to your business problems. >> This is why we consider this a whole new category of aerial intelligence, right. When you think about the capabilities that we're going to be able to deliver, as far as very accurate views of physical space, and being able to digitize it, to be able to model it, to be able to predict the material assets that are on a work site, and understand what the future value is, what the challenges might be for a maintenance cycle, to be able to understand the level and extent of damage, the anomaly detection, these are all incredible use cases that are opening up as we speak. I remember when I was on the show years ago, and we talked about the data analytics space, and particularly the self service aspect that I was pretty involved in, we used to talk about it being in the early innings of a ball game. Well, in the aerial intelligence market, we were literally in the first inning of the ball game. Like it is just getting off the ground, and when you think about the regulatory frameworks that are effectively in place, even as of 2016. The commercial operations in the United States have just opened up. You're now able to legitimately fly below 400 feet of air space. Maintaining the drone with a visual line of sight where a human operator is involved, that has actually passed the part 107 pilots exam. So, it's a framework. It's a start, but there's so much more expansion opportunities that occur when we're flying over people, when we're de-conflicting the air space, when we have the ability to do night flights, when we have the ability to be able to literally have that drone fly, without having a human operator controlling it, and understanding the visual line of sight where the drone is operating. So, these are all going to happen in the next several years, and completely open up the aerial intelligence market accordingly. >> It's fascinating, and of course the other thing that you're doing, which all good companies do, and all good entrepreneurs do, is build on the shoulders of others. So you're leveraging cloud, you're leveraging A.I., you're using the flight controls, you're using mobile applications, you're using all these bits and pieces of infrastructure, and you've packaged it up to deliver it as a service, which is fantastic. >> This is one of the fundamentals tenants for Kespry, even as of our founding in 2013. We knew that there was a lot of broken toys in the market, because if you had to take a consumer grade solution, be able to roll your own software, to be able to look at the way you collect that data on a manual basis, to be able to process that information, and get to results without having this connectivity involved with the entire end to end experience, we knew that a lot of companies could not succeed in their aerial intelligence offerings. And this is why Kespry believed that a full end to end solution, the way we built it, was better for the industrial markets that we serve, and so far so good. This past week we actually announced, just in the mining aggregate space alone, we have over 170 customers, and-- >> 170? >> Correct. Just in mining aggregate. >> How long has Kespry been around? >> We've been in business since we were founded in 2013. We started commercial operations in 2015. >> Wow. >> Amazingly, we covered over 10,400 just, mining query work sites, just in those last two and a half years that we've been in commercial operation. So, this is something that has really exponentialized, just in that market, and we're seeing similar adoptions starting to take off in the insurance roofing space, as well the construction markets. >> It's so funny. I just consider, you're an autonomous vehicle. You're just one that flies, not, that drives on the road, but, there's so much going on on the commercial side that people don't see, you know? They see the Lambo cars driving around the neighborhood, and we read about what's going on with Tesla, but on the agg side, on the commercial side, with John Deere, and these huge mining trucks, that many of them are already autonomous. This stuff is really moving very very quickly on the commercial side. >> If you think about the digital transformation of industrial work. This is a one trillion dollar market opportunity over the next several decades, and the ability to sense physical assets, and be able to make better decisions using drone tech, using other sensor based information. This is transforming the nature of industrial work, right? This is, in my view, the beginning of the fourth industrial age, and in that regard, we see this as something that's not just, like I said, you know, the first few innings of a ball game. We're going to see this evolve for decades, as we move forward. And drones are effectively a critical piece of that infrastructure evolving. >> Yeah, just in delivery. Just sensor delivery is basically what it is. Place it in places that people maybe shouldn't go, don't want to go, that dangerous to go, it makes a ton of sense. >> And then being able to blend that with the other sensors that might be on the ground, that might be in other places, that you can fuse that information together to get better understanding of physical space. >> Yeah, I love it. I love the solution approach, right. Nobody ever buys a new platform, but it sure is great to build a platform underneath a terrific application, that then you can expand after you knock it out of the park with that first application. >> And that's exactly the approach that we're going after >> All right. Well Mat, hopefully it won't be a, we looked it up before. Last time you were on was like 2014, so hopefully-- >> It's been a while. >> It won't be so long before we see you next, and thanks for stopping by. >> Thanks for having me on board, Jeff. >> All right, he's George Mathew. I'm Jeff Frick, You're watching theCUBE. Thanks for watching, I'll see you next time. (upbeat music)

>>The cube at big data SV 2014 is brought to you by headline sponsors. When disco we make Hadoop invincible and Aptean accelerating big data, 2.0, >>Okay. We're back here, live in Silicon valley. This is big data. It has to be, this is Silicon England, Wiki bonds, the cube coverage of big data in Silicon valley and all around the world covering the strata conference. All the latest news analysis here in Silicon valley, the cube was our flagship program about the events extract the signal from noise. I'm John furrier, the founders of looking angle. So my co-host and co-founder of Wiki bond.org, Dave Volante, uh, George Matthew CEO, altruist on the cube again, back from big data NYC just a few months ago. Um, our two events, um, welcome back. Great to be here. So, um, what fruit is dropped into the blend or the change, the colors of the big data space this this time. So we were in new Yorkers. We saw what happened there. A lot of talk about financial services, you know, big business, Silicon valley Kool-Aid is more about innovation. Partnerships are being formed, channel expansion. Obviously the market's hot growth is still basing. Valuations are high. What's your take on the current state of the market? >>Yeah. Great question. So John, when we see this market today, I remember even a few years ago when I first visited the cave, particularly when it came to a deep world and strata a few years back, it was amazing that we talked about this early innings of a ballgame, right? We said it was like, man, we're probably in the second or third inning of this ball game. And what has progressed particularly this last few years has been how much the actual productionization, the actual industrialization of this activity, particularly from a big data analytics standpoint has merged. And that's amazing, right? And in a short span, two, three years, we're talking about technologies and capabilities that were kind of considered things that you play with. And now these are things that are keeping the lights on and running, you know, major portions of how better decision-making and analytics are done inside of organizations. So I think that industrialization is a big shift forward. In fact, if you've listened to guys like Narendra Mulani who runs most of analytics at Accenture, he'll actually highlight that as one of the key elements of how not only the transformation is occurring among organizations, but even the people that are servicing a large companies today are going through this big shift. And we're right in the middle of it. >>We saw, you mentioned a censure. We look at CSC, but service mesh and the cloud side, you seeing the consulting firms really seeing build-out mandates, not just POC, like let's go and lock down now for the vendors. That means is people looking for reference accounts right now? So to me, I'm kind of seeing the tea leaves say, okay, who's going to knock down the reference accounts and what is that going to look like? You know, how do you go in and say, I'm going to tune up this database against SAP or this against that incumbent legacy vendor with this new scale-out, all these things are on in play. So we're seeing that, that focus of okay, tire kicking is over real growth, real, real referenceable deployments, not, not like a, you know, POC on steroids, like full on game-changing deployments. Do you see that? And, and if you do, what versions of that do you seeing happening and what ending of that is that like the first pitch of the sixth inning? Uh, w what do you, how would you benchmark that? >>Yeah, so I, I would say we're, we're definitely in the fourth or fifth inning of a non ballgame now. And, and there's innings. What we're seeing is I describe this as a new analytic stack that's emerged, right? And that started years ago when particularly the major Hadoop distro vendors started to rethink how data management was effectively being delivered. And once that data management layer started to be re thought, particularly in terms of, you know, what the schema was on read what the ability to do MPP and scale-out was in terms of how much cheaper it is to bring storage and compute closer to data. What's now coming above that stack is, you know, how do I blend data? How do I be able to give solutions to data analysts who can make better decisions off of what's being stored inside of that petabyte scale infrastructure? So we're seeing this new stack emerge where, you know, Cloudera Hortonworks map are kind of that underpinning underlying infrastructure where now our based analytics that revolution provides Altrix for data blending for analytic work, that's in the hands of data analysts, Tableau for visual analysis and dashboarding. Those are basically the solutions that are moving forward as a capability that are package and product. >>Is that the game-changing feature right now, do you think that integration of the stack, or is that the big, game-changer this sheet, >>That's the hardening that's happening as we speak right now, if you think about the industrialization of big data analytics that, you know, as I think of it as the fourth or fifth inning of the ballgame, that hardening that ability to take solutions that either, you know, the Accentures, the KPMGs, the Deloitte of the world deliver to their clients, but also how people build stuff internally, right? They have much better solutions that work out of the box, as opposed to fumbling with, you know, things that aren't, you know, stitched as well together because of the bailing wire and bubblegum that was involved for the last few years. >>I got it. I got to ask you, uh, one of the big trends you saw in certainly in the tech world, you mentioned stacks, and that's the success of Amazon, the cloud. You're seeing integrated stacks being a key part of the, kind of the, kind of the formation of you said hardening of the stack, but the word horizontally scalable is a term that's used in a lot of these open source environments, where you have commodity hardware, you have open source software. So, you know, everything it's horizontally scalable. Now, that's, that's very easy to envision, but thinking about the implementation in an enterprise or a large organization, horizontally scalable is not a no brainer. What's your take on that. And how does that hyperscale infrastructure mindset of scale-out scalable, which is a big benefit of the current infrastructure? How does that fit into, into the big day? >>Well, I think it fits extremely well, right? Because when you look at the capabilities of the last, as we describe it stack, we almost think of it as vertical hardware and software that's factually built up, but right now, for anyone who's building scale in this world, it's all about scale-out and really being able to build that stack on a horizontal basis. So if you look at examples of this, right, say for instance, what a cloud era recently announced with their enterprise hub. And so when you look at that capability of the enterprise data hub, a lot of it is about taking what yarn has become as a resource manager. What HDFS has been ACOM as a scale-out storage infrastructure, what the new plugin engines have merged beyond MapReduce as a capability for engines to come into a deep. And that is a very horizontal description of how you can do scale out, particularly for data management. >>When we built a lot of the work that was announced at strata a few years ago, particularly around how the analytics architecture for Galerie, uh, emerged at Altryx. Now we have hundreds of, of apps, thousands of users in that infrastructure. And when we built that out was actually scaling out on Amazon where the worker nodes and the capability for us to manage workload was very horizontal built out. If you look at servers today of any layer of that stack, it is really about that horizontal. Scale-out less so about throwing more hardware, more, uh, you know, high-end infrastructure at it, but more about how commodity hardware can be leveraged and use up and down that stack very easily. So Georgia, >>I asked you a question, so why is analytics so hard for so many companies? Um, and you've been in this big data, we've been talking to you since the beginning, um, and when's it going to get easier? And what are you guys specifically doing? You know, >>So facilitate that. Sure. So a few things that we've seen to date is that a lot of the analytics work that many people do internal and external to organizations is very rote, hand driven coding, right? And I think that's been one of the biggest challenges because the two end points in analytics have been either you hard code stuff that you push into a, you know, a C plus plus or a Java function, and you push it into database, or you're doing lightweight analytics in Excel. And really there needs to be a middle ground where someone can do effective scale-out and have repeatability in what's been done and ease of use. And what's been done that you don't have to necessarily be a programmer and Java programmer in C plus plus to push an analytic function and database. And you certainly don't have to deal with the limitations of Excel today. >>And really that middle ground is what Altryx serves. We look at it as an opportunity for analysts to start work with a very repeatable re reasonable workflow of how they would build their initial constructs around an analytic function that they would want to deploy. And then the scale-out happens because all of the infrastructure works on that analyst behalf, whether that be the infrastructure on Hadoop, would that be the infrastructure of the scale out of how we would publish an analytic function? Would that be how the visualizations would occur inside of a product like Tableau? And so that, I think Dave is one of the biggest things that needs to shift over where you don't have the only options in front of you for analytics is either Excel or hard coding, a bunch of code in C plus plus, or Java and pushing it in database. Yeah. >>And you correct me if I'm wrong, but it seems to be building your partnerships and your ecosystem really around driving that solution and, and, and really driving a revolution in the way in which people think about analytics, >>Ease of use. The idea is that ultimately if you can't get data analysts to be able to not only create work, that they can actually self-describe deploy and deliver and deliver success inside of an organization. And scale that out at the petabyte scale information that exists inside of most organizations you fail. And that's the job of folks like ourselves to provide great software. >>Well, you mentioned Tableau, you guys have a strong partnership there, and Christian Chabot, I think has a good vision. And you talked about sort of, you know, the, the, the choices of the spectrum and neither are good. Can you talk a little bit more about that, that, that partnership and the relationship and what you guys are doing together? Yeah. >>Uh, I would say Tableau's our strongest and most strategic partner today. I mean, we were diamond sponsors of their conference. I think I was there at their conference when I was on the cube the time before, and they are diamond sponsors of our conference. So our customers and particular users are one in the same for Tablo. It really becomes a, an experience around how visual analysis and dashboard, and can be very easily delivered by data analysts. And we think of those same users, the same exact people that Tablo works with to be able to do data blending and advanced analytics. And so that's why the two software products, that's why the two companies, that's where our two customer bases are one in the same because of that integrated experience. So, you know, Tableau is basically replacing XL and that's the mission that thereafter. And we feel that anyone who wants to be able to do the first form of data blending, which I would think of as a V lookup in Excel, should look at Altryx as a solution for that one. >>So you mentioned your conference it's inspire, right? It >>Is inspiring was coming up in June, >>June. Yeah. Uh, how many years have you done inspire? >>Inspire is now in its fifth year. And you're gonna bring the >>Cube this year. Yeah. >>That would be great. You guys, yeah, that would be fun. >>You should do it. So talk about the conference a little bit. I don't know much about it, but I mean, I know of it. >>Yeah. It's very centered around business users, particularly data analysts and many organizations that cut across retail, financial services, communications, where companies like Walmart at and T sprint Verizon bring a lot of their underlying data problems, underlying analytic opportunities that they've wrestled with and bring a community together this year. We're expecting somewhere in the neighborhood of 550 600 folks attending. So largely to, uh, figure out how to bring this, this, uh, you know, game forward, really to build out this next rate analytic capability that's emerging for most organizations. And we think that that starts ultimately with data analysts. All right. We think that there are well over two and a half million data analysts that are underserved by the current big data tools that are in this space. And we've just been highly focused on targeting those users. And so far, it's been pretty good at us. >>It's moving, it's obviously moving to the casual user at some levels, but I ended up getting there not soon, but I want to, I want to ask you the role of the cloud and all this, because when you have underneath the hood is a lot of leverage. You mentioned integrates that's when to get your perspective on the data cloud, not data cloud is it's putting data in the cloud, but the role of cloud, the role of dev ops that intersection, but you're seeing dev ops, you know, fueling a lot of that growth, certainly under the hood. Now on the top of the stack, you have the, I guess, this middle layer for lack of a better description, I'm of use old, old metaphor developing. So that's the enablement piece. Ultimately the end game is fully turnkey, data science, personalization, all that's, that's the holy grail. We all know. So how do you see that collision with cloud and the big, the big data? >>Yeah. So cloud is basically become three things for a lot of folks in our space. One is what we talked about, which is scale up and scale out, uh, is something that is much more feasible when you can spin up and spin down infrastructure as needed, particularly on an elastic basis. And so many of us who built our solutions leverage Amazon being one of the most defacto solutions for cloud based deployment, that it just makes it easy to do the scale-out that's necessary. This is the second thing it actually enables us. Uh, and many of our friends and partners to do is to be able to bring a lower cost basis to how infrastructure stood up, right? Because at the end of the day, the challenge for the last generation of analytics and data warehousing that was in this space is your starting conversation is two to $3 million just in infrastructure alone before you even buy software and services. >>And so now if you can rent everything that's involved with the infrastructure and the software is actually working within days, hours of actually starting the effort, as opposed to a 14 month life cycle, it's really compressing the time to success and value that's involved. And so we see almost a similarity to how Salesforce really disrupted the market. 10 years ago, I happened to be at Salesforce when that disruption occurred and the analytics movement that is underway really impacted by cloud. And the ability to scale out in the cloud is really driving an economic basis. That's unheard of with that >>Developer market, that's robust, right? I mean, you have easy kind of turnkey development, right? Tapping >>It is right, because there's a robust, uh, economy that's surrounding the APIs that are now available for cloud services. So it's not even just at the starting point of infrastructure, but there's definite higher level services where all the way to software as industry, >>How much growth. And you'll see in those, in that, as that, that valley of wealth and opportunity that will be created from your costs, not only for the companies involved, but the company's customers, they have top line focus. And then the goal of the movement we've seen with analytics is you seeing the CIO kind of with less of a role, more of the CEO wants to the chief data officer wants most of the top line drivers to be app focused. So you seeing a big shift there. >>Yeah. I mean, one of the, one of the real proponents of the cloud is now the fact that there is an ability for a business analyst business users and the business line to make impacts on how decisions are done faster without the infrastructure underpinnings that were needed inside the four walls in our organization. So the decision maker and the buyer effectively has become to your point, the chief analytics officer, the chief marketing officer, right. Less so that the chief information officer of an organization. And so I think that that is accelerating in a tremendous, uh, pace, right? Because even if you look at the statistics that are out there today, the buying power of the CMO is now outstrip the buying power of the CIO, probably by 1.2 to 1.3 X. Right. And that used to be a whole different calculus that was in front of us before. So I would see that, uh, >>The faster, so yeah, so Natalie just kind of picked this out here real time. So you got it, which we all know, right. I went to the it world for a long time service, little catalog. Self-service, you know, Sarah's already architectures whatever you want to call it, evolve in modern era. That's good. But on the business side, there's still a need for this same kind of cataloguing of tooling platform analytics. So do you agree with that? I mean, do you see that kind of happening that way, where there's still some connection, but it's not a complete dependency. That's kind of what we're kind of rethinking real time you see that happen. >>Yeah. I think it's pretty spot on because when you look at what businesses are doing today, they're selecting software that enables them to be more self-reliant the reason why we have been growing as much among business analysts as we have is we deliver self-reliance software and in some way, uh, that's what tablet does. And so the, the winners in this space are going to be the ones that will really help users get to results faster for self-reliance. And that's, that's really what companies like Altrix Stanford today. >>So I want to ask you a follow up on that CMOs CIO discussion. Um, so given that, that, that CMOs are spending a lot more where's the, who owns the data, is that, is we, we talk, well, I don't know if I asked you this before, but do you see the role of a chief data officer emerging? And is that individual, is that individual part of the marketing organization? Is it part of it? Is it a separate parallel role? What are you, >>One of the things I will tell you is that as I've seen chief analytics and chief data officers emerge, and that is a real category entitled real deal of folks that have real responsibilities in the organization, the one place that's not is in it, which is interesting to see, right? Because oftentimes those individuals are reporting straight to the CEO, uh, or they have very close access to line of business owners, general managers, or the heads of marketing, the heads of sales. So I seeing that shift where wherever that chief data officer is, whether that's reporting to CEOs or line of business managers or general managers of, of, you know, large strategic business units, it's not in the information office, it's not in the CEO's, uh, purview anymore. And that, uh, is kind of telling for how people are thinking about their data, right? Data is becoming much more of an asset and a weapon for how companies grow and build their scale less. So about something that we just have to deal with. >>Yeah. And it's clearly emerging that role in certain industry sectors, you know, clearly financial services, government and healthcare, but slowly, but we have been saying that, >>Yeah, it's going to cross the board. Right. And one of the reasons why I wrote the article at the end of last year, I literally titled it. Uh, analytics is eating the world, is this exact idea, right? Because, uh, you have this, this notion that you no longer are locked down with data and infrastructure kind of holding you back, right? This is now much more in the hands of people who are responsible for making better decisions inside their organizations, using data to drive those decisions. And it doesn't matter the size and shape of the data that it's coming in. >>Yeah. Data is like the F the food that just spilled all over it spilled out from the truck and analytics is on the Pac-Man eating out. Sorry. >>Okay. Final question in this segment is, um, summarize big data SV for us this year, from your perspective, knowing what's going on now, what's the big game changer. What should the folks know who are watching and should take note of which they pay attention to? What's the big story here at this moment. >>There's definite swim lanes that are being created as you can see. I mean, and, and now that the bigger distribution providers, particularly on the Hadoop side of the world have started to call out what they all stand for. Right. You can tell that map are, is definitely about creating a fast, slightly proprietary Hadoop distro for enterprise. You can tell that the folks at cloud era are focusing themselves on enterprise scale and really building out that hub for enterprise scale. And you can tell Horton works is basically embedding, enabling an open source for anyone to be able to take advantage of. And certainly, you know, the previous announcements and some of the recent ones give you an indicator of that. So I see the sense swimlanes forming in that layer. And now what is going to happen is that focus and attention is going to move away from how that layer has evolved into what I would think of as advanced analytics, being able to do the visual analysis and blending of information. That's where the next, uh, you know, battle war turf is going to be in particularly, uh, the strata space. So we're, we're really looking forward to that because it basically puts us in a great position as a company and a market leader in particularly advanced analytics to really serve customers in how this new battleground is emerging. >>Well, we really appreciate you taking the time. You're an awesome guest on the queue biopsy. You know, you have a company that you're running and a great team, and you come and share your great knowledge with our fans and an audience. Appreciate it. Uh, what's next for you this year in the company with some of your goals, let's just share that. >>Yeah. We have a few things that are, we mentioned a person inspired coming up in June. There's a big product release. Most of our product team is actually here and we have a release coming up at the beginning of Q2, which is Altryx nine oh. So that has quite a bit involved in it, including expansion of connectivity, uh, being able to go and introduce a fair degree of modeling capability so that the AR based modeling that we do scales out very well with revolution and Cloudera in mind, as well as being able to package into play analytic apps very quickly from those data analysts in mind. So it's, uh, it's a release. That's been almost a year in the works, and we're very much looking forward to a big launch at the beginning of Q2. >>George, thanks so much. You got inspire coming out. A lot of great success as a growing market, valuations are high, and the good news is this is just the beginning, call it mid innings in the industry, but in the customers, I call the top of the first lot of build-out real deployment, real budgets, real deal, big data. It's going to collide with cloud again, and I'm going to start a load, get a lot of innovation all happening right here. Big data SV all the big data Silicon valley coverage here at the cube. I'm Jennifer with Dave Alonzo. We'll be right back with our next guest. After the short break.

>> Live, from Toronto, Canada, it's theCUBE! Covering Global Cloud and Blockchain Summit 2018, brought to you by theCUBE. >> So, welcome to the Global Cloud and Blockchain Summit. I'm about to hand you over to John Furrier, who is the Co-Founder and Co-CEO of SiliconANGLE Media and Executive Editor at theCUBE, he's about to do a Fireside Chat with Al and Mathew, I'll let him introduce you to them as well. He's also involved in a major blockchain project himself, so he's going to get into that with those guys as well. So, and tomorrow we start at nine, in the meantime, enjoy the evening, enjoy the food, enjoy the chat, and I'll let you go. >> Okay. Hello? Thank you Ruth, appreciate it, thanks everyone for being part of this panel, Fireside Chat, want to make it loose, but high impact for you guys, I know, having some cocktails, having a good time. If there's any questions during, then at the end we'll pass the mic around, but. We want to have a conversation, kind of like we always do down in the lobby bar, just talking about crypto and cloud, and we ended up talking about cloud computing and crypto a lot because those are two areas that are kind of converging, and the purpose of this event. So we really wanted to share some thoughts around those two massively growing markets, one is already growing, it's continuing to be great: the cloud, and blockchain certainly is changing everything. These two important topics, we want to flesh them out, Al Burgio is the Serial Entrepreneur/Founder of DigitalBits, he's founded companies both in cloud and blockchain, so he brings a great perspective. And Matt Roszak, leading crypto investor, entrepreneur and advocate, well known in the crypto space for goin' way back, I think you gave a couple bitcoins to some very famous people early on, we'll get into that a little bit later. So guys, thanks for being part of the panel and Fireside. First question is: we know how big the money is, I mean the money is crypto is is flowin' around the world, and cloud computing we've seen specifically, and certainly in coverage now with Amazon's success, Amazon Web Services, and Microsoft and others. Trillions of dollars being disrupted in the traditional kind of the enterprise, data center area, and blockchain is doing that too, so we want to get into that. But first, before we get into it, I want you guys to take a minute to explain for the folks, just to set the context, the kinds of projects you're working on. Now Al, you have DigitalBits, Matt you're investing and you're finding a lot of interesting token dynamics. So just take a minute. Al, start. >> (mic off) So-- Everybody hear me okay? Alright, perfect. Well thanks for that lovely intro. Yes, my name is Al Burgio, I'm, I've founded a few companies, as John mentioned. Before the cloud there was internet, (light laugh) and so it started for me in the late '90s in the e-commerce era. But more recently I pioneered what's known as Interconnection 2.0, and I did that with the company called Console, for those that may know PCCW, recently it was acquired by PCCW. And with that we disrupted the way networks at the core of the internet were connected together More recently I've founded the DigitalBits project, and now DigitalBits blockchain network, and with that, you can kind of think of that as the trading and transaction layer for the points economy and other digital assets, and you can do a lot of really interesting thing with that, it's really about bringing blockchain to the masses. >> Matt, what're you workin' on? >> So, Matthew Roszak, Co-Founder and Chairman of Bloq. Bloq is a enterprise software company, we do two things, the premise is the tokenization of things, so we think the money identity, new layers of the internet are going to be tokenized. And so, we go to market in two ways, one is through Bloq Enterprise, and these are all the software layers you need to to connect to tokenized networks, so think a wallet, a node, a router, etc. And then Bloq Labs we build, and partner with, some of the leading tokenize networks and applications, so we build a connective tissue and then we actually build these new networks. I started this space as an investor over five/six years ago, investing in some of the best entrepreneurs and technologists in the space build a great network. But I love building companies, and so my Co-Founder and I, Jeff Garzik, built Bloq two and a half years ago. And then lastly, also serve of Chairman of the Chamber of Digital Commerce, so, so if you believe in these new tokenized money layers, identity layers, etc, regulation comes into play. Certainly today from an institutional adoption level, and so if you care about this space, you need to spend time to kind of help that dialogue improve; this technology moves way faster than folks in DC and elsewhere, so. >> And the project that we're workin' on at SiliconANGLE, is we've tokenized our media platform, and we're opening it up to a token model, and have kind of changed the game. So all three of us have projects, want to put those in context, we build everything on Amazon Web Services, so, the view of the cloud, we also cover it. The cloud computing market is booming, we see that Amazon Web Services numbers empower the earnings for Amazon's company, obviously Apple's trillion dollar evaluation those are clear case studies; but blockchain could potentially disrupt it all, and Al, I want to get your thoughts, because even today in the news at Microsoft Azure, which is their big cloud provider, announced blockchain as a service. And folks that are in either the data center business or in cloud know the shift that's happening in the IT world, but no ones really connected the dots on where blockchain intersects, and also, is it an opportunity for the cloud guys, what's the landscape look like, so. What's your thoughts on that, how are they connected, what does it mean, how does a cloud company maintain their relevance and competitiveness with blockchain? >> Well, just pointing on the fact that, you know, today we had that new Microsoft, the Azure cloud, their support and evangelism for blockchain. You know, a company, I think it's very important that this isn't an ICO, two kids in a garage saying their doing something blockchain this is a massive, multi-billion dollar company; and making a decision like that is not trivial, it's many, many departments, a lot of resources, before such a thing's announced. So, that's, not only is it validation, but it's a leading indicator as to this trend, that this is clearly something that's important. And a lot of people, if you're not paying attention, you need to be paying attention, including if you're in the cloud industry, 'cause many companies obviously do compete with, with Microsoft and AWS, so. It may be still early, but it's not that early, in light of the news that we saw today. With that, I would say that, a lot of the parallels I like to kind of, if I was an infrastructure provider I'd look at this from the standpoint of the emergence of Linux when it first came on the scene. What was important for companies like Red Hat to be successful, they had competition at the time, and you had shortages of Linux, let's say engineers, and what have you. And so, a company like Red Hat built a business around that, and they did that by how they kind of surfaced and validated themselves to the enterprise of that era, was partnering with hardware companies, so, it was Intel, IBM, and then Dell, HP, and they all followed, and then all of a sudden, which version of Linux do you want to use? It's Red Hat, you're paying for that support, you're paying Red Hat. And, you know, then they had their hockey stick moment. Today, you know, it's not about hardware companies per se, it's about the cloud, right? So cloud is the new hardware per se, and many enterprises obviously are looking at cloud computing companies and cloud computing providers, infrastructure providers, as the company that they need to support them with the infrastructure that they use, or sorry the technologies that they use, right? Because they're not necessarily supporting these things and making sure that they're always on within the basement of that enterprise, they're depending, or outsourcing, to depending on these managed IT providers. This was very important that whatever technologies they're using in the lab, that ultimately their infrastructure partners are able to support the implementation, the integration, the ongoing support of these technologies. So if you think of blockchain like an operating system or a database technology, or whatever you want to call it, it's important that you're able to really identify these key trends, and be able to support your customer and what they're going to need, and ultimately for them, they can't have a clog in their digital supply chain, right? So, it's clearly emerging. Microsoft is validating that today, you know, clearly they have the data, that they're seeing for their existing enterprise customers, and they don't want to lose them. >> Yeah, but remember when cloud came out; you and I have talked about this many times Al that it wasn't easy to use, I remember when Amazon Web Services came out, it was just basically, it was hard to command line, basically you had to use it, so, it became easier now, it's so easy and consumable. Blockchain, similar growing pains, but, we don't want to judge it too early with the opportunity that it has, it's going to get easier, what're your thoughts? And it has to scale by the way, Amazon, at a large scale. >> Yeah, I mean-- >> So blockchain has to scale and be easier, your thoughts? >> Another kind of way to think of it is, to not necessarily think of cloud computing, but the evolution the internet went, you know, in Internet 1.0, you know, we went through this dial-up modem era, things were very raw back then; great visions we had of the future, like, it's going to be amazing for video one day! But, not during dial-up modem era, and eventually, you know, it eventually happened. And user interfaces improved, and tool sets improved and so forth. You know, fast forward to today, we have all of that innovation to leverage, so things will move a lot faster with blockchain, it did start very raw, but it's, it's moving much faster than anything we've seen definitely in the '90s and in the last decade, so. It's just, you know, it's a matter of moments, not years. >> And I think Al brings up a great point on leverage, because Amazon leverages infrastructure to a point where it's larger than Google, Azure, and IBM's public cloud combined, and so yeah, massive leverage there. And so, when these big cloud providers provide this blockchain as a service, it is instrumented and built on top of their existing infrastructure, not necessarily on blockchain infrastructure. So, it's an interesting dynamic where they're putting it on top of existing infrastructure that's there, but what's being build right now is the decentralized Amazon Web Services. So you have every layer of Amazon being re-imagined, like, and incentivized so you have distributed compute and access and storage and database. And so, what will be interesting to see is that, given this massive opportunity, will Amazon and some of these other incumbent cloud providers become the provisioning networks of the future? Of all this new decentralized resources that get, again, if you want storage, you have to start having smarts to say: if I'm going to go to Sia or Filecoin or Genaro or Storj, compute, etc; you have to start being a provisioning layer on top of that to kind of, you know, make that blockchain essentially work. So, it'll be interesting to see the transition 'cause today the lightweight versions to say yeah, I have a blockchain as a service strategy, and that's like, well done, and check the box. Now, the question is how far in this new world will they go down? And, as it gets more decentralized, as universities and governments, corporations, plug their access utility into these networks, and to see how that changes. That is much bigger than the Amazon of today. >> I think that's an interesting point, I want to just drill down on that if you don't mind, 'cause I think that's a fundamental observation that every layer's going to be decentralized. The questions I think I'm asking and I'm seeing is: How does it all work together? And then what's the priorities? And the old model was easy; got to get the infrastructure, got to get servers, (laughs lightly) and you know, work your way up to the top of the stack. What cloud brings also is that: a software developer can whip up an application, maybe a dApp on a test network and go viral, and the next thing you know they have a great opportunity, and then they got to build down. So the question is: What are you seeing in terms of priorities on stacks, portions of the stack that are being decentralized and tokenized, do you see patterns, trends, as an investor, is there a hotter (laughs) area than others, how do you look at that? >> Well, I think it's, it's in motion right now it's, like I said, every layer of AWS is getting thought through in how to create these digital cooperatives, I have excess storage, I'm going to contribute it to this network, and I'm going to get paid in tokens when a user uses that storage network, and pays for it in those native tokens and so that, coupled with all the other layers, is happening. From a user perspective, we may not want to be going to pick a database provider, a storage, a compute, etc, we're likely going to say: I want a provisioning layer, and provision this and execute this, much like if we, you know, there'll be new provisioning layers for moving money, I don't care if routes through Lightning or Litecoin or Doge or whatever, as long as the value gets across the pond or the app gets provisioned appropriately based on you know, time, security, and cost, and whatever other tendance are important, that's all I care about, but; given the depth and the market for all that, I think it'll be interesting to see how these are developed with the provisioning layers, and I would think Amazon or Azure, the future of that is, is more provisioning than actually going and doing all that at the end of the day. >> That's great. I want to get your thoughts guys on innovation. My good friend Andy Kessler wrote an op-ed in today's Wall Street Journal around, an article around the government, the US government getting involved. You know, there's Twitter, Facebook, the big platforms, in terms of how they're handling their media, but it brings up a good point that with more regulation, there's less innovation. You mentioned some things outside the United States, it's a global cloud, cloud's operating globally with regions, it's a global fabric. Startups are really hot in this area so; how do you view the ecosystems of startups, in terms of being innovative, things happening that you think that're good, and things that aren't good, obviously I'm not a big of the government getting involved, and managing startups, the ecosystems but, blockchain has a lot of alpha entrepreneurs jumping in, you've looked at all the top ventures, the legit ventures, they're all alpha entrepreneurs, multi-time serial entrepreneurs, they see the opportunity and they go for it. Is the startup environment good, is there enough innovation opportunities, what're you thoughts on the opportunity to be innovative? >> Yeah, Al and I were just talking about this before the panel here, and were talking about our travels in Asia, and when we go there it is 10, 100 X of energy and get-it factor, and capital, and the markets are just wildly more vibrant than you know, going to some typical markets here in San Fran and New York in North America, and, so it's interesting to see that when you heat map the world, what's really happening. And you know, people are always saying: oh well this, this FinTech, or InsurTech, or whatever tech, is going to make a dent in Silicon Valley or Wall Street. This technology, this new frontier, is definitely going to do that. I think some of that will get put into more focus based on regulation, and there's two things that will happen; there's obviously a lot of whippersnapper countries that are promoting a safe place to innovate with crypto, I think Malta, Gibraltar, Barbados, etc, and there were-- >> Even Bermuda's getting in on the mix now. >> Yeah! I mean so there's no shortage of that, and so, and obviously this ecosystem outpaces the pace of regulation and then we'll see like the US doing something, or you know, other fast followers to try and catch up, and say hey, we're going to do the cryptocurrency act of 2022, miners get free power, tax-free, you know crypto trading, you know just try and play catch up. 'Cause it's kind of hard in the last year or 18 months we've seen this ecosystem go from this groundswell to this now institutional discussion; and how do you back end the the banking, the custody, all these form factors that are still relatively absent. And so, you know, we're right in the middle of it. >> It's a whole new way, you got to follow the money, right? Al, you and I talked about this; capital markets, you know entrepreneurs need to raise money and that's a good thing, you need to get capital to do stuff. >> Yeah, this is a new phenomenon that the world has never experienced before, it's awesomeness when it comes to capital formation; you know, without capital formation there is no innovation. And so the fact that more capital can be raised, it's the ultimate crowd sourcing in such an efficient period of time, capital being able, the ability to track capital from various different corners of the world, and deploy that capital to try to fuel innovation. Of course, you know, not all startups or what have you succeed, but that was true yesterday, right? You know, 90% of startups fail, but they all will give it some meaningful amounts of checks, people were employed and innovation was tried; and every once in a while something emerges that's amazing. If you can do that faster, right, when you have the opportunity to produce more and more innovation. And, of course with something so new as cryptocurrency, things like ICOs and what have you, people may kind of refer to it as the wild wild West, it's not, it's an evolution. And you have-- >> It's still the wild west though, you got to admit. (laughs) >> Well, it is but, we're getting better at it, right? As a world, this isn't the Silicon Valley community getting better at venture capital or some other part of the United States or Canada getting better at venture capital; this is the world as a whole getting better at capital formation. >> Yeah, that's a great point. >> In the new way of capital formation. >> And I wanted to just get an observation on that. I moved to Silicon Valley 20 years ago, and I love it there, for venture capital and new startups, it's the best place in the world. And I've seen people try to replicate Silicon Valley, we're the Silicon Valley of Canada, we're the Silicon Valley of the East or Europe, and it's always been hard to replicate, because it was a venture model, and you needed venture capitalists and you need money, you need a community, the culture, the failure, the starting over, and just, you know, gettin' back on the horse kind of thing. Crypto is the first time that I've seen the replica of that Silicon Valley dynamic, in a new way, because the money's flowing, (laughs) and there's community involved in crypto, crypto has a big community aspect to it. Do you guys see that as well? I mean I'm seeing, outside the United States, a lot of activity. Is that something that you're seeing? >> So, the first time we saw, well, last time we saw everybody trying to replicate Silicon Valley was first internet, you know, there was Silicon Swamp, there was Silicon Alley, there was silicon this-- >> Prairie. >> Every city was >> Silicon Beach. >> A silicon version of something, and then the capital evaporated, right? We had a mass correction happen. What wasn't being disrupted was value exchange, right, and so this is being created now, it is now possible for this to happen, and it's happening, we're seeing amazing things, Matt said, you know, in Asia. It's a truly awesome force, if anybody has an opportunity to go, they should go, it's unbelievable to experience it, and it really opens your eyes. >> And you've lived through a lot of investments during those .com days and through history now, you've seen a lot of different things. Your observations with the current state of the capital formation, startup landscapes, the global ecosystem around crypto and how it's different from say venture or classic rolling up companies and those kinds of things? >> Yeah, you hear a lot of this, you know, we're in a bubble, it's speculative, etc. And I think that when you look back at history of infrastructure, whether it's railroads, telephony, internet, and now crypto and blockchain, it's interesting, like, if you said: it would take this amount of money to innovate and come out the other end of internet with this kind of infrastructure, these kinds of applications, with these kinds of lessons learned, nobody would sign up for that number, right? It needs this fear, and greed, and all the other effervescence of markets to kind of come out the other end and have innovation. I think we're going through a very similar dynamic here with crypto and blockchain where you know, everything's getting tokenized, everything's getting decentralized. We're talking about fundamental things like money, you know, it's not like we're talking about pet food and women's shoes and airline tickets, we are talking about money, identity, things that will enable like other curves to really come into focus like in and out of things and the kind of compounding of intersections when some of these things get right is pretty extraordinary. And so, but I like what Al said in terms of capital formation and that friction to get from, you know, idea to capital to building, is getting compressed Yes, there will be edge cases of people taking advantage of that, but at the other end of this flow will be some amazing innovation. >> What do you guys think about the, if you had to answer the question with one answer, of what is the high order bit of why blockchain's so important? For me, I see it, from my standpoint, I'll just start, I see it making inefficient things more efficient for any use case, and that's being re-imagined, which is everything from IOT or whatever. Efficiency is a big thing, at least I see that. What do you guys see as a high order bit in terms of you know, the one thing that you'd say blockchain really impacts the world in terms of you know, impact, financial, etc? >> Well, I think with decentralization and all these things that we're seeing it's kind of evened the playing field. It's allowing for participation where parts of the world were unable to participate. And it's doing a whole lot of things in that area. And that's truly awesome, to really grow the economy, grow the global market, and the number of participants in that market in all areas. That's the ultimate trend at what's happening here. >> And your information? >> Absolutely, and I think there's two things, there's this blockchain dialogue, and then there's this crypto decentralization, tokenization dialogue, and on the blockchain side you have lots of companies engaging in blockchain and trying to figure out how it applies to their business, and you hear everything from McKinsey and Goldman saying financial services will save 100 billion dollars in operating expenses by applying blockchain technology, and that's great. That is probably low in terms of what they'll save, it's, to me, is just not the point of the technology, I think that when you kind of distill that down to say hey, for a group of folks to use this technology as a shared services thing to lower opex a trading settlement and decrease that, that's great, that is a step stone to creating these tokenized economies, these digital cooperatives. Meaning you contribute something and then you get something back, and it's measured in the value that this token is, like a barometric kind of value of how healthy that ecosystem is. And so, regulated public enterprises, and EC consortiums around insurance and financial services and banking, that is all fantastic, and that gets them in the pool, gets them exercising on what blockchain is, what it isn't, how they apply it, but it's, at the end of the day for them it's cost reduction The minute there's growth or IP, or disruption on the table, they're all going back to their boardrooms to say: hey let's do this, this, or that, but, if there's a way, my favorite class in college was industrial organization, and it sounds weird but, it was, it kind of told ya like how to dissect an industry, you know, what makes them competitive, who the market leaders are, and then, if you overlay like blockchain networks with tokens, with incentives, interesting things could happen, right? And so that future is going to be real interesting to see how market leaders think about how to tokenize their network, how to be, how to say: no I don't want to own this whole industrial network, I have to engage with some other participants and make sure everybody is incentivized to climb on board. So that I think is going to be more of the interesting part than just blockchain-ifying a workflow. >> Well let's just quickly drill down on that, token economics, what you're getting to. So let's assume blockchain just happens, as evolution of technology, let's just assume for a second that it's going to happen in a big way, it's private, public, hybrid chains, with all that good stuff happening, but the token economics is where the business value starts to be extracted, so the question for you is: How do you describe that to someone to look for, what are the key elements of token economics? When does it matter, when is it in play, and how should they be thinking about it? >> Yeah, I mean token economic design and getting a flywheel going to create a network and network effects is really important. You could have great technology, but Al could be a better marketer, and he gets tokens adopted better, and his network will do better because, you know, he was better able to get people to adopt and market a particular, you know, layer application. And so, it's really important to think about how you get that flywheel going, and how you get that kindling going on a particularly new ecosystem, and get users adoption and growth. That is really hard to do these days because some people don't even know what Bitcoin is, let alone to say I'm going to tokenize this layer, and every time you contribute, every time you take an action, you're going to get rewarded for it, and you're share the value of this network. >> Can you give me a good example of what's happening today that you can point to and say: that's a great example of token economics? >> Well, you see, I mean the most basic one is shared file storage, right? You know, it's like the Filecoin, Sia, Genaro model where, you know, you contribute you know, the unused storage in your laptop or your university data center or a corporate data center, and you say I'm going to contribute this, and when it's used I get these tokens and, you know at the end of the day or week or year you see what these tokens are worth, and was that worth your contribution? And so as these markets develop, and as utility develops, we'll see what that holds. >> Al, you got an example you could share? DigitalBits is a good use case obviously. >> Actually, I'm not going to use DigitalBits (John laughs) just to be neutral. This is one that Matt will know very well, definitely better than I, but one that I've-- the simpler something is, the easier it is for people to understand, and its like oh that makes sense, you know. You know, Binance is one that's very simple, you know it's a payment token, if you pay with some other currency, you pay, you know, Pricex, if you pay in the next few years with their token, you'll get the service at a discount. And in addition to that, they're using a percentage of profits, I think it's every quarter, to buy back up to, ultimately up to, 50% of tokens that are in circulation. So, you know, it's driving value, and driving return, in essence, if I can use that word. So for a user it's simple to understand, for someone that likes to speculate it's easy for someone to understand in terms of how the whole model works, so it's not some insanely complicated mathematical equation, that we can yes we can trust the math. And so in some cases, some adoption is going to just be, you know, attract participants based on simplicity. In other cases the math is important, and people will care about that, so, you know not all things are necessarily equal, and not necessarily one method is right, but there are some simple examples out there that that have proven to be successful. >> That's awesome, one last question, before we open it up if anyone has any questions. If anyone has any questions, if they want to come up, grab the microphone, and ask the three of us if you've got anything on your mind. And while you're thinking about that I'll get the final question for these guys is: A lot of people ask me hey, I want to be on the right side of history, what side of the street should I be on when the reality comes down that decentralization, blockchain, token economics, decentralized applications, becomes the norm, and that re-imagining actually happens? I don't want to be on the wrong side of history. What should I be doing, how should I be thinking differently, who should I be following, what should I be paying attention to? How do you answer that question? >> I think, at the basic level, you know, turn off your phone, lock your door, and study this technology for a day, it's the best advice I could give. Two: buy some crypto. Once you kind of have crypto on your phone, in your wallet, something changes in your brain, I think you just feel like you-- >> You check the prices every day. (all laugh) >> You lose a lot of sleep. And then after that, you know, I think you start engaging in this space in a very different way. So I think starting small, starting basic, is an important tenet. And then, what's amazing about this space is that it attracts the best and brightest out of industry, and law, and government, and technology, and you name it, and I'm always fascinated the people that show up and they're like yeah, I'm in a 20 year, you know, veteran in this space and I want to get into blockchain, it just attracts some of the best and brightest. And, I think we're going to see a lot of experience coming into the space, you know, this has been a, what I'd say a bottoms up groundswell of crypto and blockchain and the evolution of the space. And I think we're starting to see more some more mature folks come in the space to to add some history and perspective and helpin' the build out of this, and to build a lot of these networks. I think that the kind of intersection of both is going to be very healthy for the space. >> Al, your thoughts? >> Definitely agree with Matt. Definitely to lock yourself up and just try to absorb information, everyone has access to the internet, there's plenty of information. If you don't like to read go watch a few YouTube videos, just people explaining the stuff, it's really fascinating, the various different use cases and so forth. You definitely have to buy some, and, you know, whether it's five dollars worth, just go through the whole experience of being able to trade something of value that a few years ago didn't exist, and be able to trade it for something else of value is a pretty phenomenal experience. Then trying to go buy something with it, it's even more of a fascinating experience, I just bought something that used, again, something that didn't exist a few years ago. But, what I would add to that as well, you really have to get out there; if you keep surrounding yourself with people saying aw, this is, eh, whatever, >> It's never going to work. >> It's crazy, it's for criminals, and all that fun stuff. You're going to be last place. So coming to conferences, obviously future's conference you're going to meet a lot of interesting, great people, and that consistent experience, you'll learn something every time. You know, at the end of the day, I remember, I'm sure all three of us remember, with the birth of the internet there was many people that said you know the internet thing, it's crap, it's for kids, you know. And we had first movers, we had willing followers, and then the unwilling followed, you don't want to end up being-- >> The unwilling followers. >> Yeah, the unwilling. >> Alright. Does anyone have any questions they'd like to ask? Come on up. Yeah. We're recording, so we want to get it on film. >> So I have two questions. The first one is for you, Al: Two years ago I interviewed with IIX before it was Console, and I want to know why you didn't hire me? (Sparse laughs) No I'm kidding! That was a joke. Actually, I thought each of you brought up some good points, minus you Al. (chuckles) I'm just kidding. But what I really wanted to ask you guys is: so you talk a lot about this, the tokenized economy and kind of the roadmap and the things to get there, you talk about sediment layer, right, Fiat to crypto, sediment layer, your identity protocols, your dApps, X, Y, Z, right? The whole web 3.0 stack, I want each of you, or I want at least input from both of you or all of you, what are the hurdles to getting to a full adoption of web 3.0 stack, and make a bold prediction on the timing before we have a full web 3.0 stack that we use every day. >> That is a awesome question actually, timelines. You could be, being in technology, being in venture, you could be right, and you could be off by three, five, seven, 10 years, and be so wrong, right? And then at your retirement dinner you could say: I was right, but Tommy wasn't right. So, this is really hard technology, in terms of building systems that are distributed, creating the economic models, the incentive models, it takes a lot to go right in the intersection of all this. But it's not a question like is this happening? No, this is happening, this is like, it's in motion. The timelines are going to be a little elusive, I'm way more pragmatic, I was one of the early guys in the early internet, and you know everything was going to be .com and awesome and fantastic. But the timelines were a little elusive then, right? You know, it's like when was, people are thinking of today's Amazon was going to be the 2005 Amazon, you know, it's like, that took about another decade to get there, right? And people could easily just buy stuff and a drone or a UPS guy would just deliver it, and so, similar things apply today. And you know at the same time we all have a super computer in our pocket, and so it's a lot different. At the same time we're dealing with trusted mediums right? The medium of money, the medium of identity, all these different things they're, they're things that you know if I say download Instagram, and let's share cat pictures or whatever, it's not a big deal, our trust is really low for that, let's do it. For money, it's a different mental state, it's a different dynamic, especially if you're an individual, a government, or an enterprise, you go through a whole different adoption curve on that, so, you know, it is at grand scale five to 10 years, right? In any meaningful way. And so we still have a lot of work to do. >> My answer to that question, it's a good one, your question was a good one, my answer's a little bit weird because it's multi-generational. The first generation pivot was when the internet was born was because of standards, right? The government had investment. The OSI model, open system interconnect, actually never happened, the seven layers didn't get standardized, only a few key ones did; that created a lot of great things. And then when the we came out, that was very interesting protocol development there, the TCP/IP stuff, I mean HTP stuff. I don't see the standardization happening, because cloud flipped the stack model upside down because Amazon and these guys let the software developers drive the value. It used to be infrastructure drove the value of what software could do, then software became so proliferated that that drove the value of the infrastructure, so the whole cloud computing equation is making the infrastructure programmable for the first time, not the other way around, so. The cloud phenomenon's all about software driving the value, and that's happening, so. It's interesting because with blockchain you can almost do levels of services in a cloud-like way with crypto, I mean with blockchain and token economics, and have a partial stack. So think that this whole web 3.0 might be something that no one's every seen before. So, that's kind of my answer, I don't really know if that's going to be right or not, but just looking at the future, connecting the dots, it's probably not going to look like what we've seen before, and if the cloud's an indicator it's probably going to be some weird looking stack where certain sections are working, and then evolution might fill in the other ones, so. I mean, that's my take, I mean, but standards will play a role, the communities will have to get involved around certain things, and I think that's a timeless concept. >> Timing. >> Oh, timing. I think it's going to be pretty quick, I think if you look at the years it took for internet, and then the web, everything's being compressed down, but I think it's going to be much shorter. If it was a 20 year cycle in the past, that gets shortened down to 15 with the internet, and this could be five years. So five to 10 years, that could be the impact in my mind. The question I always ask is: what year will banks no longer be involved in anything? Is that 20 years or 10 years? (laughs) Exactly, so, yeah, follow the money. >> So I would say that in terms of trying to keep your finger on the pulse with things and how you kind of things, see things evolve; things are definitely moving a lot faster, you know in the past you would probably say seven to 10, I'm not sure if I would say five, sorry five to 10, it definitely feels to me that it's five max til we could start to see some of these key things fall into place, so. >> So could you answer the first question? >> What was the first question? >> Why didn't you hire me? (audience cringes) >> We've met before? Sorry. (all laugh) >> I have a question, this is Dave Vellante, Co-Host of theCUBE. And I want to pick up on something John you just said, and Matt you were talking about Goldman Sachs and Morgan Stanley, it's not about them saving hundreds of millions of dollars, it's really about them transforming business, so. And John, you just asked the question about banks, I want to actually get your answer to this: Will traditional banks, in your opinion, lose control of payment systems? Not withstanding your bias. (laughter) >> Yeah, I am definitely biased on this. But, I mean, I've been in front of the C-suite of banks, credit card companies, etc, and I said, you know, in about a decade, the center of what you do and how you make money is going to be zero. And, 'cause there'll be networks, and ways to transmit money that'll be by far cheaper, or will be subsidized by other networks, meaning, and those networks are Apple, Amazon, Alibaba, you know, Tencent, whatever networks that're out there, that're engaging in collaboration and commerce and everything else, they will give away payments as just a courtesy, like people give away messaging or email or something, as a courtesy to that network, and will harden that network, and it'll be built and based on blockchain technology and cryptocurrencies, so they don't necessarily have to worry about, you know, kind of subtle payments. But these new networks will start to encroach on banks, the banks are not worried about other banks today, the banks should be worried about these new networks that're being developed. >> How many people still have a home phone line? >> That was elegant, I like that. >> You know, I mean there's a generation of people that still like going to banks, they'll keep them in business for a while. But I think that comes to an end. >> I mean, when we covered a lot of the big data market when it started, the argument was mobile will kill the banks outlets, and now with ATMs there's more bank, more baking branches than ever before, so I think the services piece is interesting. >> And also, if you look at even the cloud basis, the software as a service, SaaS space, a decade, decade and a half ago, you would ask SAP, Oracle, what have you, what's your cloud strategy? And they'd be like cloud? That's just more efficient delivery model, not interested. 90 some billion dollars of M and A later, SAP, Oracle, etc, are cloud companies, right? And so, if banks kind of get into that same mode to say well, yeah, we need to play catch up and buy digital currency exchanges and multi-currency wallets, and this infrastructure and plumbing to be relevant in the next world, that would be interesting. But I think technology companies have as much an advantage to do that as as financial services companies, so it'll be interesting to see who kind of goes into that, goes into the crypto ecosystem to make that their own. >> It's interesting. We were talking before we came on and the OSS market, operational support systems is booming, and that's traditionally been these big operational outsource companies would manage big projects, but, if you look at in the first half of 2018, there's been a greater than 20 billion dollar commercial exits of companies through private equity merchants, IPOs, around OSS, and that's where we see operational things happening, CoreOS, Alfresco, MuleSoft, Pivotal went public, Magneto, GitHub, Treasure Data, Fastly, Elastic, DataStax, they're all in the pipeline. These are all companies that aren't cloud, they're like running stuff in cloud, so, this could be a tell sign that potentially the the blockchain operating market is going to be potentially a big one. >> Yeah, and then even look at BitMate, the world's largest miner in crypto. So, they did about a billion dollars in profit last year, did about a billion dollars in profit just in the first quarter going public, just raised a billion dollars last month, at a reportedly 50 to 70 billion dollar evaluation in Hong Kong in the next month, and the amount of money they'll raise will eclipse what Facebook raised. And so I think the institutional, the hardware, the cloud computing, the whole ecosystem starts to like resonate and think about this space a lot differently, and we need these milestones, we need these, whether they're room huddles or data points to kind of like think about how this is going to affect your business and what you do tomorrow morning. >> Any more questions from the crowd? Audience? Okay, great, well thanks for attending, appreciate you guys watching and listening, and guys thanks for the conversation; cloud and blockchain convergence. Collision course, or is it going to happen nicely, Al? >> Yeah, I think it's going to be a convergence, I don't see it necessarily as a collision course. >> And a lot of money to be made on this opportunity these days, and cloud convergence with blockchain. >> I concur with Al, I think there's going to be convergence, I think us most smarter players will engage and figure out their models in this new crypto and tokenized era. >> Thanks so much guys, appreciate it, give these guys a round of applause. (audience applause) Thank you very much. (bubbly music)

>> Narrator: Live from Dublin, Ireland. It's theCUBE, covering Hadoop Summit Europe 2016. Brought to you by Hortonworks. Now your host, John Furrier and Dave Vellante. >> Okay, welcome back here, we are here live in Dublin, Ireland, it's theCUBE SiliconANGLEs flagship program where we go out to the events and extract the signal from the noise, I'm John Furrier, my cohost Dave Vellante, our next guest is Emer Coleman who's with Disruption Limited, Open Data Governance Board in Ireland and Transport API, a growing startup built self-sustainable, growing business, open data, love that keynote here at Hadoop Summit, very compelling discussion around digital goods, digital future. Emer, welcome to theCUBE. >> It's great to be here. >> So what was your keynote? Let's just quickly talk about what you talked about, and then we can get in some awesome conversation. >> Sure. So the topic yesterday was we need to talk about techno ethics. So basically, over the last couple of months, I've been doing quite a lot of research on ethics and technology, and many people have different interpretations of that, but yesterday I said it's basically about three things. It's about people, it's about privacy, and it's about profits. So it's asking questions about how do we look at holistic technology development that moves away from a pure technocratic play and looks at the deep societal impacts that technology has. >> One of the things that we're super excited about and passionate about is this new era of openness going to a whole another level. Obviously, open source tier one software development environment, cloud computing allows for instant access to resources, almost limitless at this point, as you can project it forward with Moore's Law and whatnot. But the notion that digital assets are not just content, it's data, it's people, it's the things you mentioned about, create a whole new operating environment or user experience, user expectations with mobile phones and Internet of Things and Transport API which you have, if it moves, you capture it, and you're providing value there. So a whole new economy is developing around digital capital. Share your thoughts around this, because this is an area that you're passionate about, you've just done work here, what's your thoughts on this new digital economy, digital capital, digital asset opportunity? >> I think there's huge excitement about the digital economy, isn't there? And I think one of the things I'm concerned about is that that excitement will lead us to the same place that we are now, where we're not really thinking through what are the equitable distribution in that economy, because it seems to me that the spoils are going to a very tiny elite at the tops. So if you look at Instagram, 13 employees when it was purchased by Facebook for a billion dollars, but that's all our stuff, so I'm not getting any shares in the billion, those 13 people are. That's fantastic that you can build a business, build it to that stage and sell, but you have to think about two things, really: what are we looking at in terms of sustainable businesses into the future that create ethical products, and also the demands from citizens to get some value for their data back, because we're becoming shadow employees, we're shadow employees of Google, so when we email, we're not just corresponding, we're creating value for that company. >> And Facebook is a great example. >> And Facebook, and the thing is, when we were at the beginning of that digital journey, it was quite naive. So we were very seduced by free, and we thought, "This is great," and so we're happy with the service. And then the next stage of that, we realize what if we're not paying for the service, we're the product? >> John: Yeah. >> But we were too embedded in the platform to extricate ourselves. But now, I think, when we look at the future of work and great uncertainty that people are facing, when their labor's not going to be required to the same degree, are we going to slavishly keep producing capital and value for companies like Google, and ask for nothing more than the service in return? I don't think so. >> And certainly, the future will be impacted, and one of the things we see now in our business of online media and online open data, is that the data's very valuable. We see that, I'll say data is the new capital, new oil, whatever phrases of the day is used, and the brand marketers are the first ones to react to it, 'cause they're very data driven. Who are you, how do I sell stuff to you? And so what we're seeing is, brand marketers are saying, "Hey, I'm going to money to try to reach out to people, "and I'm going to activate that base and connect with, "engage with them on Facebook or other platform. "I'm going to add value to your Facebook or Google platform, "but yet I'm parasitic to your platform for the data. "Why just don't I get it directly?" So again, you're starting to see that thinking where I don't want to be a parasite or parasitic to a network that the value's coming from. The users have not yet gotten there, and you're teasing that out. What's your thoughts there, progression, where we're at, have people realized this? Have you seen any movement in the industry around this topic? >> No, I think there's a silence around... Technology companies want to get all the data they can. They're not going to really declare as much as they should, because it bends their service model a bit. Also, the data is emergent. Zuckerberg didn't start Facebook as something that was going to be a utility for a billion people, he started it as a social network for a university. And what grew out of that, we learned as we went along. So I'm thinking, now that we have that experience, we know that happens, so let's start the thinking now. And also, this notion of just taking data because you can, almost speculatively getting data at the point of source, without even knowing what you want it for but thinking, "I'm going to monetize this in the end." Jaron Lanier in his book Who Owns The Future talks about micro licensing back content. And I think that's what we need to do. We start, at the very beginning, we need to start baking in two things: privacy by design and different business models where it's not a winner takes all. It's a dialog between the user and the service, and that's iterated together. >> This idea that it's not a zero sum game is very important, and I want to go back to your Instagram and Facebook example. At its peak, I think Eastman Kodak had hundreds of thousands of employees, maybe four or five hundred, 450,000 employees, huge. Facebook has many many more photos, but maybe a few thousand employees? Wow, so all the jobs are gone, but at the same time, we don't want to be protecting the past from the future, so how do you square that circle? >> Correct, but I think what we know is that the rise of robotics and software is going to eat jobs, and basically, there's going to be a hollowing out of the middle class. You know, for sure, whether it's medicine, journalism, retail, exactly. >> Dave: It's not future, it's now. (laughs) >> Exactly. So we maybe come into a point where large swaths of people don't have work. Now, what do you do in a world where your labor is no longer required? Think about the public policy implications of that. Do we say you either fit in this economy or you die? Are we going to look at ideas which they are looking at in Europe, which is like a universal wage? And all of these things are a challenge to government, because they're going to have a citizenry who are not included in this brave new world. So some public policy thinking has to go into what happens when our kids can't get jobs. When the jobs that used to be done by people like us are done by machines. I'm not against the movement of technology, what I'm saying is there are deep societal implications that need some thinking, because if we get to a point where we suddenly realize, if all of these people who are unemployed and can't get work, this isn't a future we envisioned where robots would take all the crap jobs and we would go off to do wonderful things, like how are we going to bring the bacon home? >> It seems like in a digital world that the gap is creativity to combine technologies and knowledge. I find that it's scary when you talk about maybe micromanaging wages and things like that, education is the answer, but that's... How do you just transfer that knowledge? That's sort of the discussion that we're having in the United States anyway. >> I think some of the issue is that the technology is so, we're kind of seduced by simplicity. So we don't see the complexity underneath, and that's the ultimate aim of a technology, is to make something so simple, that complexity is masked. That's what the iPhone did wonderfully. But that's actually how society is looking now. So we're seduced by this simplicity, we're not seeing the complexity underneath, and that complexity would be about what do we do in a world where our labor is no longer required? >> And one of the things that's interesting about the hollowing of the middle class is the assumption is there's no replacements, so one of the things that could be counter argued is that, okay, as the digital natives, my daughter, she's a freshman in high school, my youngest son's eighth grade, they're natives now, so they're going to commit. So what is the replacement capital and value for companies that can be sustained in the new economy versus the decay and the darwinism of the old? So the digital darwinism aspect's interesting, that's one dilemma. The other one is business models, and I want to get your thoughts on this 'cause this is something we were teasing out with this whole value extraction and company platform issue. A company like Twitter. Highly valuable company, it's a global network of people tweeting and sharing, but yet is under constant pressure from Wall Street and investors that they basically suck. And they don't, they're good, people love Twitter, so they're being forced to behave differently against their mission because their profit motive doesn't really match maybe something like Facebook, so therefore they're instantly devalued, yet the future of someone connecting on Twitter is significantly high. That being said, I want to get your thoughts on that and your advice to Twitter management, given the fact it is a global network. What should they do? >> It's the same old capitalism, just it's digital, it's a digital company, it's a digital asset. It's the same approach, right? Twitter has been a wonderful thing. I've been a Twitter user for years. How amazing, it's played a role in the Arab Spring, all sorts of things. So they're really good, but I think you need as a company, so for example, in our company, in Transport API, we're not really looking to build to this massive IPO, we're trying to build a sustainable company in a traditional way using digital. So I think if you let yourself be seduced by the idea of phenomenal IPO, you kind of take your eye off the ball. >> Or in case this, in case you got IPOed, now you're under pressure to produce-- >> Emer: Absolutely, yeah. >> Which changes your behavior. But in Twitter's management defense, they see the value of their product. Now, they got there by accident and everyone loves it, but now they're not taking the bait to try to craft a short term solution to essentially what is already a valuable product, but not on the books. >> Yes, and also I think where the danger is, we know that their generation shifts across channel. So teenagers probably look at Facebook, I think one of them said, like an awkward family dinner they can't quite leave. But for next gen, they're just not going to go there, 'cause that's where your grandmother is. So the same is true of Twitter and Snapchat, these platforms come and go. It's an interesting phenomenon then to see Wall Street putting that much money into something which is essentially quite ephemeral. I'm not saying that Twitter won't be around for years, it may be, but that's the thing about digital, isn't it? Something else comes in and it's well, that becomes the platform of choice. >> Well, it's interesting, right? Everybody, us included, we criticize the... Michael Dell calls it the 90 day shock clock. But it's actually worked out pretty well, I mean, economically, for the United States companies. Maybe it doesn't in the future. What are your thoughts on that, particularly from a European perspective? Where you're reporting maybe twice a year, there's not as much pressure, but yet from a technology industry standpoint, companies outside the Silicon Valley in particular seem to be less competitive, why? >> For example, in our company, in Transport API, we've got some pretty heavyweight clients, we have a wonderful angel investor who has given us two rounds of investment. And it isn't that kind of avaricious absolutely built this super price. And that's allowed us to build from starting off with 2, now to a team of 10, and we're just about coming into break even, so it's doable. But I think it's a philosophy. We didn't want necessarily to build something huge, although we want to go global, but it was let's do this in a sustainable way with reasonable wages, and we've all put our own soul and money into it, but it's a different cultural proposition, I think. >> Well, the valuations always drive the markets. It's interesting too, to your point about things come and go channels, kind of reminds me, Dave and I used to joke about social networks like nightclubs, they're hot and then it's just too crowded and nobody goes there, as Yogi Bear would say. And then they shift and they go out of business, some don't open with fanfare, no one goes 'cause it's got different context. You have a contextual challenge in the world now. Technology can change things, so I want to ask you about identity 'cause there was a great article posted by the founder of the company called Secret which is one of these anonymous apps like Yik Yak and whatnot, and he shut it down. And he wrote a post, kind of a postmortem, saying, "These things come and go, they don't work, "they're not sustainable because there's no identity." So the role of identity in a social global virtual world, virtual being not just virtual reality, is interesting. You live in a world, and your company, Transport API, provides data which enables stuff and the role of identity. So anonymous versus identity, thoughts there, and that impact to the future of work? If you know who you're dealing with, and if they're present, these are concepts that are now important, presence, identity, attention. >> And that's the interesting thing, isn't it? Who controls that identity? Mark Zuckerberg said, "You only have one identity," which is what he said when he set up Facebook. You think, really? No, that's what a young person thinks. When we're older, we know. >> He also said that young people are smarter than older people. >> Yeah, right, okay. (John laughs) He could be right there, he could be right there, but we all have different identities in different parts of our lives. Who we are here, the Hadoop summit is different from what we're at home to when we're with friends. So identity is a multifaceted thing. But also, who gets to determine your identity? So I have 16 years of my search life and Google. Now, who am I in that server, compared to who I am? I am the sum total of my searches. But I'm not just the sum total of my searches, am I? Or even that contextualized, so I'll give you an example. A number of years ago I was searching for a large, very large waterproof plastic bag. And I typed it in, and I thought, "Oh my god, that sounds like I'm going to murder my husband "and try to bury him." (John and Dave laugh) It was actually-- >> John: Into the compost. >> Right, right. And I thought, "Oh my god, what does this look like "on the other side?" Now, it was actually for my summer garden furniture. But the point is, if you looked at that in an analytic way, who would I be? And so I think identity is very, you know-- >> John: Mistaken. >> Yeah, and also this idea of what Frank Pasquale calls the black box society. These secret algorithms that are controlling flows of money and information. How do they decide what my identity is? What are the moral decisions that they make around that? What does it say if I search for one thing over another? If I search constantly for expensive shoes, does that make me shallow? What do these things say? If I search for certain things around health. >> And there's a value judgment now associated with that that you're talking about, that you do not control. >> Absolutely, and which is probably linked to other things which will determine things like whether I get credit or not, but these can almost be arbitrary decisions, 'cause I have no oversight of the logic that's creating that decision making algorithm. So I think it's not just about identity, it's about who's deciding what that identity is. >> And it's also the reality that you're in, context, situations. Dark side, bright side of technology in this future where this new digital asset economy, digital capital. There's going to be good and bad, education can be consumed non-linear, new forms of consumptions, metadata, as you're pointing out, with the algorithms. Where do you see some bright spots and where do you see the danger areas? >> I think the great thing is, when you were saying software is the future. It's our present, but it's going to be even more so in our future. Some of the brightest brains in the world are involved in the creation of new technology. I just think they need to be focusing a bit more of that intellectual rigor towards the impact they're having on society and how they could do it better. 'Cause I think it's too much of a technocratic solution. Technologists say, "We can do this." The questions is, should they? So I think what we need to do is to loop them back into the more social and philosophical side of the discussion. And of course it's a wonderful thing, hopefully technology is going to do amazing things around health. We can't even predict how amazing it's going to be. But all I'm saying is that, if we don't ask the hard questions now about the downsides, we're going to be in a difficult societal position. But I'm hoping that we will, and I'm hoping that raising issues like techno ethics will get more of that discussion going. >> Well, transparency and open data make a big difference. >> Emer: Absolutely. >> Well, and public policy, as you said earlier, can play a huge role here. I wonder if you could give us your perspective on... Public policy, we're in the US most of the time, but it's interesting when we talk to customers here. To hear about the emphasis, obviously, on privacy, data location and so forth, so in the digital world, do you see Europe's emphasis and, I think, leading on those types of topics as an advantage in a digital world, or does it create friction from an economic standpoint? >> Yeah, but it's not all about economics. Friction is a good thing. There are some times when friction is a good thing. Most technologists think all friction is bad. >> Sure, and I'm not implying that it's necessarily good or bad, I'm curious though, is it potentially an economic advantage to have thought through and have policy on some of those issues? >> Well, what we're seeing here-- >> Because I feel like the US is a ticking time bomb on a lot of these issues. >> I was talking to VCs, some VC friends of mine here in the UK, and what they said they're seeing more and more, VCs asking what we call SMEs, small to medium enterprises, about their data policies, and SMEs not being able to answer those questions, and VCs getting nervous. So I think over time it's going to be a competitive advantage that we've done that homework, that we're basically not just rushing to get more users, but that we're looking at it across the piece. Because, fundamentally, that's more sustainable in the longer term. People will not be dumb too forever. They will not, and so doing that thinking now, where we work with people as we create our technology products, I think it's more sustainable in the long term. When you look at economics, sustainability is really important. >> I want to ask you about the Transport API business, 'cause in the US, same thing, we've seen some great openness of data and amazing innovations that have come out of nowhere. In some cases, unheard of entrepreneurs and/or organizations that better society for the betterment of people, from delivering healthcare to poor areas and whatnot. What has been the coolest thing, or of things you've seen come out of your enablement of the transport data. Use cases, have you seen any things that surprised you? >> It's quite interesting, because when I worked for the mayor of London as his director of digital projects, my job was to set up the London data store, which was to open all of London's public sector data. So I was kind of there from the beginning as a lobbyist, and when I was asking agencies to open up their data, they'd go, "What's the ROI?" And I'd just say, "I don't know." Because government's one and oh, I'm saying that was a chicken and egg, you got to put it out there. And we had a funny incident where some of the IT staff in transport for London accidentally let out this link, which is to the tracker net feed, and that powers the tube notice boards that says, "Your next tube is in a minute," whatever. And so the developer community went, "Ooh, this is interesting." >> John: Candy! >> Yeah, and of course, we had no documentation with it because it kind of went out under the radar. And one developer called Mathew Somerville made this map which showed the tubes on a map in real time. And it was like surfacing the underground. And people just thought, "Oh my god, that is amazing." >> John: It's illuminating. >> Yeah. It didn't do anything, but it showed the possibility. The newspapers picked it up, it was absolutely brilliant example, and the guy made it in half a day. And that was the first time people saw their transport system kind of differently. So that was amazing, and then we've seen hundreds of different applications that are being built all the time. And what we're also seeing is integration of transport data with other things, so one of our clients in Transport API is called Toothpick, and they're an online dental booking agency. And so you can go online, you can book your dental appointment with your NHS dentist, and then they bake in transport information to tell you how to get there. So we have pubs using them, and screens so people can order their dinner, and then they say, "You've got 10 minutes till the next bus." So all sorts of cross-platform applications. >> That you never could've envisioned. >> Emer: Never. >> And it's just your point earlier about it's not a zero sum game, you're giving so many ways to create value. >> Emer: Right, right. >> Again, I come back to this notion of education and creativity in the United States education system, so unattainable for so many people, and that's a real concern, and you're seeing the middle class get hollowed out. I think the stat is, the average wage in the United States was 55,000 in 1999, it's 50,000 today. The political campaigns are obviously picking at that scab. What's the climate like in Europe from that standpoint? >> In terms of education? >> No, just in terms of, yes, the education, middle class getting hollowed out, the sentiment around that. >> I don't think people are up to speed with that yet, I really don't think that they're aware of the scale. I think when they think robots or automation, they don't really think software. They think robots like there were in the movies, that would come, as I say, and do those jobs nobody wanted. But not like software. So when I say to them, look, E-discovery software, when it's applied retrospectively, what it shows is that human lawyers are only 60% accurate compared to it. Now, that's a no-brainer, right? If software is 100% accurate, I'm going to use the software. And the ratio difference is 1 to 500. Where you needed 500 lawyers before you need 1. So I don't think people are across the scale of change. >> But it's interesting, you're flying to Heathrow, you fly in and out, you're dealing with a kiosk. You drive out, the billboards are all electronic. There aren't guys doing this anymore. So it's tangible. >> And I think, to your point about education, I'm not as familiar with the education system in the US, but I certainly think, in Europe and in the UK, the education system is not capable of dealing even with the latest digital natives. They're still structuring their classrooms in the same way. These kids, you know-- >> John: They have missed the line with the technology. >> Absolutely. >> So reading, writing and arithmetic, fine. And the cost of education is maybe acceptable. But they may be teaching the wrong thing. >> Asynchronous non-linear, is the thing. >> There's a wonderful example of an Indian academic called Sugata Mitra, who has a fabulous project called a Hole in the Wall. And he goes to non-English speaking little Indian villages, and he builds a computer, and he puts a roof over it so only the children can do it. They don't speak English. And he came back, and he leaves a little bit of stuff they have to get around before they can play a game. And he came back six months later, and he said to them, "What did you think?" And one of the children said, "We need a faster CPU and a better mouse." Now, his point is self-learning, once you have access to technology, is amazing, and I think we have to start-- >> Same thing with the non-linear consumption, asynchronous, all this, the API economy enabling new kinds of expectation and opportunities. >> And it was interesting because the example, some UK schools tried to follow his example. And six months later, they rang him up and they said, "It's not working," and he said, "What did you do?" And they said, "Well, we got every kid a laptop." He said, "That's not the point." The point was putting a scarce resource that the children had to collaborate over. So in order to get to the game, they had figure out certain things. >> I think you're right on some of these (mumbles) that no one's talking about. And Dave and I are very passionate on this, and we're actually investing in a whole new e-learning concept. But it's not about doing that laptop thing or putting courseware online. That's old workflow in a new model. Come on, old wine in a new bottle. So that's interesting. I want to get your thoughts, so a personal question to end this segment. What are you passionate about now, what are you working, outside of the venture, which is exciting. You have a lot of background going back to technology entrepreneurship, public policy, and you're in the front lines now, thought leading on this whole new wide open sea of opportunity, confusion, enabling it. What are you passionate about, what are you working on? Share with the folks that are watching. >> So one of the main things we're trying to do. I work as an associate with Ernst & Young in London. And we've been having discussions over the past couple of months around techno ethics, and I've basically said, "Look, let's see if we can get EY "to build to build an EY good governance index." Like, what does good governance look like in this space, a massively complex area, but what I would love is if people would collaborate with us on that. If we could help to draw up an ethical framework that would convene the technology industry around some ethical good governance issues. So that's what I'm going to be working on as hard as I can over the next while, to try and get as much collaboration from the community, because I think we'd be so much more powerful if the technology industry was to say, "Yeah, let's try and do this better "rather than waiting for regulation," which will come, but will be too clunky and not fit for purpose. >> And which new technology that's emerging do you get most excited about? >> Hmm. Drones. (laughter) >> How about anything with bitcoin, block chains? >> Absolutely, absolutely, block chain. Yeah, block chain, you have to say, yeah. I think, 'cause bitcoin, you know, it's worth 20 p today, it's worth 200,000 tomorrow. >> Dave: Yeah, but block chain. >> Right, right. I mean, that is incredible potentiality. >> New terms like federated, that's not a new term, but federation, universal, unification. These are the themes right now. >> Emer: Well, it's like the road's been coated, isn't it? And we don't know where it's going to go. What a time we live in, right? >> Emer Coleman, thank you so much for spending your time and joining us on theCUBE here, we really appreciate the conversation. Thanks for sharing that great insight here on theCUBE, thank you. It's theCUBE, we are live here in Dublin, Ireland. I'm John Furrier with Dave Vellante. We'll we right back with more SiliconANGLEs, theCUBE and extracting the signal from the noise after this short break. (bright music)