(tranquil music) >> Alation was an early pioneer in solving some of the most challenging problems in so-called big data. Founded early last decade, the company's metadata management and data catalog have always been considered leading examples of modern tooling by customers and analysts alike. Governance is one area that customers identified as a requirement to extend their use of Alation's platform. And it became an opportunity for the company to expand its scope and total available market. Alation is doing just that today, announcing new data governance capabilities, and partner integrations that align with the market's direction of supporting federated governance. In other words, a centralized view of policy to accommodate distributed data in this world of an ever expanding data cloud, which we talk about all the time in theCUBE. And with me to discuss these trends and this announcement is Satyen Sangani, who's the CEO and co-founder of Alation. Satyen, welcome back to the CUBE. Good to see you. >> Thank you Dave, It's great to be back. >> Okay, so you heard my open, please tell us about the patterns that you were seeing in the market and what you were hearing from customers that led you in this direction and then we'll get into the announcement. >> Yeah, so I think there are really two patterns, right? I mean, when we started building this notion of a data catalog, as you said a decade ago, there was this idea that metadata management broadly classified was something that belonged in IT, lived in IT and was essentially managed by IT, right? I always liken it to kind of an inventory management system within a warehouse relative to Amazon.com, which has obviously broadly published for the business. And so, with the idea of bringing all of this data directly to the business and allowing people arbitrarily, depending on their role to use the data. You know, you saw one trend, which was just this massive, shift in how much data was available at any given time. I think the other thing that happened was that at the same time, data governance went through a real transitionary phase where there was a lot of demand often spurred by regulations. Whether that's GDPR, CCPA or more recently than that, certainly the Basel accord. And if you think about all of those regulations, people had to get something in a place. Now what we ended up finding out was when we were selling in to add accounts, people would say, well guess what? I've got this data governance thing going on, but nobody's really using it. I built this business glossary, it's been three years. Nothing's been really very effective. And we were never able to get the value and we need to get value because there are so many more people now accessing and using and leveraging the data. And so with that, we started really considering whether or not we needed to build a formal capability in the market. And that's what we're today that we're doing. >> I liked the way you framed that. And if you think back, we were there as you were in the early big day-to-days. And all the talk was about volume, variety and velocity. And those are sort of IT concepts. How do you deal with all these technical challenges? And then the fourth V which you just mentioned was value. And that's where the line of business really comes in. So let's get into the news. What are you announcing today? >> So we're announcing a new application on top of Alation's Catalog platform, which is an Alations data governance application. That application will be released with our 2021.3 release on September 14th. And what's exciting about that is that we are going to now allow customers to discreetly and elegantly and quickly consume a new application to get data governance regimes off the ground and initiatives off the ground, much more quickly than they've ever been able to do. This app is really all about time to value. It's about allowing customers to be able to consume what they need when they need it in order to be able to get successful governance initiatives going. And so that's what we're trying to deliver. >> So maybe you could talk a little bit about how you think about data governance and specifically your data governance approach. And maybe what's different about Alation's solution. >> Yeah, I think there's a couple of things that are different. I think the first thing that's most critically different is that we move beyond this notion of sort of policy declaration into the world of policy application and policy enforcement, right? I think a lot of data governance regimes basically stand up and say, look you know, it's all about people and then process and then technology. And what we need to do is declare who all the governors are and who all the stewards are. And then we're going to get all our policies in the same place and then the business will follow them. And the reality is people don't change their workflows to go off and arbitrarily follow some data governance policy that they don't know exists, or they don't want to actually have to follow up. And so really what you've got to do is make sure that the policy and the knowledge exists as in where the data exists. And that's why it's so critical to build governance into the catalog. And so what we're doing here is we're basically saying, look, you could declare policies with a new policy center inside of Alation. Those policies will get automatically created in some cases by integrating with technologies like Snowflake. But beyond that, what we're also doing is we're saying, look, we're going to move into the world of taking those policies and applying them to the data on an automated basis using ML and AI and basically saying that now it doesn't have to be some massive boil the ocean three-year regime to get very little value in a very limited business loss rate. Rather all of your data sets, all of your terms can be put into a single place on an automated basis. That's constantly being used by people and constantly being updated by the new systems that are coming online. And that's what's exciting about it. >> So I just want to follow up on that. So if I'm hearing you correctly, it's the humans are in the loop, but it's not the only source of policy, right? The machines are assisting. And in some cases managing end-to-end that policy. Is that right? >> You've got it. I think the the biggest challenge with data governance today is that it basically relies a little bit like the Golden Gate Bridge. You know, you start painting it and by the time you're done painting it, you've got to go back and start painting it again, because it relies upon people. And there's just too much change in the weather and there's too much traffic and there's just too much going on in the world of data. And frankly in today's world, that's not even an apt analogy because often what happens is midway through. You've got to restart painting from the very beginning because everything's changed. And so there's so much change in the IT landscape that the traditional way of doing data governance just doesn't work. >> Got it, so in winning through the press release, three things kind of stood out. I wonder if we could unpack them, there were multi-cloud, governance and security. And then of course the AI or what I like to call machine intelligence in there. And what you call the people centric approach. So I wonder if we could dig in into these and help us understand how they fit together. So thinking about multi-cloud governance, how do you think about that? Why is that so challenging and how are you solving that problem? >> Yeah, well every cloud technology provider has its own set of capabilities and platforms. And often those slight differences are causing differences in how those technologies are adopted. And so some teams optimize for certain capabilities and certain infrastructure over others. And that's true even within businesses. And of course, IT teams are also trying to diversify their IT portfolios. And that's another reason to go multi-cloud. So being able to have a governance capability that spans, certainly all of the good grade called megascalers, but also these new, huge emerging platforms like Snowflake of course and others. Those are really critical capabilities that are important for our customers to be able to get a handle on top of. And so this idea of being cloud agnostic and being able to sort of have a single control plane for all of your policies, for all of your data sets, that's a critical must have in a governance regime today. So that's point number one. >> Okay and then the machine learning piece, the AI, you're obviously injecting that into the application, but maybe tell us what that means both maybe technically and from a business stand point. >> Yeah, so this idea of a data policy, right? Can be sometimes by operational teams, but basically it's a set of rules around how one should and should not be able to use data, right? And so those are great rules. It could be that people who are in one country shouldn't be able to access the data of another country, very simple role, right? But how do you actually enforce that? Like you can declare it, but if there is a end point on a server that allows you to access the data, the policy is effectively moot. And so what you got to go do is make sure that at the point of leverage or at the point of usage, people know what the policy happens to be. And that's where AI come in. You can say let's document all the data sets that happened to be domiciled in Korea or in China. And therefore make sure that those are arbitrarily segregated so that when people want to use that as datasets, they know that the policy exists and they know that it's been applied to that particular dataset. That's somewhere where AI and ML can be super valuable rather than a human being trying to document thousands of databases or tens of thousands of data sets, which is really kind of a (mumbles) exercise. And so, that application of automation is really critical and being able to do governance at the scale that most enterprises have to do it. >> You got it 'cause humans just can't do that at scale. Now what do you mean by people-centric approach? Can you explain that? >> Yeah, often what I find with governance is that there's this notion of kind of there's this heavy notion of how one should deal with the data, right? So often what I find is that there are certain folks who think, oh well, we're going to declare the rules and people are just going to follow them. And if you've ever been well, a parent or in some cases seeing government operate, you realize that that actually isn't how things work. And involve them in how things are run. And if you do that, right? You're going to get a lot more success in how you apply rules and procedures because people will understand that and people know why they exist. And so what we do within this governance regime is we basically say, look, we want to make sure that the people who are using the data, leveraging the data are also the people who are stewarding the data. There shouldn't be a separate role of data steward that is arbitrarily defined off, just because you've been assigned to a job that you never wanted to do. Rather it should be a part of your day job. And it should be something that you do because you really want to do it. And it's a part of your workflow. And so this idea of being people centric is all about how do you engage the analyst, the product managers, the sales operation managers, to document those sales data sets and those product data sets. So that in fact, those people can be the ones who are answering the questions, not somebody off to the side who knows nothing about the data. >> Yeah, I think you've talked in previous CUBE interviews about context and that really fits to this discussion. So these capabilities are part of an application, which is what? it's a module onto your existing platform. And it's sort of it's a single platform, right? I mean, we're not bespoke products. Maybe you can talk about that. >> Yeah, that's exactly right. I mean, it's funny because we've evolved and built a relation with a lot of capability. I mean, interestingly we're launching this data governance application but I would say 60% of our almost 300 customers would say they do a form or a significant part of data governance, leveraging relations. So it's not like we're new to this market. We've been selling in this market for years. What's different though, is that we've talked a lot about the catalog as a platform over the last year. And we think that that's a really important concept because what is a platform? It's a capability that has multiple applications built on top of it, definitionally. And it's also a capability where third party developers can leverage APIs and SDKs to build applications. And thirdly, it has all of the requisite capabilities and content. So that those application developers, whether it's first party from Alation or third party can really build those applications efficiently, elegantly and economically well. And the catalog is a natural platform because it contains all of the knowledge of the datasets. And it has all of the people who might be leveraging data in some fundamental way. And so this idea of building this data governance module allows a very specialized audience of people in governance to be able to leverage the full capabilities of the platform, to be able to do their work faster, easier, much more simply and easily than they ever could have. And that's why we're so excited about this launch, because we think it's one example of many applications, whether it's ourselves building it or third parties that could be done so much more elegantly than it previously could have been. Because we have so much knowledge of the data and so much knowledge of how the company operates. >> Irrespective of the underlying cloud platform is what I heard before. >> irrespective of the underlying cloud platform, because the data as you know, lives everywhere. It's going to live in AWS, it's going to live in Snowflake. It's going to live on-premise inside of an Oracle database. That's not going to be changed. It's going to live in Teradata. It's going to live all over the place. And as a consequence of that, we've got to be able to connect to everything and we've got to be able to know everything. >> Okay, so that leads me to another big part of the announcement, which is the partnership and integration with Snowflake. Talk about how that came about. I mean, why snowflake? How should customers think about the future of data management. In the context of this relationship, obviously Snowflake talks about the data cloud. I want to understand that better and where you fit. >> Yeah, so interestingly, this partnership like most great partnerships was born in the field. We at the late part of last year had observed with Snowflake that we were in scores of their biggest accounts. And we found that when you found a really, really large Snowflake engagement, often you were going to be complementing that with a reasonable engagement with Alation. And so seeing that pattern as we were going out and raising our funding route at the beginning of this year, we basically found that Snowflake obviously with their Snowflake Ventures Investment arm realized how strategic having a great answer in the governance market happened to be. Now there are other use cases that we do with Snowflake. We can certainly get into those. But what we realized was that if you had a huge scale, Snowflake engagement, governance was a rate limiter to customers' ability to grow faster. And therefore also Snowflake's ability to grow faster within that account. And so we worked with them to not only develop a partnership but much more critically a roadmap that was really robust. And so we're now starting to deliver on that roadmap and are super excited to share a lot of those capabilities in this release. And so that means that we're automatically ingesting policies and controls from Snowflake into Alation, giving full transparency into both setting and also modifying and understanding those policies for anybody. And so that gives you another control plane through which to be able to manage all of the data inside of your enterprise, irrespective of how many instances of Snowflake you have and irrespective of how many controls you have available to you. >> And again, on which cloud runs on. So I want to follow up with that really interesting because Snowflake's promise of the data cloud, is it essentially abstracts the underlying complexity of the cloud. And I'm trying to understand, okay, how much of this is vision, how much is is real? And it's fine to have a Northstar, but sometimes you get lost in the marketing. And then the other part of the promise, and of course, big value proposition is data sharing. I mean, I think they've nailed that use case, but the challenge when you start sharing data is federated governance. And as well, I think you mentioned Oracle, Teradata that stuff's not all in the cloud, a lot of that stuff on-prem and you guys can deal with that as well. So help us sort of to those circles, if you can. Where do you fit into that equation? >> I think, so look, Snowflake is a magical technology and in the sense that if you look at the data, I mean, it reveals a very, very clear story of the ability to adopt Snowflake very quickly. So any data team with an organization can get up and running with the Snowflake instance with extraordinary speed and capability. Now that means that you could have scores, hundreds of instances of Snowflake within a single institution. And to the extent that you want to be able to govern that data to your point, you've got to have a single control plane through which you can manage all of those various instances. Whether they're combined or merged or completely federated and distinct from each other. Now, the other problem that comes up on governance is also discoverability. If you have all these instances, how do you know what the right hand is doing if the left hand is working independently of it? You need some way to be able to coordinate that effort. And so that idea of discoverability and governance is really the value proposition that Alation brings to the table. And the idea there is that people can then can get up and running much more quickly because, hey, what if I want to spin up a Snowflake instance, but there's somebody else, two teams over those already solved the problem or has the data that I need? Well, then maybe I don't even need to do that anymore. Or maybe I can build on top of that work to be able to get to even better outcome even faster. And so that's the sort of kind of one plus one equals three equation that we're trying to build with them. >> So that makes sense and that leads me to one of my favorite topics with the notion is this burgeoning movement around the concept of a data mesh in it. In other words, the notion that increasingly organizations are going to push to decentralize their data architectures and at the same time support a centralized policy. What do you think about this trend? How do you see Alation fitting in? >> Yeah, maybe in a different CUBE conversation. We can talk a little bit about my sort of stylized history of data, but I've got this basic theory that like everybody started out what sort of this idea of a single source of truth. That was a great term back in the 90s where people were like, look, we just need to build a single source of truth and we can take all of our data and physically land it up in a single place. And when we do that, it's going to all be clean, available and perfect. And we'll get back to the garden of Eden, right? And I think that idea has always been sort of this elusive thing that nobody's ever been able to really accomplish, right? Because in any data environment, what you're going to find is that if people use data, they create more data, right? And so in that world, you know, like that notion of centralization is always going to be fighting this idea of data sprawl. And so this concept of data mesh I think is, you know, there's formal technical definitions. But I'll stick with maybe a very informal one, which is the one that you offered. Which is just sort of this decentralized mode of architecture. You can't have decentralization if nobody knows how to access those different data points, 'cause otherwise they'll just have copies and sprawl and rework. And so you need a catalog and you need centralized policies so that people know what's available to them. And people have some way of being able to get conformed data. Like if you've got data spread out all over the place, how do you know which is the right master? How do you know what's the right customer record? How do you know what's your right chart of accounts? You've got to have services that exist in order to be able to find that stuff and to be able to leverage them consistently. And so, to me the data mesh is really a continuation of this idea, which the catalog really enabled. Which is if you can build a single source of reference, not a single source of truth, but a single place where people can find and discover the data, then you can govern a single plane and you can build consistent architectural rules so that different services can exist in a decentralized way without having to sort of bear all the costs of centralization. And I think that's a super exciting trend 'cause it gives power back to people who want to use the data more quickly and efficiently. >> And I think as we were talking about before, it's not about just the IT technical aspects, hey, it works. It's about putting power in the hands of the lines of business. And a big part of the data mesh conversation is around building data products and putting context or putting data in the hands of the people who have the context. And so it seems to me that Alation, okay, so you could have a catalog that is of the line of businesses catalog, but then there's an Uber catalog that sort of rolls up. So you've got full visibility. It seems that you've fit perfectly into that data mesh. And whether it's a data hub, a data warehouse, data lake, I mean, you don't care. I mean, that's just another node that you can help manage. >> That's exactly right. I mean, it's funny because we all look at these market scapes where people see these vendor landscapes of 500 or 800 different data and AI and ML and data architecture vendors. And often I get asked, well, why doesn't somebody come along and like consolidate all this stuff? And the reality is that tools are a reflection of how people think. And when people have different problems and different sets of experiences, they're going to want to use the best tool in order to be able to solve their problem. And so the nice thing about having a mesh architecture is you can use whatever tool you want. You just have to expose your data in a consistent way. And if you have a catalog, you can be able to have different teams using different infrastructure, different tools, different fundamental methods of building the software. But as long as they're exposing it in a consistent way, it doesn't matter. You don't necessarily need to care how it's built. You just need to know that you've got good data available to you. And that's exactly what a catalog does. >> Well, at least your catalog. I think the data mesh, it should be tools that are agnostic. And I think there are certain tools that are, I think you guys started with that principle. Not every data catalog is going to enable that, but I think that is the trend Satyen. And I think you guys have always fit into that. It's just that I think you were ahead of the time. Hey, we'll give you the last word. Give us the closing thoughts and bring us home. >> Well, I mean that's exactly right. Like, not all the catalogs are created equal and certainly not all governance is created equal. And I think most people say these words and think that are simple to get into. And then it's a death by a thousand cuts. I was literally on the phone with a chief data officer yesterday of a major distributor. And they basically said, look, like we've got sprawl everywhere. We've got data everywhere. We've got it in every type of system. And so having that sophistication turned into something that's actually easy to use is a super hard problem. And it's the one that we're focused on every single day that we wake up and every single night when we go to sleep. And so, that's kind of what we do. And we're here to make governance easy, to make data discovery easy. Those are the things that we hold our hats on. And we're super excited to put this release out 'cause we think it's going to make customers so much more capable of building on top of the problems that they've already solved. And that's what we're here to do. >> Good stuff, Satyen. Thanks so much, congratulations on the announcement and great to see you again. >> You too, Dave. Great talking. >> All right, thanks for watching this CUBE conversation. This is Dave Vellante, we'll see you next time. (tranquil music)

>> Narrator: From theCUBE's studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hello everyone, this is Dave Vellante. Welcome to this CUBE conversation. We got a really cool company that we're going to introduce you to, and Anthony Brooks Williams is here. He's the CEO of that company, HVR. Anthony, good to see you. Thanks for coming on. >> Hey Dave, good to see you again, appreciate it. >> Yeah cheers, so tell us a little bit about HVR. Give us the background of the company, we'll get into a little bit of the history. >> Yeah sure, so at HVR we are changing the way companies routes and access their data. And as we know, data really is the lifeblood of organizations today, and if that stops moving, or stop circulating, well, there's a problem. And people want to make decisions on the freshest data. And so what we do is we move critical business data around these organizations, the most predominant place today is to the cloud, into platforms such as Snowflake, where we've seen massive traction. >> Yeah boy, have we ever. I mean, of course, last week, we saw the Snowflake IPO. The industry is abuzz with that, but so tell us a little bit more about the history of the company. What's the background of you guys? Where did you all come from? >> Sure, the company originated out of the Netherlands, at Amsterdam, founded in 2012, helping solve the issue that customer's was having moving data efficiently at scale across all across a wide area network. And obviously, the cloud is one of those endpoint. And therefore a company, such as the Dutch Postal Service personnel, where today we now move the data to Azure and AWS. But it was really around how you can efficiently move data at scale across these networks. And I have a bit of a background in this, dating back from early 2000s, when I founded a company that did auditing recovery, or SQL Server databases. And we did that through reading the logs. And so then sold that company to Golden Gate, and had that sort of foundation there, in those early days. So, I mean again, Azure haven't been moving data efficiently as we can across these organizations with it, with the key aim of allowing customers to make decisions on the freshest data. Which today's really, table stakes. >> Yeah, so, okay, so we should think about you, as I want to invoke Einstein here, move as much data as you need to, but no more, right? 'Cause it's hard to move data. So your high speeds kind of data mover, efficiency at scale. Is that how we should think about you? >> Absolutely, I mean, at our core, we are CDC trades that capture moving incremental workloads of data, moving the updates across the network, you mean, combined with the distributed architecture that's highly flexible and extensible. And these days, just that one point, customers want to make decisions on us as much as they can get. We have companies that we're doing this for, a large apparel company that's taking some of their not only their core sales data, but some of that IoT data that they get, and sort of blending that together. And given the ability to have a full view of the organization, so they can make better decisions. So it's moving as much data as they can, but also, you need to do that in a very efficient way. >> Yeah, I mean, you mentioned Snowflake, so what I'd like to do is take my old data warehouse, and whatever, let it do what it does, reporting and compliance, stuff like that, but then bring as much data as I need into my Snowflake, or whatever modern cloud database I'm using, and then apply whatever machine intelligence, and really analyze it. So really that is kind of the problem that you're solving, is getting all that data to a place where it actually can be acted on, and turned into insights, is that right? >> Absolutely, I mean, part of what we need to do is there's a whole story around multi-cloud, and that's obviously where Snowflake fit in as well. But from our point of views of supporting over 30 different platforms. I mean data is generated, data is created in a number of different source systems. And so our ability to support each of those in this very efficient way, using these techniques such as CDCs, is going to capture the data at source, and then weaving it together into some consolidated platform where they can do the type of analysis they need to do on that. And obviously, the cloud is the predominant target system of choice with something like a Snowflake there in either these clouds. I mean, we support a number of different technologies in there. But yeah, it's about getting all that data together so they can make decisions on all areas of the business. So I'd love to get into the secret sauce a little bit. I mean we've heard luminaries like Andy Jassie stand up at last year at Reinvent, he talked about Nitro, and the big pipes, and how hard it is to move data at scale. So what's the secret sauce that you guys have that allow you to be so effective at this? >> Absolutely, I mean, it starts with  how you going to acquire data? And you want to do that in the least obtrusive way to the database. So we'll actually go in, and we read the transaction logs of each of these databases. They all generate logs. And we go read the logs systems, all these different source systems, and then put it through our webs and secret sauce, and how we how we move the data, and how we compress that data as well. So, I mean, if you want to move data across a wide area network, I mean, the technique that a few companies use, such as ourselves, is change data capture. And you're moving incremental updates, incremental workloads, the change data across a network. But then combine that with the ability that we have around some of the compression techniques that we use, and, and then just into very distributed architecture, that was one of the things that made me join HVR after my previous experiences, and seeing that how that really fits in today's world of real time and cloud. I mean, those are table stakes things. >> Okay, so it's that change data capture? >> Yeah. >> Now, of course, you've got to initially seed the target. And so you do that, if I understand you use data reduction techniques, so that you're minimizing the amount of data. And then what? Do you use asynchronous methodologies, dial it down, dial it up, off hours, how does that work? >> Absolutely, exactly what you've said they mean. So we're going to we're, initially, there's an initial association, or an initial concept, where you take a copy of all of that data that sits in that source system, and replicating that over to the target system, you turn on that CDC mechanism, which is then weaving that change data. At the same time, you're compressing it, you're encrypting it, you're making sure it's highly secure, and loading that in the most efficient way into their target systems. And so we either do a lot of that, or we also work with, if there's a ETL vendor involved, that's doing some level of transformations, and they take over the transformation capabilities, or loading. We obviously do a fair amount of that ourselves as well. But it depends on what is the architecture that's in there for the customer as well. The key thing is that what we also have is, we have this compare and repair ability that's built into the product. So we will move data across, and we make sure that data that gets moved from A to B is absolutely accurate. I mean people want to know that their data can move faster, they want it to be efficient, but they also want it to be secure. They want to know that they have a peace of mind to make decisions on accurate data. And that's some stuff that we have built into the products as well, supported across all the different platforms as well. So something else that just sets us apart in that as well. >> So I want to understand the business case, if you will. I mean, is it as simple as, "Hey, we can move way more data faster. "We can do it at a lower cost." What's the business case for you guys, and the business impact? >> Absolutely, so I mean, the key thing is the business case is moving that data as efficiently as we can across this, so they can make these decisions. So our biggest online retailer in the US uses us, on the biggest busiest system. They have some standard vendors in there, but they use us, because of the scalability that we can achieve there, of making decisions on their financial data, and all the transactions that happen between the main E-commerce site, and all the third party vendors. That's us moving that data across there as efficiently as they can. And first we look at it as pretty much it's subscription based, and it's all connection based type pricing as well. >> Okay, I want to ask you about pricing. >> Yeah. >> Pricing transparency is a big topic in the industry today, but how do you how do you price? Let's start there. >> Yeah, we charge a simple per connection price. So what are the number of source systems, a connection is a source system or a target system. And we try to very simply, we try and keep it as simple as possible, and charge them on the connections. So they will buy a packet of five connections, they have source systems, two target systems. And it's pretty much as simple as that. >> You mentioned security before. So you're encrypting the data. So your data in motion's encrypted. What else do we need to know about security? >> Yeah, you mean, that we have this concept and how we handle, and we have this wallet concept, and how we integrate with the standard security systems that those customers have already, in the in this architecture. So it's something that we're constantly doing. I mean, there's there's a data encryption at rest. And initially, the whole aim is to make sure that the customer feels safe, that the data that is moving is highly secure. >> Let's talk a little bit about cloud, and maybe the architecture. Are you running in the cloud, are you running on prem, both, across clouds. How does that work? >> Yeah, all of the above. So I mean, what we see today is majority of the data is still generated on prem. And then the majority of the talks we see are in the cloud, and this is not a one time thing, this is continuous. I mean, they've moved their analytical workload into the cloud. You mean they have these large events a few times a year, and they want the ability to scale up and scale down. So we typically see you mean, right now, you need analytics, data warehouses, that type of workload is sitting in the cloud, because of the elasticity, and the scalability, and the reasons the cloud was brought on. So absolutely, we can support the cloud to cloud, we can support on prem to cloud, I think you mean, a lot of companies adopting this hybrid strategy that we've seen certainly for the foreseeable next five years. But yeah, absolutely. The source of target systems considered on prem or in the cloud. >> And where's the point of control? Is it wherever I want it to be? >> Absolutely. >> Is it in one of the clouds on prem? >> Yeah absolutely, you can put that point of control where you want it to be. We have a concept of agents, these agents search on the source and target systems. And then we have the, it's at the edge of your brain, the hub that is controlling what is happening. This data movement that can be sitting with a source system, separately, or on target system. So it's highly extensible and flexible architecture there as well. >> So if something goes wrong, it's the HVR brain that helps me recover, right? And make sure that I don't have all kinds of data corruption. Maybe you could explain that a little bit, what happens when something goes wrong? >> Yeah absolutely, I mean, we have things that are built into the product that help us highlight what has gone wrong, and how we can correct those. And then there's alerts that get sent back to us to the to the end customer. And there's been a whole bunch of training, and stuff that's taken place for then what actions they can take, but there's a lot of it is controlled through HVR core system that handles that. So we are working next step. So as we move as a service into more of an autonomous data integration model ourselves, whichever, a bunch of exciting things coming up, that just takes that off to the next levels. >> Right, well Golden Gate Heritage just sold that to Oracle, they're pretty hardcore about things like recovery. Anthony, how do you think about the market? The total available market? Can you take us through your opportunity broadly? >> Yeah absolutely, you mean, there's the core opportunity in the space that we play, as where customers want to move data, they don't want to do data integration, they want to move data from A to B. There's those that are then branching out more to moving a lot of their business workloads to the cloud on a continuous basis. And then where we're seeing a lot of traction around this particular data that resides in these critical business systems such as SAP, that is something you're asking earlier about, what are some core things on our product. We have the ability to unpack, to unlock that data that sits in some of these SAP environments. So we can go, and then decode this data that sits between these cluster pool tables, combine that with our CDC techniques, and move their data across a network. And so particularly, sort of bringing it back a little bit, what we're seeing today, people are adopting the cloud, the massive adoption of Snowflake. I mean, as we see their growth, a lot of that is driven through consumption, why? It's these big, large enterprises that are now ready to consume more. We've seen that tail wind from our perspective, as well as taking these workloads such as SAP, and moving that into something like these cloud platforms, such as a Snowflake. And so that's where we see the immediate opportunity for us. And then and then branching out from there further, but I mean, that is the core immediate area of focus right now. >> Okay, so we've talked about Snowflake a couple of times, and other platforms, they're not the only one, but they're the hot one right now. When you think about what organizations are doing, they're trying to really streamline their data pipeline to get to turn raw data into insights. So you're seeing that emerging organizations, that data pipeline, we've been talking about it for quite some time. I mean, Snowflake, obviously, is one piece of that. Where's your value in that pipeline? Is it all about getting the data into that stream? >> Yeah, you just mentioned something there that we have an issue internally that's called raw data to ready data. And that's about capturing this data, moving that across. And that's where we building value on that data as well, particularly around some of our SAP type initiatives, and solutions related to that, that we're bringing out as well. So one it's absolutely going in acquiring that data. It's then moving it as efficiently as we can at scale, which a lot of people talk about, we truly operate at scale, the biggest companies in the world use us to do that, across there and giving them that ability to make decisions on the freshest data. Therein lies the value of them being able to make decisions on data that is a few seconds, few minutes old, versus some other technology they may be using that takes hours days. You mean that is it, keeping large companies that we work with today. I mean keeping toner paper on shelves, I mean one thing that happened after COVID. I mean one of our big customers was making them out their former process, and making the shelves are full. Another healthcare provider being able to do analysis on what was happening on supplies from the hospital, and the other providers during this COVID crisis. So that's where it's a lot of that value, helping them reinvent their businesses, drive down that digital transformation strategy, is the key areas there. No data, they can't make those type of decisions. >> Yeah, so I mean, your vision really, I mean, you're betting on data. I always say don't bet against the data. But really, that's kind of the premise here. Is the data is going to continue to grow. And data, I often say data is plentiful insights aren't. And we use the Broma you said before. So really, maybe, good to summarize the vision for us, where you want to take this thing? Yeah, absolutely so we're going to continue building on what we have, making it easier to use. Certainly, as we move, as more customers move into the cloud. And then from there, I mean, we have some strategic initiatives of looking at some acquisitions as well, just to build on around offering, and some of the other core areas. But ultimately, it's getting closer to the business user. In today's world, there is many IT tech-savvy people sitting in the business side of organization, as they are in IT, if not more. And so as we go down that flow with our product, it's getting closer to those end users, because they're at the forefront of wanting this data. As we said that the data is the lifeblood of an organization. And so given an ability to drive the actual power that they need to run the data, is a core part of that vision. So we have some some strategic initiatives around some acquisitions, as well, but also continue to build on the product. I mean, there's, as I say, I mean sources and targets come and go, there's new ones that are created each week, and new adoptions, and so we've got to support those. That's our table stakes, and then continue to make it easier to use, scale even quicker, more autonomous, those type of things. >> And you're working with a lot of big companies, the company's well funded if Crunchbase is up to date, over $50 million in funding. Give us up right there. >> Yeah absolutely, I mean a company is well funded, we're on a good footing. Obviously, it's a very hot space to be in. With COVID this year, like everybody, we sat down and looked in sort of everyone said, "Okay well, let's have a look how "this whole thing's going to shake out, "and get good plan A, B and C in action." And we've sort of ended up with Plan A plus, we've done an annual budget for the year. We had our best quarter ever, and Q2, 193% year over year growth. And it's just, the momentum is just there, I think at large. I mean obviously, it sounds cliche, a lot of people say it around digital transformation and COVID. Absolutely, we've been building this engine for a few years now. And it's really clicked into gear. And I think projects due to COVID and things that would have taken nine, 12 months to happen, they're sort of taking a month or two now. It's been getting driven down from the top. So all of that's come together for us very fortunately, the timing has been ideal. And then tie in something like a Snowflake traction, as you said, we support many other platforms. But all of that together, it just set up really nicely for us, fortunately. >> That's amazing, I mean, with all the turmoil that's going on in the world right now. And all the pain in many businesses. I tell you, I interview people all day every day, and the technology business is really humming. So that's awesome to hear that you guys. I mean, especially if you're in the right place, and data is the place to be. Anthony, thanks so much for coming on theCUBE and summarizing your thoughts, and give us the update on HVR, really interesting. >> Absolutely, I appreciate the time and opportunity. >> Alright, and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (upbeat music)

>>LA Las Vegas. It's the cube hovering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back to the cube. Our day one coverage of AWS reinvent 19 continues. Lisa Martin with Dave Volante. Dave and I have a couple of guests we'd like you to walk up. We've got Anthony Brooks billions, the CEO of HBR back on the cube. You're alumni. We should get you a pin and snowflake alumni. But Chris, your new Chris Dagon, chief revenue officer from snowflake. Chris, welcome to the program. Excited to be here. All right guys. So even though both companies have been on before, Anthony, let's start with you. Give our audience a refresher about HVR, who you guys are at, what you do. >>Sure. So we're in the data integration space, particularly a real time data integration. So we move data to the cloud in the in the most efficient way and we make sure it's secure and it's accurate and you're moving into environments such as snowflake. Um, and that's where we've got some really good customers that we happy to talk about joint custody that we're doing together. But Chris can tell us a little bit about snowflake. >>Sure. And snowflake is a cloud data warehousing company. We are cloud native, we are on AWS or on GCP and we're on Azure. And if you look at the competitive landscape, we compete with our friends at Amazon. We compete with our friends at Microsoft and our friends at Google. So it's super interesting place to be, but it very exciting at the same time and super excited to partner with Anthony and some others who aren't really a friends. That's correct. So I wonder if we could start by just talking about the data warehouse sort of trends that you guys see. When I talk to practitioners in the old days, they used to say to me things like, Oh, infrastructure management, it's such a nightmare. It's like a snake swallowing a basketball every time until it comes out with a new chips. We chase it because we just need more performance and we can't get our jobs done fast enough. And there's only three. There's three guys that we got to go through to get any answers and it was just never really lived up to the promise of 360 degree view of your business and realtime analytics. How has that changed? >>Well, there's that too. I mean obviously the cloud has had a big difference on that illustrious city. Um, what you would find is in, in, in yesterday, customers have these, a retail customer has these big events twice a year. And so to do an analysis on what's being sold and Casper's transactions, they bought this big data warehouse environment for two events a year typically. And so what's happening that's highly cost, highly costly as we know to maintain and then cause the advances in technology and trips and stuff. And then you move into this cloud world which gives you that Lester city of scale up, scale down as you need to. And then particular where we've got Tonies snowflake that is built for that environment and that elicited city. And so you get someone like us that can move this data at today's scale and volume through these techniques we have into an environment that then bleeds into helping them solve the challenge that you talk about of Yesi of >>these big clunky environments. That side, I think you, I think you kind of nailed it. I think like early days. So our founders are from Oracle and they were building Oracle AI nine nine, 10 G. and when I interviewed them I was the first sales rep showing up and day one I'm like, what the heck am I selling? And when I met them I said, tell me what the benefit of snowflake is. And they're like, well at Oracle, and we'd go talk to customers and they'd say, Oracles, you know, I have this problem with Oracle. They'd say, Hey, that's, you know, seven generations ago were Oracle. Do you have an upgraded to the latest code? So one of the things they talked about as being a service, Hey, we want to make it really easy. You never have to upgrade the service. And then to your point around, you have a fixed amount of resources on premise, so you can't all of a sudden if you have a new project, do you want to bring on the first question I asked when I started snowflake to customers was how long does it take you to kick off a net new workload onto your data, onto your Vertica and it take them nine to 12 months because they'd have to go procure the new hardware, install it, and guess what? >>With snowflake, you can make an instantaneous decision and because of our last test city, because the benefits of our partner from Amazon, you can really grow with your demand of your business. >>Many don't have the luxury of nine to 12 months anymore, Chris, because we all know if, if an enterprise legacy business isn't thinking, there's somebody not far behind me who has the elasticity, who has the appetite, who's who understands the opportunity that cloud provides. If you're not thinking that, as auntie Jessie will say, you're going to be on the wrong end of that equation. But for large enterprises, that's hard. The whole change culture is very hard to do. I'd love to get your perspective, Chris, what you're seeing in terms of industries shifting their mindsets to understand the value that they could unlock with this data, but how are big industries legacy industries changing? >>I'd say that, look, we were chasing Amad, we were chasing the cloud providers early days, so five years ago, we're selling to ad tech and online gaming companies today. What's happened in the industry is, and I'll give you a perfect example, is Ben wa and I, one of our founders went out to one of the largest investment banks on wall street five years ago, and they said, and they have more money than God, and they say, Hey, we love what you've built. We love, when are you going to run on premise? And Ben, Ben wa uttered this phrase of, Hey, you will run on the public cloud before we ever run in the private cloud. And guess what? He was a truth teller because five years later, they are one of our largest customers today. And they made the decision to move to the cloud and we're seeing financial services at a blistering face moved to the cloud. >>And that's where, you know, partnering with folks from HR is super important for us because we don't have the ability to just magically have this data appear in the cloud. And that's where we rely quite heavily on on instance. So Anthony, in the financial services world in particular, it used to be a cloud. Never that was an evil word. Automation. No, we have to have full control and in migration, never digital transformation to start to change those things. It's really become an imperative, but it's by in particular is really challenging. So I wonder if we could dig into that a little bit and help us understand how you solve that problem. >>Yes. A customer say they want to adopt some of these technologies. So there's the migration route. They may want to go adopt some of these, these cloud databases, the cloud data warehouses. And so we have some areas where we, you know, we can do that and keep the business up and running at the same time. So the techniques we use are we reading the transactional logs, other databases or something called CDC. And so there'll be an initial transfer of the bulk of the data initiative stantiating or refresh. At that same time we capturing data out of the transaction logs, wildlife systems live and doing a migration to the new environment or into snowflakes world, capturing data where it's happening, where the data is generated and moving that real time securely, accurately into this environment for somewhere like 1-800-FLOWERS where they can do this, make better decisions to say the cost is better at point of sale. >>So have all their business divisions pulling it in. So there's the migration aspects and then there's the, the use case around the realtime reporting as well. So you're essentially refueling the plane. Well while you're in mid air. Um, yeah, that's a good one. So what does the customer see? How disruptive is it? How do you minimize that disruption? Well, the good thing is, well we've all got these experienced teams like Chris said that have been around the block and a lot of us have done this. What we do, what ed days fail for the last 15 years, that companies like golden gate that we sold to Oracle and those things. And so there's a whole consultative approach to them versus just here's some software, good luck with it. So there's that aspect where there's a lot of planning that goes into that and then through that using our technologies that are well suited to this Appleton shows some good success and that's a key focus for us. And in our world, in this subscription by SAS top world, customer success is key. And so we have to build a lot of that into how we make this successful as well. >>I think it's a barrier to entry, like going, going from on premise to the cloud. That's the number one pushback that we get when we go out and say, Hey, we have a cloud native data warehouse. Like how the heck are we going to get the data to the cloud? And that's where, you know, a partnership with HR. Super important. Yeah. >>What are some of the things that you guys encountered? Because we many businesses live in the multi-cloud world most of the time, not by strategy, right? A lot of the CIO say, well we sort of inherited this, or it's M and a or it's developers that have preference. How do you help customers move data appropriately based on the value that the perceived value that it can give in what is really a multi world today? Chris, we'll start with you. >>Yeah, I think so. So as we go into customers, I think the biggest hurdle for them to move to the cloud is security because they think the cloud is not secure. So if we, if you look at our engagement with customers, we go in and we actually have to sell the value snowflake and then they say, well, okay great, go talk to the security team. And then we talked to security team and say, Hey, let me show you how we secure data. And then then they have to get comfortable around how they're going to actually move, get the data from on premise to the cloud. And that's again, when we engage with partners like her. So yeah, >>and then we go through a whole process with a customer. There's a taking some of that data in a, in a POC type environment and proving that after, as before it gets rolled out. And a lot of, you know, references and case studies around it as well. >>Depends on the customer that you have some customers who are bold and it doesn't matter the size. We have a fortune 100 customer who literally had an on premise Teradata system that they moved from on prem, from on premise 30 to choose snowflake in 111 days because they were all in. You have other customers that say, Hey, I'm going to take it easy. I'm going to workload by workload. And it just depends. And the mileage may vary is what can it give us an example of maybe a customer example or in what workloads they moved? Was it reporting? What other kinds? Yeah. >>Oh yeah. We got a couple of, you mean we could talk a little bit about 1-800-FLOWERS. We can talk about someone like Pitney Bowes where they were moving from Oracle to secret server. It's a bunch of SAP data sitting in SAP ECC. So there's some complexity around how you acquire, how you decode that data, which we ever built a unique ability to do where we can decode the cluster and pool tables coupled with our CDC technique and they had some stringent performance loads, um, that a bunch of the vendors couldn't meet the needs between both our companies. And so we were able to solve their challenge for them jointly and move this data at scale in the performance that they needed out with these articles, secret server enrollments into, into snowflake. >>I almost feel like when you have an SAP environment, it's almost stuck in SAP. So to get it out is like, it's scary, right? And this is where it's super awesome for us to do work like this. >>On that front, I wanted to understand your thoughts on transformation. It's a word, it's a theme of reinvent 2019. It's a word that we hear at every event, whether we're talking about digital transformation, workforce, it, et cetera. But one of the things that Andy Jassy said this morning was that got us start. It's this is more than technology, right? This, the next gen cloud is more than technology. It's about getting those senior leaders on board. Chris, your perspective, looking at financial services first, we were really surprised at how quickly they've been able to move. Understanding presumably that if they don't, there's going to be other businesses. But are you seeing that as the chief revenue officer or your conversations starting at that CEO level? >>It kinda has to like in the reason why if you do in bottoms up approach and say, Hey, I've got a great technology and you sell this great technology to, you know, a tech person. The reality is unless the C E O CIO or CTO has an initiative to do digital transformation and move to the cloud, you'll die. You'll die in security, you'll die in legal lawyers love to kill deals. And so those are the two areas that I see D deals, you know, slow down significantly. And that's where, you know, we, it's, it's getting through those processes and finding the champion at the CEO level, CIO level, CTO level. If you're, if you're a modern day CIO and you do not have a a cloud strategy, you're probably going to get replaced >>in 18 months. So you know, you better get on board and you'd better take, you know, taking advantage of what's happening in the industry. >>And I think that coupled with the fact that in today's world, you mean, you said there's a, it gets thrown around as a, as a theme and particularly the last couple of years, I think it's, it's now it is actually a strategy and, and reality because what Josephine is that there's as many it tech savvy people sit in the business side of organizations today that used to sit in legacy it. And I think it's that coupled with the leadership driving it that's, that's demanding it, that demanding to be able to access that certain type of data in a geo to make decisions that affect the business. Right now. >>I wonder if we could talk a little bit more about some of the innovations that are coming up. I mean I've been really hard on data. The data warehouse industry, you can tell I'm jaded. I've been around a long time. I mean I've always said that that Sarbanes Oxley saved the old school BI and data warehousing and because all the reporting requirements, and again that business never lived up to its promises, but it seems like there's this whole new set of workloads emerging in the cloud where you take a data warehouse like a snowflake, you may be bringing in some ML tools, maybe it's Databricks or whatever. You HVR helping you sort of virtualize the data and people are driving new workloads that are, that are bringing insights that they couldn't get before in near real time. What are you seeing in terms of some of those gestalt trends and how are companies taking advantage of these innovations? >>I think one is just the general proliferation of data. There's just more data and like you're saying from many different sources, so they're capturing data from CNC machines in factories, you know like like we do for someone like GE, that type of data is to data financial data that's sitting in a BU taking all of that and going there's just as boss some of data, how can we get a total view of our business and at a board level make better decisions and that's where they got put it in I snowflake in this an elastic environment that allows them to do this consolidated view of that whole organization, but I think it's largely been driven by things that digitize their sensors on everything and there's just a sheer volume of data. I think all of that coming together is what's, what's driven it >>is is data access. We talked about security a little bit, but who has rights to access the data? Is that a challenge? How are you guys solving that or is it, I mean I think it's like anything like once people start to understand how a date where we're an acid compliant date sequel database, so we whatever your security you use on your on premise, you can use the same on snowflake. It's just a misperception that the industry has that being on, on in a data center is more secure than being in the cloud and it's actually wrong. I guess my question is not so much security in the cloud, it's more what you were saying about the disparate data sources that coming in hard and fast now. And how do you keep track of who has access to the data? I mean is it another security tool or is it a partnership within owes? >>Yeah, absolutely man. So there's also, there's in financial data, there's certain geos, data leaves, certain geos, whether it be in the EU or certain companies, particularly this end, there's big banks now California, there's stuff that we can do from a security perspective in the data that we move that's secure, it's encrypted. If we capturing data from multiple different sources, items we have that we have the ability to take it all through one, one proxy in the firewall, which does, it helps him a lot in that aspect. Something unique in our technology. But then there's other tools that they have and largely you sit down with them and it's their sort of governance that they have in the, in the organization to go, how do they tackle that and the rules they set around it, you know? >>Well, last question I have is, so we're seeing, you know, I look at the spending data and my breaking analysis, go on my LinkedIn, you'll see it snowflakes off the charts. It's up there with, with robotic process automation and obviously Redshift. Very strong. Do you see those two? I think you addressed it before, but I'd love to get you on record sort of coexisting and thriving. Really, that's not the enemy, right? It's the, it's the Terra data's and the IBM's and the Oracles. The, >>I think, look, uh, you know, Amazon, our relationship with Amazon is like a, you know, a 20 year marriage, right? Sometimes there's good days, sometimes there's bad days. And I think, uh, you know, every year about this time, you know, we get a bat phone call from someone at Amazon saying, Hey, you know, the Redshift team's coming out with a snowflake killer. And I've heard that literally for six years now. Um, it turns out that there's an opportunity for us to coexist. Turns out there's an opportunity for us to compete. Um, and it's all about how they handle themselves as a business. Amazon has been tremendous in separation of that, of, okay, are going to partner here, we're going to compete here, and we're okay if you guys beat us. And, and so that's how they operate. But yes, it is complex and it's, it's, there are challenges. >>Well, the marketplace guys must love you though because you're selling a lot of computers. >>Well, yeah, yeah. This is three guys. They, when they left, we have a summer thing. You mean NWS have a technological DMS, their data migration service, they work with us. They refer opportunities to us when it's these big enterprises that are use cases, scale complexity, volume of data. That's what we do. We're not necessary into the the smaller mom and pop type shops that just want to adopt it, and I think that's where we all both able to go coexist together. There's more than enough. >>All right. You're right. It's like, it's like, Hey, we have champions in the Esri group, the EEC tuna group, that private link group, you know, across all the Amazon products. So there's a lot of friends of ours. Yeah, the red shift team doesn't like us, but that's okay. I can live in >>healthy coopertition, but it just goes to show that not only do customers and partners have toys, but they're exercising it. Gentlemen, thank you for joining David knee on the key of this afternoon. We appreciate your time. Thank you for having us. Pleasure our pleasure for Dave Volante. I'm Lisa Martin. You're watching the queue from day one of our coverage of AWS reinvent 19 thanks for watching.

(upbeat music) >> Hi, and welcome to another Cube Conversation where we speak with thought leaders in depth about the topics that are most important to the overall technology community. I'm Peter Burris, your host. Every business inspires to be a digital business, which is every business, faces a significant challenge. They need to use their data in new and value creating ways. But some of that data is not lending itself to new applications, new uses because it's locked up in formats, in technologies and applications that don't lend themselves to change. That's one of the big challenges that every business faces. What can they do to help unlock, to help liberate their data from older formats and older approaches so they can create new sources of value with it. To have that conversation, we're joined by a great guest. Greg Tinker is the CTO and Founder of SereneIT. Greg, welcome back to theCube. >> Thank you Peter, very appreciate it buddy. >> It's been a long time. This is your first time here with SereneIT so why don't you tell us a little bit about SereneIT. >> Sure, so at a high level we are a technology partner. SereneIT focuses on the next generation model structures of engineering first. There's a lot of VARS, in simplest terms, I would say we're a value at a reseller, sure. But we capitalize and focus just on the VA. Anybody can bring VR. The legacy approach of just being a reseller is no longer valid in our industry. Complexities and trying to have a situation where you can liberate data, try to take it from a legacy entrenched model, process, procedure and go into a new modern IT software defined ecosystem is very complex. And our objective is to make the, enablement of IT serene or simple and that's where SereneIT comes from. >> You know, I love the name but if you go back 20 years as you said, the asset that IT was focused on and took care of was the hardware. >> That's right. >> And we bought the hardware from a reseller, they just made the installations, configurations and what not. But as you said, today we're focused on the data. That's the asset. >> That's correct. >> And just as we used to have challenges uplifting and all the things we had to do with hardware, we're having similar types of challenges when you think about how to apply data to new uses, sustain that asset feature of it but apply it in new ways to create new value. As you talk to customers, what is the problem that you find they're encountering as they try to think what to do with their high value traditional data? So there's actually, I'll call it three strategic problems. Becoming to where it to be a workload optimized model structures or your data driven intelligence, trying to pull something out of the data model, trying to pull something out of the data, make it tangible to the business. And then trying to figure out a way to make it easy to enable the users, that is the employees to do something with the data the have. Making it more of a cloud-centric approach. Everybody wants that easy button now. So at a high level, trying to make that a possibility is where we spend our time today. And give you a quick example of that would be legacy block storage. We do a lot in the storage world. And we focus on software defined storage apparatus or solutions. So a lot of our clients are kind of mired down with legacy block, via Fibre Channel basics that were great for their era. But today with cost being a big factor in trying to be able to leverage an ecosystem where I can take my data, wherever my data sits and leverage it on multiple different apparatuses, be it BlueData, be in Kubernetes, be it name your favorite Docker solution. Trying to be able to use that in an ecosystem in a software defined hyper cloud, doing that on a legacy block is very problematic. And that's where we help customers transition from that legacy mindset, legacy IT infrastructure into a more of a modern software defined data program. >> So what's talk about that. Because there's a more modern technology, but really what they're doing is they're saying, look I've got this data, using these protocols like Fibre Channel with these applications and it's doing its job. >> That's right. >> But I want to create options on how I might use that data in the future, options that aren't available to me or aren't available to my business if it stays locked inside Fibre Channel for example. >> That's correct. >> So what you're really doing, is you're giving them paths to new options with their data that can be sustained whatever the technology is. Have I got that right? >> In a nutshell, Frank I would agree with your sentiment on that, your comment is spot on. We take customers data, we look at the business as a whole. And we focus on, what is the core of the business? Be it, maybe it's a High-Performance Computing Cluster Maybe it's a Oracle, Cyrus, Informant name your favorite data base structure. Maybe it's MapR, maybe it's a Dupe. We look at the business and determine, how are we using that data? How much data do we need? What's my data working set size? Understanding that and then we actually would design a solution that will be a software defined ecosystem that we can move that data in. And nine times out of 10 we can do it on the fly. Rarely, rarely ever do we have an outage to do it. Or that might be a small few minute outage window when we do a cut over, where we keep everything in mirroring Lockstep . >> Well that's one of the beauties of software defined is that you have those kinds of flexibilities. >> That's right. >> But think of, so talk to me a little bit about the you are, the customer realizes they have a problem. They find you guys. >> Sure. >> So how do they find you? >> So we do a lot with large scale Fortune 50, Fortune 100, the large scale enterprise businesses. And we do that with our, we're known in the engineering world, big accounts, because of our backdrop in HP engineering. And so HP brings us a lot into these accounts to help them solve a big business problem. So that's how a lot of our customers are finding us today. We are reaching out with media, like theCube here to talk to clients about the fact that we do exist and that we exist to help them consume a more modern IT in footprint. To help them go from that legacy model into that more modern model. >> Okay, so the customer realizes they have a problem, HPE and others, help identify you guys, matches you together. You show up, how do you work with the customer? Is it your big brains and the customer passive? Or you're working side by side to help them accelerate their journey? >> We find it best that we do it in a cohesive manner. We sit down and have a long discussion with their, usually their Chief Executive officer, their CTO, Chief Technology Officer, we'll sit down and talk about the business constraints. And then we'll go down to the directors the guys on the front lines that see the problems on a day to day basis. And we look at where their constraints are. Is it performance, IOP driven. Nine times out of 10, those problems are no longer there. They were solved years ago. Today it's more about the legacy model of, let me log a ticket to stand up a new virtual machine to a SQL database to do this application. So I've logged the ticket, a week two later I finally get a virtual machine. And now I got to get five more teams engaged, I get it online. Total business takes about a month to get some new apparatus up. Where if we go into a software defined ecosystem where we have these playbooks and this model written for the business, we can do that in 10 minutes. Be it on Nutanix do it with SimpliVity, VMware models, we don't' differentiate that. We let the customer tell us which one they use. 'Cause everybody has their liking. Be it some are VMware shop, some are Hyper-V, some are KBM. We do all of them. >> But the point is you want to help them move form an old world that was focused on executing the tasks associate with bringing the system up to a new world that's focused on the resources being able to configure themselves, being able to bring to bring themselves up test themselves in a software defined manner introducing some of those DevOps processes. Whatever the technology is, they have the people and the process to execute the technology. >> That's exactly right, because the technology in a nutshell. If you look at just technology itself that's not the hard part. Not for us anyway, 'cause we're an engineering team that's what we do well. The data driven intelligence stuff and helping customers bring more value out of their data. We can help them with that and show them exactly how we would do it. Be it a different technologies and stuff and we'll get into that discussion later. But the biggest problem we see is the people and processes which you just mentioned. Pushing the button, achieve an objective. That is where the old way of being very ticket driven Siloed approach, really slow down the economics of business. Was a huge driving force of not achieving the ROI that you actually set out to do years ago. Where we have one client that has a little over 4,000 servers and how my team and I explain it to the clients. Come out to the Golden Gate bridge. January 1 you start painting. December 30th you're done painting and January 1 you start painting again. You never get done. It's always getting painted. Patching of these large scale enterprises is the exact same way. You can't patch all the servers on a Saturday. You can't patch three thousand machines, BIOS, firmware, the list goes on. What we do for them is we actually put in an apparatus engine, basically an automation engine and instead of an army of 10 people doing firmware or BIOS and all the stuff updates, we automated 100% of that entire process. That's what SereneIT does. Help a customer take a, could be a legacy model, bare metal machine and show them how we can automate the bare metal machine. We can do the exact same thing in any hypervisor on the planet today. >> So that it's done faster, simpler. The outcome is more predictable. The result is more measurable. >> Yes. >> That's really great stuff. Let's go back to this notion of data because we kind of started with this idea of data and having to evolve the formats increasing the flexibility of it's utilization. We talked about hypervisors and all that technology is kind of sucking it forward, bringing that data forward making it possible to do things with it, but still the data itself is a major challenge. How are you working with customers to get them to envision the new data world independent of some of these other technologies? >> Sure, okay. So yeah, we have clients right now, we have (mumbled) systems these are global file systems that have enormous amount of data in it, some of it is compiled code logics for drivers and firmware and Kernel code structure that are forthcoming technologies that aren't even released yet. We have clients that have data based structure with ascii text is very common road driven. We have customers that have flat ascii files that are just flat text files. So we help the customers grab data from that existing data footprint for new lines of business. Determine what are we touching, how are we touching and how often are we touching it and why are we touching it? Case in point, when you have a large manufacturer doing chip design and your looking at a global file system you're trying to give assertation data as to what drivers are our developers working on most frequently. In the medical community, we have a client we're working on at global scale, we're doing real time data analytics to figure out if we're doing SQL injection from a hacker. So we show them exactly how we can do this in an inline driver stack and show them how to do it with the technology reducing their actual CapEx expend. There's legacy tools out there that work great. You know one of these is like, I won't give names of product and stuff, but there's a lot of cool technologies that's been around for a long time. >> That works. >> That works. >> And it just needs a smart person, or a smart team to put it together so it can be applied. >> That's what we've been doing with our clients is trying to show them that we can take the data that you have, be it flat ascii files or binary data structures. And we can show them that we can give you data analytics and pull that back. We have another client in law industry that we manage worldwide and we do e-discovery. On trying to figure out phrases and things that are maybe concerning to them in a financial world that is the global market. And we're able to give them that data structure on their own intellectual property and we give that to them in real time. We give them a dashboard so they can log in to the dashboard and they can see real time data transparency at a moments notice, so they can tell what the market is doing in Britain or they can tell what the market is doing in Singapore or U.S. by just looking at a dashboard and we're pulling data back. And we're pulling it from outside of world data points, this could be Facebook. Real time feeds, news, media and we pull it from internal data feeds. Email transactions that are going from their financial, they have like CIO's the Chief Investment Officers. Most people think of that as an information officer, right? So we're able to pull data from that and show them that they have a great deal of intellectual property at their fingertips that honestly they've never used before and that's what we're helping customers do today. >> Greg Tinker, Founder, CTO SereneIT. Thanks so much for being on theCube. >> Thank you very much Peter. >> And once again want to thank you for listening to this Cube Conversation. Until next time. (upbeat music)

>>live from Washington D. C. It's the Cube covering Bumi World 19 to Bide Movie. >>Hey, welcome back to the Cubes Coverage of Bumi World 19 from Washington D. C. I'm Lisa Martin with John Ferrier and John and I have a Cube alumni sitting with us. We have the chief product officer off. Del blew me. Steve would Steve, Welcome back. >>Thank you. It's great to be back. I could see again. John. Great must meet you >>back. Wise Enjoyed your keynote this morning, Man. There were so many nuggets and there I couldn't type faster. But one of my favorite things that you said is that no one is asking for less data. Slower? >>Yes, OK did I like kind of like saying because it frames things very clearly. It's just because it's clearly a prole. Every relates to him in the audience, but it was kind of amusing, so they've really got it immediately as I get that, that's a fair statement, so >>so like, and then you kind of took us the audience back. Thio 11 months ago at Bumi World 18. Some of the things that you guys said this is what we're going to be really focused on redefining the eye and I pass to be intelligent. Give her audience who wasn't able to see your keynote A little bit of that historical from 11 months ago. So what you guys are delivering today what the Bumi platform looks like today? >>Yeah, sure. So I mean, a lot of showed last Army, we kind of owe. Then we feel like we is like craters. The industry have to kind of try lead it. Where? Where is it going next? That's our big kind of duty, I guess. And so it's been taken over when we had the founder of booming attend, which was nice, but yes, so the big thing we should Last year was kind of the next generation, which is really a unified look and feel super easy to build applications that spend all of the portfolio and art in our that we offer our customers. We wanted to make it very collaborative, so users of business or business analysts or quick technical people can work together and use. Our platform is a collaboration space of the right controls in place. Eso stuff like that was really good to show that our new solutions. Overview. We've been definitely encouraging partners to put Maur intellectual property into our platform to excel, help accelerate their customers. Helping our customers just get people on board as quickly as possible. In fact, actually owned boarding employees on boarding was the solution we showed last year. >>That was fantastic. I couldn't believe how complex that was at Bumi. And when you guys said, We've got to change this huge improvements. >>Yeah, well, it was sort of a discovery that came up from one of our cells. Engineers got Andy Tiller did a fantastic job. He didn't enjoy his, um, his own boarding experience abuse me and then sort of building a solution. And we're like, we like we can actually do this way better on the platform. But what was amazing was that even for a company the size of Bumi, which is about 1000 people, we have, like, nearly 100 integration points and systems had to be coordinated to on board a single employee 100. Yeah, it's a lot, you know. So it became a really connectivity problem, actually, on >>boarding >>bits relatively easy. It's just, like connected all these systems. That's the hard bit. So yeah, we're excited to show that I think we got a kick out of seeing you together than we give progress on how we're moving that forward with various demos >>you don't want to ask you. Last year we asked the chief operating officer and the CEO Bumi what their investment priorities were going into the next year. And they said Number one was product. So that was a key thing. First and foremost go to market and then customer equation. But a product has been a big focus. That continues to be. What >>is >>the problem? Does it mean product when your chief product officer, what do you overseeing? Talk about What is the product? What is the platform And is there a difference? >>Yeah, I mean, so we we talk about the problem because we're in the product group, but we definitely see it as a platform. The investment in product is great. It means I get to spend lots of money like about my new converse. I won't try to show them, but way, but yeah, I mean, the investment partners being that we know that as we get Maur is this is this economy keeps building of integration and connective iti wanna continue to hold our leadership. We need to invest in product to make it easier. The expectations of our users is that they get a really premium experience when they're on board it onto the platform. We have to make sure we keep up to date with all of that effort. So a lot of what we talked about, it's how one is that we break our product up into discreet service is to allow us to move faster from an engineering perspective. And there's a lot of stuff that goes on there to think about ourselves as a platform to make sure we're fully extensible on. Then providing Maura Maura service is that people can build on our platform. So a lot of that investment just driving those >>activity. Rick was on yesterday talking about the big bets they made early on that are paying off. One of them was Aussie Cloud. On seeing that as you look at the architecture of this kind of new era of clobbering cloud to point, are we calling it? There's new requirements. It's the glue layers being built out. You need data to be accessible on addressable and available in real time, and you have multiple systems to talk to hence the integration you guys are doing. But this new mega trends happening is event driven architectures, which you guys talk about. There's a P I's just going from rest ful to state. And so you have micro service is here. So these air new dynamics Can >>you take >>a minute displaying like what all this means And what is event driven infrastructure? >>Yeah, a venture of architecture. But yeah, that's well, that's what we've been calling it. But yeah, I mean, it's basically that we're going to models where we're responding in real time to things that are happening out there on that revolt that involves a whole new level of scale. But, you know, we're also getting to things like streaming soas. Data come comes in, it's coming in, not in these packets, but it's constantly being fed to you, sir, constantly having to process it. You know, before in the integration space, it was like what? You'd set up a schedule you'd say, move that data at midnight from there to there and then it got faster and booming, provided real time, which was a request response that you send it personally, require a response back. But now it's like we're not going to just send it to you as a discreet thing. We're going to send it to you constantly, so event driven architectures. But how do you handle this continuous influx of data? And it's not getting any less. So how do you kind of manage this? We're being pulled in. Both ends were being pulled. There's never been more data that you never wanted to have faster. So it's like, How do you manage that? So for Bhumi, you know, that's why we're investing so heavily. >>Used to be in the old days when things were slower, events were like a trigger in a network management software alarm notification. Now they're happening. All the time is more and more events and paying attention to what events becomes a non human thing. Yeah, it's a software thing. Is that kind of where this is going? >>Yeah, well, I >>mean, we've been thinking >>a lot about that, like we sort of feel it. One is that we're gonna grow up from being on iPods to more of a data management vendor. We think that, like where the data manager in the future will come from an I pass, that we will be managing your data across like all of these systems from the catalogue and preparation to the, you know, actually integration and surfacing it up in real time and all that kind of streaming side. So I know it's Ah yeah, it's an evolving field for sure. >>One final point on this topic of product AP eyes have been great. They really made the market. Going back to the original Web service is in early two thousands to cloud. Where does a P I go? A A p I to dot or whatever you call it. What's the next Gen Place for AP? Eyes? >>Well, so it's interesting course. So we >>have >>a slightly different view of a pie management. That may be the typical AP management space, which is one thing to declare openly. But I think I >>want to >>go with that. Were right in the sense that cause I would think that because I'm a product, >>it's a good thing for a product. I don't think so Go >>and we're more than a little opinionated. So >>it is here, >>but yeah. Is that like sure. I mean, with a p I You need a gateway you need for the proxy ap eyes. Wherever they may be, wherever they may be developed. Other you build him and Bumi or you code them yourself when you told him, Manage those and throttle and scale and add policies and, you know, have developers registered to use them and monitor their usage and cut them off and have quotas. All that kind of that is old, fantastically good stuff. You know, there's lots of understeer doing a lot of that. We're adding Maur Mork capabilities there. But for us, a p I is really about AP enabling absolutely everything like we're in this world where you got refrigerators, two autonomous vehicles to cloud infrastructure to pivotal to all these different environments. And you have to have a tool that how do you How do you manage a P I across this incredibly disparate landscape of tools, technologies, things, infrastructure and it's one thing to say. OK, we could manage a P eyes and you install our software. Well, that's not good enough because, you know, with our customer like Jack in the box. They have 2200 plus retail locations. Nice have joked in my keynote that it's like painting Golden Gate Bridge. If you had to upgrade your gateway every time there was enough grade needed. It's like pain the Golden Gate Bridge to get to the end and you start all over again. That's 2200 plus retail locations. You know, I work for Dow. Ultimately is the holy owner of our business. He put five billion P seas on the planet. What if you had a gateway on five billion peces like, How do you manage that from a single control plane in the cloud? And that's what we're after. How do you do that huge scale AP enabling literally everything. >>And this was kind of under the concept of run anywhere that waas Yes, >>yes, yeah, and that was because we wanted to emphasize that it was about running Ap eyes and a pen, enabling things wherever they may be. That's why we put it under the run anywhere Banner. >>What's the biggest thing that you guys have done this year from last movie world that you're proud of? In terms of product or technology or something that could be of some obscure something prominent. What do you do? You proud of? What's the big thing? >>Yeah, well, for a point of perspective, it would be the AP I side for sure, because that was that was a big lift. There was a lot of work involved. We kind of moved ourselves forward very, very quickly in our capabilities on a p I with Gateway portal proxy, you know, literally within the span of just over a year. So that was Ah, big left. But I would, you know, because I also run engineering. So I feel like I need to, like, geek out a little bit. I mean, one of my proud things is, actually, we started wrestling and wrangling that 30 terabytes plus of metadata and starting to see what's in there. And like, anything in data science, you know, you're kind of like looking at weaken start. We started seeing all sorts of cool new things. Now I'm not gonna talk about it the inside side, But you start to see new things. We start to see ways that that meditated can be applied. So we built the infrastructure It's huge scale, massive scale they might have meditated, were ingesting and then analyzing eyes helping us, you know, improve productivity across the platforms. We talk a lot about being more efficient, more effective, so you'll see more of that in the pub. >>Can you clear up the just the commentary around the definition around single tenant instance? And when customers do multi tenant, because the benefit of the single tenants what the main core value proposition with the data, the unification of data? That's awesome. But there's also potential opportunities with customs. Might want have a roll run through things. So you have flexibility. Is that true? Is that the definite Take us through what the difference when, when multi tenant kicks in and what's >>well, so on our platform multi tendencies s. So if you think about the build experience when you're your dragon dropping, pointing, clicking, building your work flows or your processes for managing your data, you do that in the cloud, and then you can decide where you wanna put that. So where is that actually gonna be executed? And you can put it in our cloud, which is our multi tenant cloud, and then you. Could we manage it all for you? And that's fantastic. You can point or manage. Cloud service is if you have very specific requirements, usually around security, Sometimes around hyper scale. Well may put you in a manage cloud service environment. But then, if you have very sensitive data, you may want to run that workload and then stole our little run time. Adam, you know behind your firewall so we never see the data. So it's super sensitive. We don't see it. We >>see how >>it's running and we manage it. We have grade that that infrastructure for you, but we never see your data, so it kind of gives you the best of both worlds. You could be a cloud first, cloud only vendor, and you can be a traditional on perimeter. You could be a hybrid of both >>is not a requirement. The product. It's a customer choice. >>It's a total customer choice. I think that's pretty cool. Yeah, and I think actually we're one of the few that does it the way we've been doing for a long time. And it's hard, by the way, because it's like maintaining that compatibility For 10 plus years, is quite difficult to make sure everything works every time. We have, like 9000 >>customers and 80 plus countries. But on the the 30 plus terabytes of anonymous metadata, you are very clear this morning and saying that it's just the metadata that's not the actual have any any, you know, private information from any of our customers. But in terms of leveraging that data for those insights where some of the things that from last spoon me world to this one, that that access to all that data has what some are. Some of the announcements, maybe that came out today that you guys looked at saying, It's these are some of the nuggets that were able to pull out because we have the access to this musing. Maybe it's a I or what not gonna give you >>some examples in one was the the suggested filters. And it was a simple thing. I did sort of like that joke of It's one small step for Bhumi customers, but a giant leap for booming engineering. But because we rebuild a whole bunch of infrastructure to dio but suggested filters just making it easier to query information of various systems. And it is cool because it literally is looking your system, comparing it with other customers systems based on how you've configured in this case Attilio environment and then working out actually, based on what people are doing. This is kind of what the filter might look like for you, which is very, very personalized to the user. Based on intelligence. We have more That's on the bill tight. We have more on the deployment side because you can show you, actually hey, few of built in a p. I do want to deploy it out, too. A raspberry pie will. Actually, you probably want to configure the AP. I like this where you may find you see some issues here, and that's not static information that's evolving from the metadata. We can see the performance of your systems against the Oxy. All right, In that environment, I do it a bit like this. Or if you deploy to say, I Jules, we might make recommendations based on that process of that, a p I or that data quality hub that you wantto excess just make your systems run like this. So it's kind of predicting how you deployed >>I was about to say, Are you helping customers get predicted with us? >>Yes. And there's lots we can do there. I mean, like, so we'll do Maura. Maura. But we can automatically optimize your deployment. So if it's in our cloud, that that'll happens automatically. So helps us, too. But for customers, it's also making just go. Okay, we'll deploy it. And then the leverage that community to so see what works best. The most successful deployment, the most successful architecture and the way you've deployed it is was what you'll be matched with. And then the same with the run time. With monitoring, we can start to look at things and see will. Well, not slowing down a little bit. Actually, it's Linden the string error. A little bit, actually, based on what we've seen before, that system may be about to fall over, so you might want to get all not before completely does what it's gonna do. >>Well, we got you here. I want to get your definition of cloud two point. Oh, on We've been riffing on this. Been more of a takeoff on Web two point. Oh, because cloud one daughter was anything Amazon you know storage. Compute some networking, but it's Amazon that working. But you scale up start ups will go there. It's beautiful thing, but now it's enterprise. Start to embrace cloud with hybrid on premises and deal with all these hard problems and challenges. Crazy opportunity. An operating model for on premises Cloud Club one Dato Amazon. Really easy to work with. Scales are beautiful. Cloud to point is different. I got things to deal with. Observe, abilities, a hot thing you got kubernetes containers you got. How would you define what cloud? Two pointers for Enterprise? >>We'll think because we're all about the data cloud 2.0, is really like for us. Ah, data problem. I mean, it's just like E think before I mean, I was part of cells force for a while. Is this whole idea of like earlier data in the cloud will manageable for you. But when you're getting into the kind of environments were seeing, say, there's just too much data like you, it's not feasible. I mean, give you an example. Bumi itself. We moved our infrastructure customers was transplanted customers from Rackspace to eight of us Last year it was a big engineering lift to do. You can imagine moving 9000 plus customers over on our cloud Ah, design surface that but so we did that, but actually to move the data, it was so much it was actually faster to put the disk drives in the back of a van. No mobile moving over snowball using the wheel network, you know, the engine motor e one and then put the hard drives in. And then we did our sink to bring them back up so that we have the same data in both locations. And that's just an example of the kind of customer data that customers are routinely struggling with. And cloud wasn't set up for that. But that's becoming day to day now, so you need a highly distributed architecture. It was probably why we announced the Adam Fabric, which is really a fabric of connectivity, as much as is a fabric of data, so we don't need to move your data around. You can leave it where it is. We can do some analysis on it as part of an end to end >>Program Cube alumni that I was on the cube a couple weeks ago, he said. Data is the new software, data and software. What's your reaction to that when you hear that? >>To some extent, >>I think that's a CZ, A bit of a business process geek. I think you know this process around data for sure. But But I do think I've heard similar things with, like, actually, applications come and go. Business processes come and go, but the data remains so I think maybe in some respects, your date is the new software Could be a term I I could buy into a Well, >>Steve, it's been great having you on the Cube with John and me sharing all of the things that you guys have done in the last 11 months. I can't wait to see how everything becomes a P. I enabled. Still, next Bumi World, you gotta come back. Yeah, All right. Our pleasure for John Ferrier. I'm Lisa Martin. You're watching the Cube from Bhumi World 19. Thanks for watching

>> from Santa Clara, California It's the Cube covering techno ovation World Pitch Summit 2019 Brought to You by Silicon Angle Media Now here's Sonia to Gari >> Hi and welcome to the Cube. I'm your host, >> Sonia to Gari, and we're here at Oracle's >> Agnew's campus in Santa Clara, California covering techno vacations. World Pitch Summit 2019 a pitch competition in which girls from around the world developed mobile lapse in order to create positive change >> in the world with us. Today we have team >> powerful daisies from Brazil. Um, and their acts called safe tears. So their members are on a Toronado. Uh, Clara Patan. Um, Anna Julia Uh, Giacomelli um Emmanuel Amara Skin and Julie Carr Bio. Welcome to the Cuban. Congratulations on your being finalists. Thank you. So your app safe tears tell us more about that. >> So our APP is a suicide prevention app in which its user gets his own glass of blue feelings, where to use their ads or remove tears accordingly with his feelings. So if the user said they had tears any, they're happy they take theirs out. >> Wow, that's amazing. So can you tell us how someone would use Thea >> So let's say I'm set. So I go to the app and I at use. So add those as my 2% rise is the absolute send motivational messages to me like saying go talk to somebody over find help and also encouraging me to be to know, to get better. And if I'm happy, I take tourists out and I get messages like congratulating me too because I'm doing better. >> So is there like a graph of your improvement of how you feel some days you feel the other days >> we would like to implement dead in your future. But right now, in this version of the app that is not available >> OK, well, yeah, that would be a great thing, Thio. So how did you come up with this idea? >> So in our community, there was a lot of suicide cases and off course with friends and family, and it was something that really needed more help. So we went Thio lecture about suicide, and the woman said that we are like a glass of water. We we feel that up and then one day all the water gets out and then somebody you know tries to suicide themselves. So we wanted this person to thio like realize that she's getting wars so she can find help before anything bad happens. >> And I know that sometimes giving advice to someone who's depressed can be very tricky. And you have to make sure saying the right thing. So how did you find out what kind of advice to give in your app? >> Yeah, we had help over school psychologist. So she was there with those the whole time we were developing and she helped us do Every single message is that the absense to the person is, you know, viewed by >> her And have you seen has anyone used the app and has felt better? Any success stories >> they're hesitant to launch, But we did tested it and people really liked it and thought that they would use it. >> That's amazing. So how >> did you all meet and why did >> you decide to join techno vacation? >> So we were from the same school from different classes where we're from the same school. So we met there and our teacher showed us the documentary code girl and their inspired us to join techno vacation because we thought it would be a cool experience. >> And so how detective ation help you achieve your goals and make your act better. >> So without techno vacation, of course, we couldn't be here and get all this experience in learning's to improve our app. So it's helping a lot. >> And, um, can you tell us more specifically like, what skills have you learned from Tekken? Ovation. >> Like programming, big public speaking and about business. We learn a lot like doing the business plan about marketing and publicity and all that. And I heard you >> guys had an amazing week this week. You went to whoever you saw Golden Gate Bridge. Can you tell us more? About what? The highlights of the wiki pad? >> Yeah, we went to Webber, of course. And we talked to people there. He was amazing. Talk to employees and see how is life there. And also we went to the Golden Bridge and we crossed the bridge. It was a Bahar, you know, we're not used to exercising. Right? And last night we had a dance party. What? She was really fun and we got to interact with people from all over the world and it was amazing. >> That's so great. Well, thank you so much for coming on. I'm so looking forward to seeing your app in the APP store one day. And congratulations. And good luck for the pitch tonight. >> Thank you so much. This has been team >> powerful daisies from Brazil. This'd the Cube. We'll see you next time.

>> from Santa Clara, California It's the Cube covering techno ovation World Pitch Summit 2019 Brought to you by Silicon Angle Media Now here's Sonia to Gari >> Hi and welcome to the Cube. I'm your host, Sonia to Gari. And we're here at Oracle's Agnew's campus in Santa Clara, California covering techno vacations World Pitch Summit 2019. Ah, pitch competition in which girls from around the world developed mobile lapse in order to create positive change in the world with us. Today we have Team Coco from Kazakhstan. Welcome. The members are, um Dilma as camel Over and Mallika Bree by Ava Uh, Donna Ulanova and Lube of do Chen Kuo Welcome. And congratulations on being finalists. Thank you. So your app is called tech Go. Can you tell us more about it? >> Yes. Uh so so techo in three d mobile application, which has a minute reality and as connected to the hardware which has dedicated for the behavioral change of people for so that they can become more conscious and like a friendly. >> And can you tell us more about how it works? Yes, >> of course there is. Luba, who can explain this? Okay. S >> o r application is about an astronaut who needs to save the planet. S O Firstly is there is a game in which a person needs to save your hair. Virtual airs by selling some ecological problems in it so that he or she wrote, be educated to both real life scenarios. And I also have a step counter which tracks your carbon footprint and encourages people to trust Morgan Friend the transportation options And that's a rare make really impact is that we connect our application with a special trash boxes in our city. All those locations are shown on the map, and coming to this place is user received trash box. And since Rosa Garbage and then because he has restaurants carriage here, she will get some points and your impact will be realized in the eventuality. Yeah, >> So what impact in society do you hope that this app will help change >> Rapids three t mobile application and it's a game. That is why Gamification and theater magic reality, which is a r which is inside this game a cz more visually in psychological attractive to people and those challenges that we provide a game are intensified so that most of the people. When they accomplish their goals, they might get, like, have a certain profit out of it so that they can become worker friendly and gain benefits. This is how we want to make sure that people might gain my changed a behavior for the sake of ecology. >> That's awesome. So you're using essentially a game incentivize people to make better choices in their everyday lives. That's great. And so how >> did you >> come up with this idea? >> So look, I will explain >> this. Actually, there were before some eco trash boxes in our school because like the thing off, ecological problems and recycling is one of the most talked about topics in Kazakhstan nowadays. And like in our school, the students try. Thio make this echo charge boxes, but they were always empty because students wasn't incent ified to recycle the garbage. And we tested our up in our school and we already launched it in our school and this ups incentivize our students. And now this I could trash boxes with our hard way always full. So >> that's awesome. See, you already found some success with your app. Thank you. Do you think that that this is a problem in the bigger community. >> Oh, maybe Donna Comptel. >> So we're saying that we started locally, but we got to go globally within that, uh, a pollution, like a pollution global problem and we trying to solve all over the world. So in our game, we have the whole world that you become an astronaut. So you should be aware for hold the problem that was happening in the earth. So we are trying to engage and educate people to be more global on to be more responsible for our final for our home. >> It sounds like everyone in the world should download that app. Yes, I do hope Thio uh, expand if you get the funding. >> Yes, um, we plan to expand not only in our country, Kazakhstan on only locally, but also globally. And we would like to create the eco friendly community across Central Asia since we want to make sure that consciousness is global in our area. >> And what struggles have you faced trying to create this app? >> Um, probably there were some struggles and off course in the realization and, uh, the realization of technical part of this project and creating a business model, since we are not very experienced in this kind of things. But since we have participated in techno vacation and we were immersed in this protest and were modified Thio motivated. Yeah, and we're motivated to learn all this things and acquire those skills. And this is why we became more experienced in this stuff. So right now, uh, those struggles that we face before not longer problem for us. So yeah, this what we faced? >> So techno vacation has definitely helped. Do you improve your app and yes, right houses. Tech innovation Helped you? >> Yeah, Um, probably someone else wants to ask you this question. >> How is SECNAV ation help? You were What skills have you learned from this journey? For >> example, one of the most important skills, I guess iss a teamwork. Like after we started to work on the one project, we started to listen each other excavation actually helped us too. Um, I understand the opinions off other people and like to understand the problems in our society. We start to dream bigger to think bigger, wider kind of that >> That's amazing. And also take Novation helping us >> to explore new companies to be more like open a person to come to The company's asked about the help on not like B just like see the problems and trying to solve trying to find a solution and be the people of the world and be responsible for our planet for what's happening in our local community on be aware of everything. >> And, um So I heard you guys had an amazing week. Um, you you went to whoever You went some other places. So can you tell us more about your week >> you want? So we went to amazing places in a Silicon Valley in a San Francisco San Jose and we so, like it'd, for example, Golden Gate Bridge. And also the Alcatraz so were so impressed by their architecture by the people by the nature on DDE. We just expected a lot of Onda. We just got this old expectations come to the reality on dhe. We hope that that kind of dream will come true in our future, and we gonna to work in a one of the big companies that were located here. I know all the universities. So >> how is it like going to the different tech companies and seeing it in real life. >> So we >> visited Uber Company and Google Ventures, and both we I have seen people who work is there, and we're really impressive on. And we really like it. It? Yeah. And, uh, I think so. Before, like in my childhood, I dreaming to be to be in Silicon Valley, to goes there and, like, meet people who are work already working you And now, like my dream came through. >> That's awesome. And you get to see California And you you might be able to win today. So thank you so much for being on. I wish you all the best. And I hope you haven't amazing pitch tonight. Thank you. This has been Team Coco from Kazakhstan. I'm your host, Sonia to Garey. This is the Cube. Stay tuned for more

live from San Francisco it's the cube covering micron insight 2018 brought to you by micron welcome back to the San Francisco Bay everybody we saw the Sun rise in the bay this morning of an hour so we're gonna see the Sun set this gorgeous setting here at Pier 27 Nob Hills up there the Golden Gate Bridge over there and of course we have this gorgeous view of the bay you're watching the cube the leader in live tech coverage we're covering micron insight 2018 ai accelerating intelligence a lot of talk on on on memory and storage but a lot more talk around the future of AI so we got a great discussion here on the auto business and how AI is powering that business Jeff Bader is here is the corporate vice president and general manager of the embedded business unit at micron good to see you again Jeff thanks for coming on and Simon and rigor is the vice president BMW and he's also joined by Vijay Nadkarni who was the global head of AI and augmented reality at Visteon which is a supplier to Automobile Manufacturers gentlemen welcome to the cube thanks so much for coming on thank you so you guys had a panel earlier today which was pretty extensive and just a lot of talk about AI how AI will be a platform for interacting with the vehicle the consumer the driver interacting with the vehicle also talked a lot about autonomous vehicles but Simon watch you kick it off your role at BMW let's let's just start there it will do the same for Vijay and then get into it research portion that we do globally in which is represented here in North America and so obviously we're working on autonomous vehicles as well as integrating assistance into the car and basically what we're trying to do is to get use AI as much as possible in all of the behavioral parts of the vehicle that uses have an expectations towards being more personalized and having a personalized experience whereas we have a solid portion of the vehicle is going to be as a deterministic anesthetic as we have it before like all of the safety aspects for example and that is what we're working on here right now Vijay Visteon is a supplier to BMW and other auto manufacturers yes we are a tier 1 supplier so we basically don't make cars but we supply auto manufacturers of which BMW is one and my role is essentially AI technology adversity on and also augmented reality so in AI there are basically two segments that we cater to and one of them is that almost driving which is fully our biggest segment and the second one is infotainment and in that the whole idea is to give the driver a better experience in the car by way of recommendations or productivity improvements and such so that is so my team basically develops the technology and then we centrally integrate that into our products so so not necessarily self-driving it's really more about the experience inside the vehicle that is the and then on the autonomous driving side we of course very much are involved with the autonomous driving technology which is tested with detecting objects are also making the proper maneuvers for the Waker and we're definitely going to talk about that now Jeff you sell to the embedded industry of fooding automobile manufacturers we hear that cars have I forget the number of microprocessors but there's also a lot of memory and storage associate yeah I mean if you follow the chain you have our simon representing the OEMs Vijay represented the Tier one suppliers were supplier to those Tier one suppliers in essence right so so we're providing memory and storage that then goes in to the car in as you said across all of the different sort of control and engine drone and computing units within the car in particular into that infotainment application and increasingly into the a TAS or advanced driver assistance systems that are leading toward autonomous driving so there's a lot of AI or some AI anyway in vehicles today right presumably yeah affected David who did a wonderful job on the panel he was outstanding but he kind of got caught up in having multiple systems like a like an apple carplay your own system I actually have a bit about kind of a BMW have a mini because I'm afraid it's gonna be self-driving cars and I just want to drive a drive on car for this take it away from me though but but you push a button if you want to talk to a Syrian yeah push another button if you want to talk to the mini I mean it's it's gonna use it for different use cases right exactly may I is also about adaption and is also about integrating so AI is is is coming with you with the devices that you have with you anyway right so your might be an Alexa user rather than a Google assistant user and you would have that expectation to be able to ask to chat with your Alexa in your car as well that's why we have them in the vehicle also we have an own voice assistant that we recently launched in Paris Motorshow which augments the experience that you have with your own assistants because it factors in all of the things you can do with the car so you can say there is a solid portion of AI already in the vehicle it's mainly visible in the infotainment section right and of course I remember the first time I'm sure you guys experienced to that the the car braked on my behalf and then kind of freaked me out but then I kind of liked it too and that's another form of machine intelligence well that out well that counts for you that had not that has not necessarily been done by AI because in in in let's say self-driving there is a portion of pretty deterministic rule based behavior and exactly that one like hitting an object at parking you don't need AI to determine to hit the right there is no portion or of AI necessary in order to improve that behavior whereas predicting the best driving strategy for your 20-mile ride on the highway this is where AI is really beneficial in fact I was at a conference last week in Orlando it's the Splunk show and it was a speaker from BMW talking about what you're doing in that regard yeah it's all about the data right learning about it and and in turning data into insights into better behavior yes into better expected behavior from whatever the customer wants so Vijay you were saying before that you actually provide technology for autonomous vehicles all right I got a question for you could it autonomous - could today's state of autonomous vehicles pass a driver's test no no would you let it take one no it depends I mean there are certain companies like way mo for example that do a lot but I still don't think way mo can take a proper driver's test as of today but it is of course trying to get there but what we are essentially doing is taking baby steps first and I think you may be aware of the SAE levels so level 1 level 2 level 3 level 4 SF and a 5 so we and most of the companies in the industry right now are really focusing more on the level 2 through level 4 and a few companies like Google or WAV or other and uber and such are focusing on the level 5 we actually believe that the level 2 through 4 is the market would be ready for that essentially in the shorter term whereas the level 5 will take a little while to get that so everybody Christmas and everyone we're gonna have autonomous because I'm not gonna ask you that question because there's such a spectrum of self-driving but I want to ask you the question differently and I ask each of you when do you think that driving your own car will become the exception rather than than the rule well I'd rather prefer actually to rephrase the question maybe to where not when because we're on a highway setting this question can be answered precisely in roughly two to three years the the functionality will kick in and then it's going to be the renewal of the vehicles so if you answer if you if you ask where then there is an answer within the next five years definitely if we talk about an urban downtown scenario the question when is hard to answer yeah well so my question is more of a social question it is a technology question because I'm not giving up my stick shift high example getting my 17 year old to get his permit was like kicking a bird out of the nest I did drive his permanent driver on staff basically with me right so why but I mean when I was a kid that was freedom 16 years old you racing out and there is a large generational group growing up right now that doesn't necessarily see it as a necessity right so not driving your own car I think car share services right share who bore the so and so forth are absolutely going to solve a large portion of the technology of the transportation challenge for a large portion of the population I think but I agree with the the earlier answers of it's gonna be where you're not driving as opposed to necessarily win and I think we heard today of course the you know talking about I think the number is 40,000 fatalities on the roadways in the u.s. in the u.s. yeah everybody talks about how autonomous vehicles are going to help attack that problem um but it strikes me talk about autonomous cars it why don't we have autonomous carts like in a hospital or even autonomous robots that aren't relying on lines or stripes or beacons you one would think that that would come before in our autonomous vehicle am I missing something are there are there there there systems out there that that I just haven't seen well I don't know if you've ever seen videos of Amazon distribution centers yeah but they're there they're going to school on lines and beacons and they are they're not really autonomous yeah that's fair that's fair yeah so will we see autonomous carts before we see autonomous cars I think it's a question what problem that solves necessarily yeah it's just as easy for them to know where something is yeah you think about microns fabs every one of our fabs is is completely automated as a material handling system that runs up and down around the ceilings handling all the wafers and all the cartridges the wafers moving it from one tool to the next tool to the next tool there's not people anymore carrying that around or even robots on the floor right but it's a guided track system that only can go to certain you know certain places well the last speaker today ii was talking about it I remember when robots couldn't climb stairs and now they can do backflips and you know you think about the list of things that humans can do that computers can't do it let's get smaller and smaller every year so it's kind of scary to think about one hand is that does the does the concept of Byzantine fault-tolerance you guys familiar with that does that does that come into play here you guys know what that's about I don't know what it is exactly so that's a problem and I first read about it with it's the Byzantine general problem if you have nine generals for one Oh attack for one retreat and the ninth sends a message to half to retreat or not and then you don't have the full force of the attack so the concept is if you're in a self-driving boat within the vehicle and within the ecosystem around the city then you're collectively solving the problem so there these are challenging math that need to be worked out and and I'm not saying I'm a skeptic but I just wanted more I read about it the more hurdles we have there's some isolated examples of where AI I think fits really well and is gonna solve problems today but this singularity of vehicle seems to be we have a highly regulated environment obviously public transportation or public roads right are a highly regulated environment so it's like it's different than curating playlists or whatever right this is not so much regulated traffic and legislation isn't there yet so especially and it's it's designed for humans right traffic cars roads are designed for human to use them and so the adoption to they the design of any legislation any public infrastructure would be completely different if we didn't drive as humans but we have it we have machines drive them so why are robots and carts not coming because the infrastructure really is designed for humans and so I think that's what's going to be the ultimate slow down is how fast we as a society that comes up with legislation with acceptance of behavioral aspects that are driven by AI on how fast we adopt it technically I think it can happen faster than yeah yeah it's not a technology problem as much as it is the public policy insurance companies think about one of the eventually you can think of from from let's say even level four capable car on a highway is platooning yeah right instead of having X number of car lengths to the turn fryer you just stack them up and they're all going on in a row that sounds great until Joe Blow with their 20 year old Honda you know starts to pull into that Lane right so you either say this Lane is not allowed for that or you create special infrastructure essentially that isn't designed for humans there is more designed specifically for the for the machine driven car right how big is this market it's it feels like it's enormous I don't know how do you look at the tan we can talk to the memory I can talk the memory storage part of it right but today memory and storage all of memory storage for automotive is about a two and a half billion dollar market that is gonna triple in the next three years and probably beyond that my visibility is not so good maybe yours is better for sure but it then really driven by adoption rate and how fast that starts to penetrate through the car of OAM lines and across the different car in vijay your firm is when were you formed how long you've been around or vistas be around basically since around 2001 okay we were part of relatively old spun out whiskey on that at work right okay so so alright so that's been around forever yeah for this Greenfield for you for your your group right where's the aw this is transitional right so is it is it is it you try not to get disrupted or you trying to be the disrupter or is it just all sort of incremental as a 101 year old company obviously people think about you as being ripe for disruption and I think we do quite well in terms of renewing ourselves coming from aeroplane business to a motorcycle business to garbage and so I think the answer is are we fast enough I'll be fast enough in adoption and on the other hand it's fair to say that BMW with all of its brands is part of a premium thing and so it's not into the mass transportation so everything that's going to be eaten up by something like multi occupancy vehicle mass transportation in a smaller effort right this is probably not going to hurt the premium brand so much as a typical econo type of boxy car exciting time so thanks so much for coming on the cube you got a run appreciate thank you so much okay thanks for watching everybody we are out from San Francisco you've watched the cube micron inside 2018 check out Silicon angle comm for all the published research the cube dotnet as well you'll find these videos will keep on calm for all the research thanks for watching everybody we'll see you next time you

>> Live from San Francisco, it's theCUBE, covering Micron Insight 2018. Brought to you by Micron. >> Welcome back to San Francisco Bay everybody. You're watching theCUBE, the leader in live tech coverage. We're covering Micron Insight 2018. It's just wrapping up behind us. It's a day long of thought-leading content around AI, AI for good, how it's affecting the human condition and healthcare and the future of AI. I'm Dave Vellante, he's Peter Burris and that's the Golden Gate Bridge over there. You used to live right up that hill over there. >> I did. >> Dee Mooney is here. >> Until they kicked me out. >> Dee Mooney is here. She's the Executive Director of the Micron Foundation. Dee, thanks so much for taking time out of your schedule and coming on theCUBE. >> You bet, I'm very pleased to be here with you today. >> So, you guys had some hard news today. We heard about the 100 million dollar fund that you're launching, but you also had some news around the Foundation. >> That's right. >> The grant, you announced two winners of the grant. Tell us about that. >> That's right. So, it was a great opportunity for Micron to showcase its goodness and what a great platform for us to be able to launch the Advancing Curiosity grant. It is all around really focusing on that, on advancing curiosity, in the hopes that we can think about how might AI help for good, whether that's in business and health or life, and it's really a great platform for us to be able to be a part of today. >> So, what are the specifics? It was a million dollar grant? >> So, it was a million dollar fund and today we announced our first recipients. It was to the Berkeley College of Engineering, specifically their BAIR, which is Berkeley A, Artificial Intelligence Research lab, then also Stanford PHIND lab, which is the Precision, Health and Integrated Diagnostics lab. And then also a non-profit called AI For All, and really their focus is to get the next generation excited about AI and really help the underrepresented groups be exposed to the field. >> So with AI For All, so underrepresented groups as in the diversity culture-- >> Females, underrepresented groups that might not actually get the exposure to this type of math and science in schools and so they do summer camps and we are helping to send students there next summer. >> How do you decide, what are the criteria around which you decide who gets the grants, and take us through that process. >> Today, because we are all about goodness and trying to enhance and improve our communities, this was all around how can AI do some good. So, we are taking a look at what problems can be solved utilizing AI. The second thing we're taking a look at is the type of technology. We want students and our researchers to take a good look at how the technology can work. Then also, what groups are being represented. We want a very diverse group that bring different perspectives and we really think that's our true ability to innovate. >> Well, there's some real research that suggests a more diverse organization solves problems differently, gets to more creativity and actually has business outcomes. That may not be the objective here, but certainly it's a message for organizations worldwide. >> We certainly think so. The more people that are being involved in a conversation, we think the richer the ideas that come out of it. One more thing that we are taking a look at in this grant is we'd like the recipients to think about the data collection, the privacy issues, the ethical issues that go along with collecting such massive amounts of data, so that's also something that we want people to consider when they're applying. >> One of the challenges in any ethical framework is that the individuals that get to write the ethical framework or test the ethical framework, the ethics always works for them. One of the big issues that you just raised is that there is research that shows that if you put a certain class of people and make them responsible for training the AI system, that their biases will absolutely dominate the AI system. So these issues of diversity are really important, not just from a how does it work for them, but also from a very starting point of what should go into the definition of the problem, the approach and solution, how you train it. Are you going the full scope or are you looking at just segments of that problem? >> We'll take a look at, we hope to solve the problems eventually, but right now, just to start with, it's the first announcement of the fund. It's a million dollars, like we mentioned. The first three recipients were announced today. The other recipients that come along, we're really excited to see what comes out of that because maybe there will be some very unique approaches to solving problems utilizing AI. >> What other areas might you look at? How do you determine, curiosity and AI, how'd you come up with that and how do you determine the topics in the areas that you go after? >> The Micron Foundation's mission is to enhance our lives through our people and our philanthropy and we focus on stem and also basic human needs. So, when Micron is engaged in large business endeavors like today, talking about AI, it was the perfect opportunity for us to bring our goodness and focus on AI and the problems that can be solved utilizing it. >> Pretty good day today, I thought. >> Oh, yeah. >> I have to say, I've followed Micron for awhile and you guys can get pretty down and dirty on the technical side, but it was an up-level conversation today. The last speaker in particular really made us think a little bit, talking about are we going to get people to refer-- >> Max Tegmark, right? >> Was that Max Tegmark? Yeah. >> I think that's the name. I didn't catch his name, I popped in late. But he was talking about artificial general intelligence >> I know. >> Reaching, I guess a singularity and then, what struck me is he had a panel of AI researchers, all male, by the way, I think >> Yes. >> I noticed that. >> Yes, we did too. >> The last one, which was Elon Musk, who of course we all know, thinks that there's going to be artificial general intelligence or super intelligence, and he asked every single panel member, will we achieve that, and they all unanimously said yes. So, either they're all dead wrong or the world is going to be a scary place in 20, 30, 50 years. >> Right, right. What are your thoughts on that? >> Well, it was certainly thought-provoking to think about all the good things that AI can do, but also maybe the other side and I'm actually glad that we concluded with that, because that is an element of our fund. We want the people that apply to it or that we'll work with to think about those other sides. If these certain problems are solved, is there a down side as well, so that is definitely where we want that diverse thinking to come in, so we can approach the problems in a good way that helps us all. >> Limited time left, let's talk a little bit about women in tech. In California, Jerry Brown just signed a law into effect that, I believe it's any public company, has to have a woman >> On the Board? >> on the Board. What do you think about that? >> Well, personally, I think that's fantastic. >> Well, you're biased. (laughs) >> I might be a little biased. I guess it's a little unfortunate we now have to have laws for this because maybe there's not enough, I'm not exactly sure, 6but I think it's a step in the right direction. That really aligns well with what we try to do, bring diversity into the workplace, diversity into the conversation, so I think it's a good step in the right direction. >> You know, let's face it, this industry had a lack, really, of women leaders. We lost Meg Whitman in a huge Fortune 50 company, in terms of a woman leader, replaced by Antonio Neri, great guy, know him well, but that was one, if you're counting, one down. Ginni Rometty, obviously, huge presence in the industry. I want to ask you, what do you think about, I don't want to use the word quotas, I hate to use it, but if you don't have quotas, what's the answer? >> I don't know about quotas either. We do know that we help, our Foundation grants span the pipeline from young students all the way up through college and we see this pipeline. It starts leaking along the way. Fifth grade, we start seeing girls fall out. Eighth grade is another big-- >> In the U.S. >> In the U.S. >> Not so much in other countries, which is pretty fascinating. >> We are a global foundation and when we talk with our other partners, they're also interested in having stem outreach into their schools because they want to bring in the critical thinking and problem-solving skills, so, I used to think it was quite just a U.S. problem, but now being exposed to other cultures and countries, definitely they have a different approach, but I think it's a problem that we all strive to overcome. >> Well, it's pretty good research that shows that governance that includes women is generally more successful. It reaches better decisions, it reaches decisions that lead to, in the case of Boards, greater profitability, more success, so if you can't convince people with data, you have to convince them with law. At the end of the day, it would be nice if people recognized that a diverse approach to governance usually ends up with a better result but if you can't, you got to hit 'em over the head. >> I guess so, I guess so. >> Well, obviously, with the Kavanaugh confirmation, there's been a lot of talk about this lately. There's been some pretty interesting stuff. I've got two daughters, you have a daughter. Some pretty interesting stuff in our family chat that's been floating around. I saw, I think it was yesterday, my wife sent me a little ditty by a young woman who was singing a song about how tough it is for men, sort of tongue-in-cheek and singing things like, I can't open the door in my pajamas, I can't walk down the street on my phone at night, I can't leave my drink unattended, so tough for men, so tough for men, so on the one hand, you have the Me Too movement, you have a lot more, since Satya Nadella put his foot in his mouth at the Grace Opera event, I don't know if you saw that, he said-- >> I didn't. >> He said, a couple years ago >> He's the CEO of Microsoft. >> Said a couple years ago, a woman in the audience, Grace Opera, big conference for women, asked, "If we're underpaid, should we say anything?" and he said, no, that's bad kharma, you should wait and be patient, and then of course, he got a lot of you know what for that. >> That probably didn't work for them. And then, he apologized for it, he did the right thing. He said, you know what, I'm way off base and then he took proactive action. But, since then, you feel like there's been certainly much more attention paid to it, the Google debacle of last summer with the employee that wrote that Jerry Maguire tome. >> Right, right. >> Now the Me Too movement, then you see the reaction of women from the Kavanaugh appointment. Do you feel like we've made a lot of progress, but then you go, well, hmm, maybe we haven't. >> It sometimes feels like that. It sometimes feels like that. In my career, over 20 years, I have had a very positive experience working with men, women alike and have been very supported and I hope that we can continue to have the conversations and raise awareness, that everyone can feel good in their workplace, walking down the street and, like you mentioned, I think that it's very important that we all have a voice and all of us bring a different, unique perspective to the table. >> So do you feel that it's two steps forward, Dee, and maybe one step back every now and then, or are we making constant progress? >> It kind of feels like that right now. I'm not sure exactly why, but it seems like we're talking a lot about it more now and maybe just with a lot more attention on it, that's why it's seeming like we're taking a step back, but I think progress has been made and we have to continue to improve that. >> Yeah, I think if you strip out the politics of the Kavanaugh situation and then focus on the impact on women, I think you take a different perspective. I think that's a discussion that's worth having. On theCUBE last week, I interviewed somebody, she called herself, "I'm a Fixer," and I said, "You know, here's some adjectives I think of in a fixer, is a good listener, somebody who's a leader, somebody who's assertive, somebody who takes action quickly. Were those the adjectives that were described about you throughout your career, and the answer was, not always. Sometimes it was aggressive or right? >> True, true. >> That whole thing, when a woman takes swift action and is a leader, sometimes she's called derogatory names. When a man does it, he's seen as a great leader. So there's still that bias that you see out there, so two steps forward, one step back maybe. Well Dee, last thoughts on today and your mission. >> Well, we really hope to encourage the next generation to pursue math and science degrees, whether they are female or male or however they identify, and we want them to do great and hopefully have a great career in technology. >> I'm glad you mentioned that, 'cause it's not just about women, it's about people of color and however you identify. So, thanks very much for coming on theCUBE. We really appreciate it. >> You bet, thank you. >> Alright, keep it right there everybody. Back with our next guest right after this short break. We're live from Micron Insight 2018 from San Francisco. You're watching theCUBE. (techno music)

(lively music) >> Live from San Francisco, it's theCUBE covering Micron Insight 2018. Brought to you by Micron. >> Welcome back to San Francisco Bay everybody, we're here covering Micron Insight 2018. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with my cohost David Floyer. Sanjay Mehrotra is here, he's the president and CEO of Micron. Sanjay, thanks very much for coming on theCUBE. >> Great to be on the show. >> So quite an event here! First of all beautiful venue. >> Lovely venue. >> Got the Golden Gate that way, we got Nob Hill over there. So tell us about this event. It's not just about hardcore tech and memory. You guys are talking about AI for good, healthcare, changing the world. What's behind that? >> Yeah, our focus is on AI technologies and how AI is really changing the world. In terms of life, in terms of business, in terms of health. This is a showcase of how these technologies are in very very early innings, they've just barely begun. And what's happened is that AI algorithms have been around for a long time but now the compute capability and the memory and storage capability have advanced to the levels that you can really mine through a lot of data real-time, derive lot of insights and translate those insights into intelligence. And Micron plays a pivotal role here because our memory, our storage is where all this data resides, where all this data is processed. So we are very excited to bring together many industry figures, industry luminaries, park leaders, researchers, engineers all here today to engage in a dialogue on where technology is going, where AI is going, how it's shaping the world. And for the realization that hardware is absolutely central to this trend. And memory and storage is key. And we are very excited about what it means for the future. >> So a lot of thought leaders here today. Well first of all you guys have some hard news, which is relevant to what we're talking about. Talk about the hundred million dollar fund and how you've deployed it even just today you've made some sub-announcements. >> So, one of the things we announced today is we are launching a hundred million dollar fund to support, to fund start-ups in AI. Because we really think AI is going to transform the world. We want to be in the front row. With not only the large existing players that are driving this change but also the start-ups that will drive innovation. Having the front row seat with those start-ups, through our investment fund, will really help us accelerate intelligence, accelerate time to market of various AI applications. So a hundred million dollar fund is targeted toward supporting start-ups that are developing AI technologies. And what I'm really excited to talk about here is that 20% of that fund will go to start-ups that have leadership that is represented by women or under-represented groups. Under-represented--those groups that are under-represented in tech today. This demonstrates Micron's commitment to diversity and inclusion in the technologies phase. >> Well that's, well first of all congratulations on that we're big supporters >> Absolutely >> Of women and tech and diversity, it's something that we cover on the theCUBE extensively. And now you've announced two grants just today, a half a million dollars each. One with Stanford, one with Berkeley that we heard. We heard Amazon up on stage talking about Alexa AI, Microsoft was onstage we had NVIDIA on theCUBE earlier. So bringing together an ecosystem that involves academia, your partners, your customers, talk about that a little bit. >> So the two grants that you talked about, those are from Micron Foundation that is again supporting advancement of AI and AI research as well as teaching of AI to kids so that we can build the pipeline of strong engineers and technologists of the future. So the two grants that we have announced today are one to Stanford Precision Health and Integrated Diagnostics Center, 200,000 grant to Stanford, pioneers in AI applications to precision management of your health. Very exciting field that will really truly enrich life and prolong life in the future as well as advance detection of diseases. Second $200,000 grant that we are giving is to Berkeley. Artificial Intelligence Research Center, absolutely cutting-edge that will be applicable to many industries and many walks of life. These are intended to support advancement of AI research. In addition to this advanced curiosity grant to these two institutions later today you'll hear there will be announcing a $100,000 grant to AI4ALL. And this is an institution that is encouraging women and under-represented minorities at high school level, 9th grade to 11th grade to pursue STEM careers. So Micron is really promoting study of advanced research and supporting the pipeline. In addition to this of course our focus today is on bringing together industry luminaries just like you mentioned, NVIDIA, Qualcomm, autonomous driving of the future, automotive partners, BMW, Visteon, really to engage in a dialogue of how AI is advancing in these various applications. We just heard great talk from vice president at Amazon, on Alexa devices really really exciting how those devices are truly making your life so easy and so intelligent. We heard from Microsoft Corporate Vice-President of AI research. So you see we really are as leaders in our industry, we are really bringing together industry experts to engage in a thought-provoking and inspiring dialogue on AI so that when we leave here today we leave with insights into what is coming next but even more importantly what do we all need to do to get there faster, and this is all about technology. >> So Sanjay and David too, Micron is one of the few companies that was here when I started in the business and is still around. At the time you were just a component manufacturer doin' memories and wow to watch the diversification of Micron over the years but also recently, I mean it's incredibly well-run company so congratulations on the recent success. At the analyst event in New York City this year, you talked about not only that diversification in your investments and innovation but you talked about the cyclicality of this business the historical cyclicality of this business you've dampened that down a little bit, for a variety of reasons. The capital requirements in this business are enormous, there's been consolidation. So how is that going, talk about sort of the trends in your business both in terms of diversification and your ability to make this business more predictable. >> So Dave you are very right to know that Micron is 40 year old company, we actually just turned 40, very proud of it. Really a company founded on the principles of innovation and tenacity. In fact the company has contributed to the industry to the world over the course of 40 years, 40,000 patents, just imagine that's a thousand patents a year, three patents a day over the course of 40 years. We are really a prolific inventor and we absolutely through our innovations in memory and storage have shaped the world here. As technology advances it really unleashes more applications and this is what has brought about the change in our industry. Today memory is not just in your PC. Of course it is in this PC but it is also in your data center it is going to be in the autonomous records of the future you going to have as much memory as what you had in the server just a few years ago. It's inside your mobile phone Artificial Intelligence, facial recognition is only possible because of the data and memory that you have in there. You have NAND Flash that is in these devices and with technology advancing that's bringing down the price points of NAND Flash really bringing more SSD's into these notebook computers, making these notebook computers lighter, longer battery life, more powerful. And of course Flash drives are also replacing hard test drives in data centers and cloud computing. So many applications, these diverse applications really have brought greater stability in our industry. And of course technology complexity has over time moderated the supply growth. And that's what we mean that the cyclicality of our industry, yes one or two quarters here or there you can have demand and supply mismatches but overall when you look at the demand trends and combine them with the moderating supply trends the long-term trajectory for our industry is very healthy. In fact we just completed a record year. >> Our fiscal year '18 was a record 30 billion dollar year for us with profitability that puts us at the very top of the most companies with 50% operating margin and with 30 billion in revenue we are actually number two largest semiconductor company in the U.S. And a lot of opportunity ahead given the demand drivers in the industry. >> Massive free cash flow, you've said publicly the stock is undervalued which is ya know, I don't know any CEO that says it's overvalued but nonetheless the performance that you've had suggests that you very well might be right. Go ahead David please. >> Yeah I just wanted to ask your opinion on, you are leading in this area now, very very clearly you're growing faster than the industry, you've had a magnificent year and the whole area is grown both the NAND and the DRAM. How are you judging how much to invest in this for the future? What's the balance between giving money back to the stockholders by buying stock back or versus investing in this what seems to me a very very exciting area. >> Do you have an AI algorithm for that? (laughing) >> We are in a great position where we are extremely disciplined about investing in CapEx to reduce cost of production and to deploy new technologies into production. We are very ROI focused in terms of any CapEx investments we make. We of course invest in R and D. I mentioned earlier 40,000 patents over the course of 40 years that only comes in investment in R and D. Investments in R and D are essential because we are today the most comprehensive technology solutions provider in memory and storage in the world. >> Yeah. >> In the world. With our DRAM, our Flash, our 3D crosspoint technologies, as well as future emerging technologies really position us as the only company in the world that have all of these memory and storage technologies under one company roof. So we do invest very thoughtfully and we manage our expenses very carefully but we do invest in R and D and of course we are committed to driving shareholder value as well. And we had announced earlier in the year ten billion dollar share buy back program with at least 50% of a fee cash flow. Every quarter on an annual basis actually, 50% of our fee cash flow on an annual basis going, at least 50% going toward share buy back. So we are managing the business, all aspects of it, excitedly looking forward to the opportunities. At the same time prudently in an otherwise driven fashion, building shareholder value through investments in R and D and manufacturing. >> Well of course the great Warren Buffett, David, says when asked if stock buy backs are a good investment says if your stock's undervalued it's a good investment, so. Obviously you believe that Sanjay, so. >> Absolutely! >> So thanks, thanks very much for coming on the theCUBE it was great to have you. >> Thank you. >> I hope we can have you back again. >> Thank you. >> We could talk to you for a long long time. >> Thank you very much. >> Alright, keep it right there buddy, >> Thank you. >> We'll be back with our next guest. We're live from San Francisco Bay Micron Insight 2018. You're watching theCUBE. (upbeat music).

>> Live from San Francisco, it's theCUBE, covering Micron Insight 2018. Brought to you by Micron. >> Welcome back to San Francisco everybody. You're watching theCUBE the leader in live tech coverage. I'm Dave Vellante. He's David Floyer, and we're covering Micro Insight'18. It's all about bringing together artificial intelligence and the memory and storage requirements. We're here on the embarcadero. We've got treasure island that way. We've got the financial district over there. We've got Golden Gate bridge behind us. Tom Eby is here as senior vice president and GM of Micron's booming compute and networking business unit. Good to see you Tom. >> Great to be here. >> And Permal Savla is here. He's the director of deep learning at NVIDIA. Welcome. >> Thank you. >> So obviously some of these new emerging work loads require collaboration between folks like Micron and folks like NVIDIA. But Tom why don't you kick it off. What are some of the big trends that you're seeing in some of these alternative work loads that's driving this collaboration? >> Well a lot of what we're talking about here today is the drive of AI and machine learning work loads, and the implications for memory. Certainly there's a host of them, natural language processing, photo and image recognition, applications in medical research, applications in optimizing manufacturing like we're doing in our fabs, and there's many many more. And of course what's exciting for us is that to support those in an optimized way really does require the mating of the optimal processing architecture, things like GPUs. With the right high band width with low latency memory and storage solutions. That's what leads to great partner ships between partnerships like Micron and NVIDIA. >> David was explaining at our open the intensity of the work loads that you guys are serving, and how much more resources that requires to actually deliver the type of performance. Maybe you could talk about some of the things that you're seeing in terms of these emerging work loads. >> Yes, so at NVIDIA, we build systems for X rated computing. AI and deep learning is a very quickly expanding field at this point which needs a lot of CP horse power. What we are seeing is that different applications like you said there's image processing, whether it's video, whether it's natural language processing the amount of data that is there, that is required to do deep learning and AI around it, we break it up into two work flows. One is the training where you actually train the software, and make it intelligent enough to then go and do inference later on. So that you can go and get you results out of it at the end of it. We concentrate on this entire workflow. That's where when we are looking at it from a training perspective, the GPU gives it the processing power. But at the same time all the other components around it perform at the peak. That's where the memory comes in. That's where the storage comes in, and we need to process that data very quickly. >> Yeah, so we know from system's design that you got to have a balanced system or else you're just going to push the bottle necks around. We've learned that over the years, but so it's more than just slapping on a bunch of storage and a bunch of memory. You're doing some other deeper integration, is that correct and what is that integration? >> Yeah, I think the two companies have had a great relationship, just to talk about a couple examples. We essentially co-defined a technology called GEDR 5X, which greatly enhanced the speed of graphics technology. We gently introduced that to the marketplace with NVIDIA about 18 months ago. And then worked with them again very closely on a technology called GDDR six, which is the next generation of even faster technology. We were their launch and ran partner for their recently announced G-force RTX line of cards. It's a very deeply engaged early in the process, define the process, define the standards, jointly develop the solution. Very intimate sharing in the supply chain area. It's a great relationship for us. We're excited about how we can continue to expand and extend that relationship by going forward. >> So obviously there's the two parts of it. You said the learning part of it, and the inference part of the computing. What do you think is the difference between the two? I mean obviously at the end of the day, the inference part is critical. That's got to be the fastest response time. You have to have that in real time. Can you talk a little bit about what you're doing to really speed that up, to make that micro seconds as opposed to milliseconds? >> So from an NVIDIA perspective we build the entire end to end tools steps for training and inferencing. We have a set of libraries that we have made it openly available for all of our customers, all our partners, and all users. So that they can go download it, and do the training so they can use the different frameworks and libraries to accelerate the work that they're doing. And then transform it onto the inference spot. We have something called denser RT, which is basically denser real time. That gives the capability to get these answers very quickly. So on our D4 of the tuning, Chip said that we just announced. We can get a very high performance for our image. So any kind of image recognition or image processing that we need to do, we can do that on the systems very quickly. And we can meet, rebuild entire architectures. So it's not just about one piece. It's about the whole end to end architecture of the system. >> So we heard earlier today in the analyst briefing, the press briefing that Micron certainly in the last 40 years has changed. We're seeing a lot more diversity. Usually it'd be all about PCs. Now there's just so many alternative work loads emerging. Clearly NVIDIA is playing there as well with alternative processing capabilities. What do you guys see as some of the more exciting, emerging work loads that are going to require continued collaboration and innovation? >> Yeah, well I think to build a little bit on some of the other comments about the need for real time inference, one of the things in the area of diversity that we've found interesting. The relationship between Micron and NVIDIA in high performance memory really started around their graphics business. But we are seeing in other markets closer to the edge, in automotive, in networking and in other areas where there's a need for that real time performance. Yet there's also a need for a degree of cost effectiveness. Perhaps a little more so than in the data center. That we're seeing technologies like GDR six being applied to a much broader range of applications like automotive, like networking, like Edge AI, to provide the performance to get that real time response but in a form factor and at a cost point that's affordable for the application. >> Anything you'd add to that Permal? >> So I would also add you talked about applications, different applications that are changing right? Today we announced a new set of libraries and tools for the analytic space. That's again a big work load in the enterprise data centers, that we are trying to optimize and accelerate with machine learning. So we announced a whole set of tools which take in these large data sets that are coming in, and applying it in the data centers and using it to get answers very quickly. So that's what NVIDIA is also doing is expanding on these capabilities as we go in. And as these components and as these technologies get better it just gets our answers much more quickly. >> As exacts in the space and you guys both, you're component manufacturers, and so you sell to people who sell to end consumers. How do you get your information in that sort of pull through? Obviously you work with your customers very closely. >> Mm-hm. >> How do you get visibility to their customers? Just going to go to shows, you go do joint sales calls, how does that all work? >> Certainly some of that is in discussions with our customers and their marketing groups about what they're seeing from a customer point of view. But certainly there's other paths. One of the reasons behind the hundred million dollar venture fund that we announced today, is one of the best ways to get that advanced insight, is to be working with some of the most innovative start ups that understand what some of those end users needs might be and are developing some unique technologies. So there's a range. Working with our customers through eventually finding others, but it's important that we understand those needs because the lead time to developing the solutions both memory and processing architectures is quite well. >> Of course everybody wants to work with NVIDIA, you guys have an inundated like come on oh no we're the most. We're tied up now. Of course there's not a lot of choices here when you're talking about the levels of components that you're selling. But what's life like at NVIDIA? I mean they've been knocking down your doors to do partnerships. >> I think we've grown from being just the component to now being a complete system and an architecture. We don't only just build just a chip that the GPU was. We also build full SLCs. We also build the libraries, software, and the tools that are required to make this complete end to end solutions. We also do a lot of open source technologies because we want our customers and our end cast partners to build and take what we have and go beyond what it's capable of. That's where we end value at the end of the day. Yes, it's all of us together. We need to work together to make that much more faster as we go. >> The tuning is incredibly important. This is complicated stuff. It doesn't just work out of the box, right? So you need an ecosystem as well. >> Yes. >> Yes. >> That's what you guys have been out building. Tom, well give your final thoughts. >> Yeah well I guess to build a little bit. Certainly NVIDIA is moving up the stack in terms of the ecosystem, the software, the complete solution and I think Micron does as well. Like you commented, traditionally it was a component play. And increasingly, we're going to be building subsystems in memory and storage that occurs today on the storage side. I think we'll increasingly see that in memory, and with some of the future, very promising technologies like 30 Cross Point. >> Yeah it's the dawn of the days where everybody just gets piece parts and put them all together. They need you you guys to do more integration, and more out of the box like you say subsystems. So guys thanks very much for coming on theCUBE. Really appreciate it. >> Thank you. >> Thank you. >> Alright you're welcome, keep it right there everybody. We'll be back in San Francisco, you're watching theCUBE from Micron Insight 2018, accelerate intelligence. We'll be right back after this short break. (music)

>> Live from San Francisco, it's theCUBE, covering Micron Insight 2018. Brought to you by Micron. >> Welcome back to the Embarcadero everybody here in the heart of San Francisco. Actually at the bay of San Francisco. Golden Gate Bridge is that way, financial district over there, Nob Hill right up the street. You're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante, this is David Floyer, and we're covering the Micron Insight 2018 event. People are starting to filter in. Any minute now we're going to start the keynotes from the executives. A lot of buzz going on, Derek Dicker is here. He's the corporate vice-president and general manager of the storage business unit emerging activity within Micron, great to see you again. >> Thank you very much for having me. It's a pleasure to be here. >> You're very welcome, yeah, so Micron used to be just a straight memory company. We're hearing, we heard at the investor day in May how you guys are diversifying, finding new use cases, new applications, you run the storage business, and of course David Floyer was one of the first, the first, in my opinion, to predict the demise of the hard disk, spinning disk, and it's a tailwind for you guys, but Derek, take us through your business unit, your role, and let's get into it. >> Sure, that sounds great. I appreciate the opportunity again to be here. The storage business unit within Micron is actually comprised across a couple of product areas. Primarily NAND and NAND components, and then also SSDs, solid state drives. As we like to say, and we've talked a bit more about it since Sanjay's arrival, we have a pretty material focus on accelerating what we call high value solutions. It's a big focus of ours, so not only are we developing the core technology in memory and storage, but we're attempting to build more and more products that add value to our customers in the S-System space. But that's generally the storage business focus. Within the company, we have three other business units that focus on compute and networking memory as well as the embedded business unit and then the mobile business unit. >> Talk about some of the big trends that you see, I mean, we've talked about for years, the all-flash data center. We clearly see that in the customers that we work with. Some of the spinning disk guys don't necessarily fully buy into that, but even they have been investing in flash technologies. What are you seeing? >> I tell you, there is no better time, in my opinion, than to be in the memory and storage industry. When you look at what the trends are that are coming out in time. If you go and you stare at how memory and storage has evolved just going back into the 80s or the PC era, a $35 billion average size of the total market. You get into the mobile space, when mobile era started with smart phones, we were looking at a $62 billion-ish, and then in '17 we cleared $120 billion in size of the market, and we actually see a lot of secular trends that are going to continue to take us forward. A couple of things that are particularly noteworthy for us. The first one is the emergence of artificial intelligence, and machine learning, and deep learning. We're going to hear quite a bit about it here at the event. But in terms of a value driver for the consumption of both memory, DRAM, as well as storage, we see it going phenomenally up in content in every server that's purchased out in time. That's one, I think with the evolution of 5G out in time, we're also going to see that smart phone devices are going to end up having more memory to add features like facial recognition we see today, becoming mainstream, multiple cameras, that drives more DRAM content, but then also on top of that, storage is increasing. We're seeing, even today, a terabyte being put into some of the high-end phones, and we know that that's going to waterfall out in time. So I think if you look at this combination of what's happening both in the devices, you look at what's happening in the infrastructure, then you couple that with the processing that needs to happen, it's just an awesome time to be affiliated with memory and storage. >> Yeah, well, I've been following this LAN marketplace for the last, almost 10 years isn't it? More than that. And it's just broken through completely in the last two or three years. What are your thoughts about pushing compute closer and closer to that memory, adding to, for example, the SSDs, the capability of doing smart work? It's very very close to where the data is originally going to be placed? >> It's a great area of quite a bit of R&D work that's going on right now, and I actually think I view this as kind of two stages. One is there's the proliferation of solid state, as you suggested, it's been coming over time. I actually see it increasing dramatically as we look forward, and one of the key technologies that I think is going to enable that is QLC. The fact that we're now at a point where we're putting four bits per cell into devices, SSDs are starting to show up, I think that just creates even more opportunity. And I'll talk a little bit about that in just a minute, but I want to answer your direct question as to how that's changing with AnIML. But I think the ability, once solid state is prolific, to be able to architect systems where you can actually have processing take place closer to the media is a very interesting area. It's right with a ton of research going on right now. People are just starting to implement it. I think there's quite a bit of potential sitting behind it. You know, our focus, of course, is we're deploying, and as quickly as we can, on two vectors. One is, how do we proliferate more solid state into the market as an industry, and the second is how do we add value when we build those solid state drives, so I think it's definitely very viable. >> Let's talk about the significance of QLC. David, your forecasts early on were very aggressive in terms of pricing declines for flash. We kind of, maybe got caught off, a little bit surprised by the-- >> I think we were caught off by the demand. >> Well the demand, but also the supply constraints kept prices up. >> Yeah. >> Okay so, it didn't actually happen as fast. How does QLC change that, Derek, and what's the significance of it? >> Well, the thing that I think is most exciting for us as Micron is we actually ended up delivering the world's first QLC device. It put a terabit of data on a single die, which was unprecedented, but then in addition to that, what we did was we actually built a solid state drive called the 5210 ION. This is a standard drive. It's the worlds first SSD built on the technology, and by being able to develop a solution early on, it allowed us to go engage with customers and find where the right workloads were where we could add the most value. QLC technology actually is perfectly aligned for super read intensive, very read intensive environments, and if you look at what's happening in the data center, we're actually seeing more and more workloads move into more read intensive workloads, and a good chunk of that is just because there's analytics going on. The data's being collected. It's being housed in on place, but as we've talked about quite a bit here at the event, we want to be able to deliver insight out of that data, which means we're going to be reading it quite a bit, and massaging it, and performing analytics on it. And what we're now seeing is what, in the days of the past, was a four to one read to write ratio, we're seeing as high as 5,000 to one and in some cases a million to one. So we get these heavily read intensive workloads coupled with the technology that's optimized for it. It's more power efficient than what rotating media solutions offer in certain workloads, we're starting to see these tremendous values coming out of these early engagements that we're having with customers. >> And does that have implications for longevity, or do you just make an assumption that the read/write ratio is still going to be more write intensive in terms of wear leveling and things like that? How does it change the reliability, if you will, of the technology? >> Actually the beauty is, we're able to deliver an enterprise class SSD with these read/write capabilities that are affiliated with these read intensive solutions, and we can fit within the workloads and the needs that people are talking about. So the drive writes per day that are required in a machine learning infrastructure, we believe we can address with QLC. Same thing with Hadoop style clusters and Ceph clusters. We've actually, as we've gone out and engaged each of our earlier customers, we're able to crank out reference architecture documents that we're now posting to our websites, and we're describing how we can actually leverage this technology to allow us to, in some cases, we'll better optimize where an SSD was used before. But in many, many cases we're actually in the process of displacing hard disk drives. >> So what are the limits of this QLC? How many more bits can we add? How many more layers can we add? >> So, it's actually a great question, David. In terms of what does a roadmap look like. I've been asked in the recent several hours, what the longevity for NAND looks like. And what I'll tell you is this, QLC NAND is just getting its start. What comes after that in terms of bits per cell, I don't think anybody's made any broad claims on. But from a layer stacking perspective, which is kind of the dimension upon which the industry is growing, for the foreseeable future, we see nothing that encumbers us from going substantially higher and higher layer count. Which I think is going to be great for our industry because it's going to allow us to deliver more bits in a given device, and hopefully, that'll allow us to get into markets that, historically, we haven't been able to approach. If you think about the demand elasticity dynamic that occur when we start to bring more and more costs down, the number of applications open up, not unlike the machine learning workloads I just mentioned or Hadoop workloads. We're starting to see more and more thirst and interest for replacing with solid state, just because it's more power efficient, allows for a cost structure that's better, and gives better performance too. >> I'm fond of saying that data's plentiful, insights aren't. You guys are a $30 billion company now. You're making some interesting announcements today that we're going to hear about a little later on that I won't divulge right now, but you're putting your hands in a lot of different places. When you're that size of a company, you can't help but, as you mentioned before, adding more value, becoming more of a systems focus. How do you help the industry go from just raw data to insights? What's your role in that? >> Oh, it's a phenomenal question and this is a major focus of the company. Not just in our business unit, but across all of the different business units in the company. We have a huge focus on sitting down with our customers and getting closer and closer to understanding what their workload needs are, where their paying points are, and then working with them to find solutions, and the beautiful part about it is, as Micron, we're the only company in the world that can combine together a 3D XPoint set of technologies, a NAND set of technologies, a DRAM set of technologies. We go sit down and talk about these challenges with those in mind, plus the emerging memories that we're developing to go develop better and better solutions. But after we're able to come to a solution, we put together a reference architecture, and we deploy it broadly. >> We've been trying to squint through 3D Xpoint and understand the right fit. It seems to us that one of the big advantages of flash was it had the, had this behind it. (laughs) It had the consumer volumes, thank you Steve Jobs. It's unclear whether or not 3D Xpoint will have that, maybe have the same, sort of, cost advantages, but the same time, it sounds like there's new and emerging applications. Like I said, we're trying to figure out. Have you guys figured out yet? You're obviously betting big on the technology. Help us understand where the fit is. >> Sure, I think, you know, if I look back in time, just at the storage hierarchy alone, I don't think the memory hierarchy's any different. You have these portions of the market where you build out hard disk drives, and we had DRAM before, and SSDs came along, and people started asking, not unlike several years back when we talked about the early parts. Hey, how big is this going to get? Cost structures may be prohibitive. But as innovation unfurled, the more time and investment got placed into it, we found new workloads, new use cases we were able to drive costs out, and we ended up slotting in solid state drives squarely. I think this is another tier of memory and storage. That's the beauty of the 3D XP technology. There's both memory semantics and storage semantics that are available for use. I think we're still scratching the surface on the early days, but I love what we're seeing from the customer base that we're engaging and targeting in this space. >> And people will pay up for that performance capability relative to flash. They'll pay down relative to DRAM. Is it, are you seeing a gradience for like the hyperscalers, for example, or is it, maybe the industrial internet? Where are you seeing the. >> It's fair, actually I think, you know, it's probably reasonable to say that, you know, the challenges of inserting a new memory tier into a system requires new programming algorithms, new APIs and interface. There's a lot of ecosystem that needs to be there, as well as, not to mention, you've got to have an ecosystem to go put memory products into a server, for instance, or any other platform. I think we're still early days of enabling all of this. And I also believe we're going to learn more and more where the value of this sits as we put it out there in a cost effective fashion. So I would say that people who control software environments are very, very well suited for this because they can take advantage of some of those challenges without having to have a whole ecosystem in place. I think there's going to be a continued ramp in acceleration as an industry we go build out that ecosystem. >> Well it's been amazing to watch Micron the last several years, I mean, the last several decades. When you were just a pure memory manufacturer which was diversified, you know, gorilla in this space. (laughs) You guys are really an extremely well run company. I mean, your financials have born that out. You're really transparent to the street providing great guidance and congratulations on all of the success. I'm looking forward to watching in the future. >> Oh thank you so much. It's a privilege to be part of the company, and I really appreciate your time today. >> Our pleasure, thanks for coming on theCUBE. All right, keep it right there everybody. We'll be back with our next guest right after this short break. You're watching theCUBE from Micron Insight 2018. (upbeat techno music)

>> Live from Washington DC, it's theCUBE. Covering Inforum DC 2018. Brought to you by Infor. >> Well, welcome to the nation's capital, a rain soaked Washington DC. We're here for Inforum 18, Dave Vellante, John Walls We're in the Walter Washington Convention Center. The fourth time, theCUBE has been at an Infor show and getting bigger and better than ever, David. >> That's right John. This is, let's see, the first one was in New Orleans several years ago. Then Infor skipped a year, and then did Javits couple years in a row. That's sort of the headquarters of where Infor is, very close to the Javits Center. And Charles Phillips, of course, lives in New York City. And this year they decided to come to the nation's capital. I mean, Infor is an interesting company. About $3billion in revenue, essentially it is a private equity roll up. From Golden Gate and others, that really the roots of it are in Lawson Softwares. Some of you may remember Lawson Softwares, the enterprise software company. And then Charles Phillips came on, and of course he was the architect of Oracle's M and A. Probably spent $30 plus billion for Larry Ellison, remaking Oracle. Completely transforming Oracle, brought some of that expertise to Infor in this private equity play, this roll up. And then bought many, many software companies, rolled them up together and really started to compete, using a different model. So, Infor's sort of expertise, if you will is around so called Micro verticals, so they cover a lot of different industries, hospitality industries, they got also manufacturing, ERP, >> Retail financial >> Retail financial, health care, and then they also have horizontal applications like Human Capital management. Their differentiation, is several fold. One major point is they go after what they call the last mile. So they call this micro verticals. So the last mile functionality that would normally have to be customized, Infor does that work for you. Now, the advantage of that is two fold. One is you don't have to do a bunch of custom mods all that hard work is done. The second is, another part of the differentiation is cloud. So they chose, several years ago to go with AWS cloud to put their SaaS on the cloud. Charles Phillips said 'hey when we were an on-prem software company, we didn't manage our own servers for our customers. Or manage customer servers, we didn't do that. So why would we do it in the cloud? We don't want to compete with Google and Microsoft and Amazon in terms of scale, so were going to put our software on the Amazon cloud.' So that's another point of differentiation, the reason that is so important in the context of custom mods, is if you're rolling out new upgrades on a periodic basis, and you hear this a lot from Servicenow customers, for example another cloud software company. You can't do custom mods and then take advantage of the new releases. Because you're going to be way behind. Okay, so you have to have that hard work done so that you can avoid those custom modification. And that is something Infor has been very proud of. So as I say, $3billion company. Last year they took a $2billion investment from Koch industries. Now that investment, largely went to recapitalising the company, the private equity guys probably took some money off the table as did the four, what I call the four horsemen. They were the four, sort of new founders of Infor including Charles Phillips, Pam Murphey who is still there and then two others Duncan Angove and Stephan who have left the company, so they have got some succession planning now. We saw a different, two new faces up on stage Soma and we're going to have some other folks on that we'll introduce you to. But so, now we're entering a new phase and it's the phase of what Charles Phillip's coined 'Human Potentials'. So big focus this year on human capital management, we heard that. Big focus on AI, they talked a lot about robotic process automation. I just had a meeting, last night at the airport in DCA with the head of marketing at an RPA company, UiPath, they are smoking hot, they just raised 225 million they have gone from 2 million to 200 million over night. And that space is exploding, it was interesting to hear Charles Phillips talk a lot today about Robotic process automation, RPA. Which is essentially software >> Break that down for me. >> So RPA is software robots and software robots are used to automate mundane tasks. Having machines do very specific tasks and you are seeing this a lot in financial services and a lot of back office automation. It's not physical robots moving around, it's basically software based processes that machines can do. Repetitive processes, that machines can do better. Machines don't get tired, so they can do these repetitive tasks, take that away those mundane tasks away from humans. You heard a lot of conversation about that today. You also heard a little competitive fire. So Oracle is now taking ads out against Infor, we've seen that. All the cabs here, many of the cabs have Oracle branding on them. So Oracle is paying attention to Infor. >> And they're right down the road here too, by the way. You know, I mean, Western Virginia not far so this is their backyard. >> Well congratulations Infor, Oracle is paying attention to you that means, must mean you're hurting them We've seen this before with others, I mean we certainly saw it, you know in past days with IBM, we see it extensively with Workday. We've seen some kind of, tit for tat with SalesForce, even though SalesForce is one of Oracles largest customers. So that's been kind of fun, fun to watch. And now Infor, so Infor clearly is doing some damage, to the traditional guys. Oracle, SAP, Workday maybe not so much Workday is growing like crazy, but Infor claims it is growing SaaS revenue 50% faster than Oracle's SaaS revenue. It's growing double the rate of SAP, and growing as fast almost as Workday, is kind of what it claims. And so, this whole enterprise resource planning, HCM, vertical market software, horizontal software the market is always been hot. It's a huge, huge market. Many, many, tens of billions, it's probably a hundred billion dollar TAM. And the big, big whales are of course Oracle and SAP, and then of course, SalesForce and you've seen the emergence of companies like ServiceNow which has quite a bit of different strategy but with Oracle, with Infor's sort of Oracle heritage a lot of people in the company came from Oracle so they know where the skeletons are buried they know how to compete, they have relationships with the customers. And they're offering some differentiation, as they say with those Micro verticals, the last mile, and the pure cloud model. Now, if you look at the income statement you'll see the SaaS portion of the business only represents about 25% of the revenues but remember, that's a ratable model. So you're only recognizing revenue as you're, as the months go on, so you're billing sort of monthly if you will, or recognizing monthly. And so, as a result that skews and dampens the effects of the SaaS software, I think from a booking stand point is probably much higher, proportion of bookings I would guess closer to 50% as they said they took $2billion last year from Koch industries. That $2billion dollars didn't really hit the balance sheets, they get about $330million on the balance sheet. And they've a lot of debt, because they you know did you know, it was a private equity you know leverage deal. They did a lot of acquisitions, so they've probably got about $5.7billions of what they call net debt, which presumably is debt after cash. So I would guess close to $6billion in debt. They're a quasi, they're not a public company they're a private company, but they act in many ways like a public company, I would suspect within the next couple of years here, if this kind of growth continues that you'll see an IPO, from Infor. Although, presumably Koch industries, we heard Koch on stage today, they said they've made $15billion in investments in technology companies. $2billion, this has to be one of their largest. And, but that's patient capital. They get the benefit of the cash flow, they can probably take dividends if they want to do that. And if they're smart, and they invest and they can take market share from Oracle and SAP and others, and gain share in the market space, they can do an IPO. They're revenues are $3billion, their valuation, they implied a valuation based on the Koch industries investment is $15billion. So if they can take that $15billion to $30billion 20 to 30 billion, there's going to be a nice return. >> You know I thought, what's interesting about Koch too they talked about this, it's certainly as you talked about 2billion right. They put the money in, but they're also, it's a symbiotic relationship, in that that Koch is using it's organization as a test lab. For a lot of products and services, that Infor is producing. And allowing them to refine that under the Koch umbrella before they take it out to the market place. So that's pretty true, I feel like seems to makes sense. You have a company that has 60,000 world wide employees, you're in dozens of countries, you've a chance to let them take their products to scale, in maybe a somewhat more friendlier, controlled environment before you take it out to the marketplace. That seems to make a lot of sense. >> Yeah, we heard the CIO of Koch industries today and I talked to him last year, and we were talking about some of the technical debt that they had, again going back to those custom modifications that I was talking about earlier. They were in this terrible virtuous cycle almost a negative virtuous cycle where they had so many custom mods that they couldn't make changes. So the applications were becoming voxalised, so they were becoming non competitive and that is the last thing that a line of business wants to hear, is 'hey we can't make the changes, right IT says no, we can't touch the code, it's working or changes take too long. They take months or sometimes years, to get to a major release and so as a result Koch was looking for ways to simplify its application portfolio and its application infrastructure. The other thing that Koch industries has brought is, you might notice on the show floor here, you see Accenture, you see Deloitte, you're seeing Grant Thornton, now these guys weren't really going after, or going hard after the Infor base before. I think, a company like Koch industries does a lot of business with these SIs and so I think Koch has introduced the SIs to the Infor opportunity and maybe nudged them a little bit and say 'hey as a big you know supplier to us, we're a big customer of yours we want you to pay attention to that opportunity and in earnest go look at ways to partner with Infor. And that's happened, my intelligence suggests there are many multi million dollar deals that are being capitalized by these big SIs and they do a ton of business with SAP and Oracle. So that's another positive in the tail wind that Koch industries, I think it's brought to the table. >> Alright, you mention human potential which is the real overarching theme of the show here this week. Again, we're here in Washington DC. I was just listening to Van Jones from CNN. One of their anchors and political contributor talking about that as his personal mantra but certainly that intersects with what Infor is talking about in terms of unlocking human potential and using technology to do that. Share a little light from Charles Phillip's perspective the key note address that he gave, in terms of how do they view human potential and unlocking it with the use of their services? >> Well we're going to have Charles Phillip's on so we'll certainly ask him that but Charles Phillip's is a guy with a lot of potential. And that he is realizing that potential >> Lot of track record too >> Exactly, this is an individual with a military background, he became I don't know if you know the story but he became a highly successful Wall Street analyst. He wrote the seminal piece in the 90s that said the software industry, is too many software players and is going to consolidate. Larry Ellison, prior to reading that used to denigrate competitors for writing cheques not code. Meaning, his competitors were acquiring companies instead of innovating. Well then, he went on a spending spree probably 30, 35 million dollars in acquisitions orchestrated by Charles Phillips. And they totally remade Oracle starting with a soft hostile takeover. And then now you see Oracle, obviously this Saas powerhouse with many many companies that were bought in. Charles Phillips left Oracle, became the CEO of Infor and we heard today, architected an entirely new strategy with a stack, they call this thing the Stack. I'll just go through this briefly, I wrote about it last year, in the WikiBon blog. They've got the Infor platform, the Infor OS and then it goes all the way up to AI, the last mile software, the cloud. They have this thing called GT nexus, which is a supply chain network and that where their IoT play fits. Then they bought a company last year called Birst, to do BI and analytics, and then on top of that is Coleman. So they've got this stack that they are basically infusing into their applications, and I will answer your question. Essentially what they want to do is, use automation and artificial intelligence to essentially coach people, worker, as they're doing their jobs. So we heard today, that there are more openings than there are unemployed >> Employees, yeah. >> And productivity is going down. So Infor, Charles Phillips wants to attack that problem through software and automation. How do you do that? Well, if you could use artificial intelligence to monitor people's KPIs, they didn't use those terms but that is essentially what they are doing. And then provide feedback on outcomes, 'hey you could have done it differently. You could have done it more quickly. The outcome could have been better if.' Also, analyzing other factors like the relationship for example, using data to analyze the relationship between say tenure or were you recently promoted or turn over on the productivity of for instance stores, retail stores for example. And so, you're seeing an infusion of AI and software and automation in to the entire application portfolio to unlock the human potential. That's one part of it, the other part of it is Charles Phillips is big on diversity, big on women in business, and so that's another angle that I am sure we are going to hear more about this week. >> I thought it was interesting too any time a show comes to Washington there is a reason. And it's generally federal sector based, policy based. There's a regulatory undertone of some kind. And it was addressed somewhat on the key note stage here this morning. But the idea, the notion was that federal regulation and federal mandates, whatever, can't keep up the pace. They just can't, and it really is up to the tech sector because it works on a much different time frame, right? I mean, changes are made by the minute, whereas policy gets shaped by the year. You know, up on the hill here, not far about 3 miles 2 miles from here. So, the tech sector's responsibility in that regard in terms of being more diverse, of having more inclusivity, of looking at environmental considerations. All these things, and of unleashing human potential. And not at making a government do that. Not letting a regulation do that. That certainly plays in the Infor's thinking as well, I would think? >> Yes, so first of all we were down here at the AWS public sector event in June. And there were ten thousand people here. So AWS has a huge presence here. Infor and AWS are big time partners. And remember the CIA was the first deal, the first cloud deal, that AWS did, they won. IBM contested it, the judge eviscerated IBM in his ruling. Basically saying they were gaming the system. They were purposely misinterpreting the RFP. Amazon won hands down, it was a huge victory for Amazon. Forced IBM to go out and capitulate and purchase Softlayer for $2billion. I believe that only helps a company like Infor who has decided to be all public cloud, with AWS and drafting off AWS' deep ties to various government agencies, in the GovCloud. So for instance, AWS was first with fedramp. First with a lot of different certifications and security hurdles. And so Infor can just draft off of that. The CIA, again a big account, we heard the CIA talk in June about how security on the worst day of cloud is better than its client server applications on their best day. And so, I suspect Infor is doing business with the CIA although that's not come out publicly. But I would think that there is an advantage Infor has because of that AWS relationship. And that makes DC all the much more important for them. Well, we are at Inforum 18, we have a full 2 days of scheduling for you. Great guest coming up here on theCUBE. I am with Dave Vellante, I'm John Walls We'll continue here on theCUBE live from DC right after this break.

(upbeat digital music) >> Announcer: Live, from the Javits Center in New York City, it's theCube, covering Inforum 2017. Brought to you by Infor. >> Welcome to day two of theCube's live coverage of Inforum 2017 here in New York City at the Javits Center. I'm your host, Rebecca Knight, along with my co-hosts, Dave Vellante, and Jim Kobielus, who is the lead analyst at Wikibon for AI. So we're here in day two, fellas. We just heard the keynote. Any thoughts on what your expectations are for today, Jim, and what you're hoping to uncover, or at least get more insight on what we learned already in day one? >> I'd like to have Infor unpack a bit more of the Coleman announcement. I wrote a blog last night that I urge our listeners to check out on wikibon.com. There's a number of unanswered issues in terms of their strategy going forward to incorporate Coleman AI and their technology. You know, I suspect that Infor, like most companies, is working out that strategy as they go along, piece by piece, they've got a good framework then. We have Duncan Angove on right after this segment. Dave and I and you, we'll grill Duncan on that and much more, but that in particular. You know, I mean, AI is great. AI is everybody's secret sauce, now. There's a lot of substance behind what they're doing at Infor that sets them apart from their competitors in the ERP space. I want to go deeper there. >> So, yeah, so I'm looking at the blog right now. But what are the particular questions that you have regarding Coleman, in terms of how it's going to work? >> Yeah, well, first of all, I want to know, do they intend to incorporate Coleman AI in their premises-based software offerings? You know, for, I'm sure the vast majority of their customers want to know when, if ever, they're going to get access to Coleman, number one. Number two is, when are they going to complete the process of incorporating Coleman in their CloudSuite portfolio, which is vast and detailed? And then, really number three, are they going to do all the R&D themselves? I mean, they've got AWS as a major partner. AWS has significant intellectual property in AI. Will they call on others to work with them on co-developing these capabilities? You know, those are, like, the high-level things that I want to get out of today. >> Rebecca: Okay, okay. >> Well, so a couple things. So, I mean, the keynote today was okay. It wasn't, like, mind-blowing. We had customer appreciation, which was great. Alexis, who is from Foot Locker, cube alum was up there, and B of A got customer of the year. I met those guys last night at one of the customer appreciation dinners, so that was kind of cool. They all got plaques, or you know, that's nice, little trophies. I heard a lot about design thinking, and they shared some screen shots, essentially, of this new UI, started talking about AI is the new UI. It was very reminiscent of the conversation that we had in May at the ServiceNow Knowledge conference, where they're bringing consumer-like experience to the enterprise. It's always been something that ServiceNow has focused on, and certainly, Charles Phillips and Hook and Loop have been focused on that. The difference is, quite frankly, that ServiceNow showed an actual demo, got a lot of claps as a result. Infor said this is ready to be tested and downloaded, but they didn't show any demo. So that was sort of like, hmm. >> Jim: They haven't shown any demos. >> Rebecca: Yeah. >> Is it really baked out? Steve Lucas was up there. He killed it, very high energy guy. You know, again, another cube alum. He's been in our studio, and he's an awesome dude. >> Jim: He's awesome. >> And I thought he did a really good job. >> From Marketo. >> Talking about, you know, the whole engagement economy, you know, we think it's going a little bit beyond engagement to more action, and systems of an action, I think, is a term you guys use. >> Systems of agency or enablement, yeah. Bringing more of the IoT into it and robotics and so forth, yeah. >> And then DSW was up there. I said yesterday, "I love DSW." I tweeted out that, you know, the CIO had a picture, Ashlee had a picture of DSW, and I said, "Okay, when the girls and I go to DSW, "I break left, they go middle-right, "we meet at the checkout to negotiate "what actually goes home," so that was good. It was kind of fun. And then a lot of talk about digital transformation. Marc Scibelli was talking about that, and IoT and AI and data. So that's sort of, you know, kind of a summary there. As you know, Rebecca, I've been kind of trying to make the math work on the $2-plus billion investment from Koch. >> Rebecca: Yes, this is your-- >> And the messaging that Infor is putting forth is this is a source of new capital for us, but I'm-- >> Rebecca: You're skeptical. >> You know, as a private company, they have the right not to divulge everything, and they're not on a 90-day shot clock. Charles Phillips, I think, said yesterday, "We're on a 10-year shot clock." I said, "Okay." I think what happened is, so I found, I scanned 10-Qs, and I've been doing so for the last couple of days. There is virtually no information about how much, exactly, of the cash went in and what they're doing with it. And so, I suspect, but there are references to Golden Gate Capital and some of the management team taking some money off the table. Cool, that's good. I'm just, it's unclear to me that there's any debt being retired. I think there is none. And it's unclear to me how much cash there is for the business, so the only reference I was able to find, believe it or not, was on Wikipedia, and it says, "Citation still needed," okay? And the number here, and the math works, is $2.68 billion for 66.6% of the company, and a valuation of $10 billion, which Charles Phillips told us off-camera yesterday, it was $10.5 billion. So you can actually make the math work if you take that $10 billion and subtract off the $6 billion in debt. Then the numbers work, and they get five out of 11 board seats, so they've got about 45% or 49%, I think, is the actual number, you know, voting control of the company. So here's the question. What's next? And now, a couple billion for Koch is nothing. It's like the money in my pocket, I mean, it's really-- >> Rebecca: Right, right, right, the empty, yeah, exactly. >> And I suspect what happened is, 'cause it always says "$2 billion plus." So in squinting through this, my guess is, this is a pure guess, we'll try to confirm this, is that what happened is, Koch provided the additional funding to buy Birst recently. That upped their share to 66%, and maybe that's how Koch is going to operate going forward. When they see opportunities to help invest, they're going to do that. Now, one might say, "Well, that's going to further dilute "the existing Infor shareholders," but who cares, as long as the valuation goes up? And that's the new model of private equity. The old model of private equity is suck as much cash out of the company as possible and leave the carcass for somebody else to deal with. The new model of private equity is to invest selectively, use, essentially, what is a zero-interest loan, that $6 billion debt is like free money for Infor, pay down that debt over time with the cashflow of the company, and then raise the valuation of the company, and then at some point, have some kind of public market exit, and everybody's happy and makes a ton of dough. So, I think that's the new private equity play, and I think it's quite brilliant, actually, but there's not a lot of information. So a lot of this, have to be careful, is speculation on my part. >> Right, right. >> Well, the thing is, will the Coleman plan, initiative raise the valuation of the company in the long term if it's, you know, an attrition war in ERP, and they've got SAP, Oracle, Microsoft, all of whom have deep pockets, deeper than Infor, investing heavily in this stuff? Will Coleman be a net-net, just table stays? >> Well, so I think again, there's a couple ways in the tech business, as you guys know, to make money, and one is to invest in R&D and translate that R&D into commercial products. Some companies are really good at that, some companies aren't so good at that. The other way to make money is to do acquisitions and tuck-ins, and many, many companies have built value doing that, certainly Oracle, certainly IBM has, EMC back in the day, with its VMware acquisition, hit probably the biggest home run ever, and Infor has done a very good job of M&A, and I think, clearly, has raised the value of the company. And the other way is to resell technologies and generate cash and keep your costs low. I think a software company like Infor has the opportunity to innovate, to do tuck-in acquisitions, and to drive software marginal economics, so I think, on paper, that's all good, if, to answer your question, they can differentiate. And their differentiation is the way in which they're embedding AI into their deep, vertical, last-mile approach, and that is unique in the software business. Now, the other big question you have is beautiful UIs, and it sounds really great and looks really great, well, when you talk to the customers, they say, "Yeah, it's a little tough to implement sometimes," so it's still ERP, and ERP is complicated, alright? So, you know, it's not like Infor is shielded from some of the complexities of Oracle and SAP. It might look prettier, they might be moving a little faster in certain areas, they might, they clearly have some differentiation. At the end of the day, it's still complicated enterprise software. >> Right, exactly, and we heard that over and over again from the people, from Infor themselves, and also from customers, is that it isn't seamless. It's complicated, it involves a lot of change management initiatives, people have to be on board, and that's not always easy. >> Well, and that's why I'm encouraged, that to see some of the larger SIs, you know, you see Grant Thornton, Capgemini, I think Accenture's here, Deloitte-- >> Rebecca: We're having Capgemini later on the program. >> Deloitte's coming on as well. And so, those guys, even though I always joke they love to eat at the trough and do big, complex things, but, this is maybe not as lucrative as some of the other businesses, but it's clearly a company with momentum, and some tailwind that, in the context of digital transformations and AI, the big SIs and some of the smaller SIs, you know, like Avaap, that we had on yesterday, can do pretty well and actually help companies and customers add value. >> And with a fellow like Charles Phillips at the helm, I mean, he is just an impressive person who, as you have pointed out multiple times, is a real visionary when it comes to this stuff. >> Yeah, except when he's shooting hoops. He's not impressive on the hoop court, no. >> No? Oh! (laughing) >> I tweeted out last night, "He's got Obama's physique, "but not his hoop game." >> Oh! (laughing) >> So don't hate me for saying that, Charles. But yes, I think he's, first of all, he's a software industry guru. I think he, you know, single-handedly changed, I shouldn't say that, single-handedly, but he catalyzed the major change in the software business when Oracle went on its acquisition spree, and he architected that whole thing. It was interesting to hear his comments yesterday about what he sees. He said, "You'll see a lot more tech industry "CEOs running non-tech-industry companies "because they're all becoming SAS companies." >> If they have been so invested in understanding the vertical, they really get it. You can see someone who worked on a retail vertical here going in and being the CEO of Target or Walmart or something. >> Yes, I thought that was a pretty interesting comment from somebody who's got some chops in that business, and again, very impressive, I mean, the acquisitions that this company has done and continues to do. You and I both like the Birst acquisition. It's modern-day BI, it's not sort of just viz, and I don't mean to deposition Clik and Tableau, they've done a great job, you know, but it's not, it doesn't solve all your enterprise-grade, BI sort of problems. And, you know, you talk to the Cognos customer base, as great of an acquisition as that was for IBM, that is a big, chewy, heavy lift that IBM is trying to inject Watson and Watson Analytics. I mean, you know, you used to work at IBM, Jim. And they're doing a pretty good job of that, improving the UI, but it's still big, chunky, Cognos BI. Build cubes, wait for results. >> Yeah. So in many ways, the Birst acquisition for Infor and their portfolio is a bit like the thematics that IBM's been putting out on HTAP, you know, injecting analytics into transactional processing to make them more agile, and so forth. What I like about the Birst acquisition, vis-a-vis Coleman and where Infor is going, is that the Birst acquisition gives them a really good team, the people who really know analytics and how to drive it into transactional environments such as this. They've got, I mean, ostensibly, a deep fund of capital to fund the Coleman development going forward. Plus, they've got a really strong plan. I think there's potential strong differentiators for Infor, far more comprehensive in their plan to incorporate AI across their portfolio than SAP or Oracle or Microsoft have put out there in public, so I think they're in a good position for growth and innovation. >> Well, we have a lot of great guests coming up today. As you said, Duncan Angove is going to be on, up next. So, I'm Rebecca Knight, for Dave Vellante and Jim Kobielus, we will have more from Inforum just after this. (digital music) (pensive electronic music)

>> Announcer: Live from the Javits Center in New York City, it's theCUBE! Covering Inforum 2017. Brought to you by Inforum. >> Welcome to day one of theCUBE's coverage of Inforum here at the Javits Center in New York City. I'm your host, Rebecca Knight, along with my co-host, Dave Vellante. We are also joined by Jim Kobielus, who is the lead analyst for artificial intelligence at Wikibon. Thanks so much. It's exciting to be here, day one. >> Yeah, good to see you again, Rebecca. Really, our first time, we really worked a little bit at Red Hat Summit. >> Exactly, first time on the desk together. >> It's our very first time. I first met you a little while ago, and already you're an old friend. >> This is the third time we've done Inforum. The first time we did it was in New Orleans, and then Infor decided to skip a year. And then, last year, they decided to have it in the middle of July, which is kind of a strange time to have a show, but there are a lot of people here. I don't know what the number is, but it looks like several thousand, maybe as many as 4000 to 5000. I don't know what you saw. >> Rebecca: No, no, I feel like this is a big show. >> Jim: Heck, for July? For any month, actually. >> Exactly, particularly at a time where we're having a lot of rail issues, issues at LaGuardia too, so it's exciting. >> theCUBE first met Infor at the second Amazon re:Invent. I remember the folks at Amazon told us, "We really have an exciting SAS company. "It's the largest privately-held SAS company in the world." We were thinking, is that SAS? And they said, "No, no, it's a company called Infor." We said, "Who the heck is Infor?" And then we had Pam Murphy on. That's when we first were introduced to the company, and then, of course, we were invited to come to New Orleans. At the time, the questions around Infor were, who is Infor? What are they all about? And then it became, okay, we started to understand the strategy a little bit. For those of you who don't familiar with Infor, their strategy from early on was to really focus on the micro-verticals. We've talked about that a little bit. Just a quick bit of history. Charles Phillips, former president of Oracle, orchestrator of the M&A at Oracle, PeopleSoft, Siebel and many others, left, started Infor to roll up, gold-funded by Golden Gate Capital and other private equity, substantial base of Lawson Software customers, and then, many, many other acquisitions. Today, fast forward, you got a basically almost $3 billion company with a ton of debt, about $5 billion in debt, notwithstanding the Koch brothers' investment, which is almost $2.5 billion, which was to retire some of the equity that Golden Gate had, some of the owners, Charles and the three other owners took some money off the table, but the substantial amount of the investment goes into running the company. Here's what's interesting. Koch got a 2/3 stake in the company, but a 49% voting share, which implies a valuation of about, I want to say, just under four billion. Let's call it 3.7, 3.8 billion. For a $2 billion to $3 billion company, that's not a software company with 28% operating margin. That's not a huge valuation. So, we'll ask Charles Phillips about that, I mean, some of this wonky stuff in the financials, you know, we want to get through. I'm sure Infor doesn't want to talk too much about that. >> But it is true. It is, for a unicorn, for a privately-held company, this is one of them. This is up there with Uber and Airbnb, and it's a question that, why isn't it valued at more? >> My only assumption here is they went to Koch and said, "Okay, here's the deal. "We want $2 billion plus. "You only get 49%, only. "If you get 49% of the company in terms of voting rights, "we'll give you 2/3 in terms of ownership. "It's a sweetheart deal. "Of course, it's a lot of dough. "You get a board seat." Maybe two board seats, I can't remember. "And we'll pump this thing up, we'll build up the equity, "and we'll float it someday in the public markets, "and we'll all make a bunch of dough "and our shareholders will all be happy." That's the only thing I can assume, was this sort of conversation that went on. Well, again, we'll ask Charles Phillips, see if he answers that. But James, you sat in yesterday at the analyst event, you got sort of the history of the company, and the fire hose of information leading up to what was announced today, Coleman AI. What were your impressions as an analyst? >> Well, first of all, my first impression was a thought, a question. Is Infor with Coleman AI simply playing catch-up in a very, I call it a war of attrition in the ERP space. Really, it's four companies now. It's SAP, it's Microsoft, it's Oracle, and it's Infor duking it out. SAP, Microsoft and Oracle all have fairly strong AI capabilities and strategies and investments, and clearly they're infused, I was at Microsoft Build a few months ago. They're infusing those capabilities into all of their offerings. With Coleman, sounds impressive, thought it's just an early announcement, they've only begun to trickle it out to their vast suite. I want to get a sense, and probably later today we'll talk to Mr. Angove, Duncan Angove. I want to get a sense for how does, or does, Infor intend to differentiate their suite in this fiercely competitive ERP world? How will Coleman enable them to differentiate it? Right now it seems like everything they're announcing about Coleman is great in terms of digital assistance, conversational interface, everybody does this, too, now, with chatbots and so forth, in-line providing recommendations. Everybody's doing that. Essentially, everybody wants to go there. How are they going to stand apart with those capabilities, number one? Number two is just the timeline. They have this vast suite, and we just came from the keynote, where Charles and the other execs laid out in minute detail the micro-vertical applications. What is their timeline for rolling out those Coleman capabilities throughout the suite so customers can realize they have value? And is there a layered implementation? They talked about augmentation versus automation, and versus assistance. I'd like to see sort of a layer of capabilities in an architecture with a sense for how they're going to invest in each of those capabilities. For example, they talked about open source, like with TensorFlow, which is a new deep learning framework from Google Open Source. I just want to get a deep dive into where the investment funds that they're getting from Koch and others, especially from Koch, where that's going in terms of driving innovation going forward in their portfolio. I'm not cynical about it, I think they're doing some really interesting things. But I want some more meat on the bones of their strategy. >> Well, it's interesting, because I think Infor came into the show wanting to message innovation. They're not known as an innovative company. But you heard Charles Phillips up there talking, today he was talking about quantum computing, he was talking about the end of Moore's Law, he was obviously talking about AI. They named Coleman after Katherine Coleman Johnson. >> Here's my speculation. My speculation, of course, they recently completed the acquisition of Birst. Brad Peters did a really good discussion of Birst, the BI startup that's come along real fast. My sense, and I want to get confirmation, is that, possibly, Birst and Brad Peters and his team, will they drive the Coleman strategy going forward? It seems likely, 'cause Birst has some AI assets that Brad Peters brought us up to speed on yesterday. I want to get a sense for how Birst's AI and Coleman AI are going to come together into a convergence. >> But wouldn't they say that it's quote-unquote embedded, embedded AI? >> Jim: It'll be invisible, it has to be. >> You know, buried within the software suite? We saw, like you said, in gory detail the application portfolio that Infor had. I think one of the challenges the company has, it's like some of my staff meetings. Not everything is relevant to everybody. Very clearly, they have a lot of capabilities that most people aren't aware of. The question is, how much can they embed AI across those, and where are the use cases, and what's the value? And it's early days, right? >> Oh, yeah, very much. And you know, in some of those applications, probably many of them, the automation capabilities that they described for Coleman will be just as important as the human augmentation capabilities. In other words, micro-verticalize their AI in diverse ways going forward across their portfolio. In other words, one AI brush, broad brush of AI across every application probably won't make sense. The applications are quite different. >> I want to talk about the use cases, here. The selling points for these things are making the right decision all the time, more quickly. >> Jim: Productivity accelerators for knowledge workers, all that. >> And one of the other points that was made is that there are fewer arguments, because we are all looking at the same data, and we trust the data. Where do you see Birst and Coleman? Give me an example of where you can see this potentially transforming the industry? >> "We all trust data." Actually, we don't all trust data, because not all data is created the same. Birst comes into the portfolio not just to, really great visualizations and dashboarding and so forth, but they've got a well-built data management backend for data governance and so forth, to cleanse the data. 'Cause if you have dirty data, you can't derive high-quality decisions from the data. >> Rebecca: Excellent point, right. >> That's really my general take on where it's going. In terms of the Birst, I think the Birst acquisition will become pivotal in terms of them taking their data-driven functionality to the next level of consumability, 'cause Birst has done a really good job of making their capability consumable for the general knowledge worker audience. >> Well, a couple things. Actually, let me frame. Charles Phillips, I thought, did a good job framing the strategy. Sort of his strategy stack, if you will, starting with, at the bottom of the stack, the micro-verticals strategy, and then moving up the next layer was their decision to go all cloud, AWS Cloud. The third was the network. Infor made an acquisition of a company called GT Nexus, which is a commerce platform that has 18 years of commerce data and transaction data there. And the next layer was analytics, which is Birst, and I'll come back to that. And then the top layer is Coleman AI. The Birst piece is interesting, because we saw the ascendancy of Tableau and its land-and-expand strategy, and Christian Chabot, the CEO of Tableau, used to talk about, and they said this yesterday, the slow BI, you know, cubes, and the life cycle of actually getting an answer. By the time you get the answer, the market has changed. And that's what Tableau went after, and Tableau did very, very, well. But it turned out Tableau was largely a desktop tool. Wasn't available in the Cloud. It is now. And it had its limitations. It was basically a visualization tool. What Infor has done with Birst is they're positioning the old Cognos, which is now IBM, and the micro strategies of the world as the old guard. They're depositioning Tableau, and they didn't use that specific name, Tableau, but that's what they're talking about, Tableau and Click, as less than functional. Sort of spreadsheet plus. And they are now the rich, robust platform that both scales and has visualization, and has all the connections into the enterprise software world. So I thought it was interesting positioning. Would love to talk to some customers and see what that really looks like. But that, essentially, was the strategy stack that Charles Phillips laid out. I guess the last point I'd make as I come back to the decision to go AWS, you saw the application portfolio. Those are hardcore enterprise apps which everybody says don't live in the Cloud. Well, 55% of Infor's revenue is from the Cloud, so, clearly, it's not true. A lot of these apps are becoming cloud-enabled. >> Jim: Yeah, most of them. >> Most of them? >> Most of them are, yeah. BI, mode-predictive analytics, most AI. Machine learning is going in the Cloud. >> 'Cause Oracle's argument is, Oracle will be only one who can put those apps in the Cloud. >> 'Cause the data lives in the Cloud. It's trained on the data. >> Not all the data lives in the Cloud. >> It's like GT Nexus. That's EDI, that's rich EDI data, as they've indicated for training this new generation of neutral networks, machine learning and deep learning models continuously from fresh transaction data. You know that's where GT Nexus and e-commerce network fits into this overall strategy. It's a massive pile stream of data for mining. >> But, you know, SAP has struggled in the Cloud. SuccessFactors, obviously, is their SAS play. Most of their stuff remains on-prem. Oracle again claims they have the only end-to-end hybrid. You see Microsoft finally shipping Azure Stack, or at least claiming to soon be shipping Azure Stack. They've obviously got a strategy there with their productivity estate. But here you have Infor-- >> Don't forget IBM. They've got a very rich, high-rated portfolio. >> Well, you heard, I don't know if it was Charles, somebody took a swipe at IBM today, saying that the company's competitors have purchased all these companies, these SAS companies, and they don't have a way to really stitch them together. Well, that's not totally true. Bluemix is IBM's way. Although, that's been a heavy lift. We saw with Oracle Fusion, it took over a decade and they're still working on that. So, Infor, again, I want to talk to customers and find out, okay, how much of this claim that everything's seamless in the Cloud is actually true? I think, obviously, a large portion of the install base is still that legacy on-prem Lawson base that hasn't modernized. That's always, in my view, enforced big challenges. How do you get that base, leverage that install base to move, and then attract new customers? By all accounts, they're doing a pretty good job of it. >> I don't think what's going on, I don't think a lot of lift-and-shift is going on. Legacy Lawson customers are not moving in droves to the Cloud with their data and all that. There's not a massive lift-and-shift. It's all the new greenfield applications for these new use cases, in terms of predictive analytics. They're being born and living their entire lives in the Cloud. >> And a lot of HR, a lot of HCM, obviously, competing with Workday and Peoplesoft. That stuff's going into the Cloud. We're going to be unpacking this all day today, and tomorrow. Two days here of coverage. >> Indeed, yes indeed. >> Dave: Excited to be here. >> It's going to be a great show. Bruno Mars is performing the final day. >> Jim: Bruno Mars? >> I know, very-- >> You know a company's doing good, Infor, when they can pay for the likes of a Bruno Mars, who's still having mega hits on the radio. I wish I was staying long enough to catch that one. >> I know, indeed, indeed. Well, for Dave and Jim, I'm Rebecca Knight, and we'll be back with more from Inforum 2017 just after this. (fast techno music)