(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)

(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)

>> 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)