(upbeat techno) >> Announcer: Live, from Las Vegas, it's theCUBE. Covering NetApp Insight 2017. Brought to you by, NetApp. >> Hello, everyone, welcome back to our Cube coverage, exclusive coverage here at the NetApp Insight 2017. This is theCUBE, I'm John Furrier, the co-host, co-founder of the SiliconANGLE Keith Townsend CTO advisor here in Las Vegas, Nevada at the Mandalay Bay, our next guest is Jennifer Meyer, senior director cloud product marketing, and Ingo Fuchs who's the senior manager cloud product marketing. You guys are doing a lot of the heavy lifting on the front lines for NetApp on the cloud, welcome to theCUBE, good to see you. >> Thank you so much for having us. >> Okay, so, we've been covering it, but now it's pretty clear there's a cloud play, there is a cloud play for Netapp, you guys are showing product, lot of products in the keynotes, both in the data center in the next generation but the cloud's the big part of the story, it's certainly we hear resonating with customers, and all the guests that have come up on the A teams, and your partner channels, all are like this is really, really great thing. >> Yeah, I think -- >> Part of the plan? >> Absolutely part of the plan, I mean if you caught any of the latest messaging which, you know, Jean and the team have worked really hard on, it's all about us being the data authority and the hybrid cloud, right, and so, if you think about, let's unpack hybrid cloud, there's only about 1% of the population of the planet that's not adopting cloud in some way, and we believe that after the last 25 years of our history in data management and our leadership with things like ONTAP that we are well-equipped to help people get there, how they want to get there and with what, right. >> And you have an install base too, so you've been selling boxes, everyone knows you for selling, that's an old term but I'm showing my age, (Jennifer laughs) hardware, but hardware's not going away either, Amazon makes their own stuff too, so you got to still store stuff, so storage will be there, servers will be there, hyperconverging, all that's happening under the hood, but the software's where the value is, certainly, you know, we have expression at SiliconANGLE, software's eating the world as Mark Andreesen said, but data's eating software, Anthony, your general manager came on and said, you know, data is trumping applications, used to be applications had data, now data has applications. >> Right. >> So that flips things, upside-down, and you guys got to go build that market out for your customers. How do your customers at NetApp, and prospective customers, new customers, NetNew, engage with NetApp and what's the positioning, what's the value? >> Yeah, there are a lot of different ways to do it. So if you're an existing NetApp customer today, a really really easy way to get into the cloud, so we have one of our product called ONTAP Cloud, it's our storage operating system, the number one operating system in the world, running inside Azure and AWS hyperscalers so you use all the same tools, all the same mechanisms that you would use on premises, but you're now running in the cloud, so that makes it really easy to lift and shift applications that are using NFS or CIFS or iSCSI protocols, straight into the cloud, because you have the same storage operating system that you have on premises, you have datafication, you have snapshot, you have cloning, you have all of the advantages of data management infrastructure that has been developed over the last 25 years. >> So some of the push-back that I've seen is that, yeah, you have the tooling, but isn't the cloud all about the new? Can you actually build new apps with on, using ONTAP and Microsoft Azure NFS, can you talk to us a little bit about the story, about not just bringing your legacy tools, quote unquote, but also, the new capabilities that developers will find as a result of the cloud offerings. >> Yeah, absolutely, I think in my opinion the most exciting announcement this week, and others may argue differently -- >> You're a little biased. >> You're a little bit, yeah. >> I'm a little bit biased, because you know, >> We'll take it with a grain of salt. >> It's my baby so I do care about it, is that we, that Microsoft announced, and that we announced that we are the technology provider for Microsoft launching an Enterprise-class NFS service natively in Azure. Now, if you think about that, if it runs natively in Azure, it sits right next to the infrastructure that is processing HDInsight, that's running SQL server, Microsoft announced that they are having SQL running on Linux, so suddenly having an Enterprise cloud very very fast, high performance, managed by NetApp NFS service running natively in Azure opens up the opportunities to do IoT, run your Enterprise databases against this infrastructure and really opening up the door for customers to do more. And because you're using tools like HDInsight, you can run analytics, you can now expand into AI, into machine learning, all of that is now open to people that are cloud-native, and cloud natives don't want to go back and learn how to manage a storage infrastructure, that's not a good use of their time, so something like the NFS service in Azure, you don't have to learn how to do storage, all you do is go to the portal, you provision it, you click on it, it's running, it's done. >> I think that's a really important point, because everybody just hears it's a new native or first-party service in Azure, which frankly is industry-first. I mean, nobody, especially from the storage provider standpoint is doing that today, but I think the ability to get all those Enterprise-class services without it feeling like a prostate exam is probably a first for everybody. (men laughing) >> Probably you get, you get put under for that these days, but I mean, my point is, the multi-cloud thing's interesting to me, and I think you guys have hit on something with the Cloud Orchestrator product we saw on stage, the demo, is that multi-cloud, customers don't want to be locked in. >> That's right. >> That's the number one thing we hear in theCUBE, and the suppliers, whoa, we don't lock in, now open-source has been growing, that's great, but you know, the new lock-in as we still call it, is functionality, are you helping customers scale up and scale out at the same time, so the question for you is, how far along is that cloud orchestrator, and is that the guiding principle of the cloud group to seamlessly, first of all the cloud orchestrator allows you to move data around just by clicking buttons, so it takes away all the under-the-covers work that's needed. >> That's right. >> 'Cause each cloud has its own architecture. >> That's right. >> How they do things. So, that's a value quotient I think will be a home run. >> It is, and a big priority for NetApp and specifically in our cloud business unit and our cloud marketing is to make sure that people feel like they have the freedom to choose where they want to go and how, right, and so think about it like a compass, a compass still needs you to pick the destination, and it tells you the best way to get there. That's really sort of what we're trying to do and the orchestrator is just a very flexible way to help people do it, even at the API level. >> Alright, so for all the naysayers out there that are, oh NetApp, they're just cloud washing, they're not really in the cloud game, what does this mean, how do you put that to rest, 'cause I know you've been involved in Amazon for some time, now with the Microsoft deal pretty significant, what do you say to the naysayers or customers that might learn for the first time wow, good story there, or there's a path to the cloud. >> You know, we joked one time we should have an entire marketing campaign that said, oh, I didn't know NetApp did that, because there are so many things, even me, being fairly new to NetApp that I didn't even know we were doing, let alone how long we were doing them for, so it might shock some people to know that we've been doing the ONTAP cloud product for four years, I mean four years, and that product frankly was born out of our own need to abstract the software and test it on our own for TestApp, right, >> Well Jean's in town so she's a good marketer so she should do a good job of changing the marketing angle, but the tell sign to me at events is on keynotes, right, this is to me the relevance barometer, I think Amazon has really nailed this, they have so many announcements they can't even keep track of them, they actually, there's just a tsunami, and that is an indicator of success, and that's to me the competitive advantage, keep on introducing new products. You guys had how many products introduced on stage today, I mean, it was just not enough time. >> A lot, the payload was huge. >> There's a huge -- >> It's a really good sign of momentum and what's to come, yeah. >> Great sign, great sign. And I think what's going to, I'm sorry, we're so excited we can't even help ourselves. (men laughing) I think what's going to be interesting and a challenge for marketing moving forward is how do you put a net around it when you want to announce it, because when you look at continuous innovation and delivery, we're going to be doing something every few days, right, once a month, once every two weeks, so -- >> Well you guys have a good install base, and I always said you can't go out of business if you have money in the bank and if you have customers, thousands of customers do you guys have, not losing that core, building on the core, so how are you guys, from a product marketing standpoint, you got to package to the core, you got to have your core base, but now you have new constituencies, new personas in your base, now, developing, you have analytics, you have chief data officers, you have the guy who's going to be thinking about governance now and GP, GS, >> GDPR. >> G, D, >> G, D, P, R, >> G, E, P, R. Gettin' late in the day. (Jennifer laughing) But it's a global skill, you guys now have a new territory to take down, what's the plan? >> You take that one. >> Yeah, I think it's a really interesting one. Let me give you a specific example, and then we can broaden the story a little bit, but we recognize that one of the problems that our customers have is packing up their SAS environments. So that they have come from on-premises environments, where they were maybe using our storage, maybe not, moved into the cloud, and now, like one of our customers was talking recently about, he has hundreds of SAS providers, and he doesn't really know what data they have, so he's concerned about data protection, he's concerned about losing that data, obviously hacking attacks and similar things. >> Yeah. >> So we actually started a program around a product that we call Cloud Control, and Cloud Control for Office 365 is a first iteration of that that we launched just a few months ago, and it takes the Office 365 data and protects it and retains that data so that if something happens, somebody hacks, somebody corrupts your files, your CEO deletes emails and three months later you want it back, that data is there and it's protected and it's secure, so that's a native cloud service, you don't buy any equipment from us, your earlier comment about moving boxes, so the cloud for us is a great vehicle to get to these new buyers, and the interest that we're getting back is tremendous, but you're absolutely right that we need to find different ways and we are finding different ways to get to these buyers, to get to these personas that are out there. >> Well, not having a hardware-specific thing is certainly a great way, cloud, I mean. >> Exactly. >> Absolutely. >> you got a lot of data back in the recovery, there's no walls in the cloud, so the on-premises paradigm changes it a lot. >> Yeah, and this time we're talking SAS to SAS, right? >> That's great, so ecosystem partners, one of the big successes is partnerships. What's the strategy on partners, I mean cloud-native foundation, cloud CNCF cloud native compute foundations has grown, who's in there are you guys getting involved in that, what's your position, what's the strategy for partnering. >> Yeah, so as you would expect, you know, cloud is different enough that one framework doesn't match the things that we've been doing for those 25 years that we've been so successful in this business, so what we've tried to do in this new cloud first partner program that we've launched several months ago is really target our cloud native partners, these guys that couldn't care less about on-prem, they don't even know how to spell the word storage, and see how do we help service them with some of these great data services that we're bringing to bear, really, and these guys have no previous NetApp history with us. And we've got, you know, a couple dozen partners that have already signed up on our behalf, and we'll continue that momentum, but we're certainly excited to give them a new level of treatment that NetApp hasn't done before. >> So I would love to hear feedback from the lower-level from the ecosystem. NetApp I think, which is I think is a good thing, is very opinionated when it comes to its approach to cloud. This isn't oh, bring any old object store to the, it's you know what if you adopt ONTAP, if you adapt NetApp, data-driven vision, the data fabric, if you adopt that, then you enable a new level of cloud mobility. So if you, as you've brought that nest to the ecosystem, what's been the response, I mean a lot of these guys are pretty opinionated themselves. >> I was going to say you've already talked to Anthony and he's pretty opinionated. >> Yes (laughing). >> Yeah, no I think it's well-received, right, I mean, who doesn't want the ability to have some freedom to move around and choose their partners as we go, and I think one thing that Ingo was alluding to earlier is the fact that we're pretty heterogeneous in our data services, you don't have to have NetApp to be able to benefit from Cloud Control, or Cloud Sync, or OnCommand Insight, which is one of our sort of business insight tools for infrastructure and cloud-cost monitoring. So, it's nice to be able to give them a more sort of open message, but still have a pretty strong opinion on where people need to go and why. >> So let's talk about Cloud Control a little bit more, is Cloud Control an API, or is that just a, is that only control plane? >> It's a service, so it's a native cloud service, you can buy it on the marketplace, you can do free trials, you don't buy any hardware anywhere, it will grab the data through official APIs out of Office 365 and store it in a choice of locations, so we can host the storage for you, or you can store it in AWS, you can store it in Azure, or you can store it on-premises and storage with AppScale, which is our object store, so you know, for some customers it's important for compliance reasons to have an off-site on-premises copy, other customers would prefer to use Azure, use AWS, depends on what kind of licensing agreement, or massive purchase agreements they might have, so we give our customers that flexibility, but that is an example for native cloud service. We have another one that's called Cloud Sync, which is a data migration tool, you can go from CIFS, NFS, or S3, to CIFS, NFS, or S3. To, and it transforms the data, so you can go from an NFS source and move it natively into an S3 object in the cloud. It's another example for a native cloud service, it's not a license, it's not something that you buy and install on-premises. >> So that brings a question about data mobility today, I know cloud orchestrator is something that's coming in the future, but as far as data mobility, can I do something as simple as, say, or as complex, depending on your perspective, say I have two AWS regions, I'm front-ending this with ONTAP and I'm using ONTAP as a filer, and I want to replicate storage from one AWS region to another one, can I do that with object in the back-end and then use ONTAP to present that as files on both coasts, for example? >> Yeah, it depends a little bit on your application, the database that you're using, but say you're using ONTAP cloud, you can replicate between regions using cross-region replication, that's easy. But what's different is we have HA, so what you can do with ONTAP cloud is that you can do a fail-over from one availability zone to another availability zone, and that's all managed within the software. So if you're thinking about moving Enterprise application, mission-critical applications running production inside the cloud, you definitely do want to have HA, we did, we tackled this a little bit different for the NFS Azure service 'cause we were running and operating the infrastructure that is underneath the Azure portal so we have the reliability built into our product because it's running on our equipment. So we have complete control over that. >> Guys, final question, I know we got to go but I want to get your thoughts on management software, because the management game is changing the cloud too, as the trend of having the same code bases running on-prem or on the cloud, or applications working across multiple clouds brings up the role of the folks that are being shifted to high-value activities. One of them is, you know, managing dashboards automating some of the system management, application management, OnCommand has been around for a long, long time, NetApp has a history of good management tooling. How does that translate to the products in the cloud? >> It does, and I want to pull back to talk a little bit about OnCommand Insight 'cause we kind of overlook it because it's been around for a little while and it's more traditionally thought of as an SRM tool, but really, some of the capabilities that we've talked about even as early as today, was the fact that now we're extending sort of those infrastructure analytics and those business insights so you can identify resources that are wasted or places where you're out of capacity and you're bottlenecking, now into the cloud for things like cost-monitoring. So, imagine you're a CIO and you have people going around your back swiping credit cards to find whatever tools they want to use in the SAS universe to get their jobs done, only you have no idea where they're spending your money. Now you'll have the ability to look at almost a unified bill and see which departments are charging what money, and charge back those departments to keep them accountable in your budget. >> John: We call that the toolshed problem. >> Toolshed >> All these tools. >> They're everywhere. >> They're everywhere, don't be a tool, get out, get that toolshed, there's too many things in a tool, you get too many tools >> We have a lot of tools. Yeah, so we're happy to have things like that that help to give people a little bit more empowerment to first identify what's going on and how to fix it. >> The problem is though, in tools, they buy a tool, sometimes it turns into something else, like you buy a hammer and it turns into a lawnmower, but that's not what it's designed for. >> That's right. >> You can't mow your lawn with a hammer. >> You can't. >> So a final question before we break is product marketing focus. What's your to-do items, you guys got your list, I know you're making decisions on there with the product teams on how to take it to market, what's the to-do list for you guys. >> I'll give my answer and then I'll let you close, but it's messaging, messaging, messaging, right? I think in marketing we traditionally get sick of our own message before sometimes our audiences have heard it, and certainly we don't want to let Jean down, because she's done such a phenomenal job of getting the ship steered in a singular direction, so you're going to see a lot of big bold messages from us, a lot of us not being apologetic about some of the great IP that we've got and some of the things that we're doing, so we want to be sort of out there, reiterating that we're helping people harness the power of the hybrid cloud, and that we are the data authority on the hybrid cloud. >> And they say position it and they will come. That's absolutely right, anything you'd like to add? >> You know, so I spend a lot of time both with our internal product team and with our partners like Microsoft for example, it's really exciting the last few weeks, and the great thing for me is that we have more and more partners coming to us, wanting to leverage our products and working with us and understanding how they can participate in the data fabric vision, how can they be part of this network of partners and solutions and services that we're building, and that has been really, really exciting, cloud is real, and we're making it work. >> We're a little excited. >> Cloud is real, we look forward to following up, I'll have to get you guys into the studio in Palo Alto, a lot to talk about, lot more certainly, Kubernetes containers, we're getting a huge renaissance in application development that's going to create a lot of value, you guys are at the center of it. That's the keyword, the center of the action, here in Las Vegas with NetApp Insight 2017, we'll be right back with more live coverage afterwards I'm John Furrier, Keith Townsend, we'll be right back. (upbeat techno)

(upbeat music) >> Announcer: Live from San Jose, California, it's theCUBE covering Big Data Silicon Valley 2017. >> Welcome back everyone. We are here live in Silicon Valley for theCUBE's Big Data coverage. Our event, Big Data Silicon Valley, also called Big Data SV. A companion event to our Big Data NYC event where we have our unique program in conjunction with Strata Hadoop. I'm John Furrier with George Gilbert, our Wikibon big data analyst. And we have Basil Faruqui, who is the Solutions Marketing Manager at BMC Software. Welcome to theCUBE. >> Thank you, great to be here. >> We've been hearing a lot on theCUBE about schedulers and automation, and machine learning is the hottest trend happening in big data. We're thinking that this is going to help move the needle on some things. Your thoughts on this, on the world we're living in right now, and what BMC is doing at the show. >> Absolutely. So, scheduling and workflow automation is absolutely critical to the success of big data projects. This is not something new. Hadoop is only about 10 years old but other technologies that have come before Hadoop have relied on this foundation for driving success. If we look the Hadoop world, what gets all the press is all the real-time stuff, but what powers all of that underneath it is a very important layer of batch. If you think about some of the most common use cases for big data, if you think of a bank, they're talking about fraud detection and things like that. Let's just take the fraud detection example. Detecting an anomaly of how somebody is spending, if somebody's credit card is used which doesn't match with their spending habits, the bank detects that and they'll maybe close the card down or contact somebody. But if you think about everything else that has happened before that as something that has happened in batch mode. For them to collect the history of how that card has been used, then match it with how all the other card members use the cards. When the cards are stolen, what are those patterns? All that stuff is something that is being powered by what's today known as workload automation. In the past, it's been known by names such as job scheduling and batch processing. >> In the systems businesses everyone knows what schedulers, compilers, all this computer science stuff. But this is interesting. Now that the data lake has become so swampy, and people call it the data swamp, people are looking at moving data out of data lakes into real time, as you mention, but it requires management. So, there's a lot of coordination going on. This seems to be where most enterprises are now focusing their attention on, is to make that data available. >> Absolutely. >> Hence the notion of scheduling and workloads. Because their use cases are different. Am I getting it right? >> Yeah, absolutely. And if we look at what companies are doing, every CEO and every boardroom, there's a charter for digital transformation for companies. And, it's no longer about taking one or two use cases around big data and driving success. Data and intelligence is now at the center of everything a company does, whether it's building new customer engagement models, whether it's building new ecosystems with their partners, suppliers. Back-office optimization. So, when CIOs and data architects think about having to build a system like that, they are faced with a number of challenges. It has to become enterprise ready. It has to take into account governance, security, and others. But, if you peel the onion just a little bit, what architects and CIOs are faced with is okay, you've got a web of complex technologies, legacy applications, modern applications that hold a lot of the corporate data today. And then you have new sources of data like social media, devices, sensors, which have a tendency to produce a lot more data. First things first, you've got a ecosystem like Hadoop, which is supposed to be kind of the nerve center of the new digital platform. You've got to start ingesting all this data into Hadoop. This has to be in an automated fashion for it to be able to scalable. >> But this is the combination of streaming and batch. >> Correct. >> Now this seems to be the management holy grail right now. Nailing those two. Did I get that? >> Absolutely. So, people talk about, in technical terms, the speed layer and the batch layer. And both have to converge for them to be able to deliver the intelligence and insight that the business users are looking for. >> Would it be fair to say it's not just the convergence of the speed layer and batch layer in Hadoop but what BMC brings to town is the non-Hadoop parts of those workloads. Whether it's batch outside Hadoop or if there's streaming, which sort-of pre-Hadoop was more nichey. But we need this over-arching control, which if it's not a Hadoop-centric architecture. >> Absolutely. So, I've said this for a long time, that Hadoop is never going to live on an island on its own in the enterprise. And with the maturation of the market, Hadoop has to now play with the other technologies in the stack So if you think about, just take data ingestion for an example, you've got ERP's, you've got CRM's, you've got middleware, you've got data warehouses, and you have to ingest a lot of that in. Where Control-M brings a lot of value and speeds up time to market is that we have out-of-the box integrations with a lot of the systems that already exist in the enterprise, such as ERP solutions and others. Virtually any application that can expose itself through an API or a web service, Control-M has the ability to automate that ingestion piece. But this is only step one of the journey. So, you've brought all this data into Hadoop and now you've got to process it. The number of tools available for processing this is growing at an unprecedented rate. You've got, you know MapReduce was a hot thing just two years ago and now Spark has taken over. So Control-M, about four years ago we started building very deep native capabilities in their new ecosystem. So, you've got ingestion that's automated, then you can seamlessly automate the actual processing of the data using things like Spark, Hive, PEG, and others. And the last mile of the journey, the most important one, is them making this refined data available to systems and users that can analyze it. Often Hadoop is not the repository where analytic systems sit on top of. It's another layer where all of this has to be moved. So, if you zoom out and take a look at it, this is a monumental task. And if you use siloed approach to automating this, this becomes unscalable. And that's where a lot of the Hadoop projects often >> Crash and burn. >> Crash and burn, yes, sustainability. >> Let's just say it, they crash and burn. >> So, Control-M has been around for 30 years. >> By the way, just to add to the crash-and-burn piece, the data lake gets stalled there, that's why the swamp happens, because they're like, now how do I operationalize this and scale it out? >> Right, if you're storing a lot of data and not making it available for processing and analysis, then it's of no use. And that's exactly our value proposition. This is a problem we haven't solved for the first time. We did this as we have seen these waves of automation come through. From the mainframe time when it was called batch processing. Then it evolved into distributed client server when it was known more as job scheduling. And now. >> So BMCs have seen this movie before. >> Absolutely. >> Alright, so let's take a step back. Zoom out, step back, go hang out in the big trees, look down on the market. Data practitioners, big data practitioners out there right now are wrestling with this issue. You've got streaming, real-time stuff, you got batch, it's all coming together. What is Control-M doing great right now with practitioners that you guys are solving? Because there are a zillion tools out there, but people are human. Every hammer looks for a nail. >> Sure. So, you have a lot of change happening at the same time but yet these tools. What is Control-M doing to really win? Where are you guys winning? >> Where we are adding a lot of value for our customers is helping them speed up the time to market and delivering these big data projects, in delivering them at scale and quality. >> Give me an example of a project. >> Malwarebytes is a Silicon Valley-based company. They are using this to ingest and analyze data from thousands of end-points from their end users. >> That's their Lambda architecture, right? >> In Lambda architecture, I won't steal their thunder, they're presenting tomorrow at eleven. >> Okay. >> Eleven-thirty tomorrow. Another example is a company called Navistar. Now here's a company that's been around for 200 years. They manufacture heavy-duty trucks, 18-wheelers, school buses. And they recently came up with a service called OnCommand. They have a fleet of 160,000 trucks that are fitted with sensors. They're sending telematic data back to their data centers. And in between that stops in the cloud. So it gets to the cloud. >> So they're going up to the cloud for upload and backhaul, basically, right? >> Correct. So, it goes to the cloud. From there it is ingested inside their Hadoop systems. And they're looking for trends to make sure none of the trucks break down because a truck that's carrying freight breaks down hits the bottom line right away. But that's not where they're stopping. In real time they can triangulate the position of the truck, figure out where the nearest dealership is. Do they have the parts? When to schedule the service. But, if you think about it, the warranty information, the parts information is not sitting in Hadoop. That's sitting in their mainframes, SAP systems, and others. And Control-M is orchestrating this across the board, from mainframe to ERP and into Hadoop for them to be able to marry all this data together. >> How do you get back into the legacy? That's because you have the experience there? Is that part of the product portfolio? >> That is absolutely a part of the product portfolio. We started our journey back in the mainframe days, and as the world has evolved, to client server to web, and now mobile and virtualized and software-defined infrastructures, we have kept pace with that. >> You guys have a nice end-to-end view right now going on. And certainly that example with the trucks highlights IOT rights right there. >> Exactly. You have a clear line of sight on IOT? >> Yup. >> That would be the best measure of your maturity is the breadth of your integrations. >> Absolutely. And we don't stop at what we provide just out of the box. We realized that we have 30 to 35 out-of-the box integrations but there are a lot more applications than that. We have architected control them in a way where that can automate data loads on any application and any database that can expose itself through an API. That is huge because if you think about the open-source world, by the time this conference is going to be over, there's going to be a dozen new tools and projects that come online. And that's a big challenge for companies too. How do you keep pace with this and how do you (drowned out) all this? >> Well, I think people are starting to squint past the fashion aspect of open source, which I love by the way, but it does create more diversity. But, you know, some things become fashionable and then get big-time trashed. Look at Spark. Spark was beautiful. That one came out of the woodwork. George, you're tracking all the fashion. What's the hottest thing right now on open source? >> It seems to me that we've spent five-plus years building data lakes and now we're trying to take that data and apply the insides from it to applications. And, really Control-M's value add, my understanding is, we have to go beyond Hadoop because Hadoop was an island, you know, an island or a data lake, but now the insides have to be enacted on applications that go outside that ecosystem. And that's where Control-M comes in. >> Yeah, absolutely. We are that overarching layer that helps you connect your legacy systems and modern systems and bring it all into Hadoop. The story I tell when I'm explaining this to somebody is that you've installed Hadoop day-one, great, guess what, it has no data in it. You've got to ingest data and you have to be able to take a strategic approach to that because you can use some point solutions and do scripting for the first couple of use cases, but as soon as the business gives us the green light and says, you know what, we really like what we've seen now let's scale up, that's where you really need to take a strategic approach, and that's where Control-M comes in. >> So, let me ask then, if the bleeding edge right now is trying to operationalize the machine learning models that people are beginning to experiment with, just the way they were experimenting with data lakes five years ago, what role can Control-M play today in helping people take a trained model and embed it in an application so it produces useful actions, recommendations, and how much custom integration does that take? >> If we take the example of machine learning, if you peel the onion of machine learning, you've got data that needs to be moved, that needs to be constantly evaluated, and then the algorithms have to be run against it to provide the insights. So, this in itself is exactly what Control-M allows you to do, is ingest the data, process the data, let the algorithms process it, and then of course move it to a layer where people and other systems, it's not just about people anymore, it's other systems that'll analyze the data. And the important piece here is that we're allowing you to do this from a single pane of glass. And being able to see this picture end to end. All of this work is being done to drive business results, generating new revenue models, like in the case of Navistar. Allowing you to capture all of this and then tie it to business SOAs, that is one of the most highly-rated capabilities of Control-M from our customers. >> This is the cloud equation we were talking last week at Google Next. A combination of enterprise readiness across the board. The end-to-end is the picture and you guys are in a good position. Congratulations, and thanks for coming on theCUBE. Really appreciate it. >> Absolutely, great to be here. >> It's theCUBE breaking it down here at Big Data World. This is the trend. It's an operating system world in the cloud. Big data with IOT, AI, machine learning. Big themes breaking out early-on at Big Data SV in conjunction with Strata Hadoop. More right after this short break.