>> Announcer: Live from Midtown Manhattan it's theCUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> OK, welcome back everyone we're here in New York City it's theCUBE's exclusive coverage of Big Data NYC, in conjunction with Strata Data going on right around the corner. It's out third day talking to all the influencers, CEO's, entrepreneurs, people making it happen in the Big Data world. I'm John Furrier co-host of theCUBE, with my co-host here Jim Kobielus who is the Lead Analyst at Wikibon Big Data. Nenshad Bardoliwalla. >> Bar-do-li-walla. >> Bardo. >> Nenshad Bardoliwalla. >> That guy. >> Okay, done. Of Paxata, Co-Founder & Chief Product Officer it's a tongue twister, third day, being from Jersey, it's hard with our accent, but thanks for being patient with me. >> Happy to be here. >> Pranav Rastogi, Product Manager, Microsoft Azure. Guys, welcome back to theCUBE, good to see you. I apologize for that, third day blues here. So Paxata, we had your partner on Prakash. >> Prakash. >> Prakash. Really a success story, you guys have done really well launching theCUBE fun to watch you guys from launching to the success. Obviously your relationship with Microsoft super important. Talk about the relationship because I think this is really people can start connecting the dots. >> Sure, maybe I'll start and I'LL be happy to get Pranav's point of view as well. Obviously Microsoft is one of the leading brands in the world and there are many aspects of the way that Microsoft has thought about their product development journey that have really been critical to the way that we have thought about Paxata as well. If you look at the number one tool that's used by analysts the world over it's Microsoft Excel. Right, there isn't even anything that's a close second. And if you look at the the evolution of what Microsoft has done in many layers of the stack, whether it's the end user computing paradigm that Excel provides to the world. Whether it's all of their recent innovation in both hybrid cloud technologies as well as the big data technologies that Pranav is part of managing. We just see a very strong synergy between trying to combine the usage by business consumers of being able to take advantage of these big data technologies in a hybrid cloud environment. So there's a very natural resonance between the 2 companies. We're very privileged to have Microsoft Ventures as an investor in Paxata and so the opportunity for us to work with one of the great brands of all time in our industry was really a privilege for us. Yeah, and that's the corporate sides so that wasn't actually part of it. So it's a different part of Microsoft which is great. You have also business opportunity with them. >> Nenshad : We do. >> Obviously data science problem that we're seeing is that they need to get the data faster. All that prep work, seems to be the big issue. >> It does and maybe we can get Pranav's point of view from the Microsoft angle. >> Yeah so to sort of continue what Nenshad was saying, you know the data prep in general is sort of a key core competence which is problematic for lots of users, especially around the knowledge that you need to have in terms of the different tools you can use. Folks who are very proficient will do ETL or data preparation like scenarios using one of the computing engines like Hive or Spark. That's good, but there's this big audience out there who like Excel-like interface, which is easy to use a very visually rich graphical interface where you can drag and drop and can click through. And the idea behind all of this is how quickly can I get insights from my data faster. Because in a big data space, it's volume, variety and velocity. So data is coming at a very fast rate. It's changing it's growing. And if you spend lot of time just doing data prep you're losing the value of data, or the value of data would change over time. So what we're trying to do would sort of enabling Paxata or HDInsight is enabling these users to use Paxata, get insights from data faster by solving key problems of doing data prep. >> So data democracy is a term that we've been kicking around, you guys have been talking about as well. What is actually mean, because we've been teasing out first two days here at theCUBE and BigData NYC is. It's clear the community aspect of data is growing, almost on a similar path as you're seeing with open source software. That genie's out the bottle. Open source software, tier one, it won, it's only growing exponentially. That same paradigm is moving into the data world where the collaboration is super important, in this data democracy, what is that actually mean and how does that relate to you guys? >> So the perspective we have is that first something that one of our customers said, that is there is no democracy without certain degrees of governance. We all live in a in a democracy. And yet we still have rules that we have to abide by. There are still policies that society needs to follow in order for us to be successful citizens. So when when a lot of folks hear the term democracy they really think of the wild wild west, you know. And a lot of the analytic work in the enterprise does have that flavor to it, right, people download stuff to their desktop, they do a little bit of massaging of the data. They email that to their friend, their friend then makes some changes and next thing you know we have what what some folks affectionately call spread mart hell. But if you really want to democratize the technology you have to wrap not only the user experience, like Pranav described, into something that's consumable by a very large number of folks in the enterprise. You have to wrap that with the governance and collaboration capabilities so that multiple people can work off the same data set. That you can apply the permissions so that people, who is allowed to share with each other and under what circumstances are they allowed to share. Under what circumstances are you allowed to promote data from one environment to another? It may be okay for someone like me to work in a sandbox but I cannot push that to a database or HDFS or Azure BLOB storage unless I actually have the right permissions to do so. So I think what you're seeing is that, in general, technology is becoming a, always goes on this trend, towards democratization. Whether it's the phone, whether it's the television, whether it's the personal computer and the same thing is happening with data technologies and certainly companies like. >> Well, Pranav, we're talking about this when you were on theCUBE yesterday. And I want to get your thoughts on this. The old way to solve the governance problem was to put data in silos. That was easy, I'll just put it in a silo and take care of it and access control was different. But now the value of the data is about cross-pollinating and make it freely available, horizontally scalable, so that it can be used. But the same time and you need to have a new governance paradigm. So, you've got to democratize the data by making it available, addressable and use for apps. The same time there's also the concerns on how do you make sure it doesn't get in the wrong hands and so on and so forth. >> Yeah and which is also very sort of common regarding open source projects in the cloud is a how do you ensure that the user authorized to access this open source project or run it has the right credentials is authorized and stuff. So, the benefit that you sort of get in the cloud is there's a centralized authentication system. There's Azure Active Directory, so you know most enterprise would have Active Directory users. Who are then authorized to either access maybe this cluster, or maybe this workload and they can run this job and that sort of further that goes down to the data layer as well. Where we have active policies which then describe what user can access what files and what folders. So if you think about the entrance scenario there is authentication and authorization happening and for the entire system when what user can access what data. And part of what Paxata brings in the picture is like how do you visualize this governance flow as data is coming from various sources, how do you make sure that the person who has access to data does have access data, and the one who doesn't cannot access data. >> Is that the problem with data prep is just that piece of it? What is the big problem with data prep, I mean, that seems to be, everyone keeps coming back to the same problem. What is causing all this data prep. >> People not buying Paxata it's very simple. >> That's a good one. Check out Paxata they're going to solve your problems go. But seriously, there seems to be the same hole people keep digging themselves into. They gather their stuff then next thing they're in the in the same hole they got to prepare all this stuff. >> I think the previous paradigms for doing data preparation tie exactly to the data democracy themes that we're talking about here. If you only have a very silo'd group of people in the organization with very deep technical skills but don't have the business context for what they're actually trying to accomplish, you have this impedance mismatch in the organization between the people who know what they want and the people who have the tools to do it. So what we've tried to do, and again you know taking a page out of the way that Microsoft has approached solving these problems you know both in the past in the present. Is to say look we can actually take the tools that once were only in the hands of the, you know, shamans who know how to utter the right incantations and instead move that into the the common folk who actually. >> The users. >> The users themselves who know what they want to do with the data. Who understand what those data elements mean. So if you were to ask the Paxata point of view, why have we had these data prep problems? Because we've separated the people who had the tools from the people who knew what they wanted to do with it. >> So it sounds to me, correct me if this is the wrong term, that what you offer in your partnership is it basically a broad curational environment for knowledge workers. You know, to sift and sort and annotating shared data with the lineage of the data preserved in essentially a system of record that can follow the data throughout its natural life. Is that a fair characterization? >> Pranav: I would think so yeah. >> You mention, Pranav, the whole issue of how one visualizes or should visualize this entire chain of custody, as it were, for the data, is there is there any special visualization paradigm that you guys offer? Now Microsoft, you've made a fairly significant investment in graph technology throughout your portfolio. I was at Build back in May and Sacha and the others just went to town on all things to do with Microsoft Graph, will that technology be somehow at some point, now or in the future, be reflected in this overall capability that you've established here with your partner here Paxata? >> I am not sure. So far, I think what you've talked about is some Graph capabilities introduced from the Microsoft Graph that's sort of one extreme. The other side of Graph exists today as a developer you can do some Graph based queries. So you can go to Cosmos DB which had a Gremlin API. For Graph based query, so I don't know how. >> I'll get right to the question. What's the Paxata benefits of with HDInsight? How does that, just quickly, explain for the audience. What is that solution, what are the benefits? >> So the the solution is you get a one click install of installing Paxata HDInsight and the benefit is as a benefit for a user persona who's not, sort of, used to big data or Hadoop they can use a very familiar GUI-based experience to get their insights from data faster without having any knowledge of how Spark works or Hadoop works. >> And what does the Microsoft relationship bring to the table for Paxata? >> So I think it's a couple of things. One is Azure is clearly growing at an extremely fast pace. And a lot of the enterprise customers that we work with are moving many of their workloads to Azure and and these cloud based environments. Especially for us, the unique value proposition of a partner who truly understands the hybrid nature of the world. The idea that everything is going to move to the cloud or everything is going to stay on premise is too simplistic. Microsoft understood that from day one. That data would be in it and all of those different places. And they've provided enabling technologies for vendors like us. >> I'll just say it to maybe you're too coy to say it, but the bottom line is you have an Excel-like interface. They have Office 365 they're user's going to instantly love that interface because it's an easy to use interface an Excel-like it's not Excel interface per se. >> Similar. >> Metaphor, graphical user interface. >> Yes it is. >> It's clean and it's targeted at the analyst role or user. >> That's right. >> That's going to resonate in their install base. >> And combined with a lot of these new capabilities that Microsoft is rolling out from a big data perspective. So HDInsight has a very rich portfolio of runtime engines and capabilities. They're introducing new data storage layers whether it's ADLS or Azure BLOB storage, so it's really a nice way of us working together to extract and unlock a lot of the value that Microsoft. >> So, here's the tough question for you, open source projects I see Microsoft, comments were hell froze because LINUX is now part of their DNA, which was a comment I saw at the even this week in Orlando, but they're really getting behind open source. From open compute, it's just clearly new DNA's. They're they're into it. How are you guys working together in open source and what's the impact to developers because now that's only one cloud, there's other clouds out there so data's going to be an important part of it. So open source, together, you guys working together on that and what's the role for the data? >> From an open source perspective, Microsoft plays a big role in embracing open source technologies and making sure that it runs reliably in the cloud. And part of that value prop that we provide in sort of Azure HDInsight is being sure that you can run these open source big data workloads reliably in the cloud. So you can run open source like Apache, Spark, Hive, Storm, Kafka, R Server. And the hard part about running open source technology in the cloud is how do you fine tune it, and how do you configure it, how do you run it reliably. And that's what sort of what we bring in from a cloud perspective. And we also contribute back to the community based on sort of what learned by running these workloads in the cloud. And we believe you know in the broader ecosystem customers will sort of have a mixture of these combinations and their solution They'll be using some of the Microsoft solutions some open source solutions some solutions from ecosystem that's how we see our customer solution sort of being built today. >> What's the big advantage you guys have at Paxata? What's the key differentiator for why someone should work with you guys? Is it the automation? What's the key secret sauce to you guys? >> I think it's a couple of dimensions. One is I think we have come the closest in the industry to getting a user experience that matches the Excel target user. A lot of folks are attempting to do the same but the feedback we consistently get is that when the Excel user uses our solution they just, they get it. >> Was there a design criteria, was that from the beginning how you were going to do this? >> From day one. >> So you engineer everything to make it as simple as like Excel. >> We want people to use our system they shouldn't be coding, they shouldn't be writing scripts. They just need to be able. >> Good Excel you just do good macros though. >> That's right. >> So simple things like that right. >> But the second is being able to interact with the data at scale. There are a lot of solutions out there that make the mistake in our opinion of sampling very tiny amounts of data and then asking you to draw inferences and then publish that to batch jobs. Our whole approach is to smash the batch paradigm and actually bring as much into the interactive world as possible. So end users can actually point and click on 100 million rows of data, instead of the million that you would get in Excel, and get an instantaneous response. Verses designing a job in a batch paradigm and then pushing it through the the batch. >> So it's interactive data profiling over vast corpuses of data in the cloud. >> Nenshad: Correct. >> Nenshad Bardoliwalla thanks for coming on theCUBE appreciate it, congratulations on Paxata and Microsoft Azure, great to have you. Good job on everything you do with Azure. I want to give you guys props, with seeing the growth in the market and the investment's been going well, congratulations. Thanks for sharing, keep coverage here in BigData NYC more coming after this short break.

>> Announcer: Live from Midtown Manhattan, it's theCUBE, covering Big Data, New York City, 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay, welcome back, everyone. Live in Manhattan, this is theCUBE's coverage of our fifth year doing Big Data, NYC; eighth year covering Hadoop World, which is now evolved into Strata Data which is right around the corner. We're doing that in conjunction with that event. This is, again, where we have the thought leaders, we have the experts, we have the entrepreneurs and CEOs come in, of course. The who's who in tech. And my next two guests, is Jagane Sundar, CUBE alumni, who was on yesterday. CTO of WANdisco, one of the hottest companies, most valuable companies in the space for their unique IP, and not a lot of people know what they're doing. So congratulations on that. But you're here with one of your partners, a company I've heard of, called Microsoft, also doing extremely well with Azure Cloud. We've got Pranav Rastogi, who's the program manager of Microsoft Cloud Azure. You guys have an event going on as well at Microsoft Ignite which has been creating a lot of buzz this year again. As usual, they have a good show, but this year the Cloud certainly has taken front and center. Welcome to theCUBE, and good to see you again. >> Thank you. >> Thank you. >> Alright, so talk about the partnership. You guys, Jagane deals with all the Cloud guys. You're here with Microsoft. What's going on with Microsoft? Obviously they've been, if you look at the stock price. From 20-something to a complete changeover of the leadership of Satya Nadella. The company has mobilized. The Cloud has got traction, putting a dent in the universe. Certainly, Amazon feels a little bit of pain there. But, in general, a lot more work to do. What are you guys doing together? Share the relationship. >> So, we just announced a product that's a one-click deployment in the Microsoft Azure Cloud, off WANdisco's Fusion Replication technology. So, if you got some data assets, Hadoop or Cloud object stores on-premise and you want to create a hybrid or a Cloud environment with Azure and Picture, ours is the only way of doing Active/Active. >> Active/Active. And there is some stuff out there that's looking like Active/Active. DataPlane by Hortonworks. But it's fully not Active/Active. We talked a little bit about that yesterday. >> Jagane: Yes. >> Microsoft, you guys, what's interesting about these guys besides the Active/Active? It's a unique thing. It's an ingredient for you guys. >> Yes, the interesting thing for us is, the biggest problem that we think customers have for big data perspective is, if you look at the landscape of the ecosystem in terms of open source projects that are available it's very hard to a: figure out How do I use this software?, b: How do I install it? And, so what we have done is created an experience in Azure HDInsight where you can discover these applications, within the context of your cluster and you can install these applications by one-click install. Which installs the application, configures it, and then you're good to go. We think that this is going to sort of increase the productivity of users trying to get sense out of big data. The key challenges we think customers have today is setting up some sort of hybrid environment between how do you connect your on premise data to move it to the Cloud, and there are different use cases that you can have you can move parts of the data and you can do experiment easily in the Cloud. So what we've done is, we've enabled WANdisco as an application on our HDInsight application platform, where customers can install it using a single-click deploy connected with the data that's sitting on-prem, use the Active/Active feature to have both these environments running simultaneously and they're in sync. >> So one benefits the one-click thing, that's on your side, right? You guys are enabling that. So, okay, I get that. That's totally cool. We'll get to that in a second. I want to kind of drill down on that. But, what's the benefit to the customers, that you guys are having? So, I'm a customer, I one-click, I want some WANdisco Active/Active. Why am I doing it? What does the Cloud change? How does your Cloud change from that experience? >> One example that you can think about is going to change is in an on-premise environment you have a cluster running, but you're kind of limited on what you can do with the cluster, because you've already setup the number of nodes and the workloads your running is fairly finite, but what's happening in reality and today is, lots of users, especially in the machine learning space, and AI space, and the analytic space are using a lot of open source libraries and technologies and they're using it on top of Hadoop, and they're using it on top of Spark. However, in experimenting with these technologies is hard on-prem because it's a locked environment. So we believe, with the Cloud, especially with it offering WANdisco and HDInsight, once you move the data you can start spinning up clusters, you can start installing more open source libraries, experiment, and you can shut down the clusters when you're done. So it's going to increase your efficiency, it's going to allow you to experiment faster, and it's going to reduce for cost as well, because you don't have to have the cluster running all the time and once you are done with your experimentation, then you can decide which way do you want to go. So, it's going to remove the-- >> Jagane, what's your experience with Azure? A lot of people have been, some people have been critical, and rightfully so. You guys are moving as fast you can. You can only go as fast you can, but the success of the Cloud has been phenomenal. You guys have done a great job with the Cloud. Got to give you props on that. Your customers are benefiting, or Microsoft's customers are benefiting. How's the relationship? Are you getting more customers through these guys? Are you bringing customers from on-prem to Cloud? How's the customer flow going? >> Almost all of our customers who have on-prem instances of Hadoop are considering Cloud in one form or the other. Different Clouds have different strengths, as they've found-- >> Interviewer: And different technologies. >> Indeed. And Azure's strengths appear to be the HDInsight piece of it and as Pranam just mentioned, the cool thing is, you can replicate into the Cloud, start up a 50 node Spark cluster today to run a query, that may return results to you really fast. Now, remember this is data that you can write to both in the Cloud and on-premise. It's kept consistent by our technology, or tomorrow you may find that somebody tells you, Hive with the new Tez enhancements is faster, sure, spin up a hundred node Hive cluster in the Cloud, HDInsight supports that really well. You're getting consistent data and your queries will respond much faster than your on-premise. >> We've had Oliver Chu on, before with Hortonworks obviously they're partnering there. HDInsight's been getting a lot of traction lately. Where's that going? We've seen some good buzz on that. Good people talking about it. What's the latest update on your end? >> HDInsight is doing really good. The customers love the ease of creating a cluster using just a few clicks and the benefits that customers get, clusters are optimized for certain scenarios. So if you're doing data science, you can create a Spark cluster, install open source libraries. We have Microsoft R Server running on Spark, which is a unique offering to Microsoft, which lots of customers have appreciated. You also have streaming scenarios that you can do using open source technologies, like we have Apache Kafka running on a stack, which is becoming very popular from an ingestion perspective. Folks have been-- >> Has the Kupernetes craze come down to your group yet? Has it trickled down? It seems to be going crazy. You hired an amazing person from Google, Brendan Burns, we've interviewed before. He's part of the original Kubernetes spec he now works for Microsoft. What's the buzz on the Kubernetes container world there? >> In general, Microsoft Azure has seen great benefits out of it. We are seeing lots of traction in that space. From my role in particular, I focus more on the HDInsight big data space, which is kind of outside of what we do with Kubernetes' work. >> And your relationship is going strong with WANdisco? >> Pranav: Yes. >> Right. >> We just launched this offering just about yesterday is what we announced and we're looking forward to getting customers on to the stack. >> That's awesome. What's your take on the industry right now? Obviously, the partnerships are becoming clearer as people can see there's (mumbles). You're starting to see the notion of infrastructure and services are changing. More and more people want services and then you got the classic infrastructure which looks like it's going to be hybrid. That's pretty clear, we see that. Services versus infrastructure, how should customers think about how they architect their environments? So they can take advantage of the Active/Active and also have a robust, clean, not a lot of re-skilling going on, but more of a good organization from a personnel standpoint, but yet get to a hybrid architecture? >> So, it depends, the Cloud gives you lots of options to meet the customers where they are. Different customers have different kinds of requirements. Customers who have specialized, some of their applications will probably want to go more of an infrastructure route, but customers also love to have some of the past benefits where, you know, I have a service running where I don't have to worry about the infrastructure, how dispatching happen, how does OS updates happen, how does maintenance happen. They want to sort of rely on the Microsoft Azure Cloud provider to take care of it. So that they can focus on their application specific logic, or business specific logic, or analytical workloads, and worry about optimizing those parts of the application because that is their core-- >> It's been great.I want to get your thoughts real quick. Share some color. What's going on inside Microsoft? Obviously, open source has become a really big part of the culture, even just at Ignite. More Linux news is coming. You guys have been involved in Linux. Obviously, open source with Azure, ton of stuff, I know is built in the Microsoft Cloud on open source. You're contributing now as to Kubernetes, as I mentioned earlier. Seems to be a good cultural shift at Microsoft. What's the vibe on the open source internally at Microsoft? Can you share, just some anecdotal insight into what's the vibe like inside, around open source? >> The vibe has increased quite a lot around open source. You rightly mentioned, just recently we've announced a SQL server on Linux as well, at the Ignite conference. You can also deploy a SQL server on a docker container, which is quite revolutionary if you think about how forward we have come. Open source is so pervasive it's almost used in a lot of these projects. Microsoft employees are contributing back to open source projects in terms of, bug fixes, feature requests, or documentation updates. It's a very, very active community and by and large I think customers are benefiting a lot, because there are so many folks working together on open source projects and making them successful and especially around the Azure stack, we also ensure that you can run these open source workloads lively in the Cloud. From an enterprise perspective, you get the best of both worlds. You get the latest innovations happening in open source, plus the reliability of the managed platform that Azure provides at an enterprise scale. >> So again, obviously Microsoft partnership is huge, all the Clouds as well. Where do you want to take the relationship with Microsoft? What happens next? You guys are just going to continue to do business, you're like expecting the one-click's nice, I have some questions on that. What happens next? >> So, I see our partnership becoming deeper. We see the value that HDInsight brings to the ecosystem and all of that value is captured by the data. At the end of the day, if you have stale data, if you have data that you can't rely on the applications are useless. So we see ourselves getting more and more deeply embedded in the system. We see of ourselves as an essential part of the data strategy for Azure. >> Yeah, we see continuous integration as a development concept, continuous analytics as a term, that's being kicked around. We were talking yesterday about, here in theCUBE, real time, I want some data real time and IT goes back, "Here it is, it's real time!" No, but the data's three weeks old. I mean, real time (laughs) is a word that doesn't mean I got to see it really fast, low latency response. Well, that's not the data I want. I meant the data in real time, not you giving me a real time query. So again, this brings up a mind shift in terms of the new way to do business in the Cloud and hybrid. It's changing the game. As customers scratch their heads and try to figure out how to make their organizations more DevOps oriented, what do you guys see for advice for those managers, who are really getting behind it, really want to make change, who kind of have to herd the cats a little bit, and maybe break out security and put it in it's own group? Or you come and say, okay IT guys we're going to change into our operating model, even on-prem, we'll use some burst in to the Cloud, Azure's got 365 on there, lot of coolness developing. What's the advice for the mindset of the change agents out there that are going to do the transformation? >> My advice would be, if you've done the same thing by hand over two times, it's time you automated it, but-- >> Interviewer: Two times?! >> Two times. >> No three rule? Three strikes you're out? >> You're saying two, contrarian. >> That's a careful statement. Because, if you try automating something that you've never actually tried by hand, that's a disaster as well. A couple times, so you know how it's supposed to work. >> Interviewer: Get a good groove on it. >> Right, then you optimize, you automate, and then you turn the knobs. So, you try a hundred node cluster, maybe that's going to be faster. Maybe after a certain point, you don't get any improvements, so you know how to-- >> So take some baby steps, and one easy way to do it is to automate something that you've done. >> Jagane: Yes, exactly. >> That's almost risk-free, relatively speaking. Thoughts, advice to change agents out there. This is your industry hat on. You can take your Microsoft hat off. >> Baby steps. So you start small, you get familiar with the environment and your toolsets are provided so that you get a consistent experience on what you were doing on-prem and sort of in a hybrid space. And the whole idea is as you get more comfortable the benefits of the Cloud far outweigh any sort of cultural changes that need to happen-- >> Guys, thanks for coming on theCUBE, really appreciate it. Thoughts on the Big Data NYC this week? What do you think? >> I think it's a conference that has a lot of Cloud hanging over it and people are scratching their heads. Including vendors, customers, everybody scratching their head, but there is a lot of Cloud in this conference, although this is not a Cloud conference. >> Yeah, they're trying to make it an AI conference. A lot of AI watching certainly we're seeing that everywhere. But again, nothing wrong hyping up AI. It's good for society. It really is cool, but still, that's talking about baby steps, AI is still not there. It seems like, AI from when I got my CS degree in the 80's, not a lot innovation, well machine learning is getting better, but, a lot more way to go on AI. Don't you think? >> Yes, you know a few of the announcements we've made in this week is all about making it easier for developers to get started with AI and machine learning and our whole hope is with these investments that we've done and Azure machine learning improvements and the companion app and the workbench, allows you to get started very easily with AI and machine learning models and you can apply and build these models, do a CICD process and deploy these models and be more effective in the space. >> Yeah and also the tooling market has kind of gotten out of control. We were just joking the other day, that there's this tool shed mindset where everything is in the tool shed and people bought a hammer and turned it into a lawnmower. So it's like, you got to be careful which tools you have. Think about a platform. Think holistically, but if you take the baby steps and implement it, certainly it's there. My personal opinion, I think the Cloud is the equalizer. Cloud can bring compute power that changes what a tool was built for. Even, go back six years, the tools that were out there even six years ago are completely changed by the impact of unlimited, potentially unlimited capacity horsepower. So, okay that resets a little bit. You agree? >> I do. I totally agree. >> Who wins, who loses on the reset? >> The Cloud is an equalizer, but there is a mindset shift that goes with that those who can adapt to the mindset shift, will win. Those who can not and are still clinging to their old practices will have a hard time. >> Yeah, it's exciting. If you're still reinventing Hadoop from 2011 then, probably not good shape right now. >> Jagane: Not a good place to be. >> Using Hadoop is great for Bash, but you can't make that be a lawnmower. That's my opinion. Okay, thanks for coming on. I appreciate it (laughs) You're smiling, you got something that you, no? >> Pranav: (laughs) Thank you so much for that comment. >> Yeah, tool sheds are out there, be careful. Guys do your job. Congratulations on your partnership, appreciate it. This is theCUBE, live in New York. More after this short break. We'll be right back.