>> 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.