(Upbeat Techno Music) >> Announcer: Live from Copenhagen, Denmark. It's theCUBE! Covering Nutatnix.Next 2019. Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of Nutanix.Next. We are here at the Bella Center in Copenhagen. I'm your host, Rebecca Knight, alongside of Stu Miniman, the analyst for theCUBE. We have two guests for this segment. We have Manoj Agarwal. He is the SVP of Engineering at Nutanix. Thanks so much for coming on the show. >> Thank you Rebecca. That's good. >> And Gil Haberman. He is the Senior Director of Product Marketing at Nutanix. Thank you so much for coming on the show. >> Thanks for having me. So, our topic today is Xi Clusters. These were announced at Anaheim, at .Next back in Anaheim. Gil, why don't we start with you. Describe the business problems you were hearing from customers and how these Xi Clusters are designed to help solve them. >> Gil: Sure, first thanks for inviting me. I'm a big fan of theCUBE. It's so great to be here. To your question, at Nutanix, we've been working with customers on the vision of Hybrid Cloud for a number of years now. And the different challenges have evolved over time. Initially, there were pockets of public cloud adoption where customers wanted to simply find a way to operate across multiple clouds. But today, the challenges are different. Now, as customers are looking to adopt business critical applications that span private and public, bursting and migrating applications, there's a strong need for consistency across environments. And we gear around consistency around 3 aspects. The first is infrastructure. The second is operations. And the third is the consumption model itself. From an individual perspective, what we keep hearing is that the same VMs and applications must be able to work across environments, without significant replatforming or retooling. From an operation's perspective, cloud engineers truly need a way to utilize the same practices, integrations, in work that they have done on their applications for many years, across multiple clouds. So there's a need to sustain the same practices across these multiple clouds. And finally from a consumption model perspective, there's a need to have a platform that drives the same level of consistency in terms of licensing and software across different environments. And for that, we at Nutanix have to evolve to empower operators to be able to address all of these needs of consistency across private and public. >> Now, I would like to add something to it. You just think about three years ago. The entire world was talking about "Everything is going to be public cloud." And very soon, all these CIOs also realized that it's not going to be just public cloud or just private cloud. It's going to be Hybrid. And we ran a survey with 2,700 IT professionals who participated in the survey, and what we learned mainly 91% of them, they said hybrid is ideal. And the second thing that was not also a surprising thing was 94% of them, they said the app migration or app mobility is going to be the key. And then we look at that option like "How are you going to adopt?" And that was also strikingly similar, like what we see currently maybe 18% or so, that they are into the hybrid world and getting onto close to 41% or so in the next 24 months. >> Yeah, but Manoj, I'm glad you brought that up. When I talk to users, the thing that they're concerned the most about are their applications% and their data. And in IT forever, migrations have been a challenging thing to do and it was usually, you set up a migration and it takes you weeks or months to do it. Today, migrations aren't even going to be even a one time thing. If I'm moving from one cloud to another, if I'm moving from private to public, or even public to private. I need to have some flexibility to what I'm building. How has that informed how you're building your architectural designs? >> That's a great point. In fact, we always feel that architecture matters, and why the fundamental technologies that we are building should help. Two things that I'll say. One is the data replication technologies that we have built and strengthened over time. Plus the second thing is the network. If you get the network right, then you are very slowly there. And we had been reflecting on the data side, you know. 10 years of journey and data replication technologies like we have built. Networking we have been very hard at work on that front also in the last three years or so, with the building of Xi Cloud. We'll see and hear more and more, especially in the context of Xi Cluster. What you see is that we have done the ready integration with AWS ETCs. Thereby first of all all the services that exist in AWS. It's available to the customers with their app, running on XI Clusters without changing anything there. >> This is a competitive market so let's talk about differentiation. How do you see the product as completely different from your rivals and then how are you positioning it to your customers? >> Yeah. I'll go back to again the same thing. Architecture matters. We were not the first ones to go out with a hybrid converse like in 2013. There were a lot of competitive solutions that existed at the time. But we took our time. We wanted to make sure that we do it right. We do provide choice to our customers. That's where we matter. As we are building out solutions, again going back to the four principles. Applications sort of require change. You don't require an IPO presence to change, so when we are building the solution, we are making sure if you want to pay for private cloud, on-prem our service provider. Or you want a public cloud. Any of the big cloud players or this new cloud, that you have a common architecture underneath. You have the same management plain with the prism. You can really orchestrate, and manage the entire infrastructure. You have the flexibility in terms of the networking. Other services that you want to go and use, you have the choice of wahtever platform also. Like something that we don't want you to go and change if you don't need a change. Lastly, I would say, on the business side, we do want to give the smarty cloud world the flexibility for the customers to bring a cloud of their choice and if they want to switch, they should be able to switch with one click also. >> Yeah. Gil, I'm wondering if you can actually explain to our audience one of the challenges here is deploying unbared metal is not something that anybody can just do on the public clouds. For AWS, the first solution was actually VM ware on AWS. They had to develop that but they're now opening that to be able to use. Can you walk us through where we are with the cloud providers and that's I think part of the reason why this isn't yet generally available. Indeed, AWS has been the first to open bare metal and this is really the path for us at Nutanix to make clouds invisible as well. We worked with a number of platforms on Prem and now we want to extend that to public cloud and having an ability to actually access bare metal is the first step in doing so. Beyond that, what we've done is what we believe is the hard work of making things very simple to drive customer delight. And so what we've done is integrate into AWS rather than just running on top of AWS, inside existing accounts and VPCs of customers and the outcome has benefits on both technology and business perspective. From the technology perspective, cloud operators can see all bare metal as well as cloud native services in one place, one inventory. And we believe that this type of topology will provide better performance. And then on the business side, this allows us to do a couple of things. The first, if you are an AWS user like most of our customers, they can use AWS credits for that bare metal infrastructure. At Nutanix, we are now able to evolve our services to provide hybrid licenses, so our licenses would eventually be portable. And so you see how we are gradually building towards this portability across multiple clouds, AWS being the first cloud. >> Yeah, it's great to see Nutanix- We've seen a few other companies moving towards that model because if I'm software and truly agnostic, you should be able to have it across those environments. I believe Solidfire a couple of years ago started doing some of the things; A couple other companies. So the X in AWS sounds like it will be first. We know Google has been the partner of Nutanix for a while. Could you just give us where are we with Google and Azure? Kind of to round out the big three. >> Sure, so we have started to work with AWS and we have announced early access now inviting customers to sign up with us to get access. We are also actively working with Azure to figure out how to together bring better bare metal services and the type of software on top of that. And of course, we believe that other cloud vendors are going to open this up as well and Google Cloud being a close partner of ours is an important part of that strategy as well. >> And we are doing something with Google already as you know. We have integrated the entire stack using their nested vertilization technologies, like running on their vertilization the HB which is nested. Today, we run a lot of our customers prospect they run. The test, our experience the entire solution on Google test prime. We have brought out more than a thousand users every month, that they access it. So it's a journey, like when they have the full bare metal, you can see a lot more but we are very engaged with them. >> I want to talk about the future now and have you looked into your crystal ball a bit, 6, 10, years from now. What do you see- This is such a fast changing environment but how do you see the cloud evolving and then how do you see Nutanix? What role does Nutanix play? >> Last 10 years, it was all about how we bring public cloud into the private cloud, right? Next 5, 10 years when you think about it is all how do we really make it hybrid. The experience that what customers have come to expect in the last 10 years. You can go and pick any kind of platform on which you want to run the same stack. You won't need to worry about it. Something similar that needs to happen and the underlying architecture of technology which will go and drive that is going to be data mobility, same control plane that can go and extend this smarty cloud. This story by the way resonates very very well with the customers because it's not easy to get your IT for support, to get trained on different cloud technologies also because the talent things cost there. And if you can go and teach them one interface and have them run with the choice of infrastructure or the back form or the cloud, that's what we think we can make a huge difference for the customers. >> Yeah, so I want to make sure I understand when talking about your hybrid or multicloud strategy, we've got Xi Clusters help you get in and matches what you have on sight. Have you had a conversation about Kubernetes yet? Where does Carbon which is the Nutanix Kubernetes fit into this overall discussion? Is that just part of the platform that gets baked in and therefore we don't need to talk about it or am I missing a piece? >> That's a great question because the beauty of what we're talking about is that we bring the entire software and the entire platform with us wherever we go. Part of that stack is carbon and calm. We need the ability to have both traditional applications alongside modern applications with Kubernetes. Even hybrid applications that include some front end that might be containerized, maybe back end that is not yet containerized. And all that, everything that we've been doing on-prem, can now be moved into any other public cloud we provide. >> It's part of the compute, right? You got the VMs, now you got the containers. It's part of the backbone. >> So yeah, we've heard from some people say that Kubernetes is just the new containerized compute. We don't need to talk about it and I'm okay with that, because it's just in there. >> Yes. Absolutely. >> Excellent. Well Gil and Manoj, thank you so much for coming on theCUBE. >> Manoj: Thanks so much for hosting us. >> Gil: Thanks for having us. >> I'm Rebecca Knight for Stu Miniman. Stay tuned for more of theCUBE's live coverage of .Next. (Techno outro plays)

>> Announcer: Live from Miami Beach, Florida, it's theCUBE covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to Miami everybody. This is Dave Volante with Peter Burris and you're watching theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise, and we're here at VeeamON 2019 in Miami at the Fontainebleau Hotel. Raj Perumal is here. He's the CIO of Ducks Unlimited, Canada-based wetland and waterfowl conservation. Great to have you on theCUBE, thanks. >> Thank you. >> The keynote yesterday was awesome. You guys were talking about some of things that you're doing. We're going to get into that. You made a great statement. You said "the wetlands are the kidneys of the world." >> Raj: Yes. >> You know, explain that. >> (laughs) Sure, so, most people are very familiar with the Amazon rain forest, right? When you think about saving the planet and saving the environment, that's where everyone's mind or eyes go to, right? Well, wetlands are Mother Nature's way of essentially filtering water, stopping overland flooding, and so on. So, that's why we say they are the kidneys of the earth. >> Yeah, and so talk a little bit about the trends in the earth. It's been very challenging, right? I mean despite the great work that you're doing, you're still fighting this battle which sometimes might feel unwinnable. But give us the data, yeah. >> Absolutely, urban expansion, right? At the end of the day, you know as humans we're going across the planet. We're constantly building more cities, more parking lots, more everything, right? So wetlands are getting replaced with various things. Same thing with various resource mining, et cetera. Wetlands go away. So what Ducks Unlimited likes to do is adopt a no net loss policy. So what we do is we work closely with governments in various provinces across Canada. So if someone destroys an acre of wetlands, we can try and restore maybe four or ten acres for every one destroyed. It's better not to destroy it in the first place, but if it's going to happen, restore it somewhere else. >> Dave: So, some of the stats I saw. You've done 12,000 projects since you started this in the 1930's. 163.5 million acres that you have preserved. And as I say, still the wetlands loss is enormous. Is it not regulated to the point where public policy can help? >> Raj: Well, there's policy and there's law. And when it comes to Canada, there's policy but there's always exceptions. So what ends up happening is, you have these policies that say you can't do this, but then there's exception, exception, exception, exception. And usually corporations can get a way through some various exception and actually get through. Ducks Unlimited helped pass a law in Quebec not too long ago, so we actually have it in law in Quebec where it is actually being supported. >> So, the old adage that if you can't measure it, it doesn't get done. >> That's right. >> One of the most amazing things about some of these digital transformations is satellite imagery, other types of weather and related data, are making it possible to track typology in unbelievable minute detail. >> Absolutely. >> Peter: Now that's got to help you, but at the same time, it's got to really dramatically require a greater focal point on things like data protection. Especially since operational time series for wetlands is not measured in nanoseconds. It's measured in years. >> That's right. >> So you got to be able to use this technology to both enhance your mission right now, but also be able to show over time how things are changing. Have I got that right? >> That's absolutely correct. With climate change as an example, and yes, that's a real thing. With climate change, you're measuring, We want to keep data like over 30 years. And that's where we actually see true change. We're just talking about five, ten years. That's just weather, that's not climate change, right? So we need to keep that data. So yes, we have a whole GIS department, Geographical Information Systems, where we have satellite imagery, drone imagery of Canada, going years and years and years back. We have to keep all of that data and we can never get rid of it. >> So what does this mission have to do with Veeam? >> Sure, absolutely. So with all of that data, GIS data is very imagery intense. So think of it like x-rays or CAD. So it takes up a lot of space. So we have to back up that data. Every map has layers and layers and layers, so it's almost like a Google Maps for the environment. You can think of it that way. We run something called the Canadian Wetland Inventory. It's the largest inventory of wetlands, mapping of wetlands, in Canada. And we leave that as open data, so anyone can access the data and use it. So we use Veeam to back all of that up, and also to maintain our disaster recovery and so on for all our different operations. That's just one aspect of our operations, another big part, and you talked about the 12,000 projects we were doing. We started a division called conservation technology which is all about using technology to monitor the wetlands. So putting internet of things sensors out in the wetlands, gathering that data automatically through satellite and cellular networks, analyzing it with artificial intelligence and machine learning. Once we have that, we can get those insights, give them to our scientists or PhDs where the big minds can go and crunch that and go and look at it and go, okay, this is what's happening in the world. We need to back that data up too. And once again, going back to what I said before, we need to keep that data over long periods of time so we can actually see patterns and figure out what's going on with our planet. >> Do you do video on the ground as well? I mean, you're right Peter. With satellite imagery, you can get pretty minute detail. But then, like the ground truth, sometimes you got to go on the ground. . Are you capturing video on the ground? >> A little bit, not a lot. >> Dave: The changes in flora and fauna? Do you see that as useful in the future? Or is it just too much data or not as useful to sort of deploy those kind of cameras? >> I would love to be able to capture all of that data real-time. The problem with that is in Canada, our internet infrastructure is quite poor in the rural areas. In some places, you have better-than-dial-up speeds. That's it. So unfortunately, we can't bring that data back. So a lot of the times, we can't capture the video. But where we can, we do. >> Dave: Okay, but so you are putting sensors there and so talk more about that data. What are you doing with that data? Does that come back into a cloud? Yes, so we pull that into the cloud, Microsoft Azure, where we analyze it and do that AI and machine learning, and then spit it out from there. So we are in the hybrid cloud. So we have some stuff internally, some in the public cloud. A little mixture of everything. That's where Veeam comes into play. >> So I had a couple questions. One is on the data source side and one is on the data sync side, starting with the data sync. Certainly, climate scientists and others, folks who are looking at geopolitics and other types of things, are taking this kind of information and they're using it as a source for even more complex and advanced applications. Are you seeing communities evolve and emerge and evolve in response to the availability of your data? >> Absolutely, people are clamoring for more though. Everyone wants real-time data. A lot of our data is manually gathered at this point. We have people driving out to a specific project in the middle of nowhere, gathering the data manually, driving back and then uploading it because that's the only way we can do it. So, absolutely, we are seeing people wanting more use of it and making use of that data, but they want it live. They want it right now. We kind of live in an instant-on society, right? But once again, the challenges of rural areas kind of tie our hands. >> Well that was my second question. Do you see an opportunity to do crowdsourcing of video or other types of information? >> Absolutely. >> So is that becoming a way and are you using artificial intelligence? Start taking an extended number of data sources as people go out and take pictures of ducks, or whatever else it is, and then ingesting that into your system. Does that become part of the flow? >> Yeah, absolutely, so that kind of takes us back to the 1930's when Ducks first started. We had the key men of old that actually kind of stewarded their local areas for conservation. So, absolutely, we can use crowdsourcing in this day and age, and it's something we want to explore. We're not doing it yet, but we're getting there. >> How is your data pipeline? 1930's, you know the data, the data model in 1930's is a lot different than it is today. The keynote speaker today talked about the sort of bending of the innovation curve and how the next 20, 30, 40, 50 years we're going to see more change than we've ever seen before. We'll see. But the data model that you guys are doing, I mean at least in the last 10 years you've seen new technologies come out, new processes. How are you evolving that data model? >> It's more like data models. (laughs) For the various line of business because we do so many different things, right? But essentially what we're trying to do-- >> The big thing is keeping it all connected. Keeping it all in sync. Implementing things like master data management. We're a big partner with Dell Boomi for example. So we leverage them to move our data back and forth between all our systems, et cetera, while Veeam backs it up. So I would say it's hugely important to be continually pushing the envelope and how you move data and how you synchronize data, how you authenticate that data and how you verify that data. Especially in science, you want to make sure that it's not being tampered with. You got to make sure that the data is consistent and true. >> Raj, how long have you been in this role? >> At Ducks Unlimited? A little over two years, but in the industry, over 25. >> So Veeam at Ducks preceded you, is that right? >> No, I brought it in. >> Dave: So you brought it in? Talk about that. Why did you bring it in and what was going on before? Maybe tell us a before and after. >> Sure, absolutely. So I actually used to be on the reseller side of the business. I used to be a CIO for one of the larger IT consulting companies in Canada. And during my time there, I brought Veeam into the province of Manitoba and spent a lot of time with various different customers, putting Veeam into various different projects and company types. So lots of exposure to the product. So when I came into Ducks Unlimited Canada, I already came in knowing what was possible, and gave the existing backup product a shot because I didn't necessarily want to rip and replace everything on my team with the CIO coming in day one. >> Dave: New sheriff in town! Ugh, who's this guy? >> But when it wasn't doing exactly what I needed it to do, we decided to bring Veeam in and the rest is basically history. >> Talk more about that. What was the business impact of bringing-- >> Oh sure, absolutely, so before Veeam, we were spending over 40 hours a week just administering backups. >> Peter: 40 hours a week? >> Yeah, easily. And we have large data sets, and so as I was talking about in the keynote, with those large data sets, if you're doing a backup or a restore, especially a restore, if it fails, you can blow a day trying to get that data back. And so you've lost a day. So that's how you easily end up losing that much time. Especially with an organization where you have 27 locations across Canada, and 500 staff, and 4,500 volunteers all accessing this data in some way, shape, or form. So by moving to Veeam, all those tasks that we used to do before, just worked. Veeam always says "it just works." It's true. And so what ended up happening is stuff that was taking the team a week, all of a sudden was taking them minutes. Like literally minutes. And it's unbelievable. That FT, that full-time equivalent staff member all of a sudden becomes freed up to do the work I was talking about in conservation technology and other areas of our business. We're directly impacting science on the planet, so a lot more fun that just supporting regular IT. >> So you have that 40 hours, was arms and legs of the team? And how large was the team? >> 16. >> So six, zero? >> Raj: 16. >> 16! Okay, so it was 16, pieces of 16. Which a lot of times, people hear that and they're like oh, it's going to reduce jobs. I don't want to talk about that. But these guys must have hated that. That job, the 40 hours-- >> Absolutely, they're doing mund-numbing work, right? >> Dave: It's interruptive and-- >> Yeah, and so now they're doing a lot funner stuff, right? >> What funner stuff are they doing? >> Absolutely, so once again being involved directly with conservation technology and our IOT play and all of that AI and machine learning research. All the sexy stuff in IT that's happening now, right? So they're very happy. >> You guys got a pretty interesting IOT use case. So how, I'm curious as to, you know we've been watching various companies come in and announce their grand IOT strategies and say "Okay we're going to bring this box to the edge." What are your thoughts on IOT, the edge, all those sort of buzz words. How do you look at it from a practitioner and a customer standpoint? >> It's very much like building a mobile app. So, you know everyone says we need an app for their company, right? They don't know why they need an app. They just say they need an app. And then they go and build that app and then nothing happens with it, right? And then it all fails. IOT is much the same way. Internet of things, AI, machine learning, it's all the buzz words. But then you need to understand what you want to get out of it in the first place. Like where are you trying to go? What are you trying to do? What are you trying to accomplish? And then if IOT fits that, AI, machine learning, if that fits that, then great. And if it doesn't, then don't waste your time. That's my thought. >> So, specifically, what's your IOT strategy? What can you accomplish with edge? >> Absolutely, if we can get instant live data streaming into the cloud and actively analyzing it on the fly using cloud services like Azure, AI, machine learning IOT et cetera, or even Amazon services, a lot of different services out there. If we can do that on the fly and feed that into the Canadian Wetland Inventory that I was talking about before, using open data initiatives, we can now feed data to the planet about what's happening real-time to academia, to governments, et cetera, so they can make decisions with evidentiary-based statistics, right? Right now it's very hard for, this is why the fight over climate change, people go "There is such a thing." Other people go, "No there isn't", and this happens because there's not enough data available to the general public, right? So by having this open data and making it available to the general public, not just the scientific communities, I think that would go a long way to helping get support for these causes. >> That's awesome, changing the world. What are the skill sets you need to achieve that vision? Is it data science-heavy? Can you sort of outsource some of that? Is the tooling simplified enough now? Talk about that. >> It's a little bit of networking, little bit of data science, a lot of GIS, and a lot of old fashioned networking and talking to people, right? So that's really what makes up the team and allows us to do what we do. >> Are you hiring data scientists? >> Not at the moment, no. We have everyone we need. >> But you have data scientists on staff. >> Yes, exactly. Because even before the IOT thing, we have scientists on staff that do just that, right? It's just in the traditional sense, before that. >> So did you sort of create that role? Take somebody who's good in math and computers and stats and say "Hey, you're the data scientist now. Go do some training and make it happen." Or did you actually hire in a data scientist? >> We actually created that role, so we have numerous people that feed different aspects of that, but the main man that's actually running that for me is our right hand man and your manager of IT. He started as a biologist that became a GIS guy that became my manager of IT. So he has a little bit of experience in all these different areas and he's like the perfect person to run the conservation technology division for us. >> Cool. >> And he's here today. >> Oh really? So what do you think of VeeamOn? Have you been to previous Veeam shows? >> Yeah, most of them actually. >> Dave: Really? >> It's great, yeah. >> Oh, that's awesome, seeing the CIO crowd hang out with all us backup wonks. So, thoughts from the show, takeaways? >> Sure, absolutely. Well, first of all, if anyone isn't using Veeam, they should be using it already. I got to say that right now. So many people waste their time picking and choosing and hemming and hawing. Just use it, it just works. So please do that. You won't regret it whatsoever. Veeam has done some really great things. I love the announcements with Orchestrator in version 2 there, and some of the good things that are coming with the restore plans and the scopes, et cetera. And that's fantastic. So I think there's a lot of great things that Veeam is bringing to data management and data availability. >> Yeah, so they made a big deal out of being able to do restores from the backup corpus. Not having to go to a replicated chunk of data. Why is that important for you, and will you take advantage of that? >> It's just the speed. It's just the speed, so I don't have to bring it back from another place, right? It's just instant. >> Yeah, okay, so then you're going to use that other place for disaster recovery or just a second copy for just in case? >> Yup! >> But you've got basically a local copy that you can bring back instantaneously. Okay, great. And I presume that supports your sort of compressed RTO and RPO. Which, as long as I've been in this business, they've shrunk and shrunk and shrunk. >> Yup, that's right. >> Shrunk the RPO. Great, okay, I'll give you final words. Cool stuff you're working on, things you'd like to see our industry do better, you pick it. >> Sure, cool stuff we're working on. So, talking about what we're doing at Ducks Unlimited with IT and really kind of changing the shape of IT and how it's involved in science, and I talked about Wetland Inventory, that live data, et cetera. If we can build a model like that here, imagine what we can do across the world, right? I'd love to take that model and take it to other countries where they can do the same type of work, so altruistically, and share that data, that whole open data initiative, so other people can go and save wetlands. If we can get everyone working together that way, I think we'll all be better off. >> That's awesome, Raj, thank you so much for coming to theCUBE, sharing your insights and experiences. Appreciate it. All right, keep it right there buddy. We'll be back with our next guest. This is theCUBE live from VeeamON 2019 from Miami. We'll be right back.

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hello and welcome to this special cube conversation here in Palo Alto California cube headquarters I'm Jennifer echoes the cube our guest here is Megan Eisenberg CMO of a new hot company called trip actions formerly the CMO at MongoDB before that taki sign we've known each other some advisory boards great to see you yes great to see you as well so exciting new opportunity for you at trip actions just transitioned from MongoDB which by the way had great earnings they did what was the big secret to Mongo DB z earnings tell us well it's fresh and I think they're executing and their growth is amazing they're bringing their costs down I mean they're they've got product market fit their developers love them and so I'm proud and not surprised you're there for four years yeah transformed their go-to market so that fruits coming off the tree yes yeah it's exciting to see the you know process people technology all coming together and seeing them scale and do so well in the markets yes you know being here in 20 years living in California Palo Alto you see the rocket ships the ones that flame out the ones that make it and there's a pattern right when you start to see companies that are attracting talent ones that have pedigree VCS involved yeah raising the kind of rounds in a smart way where there's traction product market fit you kind of take special notice and one of the companies that you're now working for trip actions yes seems to have the parameters so it's off the pad it's going up its orbit or taking off you guys have really growing you got a new round of funding one hundred fifty million dollars yes unique application in a market that is waiting to be disrupted yes travel about company you work for transactions trip actions is a fast growing business travel platform we service customers like we work slack zoom box and we're growing we're adding 200 customers a month and it's amazing just to see these fast-growing companies right when they hit product market fit I think the keys are they've gotten a massive addressable market which we have 800 billion online travel they're solving a pain and they're disrupting a legacy the legacy providers that are out there we're three and a half years old and we are you know really focused on the customer experience giving you the choice that you want when you book making it easy down to six minutes not an hour to book something and we've got 24/7 support which not many can compete with you know it's interesting you know I look at these different ways of innovation especially SAS and mobile apps you know chapter one of this wave great economics yeah and once you get that unit economics visibility say great SAS efficacious happened but now we're kind of in a chapter two I think you guys kind of fit into this chapter to where it's not just SAS cuz you know we've seen travel sites get out there you book travel it's chapter two of SAS is about personalization you see machine learning you got cloud economics new ventures are coming out of the woodwork where you could take a unique idea innovate on it and disrupt a category that seems to be what you guys are doing talk about this new dynamic because this is not just another travel app when you guys are doing gets a unique angle on this applying some tech with the Corpse talked about that this chapter to kind of assess business I think when I think about chapter 2 I think about all the data that's out there I think about the machine learning I think about how we understand the user and personalize everything to them to make it frictionless and these apps that I love on my phone are because they they know what I want before I want it and I just took a trip to Dallas this week and the app knew I needed to check in it was one click told me my flight was delayed gave me options checked me in for my hotel I mean it was just amazing experience that I haven't seen before and it's really if you think about that that business travel trip there's 40 steps you have to do along the way there's got to be a way to make it easier because all we want to do is get to the business meeting and get back we don't want to deal with weather we don't want to deal with Hotel issues or flight changes and our app is specific to when you look at it you've got a chat 24/7 and someone's taking care of you that concierge service and we can do that because the amount of data we're looking at we're learning from it and we make it easier for travel manager half the people go rogue and don't even book through their travel solution it's because it's not tailored to them so this is the thing I want to get it so you guys aren't like a consumer app per se you have a specific unique target audience on this opportunity its travel management I'm I'm gonna date myself but back when I broke into the business they would have comes like Thomas Cook would handle all the travel for youlet Packard when I worked there in the 80s and you had these companies I had these contracts and they would do all the travel for the employees yes today it's hard to find that those solutions out there yes I would say it's hard to find one that you love and trip Actions has designed something that our travelers love and it is it's for business travel it's for your business trips it's taking care of your air your hotel your car your rail whatever you need and making sure that you can focus on the trip focus on getting there and not just the horrible experience we've all had it you travel a lot I traveled certainly back and forth to the East Coast and to take those problems away so I can focus on my business is what it's so just just look at this right so you guys are off to unicorn the funding great valuation growing like crazy got employees so people looking for jobs because they're hiring probably yeah but you're targeting not consumers to download the app it's for businesses that want to have company policies and take all that pressure off yes of the low so as a user can't buy myself can't just use the app or get I know you can Nano that's the the the whole thing is that as a user there's three things we're providing to one inventory and choice so you go and you know all the options you get the flight you want it's very clear and art we have a new storefront where it shows you what's in policy what's not so we've got that its ease of use it's booking quickly nobody wants to waste time dealing with this stuff right you want to go in booked quickly and then when you're on the trip you need 24/7 support because things go wrong airline travel gets cancelled weather happens you need to change something in your trip and so yes the user has the app on their phone can book it can you do it fast and can get support if they need it so stand alone usually can just use it as a consumer app but when you combine with business that's the magic that you guys see is that the opportunity yes I should say as a consumer as a business traveler so you're doing it through your company so I'm getting reimbursed for the companies the company is your customer yes the company's our customer is the traveler yes okay got it so if we want to have a travel desk in our company which we don't have yet yes it would we would sign up as a company and then all your employees would have the ease of use to book travel so what happens what's the sum of the numbers in terms of customers you have said 200 month-over-month yes we're over 1500 customers we're adding 200 a month we've got some significant growth it's amazing to see product market and the cost of the solution tell people $25 a booking and there's no add-on costs after that if you need to make as many changes as you need because of the trip calls on it you do it so basically per transaction yes well Little Feat one of our dollars yes okay so how do you guys see this growing for the company what's the some of the initiatives you guys are doing a new app yes mo what's what's the plan it's a massive market 800 billion right and we've only just started we've got a lot of customers but we've got many more to go after we are international so we have offices around the world we have an Amsterdam office we've got customers travelling all over so we're you know continuing to deliver on that experience and bringing on more customers we just on-boarded we were ten thousand travelers and will continue to onboard more and more so as head of marketing what's the current staff you have openings you mentioned yet some some some open recs yes yes hi are you gonna build out I've got 20 open Rex on the website so I'm hiring in all functions we're growing that fast and what's the marketing strategy what's your plan can you give it a little teaser on yes thinking core positioning go to market what are some of the things you're thinking about building out marketing CloudStack kind of thing what's what's going on all of these things my three top focuses are one marketing sales systems making sure we have that mark tech stack and that partnership with the sales tech stack second thing is marketing sales alignment that closed-loop we're building we're building pipeline making sure when people come in there's a perfect partnership to service what they need and then our our brand and messaging and it's the phase I love in these companies it's really building and it's the people process and technology to do that in the core positioning is what customer service being the most user-friendly what's the core position we're definitely focused on the traveler I would say we're we're balancing customer experience in making sure we get that adoption but also for the travel managers making sure that they can administer the solution and they get the adoption and we align the ascent in the incentives between the traveler and the travel manager and customer profile what small munis I business to large enterprise we have SMB and we're going all the way up to enterprise yes has it been much of a challenge out there in the business travel side I'm just don't know that's why I'm asking is like because we don't have one I can see our r-cube team having travel challenge we always do no centralizing that making that available but it'd have to be easier is it hard to get is there a lot of business travel firms out there is what are some of the challenges that you guys are going after there well I I think what matters is one picking the solution and being able to implement it quickly we have customers implementing in a week right it's understanding how we load your policies get you on board get your cut you're you're really your employees traveling and so it's pretty fast onboarding and we're able to tailor solutions to what people need what are some of the policies that are typical that might be out there that people like yeah so maybe for hotels you may have New York and your your policy is $500 a night what the I would say a normal typical behavior would someone would book it at $4.99 they go all the way up to the limit we've actually aligned our incentives with the travel managers and the employees and that if you save your company money you save and get rewards back so let's say you book it for 400 that $100 savings $30 goes back to the employee and rewards they can get an Amazon card donate to Cherry charity whatever they'd like to kind of act like an owner cuz they get a kickback yes that's the dot so that's how you an interest adoption yes what other adoption concerns you guys building around with the software and or programs to make it easy to use and we're constantly thinking about the experience we want to make sure just I mean I think about what I used to drive somewhere I'd pull out a map and map it out and then I got lucky and you could do MapQuest and now you have ways we are that ways experience when you're traveling we're thinking about everything you need to do that customer when they leave their front door all the way to the trip all the things that can hang them up along the way we're trying to remove that friction that's a very example I mean Waze is a great service yes these Google Maps or even Apple Maps ways everyone goes to backed away yes yeah I don't I mean ways did cause a lot of Street congestion the back streets of Palo Alto we're gonna expedite our travelers well it's a great utility new company what what attracted you to the opportunity when was some of the because you had a kid going over there MongoDB what it was the yeah motivation to come over to the hot startup yeah you know I love disruptive companies I love massive addressable markets good investors and a awesome mission that I can get behind you know I'm a mom of three kids and I did a lot of travel I'm your typical road warrior and I wanted to get rid of the pain of travel and the booking systems that existed before trip actions and so I was drawn to the team the market and the product that's awesome well you've been a great CMO your career has been phenomenal of great success as a CPM mother of three you know the challenges of juggling all this life is short you got to be using these apps to make sure you get on the right plane I mean I know I'm always getting back for my son's lacrosse game or yes event at school this is these are like it's like ways it's not necessary in the travel portfolio but it's a dynamic that the users care about this is the kind of thing that you guys are thinking about is that right yeah definitely I mean I always think about my mom when she worked in having three daughters and I work and have three daughters I feel like I can do so much more I've got door - I've got urban sitter I've got ways I've got Google Calendar I've got trip actions right I've got all these technologies that allow me to do more and not focus on things that are not that productive and I have no value add on it just makes me more efficient and productive how about some of the tech before we get in some of the industry questions I want to talk about some of the advantages on the tech side is there any machine learning involved what's some what's not what's some of the secret sauce and the app yeah definitely we're constantly learning our users preferences so when you go in we start to learn what you what hotels you're gonna select what where do you like to be near the office do you like to be near downtown we're looking at your flights do aisle window nobody wants middle yes but we're we're learning about your behaviors and we can predict pretty closely one if you're gonna book and two what you're gonna book and as we continue learning you that's why we make you more efficient that's why we can do it in six minutes instead of an hour that's awesome so Megan a lot of things going on you've been a progressive marker you love Terry's tech savvy you've done a lot of implementations but we're in a sea change now where you know people that think differently they gonna think okay I need to be on an app for your case with with business travel it's real policies there so you want to also make it good for the user experience again people centric this personalization has been kind of a cutting edge concept now in this chapter to a lot of CMOS are either they're they're not are trying to get there what are you finding in the industry these days that's a best practice to help people cross that bridge as they think they cracked the code on one side then realize wow it's a whole another chapter to go you know I think traditionally a lot of times we think we need we're aligning very much with sales and that matters that go to market marketing sales aligned but when it comes to products and a customer experience it's that alignment with marketing and the product and engineering team and really understanding the customer and what they want and listening and hearing and testing and and making sure we're partnering in those functions in terms of distribution getting the earned concept what's your thoughts on her and media yeah I mean I definitely think it's the direction right there's a ton of noise out there so you've got to be on topic you've got to understand what people care about you've got to hit them in the channel that they care about and very quick right is you don't have time nobody's gonna watch something that's 30 minutes long you get seconds and so part of the earned is making sure you're relevant you what they care about and they can find you and content big part of that for you guys huge part of it yes and understanding the influencers in the market who's talking about travel who's who is out there leading ahead you know leading in these areas that travel managers go and look to you know making sure we're in front of them and they get to see what we're delivering I like how you got the incentives of the employees to get kind of a line with the business I mean having that kind of the perks yes if you align with the company policies the reward could be a Starbucks card or vacation one more time oh whatever they the company want this is kind of the idea right yeah they kind of align the incentives and make the user experience both during travel and post travel successful that's right yes making sure that they are incented to go but they have a great experience okay if you explain the culture of the company to someone watching then maybe interested in using the app or buying you guys as a team what's the trip actions culture like if you had to describe it yeah I would say one we love travel too we are fast growing scaling and we're always raising the bar and so it's learning and it's moving fast but learning from it and continually to improve it's certainly about the user all of the users so not just the travel manager but our travelers themselves we love dogs if you ever come to the Palo Alto office we've got a lot of dogs we love our pups and just you know building something amazing and it's hard to be the employees gonna know that's a rocket ship so it's great get a hold on you got a run hard yes that's the right personality to handle the pace because you're hiring a lot of people and I think that's a part of the learning we need continual learning because we are scaling so fast you have to reinvent what we need to do next and not a lot of people have seen that type of scale and in order to do it you have to learn and help others learn and move fast well great to see you thanks for coming in and sharing the opportunity to give you the final plug for the company share what who you what positions you're hiring for what's your key hires what are you guys trying to do give a quick plug to the company yeah so I mean we've grown 5x and employees so we're hiring across the board from a marketing standpoint I'm hiring in content and product marketing I'm hiring designers I'm hiring technical I you know I love my marketing technology so we're building out our tech stack our website pretty much any function all right you heard it here trip actions so when you get the product visibility those unit economics as they say in the VC world they've got a rocket ship so congratulations keep it up yeah now you're in palo alto you can come visit us here anytime yes love to Meagen Eisenberg CMO trip access here inside the cube I'm John Ferrier thanks for watching you [Music]

>> Live from Washington, D.C., it's theCUBE! Covering Inforum D.C. 2018. Brought to you by Infor. >> Well, welcome back to Washington, D.C., We are alive here at the Convention Center at Inforum 18, along with Dave Vellante, I'm John Walls. It's a pleasure now, welcome to theCUBE, Leigh Martin, who is the Senior Director of the Dynamic Science Labs at Infor, and good afternoon to you Leigh! >> Good afternoon, thank you for having me. >> Thanks for comin' on. >> Thank you for being here. Alright, well tell us about the Labs first off, obviously, data science is a big push at Infor. What do you do there, and then why is data science such a big deal? >> So Dynamic Science Labs is based in Cambridge, Massachusetts, we have about 20 scientists with backgrounds in math and science areas, so typically PhDs in Statistics and Operations Research, and those types of areas. And, we've really been working over the last several years to build solutions for Infor customers that are Math and Science based. So, we work directly with customers, typically through proof of concept, so we'll work directly with customers, we'll bring in their data, and we will build a solution around it. We like to see them implement it, and make sure we understand that they're getting the value back that we expect them to have. Once we prove out that piece of it, then we look for ways to deliver it to the larger group of Infor customers, typically through one of the Cloud Suites, perhaps functionality, that's built into a Cloud Suite, or something like that. >> Well, give me an example, I mean it's so, as you think-- you're saying that you're using data that's math and science based, but, for application development or solution development if you will. How? >> So, I'll give you an example, so we have a solution called Inventory Intelligence for Healthcare, it's moving towards a more generalized name of Inventory Intelligence, because we're going to move it out of the healthcare space and into other industries, but this is a product that we built over the last couple of years. We worked with a couple of customers, we brought in their loss and data, so their loss in customers, we bring the data into an area where we can work on it, we have a scientist in our team, actually, she's one of the Senior Directors in the team, Dawn Rose, who led the effort to design and build this, design and build the algorithm underlying the product; and what it essentially does is, it allows hospitals to find the right level of inventory. Most hospitals are overstocked, so this gives them an opportunity to bring down their inventory levels, to a manageable place without increasing stockouts, so obviously, it's very important in healthcare, that you're not having a lot of stockouts. And so, we spent a lot of time working with these customers, really understanding what the data was like that they were giving to us, and then Dawn and her team built the algorithm that essentially says, here's what you've done historically, right? So it's based on historic data, at the item level, at the location level. What've you done historically, and how can we project out the levels you should have going forward, so that they're at the right level where you're saving money, but again, you're not increasing stockouts, so. So, it's a lot of time and effort to bring those pieces together and build that algorithm, and then test it out with the customers, try it out a couple of times, you make some tweaks based on their business process and exactly how it works. And then, like I said, we've now built that out into originally a stand-alone application, and in about a month, we're going to go live in Cloud Suite Financials, so it's going to be a piece of functionality inside of Cloud Suite Financials. >> So, John, if I may, >> Please. >> I'm going to digress for a moment here because the first data scientist that I ever interviewed was the famous Hilary Mason, who's of course now at Cloudera, but, and she told me at the time that the data scientist is a part mathematician, part scientist, part statistician, part data hacker, part developer, and part artist. >> Right. (laughs) >> So, you know it's an amazing field that Hal Varian, who is the Google Economist said, "It's going to be the hottest field, in the next 10 years." And this is sort of proven true, but Leigh, my question is, so you guys are practitioners of data science, and then you bring that into your product, and what we hear from a lot of data scientists, other than that sort of, you know, panoply of skill sets, is, they spend more time wrangling data, and the tooling isn't there for collaboration. How are you guys dealing with that? How has that changed inside of Infor? >> It is true. And we actually really focus on first making sure we understand the data and the context of the data, so it's really important if you want to solve a particular business problem that a customer has, to make sure you understand exactly what is the definition of each and every piece of data that's in all of those fields that they sent over to you, before you try to put 'em inside an algorithm and make them do something for you. So it is very true that we spend a lot of time cleaning and understanding data before we ever dive into the problem solving aspect of it. And to your point, there is a whole list of other things that we do after we get through that phase, but it's still something we spend a lot of time on today, and that has been the case for, a long time now. We, wherever we can, we apply new tools and new techniques, but actually just the simple act of going in there and saying, "What am I looking at, how does it relate?" Let me ask the customer to clarify this to make sure I understand exactly what it means. That part doesn't go away, because we're really focused on solving the customer solution and then making sure that we can apply that to other customers, so really knowing what the data is that we're working with is key. So I don't think that part has actually changed too much, there are certainly tools that you can look at. People talk a lot about visualization, so you can start thinking, "Okay, how can I use some visualization to help me understand the data better?" But, just that, that whole act of understanding data is key and core to what we do, because, we want to build the solution that really answers the answers the business problem. >> The other thing that we hear a lot from data scientists is that, they help you figure out what questions you actually have to ask. So, it sort of starts with the data, they analyze the data, maybe you visualize the data, as you just pointed out, and all these questions pop out. So what is the process that you guys use? You have the data, you've got the data scientist, you're looking at the data, you're probably asking all these questions. You get, of course, get questions from your customers as well. You're building models maybe to address those questions, training the models to get better and better and better, and then you infuse that into your software. So, maybe, is that the process? Is it a little more complicated than that? Maybe you could fill in the gaps. >> Yeah, so, I, my personal opinion, and I think many of my colleagues would agree with me on this is, starting with the business problem, for us, is really the key. There are ways to go about looking at the data and then pulling out the questions from the data, but generally, that is a long and involved process. Because, it takes a lot of time to really get that deep into the data. So when we work, we really start with, what's the business problem that the customer's trying to solve? And then, what's the data that needs to be available for us to be able to solve that? And then, build the algorithm around that. So for us, it's really starting with the business problem. >> Okay, so what are some of the big problems? We heard this morning, that there's a problem in that, there's more job openings than there are candidates, and productivity, business productivity is not being impacted. So there are two big chewy problems that data scientists could maybe attack, and you guys seem to be passionate about those, so. How does data science help solve those problems? >> So, I think that, at Infor, I'll start off by saying at Infor there's actually, I talked about the folks that are in our office in Cambridge, but there's quite a bit of data science going on outside of our team, and we are the data science team, but there are lots of places inside of Infor where this is happening. Either in products that contains some sort of algorithmic approach, the HCM team for sure, the talent science team which works on HCM, that's a team that's led by Jill Strange, and we work with them on certain projects in certain areas. They are very focused on solving some of those people-related problems. For us, we work a little bit more on the, some of the other areas we work on is sort of the manufacturing and distribution areas, we work with the healthcare side of things, >> So supply chain, healthcare? >> Exactly. So some of the other areas, because they are, like I said, there are some strong teams out there that do data science, it's just, it's also incorporated with other things, like the talent science team. So, there's lots of examples of it out there. In terms of how we go about building it, so we, like I was saying, we work on answering the business, the business question upfront, understanding the data, and then, really sitting with the customer and building that out, and, so the problems that come to us are often through customers who have particular things that they want to answer. So, a lot of it is driven by customer questions, and particular problems that they're facing. Some of it is driven by us. We have some ideas about things that we think, would be really useful to customers. Either way, it ends up being a customer collaboration with us, with the product team, that eventually we'll want to roll it out too, to make sure that we're answering the problem in the way that the product team really feels it can be rolled out to customers, and better used, and more easily used by them. >> I presume it's a non-linear process, it's not like, that somebody comes to you with a problem, and it's okay, we're going to go look at that. Okay now, we got an answer, I mean it's-- Are you more embedded into the development process than that? Can you just explain that? >> So, we do have, we have a development team in Prague that does work with us, and it's depending on whether we think we're going to actually build a more-- a product with aspects to it like a UI, versus just a back end solution. Depends on how we've decided we want to proceed with it. so, for example, I was talking about Inventory Intelligence for Healthcare, we also have Pricing Science for Distribution, both of those were built initially with UIs on them, and customers could buy those separately. Now that we're in the Cloud Suites, that those are both being incorporated into the Cloud Suite. So, we have, going back to where I was talking about our team in Prague, we sometimes build product, sort of a fully encased product, working with them, and sometimes we work very closely with the development teams from the various Cloud Suites. And the product management team is always there to help us, to figure out sort of the long term plan and how the different pieces fit together. >> You know, kind of big picture, you've got AI right, and then machine learning, pumping all kinds of data your way. So, in a historical time frame, this is all pretty new, this confluence right? And in terms of development, but, where do you see it like 10 years from now, 20 years from now? What potential is there, we've talked about human potential, unlocking human potential, we'll unlock it with that kind of technology, what are we looking at, do you think? >> You know, I think that's such a fascinating area, and area of discussion, and sort of thinking, forward thinking. I do believe in sort of this idea of augmented intelligence, and I think Charles was talking a little bit about, about that this morning, although not in those particular terms; but this idea that computers and machines and technology will actually help us do better, and be better, and being more productive. So this idea of doing sort of the rote everyday tasks, that we no longer have to spend time doing, that'll free us up to think about the bigger problems, and hopefully, and my best self wants to say we'll work on famine, and poverty, and all those problems in the world that, really need our brains to focus on, and work. And the other interesting part of it is, if you think about, sort of the concept of singularity, and are computers ever going to actually be able to think for themselves? That's sort of another interesting piece when you talk about what's going to happen down the line. Maybe it won't happen in 10 years, maybe it will never happen, but there's definitely a lot of people out there, who are well known in sort of tech and science who talk about that, and talk about the fears related to that. That's a whole other piece, but it's fascinating to think about 10 years, 20 years from now, where we are going to be on that spectrum? >> How do you guys think about bias in AI and data science, because, humans express bias, tribalism, that's inherent in human nature. If machines are sort of mimicking humans, how do you deal with that and adjudicate? >> Yeah, and it's definitely a concern, it's another, there's a lot of writings out there and articles out there right now about bias in machine learning and in AI, and it's definitely a concern. I actually read, so, just being aware of it, I think is the first step, right? Because, as scientists and developers develop these algorithms, going into it consciously knowing that this is something they have to protect against, I think is the first step, for sure. And then, I was just reading an article just recently about another company (laughs) who is building sort of a, a bias tracker, so, a way to actually monitor your algorithm and identify places where there is perhaps bias coming in. So, I do think we'll see, we'll start to see more of those things, it gets very complicated, because when you start talking about deep learning and networks and AI, it's very difficult to actually understand what's going on under the covers, right? It's really hard to get in and say this is the reason why, your AI told you this, that's very hard to do. So, it's not going to be an easy process but, I think that we're going to start to see that kind of technology come. >> Well, we heard this morning about some sort of systems that could help, my interpretation, automate, speed up, and minimize the hassle of performance reviews. >> Yes. (laughs) >> And that's the classic example of, an assertive woman is called abrasive or aggressive, an assertive man is called a great leader, so it's just a classic example of bias. I mentioned Hilary Mason, rock star data scientist happens to be a woman, you happen to be a woman. Your thoughts as a woman in tech, and maybe, can AI help resolve some of those biases? >> Yeah. Well, first of all I want to say, I'm very pleased to work in an organization where we have some very strong leaders, who happen to be women, so I mentioned Dawn Rose, who designed our IIH solution, I mentioned Jill Strange, who runs the talent science organization. Half of my team is women, so, particularly inside of sort of the science area inside of Infor, I've been very pleased with the way we've built out some of that skill set. And, I'm also an active member of WIN, so the Women's Infor Network is something I'm very involved with, so, I meet a lot of people across our organization, a lot of women across our organization who have, are just really strong technology supporters, really intelligent, sort of go-getter type of people, and it's great to see that inside of Infor. I think there's a lot of work to be done, for sure. And you can always find stories, from other, whether it's coming out of Silicon Valley, or other places where you hear some, really sort of arcane sounding things that are still happening in the industry, and so, some of those things it's, it's disappointing, certainly to hear that. But I think, Van Jones said something this morning about how, and I liked the way he said it, and I'm not going to be able say it exactly, but he said something along the lines of, "The ground is there, the formation is starting, to get us moving in the right direction." and I think, I'm hopeful for the future, that we're heading in that way, and I think, you know, again, he sort of said something like, "Once the ground swell starts going in that direction, people will really jump in, and will see the benefits of being more diverse." Whether it's across, having more women, or having more people of color, however things expand, and that's just going to make us all better, and more efficient, and more productive, and I think that's a great thing. >> Well, and I think there's a spectrum, right? And on one side of the spectrum, there's intolerable and unacceptable behavior, which is just, should be zero tolerance in my opinion, and the passion of ours in theCUBE. The other side of that spectrum is inclusion, and it's a challenge that we have as a small company, and I remember having a conversation, earlier this year with an individual. And we talk about quotas, and I don't think that's the answer. Her comment was, "No, that's not the answer, you have to endeavor to reach deeper beyond your existing network." Which is hard sometimes for us, 'cause you're so busy, you're running around, it's like okay it's the convenient thing to do. But you got to peel the onion on that network, and actually take the extra time and make it a priority. I mean, your thoughts on that? >> No, I think that's a good point, I mean, if I think about who my circle is, right? And the people that I know and I interact with. If I only reach out to the smallest group of people, I'm not getting really out beyond my initial circle. So I think that's a very good point, and I think that that's-- we have to find ways to be more interactive, and pull from different areas. And I think it's interesting, so coming back to data science for a minute, if you sort of think about the evolution of where we got to, how we got to today where, now we're really pulling people from science areas, and math areas, and technology areas, and data scientists are coming from lots of places, right? And you don't always have to have a PhD, right? You don't necessary have to come up through that system to be a good data scientist, and I think, to see more of that, and really people going beyond, beyond just sort of the traditional circles and the traditional paths to really find people that you wouldn't normally identify, to bring into that, that path, is going to help us, just in general, be more diverse in our approach. >> Well it certainly it seems like it's embedded in the company culture. I think the great reason for you to be so optimistic going forward, not only about your job, but about the way companies going into that doing your job. >> What would you advise, young people generally, who want to crack into the data science field, but specifically, women, who have clearly, are underrepresented in technology? >> Yeah, so, I think the, I think we're starting to see more and more women enter the field, again it's one of those, people know it, and so there's less of a-- because people are aware of it, there's more tendency to be more inclusive. But I definitely think, just go for it, right? I mean if it's something you're interested in, and you want to try it out, go to a coding camp, and take a science class, and there's so many online resources now, I mean there's, the massive online courses that you can take. So, even if you're hesitant about it, there are ways you can kind of be at home, and try it out, and see if that's the right thing for you. >> Just dip your toe in the water. >> Yes, exactly, exactly! Try it out and see, and then just decide if that's the right thing for you, but I think there's a lot of different ways to sort of check it out. Again, you can take a course, you can actually get a degree, there's a wide range of things that you can do to kind of experiment with it, and then find out if that's right for you. >> And if you're not happy with the hiring opportunities out there, just start a company, that's my advice. >> That's right. (laughing together) >> Agreed, I definitely agree! >> We thank you-- we appreciate the time, and great advice, too. >> Thank you so much. >> Leigh Martin joining us here at Inforum 18, we are live in Washington, D.C., you're watching the exclusive coverage, right here, on theCUBE. (bubbly music)