(upbeat music) >> Good afternoon, everyone. Welcome back to the CUBE's day one coverage of VMware Explorer 22, live from San Francisco. I'm Lisa Martin. Dave Nicholson is back with me. Welcome back to the set. We're pleased to welcome William Bell as our next guest. The executive vice president of products at Phoenix NAP. William, welcome to the CUBE. Welcome back to the CUBE. >> Thank you, thank you so much. Happy to be here. >> Talk to us a little, and the audience a little bit about Phoenix NAP. What is it that you guys do? Your history, mission, value prop, all that good stuff. >> Absolutely, yeah. So we're global infrastructures as a service company, foundationally, we are trying to build pure play infrastructure as a service, so that customers that want to adopt cloud infrastructure but maybe don't want to adopt platform as a service and really just, you know, program themselves to a specific API can have that cloud adoption without that vendor lock in of a specific platform service. And we're doing this in 17 regions around the globe today. Yeah, so it's just flexible, easy. That's where we're at. >> I like flexible and easy. >> Flexible and easy. >> You guys started back in Phoenix. Hence the name. Talk to us a little bit about the evolution of the company in the last decade. >> Yeah, 100%. We built a data center in Phoenix expecting that we could build the centralized network access point of Phoenix, Arizona. And I am super proud to say that we've done that. 41 carriers, all three hyperscalers in the building today, getting ready to expand. However, that's not the whole story, right. And what a lot of people don't know is we founded an infrastructure as a service company, it's called Secured Servers no longer exists, but we founded that company the same time and we built it up kind of sidecar to Phoenix NAP and then we merged all of those together to form this kind of global infrastructure platform that customers can consume. >> Talk to us about the relationship with VMware. Obviously, here we are at VMware Explore. There's about seven... We're hearing 7,000 to 10,000 people here. People are ready to be back to hear from VMware and it's partner ecosystem. >> Yeah, I mean, I think that we have this huge history with VMware that maybe a lot of people don't know. We were one of the first six, the SPPs in 2011 at the end of the original kind of data center, whatever, vCloud data center infrastructure thing that they did. And so early on, there was only 10 of us, 11 of us. And most of those names don't exist anymore. We're talking, Terramark, Blue Lock, some of these guys. Good companies, but they've been bought or whatnot. And here's plucky Phoenix NAP, still, you know, offering great VMware cloud services for customers around the globe. >> What are some of the big trends that you're seeing in the market today where customers are in this multi-cloud world? You know this... I love the theme of this event. The center of the multi-cloud universe. Customers are in that by default. How do you help them navigate that and really unlock the value of it? >> Yeah, I think for us, it's about helping customers understand what applications belong where. We're very, very big believers both in the right home. But if you drill down on that right home for right applicator or right application, right home, it's more about the infrastructure choices that you're making for that application leads to just super exciting optimizations, right. If you, as an example, have a large media streaming business and you park it in a public called hyperscaler and you just eat those egress fees, like it's a big deal. Right? And there are other ways to do that, right. If you need a... If your application needs to scale from zero cores to 15,000 cores for an hour, you know, there are hyperscalers for that, right. And people need to learn how to make that choice. Right app, right home, right infrastructure. And that's kind of what we help them do. >> It's interesting that you mentioned the concept of being a pure play in infrastructure as a service. >> Yeah. >> At some point in the past, people would have argued that infrastructure as a service only exists because SaaS isn't good enough yet. In other words, if there's a good enough SaaS application then you don't want IaaS because who wants to mess around with IaaS, infrastructures as a service. Do you have customers who look at what they're developing as so much a core of what their value proposition is that they want to own it? I mean, is that a driving factor? >> I would challenge to say that we're seeing almost every enterprise become a SaaS company. And when that transition happens, SaaS companies actually care a lot about the cost basis, efficiency, uptime of their application. And ultimately, while they don't want to be in the data center business anymore, it doesn't mean that they want to pay someone else to do things that they feel wholly competent in doing. And we're seeing this exciting transition of open source technologies, open source platforms becoming good enough that they don't actually have to manage a lot of things. They can do it in software and the hardware's kind of abstracted. But that actually, I would say is a boon for infrastructure as a service, as an independent thing. It's been minimized over the years, right. People talk about hyperscalers as being cloud infrastructure companies and they're not. They're cloud platform companies, right. And the infrastructure is high quality. It is easy to access and scale, right, but it's ultimately, if you're just using one of those hyperscalers for that infrastructure, building VMs and doing a bunch of things yourself, you're not getting the value out of that hyperscaler. And ultimately that infrastructure's very expensive if you look at it that way. >> So it's interesting because if you look at what infrastructure consists of, which is hardware and software-- >> Yeah. >> People who said, eh, IaaS as is just a bridge to a bright SaaS future, people also will make the argument that the hardware doesn't matter anymore. I imagine that you are doing a lot of optimization with both hardware and stuff like the VMware cloud stack that you deploy as a VCPP partner. >> Absolutely, yeah. >> So to talk about that. >> Absolutely. >> I mean, you agree. I mean, if I were to just pose a question to you, does hardware still matter? Does infrastructure still matter? >> Way more than people think. >> Well, there you go. So what are you doing in that arena, specifically with VCPP? >> Yeah, absolutely. And so I think a good example of that, right, so last VMworld in person, 2019, we showcased a piece of technology that we had been working with Intel on for about two years at the time which was Intel persistent memory DC, persistent memory. Right? And we launched the first VMware cloud offering to have Intel DC persistent memory onboard. So that customers with the VMs that needed that technology could leverage it with the integrations in vSphere 6.7 and ultimately in seven more, right. Now I do think that was maybe a swing and a miss technology potentially but we're going to see it come back. And that specialized infrastructure deployment is a big part of our business, right. Helping people identify, you know, this application, if you'd have this accelerator, this piece of infrastructure, this quality of network can be better, faster, cheaper, right. That kind of mentality of optimization matters a lot. And VMware plays a critical role in that because it still gives the customer the operational excellence that they need without having to do everything themselves, right. And our customers rely on that a lot from VMware to get that whole story, operationally efficient, easy to manage, automated. All those things make a lot of difference to our VMware customers. >> Speaking of customers, what are you hearing, if anything, from customers, VMware customers that are your joint customers about the Broadcom acquisition? Are they excited about it? Are they concerned about it? And how do you talk about that? >> Yeah, I mean, I think that everyone that's in the infrastructure business is doing business with Broadcom, all right. And we've had so many businesses that we've been engaged with that have ultimately been a acquiree. I can say that this one feels different only in the size of the acquisition. VMware carries so much weight. VMware's brand exceeds Broadcom's brand, in my opinion. And I think ultimately, I don't know anything that's not public, right-- >> Well, they rebranded. By the way, on the point of brand, they rebranded their software business, VMware. >> Yeah. I mean, that's what I was going to say. That was the word on the street. I don't know if there's beneficial. Is that a-- >> Well, that's been-- >> But that's the word, right? >> That's what they've said. Well, but when a Avago acquired Broadcom they said, "we'll call ourselves Broadcom." >> Absolutely. Why wouldn't you? >> So yeah. So I imagine that what's been reported is likely-- >> Likely. Yeah, I 100% agree. I think that makes a ton of sense and we can start to see even more great intellectual property in software. That's where, you know, all of these businesses, CA, Symantec, VMware and all of the acquisitions that VMware has made, it's a great software intellectual property platform and they're going to be able to get so much more value out of the leadership team that VMware has here, is going to make a world of difference to the Broadcom software team. Yeah, so I'm very excited, you know. >> It's a lot of announcements this morning, a lot of technical product announcements. What did you hear in that excites you about the evolution of VMware as well as the partnership and the value in it for your customers? >> You know, one of our fastest growing parts of our business is this metal as a service infrastructure business and doing very, very... Using very specific technologies to do very interesting things, makes a big difference in our world and for our customers. So anything that's like smartNICs, disaggregated hypervisor, accelerators as a first class citizen in VMware, all that stuff makes the Phoenix NAP story better. So I'm super excited about that, right. Yeah. >> Well, it's interesting because VCPP is not a term that people who are not insiders know of. What they know is that there are services available in hyperscale cloud providers where you can deploy VMware. Well, you know, VMware cloud stack. Well, you can deploy those VMware cloud stacks with you. >> Absolutely. >> In exactly the same manner. However, to your point, all of this talk about disaggregation of CPU, GPU, DPU, I would argue with it, you're in a better position to deploy that in an agile way than a hyperscale cloud provider would be and foremost, I'm not trying to-- >> No, yeah. >> I'm not angling for a job in your PR department. >> Come on in. >> But the idea that when you start talking about something like metal as a service, as an adjunct or adjacent to a standard deployment of a VMware cloud, it makes a lot of sense. >> Yeah. >> Because there are people who can't do everything within the confines of what the STDC-- >> Yes. >> Consists of. >> Absolutely. >> So, I mean... Am I on the right track? >> No, you are 100% hitting it. I think that that point you made about agility to deliver new technology, right, is a key moment in our kind of delivery every single year, right. As a new chip comes out, Intel chip or Accelerator or something like that, we are likely going to be first to market by six months potentially and possibly ever. Persistent memory never launched in public cloud in any capacity but we have customers running on it today that is providing extreme value for their business, right. When, you know, the discreet GPUs coming from the just announced Flex series GPU from Intel, you're likely not going to see them in public cloud hyperscalers quickly, right. Over time, absolutely. We'll have them day one. Isolate came out, you could get it in our metal as a service platform the morning it launched on demand, right. Those types of agility points, they're not... Because they're hyperscale by nature. If they can't hyperscale it, they're not doing it, right. And I think that that is a very key point. Now, as it comes in towards VMware, we're driving this intersection of building that VCF or VMware cloud foundation which is going to be a key point of the VMware ecosystem. As you see this transition to core based licensing and some of the other things that have been talked about, VMware cloud foundation is going to be the stack that they expect their customers to adopt and deliver. And the fact that we can automate that, deliver it instantaneously in a couple of hours to hardware that you don't need to own, into networks you don't need to manage, but yet you are still in charge, keys to the kingdom, ready to go, just like you're doing it in your own data center, that's the message that we're driving for. >> Can you share a customer example that you think really just shines a big flashlight on the value that you guys are delivering? >> We definitely, you know, we had the pleasure of working with Make-A-Wish foundation for the last seven years. And ultimately, you know, we feel very compelled that every time we help them do something unique, different or what not, save money, that money's going into helping some child that's in need, right. And so we've done so many things together. VMware has stepped up as the plate over the years, done so many things with them. We've sponsored stuff. We've done grants, we've done all kinds of things. The other thing I would say is we are helping the City of Hope and Translational Genomics Research Institute on sequencing single cell RNA so that they can fight COVID, so that they can build cure, well, not cures but build therapies for colon cancer and things like that. And so I think that, you know, this is a driving light for us internally is helping people through efficiency and change. And that's what we're looking for. We're looking for more stories like that. We're looking... If you have a need, we're looking for people to come to us and say, "this is my problem. This is what this looks like. Let us see if we can find a solution that's a little bit different, a little bit out of the box and doesn't have to change your business dramatically." Yeah. >> And who are you talking to within customers? Is this a C level conversation? >> Yeah, I mean, I would say that we would love it to be... I think most companies would love to have that, you know, CFO conversation with every single customer. I would say VPs of engineering, increasingly, especially as we become more API centric, those guys are driving a lot of those purchasing decisions. Five years ago, I would've said director of IT, like director of IT. Now today, it's like VP of engineering, usually software oriented folks looking to deliver some type of application on top of a piece of hardware or in a cloud, right. And those guys are, you know, I guess, that's even another point, VMware's doing so much work on the API side that they don't get any credit for. Terraform, Ansible, all these integrations, VMware doing so much in this area and they just don't get any credit for it ever, right. It's just like, VMware's the dinosaur and they're just not, right. But that's the thing that people think of today because of the hype of the hyperscaler. I think that's... Yeah. >> When you're in customer conversations, maybe with prospects, are you seeing more customers that have gone all in on a hyperscaler and are having issues and coming to you guys saying help, this is getting way too expensive? >> Yeah, I think it's the unexpected growth problem or even the expected growth problem where they just thought it would be okay, but they've suffered some type of competitive pressure that they've had to optimize for and they just didn't really expect it. And so, I think that increasingly we are finding organizations that quickly adopted public cloud. If they did a full digital transformation of their business and then transformation of their applications, a lot of them now feel very locked in because every application is just reliant on x hyperscaler forever, or they didn't transform anything and they just migrated and parked it. And the bills that are coming in are just like, whoa like, how is that possible? We are typically never recommending get out of the public cloud. We are just... It's not... If I say the right home for the right application, it's by default saying that there are right applications for hyperscalers. Parking your VMware environment that you just migrated to a hyperscaler, not the right application. You know, I would love you to be with me but if you want to do that, at least go to VMC on AWS or go to OCVS or GCVE or any of those. If that's going to go with a Google or an Amazon and that's just the mandate and you're going to move your applications, don't just move them into native. Move them into a VMware solution and then if you still want to make that journey, that full transformation, go ahead and make it. I would still argue that that's not the most efficient way but, you know, if you're going to do anything, don't just dump it all into cloud, the native hyperscaler stuff. >> Good advice. >> So what do typical implementations look like with you guys when you're moving on premises environments into going back to the VCPP, STDC model? >> Absolutely. Do you have people moving and then transforming and re-platforming? What does that look like? What's the typical-- >> Yeah. I mean, I do not believe that anybody has fully made up their mind if exactly where they want to be. I'm only going to be in this cloud. It's an in the close story, right. And so even when we get customers, you know, we firmly believe that the right place to just pick up and migrate is to a VCPP cloud. Better cost effectiveness, typically better technology, you know service, right. Better service, right. We've been part of VMware for 12 years. We love the technology behind VMC's, now AWS is fantastic, but it's still just infrastructure without any help at all right, right. They're going to be there to support their technology but they're not going to help you with the other stuff. We can do some of those things. And if it's not us, it's another VCPP provider that has that expertise that you might need. So yes, we help you quickly, easily migrate everything to a VMware cloud. And then you have a decision point to make. You're happy where you are, you are leveraging public cloud for a certain applications. You're leveraging VMware cloud offerings for the standard applications that you've been running for years. Do you transform them? Do you keep them? What do you do? All those decisions can be made later. But I stress that repurchasing all your hardware again, staying inside your colo and doing everything yourself, it is for me, it's like a company telling me they're going to build a data center for themselves, single tenant data center. Like no one's doing that, right. But there are more options out there than just I'm going to go to Azure, right. Think about it. Take the time, assess the landscape. And VMware cloud providers as a whole, all 17,000 of us or whatever across the globe, people don't know that group of individuals of the companies is the third or fourth potentially largest cloud in the world. Right? That's the power of the VMware cloud provider ecosystem. >> Last question for you as we wrap up here. Where can the audience go to learn more about Phoenix NAP and really start test driving with you guys? >> Absolutely. Well, if you come to phoenixnap.com, I guarantee you that we will re-target you and you can click on a banner later if you don't want to stay there. (Lisa laughs) But yeah, phoenixnap.com has all the information that you need. We also put out tons of helpful content. So if you're looking for anything technology oriented and you're just, "I want to upgrade to Ubuntu," you're likely going to end up on a phoenixnap.com website looking for that. And then you can find out more about what we do. >> Awesome, phoenixnap.com. William, thank you very much for joining Dave and me, talking about what you guys are doing, what you're enabling customers to achieve as the world continues to evolve at a very dynamic pace. We appreciate your insights. >> Absolutely, thank you so much >> For our guest and Dave Nicholson, I'm Lisa Martin. You've been watching the CUBE live from VMware Explorer, 2022. Dave and I will be joined by a guest consultant for our keynote wrap at the end of the day in just a few minutes. So stick around. (upbeat music)

(upbeat music) >> Man: We're good. >> Hey everyone. Welcome back to theCube's live coverage of AWS Summit NYC. We're in New York City, been here all day. Lisa Martin, John Furrier, talking with AWS partners ecosystem folks, customers, AWS folks, you name it. Next up, one of our alumni, rejoins us. Please welcome Anshu Sharma the co-founder and CEO of Skyflow. Anshu great to have you back on theCube. >> Likewise, I'm excited to be back. >> So I love how you guys founded this company. Your inspiration was the zero trust data privacy vault pioneered by two of our favorites, Apple and Netflix. You started with a simple question. What if privacy had an API? So you built a data privacy vault delivered as an API. Talk to us, and it's only in the last three and a half years. Talk to us about a data privacy vault and what's so unique about it. >> Sure. I think if you think about all the key challenges we are seeing in our personal lives when we are dealing with technology companies a lot of anxiety is around what happens to my data, right? If you want to go to a pharmacy they want to know not just your health ID number but they want to know your social security number your credit card number, your phone number and all of that information is actually useful because they need to be able to engage with you. And it's true for hospitals, health systems. It's true for your bank. It's true for pretty much anybody you do business with even an event like this. But then question that keeps coming up is where does this data go? And how is it protected? And the state of the art here has always been to keep kind of, keep it protected when it's in storage but almost all the breaches, all the hacks happen not because you've steal somebody's disc, but because someone enters through an API or a portal. So the question we asked was we've been building different shapes of containers for different types of data. You don't store your logs in a data warehouse. You don't store your analytical data in a regular RDBMS. Similarly, you don't store your passwords and usernames you store them in identity systems. So if PI is so special why isn't it a container that's used for storing PII? So that's how the idea of Pii.World came up. >> So you guys just got a recent funding, a series B financing which means for the folks out there that don't know the inside baseball, must people do, means you're doing well. It's hard to get that round of funding means you're up and growing to the right. What's the differentiator? Why are you guys so successful? Why the investment growth, what's the momentum driver? >> So I think in some ways we took one of the most complex problems, data privacy, like half the people can't even describe like, does data privacy mean like I have to be GDPR compliant or does it actually mean I'm protecting the data? So you have multiple stakeholders in any company. If you're a pharma company, you may have a chief privacy officer, a data officer, this officer, that officer, and all of these people were talking and the answer was buy more tools. So if you look around behind our back, there's probably dozens of companies out there. One protecting data in an API call another protecting data in a database, another one data warehouse. But as a CEO, CTO, I want to know what happens to my social security number from a customer end to end. So we said, if you can radically simplify the whole thing and the key insight was you can simplify it by actually isolating and protecting this data. And this architecture evolved on its own at companies like Apple and other places, but it takes dozens of engineers for those companies to build it out. So we like, well, the pattern will makes sense. It logically kind is just common sense. So instead of selling dozens of tools, we can just give you a very simple product, which is like one API call, you know, protect this data... >> So like Stripe is for a plugin for a financial transaction you plug it into the app, similar dynamic here, right? >> Exactly. So it's Stripe for payments, Twilio for Telephony. We have API for everything, but if you have social security numbers or pan numbers you still are like relying on DIY. So I think what differentiated us and attracted the investors was, if this works, >> It's huge. every company needs it. >> Well, that's the integration has become the key thing. I got to ask you because you mentioned GDPR and all the complexities around the laws and the different regulations. That could be a real blocker in a wet blanket for innovation. >> Anshu: Yes. >> And with the market we're seeing here at, at your Summit New York, small event. 10,000 people, more people here than were at Snowflake Summit as an example. And they're the hottest company in data. So this small little New York event is proven that that world is growing. So why should this wet blanket, these rules slow it down? How do you balance it? 'Cause that's a concern. If you checking all the boxes you're never actually building anything. >> So, you know, we just ran into a couple of customers who still are struggling with moving from the data center to AWS Cloud. Now the fact that here means they want to but something is holding them back. I also met the AI team of Amazon. They're doing some amazing work and they're like, the biggest hindrance for them is making customers feel safe when they do the machine learning. Because now you're opening up the data sets to more people. And in all of those cases your innovation basically stops because CSO is like, look you can't put PII in the cloud unprotected. And with the vault architecture we call it privacy by architecture. So there's a term called privacy by design. I'm like what the, is privacy by design, right? >> John: It's an architecture. (John laughing) >> But if you are an architecture and a developer like me I was like, I know what architecture is. I don't know what privacy by design is. >> So you guys are basically have that architecture by design which means foundational based services. So you're providing that as a service. So other people don't have to build the complex. >> Anshu: Exactly. >> You know that you will be Apple's backend team to build that privacy with you you get all that benefit. >> Exactly. And traditionally, people have had to make compromises. If you encrypt the data and secure it, then you can't use it. Using a proprietary polymorphic encryption technology you can actually have your cake and eat it to. So what that means for customers is, if you want to protect data in Snowflake or REDshare, use Skyflow with it. We have integrations to databases, to data lakes, all the common workflow tools. >> Can you give us a customer example that you think really articulates the value of what Skyflow is delivering? >> Well, I'll give you two examples. One in the FinTech space, one in the health space. So in the FinTech space this is a company called Nomi Health. They're a large payments processor for the health insurance market. And funnily enough, their CTO actually came from Goldman Sachs. He actually built apple card. (John laughing) Right? That if we all have in our phones. And he saw our product and he's like, for my new company, I'm going to just use you guys because I don't want to go hire 20 engineers. So for them, we had a HIPAA compliant environment a PCI compliant environment, SOC 2 compliant environment. And he can sleep better at night because he doesn't have to worry what is my engineer in Poland or Ukraine doing right now? I have a vault. I have rules set up. I can audit it. Everything is logged. Similarly for Science 37, they run clinical trials globally. They wanted to solve data residency. So for them the problem was, how do I run one common global instance? When the rules say you have to break everything up and that's very expensive. >> And so I love this. I'm a customer. For them a customer. I love it. You had me at hello, API integration. I love it. How much does it cost? What's it going to cost me? How do I need to think about my operationalizing? 'Cause I know with an API, I can do that. Am I paying by the usage, by the drink? How do I figure out? >> So we have programs for startups where it's really really inexpensive. We get them credits. And then for enterprises, we basically have a platform fee. And then based on the amount of data PII, we charge them. We don't nickel and dime the customers. We don't like the usage based model because, you don't know how many times you're going to hit an API. So we usually just based on the number of customer records that you have and you can hit them as many time as you want. There's no API limits. >> So unlimited record based. >> Exactly. that's your variable. >> Exactly. We think about you buying odd zero, for example, for authentication you pay them by the number of active users you have. So something similar. >> So you run on AWS, but you just announced a couple of new GTM partners, MuleSoft and plan. Can you talk to us about, start with MuleSoft? What are you doing and why? And the same with VLA? >> Sure. I mean, MuleSoft was very interesting customers who were adopting our products at, you know, we are buying this product for our new applications but what about our legacy code? We can't go in there and add APIs there. So the simplest way to do integration in the legacy world is to use an integration broker. So that's where MuleSoft integration came out and we announced that. It's a logical place for you to swap out real social security numbers with, you know, fake ones. And then we also announced a partnership with SnowFlake, same thing. I think every workload as it's moving to the cloud needs some kind of data protection with it. So I think going forward we are going to be announcing even more partnerships. So you can imagine all the places you're storing PII today whether it's in a call center solution or analytics solution, there's a PII story there. >> Talk about the integration aspect because I love the momentum. I get everything makes secure the customers all these environments, integrations are super important to plug into. And then how do I essentially operate you on my side? Do I import the records? How do you connect to my environment in my databases? >> So it's really, really easy when you encrypt the data and use Skyflow wall, we create what is called a format preserving token, which is essentially replacing a social security number with something that looks like an SSN but it's not. So that there's no schema changes involved. You just have to do that one time swap over and then in terms of integrations, most of these integrations are prebuilt. So Snowflake integration is prebuilt. MuleSoft integration is prebuilt. We're going to announce some new ones. So the goal is for off the table in platforms like Snowflake and MuleSoft, we prebuilt all the integrations. You can build your own. It takes about like a day. And then in terms of data import basically it's the same standard process that you would use with any other data store. >> Got to ask you about data breaches. Obviously the numbers in 2021 were huge. We're seeing so much change in the cyber security landscape ransomware becoming a household word, a matter of when but not if... How does Skyflow help organizations protect themselves or reduce the number of breaches so that they are not the next headline? >> You know, the funny thing about breaches is again and again, we see people doing the same mistakes, right? So Equifax had a breach four years ago where a customer portal, you know, no customer support rep should have access to a 100 million people's data. Like is that customer agent really accessing 100 million? But because we've been using legacy security tools they either give you access or don't give you access. And that's not how it's going to work. Because if I'm going to engage with the pharmacy and airline they need to be able to use my data in multiple different places. So you need to have fine grain controls around it. So I think the reason we keep getting breaches is cybersecurity industry is selling, 10s of billions of dollars worth of tools in the name of security but they cannot be applied at a fine grain level enough. I can't say things like for my call center agent that's living in Phoenix, Arizona they can only verify last four digits, but the same call center worker in Philippines can't even see that. So how do you get all that granular control in place? Is really why we keep seeing data breaches. So the Equifax breach, the Shopify breach the Twitter breaches, they're all the same. Like again and again, it's either an inside person or an external person who's gotten in. And once you're in and this is the whole idea of zero trust as you know. Once you're in, you can access all the data. Zero trust means that you don't assume that you actually isolate PII separately. >> A lot of the cybersecurity issues as you were talking about, are people based. Somebody clicking on something or gaining access. And I always talk to security experts about how do you control for the people aspect besides training, awareness, education. Is Skyflow a facilitator of that in a way that we haven't seen before? >> Yeah. So I think what ends up happening is, people even after they have breaches, they will lock down the system that had the breach, but then they have the same data sitting in a partner database, maybe a customer database maybe a billing system. So by centralizing and isolating PII in one system you can then post roles based access control rules. You can put limitations around it. But if you try to do that across hundreds of DS bases, you're just not going to be able to do it because it's basically just literally impossible, so... >> My final question for you is on, for me is you're here at AWS Summits, 10,000 people like I said. More people here than some big events and we're just in New York city. Okay. You actually work with AWS. What's next for you guys as you got the fresh funding, you guys looking for more talent, what's your next mountain you're going to climb? Tell us what's next for the company. Share your vision, put a plug in for the company. >> Well, it's actually very simple. Today we actually announced that we have a new chief revenue officer who's joining us. Tammy, she's joined us from LaunchDarkly which is it grew from like, you know, single digits to like over nine digits in revenue. And the reason she's joining Skyflow is because she sees the same inflection point hitting us. And for us that means more marketing, more sales, more growth in more geographies and more partnerships. And we think there's never been a better time to solve privacy. Literally everything that we deal with even things like rove evade issues eventually ties back into a issue around privacy. >> Lisa: Yes. >> AWS gets the model API, you know, come on, right? That's their model. >> Exactly. So I think if you look at the largest best companies that have been built in the last 20 years they took something that should have been simple but was not. There used to be Avayas of the world, selling Telephony intel, Twilio came and said, look an API. And we are trying to do the same to the entire security compliance and privacy industry is to narrow the problem down and solve it once. >> (indistinct) have it. We're going to get theCube API. (Lisa laughing) That's what we're going to do. All right. >> Thank you so much. >> Awesome. Anshu, thank you for joining us, talking to us about what's new at Skyflow. It sounds like you got that big funding investment. Probably lots of strategic innovation about to happen. So you'll have to come back in a few months and maybe at next reinvent in six months and tell us what's new, what's going on. >> Last theCube interview was very well received. People really like the kind of questions you guys asked. So I love this show and I think... >> It's great when you're a star like you, you got good market, great team, smart. I mean, look at this. I mean, what slow down are we talking about here? >> Yeah. I don't see... >> There is no slow down on the enterprise. >> Privacy's hot and it's incredibly important and we're only going to be seeing more and more of it. >> You can talk to any CIO, CSO, CTO or the board and they will tell you there is no limit to the budget they have for solving the core privacy issues. We love that. >> John: So you want to move on to building? >> Lisa: Obviously that must make you smile. >> John: You solved a big problem. >> Thank you. >> Awesome. Anshu, thank you again. Congrats on the momentum and we'll see you next time and hear more on the evolution of Skyflow. Thank you for your time. >> Thank you. >> For John furrier, I'm Lisa Martin. You're watching theCube live from New York City at AWS Summit NYC 22. We'll be right back with our next guest. So stick around. (upbeat music)

>> live from Miami Beach, Florida It's the que covering demon 2019. Brought to you, by the way, >> Welcome back to Vima on 2019 in Miami. Everybody, we're here at the Fountain Blue Hotel. This is Day two of our coverage of the Cube, the leader in live Tech. And I'm David Dante with Peter Bors. Pippen. Jay Raj is here. He's the vice president and CEO of Make A Wish America. Just that awesome foundation nonprofit people. Thanks for coming on the Cube. >> Thank you for having me appreciate it. >> So make a wish. Children with wishes and have terminal illnesses. You guys make them come true. It's just a great organizations. Been around for a long time, I think, since the early eighties, right, >> 39 years and going >> years and hundreds of thousands of wishes made. So just how did you get Teo make a wish that all come about >> it? It wasn't interesting journey. I was consulting in I t for multiple big companies. And, you know, two years back, it was through a recruiting channel that I got an opportunity to start some conversations as the CIA and make a wish. Uh, the thing that got me in the opportunity was predominately about enterprises and just to give you a little bit off, make official operations. Make a Wish was Founded and Phoenix, Arizona. And but we also operate a 60 chapters across the United States that it is 60 chapters each of the chapter there 501 C three companies themselves with the CEO and abort. Essentially, it is 60 plus one. The national team kind of managing. All of the chapters are helping the chapters. National does not do any wish. Granting all the wish planning happens to the chapters. But National helps the chapters with the distribution of funding models brand. And thanks for That's a couple of years back in the national board talked about in our dream and mission, which is granting every eligible child the notion ofthe enterprise. You know, working as an enterprise came into four and it being a great piece off providing shared services and thanks for that. So I was brought on board and we took on I would call as the leader today said and dashes dream off. Bringing together all the 60 chapters and the city chapter's essentially are split across 120 locations. So Wade took on a project off. You know, combining our integrating all of their infrastructure needs into one place. And Phoenix without ada, sent a provider. You know, we worked with a partner. Phoenix. Now fantastic partners >> there. We had them on the other day. >> Yep, yep. Yeah, MacLaren. I mean, and the team, they did a great job. And, you know, when we had to move all of the data, everything from the 60 chapters applications everything into a centralized data center, locations that we managed right now from Make a Wish National office and provide a service back to the chapters That gives you a little bit off. You know, from behind the scenes. What happened? >> You provide the technical overview framework for all the 60 chapters. >> It almost sounds like a franchise model. >> It's what we call a Federated model back in the nonprofit. >> But but but but because make a wish is so driven by information. Yep. Both in the application as well as the programs to deliver thie brand promise. And the brand execution has got to be very, very closely tied to the quality of a shared services you provide >> exactly. Exactly. And like I said, the reason I talked about them being a separate companies themselves is you know, as I always say to my 60 CEOs, Ah, I should be able to provide the services because they wanted, because they have a choice to go outside and have their own partner. Another thing for that which they can. But they would want to work with the national team and get my, you know, work through our services rather than having have to because of the very it's A. It's a big difference when it comes to, but I've been lucky on privileged to you have these conversations with the CEO's. When I start talking to them about the need for centralization, the enterprise society assed much, there are questions when he start leading with the mission and the business notion of why we need to do that, it's It's fantastic. Everybody is in line with that. I mean, there's no question, then, as toe Hey, guys, uh, let me do all the Operation Manisha fight and leave it to me and I'll in a handler for you, and I let you guys go to what you do best. which is granting wishes. So then it becomes it doesn't become a question off, you know, should be a shouldn't way. And of course, to back that up. But I was talking to the dean, folks, It just solutions. Like VMware, Veeam. It makes it much simpler even from a cost prospect. You not for me to manage a bigger team s so that I can take those dollars and give it back to the business to grant another wish. So it's it's pretty exciting that >> way. So you set the standards. Okay, here's what you know, we recommend and then you're you're saying that adoption has been quite strong. Yeah, I remember Peter. Don't say easy. I used to run Kitty Sports in my local town in which is small town. And there was, you know, a lot of five or six or seven sports, and I was the sort of central organization I couldn't get six sports to agree that high man is 60 different CEO's. But that's okay. So not easy. But so how were you able to talk leadership or leading as we heard from Gino Speaker today? How were you able to get those guys, you know, aligned with your vision. >> Uh, it's it's been fantastic. I've had a lot ofthe good support from our executive came from a leadership team because leadership is always very important to these big initiatives are National board, which comprises off some of the that stuff best leaders in America and I have the fortune toe be mentored by Randy Sloan, who used to be the CEO of Southwest. And before that, you see a global CEO for, uh, you know, Popsicle. You know, he always told me, but but I mean CIA job. One thing is to no the technology, but completely another thing. Toe building relationships and lead with the business conversation. And so a typical conversation with the CEO about Hey, I need to take the data that you have all the I t things that you have and then me doing it. And then there are questions about what about my staff and the's conversations. Because you know, it's a nonprofit is a very noble, nice feeling, and you wouldn't want the conversations about, you know, being rift and things like that are being reduced producing the staff and thinks of that. But you know as he walked through that and show the benefits of why we doing it. They get it. And they've been able to repurpose many off the I. D functions back in tow, revenue generation model or ofhis granting in our team. And in many cases, I've been ableto absolve some off their folks from different places, which has worked out fine for me, too, because now I have kind of a power user model across the United States through which I can manage all these 120 locations. It's very interesting, >> you know, site Reliable and Engineering Dev Ops talks about thie error budget or which is this notion of doo. You're going tohave errors. You're going to have challenges. Do you want it in the infrastructure you wanted the functions actually generating value for the business? I don't know much about Make a wish. I presume, however, that the mission of helping really sick kids achieve make achieve a wish is both very rewarding, very stressful. He's gotta be in a very emotional undertaking, and I imagine it part of your message them has got to be let's have the stress or that emotional budget be dedicated to the kids and not to the technology >> completely agree. That's that. That's been one of my subjects, as you asked about How is it going about? It's about having the conversation within the context of what we talked about business and true business. Availability of data. You know, before this enterprise project data was probably not secure enough, which is a big undertaking that we're going down the path with cyber security. And you know, that is a big notion, misplaced notion out there that in a non profits are less vulnerable. Nobody. But that's completely untrue, because people have found out that nonprofits do not probably have the securing of walls and were much more weight being targeted nonprofits as a whole, targeted for cyber security crimes and so on and so forth. So some of these that I used to, you know, quote unquote help or help the business leaders understand it, And once they understand they get it, they ableto, you know, appreciate why we doing it and it becomes the conversation gets much more easier. Other What's >> the scope of the size of the chapters is that is a highly variable or there is. >> It is highly variable, and I should probably said, That's Thesixty chapters. We look at it as four categories, so the cat ones are what we call the Big Ice, the Metro New Yorkers and Francisco Bay Area. They're called Category one chapters anywhere between 4 1 60 to 70 staff. Grant's close to around 700 wishes you so as Make a Wish America, we ran close toe 15,600 wishes a year, and cat ones do kind of close to 700 15,600 400 to 700. And then you get into care to scare threes and cat for scat force are anywhere between, you know, given example Puerto Rico or Guam territory there. Cat Force New Mexico is a cat for three staff members Gammas operated by two staff members and 20 volunteers. They grant about 3 2 20 12 to 15 which is a year, so it's kind of highly variable. And then, you know, we talk about Hawaii chapter. It's a great example. They cat once predominate because of the fact that you know, they they do. There's not a lot ofthe wishes getting originated from how I but you know, Florida, California and how your three big chapters with a grand are a vicious ist with a lot of grant, you know, wish granting. So there's a lot off, you know, traffic through those chapters >> so so very distributed on diverse. What's the relationship between data and the granting of wishes? Talk about the role of data. >> Should I? I was say this that in a and I probably race a lot of fibrosis and my first introductory session a couple of years back when I John make a wish with the CEO's uh, when we had the CEO meeting and talk to them about I leaders the days off making decisions based on guts are gone. It has to be a data driven decision because that's where the world is leading to be. Take anything for that matter. So when we talk about that, it was very imperative going back to my project that the hall we had all of the data in one place or a semblance off one single place, as opposed to 60 different places to make decisions based on wish forecast, for example, how many wishes are we going to do? How many wishes are coming in? How's the demand? Was the supply matching up one of the things that we need to do. Budget purposes, going after revenue. And thanks for that. So data becomes very important for us. The other thing, we use data for the wish journeys. Essentially, that's a storytelling. You know, when I you know, it was my first foray into for profit Sorry, nonprofit. And me coming from a full profit is definitely a big culture shock. And one of the things they ask us, what are we selling? Its emotions and story. And that's our data. That is what you know. That's huge for us if we use it for branding and marketing purposes. So having a good semblance off data being ableto access it quickly and being available all the time is huge for us. >> Yeah, and you've got videos on the site, and that's another form of data. Obviously, as we as we know here, okay. And then, from a data protection standpoint, how do you approach that? Presume you're trying to standardize on V maybe is way >> are actually invested in veeam with them for a couple of years right now, as we did the consolidation of infrastructure pieces Veeam supporters with all of the backup and stories replication models. Uh, we're thinking, like Ratmir talked about act one wi be a part of the journey right now, and we're looking at active. What that brings to us. One of the things that you know, dream does for us is we have close to 60 terabytes of data in production and close to another 400 terabytes in the back of things. And, uh, it's interesting when they look about look at me equation, you think about disaster recovery back up. Why do you need it? What? The business use cases case in point. This classic case where we recently celebrated the 10th anniversary ofthe back wish bad kid in San Francisco, we have to go back and get all the archives you know, in a quick fashion, because they're always often requests from the media folks to access some of those. They don't necessarily come in a planned manner. We do a lot of things, a lot of planning around it, but still there are, you know, how How did that come about? What's the story behind? So you know, there are times we have to quickly go back. That's one second thing is having having to replicate our data immediately. Another classic case was in Puerto Rico. There was a natural disaster happened completely. Shut off. All the officers work down. We had to replicate everything what they had into a completely different place so that they could in a vpn, into an access that other chapters and our pulled in to help. They were close to 10 wish families close to 10 which families were stranded because of that. So, you know, gaining that data knowledge of where the family is because the minute of his journey starts. Everything is on us till the witch's journey ends. So we need to make sure everything is proper. Everything goes so data becomes very crucial from those pants >> you're tracking us. I mean, if you haven't been on the make a Wish site is some amazing stories. There I went on the other day. There's a story of ah, of 13 year old girl who's got a heart condition. Who wanted to be a ballerina. A kid with leukemia five years old wants to be a You want to be a chef. My two favorites, I'll share What? It was this kid Brandon a 15 year old with cystic fibrosis. I wanted to be a Navy seal. You guys made that happen. And then there was this child. Colby was 12 years old and a spinal muscular issue. You want to be a secret agent so very creative, you know, wishes that you ran >> way had another wish a couple of years last year in Georgia, where they wish kid wanted to go to Saturn. Yes, yes, it was huge. I mean, and you know the best part about us once we start creating those ideas, it's amazing how much public support we get. The community comes together to make them wish granting process. Great. Now. So I got involved in that. They gave the wish Kato training sessions to make sure that he is equipped when he goes into. And we had a bushel reality company create the entire scene. It was fabulous. So, you know, the way you talk about data and the technology is now some of the things I'm very excited about us usage off thes next Gen technology is like our winter reality to grant a wish. I mean, how cool would that be for granting a wish kid who is not able to get out of the bed. But having able to experience a the Hawaii is swimming. Are being in Disney World enough a couple of days? That's That's another use case that we talked about. That other one is to put the donors who pay the money in that moment off granting, you know, they are big major gift, uh, donors for make a wish. Sometimes we were not able to be part of a fish, but that would be pretty cool if you can bring the technology back to them and you know not going for them. You know pretty much everybody and make the ass through that rather than a PowerPoint or a storytelling, when the storytelling has to evolve to incorporate all of that so pretty excited >> and potentially make a participatory like, say, the virtual reality and then even getting in more into the senses and the that the smells. And I mean this is the world that we're entering the machine intelligence, >> which you still have to have, But you still have to be a functioning, competent, operationally sound organization. There've been a number of charities, make a wish is often at the top of the list of good charities. But there were a number of charities where the amount of money that's dedicated to the mission is a lot less an amount of money, dedicated administration of fundraising, and they always blame it. Systems were not being able to track things. So no, it's become part of the mission to stay on top of how information's flowing because it's not your normal business model. But the services you provide is really useful. Important. >> Sure, let me percent you the business conundrum that I have personally as a 90 leader. It takes close to $10,400 on an average to grant a wish. Uh, and, uh, partly because of me. But being part of the mission, plus me as a 90 leader wanting to understand the business more, I signed up. I'm a volunteer at the local Arizona chapter. I've done couple of expanding myself, and, uh, the condom is, if asked, if you want to go, uh, you know, do the latest and greatest network upgrade for $10,400 are what do you want to, uh, you know and make the network more resilient cyber security and all that stuff. What do you want to go grant? Another wish as a 90 leader probably picked the former. But as a volunteer, I would be like, No, it needs to go to the kid. It's Ah, it's It's an interesting kind of number, you know? You have to find the right balance. I mean, you cannot be left behind in that journey because at many points of time s I talked about it being a cost center. It being a back office. I think those days have clearly gone. I mean, we we evolved to the point where it is making you steps to be a participant b A b a enabler for the top line to bring in more revenues, tow no augment solutions for revenue and things. For that sofa >> rattles the experience or exact role citizens. And in your case, it's the experience is what's being delivered to the degree that you can improve the experience administratively field by making operations cheaper. Great. But as you said, new digital technologies, they're going to make it possible to do things with the experience that we could even conceive of. Five >> wears a classic example. Williams and Beam. I couldn't have taken the data from 60 chapters 120 locations into one single location manageable, and it reduced the cost literally reduce the cost of the 60 instances in one place without technology is like, you know what Sharia virtual machines. And and then to have a backup robust backup solution in a replication off it. It's fantastic. It's amazing >> there. And that's against here. You could give back to the dash chapters and backing, But thanks so much for sharing your story. You Thank you. Thank you. You're welcome. Alright, keep it right there. Buddy. Peter and I were back with our next guest. You watching the Cube live from V mon from Miami? 2019. We're right back. Thank you.

>> Live from Miami Beach, Florida, it's theCUBE covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to Miami, everybody. I think I just saw Don Johnson running by. This is Dave Vellante with Peter Burris. You're watching theCUBE, the leader in live tech coverage. We're here at VeeamON 2019. This is day one of our wall-to-wall coverage. Ian McClarty is here. He's the president of PhoenixNAP, Ian thanks for coming on theCUBE. >> Thank you. >> So PhoenixNAP, service provider based in the southwest. Tell us more about the company. >> Yeah so we started on the Southwest, hence the name Phoenix, and NAP stands for network access point. So we focus on the connectivity side, on the telecom. But we really have moved more to infrastructure services, and that's been more of a world wide deployment. Last year we did about six global locations that were new to us, so today we're at about on 15 locations. >> So I always ask guys like you, you know, the Cloud was suppose to put you out of business, and then the Cloud has been this huge tail wind. >> Yeah. >> Why, what was it that everybody missed about the cloud and how have you able to exploit it? >> Yeah, so we come from a hosting background. So the Cloud has been around for us forever, right? Before it was termed Cloud, we believed in OpEx model for infrastructure services. That's what the Cloud is. Scalable, easy to absorb. So for us, what the Cloud did was make us mainstream. Because hosting was very boutique back in the day, back in the 90's. Now today we're a very mainstream brand, very mainstream products. So Cloud has really made our lives easier, actually. >> So it opened up everybody's eyes. >> Yeah. >> Sort of ... The guys like Amazon and Azure did a lot of market development for you. >> They did, a lot. And a lot of market development that we ourselves cannot do because we are smaller companies. >> Right. So talk a little bit about what your unique value proposition is, how you guys, you know, compete in the market place. Why PhoenixNAP? >> Why PhoenixNAP? So its really about the suite of infrastructure products. So our spectrum really starts with co-location on one end and it ends to bare metal dedicated Cloud systems. And then in between we have all the virtual station cloud platforms, more standard BMR deployments. So really its about our spectrum of services that we cover and we really are really good at that spectrum of services. So we have developed a lot of depth also around these different offerings. >> And your facilities, as you say you started in the Southwest, but where are you guys located? Are you? ... >> Yeah, so we're, So we own and operate out of Phoenix, Arizona, 120,000 square foot of facility. With the I-T usable space, um, and we have expanded now to other, with other partnerships with taking on large location spaces to basically seed our different locations and put us in point we are building those locations. Ashburn is one we are getting very close with actually. >> Uh-huh. So you're data centered guys right? I mean, you know - >> We're data, We're hosting guys that went into the data center business, and became infrastructure people. >> Okay, so it sort of evolved, this is act 3 for you >> Yes, this is act 3. >> We've been talking about act 2 all day. So how have you evolved your, you skillset, your customer base, talk about the evolution of the, of the company and where you see it going. >> Yeah so I mean, today we're focusing very much on mid-market enterprise, that's where our, and again, how do you define that? We define that by $50 to $500 million in revenue that's out definition of mid-market enterprise. So we're not going after the Fortune 500, and we're not going after S&B. And we have really tapped into the space. It's a very hard space for, for the, for the public clouds to, um, to act in today. >> So what's different? So obviously, the difference between mid and large enterprises is the mid-size guys, they're more generalists, they don't have, you know, all kinds of specialists, they don't have the resources, >> They do not. >> That the large guys do. But they're more advanced than the S. >> Yes. >> S and M are different, >> Yes, they are. >> Than the large. So what are the unique attributes of M that really uh, you try to focus on delivering? >> So M has budget, but M doesn't want to outsource. That's key. They know enough, but they don't have expertise. So what they're looking at, they're looking for supplemental I-T, and really what we focus on. >> So they don't want to outsource their strategic jewel, the family jewels, but they need help. >> They need supplemental help. And they don't want to go to consultants either. >> But M also wants to be L and I think that's the big issue, M wants to be L, typically M wants to be L, So they're looking for, they have budget, they have plans, >> Yeah. >> They want to scale, but they have to be very careful about how they invest to get there. >> And then like to (mumbles) still, they like (mumbles), infrastructure, they want to know you, they want to build a relationship. That's what I'm saying, it's very hard for the public clouds to tap into that space because of that. It had a lot of nuances. >> M wants to scale they want to act like a real business, >> Yes. >> They want, they want to know their suppliers, because they want to know if they're going to be able to go with them. >> (Ian) They want to have control over their suppliers as well. >> Exactly. But come back to that, because that becomes, that becomes more increasingly a services play. >> Yes. >> As M gets more experiences, these medium-size companies get more experience, they are starting to acknowledge and recognize the new classes of services that they need because they have that sophistication. So how is your business changing? And specifically thinking about what Veeam's doing here, to become more of a service-provider, of, at a higher level than just the underlying infrastructure. >> So I'll tell you what we're doing right now. On the surface-side, we're really focusing more on manage-infrastructure, right? That's the moniker we use. But what infrastructure means is really changing. So today we're (mumbles), right? What are we going to do have a managed (mumbles) stack, that is deliverable in an A-P-I model? That's our vision for the company. >> So, um, you're a platinum partner of Veeam, uh, can you talk a little bit about where they fit in your stack? I mean, you've got a whole security layer. >> (IAN) Yep. >> I think you were saying to us earlier that, you know, the data protection piece, the backup is sort of the last-- >> It's a lifeline. >> Resort, yeah. So describe that infrastructure and what you guys have built up. >> Yeah so when we started the company, we started at the edge, right? Plus folks on the (mumbles), those folks on network protection, let's start there, and let's work our way down. And so now then we've built a V-M-R stack that basically is, um, it's third-party audited, it follows compliance rules. When you go to the, um, (mumbles) it works on PCI, when you go to the PCI website you can see PheonixNAP listed as E-S-S provider there, and it abstractly outlines what we protect on the cloud side. So very clear in where we transferred on that side, so it's been layered for us, a layered approach of protecting services. But there will always be a breach, and you have to count on that. It's unfortunate, but it's a reality, right? And once you embrace that, you can build products around that, and so really V-M-R has become a very key part of that equation with both backup and recovery services, and then if there is a breach, then you need to be able to recover those services somewhere, so the (mumbles) recovery services for us is big. So it really fills that missing piece that we had in the equation. >> Yeah I mean you've made that point Peter, many times, is that the breach is inevitable, it's how you repsond to that breach that's really critical. >> Yes. >> And that's, I mean not brand-new thinking, but it's certainly over the last ten years has evolved, you know Peter-- >> (IAN) You've got to embrace it. >> People used to not talk about breaches, oh no, don't talk about it, now it's like at the board level, yeah we acknowledge that it's going to happen, and we're putting more and more resources into our response, is that sort of what you're seeing? >> Yes, that is exactly what I'm seeing. And this year alone fifteen-thousand breaches that were reported right? And again, who reports those breaches? It's not the S, not the M, it's the large enterprise that reports those breaches. So those numbers are even worse in the S and M market right? >> (DAVE) Right, right. >> Although the M guys have, are now getting large enough When-- >> They have to report. >> They have to start reporting. You're coming back to this notion, that, and it used to be that when there was a breach, it was always discussed in terms of hardware, it was discussed in terms of network. >> Yeah. >> But now it's data! >> It is. >> Because that's where the asset is, and that's where people after, >> Exactly. >> So again, coming back to that notion of higher-level services, backup used to be something that you kind of, checked off as you were leaving the customer's location, taken the order, has it become something that's increasingly one of the reasons why customers are bringing you in? >> I will tell you, the easiest way for us to (mumbles) another part where Veeam falls into our equation, is customer acquisition. Like Veeam to me is not the highest revenue, product, period, right? But from a customer acquisition perspective, it's the best product that we have. It's an easy conversation, because it is. Historically it's been a checkbox, but once the customer figures out, "hey, okay so I've got backups, now how do I recover these backups? How do I restore them? Where do I go?" that's where we can have a much more complex conversation with them. >> A lot of these M customers, to become L, are now realizing "I'm not going to get there, if I don't use data in ways that the L guys have hard time using it. So I need to focus on data assets, I need to focus on my digital transformation", which means it's essential that they start thinking about how data protection is going to operate within their business, because increasingly, they're becoming digital businesses. And data protection becomes digital business protection. Are you having those conversations? >> All the time. On day-to-day basis. That's the bulk of our conversations now, for new customer acquisition. >> (DAVE) Why Veeam? >> Yeah. >> You know a lot of companies out there, a lot of new startups entering the marketplace, you've got big wheels like, you know, Dell EMC, and some established companies like Veritas, IBM, you got the big blue blanket, why Veeam? >> Why Veeam for us? Well for us, part of it is culture, right? That was very critical for us. First, the technology piece, obviously solid, works right? The "it does work" moniker that was used, it's true right? And the simplicity of it, too. As a service provider, we know what to expect with Veeam, so we built a lot of competency around Veeam as a product line. Obviously we've played, we've used other products, but we always go back to Veeam. Because, again, it's evolving in a place that we like. We see where they're going for the recovery piece, right? The restoration piece. We like that as a vision piece also, that it's not talked about a lot. It's coming right? It's always the upcoming. But for us it's good to (mumbles) another vendor. The second that comes out, it's a (mumbles) vendor for us. So we like the vision of the company, we like where they're heading, we also like from a corporate culture perspective, what they're doing for channel-centric. For us it helps us mature as an organization tremendously. You know Ratmir hit the nail on the head when he said, "Not the best product wins in the market", right? You have to have, the company that has the best sales and marketing along with that as well. So for us you know, we have pretty decent sales. Marketing we're weaker on, and Veeam has really coached us along the way to make our marketing efforts even stronger. >> Yeah Veeam knows how to market! >> Yeah they do, they are marketing geniuses. And I love them for that, right? And I have a lot of respect towards them for that, so. >> Ian, thanks so much for coming on theCUBE, it was great to have you. >> You as well. >> All right keep it right there everybody, this is Peter Burris and Dave Vellante, we're live at Veeamon 2019 from Miami. You're watching theCUBE, we'll be right back. (poppy electro music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> Welcome back to theCUBE. We are live in Las Vegas. Day two of Dell Technologies World. I am Lisa Martin with Stu Miniman, my cohost. And we're excited to welcome to theCUBE for the first time the CIO of TGen, Translational Genomics, James Lowey. James, welcome to theCUBE. >> Ah, thank you so much, it's great being here. >> So, genomics, really interesting topic that we want to get into and understand. How are you making IT and digital and workforce transformation real in it, but get give our viewers and overview of TGen. It started out about 16 years ago as a very collaborative effort within Arizona and really grew. Talk to us about that. >> Yeah, absolutely. So, TGen is a nonprofit biomedical research institute based in Phoenix, Arizona. As you mentioned, we've been around about 16 years. We were, the inception of the institute was really built around bringing biomedical technology into the sate of Arizona. And we're fortunate enough to have a really visionary and gifted leader in Dr. Jeffrey Trent, who is one of the original guys to sequence the human completely for the first time. So I don't know if you get any better street cred than that when it comes to genomics. >> And you mentioned, before we went live, give our viewers an overview of what it took to sequence the human genome in terms of time and money and now, how 15 years later, how fast it can be done. >> Yeah, so, you know we've moved from a point where it costs billions of dollars and took many years to complete the first sequence to today where it takes a little bit over a day and about $3 thousand. So it's really the democratization of the technology is driving clinical application, which, in turn, is going to benefit all of us. >> Yeah, James, genomics is one of those areas, when we talk about there is the opportunity of data, but there's also the challenge of data, because you've got to, I have to imagine, orders of magnitude more data than your typical company does, so talk to us a little bit about the role of data inside your organization. >> Well, data is our lifeblood. I mean, we've been generating terascale then petascale for many years now. And the fact is, is every time you sequence a patient you're generating about 4 terabytes of data for one patient. So if you're doing 100 patients, do the math, or you're doing a thousand patients. We're talking just an immense volume of data. And really, data is what drives us because that information that's encoded in our genome is nothing but data, right? It's turning our analog selves into a digital format that then we can interrogate to come up with better treatments to help patients. >> Can you bring this inside? When you talk about the infrastructure that enables that. You know, what I was teasing out with the last question, it's not just about storing data, you need to be able to access the data, you need to be able to share data. So as the CIO, what's your purview? Give us a little bit of a thumbnail sketch as to what your organization-- >> Oh yeah, yeah, no that's great. You know, so we've been a long time Isilon customer. The scale-out storage is what really has enabled us to be successful. Our partnership with Dell EMC has spanned many years and we're fortunate enough to have enough visibility within the organization to get early access to technologies. And really, that's really important because the science moves faster than the IT. So having things like scale-out, super fast flash, you know, having new Intel processors, all these things are what really enable us to do our job and to be successful. >> How have, you've been with TGen for a long time now, you've been the CIO for about three years. Talk to us about the transformation of the technology and how you've evolved it to not just facilitate digital transformation and IT transformation, but I imagine security transformation with human genetic data is of paramount importance. >> You know, that's a really good point. Security is always on my mind, for obvious reasons because I would say there's nothing more personally identifiable than your genome. There's the laws around these things still have not been totally codified. So we're sitting at a point today where we're still uncertain to how exactly best protect this very, very important data. But to that end, we tend to fail in the closed state of doing things, everything's encrypted. You know, we are big believers in identity management and making sure that the right people have access to the right data at the right time. We've utilized SecureWorks, for instance, for perimeter, logging, and to get their expertise. 'Cause one of the things I've learned in my tenure as CIO is that it's really all about the people and they're what drive your success. And so I'm fortunate enough to have a team that's amazing. These folks are some of the best people in their field and really do a great job at helping us, protect the data, get access to the data, as well as thinking about what the next iteration is going to look like. >> When you look at, just as a whole, the security and data protection, you think about everybody, if they get those home kits, or things like that, how has that evolved the last few years? I'm curious if that impacts your business. >> Well, I think it does impact our business insofar as it creates awareness. And you know, I think it's really fantastic when I attend a cocktail party or something and people come up and ask, say, "You know, should I get the 23andMe Ancestry?" And they're really engaged and interested and wanting to learn about these things. And I think that's going to spur questions to be asked when they go in to be treated by a physician. Which is really important. I think, I'm a believer that we should own our own data, especially our genomic data, because what's more personal than that? And so we have a lot of challenges ahead, I think, in IT in particular, in protecting, storing, and providing that data to patients. >> Just a quick followup, I'm sure you secure stuff. What's the cocktail answer for that? If, you know, should I get that? Can I trust this company? Is my insurance company and everybody else going to get that? What do you advise the average consumer? >> I would say read the terms of use agreement very carefully. >> so the theme of the event, James, make it real. You know, few things are more real than our own data, our own genomes, what does that theme mean to you from an application perspective? How are you making digital transformation real? And things like the alliance with City of Hope to impact disease study and cures? What is that reality component to you? >> Yeah, it has, you know, I really like the make it real theme, and I think it's something that we are doing every day. I think it just speaks to, you know, taking technology, applying it for meaningful use, to actually make a difference, and to do something that has real impact. And I think that at TGen, I've been empowered to build systems that can do that, that can help our scientists and ultimately help patients. You mentioned City of Hope. We're, our alignment with them is amazing. They have just hired a Chief Digital Officer as they go through a digital transformation of their own. And you know, we're on board in striving to help them go through this process because, as you might be aware, everything's about the data. And that's where we have to focus. >> James, if you go back, you talked about your scale-out architecture with Isilon. How do you report back to the business as to the results you're doing? What are the, do you have any hero metrics or things that you point out that says this is why we're successful. This is why we've made the right decision. This is why we should be doing this in the future. >> Well, I think we're especially fortunate that we can measure our success in people's lives. So, meeting a kid who's in full remission from brain cancer who was treated using drugs that were derived from being sequenced and run through our labs and then our computational infrastructure and having them say thank you, I think is pretty much a metric that I don't know how you can beat that. >> Talk about making it real. That's where it's really impactful. I'd love to understand your thoughts as you continue to evolve your transformation as a company. We've heard a lot about emerging technologies and what Dell EMC, Dell Technologies, is doing to enable organizations and customers to be able to realize what's possible with artificial intelligence, machine learning, IoT. What are your thoughts about weaving in those emerging technologies to make what TGen delivers even more impactful. >> Well you just said three of my favorite things that I'm spending a lot of time thinking about. You know, artificial intelligence is going to be absolutely, is required to interrogate the vast amounts of data that are being created. I mean, this is all unstructured data, so you have to have systems that can store and present that data in such a way that you're going to be able to do something meaningful. IoT is another area where we're spending a lot of time and energy in what we believe is like quantitative medicine. So basically taking measurements all the time to see about changes and then using that to hopefully gain insight into treatment of diseases. You know, machine learning and some of these technologies are also absolutely going to be critical, especially when we start building out drug databases and being able to match the patient with the drug. >> Yeah, James, bring us inside to your organization a little bit. What kind of skill sets do you have to have to architect, operate, a theme of this show, they've got Andy McAfee, who's from MIT, we've spoken to, it's about people and machines. You can't have one without the other. You need to be able to marry those two. How does an organization like yours get ready for that and move forward? >> Yeah, it's a really good point. I think the technology enables the people, and you have to have the right people to help make the decisions and what technologies you get and apply. And I think that the skill sets that we look for is generally people who have a broad view of the world. You know, people who are particular experts, at least in the IT side are of limited use, because we need people to be able to switch gears quickly and to think about problems holistically. So I'd say most of the IT folks are working several different disciplines and are really good at that. On the scientific side it's a little different. We're looking for data scientists all the time. So if anybody's watching and wants to come work for a great place, TGen, look us up. Because that's really where we're headed. You know, we have a lot of biologists, we have a lot of molecular biologists, we have people who do statistics, but it's not quite the same as data science. So that's kind of the new area that we're really focused on. >> All right, so James, one of the things I always love to ask when I get a CIO here is, when you're talking to your peers in the industry, how do you all see the role of the CIO changing? What are some of the biggest challenges that you're facing? >> So, yeah, it's a great question. I think the role's changing towards being empowered in the business. And I think that as that has to be part of the transformation. Is you have to be aligned completely with what your objectives are. And we're fortunate, you know, we are. And I feel very lucky to have a boss and a boss's boss who both understand the importance and the value that we bring to the organization. I also see that in the industry, especially in healthcare, a need for folks who are focused beyond just the EMR and daily IT things, to really start looking beyond maybe where you're comfortable. I know that I stretch my boundaries, and I think that in order to be successful as a CIO I think that's what you're going to have to do. I think you're going to have to push the envelope. You're going to have to look for new technologies and new ways to make a difference. >> So last question, big impact that TGen has made to the state of Arizona. I read on LinkedIn that you like building high-performance teams. What are some of the impacts that this has made for Arizona but also maybe as an example for other states to look to be inspired to set up something similar? >> That's really a great question. I think, you know, Arizona made an investment, and the way that it's easy to measure. So if you come down to the TGen building and realize that that building was the first building that is now surrounded by buildings, including a full-on cancer center, that's all in downtown Phoenix. And it's almost the if you build it they will come, but it's not just the infrastructure, it really is about the people and identifying the right folks to come in and help build that, to invest in them and to provide basically the opportunity for success. You know, Arizona has really been fortunate, I think, in being able to build out this amazing infrastructure around biotechnology. And you know, but we're just getting going. I mean, we are, we've only been doing this for about 16 years and I look forward to the next 16. >> Well thanks so much, James, for stopping by and talking about how you're applying technologies, not just from Dell EMC but others as well to make transformation real, to make it real across IT, digital, workforce, security, and doing something that's really literally has the opportunity to save lives. Thanks so much. >> Well thank you very much, it's been a pleasure. >> We want to thank you for watching theCUBE. I'm Lisa Martin, with my cohost Stu Miniman. We are live day two of Dell Technologies World. We'll be back after a lunch break. We'll see you then.

>> Announcer: Live from the Wigwam in Phoenix, Arizona it's the CUBE, covering Data Platforms 2017. Brought to you by Qubal. >> Hey, welcome back everybody, Jeff Frick here with the CUBE along with George Gilbert. We're at Data Platforms 2017 a the historic 99 years young Wigwam resort outside of Phoenix and we're excited to be joined by our next guest, Alex Sadovsky, he the director of data science for Oracle Data Cloud. Welcome. >> Thanks, thanks for having me. >> Absolutely, I know so I know we got a short time window, you're racing off to your next session. So, for the people that aren't here, what are you going to be talking about in your session here? >> So, the Oracle Data Cloud, what we do is online advertising and essentially we have lots and lots of data, customers comet to us and they have some sort of question in mind. They want to say, I want to figure out who's going to buy a mini-van in California next month, or who's going to get a hotel in Las Vegas, who's going to buy Kraft macaroni and cheese? All sorts of different questions. We have all of that data, we have to turn it into actionable insights, into audiences for them so they can advertise Facebook, Twitter, all over the web. And so, what this talk is really focusing on is how do we take all of this data and use it efficiently? And it's going to talk about the technologies that we've used specifically Hive, and then moving that technology over to Spark, just so that we can use more data, get quicker processing, and essentially make our clients have a better experience and give 'em a better product. >> And do the clients execute the results of this process inside their other Oracle apps, or is it something that they can use with any number of apps? >> So, a lot of the ways that we work, we actually are interfaced with companies like Facebook and Twitter directly. And so, essentially what we're doing is we're partnering with them so that the client, all they really need to do is kind of come to us either onboard some data through maybe other Oracle applications or onboard data directly through us and then push it out, we help push it all the way through the process, all the way into Facebook, etc. >> Yes, 'cause we were covering Oracle modern marketing, which is now Oracle modern customer experience, I'm sure you guys must be tightly integrated with all that. >> Yeah, and so for Oracle Data Cloud it's kind of interesting we're a collaboration of five recently acquired start-ups. And so it's everything from two to three years ago all of this coming together. So, for us, we're really excited because we're just at the tip of the iceberg of getting into the whole Oracle ecosystem and having that help build up our product even better. >> So, when you say partner with Facebook or Twitter, that would be for brand or direct response advertising that one of your B2B clients has signed up for? Or I should say, B2B, your B the client is B, and the end customer's C, so it's a B2B2C. And now okay, so you help them in a consultative way. You have the data, you have a consultative sales approach, are you building models for them? Or are you telling them, sort of running a model? >> Alex: Yeah. >> Sort of which is it? >> So, we will, we run models based upon data. So, a customer could come to us with, here are a thousand people that that customer knows bought their product last month, and they say, we want to expand our business, we want to advertise to 20 million people who might be similar to those thousand. And so that's where all of our data comes in. We can look at those thousand people and we can say, hey did you guys know that most of your customers are millennials? Did you know that most of them tend to live on the west coast or east coast populated cities? And we're not really consulting that in the sense of like there's people looking at the data, it's all machine learning. And so computers are looking at all of our data to help get insights from what the customers bringing to us. >> So, would it be fair to say then that the, let's say the thousand example that the customer brings in is the training data. >> Yes. >> And then you use your data in your databases, your consumer databases, to say, to generate essentially scores, since they were going to send out to these. >> That's 100% right. They come in with a thousand of their customers, we see how those customers rank up against every single household in the entire United States. >> I was going to say, we're going to be at Spark Summit in a couple weeks or a week, whenever it is. I can't keep track of all these shows. So, they can't do the whole thing wiHive to Spark, but in three minutes or less wiHive to Spark. >> So, number one reason for us, and number one reason I think a lot of people are moving to Spark is just speed. Without getting into a lot of technical details, there's just a lot better engine, a lot better flexible engine underneath Spark than kind of traditional Hive. >> And then machine learning models are, most of the libraries are built in, which Hive doesn't have. >> Yeah, machine learning is really built into Spark. There's, you know, whole projects within Spark built around that. And so, for us, we really, Spark considers machine learning kind of a first class citizen. And since that's essentially what our business is, we go 100% into Spark as well. >> So, let me ask you, what is the scope now and potentially in the future for these data based predictive models where customer comes to you with essentially some labeled data and then you'll come out with I guess that's the training data and then right now you have data in what categories? And then what categories would you like to have? >> So, we have data everything from what people are doing on the web, so what they're searching for, what websites they're going for. We have grocery store data. So, what people are buying in the grocery store. We have retail data. So, what people are buying in the malls. Because a lot of what happens is, even though consumers are spending a lot more time on the web, 80%-90% of purchases are still made in the store. So, we have all of this actual real world purchase data that we've partnered with different retail partners, including like automotive data, too. So that's really like the core of our data. So, really what we try to do is have data sets strategically placed all around and that's why the Oracle Data Cloud is made up of so many different start-ups, we're really getting expertise from different areas for different data sets to bring that together. >> Do you need to buy those sources of data? Or can you license? >> Data is everything from licensed to purchased outright to shared, revenue sharing with other companies. It's really, there's a huge data market right now. It's kind of the data gold rush and we're trying get in anywhere we can, figure out what's going to help us and what's going to help our customers make better models. >> What would you like to see in terms of a, if you look out a couple years, where would you like to see your data assets sort of augment all your Oracle applications? >> Yeah, so I think... SO, augmenting Oracle really we have so many different data assets that everything from like live streaming data, of what people are searching for on the web, to historically what someone has bought in the last three years and so, as we partner more and more with Oracle, Oracle has different things in healthcare, in retail, in all sorts of B2B applications. And our data really can fit almost everywhere. It's really like a data driven sort of product. And so, we've been partnering with Oracle left and right many different groups just trying to figure out where can this data help augment kind of your services. >> Alright, Alex, well, we got to leave it there. That was a good summary. I know you got to race off to your thing. I'll let you take a breath and get a glass of water. So thanks for squeezing us in your busy day. >> Alex: Thanks so much. >> Alright, he's Alex, he's George, I'm Jeff, you're watching the CUBE from Data Platforms 2017. We'll be right back after this short break. Thanks for watching.

>> Announcer: Live from the Wigwam in Phoenix, Arizona. It's theCUBE covering Data Platforms 2017. Brought to you by Qubole. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We're at the historic Wigwam Resort. 99 years young just outside of Phoenix. At Data Platforms 2017. I'm Jeff Frick here with George Gilbert from Wikibon who's co-hosting with me all day. Getting to the end of the day. And we're excited to have our next guest. She is Kellyn Gorman. The technical intelligence manager and also the office of the CTO at Delphix, welcome. >> Yes, thank you, thank you so much. >> Absolutely, so what is Delphix for people that aren't familiar with Delphix? >> Most of realize that the database and data in general is the bottleneck and Delphix completely revolutionizes that. We remove it from being the bottleneck by virtualizing data. >> So you must love this show. >> Oh I do, I do. I'm hearing all about all kinds of new terms that we can take advantage of. >> Right, Cloud-Native and SEPRATE, you know and I think just the whole concept of atomic computing. Breaking down, removing storage, from serve. Breaking it down into smaller parts. Sounds like it fits right into kind of your guys will house. >> Yeah, I kind of want to containerize it all and be able to move it everywhere. But I love it. Yeah. >> So what do you think of this whole concept of Data Ops? We've been talking about Dev Ops for, I don't know how long... How long have we been talking about Dev Ops George? Five years? Six years? A while? >> Yeah a while (small chuckle) >> But now... >> Actually maybe eight years. >> Jeff: you're dating yourself George. (all laugh) Now we're talking about Data Ops, right? And there's a lot of talk of Data Ops. So this is the first time I've really heard it coined in such a way where it really becomes the primary driver in the way that you basically deliver value inside your organization. >> Oh absolutely. You know I come from the database realm. I was a DBA for over two decades and Dev Ops was a hard sell to a lot of DBAs. They didn't want to hear about it. I tried to introduce it over and over. The idea of automating and taking us kind of out this manual intervention. That introduced many times human error. So Dev Ops was a huge step forward getting that out of there. But the database was still in data in general was still this bottleneck. So Data Ops is the idea that you automate all of this and if you virtualize that data we found with Delphix that removed that last hurdle. And that was my, I guess my session was on virtualizing big data. The idea that I could take any kind of structured or unstructured file and virtualize that as well and instead of deploying it to multiple environments, I was able to deploy it once and actually do IO on demand. >> So let's peel the onion on that a little bit. What does it mean to virtualize data? And how does that break databases' bottleneck on the application? >> Well right now, when you talk about a relational data or any kind of legacy data store, people are duplicating that through our kick processes. So if we talk about Oracle they're using things like Datapump. They're using transportable table spaces. These are very cumbersome they take a very long time. Especially with the introduction of the cloud, there's many room for failure. It's not made for that, especially as the network is our last bottleneck. Is what we're also feeling too for many of these folks. When we introduce big data, many of these environments many of these, I guess you'd say projects came out of open source. They were done as a need, as a necessity to fulfill. And they've got a lot of moving pieces. And to be able to containerize that and then deploy it once and the virtualize it so instead of let's say you have 16 gigs that you need to duplicate here and over and over again. Especially if you're going on-prem or to the cloud. That I'm able to do it once and then do that IO on demand and go back to a gold copy a central location. And it makes it look like it's there. I was able to deploy a 16 gig file to multiple environments in less than a minute. And then each of those developers each have their own environment. Each tester has their own and they actually have a read write full robust copy. That's amazing to folks. All of a sudden, they're not held back by it. >> So our infrastructure analysts and our Wikibon research CTO David Floyer, if I'm understanding this correctly, talks about this where it's almost like a snapshot. >> Absolutely >> And it's a read write snapshot although you're probably not going to merge it back into the original. And this way Dev tests and whoever else wants to operate on live data can do that. >> Absolutely, it's full read write what we call it data version control. We've always had version control at the cold level. You may of had it at the actual server level. But you've rarely ever had it at the data level for the database or with flat files. What I used was the cms.gov data. It's available to everyone, it's public data. And we realized that these files were quite large and cumbersome. And I was able to reproduce it and enhance what they were doing at TIME magazine. And create a used case that made sense to a lot of people. Things that they're seeing in their real world environments. >> So, tell us more, elaborate how dev ops expands on this, I'm sorry, not dev ops data ops. How, take that as an example and generalize it some more so that we see how if DBAs were a bottleneck. How they now can become an enabler? >> One it's getting them to raise new skills. Many DBAs think that their value relies on those archaic processes. "It's going to take me three weeks to do this." So I have three weeks of value. Instead of saying "I am going to be able to do this in one day" and those other resources are now also valuable because they're doing their jobs. We're also seeing that data was seen as the centralized point. People were trying to come up with these pain points of solution to them. We're able to take that out completely. And people are able to embrace agility. They have agile environments now. Dev Ops means that they're able to automate that very easily instead of having that stopping point of constantly hitting a data and saying "I've got to take time to refresh this." "How am I going to refresh it?" "Can I do just certain..." We hear about this all the time with testing. When I go to testing summits, they are trying to create synchronized virtualized data. They're creating test data sets that they have to manage. It may not be the same as production where I can actually create a container of the entire developmental production environment. And refresh that back. And people are working on their full product. There's no room for error that you're seeing. Where you would have that if you were just taking a piece of it. Or if you were able to just grab just one tier of that environment because the data was too large before. >> So would the automation part be a generation of snapshot one or more snapshots. And then the sort of orchestration distribution to get it to the intended audiences? >> Yes, and we would use >> Okay. things like Jenkins through Chev normal dev ops tools work along with this. Along with command line utilities that are part of our product. To allow people to just create what they would create normally. But many times it's been siloed and like I said, work around that data. We've included the data as part of that. That they can deploy it just as fast. >> So a lot of the conversation here this morning was really about put the data all in this through your or pick your favorite public cloud to enable access to all the applications to the UPIs, through all different types of things. How does that impact kind of what you guys do in terms of conceptually? >> If you're able to containerize that it makes you capable of deploying to multiple clouds. Which is what we're finding. About 60% of our customers are in more than one cloud, two to five exactly. As we're dealing with that and recognizing that it's kind of like looking at your cloud environments. Like your phone providers. People see something shiny and new a better price point, lesser dollar. We're able to provide that one by saving all that storage space. It's virtualized, it's not taking a lot of disc space. Second of all, we're seeing them say "You know, I'm going to go over to Google." Oh guess what? This project says they need the data and they need to actually take the data source over to Amazon now. We're able to do that very easily. And we do it from multi tier. Flat files, the data, legacy data sources as well as our application tier. >> Now, when you're doing these snapshots, my understanding if I'm getting it right, is it's like a, it's not a full Xerox. It's more like the Delta. Like if someone's doing test dev they have some portion of the source of the source of truth, and as they make changes to it, it grows to include the edits until they're done, in which case then the whole thing is blown away. >> It depends on the technology you're looking at. Ours is able to trap that. So when we're talking about a virtual database, we're using the native recovery mechanisms. To kind of think of it as a perpetual recovery state inside our Delphix engine. So those changes are going on and then you have your VDBs that are a snapshot in time that they're working on. >> Oh so like you take a snapshot and then it's like a journal >> the transactional data is from the logs is continually applied. Of course it's different depending on each technology. So we do it differently for Cybase versus Oracle versus Sequal server and so on and so forth. Virtual files when we talk about flat files are different as well. Your parent, you take an exact snapshot of it. But it's really just projecting that NFS mount to another place. So that mount, if you replace those files, or update them of course, then you would be able to refresh and create a new shot of those files. So somebody said "We refresh these files every single night." You would be able to then refresh and project them out to the new place. >> Oh so you're, it's almost like you're sub-classing them... >> Yes. >> Okay, interesting... When you go into a company that's got a big data initiative, where do you fit in the discussion, in the sequence how do you position the value add relative to the data platform that it's sort of the center of the priority of getting it a platform in place? >> Well, that's what's so interesting about this is that we haven't really talked to a lot of big data companies. We've been very relational over a period of time. But our product is very much a Swiss Army knife. It will work on flat files. We've been doing it for multi tier environments forever. It's that our customers are now going "I have 96 petabytes in Oracle. I'm about to move over to big data." so I was able to go out and say we how would I do this in a big data environment? And I found this used case being used by TIME magazine and then created my environment. And did it off of Amazon. But it was just a used case. I was just a proof of concept that I built to show and demonstrate that. Yeah, my guy's back at the office are going "Kellyn when you're done with it, you can just deliver it back to us." (laughing) >> Jeff: Alright Kellyn. Well thank you for taking a few minutes to stop by and pretty interesting story. Everything's getting virtualized machines, databases... >> Soon us! >> And our data. >> Soon George! >> Right, not me George... (George laughs) Alright, thanks again Kellyn >> Thank you so much. >> for stopping by. Alright I'm with George Gilbert. I'm Jeff Frick you're watching theCUBE from Data Platforms 2017 in Phoenix, Arizona. Thanks for watching. (upbeat electronic music)

>> Narrator: Live from The Wigwam in Phoenix, Arizona, it's the CUBE. Covering Data Platforms 2017. Brought to you by Qubole. (techno music) >> Hey, welcome back everybody. Jeff Frick here with the CUBE. We are in The Wigwam Resort, historic Wigwam Resort, just outside of Phoenix, Arizona at Data Platforms 2017. It's a new Big Data event. You might say, god there's already a lot of Big Data events, but Qubole's taken a different approach to Big Data. Cloud-first, cloud-native, you're integrated with all the big public clouds and they all come from Big Data backgrounds, practitioner backgrounds. So it's a really cool thing and we're really excited to have our next guest, Colin Ridell, he's a Big Data architect from Epic Games, was up on a panel earlier today. Colin, Welcome. >> Thank you, thank you for having me. >> Absolutely, so, enjoyed your panel, a lot of topics that you guys covered. One of the ones we hear over and over again is get early wins. How do you drive adoption, change people's behaviors, it's not really a technology story. It's a human factors and behaviors story. So I wonder if you can share some of your experience, some best practices, some stories. >> So I don't know if there's really a rule book on best practices for that. Every environment is different, every company is different. But one thing that seems to be constant is resistance to change in a lot of the places, so... >> Jeff: That is consistent. >> We had some challenges when I came in. We were running a system that was on it's last legs basically, and we had to replace it. There was really no choice. There was no fixing it. And so, I did actually encounter a fair bit of resistance with regards to that when I started at Epic. >> Now it's interesting, you said a fair amount of resistance. Another one of your lessons was start slow, find some early wins, but you said, that you were thrown into a big project right off the bat. >> Colin: So, we were, yeah. >> I'm curious, how did the big project go, but when you do start slow, how small does it need to be where you can start to get these wins to break down the resistance. >> I think what we, the way we approached it was we looked at what was the most crucial process, or the most crucial set of processes. And that's where we started. So that was what we tried to convert first and then make that data available to people via an alternative method, which was Hive. And once people started using it and learned how to interact with it properly the barriers start to fall. >> What were some of the difficult change management issues? Where did you come from in terms of the technology platform and what resistance did you hit? >> So it was really a user interface was the main factor of resistance. So we were running a Hadoop cluster. It was fixed sized, it wasn't on PRaM, but it was in a private cloud. It was basically, simply being overloaded. We had to do constant maintenance on it. We had to prop it up. And it was, the performance was degrading and degrading and degrading. The idea behind the replacement was really to give us something that was scalable, that would grow in the future, that wouldn't run into these performance blockers that we were having. But again, like I said, the hardest factor was the user interface differences. People were used to the tool set that they were working with, they liked the way it worked. >> What was the tool set? >> I would rather not actually say that on camera, >> Jeff: That's fine. >> Does it source itself in Redmond or something? >> No, no it doesn't, they're not from Redmond. I just don't want to cast aspersions. >> No, you don't need to cast aspersions. The conflict was really just around familiarity with the tool, it wasn't really about a wholesale change in behavior and becoming more data-centric. >> No, because the tool that we replaced was an effort to become more data-centric to begin with. There definitely was a corporate culture of we want to be more data-informed. So that was not one of the factors that we had to overcome. It was really tool-based. >> But the games market is so competitive, right? You guys have to be on your game all the time and you got to keep an eye on what everybody else is doing in their games, and make course corrections as I understand, something becomes hot, or new, so you guys have to be super nimble on your feet. How does taking this approach help you be more nimble in the way that you guys get new code out, new functionality? >> It's really, really very easy for us now to inject new events into the game, we basically can break those events out and report on them or analyze what's going on in the game for free with the architecture that we have now. >> Does that mean it's the equivalent of, in IT operations, we instrument everything from the applications, to the middleware, down to the hardware. Are you essentially doing the same to the game so you can follow the pathway of a gamer, or the hotspots of all the gamers, that sort of thing? >> I'm not sure I fully understand your question. >> When you're running analytics on a massively multi-player game, what questions are you seeking to answer? >> Really what we are seeking to answer at the moment is what brings people back? What behaviors can we foster in-- >> Engagement. >> in our players. Yeah, engagement, exactly. >> And that's how you measure engagement, it's just as simple as, do they come back or time on game? >> That's the most simple measure that we use for it, yeah. >> So Colin, we're short on time, want to give you the last word. When you come to a conference like this, there's a lot of peer interaction, there's some great questions coming out of the panel, around specifically, how do you measure success? It wasn't technical at all. It's, what are the things that you're using to measure whether stuff is working. I wonder if you can talk to the power of being in an ecosystem of peers here. Any surprises or great insights that you've got. I know we've only been here for a couple days. >> I would say that one of the biggest values, obviously the sessions and the breakouts are great, but I think one of the greatest values of here is simply the networking aspect of it. The being able to speak to people who are facing similar challenges, or doing similar things. Even although they're in a completely different domain, the problems are constant. Or common at least. How do you do machine learning to categorize player behaviors in our case and in other cases it's categorization of feedback that people get from websites, stuff like that. I really think the networking aspect is the most valuable thing to conferences like this. >> Alright, awesome. Well, Colin Ridell, Epic Games, thanks for taking a few minutes to stop by the CUBE. >> You're welcome, more than welcome, thank you very much. >> Absolutely, alright, George Gilbert, I'm Jeff Frick, you're watching the CUBE from Data Platforms 2017 at the historic Wigwam Resort. Thanks for watching. (upbeat techno music)

>> Announcer: Live from the Wigwam in Phoenix, Arizona. It's theCUBE. Covering Data Platforms 2017. Brought to you by Kubo. >> Hey welcome back everybody. Jeff Frick here with theCUBE along with George Gilbert from Wikibon. We've had a tremendous day here at DataPlatforms 2017 at the historic Wigwam Resort, just outside of Phoenix, Arizona. George, you've been to a lot of big data shows. What's your impression? >> I thought we're at the, we're sort of at the edge of what could be a real bridge to something new, which is, we've built big data systems for like out of traditional, as traditional software for deployment on traditional infrastructure. Even if you were going to put it in a virtual machine, it's still not a cloud. You're still dealing with server abstractions. But what's happening with Kubo is, they're saying, once you go to the cloud, whether it's Amazon, Azure, Google or Oracle, you're going to be dealing with services. Services are very different. It greatly simplifies the administrative experience, the developer experience, and more than that, they're focused on, they're focused on turning Kubo, the product on Kubo the service, so that they can automate the management of it. And we know that big data has been choking itself on complexity. Both admin and developer complexity. And they're doing something unique, both on sort of the big data platform management, but also data science operations. And their point, their contention, which we still have to do a little more homework on, is that the vendors who started with software on-prem, can't really make that change very easily without breaking what they've done on-prem. Cuz they have traditional perpetual license physical software as opposed to services, which is what is in the cloud. >> The question is, are people going to wait for them to figure it out. I talked to somebody in the hallway earlier this morning and we were talking about their move to put all their data into, it was S3, on their data lake. And he said, it's part of a much bigger transformational process that we're doing inside the company. And so, this move, from his cloud, public cloud viable, to tell me, give me a reason why it shouldn't go to the cloud, has really kicked in big time. And hear over and over and over that speed and agility, not just in deploying applications, but in operating as a company, is the key to success. And we hear over and over how many, how short the tenure is on the Fortune 500 now, compared to what it used to be. So if you're not speed and agile, which you pretty much have to use cloud, and software driven automated decision-making >> Yeah. >> that's powered by machine learning to eat. >> Those two things. >> A huge percentage of your transaction and decision-making, you're going to get smoked by the person that is. >> Let's let's sort of peel that back. I was talking to Monte Zweben who is the co-founder of Splice Machine, one of the most advance databases that sort of come out of nowhere over the last couple of years. And it's now, I think, in close beta on Amazon. He showed me, like a couple of screens for spinning it up and configuring it on Amazon. And he said, if I were doing that on-prem, he goes I needed Hadoop cluster with HBase. It would take me like four plus months. And that's an example of software versus services. >> Jeff: Right. >> And when you said, when you pointed out that, automated decision-making, powered by machine learning, that's the other part, which is these big data systems ultimately are in the service of creating machine learning models that will inform ever better decisions with ever greater speed and the key then is to plug those models into existing systems of record. >> Jeff: Right. Right. >> Because we're not going to, >> We're not going to to rip those out and rebuild them from scratch. >> Right. But as you just heard, you can pull the data out that you need, run it through a new age application. >> George: Yeah. >> And then feed it back into the old system. >> George: Yes. >> The other thing that came up, it was Oskar, I have to look him up, Oskar Austegard from Gannett was on one of the panels. We always talk about the flexibility to add capacity very easily in a cloud-based solution. But he talked about in the separation of storage and cloud, that they actually have times where they turn off all their compute. It's off. Off. >> And that was If you had to boil down the fundamental compatibility break between on-prem and in the cloud, the Kubo folks, both the CEO and CMO said, look, you cannot reconcile what's essentially server send, where the storage is attached to the compute node, the server. With cloud where you have storage separate from compute and allowing you to spin it down completely. He said those are just the fundamentally incompatible. >> Yeah, yeah. And also, Andretti, one of the founders in his talk, he talked about the big three trends, which we just kind of talked about, he summarized them right in serverless. This continual push towards smaller and smaller units >> George: Yeah. >> of store compute. And the increasing speed of networks is one, from virtual servers to just no servers, to just compute. The second one is automation, you've got to move to automation. >> George: Right. If you're not, you're going to get passed by your competitor that is. Or the competitor you that you don't even know that exists that's going to come out from over your shoulder. And the third one was the intelligence, right. There is a lot of intelligence that can be applied. And I think the other cusp that we're on, is this continuing crazy increase in compute horsepower. Which just keeps going. That the speed and the intelligence of these machines is growing at an exponential curve, not a linear curve. It's going to be bananas in the not too distance future. >> We're soaking up more and more that intelligence with machine learning. The training part of machine learning where the datasets to train a model are immense. Not only the dataset are large, but the amount of time to sort of chug through them to come up with the, just the right mix of variables and values for those variables. Or maybe even multiple models. So that we're going to see in the cloud. And that's going to chew up more and more cycles. Even as we have >> Jeff: Right. Right. >> specialized processors. >> Jeff: Right. But in the data ops world, in theory yes, but I don't have to wait to get it right. Right? I can get it 70% right. >> George: Yeah. >> Which is better than not right. >> George: Yeah. >> And I can continue to iterate over time. In that, I think was the the genius of dev-ops. To stop writing PRDs and MRDs. >> George: Yeah. >> And deliver something. And then listen and adjust. >> George: Yeah. >> And within the data ops world, it's the same thing. Don't try to figure it all out. Take the data you know, have some hypothesis. Build some models and iterate. That's really tough to compete with. >> George: Yeah. >> Fast, fast, fast iteration. >> We're doing actually a fair amount of research on that. On the Wikibon side. Which is, if you build, if you build an enterprise application that has, that is reinforced or informed by models in many different parts, in other words, you're modeling more and more digital entities within the business. >> Jeff: Right. >> Each of those has feedback loops. >> Jeff: Right. Right. >> And when you get the whole thing orchestrated and moving or learning in concert then you have essentially what Michael Porter many years ago called competitive advantage. Which is when each business process reinforces all the other business processes in service of a delivering a value proposition. And those models represent business processes and when they're learning and orchestrated all together, you have a, what Trump called a fined-tuned machine. >> I won't go there. >> Leaving out that it was Bigley and it was finely-tuned machine. >> Yeah, yeah. But the end of the day, if you're using resources and effort to improve an different resource and effort, you're getting a multiplier effect. >> Yes. >> And that's really the key part. Final thought as we go out of here. Are you excited about this? Do you see, they showed the picture the NASA headquarters with the big giant snowball truck loading up? Do you see more and more of this big enterprise data going into S3, going into Google Cloud, going into Microsoft Azure? >> You're asking-- >> Is this the solution for the data lake swamp issue that we've been talking about? >> You're asking the 64 dollar question. Which is, companies, we sensed a year ago at the at the Hortonworks DataWorks Summit in, was in June, down in San Jose last year. That was where we first got the sense that, people were sort of throwing in the towel on trying to build, large scale big data platforms on-prem. And what changes now is, are they now evaluating Hortonworks versus Cloudera versus MapR in the cloud or are they widening their consideration as Kubo suggests. Because now they want to look, not only at Cloud Native Hadoop, but they actually might want to look at Cloud Native Services that aren't necessarily related to Hadoop. >> Right. Right. And we know as a service wins. It's continue. PAS is a service. Software is a service. Time and time again, as a service either eats a lot of share from the incumbent or knocks the incumbent out. So, Hadoop as a service, regardless of your distro, via one of these types of companies on Amazon, it seems like it's got to win, right. It's going to win. >> Yeah but the difference is, so far, so far, the Clouderas and the MapRs and the Hortonworks of the world are more software than service when they're in the cloud. They don't hide all the knobs. You still need You still a highly trained admin to get them up-- >> But not if you buy it as a service, in theory, right. It's going to be packaged up by somebody else and they'll have your knobs all set. >> They're not designed yet that way. >> HD Insight >> Then, then, then, then, They better be careful cuz it might be a new, as a service distro, of the Hadoop system. >> My point, which is what this is. >> Okay, very good, we'll leave it at that. So George, thanks for spending the day with me. Good show as always. >> And I'll be in a better mood next time when you don't steal my candy bars. >> All right. He's George Goodwin. I'm Jeff Frick. You're watching theCUBE. We're at the historic 99 years young, Wigwam Resort, just outside of Phoenix, Arizona. DataPlatforms 2017. Thanks for watching. It's been a busy season. It'll continue to be a busy season. So keep it tuned. SiliconAngle.TV or YouTube.com/SiliconAngle. Thanks for watching.

>> Live, from The Wigwam, in Phoenix, Arizona, it's theCube, covering Data Platforms 2017. Brought to you by Cue Ball. Hey, welcome back everybody. Jeff Frick here with theCube. Welcome back to Data Platforms 2017, at the historic Wigwam Resort, just outside of Phoenix, Arizona. I'm here all day with George Gilbert from Wikibon, and we're excited to be joined by our next guest. He's Mick Bass, the CEO of 47Lining. Mick, welcome. >> Welcome, thanks for having me, yes. >> Absolutely. So, what is 47Lining, for people that aren't familiar? >> Well, you know every cloud has a silver lining, and if you look at the periodic table, 47 is the atomic number for silver. So, we are a consulting services company that helps customers build out data platforms and ongoing data processes and data machines in Amazon web services. And, one of the primary use cases that we help customers with is to establish data lakes in Amazon web services to help them answer some of their most valuable business questions. >> So, there's always this question about own vs buy, right, with Cloud and Amazon, specifically. >> Mm-hmm, mm-hmm. >> And, with a data lake, the perception right... That's huge, this giant cost. Clearly that's from benefits that come with putting your data lake in AWS vs having it on Primm. What are some of the things you take customers through, and kind of the scenario planning and the value planning? >> Well, just a couple of the really important aspects, one, is this notion of elastic and on-demand pricing. In a Cloud based data lake, you can start out with actually a very small infrastructure footprint that's focused on maybe just one or two business use cases. You can pay only for the data that you need to get your data leg bootstrapped, and demonstrate the business benefit from one of those use cases. But, then it's very easy to scale that up, in a pay as you go kind of a way. The second, you know, really important benefit that customers experience in a platform that's built on AWS, is the breadth of the tools and capabilities that they can bring to bare for their predictive analytics and descriptive analytics, and streaming kinds of data problems. So, you need Spark, you can have it. You need Hive, you can have it. You need a high performance, close to the metal, data warehouse, on a cluster database, you can have it. So, analysts are really empowered through this approach because they can choose the right tool for the right job, and reduce the time to business benefit, based on what their business owners are asking them for. >> You touched on something really interesting, which was... So, when a customer is on Primm, and let's say is evaluating Cloudera, MaPr, Hortonworks, there's a finite set of services or software components within that distro. Once they're on the Cloud, there's a thousand times more... As you were saying, you could have one of 27 different data warehouse products, you could have many different sequel products, some of which are really delivered as services. >> Mm-hmm >> How does the consideration of the customer's choice change when they go to the Cloud? >> Well, I think that what they find is that it's much more tenable to take an agile, iterative process, where they're trying to align the outgoing cost of the data lake build to keep that in alignment with the business benefits that come from it. And, so if you recognize the need for a particular kind of analytics approach, but you're not going to need that until down the road, two or three quarters from now. It's easy to get started with simple use cases, and then like add those incremental services, as the need manifests. One of the things that I mention in my talk, that I always encourage our customers to keep in mind, is that a data lake is more than just a technology construct. It's not just an analysis set of machinery, it's really a business construct. Your data lake has a profit and loss statement, and the way that you interact with your business owners to identify this specific value sources, that you're going to make pop for you company, can be made to align with the cost footprint, as you build your data lake out. >> So I'm curious, when you're taking customers though the journey to start kind of thinking of the data lake and AWS, are there any specific kind of application spaces, or vertical spaces where you have pretty high confidence that you can secure an early, and relatively easy, win to help them kind of move down the road? >> Absolutely. So, you know, many of our customers, in a very common, you know, business need, is to enhance the set of information that they have available for a 360 degree view of the customer. In many cases, this information and data, it's available in different parts of the enterprises, but it might be siloed. And, a data lake approach in AWS really helps you to pull it together in an agile fashion based on particular, quarter by quarter, objectives or capabilities that you're trying to respond to. Another very common example is predictive analytics for things like fraud detection, or mechanical failure. So, in eCommerce kinds of situations, being able to pull together semi-structured information that might be coming from web servers or logs, or like what cookies are associated with this particular user. It's very easy to pull together a fraud oriented predictive analytic. And, then the third area that is very common is internet of things use cases. Many enterprises are augmenting their existing data warehouse with sensor oriented time series data, and there's really no place in the enterprise for that data currently to land. >> So, when you say they are augmenting the data warehouse, are they putting it in the data warehouse, or they putting it in a sort of adjunct, time series database, from which they can sort of curate aggregates, and things like that to put in the data warehouse? >> It's very much the latter, right. And, the time series data itself may come from multiple different vendors and the input formats, in which that information lands, can be pretty diverse. And so, it's not really a good fit for a typical kind of data warehouse ingest or intake process. >> So, if you were to look at, sort of, maturity models for the different use cases, where would we be, you know, like IOT, Customer 360, fraud, things like that? >> I think, you know, so many customers have pretty rich fraud analytics capabilities, but some of the pain points that we hear is that it's difficult for them to access the most recent technologies. In some cases the order management systems that those analytics are running on are quite old. We just finished some work with a customer where literally the order management system's running on a mainframe, even today. Those systems have the ability to accept steer from like a sidecar decision support predictive analytic system. And, one of the things that's really cool about the Cloud is you could build a custom API just for that fraud analytics use case so that you can inject exactly the right information that makes it super cheap and easy for the ops team, that's running that mainframe, to consume the fraud improvement decision signal that you're offering. >> Interesting. And so, this may be diving into the weeds a little bit, but if you've got an order management system that's decades old and you're going to plug-in something that has to meet some stringent performance requirements, how do you, sort of, test... It's not just the end to end performance once, but you know for the 99th percentile, that someone doesn't get locked out for five minutes while he's to trying to finish his shopping cart. >> Exactly. And I mean, I think this is what is important about the concept of building data machines, in the Cloud. This is not like a once and done kind of process. You're not building an analytic that produces a print out that an executive is going to look at (laughing) and make a decision. (laughing) You're really creating a process that runs at consumer scale, and you're going to apply all of the same kinds of metrics of percentile performance that you would apply at any kind of large scale consumer delivery system. >> Do you custom-build, a fraud prevention application for each customer? Or, is there a template and then some additional capabilities that you'll learn by running through their training data? >> Well, I think largely, there are business by business distinctions in the approach that these customers take to fraud detection. There's also business by business direction distinction in their current state. But, what we find is that the commonalities in the kinds of patterns and approaches that you tend to apply. So, you know... We may have extra data about you based on your behavior on the web, and your behavior on a mobile app. The particulars of that data might be different for Enterprise A vs Enterprise B, but this pattern of joining up mobile data plus web data plus, maybe, phone-in call center data. Putting those all together, to increase the signal that can be made available to a fraud prevention algorithm, that's very common across all enterprises. And so, one of the roles that we play is to set up the platform, so that it's really easy to mobilize each of these data sources. So in many cases, it's the customer's data scientist that's saying, I think I know how to do a better job for my business. I just need to be unleashed to be able to access this data, and if I'm blocked, I need a platform where the answer that I get back is oh, you could have that, like, second quarter of 2019. Instead, you want to say, oh, we can onboard that data in an agile fashion pay, and increment a little bit of money because you've identified a specific benefit that could be made available by having that data. >> Alright Mick, well thanks for stopping by. I'm going to send Andy Jassy a note that we found the silver lining to the Cloud (laughing) So, I'm excited for that, if nothing else, so that made the trip well worth while, so thanks for taking a few minutes. >> You bet, thanks so much, guys. >> Alright Mick Bass, George Gilbert, Jeff Frick, you're watching theCube, from Data Platforms 2017. We'll be right back after this short break. Thanks for watching. (computer techno beat)

>> Narrator: Live from the Wigwam in Phoenix Arizona, it's theCUBE, covering data platforms 2017, brought to you by Qubole. >> Hey welcome back everybody, Jeff Frick here with theCUBE. I'm joined by George Gilbert from Wikibond and we're at DataPlatforms 2017. Small conference down at the historic Wigwam Resort, just outside of Phoenix, talking about, kind of a new approach to big data really. A Cloud native approach to big data and really kind of flipping the old model on it's head. We're really excited to be joined by Tripp Smith, he's the CTO of Clarity Insights, up on a panel earlier today. So first off, welcome Tripp. >> Thank you. >> For the folks that aren't familiar with Clarity Insights Give us a little background. >> So Clarity is a pure play data analytics professional services company. That's all we do. We say we advise, build and enable for our client. So what that means, is data strategy, data engineering and data science and making sure that we can action the insights that our customers get out of their data analytics platforms. >> Jeff: So not a real busy area these days. >> It's growing pretty well. >> Good for you. So a lot of interesting stuff came up on the panel. But one of the things that you reacted to, I reacted to as well from the keynote. Was this concept of, you know before you had kind of the data scientist with the data platform behind them, being service providers to the basic business units. Really turning that model on it's head. Giving access to the data to all the business units, and people that want to consume that. Making the data team really enablers of kind of a platform play. Seemed to really resonate with you as well. >> Yeah absolutely, so if you think about it, a lot of the focus on legacy platforms was driven by, scarcity around the resources to deal with data. So you created this almost pyramid structure with IT and architecture at the top. They were the gatekeepers and kind of the single door where Insights got out to the business. >> Jeff: Right. >> So in the big data world and with Cloud, with elastic scale, we've been able to turn that around and actually create much more collaborative friction in parallel with the business. Putting the data engineers, data scientists and business focus analystist together and making them more of partners, than just customers of IT. >> Jeff: Right, very interesting way, to think of it as a partner. It's a very different mindset. The other piece that came up over and over in the Q&A at the end. Was how do people get started? How are they successful? So you deal with a lot of customers, right? That's your business. What are some stories, or one that you can share of best practices, when people come and they say, we obviously hired you, we wrote a check. But how do we get started, where do we go first? How do you help people out? >> We focus on self funding analytic programs. Getting those early wins, tend to pay for more investment in analytics. So if you look at the ability to scale out as a starting point. Then aligning that business value and the roadmap in a way that going to both demonstrate the value along the way, and contribute to that capability is important. I think we also recommend to our clients that they solve the hard problems around security and data governance and compliance first. Because that allows them to deal with more valuable data and put that to work for their business. >> So is there any kind of low hanging fruit that you see time and time and time again? That just is like, ah we can do this. We know it's got huge ROI. It's either neglected cause they don't think it's valuable or it's neglected because it's in the backroom. Or is there any easy steps that you find some patterns? >> Yeah, absolutely. So we go to market by industry vertical. So within each vertical, we've defined the value maps and ROI levers within that business. Then align a lot of our analytic solutions to those ROI levers. In doing that, we focus this on being able to build a small, multifunctional team that can work directly with the business. Then deliver that in real time in an interactive way. >> Right, another thing you just talked about security and government, are we past the security concerns about public Cloud? Does that even come up as an issue anymore? >> You know, I think there was a great comment today that if you had money, you wouldn't put it in your safe at home. You'd put it in a bank. >> Jeff: I missed that one, that's a good one. >> The Cloud providers are really focused on security in a way that they can invest in it. That an individual enterprise really can't. So in a lot of cases, moving to the Cloud means, letting the experts take on the area that they're really good at and letting you focus on your business. >> Jeff: Right, interesting they had, Amazon is here, Google's here, Oracle's here and Azure is here. AWS reinvent one of my favorite things, is Tuesday night with James Hamilton. Which I don't know if you've ever been, it's a can't miss presentation. But he talks about the infrastructure investments that Amazon, AWS can make. Which again, compared to any individual enterprise are tremendous in not only security, but networking and all these other things that they do. So it really seems that the scale that these huge Cloud providers have now reach, gives them such an advantage over any individual enterprise, whether it's for security, or networking or anything else. So it's very different kind of a model. >> Yeah, absolutely, or even the application platform, like Google now having Spanner. Which has the scale advantage of Cassandra or H Based. The transactional capabilities of a traditional RDB mess. I guess my question is. Once a customer is considering Qubole, as a Cloud first data platform. How do you help the customer evaluate it? Relative to the dist rose that started out on Prim, and then the other Cloud native ones that are from Azure and Google and Amazon. >> You know I think that's a great question. It kind of focuses back on, letting the experts do what they're really good at. My business may not be differentiated by my ability to operate and support Hadoop. But it's really putting Hadoop to work in order to solve this business problems that makes me money. So when I look at something like Qubole, it's actually going to that expert and saying, "Hey own this for me and deliver this in a reliable way." Rather than me having to solve those problems over and over again myself. >> Do you think that those problems are not solved to the same degree by the Cloud native services? >> So I think there's definitely an ability to leverage Cloud data services. But there's also this aspect of administration and management, and understanding how those integrate within an ecosystem. That I don't think necessarily every company is going to be able to approach in the same way, that a company like Qubole can. So again, being able to shift that off and having that kind of support gives you the ability to focus back on what really makes a difference for you. >> So Tripp we're running out of time. We got a really tight schedule here. I'm just curious, it's a busy conference season. Big data's all over the place. How did you end up here? What is it about this conference and this technology that got you to come down to the, I think it's only a 106 today, weather to take it in. What do you see that's a special opportunity here? >> Yeah you know, this is Data Platforms 2017. It's been a really great conference, just in the focus on being able to look at Cloud and look at this differentiation. Outside of the realm of inventing new shiny objects and really putting it to work for new business cases and that sort of thing. >> Jeff: Well Tripp Smith, thanks for stopping by theCUBE. >> Excellent, Thank you guys for having me. >> All right, he's George Gilbert, I'm Jeff Frick. You're watching Data Platforms 2017 from the historic Wigwam Resort in Phoenix Arizona. Thanks for watching. (techno music)

>> Narrator: Hi from the Wigwam in Phoenix, Arizona, it is theCUBE, covering Data Platforms 2017. Brought to you by Qubole. >> Hey welcome back everybody. Jeff Frick with theCUBE. We are down at the historic Wigwam 99 years young just outside of Phoenix, Arizona, Data Platforms 2017. It is really talking about a new approach to big data in cloud put on by Qubole about 200 people, very interesting conversation this morning and we're really interested to have Karthik Ramasamy. He is the co-founder of Streamlio which is still in stealth mode according to his LinkedIn profile so we won't talk about that but long time Twitter guy and really shared some great lessons this morning about things that you guys learned while growing Twitter. So welcome. >> Thank you, thanks for having me. >> Absolutely. One of the key parts of your whole talk was this concept of real time. I always joke with people real time is in time to do something about it. You went through a bunch of examples of real time is really a variable depending on what the right application is but at Twitter real time was super, super important. >> Yes it is indeed important because the nature of the streaming data, the nature of the Twitter data is streaming data because the tweets are coming at a high velocity. And Twitter positioned itself as more of a real time delivery company because that way what happens is whatever the information that we get within Twitter we need to have a strong time budget before we can deliver it to people so that people when they consume the information the information is live or real time. >> But the real time too is becoming obviously for Twitter but for lot of big enterprises it is more and more important and the great analogy I referred before is you used a sample data, is the sample historic data to make decisions. Now you want to keep all the data in real time to make decisions, so its a very different way you drive your decision-making process. >> Very different way of thinking. Especially considering the fact as you said the enterprises are getting into understanding what real time means for them and but if you look at some of the traditional enterprise like financial, they understand the value of real time. Similarly the upcoming new used cases like IoT they understand the value of real time like autonomous vehicles where they have to make quick decisions. Healthcare you have to make quick decisions because the preventive and the predictive maintenance is very important in those kind of segments. So because of those segments, its getting really popular and traditional enterprises like retail and all they're also valuing real time because it allows to blend in into the user behavior so that they can recommend products and other things in real time so that people can react to that so that its becoming more and more important. That's what I would say. >> So Hadoop started out as mostly batch infrastructure and Twitter was pioneer in the design pattern to accommodate both batch and in real time. How has that big data infrastructure evolved so that one, you don't have to split batch in real time and what should we expect going forward to make that platform stronger in terms of in your real time analytics and potentially so that it can inform decisions in systems of record. >> I think like today as of now there are two different infrastructures. One is in general is the Hadoop infrastructure. Other one is more of a real time infrastructure at this point. And the Hadoop is kind of considered as this monolithic, not monolithic, its kind of a mega store where every data like similar to all the rivers kind of reach the sea, it kind of becomes a storage sea where all the data comes and stores there. But before the data comes and stores there, lot of analytics and lot of visibility about the data from the point of its creation before it ends up there it setting done on those rive, whatever you call the data river so you could get lot of analytics done during the time before it ends up so that its more live than the other analytics. Hadoop had its own kind of limitations in terms of how much data it can handle, how real time the data can be. For example, you can kind of dump the data in real time into Hadoop but until you close the file you cannot see the data at all. There is a time budget gets into play there. And you could do smaller files like small, small files writing but the namenode will blob because like within a day you write million files, the namenode is not going to sustain that. So those are the trade-off. That's one of the reason we have to end up doing new real time infrastructure like the distributor log that allows you to the moment the data comes in data is immediately visible within the three to five millisecond timeframe. >> The distributed log you're talking about would be Kafka. The output of that would be to train the model or just score a model and then would that model essentially be carved off from this big data platform and be integrated within a system of record where would informed decisions. >> There are multiple things you could do. First of all, the distributed log essentially the data is kind of, you can think about as a data staging environment where the data kind of lands up there and once it lands up there when there's a lot of sharing of that same data going on in real time, when several jobs are taking they're using some popular data source, it provides a high fan out in the sense like 100 jobs can consume the same data they can be at different parts of the data itself. So that provides a nice sharing environment. Now once the data is around there, now the data is being used for different kind of analytics and one of them could be a model enhancement because typically in the back segment you build the model because you're looking at lot of data and other things, then once the model is built that model is pre-loaded into the real time computer environment like HERON then you look up this model and serve data based on that model whatever it tells you. For example when you do a ad serving to look up that model and what is our relevant ad for you to click. Then the next aspect is model enhancement. Because users behavior is going to change, over a period of time. Now can you capture and incrementally update the model so that those things are also partly done on the real time aspects rather than recomputing the batch and again and again and again. >> Okay so its sort of like a what's the delta? >> Karthik: Yes. >> Let's train on the delta and lets score on the delta. >> Yes and once the delta gets updated then when the new user behavior comes in they can look at that new model what that's being continuously being enhanced and once that enhancement is kind of captured you know that user behavior is changing. And ads are served accordingly. >> Okay so now that our customers are getting serious about moving to the cloud with their big data platforms and the applications on them, have you seen a change in the patterns of the apps they're looking to build or a change in the makeup of the platform that they want to use. >> SO that depends on, typically like, one disclosure is I've worked with Amazon and all, the AWS but within the companies that I worked for its everything is an on frame but thing is having said that cloud is nice because it gives you machines on the fly whenever you need to and it gives a bunch of tools around it where you can bootstrap it and all the various stuff. This works ideal for a smaller company and medium companies but the big companies one of the this things that we calculate in terms of the costwise how much is the cost that we have to pay versus doing it inhouse so there's still a huge gap unless cloud provider is going to provide a huge discount or whatever for the big companies to move in. So that is always a challenge that we get into because think about I have 10 or 20,000 notes of Hadoop can I move all of them into Amazon AWS, how much I am going to pay? Versus the cost of maintaining my own data centers and everything. I would say like I don't know the latest pricing and other things but approximately it comes to three x in terms of cost wise. >> If you're using... >> Our own on-prem and the data center and all of the staffing and everything. There's a difference of I would say three x. >> For on-prem being higher. >> On-prem being lower. >> Lower? >> Yes. >> But that assumes then that you've got flat utilization. >> Flat utilization but, I mean cloud of course I have the expands out of scale and all the various thing that you can, it gives an illusion of unlimited resources but in our case if you're provisioning so much machines in most of the at least 50 or 60% of the machines are used for production but the rest of them are used for staging, development, and all the various other environments so which means like the total cost of those machines even though like only is 50% utilized still you end up saving so much shit like operate out one-third of the cost that might be in the cloud. >> Alright Karthik, that opens up a whole can of interesting conversations. Again we just don't have time to jump into. So I'll give you the last word. When can we expect you to come out of stealth or is that stealthy too? >> It is kind of, that is stealthy too. >> Okay fair enough, I don't want to put you on the spot but thanks for stopping by and sharing your story. >> Karthik: Thanks, thanks for everything. >> Alright, he is Karthik, he is George, I'm Jeff. You're watching theCUBE. We are in the Wigwam resort just outside of phoenix at Data Platforms 2017. We will be back after this short break. Thanks for watching.

>> Narrator: Live from New Orleans, it's theCUBE covering VeeamOn 2017 brought to you by Veeam. >> Welcome back to VeeamOn in New Orleans, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante and I'm here with my co-host for the week, Stu Miniman. We're going to talk cloud service providers. Cloud is obviously a very hot topic this week at VeeamOn. Matt Chesterton is here. He's the CEO of OffsideDataSync and he's joined by William Bell who's the vice president of production development for cloud and enterprise services at PhoenixNAP. Gents, welcome to theCUBE. >> Thank you. >> Thanks. >> So, let's start. What's happening at VeeamOn? You heard what I said about, you know, cloud seems to be a major theme here. What are you guys seeing this week? >> We're seeing the same thing. So today is officially cloud day at VeeamOn and some great announcements that are going on so new product announcements with B10, so we're excited about that. >> William, anything you'd add? >> Yeah, I mean, the general session this morning covered so much around cloud and what's that's going to mean to the end user at Veeam. Right, and how the ecosystem is being built and working both with the hyper-scalers and guys like us. >> So, so much talk in the industry about the big, really the big three. Maybe you throw a China cloud in there, a Japan cloud in there, how is it that folks like you all can differentiate from the likes of AWS and Azure and Google. Maybe you can start, Bill, and share with us. >> Yeah, sure, and service. I think that's really the key is that customers need a help. >> Dave: You mean I could talk to you? >> You could talk to me. We can actually help you achieve an outcome that you're looking for with your business. That's not something that you're going to get from a hyper-scaler, period. >> You don't have a little device I can put in my house that I talk to instead? >> No, no new devices, no books, no operating systems to install, just help. >> So your value property is really high-touch. >> High-touch, high-touch for us, it's high-touch global, right? So we can help you do the same things that you're trying to accomplish anywhere in the world talking to the same people, alright? And that's our kind of commitment. >> And yet you've also got infrastructure behind that. >> William: We do. >> So why wouldn't you, for example, could a viable strategy be, say, I'll put that high-touch in front of AWS or Azure? Why not? >> Well, for us, it really comes down to margins, right? At the end of the day, it's that we derive margin from infrastructure just the same way we do from the service angle of that. So if it's only service and there's no margin on the infrastructure it's a tougher business to scale, right? We also can capture markets that are uncapturable. This isn't a cloud business for us, right? We're data center owner-operators. We're doing things that customers need that are not cloud-centric. >> How about you guys, Matt? Little different story here. You guys are more specialized. >> Yeah, little bit, little bit different. So service is always important. We've taken the approach with the public clouds of kind of going with the tide. So layering products and services that go with that. Example, today or yesterday, I think it was announced with the scale-up backup repositories being integrated with storage like Glacier. I'm sure there's a product plan there for a service provider like us so that we can offer that as a service, too. So kind of taking that momentum and working with it. So integrating with what's already going on. It's going to be a tough tide to fight if we don't kind of direct it in the way we want, so we're kind of taking that and going in the direction of how can we use it and how can we benefit from it. >> Matt, can you build on that Veeam as a partner. I think it was Peter McKay told us 30% of their business is to the, you know, thousands and thousands of service providers they have. You know, where do you find opportunity, products, growth when it comes to Veeam? >> Good question, Stu. What Veeam's doing, they make it very easy for us as partners, in the cloud of course, so that when something's delivered, they make a cloud available, as well. So as you can see, users of Veeam can direct their backups and archives to the cloud, private, public, but they've also made that available and are going to make that available for us so they're a great partner. They always think about cloud and cloud first so they don't just develop a product that can be used in and around service providers but that we can take and capitalize from it as well. >> William, what I want to add on there, you're also a VMware partner. Maybe tell us what it's like being a VMware and Veeam and do you go beyond the VMware piece too with Veeam or? >> Yeah, so I mean, in Veeam's ecosystem, VMware and Microsoft are very important to both of them, right? And because of where Veeam started, hyper-V's a large part of their business and growing still very rapidly part of their business, right? And so we're forced to address both sides of that. When we go to build our own infrastructure, when we're going to offer our own services, we've made a commitment to VMware today, right? And we're building services around that ecosystem including the stuff that's happening with Veeam. But let me talk about Veeam as a partner, right? Veeam has been singularly the best manufacturer partner that we've worked with up until this point. Maybe it doesn't mean that somebody else maybe not tomorrow, but at least up until this point, they've help both of our businesses really grow. >> Matt: I couldn't agree more. >> And grow in branding and grow in product diversity and grow all over the place. >> Explain that more. >> Is it simplicity? Is it pricing? Is it, you know, community? >> It's their dedication to us as a partner. So you hear of partner relationships in the community. Veeam has taken it to a new level. They're truly a partner with us. They care about how our business is doing and how they can develop us and how they can find out what we don't have experience with and then help us. So design a program or introduce us to the right folks or make the right alliance relationships. So they genuinely look at it >> So are they a channel for you or are you a channel for them? >> William: Both. >> Yeah, sometimes you don't know. The lines are not exactly clear. And that's good. >> Yeah, I think that those unclear lines means an increase in all kinds of things for both of our companies mutually, right? We're here. We started together in this Veeam ecosystem, you know, three and a half years ago I guess now, and you know, as the first five service providers that were teamed up with Veeam, and we're also both standing here with gigantic platinum sponsorships at their show because it's become that important to us and our business. >> And you guys, I mean, you sell to, your customers are doing everything. They got one of everything in their floor. They're, I'm sure, diverse. You've seen a bunch of folks on stage this week. We saw Microsoft today, Hewlett Packard Enterprise. We saw Cisco yesterday. What kind of relationships do you have with the big whales? >> So we align very well with Cisco. In fact, that's what we power our networks with, and we use their Cisco UCS series for everything we power in our data centers, too. So it's great to see them here and interact with the team. They're a great partner for us. >> And HP Nimble Storage is our other clear-cut top partner, right, in this ecosystem. And there's a great marriage there, both on the integration side, but from a powering these Veeam powered cloud services like offsite backup and Zas recovery requires a lot of storage, right, to take that data in and hold it and replicate it and do things with it. And so our partnership with HP Nimble's large. 6- In some of the expansion that we're seeing Veeam talk about, the kind of new ten years where they're going, some of that is as a service. How do they talk about that dynamic of potentially being a competitor now to the 18,000 great partners that they've had? >> You know, I think a lot of it's got up in a bit of semantics problems, right, semantic issues. Veeam is doing a lot of things that are going to enable services and as a service, I don't see them building solutions that would compete, right? They have a great example of what it looks like to do that with vCloud Air being such a VMware-centric partnership, that was a headwind that they were unable to overcome even the size of VMware, right, going out and building and being a service provider and building an infrastructure service, trying to take their software company and become a service provider, it doesn't work. The same for us, I'm not going to go start building backup software. (laughs) >> So, if you think about the mega phases of cloud. We've been doing this for a long time, and I think back to the early VMworlds that we did, we had so much discussion around cloud, and back in the early days, it was kind of, you know, after Amazon announced AWS and cloud sort of got coined, it was an experiment, it was for startups, and that was pretty clear. And then in sort of 2008 when the economy tanked, a lot of CFOs said, "All right, shift capex to opex." And that was sort of the next phase. And then coming out of the downturn, a lot of lines of business said, "Hey, we got cash. We need speed. Let's go," and started to invest. And then after that IT sort of embraced it. And now seems to be whatever term you want to use, cloud broker or just, they've sort of captured a religion in a nut to hang it onto lun provisioning anymore as a practice. Now I'm wondering if that is a reflection of your world or because you in your case are specialists and you guys are more service oriented, did you ride those waves, was it different ways. Maybe William we can start with you. >> So, our first product line was a 250,000 square foot facility in Phoenix, Arizona, right? Building a kolo, a network access point, that's the heritage of the PhoenixNAP, right, the name, and so we were relying on capex. People to go in and buy equipment and stick it in our facility. Everyone had already decided they didn't want to build data centers. Right, in 2010, everyone's like, "You know what, ten million dollars to get my data room up? No thanks." Right? But they were committed to buying hardware. And we took advantage of that and grew that business and we started to address the opex side in 2012 kind of moving forward. At least we believe we're prime positioned because at the end of the day, it's going to be both. All opex is not the answer, right? I truly believe that. And that's part of that hybrid story, as well. >> And Matt, what about you guys? Again, being specialists in all kinds of things, DR, recovery, etc, did you take a different journey? >> Yeah, Dave, we did. And I heard the term even this week, born in the cloud. If it makes sense, we're a cloud company that had that vision from the beginning. So we didn't build a facility, but that's certainly what we do, leverage space power bandwidth that we partner with Switch and Supernet facilities for our data centers. And we believe that customers are and will continue to move into the opex model into the cloud, so both production work loads and DRAs backup as well. It's interesting to see that mix, too, especially as things from Veeam are announced that really becomes one. So the workloads of DRAs are soon within, you know, 15 minutes or 15 seconds can become a production work load. So if customers aren't necessarily moving their infrastructure to the cloud, it's going to happen one way or the other, whether it's the model of they don't want to purchase hardware any longer or they've had some sort of failure, disaster, and they're going to move that way. >> I want to let you speak a little bit more about your customers. There was a great line, I thought, from Mark Russinovich which said that the C-suite doesn't come asking for infrastructure as a service, they want to figure out how to take their business to the next level. Where are you customers in that kind of cloud strategy and how are you helping them along that journey? >> We have a discussion with them. We try to understand what their business objectives are and what they're trying to achieve by either pushing to the cloud or understanding what the cloud is. And there's a spectrum there from as I mentioned before, backup, disaster recovery as a service, infrastructure as a service, and not all things line up to one single service or way you can put it in the cloud. So we try to understand what their business objectives are and say, "It's going to make the most sense to put some of the work load in the cloud, but some applications stay onsite and you have DRAs replication to get them offsite." So really engaging and understanding what their business needs are and getting under the hood of what they're trying to achieve. >> Yeah, I think that at the end of the day, we are focused on a hybrid future. We truly believe that customers will search for the cloud experience, the business optimization for a period of time where they're saying, "You know what? I don't care. I want this outcome. Go get me this outcome." At some point, it will come back. They will be like, "We have the outcome. How can we optimize this outcome? Are we spending the right amount of money to achieve this outcome?" And the moment they do that, they will find that opex purely and blatantly, if you just say, "I'm all in. I'm always on. I'm only opex." You will spend more money on that over time. If you pick and choose the things that you are incapable of doing or would cost you more to do through capex and staffing, then you can basically position both of those things to maximize value. >> Horses for course, gentlemen, we have to leave it there. Thanks very much for coming on theCUBE, 'preciate it. >> Absolutely. >> Alright, keep it right there everybody. Stu and I will be back with our next guest. We're live from VeeamOn 2017. This is theCUBE.

(calm pop music) >> From Phoenix, Arizona, theCUBE. At Catalyst conference. Here's your host, Jeff Frick. >> Hey, welcome back everybody, Jeff Frick here in Phoenix Arizona, at the Girls in Tech Catalyst Conference. Fourth year of the conference. Going to be back in the Bay Area next year, but again as we've said before, something in the water here in Phoenix because we were here two years ago for the Grace Hopper Conference as well. So a lot of good women in tech action happening in Phoenix. So, we're really excited to have the brainchild behind this whole thing. The force who's really making it happen, Adriana Gascoigne. Welcome. >> Thank you. Good to be here. >> Thanks for having us down. So Adriana, tell us the story of Girls in Tech and Catalyst specifically. >> So Catalyst was an inspiration based on when I worked in intel. We invested, or sponsored a conference, for Oprah. It was called Oprah's O Conference, and what was super compelling about that conference, was that there were 10,000 women in the Moscone Center in San Francisco, and they were engaging and raising their hand, and sharing their own personal stories, trials and tribulations, and speaking about really interesting hot button topics. Such as building a business, or finances, or interior design, things that really were compelling to them. And so what really struck me about this environment is that women actually had a voice. They were encouraged to raise their hand and speak up. And I wanted to do this in the tech world because in a very, gender-scare world, it's important for us to have both voices, right? So, I think this environment enables women to speak up and share their feelings and their passions openly. >> And I think I heard your story early on, where you were at a startup, and you were like the only woman. And then they hired more people, and you were still the only woman, and they hired more people and (chuckles), you were still the only woman. So you kind of lived it firsthand. >> Yeah. So that was sort of the impetus behind Girls in Tech, and I felt that the company, the startup I was working at, wasn't doing enough for recruiting. And recruiting, not just women, but just diverse groups of people, which does affect product development. You need many different perspectives, many different experiences and backgrounds, in order to have a comprehensive product. So I decided to take matters into my own hands, and I started Girls in Tech in 2007, and nine plus years later, we're in 60 cities around the world, and six continents, and 36 countries, with over 40,000 members. So it's awesome to see the growth. I'm now doing it full-time, and the sky's the limit. >> So how do people get involved. What's your kind of, corporate mission statement? And then, if people are watching from some city that you either are in, or maybe you're not, how do they get involved? What does it mean to be involved in Girls in Tech in city X. >> Yeah, so our tagline is, empowerment, engagement, and education of women in tech. So this is an inclusive organization, for both high-tech women who want to learn more about entrepreneurship and leadership, and for women that are in startups that want to be employees, or leaders, or start their own companies. So we've developed curriculum that we prototype and pilot in Silicone Valley, perfect it, and then deploy it to our 60 chapters around the world in electronic press kit format. This is great because we get to customize it with the teams on the ground, and do everything from coding and design boot camps, entrepreneurship boot camps, to the Catalyst Conference, to our lady pitch night competition. Pitch night, not anything else (laughs). >> Yeah, yeah, I got that. Pitch, it's pitch. >> It's pitch. >> You know, we're a PG show, no problem. (laughs) >> And we do an exchange program that brings 20 to 30 female entrepreneurs to Silicone Valley to really experience the nuances of this tech ecosystem, what makes it thrive, learning skills on how to become entrepreneurs, meet and greet with VCs and influential people in Silicone Valley. And we have a few other programs that you can check out on the website. But it's exciting, because it's not one size fits all approach. It's, I'm a woman and there are many different changes I have in my career lifetime. So we want to be there for you within your junior, middle career, as well as a leader. >> Right, and we certainly heard that over and over with the guests that we've had on today, about people changing tracks, changing careers, changing industries, and really this theme of continual learning, continual growing. It's a long journey. We have a saying at our company, you're never there, you're only here, there is still there, and you keep moving down the road and it just keeps moving further out. So a couple three-day conference. What are some of your takeaways, some surprises, over the last three days that you'd like to share? >> Wow, where do I begin? I mean the soundbites are all so stellar, inspirational, skills, best practices, but the thing that really stood out, I think in this year specifically, was people's stories. Their emotional stories, their passions. The things that wake them up in the morning. And they say, yes, I want to change the world and make an impact and love my life while doing it. It was very candid, you know, some of these women really shared difficult situations. And these situations help fuel energy and their fire to make change in their life, to help and pay it forward with up and coming women, and leaders in the tech industry. So it was powerful from the candor, and the friends that were made, and the passions that were shared. >> Awesome. Well I know you got to get back to the conference, you're the master of ceremonies, keeping everything on track. (laughs) So I appreciate you taking a few minutes out of your time to stop by >> It's my pleasure. >> Again, thanks for inviting us to this conference. We're really excited to come down, and we'll look forward to next year's. >> Yeah, next year's going to going to be in the Bay Area. So, in your neck of the woods. >> Awesome. >> Yeah. >> Adriana, again thanks for inviting us. Running a great show, the Girls in Tech Conference. I'm Jeff Frick, you're watching theCUBE. Thanks for watching. We'll catch ya next time. (upbeat pop music)

>> From Phoenix, Arizona The Cube at Catalyst Conference. Here's your host, Jeff Frick. (upbeat music) >> Hey welcome back everybody. Jeff Frick here with The Cube. We are on the ground in Phoenix, Arizona at the Girls in Tech Catalyst Conference. About 400 people, fourth year of the conference. They're going to be back in the Bay area next year. Really a lot of good things going on around the Women in Tech theme that we cover on The Cube, so we wanted to come down, check it out. Our first time here, I'm sure we'll be back again. And we're excited by our next guest, Hilary Weber, the founder and CEO of Opportu. Welcome. >> Thank you. >> So what is Opportu? >> Opportu is an unusual company. It is a coaching and consulting company that focuses on innovation. So I have two main audiences that I work with. >> Okay. >> So startups are one because startups are innovation in essence, but 95 percent of them fail, so we're trying to make sure that less of them fail. And we're focusing on sort of innovating their innovation by a culture focus. >> Mm-hmm. So it kind of process of innovation? Culture of innovation? There's a lot of kind of way to slice that. >> It's both, but it's all around people. It's all around people. And not just startups' struggle with innovation, bigger companies struggle with it too. So what we're trying to do is kind of help startups act a little bit like bigger companies 'cause that's what they're aspiring to be. But really preserving that wonderful culture that they usually have and if they don't have a wonderful culture, making sure we work on that right away. >> Right. >> And then the bigger companies, as companies get bigger and bigger and bigger, they tend to lose their innovation edge and it typically is rooted in culture as well. So we have some interesting tools that we work with. I've been partnering with UC Berkeley on some really cutting edge innovation tools, being able to actually measure a company's propensity for innovation, their capability to innovate. So it's brand new, right? >> Right. Right. >> So that's very exciting. So that's what we do. >> That's great. One of my all-time favorite interviews was with the San Francisco Giants and we interviewed them specifically around the kale garden. Which, I don't know how much kale you eat... >> A lot. >> They put the kale garden behind the center field wall. >> Wow. >> Where you can now go get a salad, and they'll pick it off these hydroponic things growing all the lettuce. It has nothing to do with baseball, but to me it was a fascinating story on a culture of innovation. The Giants are really innovative, Bill Schlough over there, the CIO. To me, it was, who came up with this idea, A, and then was able to get it through their organization to have the confidence to say it, to get it funded, and to actually get it implemented where now you can go stand at the Giant's game and pick a piece of lettuce and they'll put it in a bowl, put some salad dressing and you're eating salad. What are some of the secrets of having a culture of innovation as opposed to just innovation in terms of making interesting things? 'Cause it's really about the culture. >> Well it is. You mentioned the confidence word. Confidence is a big focus. A lot of people think that hiring millennials is going to solve their innovation problem. Maybe yes, maybe no. It's really the mix. It's how are these people collaborating, how free is that newest newbie to share an idea? If you get in there and you realize this company operates by having ideas come from the top down, and I'm not going to stick my neck out. >> Right. >> And especially for women. And especially for women, since we're here at Girls in Tech, where they're by far the minority around the table, so the risk of them speaking up is higher for them. They feel more of an outsider. >> Sure. >> So, figuring out ways to honor the diversity rather than make it be a problem and creating a team that just fires on all cylinders, and so ideas just come. >> So if I'm running a company, and I know I've got a disproportionate, a bunch of male engineers of the tech company, what are some of the things that I can do to help to encourage that young woman with this great idea to get it out of her? To make it comfortable for her to share? What are some of the things that I can do from this side of the table to really enable that? >> I think part of it is really raising the awareness of what it's like for others. There are multiple tools out there that you can use but sometimes working with someone from the outside that can help them see things differently. The function of a coach is often holding up a mirror. And when you're inside of something it is really hard to see what's really going on. Sometimes I'll describe to the startups that we work with, I'll say, "If you're on the inside of an apple, it looks all white with these big black seeds. From out here, it looks shiny and red. It's still an apple, but it looks very different from the inside to the outside." So having a different perspective. The other thing is that kind of vibe starts with the leader. They have to model the behavior. They have to look at their own behavior and see, what am I doing or not doing that is encouraging that and enabling that. And, maybe hire some more women. Have women on your board. It's proven. You have a woman on your board, you get 20 percent more revenue and productivity. >> Right. >> There's statistics all around that. >> So do you find the value in what you do, a large part of it is simply putting the mirror on? There's techniques and stuff but just get, take a minute, take a breath, look at what's happening here from the outside and you'll see and it'll be more obvious. Do people just get kind of wrapped up in the way they've always done things, or busy, they don't really have time to lift their head up and take a breath? What do you find in you clients? >> Awareness is the first step, certainly. >> They wouldn't bring you in, right, if they didn't want to make improvements. >> Precisely. Precisely. If there's a lack of awareness, then a lot of times it's... >> A self perpetuated thing. >> Yeah, exactly. But a lot of times there'll be sort of a moment that will happen, unfortunately sometimes where somebody's super unhappy or there's a lawsuit or something like that. That's an extreme case but... >> But sometimes it takes a catalyst like that, unfortunately, right. >> Sometimes, sometimes. But hopefully you've got one or two people who are, "we're at a certain stage where I think we need to really up our leadership game, up our professional development, look at things differently. We're losing too many people." Those kind of things. >> Right. What tips for the woman on the other side of the table? You're by yourself, you're outnumbered, maybe you're not as loud, maybe you're not 100 percent sure that this is the answer you want to give or the suggestion you want to make, but you think its got legs. What are some of the tips and tricks that you give them to get your voice out? How do you kind of counsel ways that they can get that out? >> Mm-hmm. Well, confidence comes in all forms. Women tend to have been successful in their lives, there's statistics on this too, where we tend to be rule followers when we're younger, right? We get all A's, we get the praise of the teacher. And we finally get to the workplace and kind of following all the rules really doesn't work. So they haven't had a lot of chances to fail, basically. >> Right, right. >> So I kind of give them failure lessons. Learn how to fail at something small. One of my clients went out and did trivia night with her friends, and she knew she was going to not do well in some categories, even though she's super smart. >> I should practice doing that. >> To kind of flex the failure muscle and be okay with, not all your ideas are going to be winners, and it's okay. >> Right, right. >> The other thing I would really say is take a look at your own values. I have a values assessment that I put on my website so anybody can do it. I think it's really underutilized for individuals and for companies to do a values assessment. "What do I really care about? What are the battles that I am going to go to the ends of the earth to get to? What are the things that I really want to promote and why?" If you know that inside of yourself, that can really fuel your confidence when you're sitting in a meeting where it's a little bit scary. >> Right, but that almost, again sounds like the mirror thing that you talked about before. It's reconnecting with those values in the context of the moment as opposed to, you know we all just get so busy. You're just wrapped up with getting stuff done and trying to get through, whatever you're trying to get through. >> Exactly. And I think a lot of people either go through their day kind of just trying to get through the day, kind of please just get me to the end, or they get into fight mode, where they're just like, it's me or you and that doesn't really work. Trying to get out of that sort of overly me orientation and starting to think about how can we make this something better. How can we be more than the sum of our parts? >> Right, right. Important stuff you're working on there, Hilary. So how could people learn more, how could they reach out and connect with you? >> They can go to Opportu dot com. O-P-P-O-R-T-U dot com. They can email me, H Weber, with one b, H-W-E-B-E-R at Opportu dot com or find me on Twitter or Facebook. >> Excellent. Well thank you for taking a few minutes. Really important stuff you're working on. >> Thank you very much. >> All right. Hilary Weber, I'm Jeff Frick, we are at the Girls in Tech Catalyst Conference in Phoenix, Arizona. You're watching The Cube. Thanks for watching.

(upbeat music) >> From Phoenix, Arizona, theCUBE, at Catalyst Conference. Here's your host, JefF Frick. (upbeat music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are in Phoenix, Arizona at the Girls in Tech Catalyst Conference. About 400 people, fourth year of the conference. Something in the water here in Phoenix, every time we come down here to some Women in Tech event. We were here two years ago for the Grace Hopper Celebration of Women in Computing which was fantastic, so we're really happy to be here, get a wide variety, really of women in tech stories from the people here at the conference, so we're excited by our next guest, Tejal Shah, the founder and CEO of Kid Admit. Welcome. >> Well thank you for having me. >> So what is Kid Admit? >> So we help parents search, compare, and apply to preschools based on criteria that's important to them. And so we partner with the schools, we give them the technology to bring their admissions process online, hence making it easier for parents to find schools nearby to them and based on criteria like philosophy that's important, schedule, that sort of stuff. >> So just for preschool? >> Right now just for preschool. The bigger vision is to add more products and services as the kids get older and so we'll have this great, rich data set of information on parents, so then we can give them more relevant recommendations and things that fit in their lives for their kids, like other extracurricular activities and that sort of stuff. >> So it's kind of like helping people with the college admissions process but for-- >> For preschool. >> The five year old right? So I mean, I've got kids, it seems like it's really kind of a function of proximity, is probably the number one thing, or is it in route to my office so I can drop the kid on the way to or from. What are some of the factors that are less obvious that people use in kind of deciding where they want their child to go to preschool? >> Yeah, I mean parenting has changed, because everything is available on the tips of your smartphone, so everyone is researching so many more things that are trying to make it more relevant to the child. It's not like, "Oh we're going to send the kid down the street "to the nearby preschool" anymore. It's like, "Oh we really want this philosophy "because they're going to excel in that." And really, that's kind of the more subtle things that parents are doing now is because it's so easy to find this information, matching up what's going to make their child succeed in these environments. >> And then how are the preschools, because now that you are saying that, I'm thinking of all these preschools in our neighborhood, that are very, very different, in kind of look and feel and the way they operate. How are you collecting that data, how are they getting you that data? How excited are they to have the opportunity to actually communicate how they're different, rather than whether they're on the main strip to the freeway? >> Yeah, it's actually really exciting, because I think the technology has changed so much since we started Kid Admit. And at first, there was a little bit of hesitancy, because people are like, "What are you doing? "What is this? "Why do you need a technology solution here?" And as technology has changed so drastic in the last few years, all of these schools are very excited to be part of a platform that makes their reach a lot bigger. You don't have to just put up fliers in your neighborhood anymore. You can attract people in a slightly bigger geo code. And there's been a lot of new preschools opening up as well for the demand. And it's nice for them to be able to be a part of a platform and easily get to families really quickly. >> Okay, so just a little bit more on Kid Admit. So you said you're three and a half years old? >> Yes, correct. >> And did you raise some outside funding? >> Yes, we raised 1.15 million dollars over a pre-seed and a seed round, so we're still early stage. >> Congratulations. >> Thank you. >> And what metro areas do you operate in? >> So we're in about 9,000 preschools across 20 states, and we're poised to be nationwide soon. So we are actually here in Phoenix, we just launched here recently, which has been pretty exciting. And yeah, so we actually have listings for more than that many schools, but the ones that partner with us. So we get the information from the state licensing, and then we do our own data, and get more data on our data-mining efforts. After that, we reach out to the schools directly, so they become member schools, and then they can add any information that they need that makes their program special. And with that, once they be part of the platform, then it's easier for parents to navigate the whole process. >> And from how many preschools do generally people kind of search through, what's kind of their tam if you will when they're trying to figure out their preschool? They start with how many and whittle it down to one, what do you kind of see? >> Yeah, so it's interesting. Most people only hear about five, and then you go on Kid Admit and the search in San Francisco, there's 357 preschools so, obviously that's not the pool that they're going to go after, it's probably based on a couple of criteria filters, it will probably whittle down to maybe 10. And so now you're not researching 350, you're getting down to 10. But even if they go a little bit specific, it's usually they'll really evaluate about four to five. >> And what are the top five factors? Not necessarily the value in the factors, but the factors that they're looking at that help drive the decision? >> Yeah, location is definitely a big, big factor. You want to make your life as convenient as possible, and you don't want to have to, if you're dealing with work, and kids, and if you have multiple kids, you want to keep that obviously pretty proximal. And it could be on your way to work too, like you mentioned earlier. Then philosophy, so Montessori, Reggio, is it play based, those, and schedule is a big thing, whether you want part-time or full-time. Interestingly, people talk about price, but ends up being a secondary factor, cause people want what's best for their children, and they want to see what all of those options that are available. >> What is the most surprising factor that you had no idea mattered so much to people as you've gone through this process? >> That they think that it's going to dictate the rest of their child's life on this first educational milestone. And it's just surprising that how it's completely false. And it's just crazy to see how much people still buy into this. >> Right, right. It's like the old Seinfeld episodes right? From Manhattan, and people trying to get in that first, getting in that school, but that's not what you're about at all, you're really about just knowing what the options are and finding the right fit. >> Yeah, we want to like democratize it a little bit, get the access to it. So a lot of people in Manhattan, or even San Francisco hire consultants to help for this, and they're like $15,000 to help you just with preschool. And so you can search Kid Admit for free, you get to see all the information, things that giving access to more families to make better choices for their kids, and it's all about finding a nice environment for your kid, who's going to develop a life-long love of learning. That's the only thing about preschool that makes it great. >> And how did you come up with this idea? >> So I have kids myself, and I went through the process. It was super, super crazy cause Google didn't spit out any results when I did this, my oldest one's seven and a half. And when I was pregnant, people were like, "Are you on the wait list?" I'm like, "I don't even know my child, "how am I going to go and find a preschool at this stage?" So I didn't take that advice, I'm like, "You know what. "I will do this when it's appropriate, "and I feel comfortable." And I did, and then I created this crazy spreadsheet, and cause there wasn't a lot of information available on the internet, so I'd have to call around, and ended up being another full-time job of mine. And once I created this, then a lot of my friends started using it, and using it, and so that was kind of the start of Kid Admit. >> Awesome. So we've had a lot of conversations here over the course of the day, about pivoting and getting involved in tech, and not necessarily being a tech person, and changing career paths. We talked a little bit offline before we came on air, you've got kind of an interesting journey. You started out as a mechanical engineer I think you said, and then got into finance, and now you're doing a kid based, basically marketplace exchange. >> Yes. >> How did that happen? I think I've always wanted to be an entrepreneur, though I didn't quite, was not truthful to myself when I was younger. I became a mechanical engineer. I worked at Ford Motor Company right out of school designing fuel systems, and then I did a lot of other things. Ended up in finance and I kept switching these careers, but I learned all these different skill sets. And all these different things then when you become CEO and start a company, they actually really are very relevant cause you get to, I have to book keep, and manage my own finances for the start-up. I've had to, for when I did financial services, I also cold called. I did that when I started doing early customer development. I did marketing for a medical devices company a long time ago and that's part of it. So all of this journey, as different as it is, it kind of led me to be able to be a generalist to start a company. >> Right, and then what was the tipping point that you said, "Okay, I'm doing it. "I'm going to start this company, I'm going to quit my job and do this?" >> Yeah, so I wanted to leave financial services after 2008. So it's been a-- >> Good timing. >> Yeah, well, but I still stuck onto it for two more years, because in that timeframe, actually four more years, in 2010 we left to start our own wealth management firm, my husband and I, and then I wanted to ramp that up before I could actually formally leave to start my own. So I always wanted knew I did it, but I wanted to have the timing, as well as the idea. >> Right, right. Okay so we're running low on time. So what advice would you give to the budding entrepreneur out there that's got an idea, that's just needs that final little kick out of the nest to go for it? What are some of the learnings that you can share, and advice that you would give them? >> Yeah, you'll never have, you'll never be ready. Just like anything else in life. You just have to kind of take that leap of faith. You're not going to know everything on the journey, and there's something sweet about that. It's something, I kind of miss some of the naitivity I had when I first started this because it keeps you really excited and passionate and relevant in that. And tenacity, resourcefulness, you definitely have to have those things. And just enjoy the journey cause as much as it's a high and low and roller coaster of a start-up experience, you definitely have to enjoy it. And I've gotten to do some really amazing, amazing things and meet some incredible people along the way, and I relish those times. >> Excellent. Well, Tejal thanks for sharing your story with us. >> Well thank you, thanks for having me. >> Absolutely. So great story on entrepreneurship. Eventually you've got to jump out of the nest. It's never easy, but as you said, there's never a right time. You just got to go for it, like everything else that's important in life. So thanks for watching, we're here at the Girls in Tech Catalyst Conference. I'm Jeff Frick, you're watching theCUBE. Thanks for watching. (upbeat music)