>>The Cube presents Ignite 22, brought to you by Palo Alto Networks. >>Welcome back to Vegas. Guys. We're happy that you're here. Lisa Martin here covering with Dave Valante, Palo Alto Networks Ignite 22. We're at MGM Grand. This is our first day, Dave of two days of cube coverage. We've been having great conversations with the ecosystem with Palo Alto executives, with partners. One of the things that they have is unit 42. We're gonna be talking with them next about cyber intelligence. And the threat data that they get is >>Incredible. Yeah. They have all the data, they know what's going on, and of course things are changing. The state of play changes. Hold on a second. I got a text here. Oh, my Netflix account was frozen. Should I click on this link? Yeah. What do you think? Have you had a, it's, have you had a little bit more of that this holiday season? Yeah, definitely. >>Unbelievable, right? A lot of smishing going on. >>Yeah, they're very clever. >>Yeah, we're very pleased to welcome back one of our alumni to the queue. Wendy Whitmore is here, the SVP of Unit 42. Welcome back, Wendy. Great to have >>You. Thanks Lisa. So >>Unit 42 created back in 2014. One of the things that I saw that you said in your keynote this morning or today was everything old is still around and it's co, it's way more prolific than ever. What are some of the things that Unit 42 is seeing these days with, with respect to cyber threats as the landscape has changed so much the last two years alone? >>You know, it, it has. So it's really interesting. I've been responding to these breaches for over two decades now, and I can tell you that there are a lot of new and novel techniques. I love that you already highlighted Smishing, right? In the opening gate. Right. Because that is something that a year ago, no one knew what that word was. I mean, we, it's probably gonna be invented this year, right? But that said, so many of the tactics that we have previously seen, when it comes to just general espionage techniques, right? Data act filtration, intellectual property theft, those are going on now more than ever. And you're not hearing about them as much in the news because there are so many other things, right? We're under the landscape of a major war going on between Russia and Ukraine of ransomware attacks, you know, occurring on a weekly basis. And so we keep hearing about those, but ultimately these nations aid actors are using that top cover, if you will, as a great distraction. It's almost like a perfect storm for them to continue conducting so much cyber espionage work that like we may not be feeling that today, but years down the road, they're, the work that they're doing today is gonna have really significant impact. >>Ransomware has become a household word in the last couple of years. I think even my mom knows what it is, to some degree. Yeah. But the threat actors are far more sophisticated than they've ever written. They're very motivated. They're very well funded. I think I've read a stat recently in the last year that there's a ransomware attack once every 11 seconds. And of course we only hear about the big ones. But that is a concern that goes all the way up to the board. >>Yeah. You know, we have a stat in our ransomware threat report that talks about how often victims are posted on leak sites. And I think it's once every seven minutes at this point that a new victim is posted. Meaning a victim has had their data, a victim organization had their data stolen and posted on some leak site in the attempt to be extorted. So that has become so common. One of the shifts that we've seen this year in particular and in recent months, you know, a year ago when I was at Ignite, which was virtual, we talked about quadruple extortion, meaning four different ways that these ransomware actors would go out and try to make money from these attacks in what they're doing now is often going to just one, which is, I don't even wanna bother with encrypting your data now, because that means that in order to get paid, I probably have to decrypt it. Right? That's a lot of work. It's time consuming. It's kind of painstaking. And so what they've really looked to do now is do the extortion where they simply steal the data and then threaten to post it on these leak sites, you know, release it other parts of the web and, and go from there. And so that's really a blending of these techniques of traditional cyber espionage with intellectual property theft. Wow. >>How trustworthy are those guys in terms of, I mean, these are hackers, right? In terms of it's really the, the hacker honor system, isn't it? I mean, if you get compromised like that, you really beholden to criminals. And so, you >>Know, so that's one of the key reasons why having the threat intelligence is so important, right? Understanding which group that you're dealing with and what their likelihood of paying is, what's their modus operandi. It's become even more important now because these groups switch teams more frequently than NFL trades, you know, free agents during the regular season, right? Or players become free agents. And that's because their infrastructure. So the, you know, infrastructure, the servers, the systems that they're using to conduct these attacks from is actually largely being disrupted more from law enforcement, international intelligence agencies working together with public private partnerships. So what they're doing is saying, okay, great. All that infrastructure that I just had now is, is burned, right? It's no longer effective. So then they'll disband a team and then they'll recruit a new team and it's constant like mixing and matching in players. >>All that said, even though that's highly dynamic, one of the other areas that they pride themselves on is customer service. So, and I think it's interesting because, you know, when I said they're not wanting to like do all the decryption? Yeah. Cuz that's like painful techni technical slow work. But on the customer service side, they will create these customer service portals immediately stand one up, say, you know, hey it's, it's like an Amazon, you know, if you've ever had to return a package on Amazon for example, and you need to click through and like explain, you know, Hey, I didn't receive this package. A portal window pops up, you start talking to either a bot or a live agent on the backend. In this case they're hu what appeared to be very much humans who are explaining to you exactly what happened, what they're asking for, super pleasant, getting back within minutes of a response. And they know that in order for them to get paid, they need to have good customer service because otherwise they're not going to, you know, have a business. How, >>So what's the state of play look like from between nation states, criminals and how, how difficult or not so difficult is it for you to identify? Do you have clear signatures? My understanding in with Solar Winds it was a little harder, but maybe help us understand and help our audience understand what the state of play is right now. >>One of the interesting things that I think is occurring, and I highlighted this this morning, is this idea of convergence. And so I'll break it down for one example relates to the type of malware or tools that these attackers use. So traditionally, if we looked at a nation state actor like China or Russia, they were very, very specific and very strategic about the types of victims that they were going to go after when they had zero day. So, you know, new, new malware out there, new vulnerabilities that could be exploited only by them because the rest of the world didn't know about it. They might have one organization that they would target that at, at most, a handful and all very strategic for their objective. They wanted to keep that a secret as long as possible. Now what we're seeing actually is those same attackers going towards one, a much larger supply chain. >>So, so lorenzen is a great example of that. The Hafnia attacks towards Microsoft Exchange server last year. All great examples of that. But what they're also doing is instead of using zero days as much, or you know, because those are expensive to build, they take a lot of time, a lot of funding, a lot of patience and research. What they're doing is using commercially available tools. And so there's a tool that our team identified earlier this year called Brute Rael, C4 or BRC four for short. And that's a tool that we now know that nation state actors are using. But just two weeks ago we invested a ransomware attack where the ransomware actor was using that same piece of tooling. So to your point, yak can get difficult for defenders when you're looking through and saying, well wait, they're all using some of the same tools right now and some of the same approaches when it comes to nation states, that's great for them because they can blend into the noise and it makes it harder to identify as >>Quickly. And, and is that an example of living off the land or is that B BRC four sort of a homegrown hacker tool? Is it, is it a, is it a commercial >>Off the shelf? So it's a tool that was actually, so you can purchase it, I believe it's about 2,500 US dollars for a license. It was actually created by a former Red teamer from a couple well-known companies in the industry who then decided, well hey, I built this tool for work, I'm gonna sell this. Well great for Red teamers that are, you know, legitimately doing good work, but not great now because they're, they built a, a strong tool that has the ability to hide amongst a, a lot of protocols. It can actually hide within Slack and teams to where you can't even see the data is being exfiltrated. And so there's a lot of concern. And then now the reality that it gets into the wrong hands of nation state actors in ransomware actors, one of the really interesting things about that piece of malware is it has a setting where you can change wallpaper. And I don't know if you know offhand, you know what that means, but you know, if that comes to mind, what you would do with it. Well certainly a nation state actor is never gonna do something like that, right? But who likes to do that are ransomware actors who can go in and change the background wallpaper on a desktop that says you've been hacked by XYZ organization and let you know what's going on. So pretty interesting, obviously the developer doing some work there for different parts of the, you know, nefarious community. >>Tremendous amount of sophistication that's gone on the last couple of years alone. I was just reading that Unit 42 is now a founding member of the Cyber Threat Alliance includes now more than 35 organizations. So you guys are getting a very broad picture of today's threat landscape. How can customers actually achieve cyber resilience? Is it achievable and how do you help? >>So I, I think it is achievable. So let me kind of parse out the question, right. So the Cyber Threat Alliance, the J C D C, the Cyber Safety Review Board, which I'm a member of, right? I think one of the really cool things about Palo Alto Networks is just our partnerships. So those are just a handful. We've got partnerships with over 200 organizations. We work closely with the Ukrainian cert, for example, sharing information, incredible information about like what's going on in the war, sharing technical details. We do that with Interpol on a daily basis where, you know, we're sharing information. Just last week the Africa cyber surge operation was announced where millions of nodes were taken down that were part of these larger, you know, system of C2 channels that attackers are using to conduct exploits and attacks throughout the world. So super exciting in that regard and it's something that we're really passionate about at Palo Alto Networks in terms of resilience, a few things, you know, one is visibility, so really having a, an understanding of in a real, as much of real time as possible, right? What's happening. And then it goes into how you, how can we decrease operational impact. So that's everything from network segmentation to wanna add the terms and phrases I like to use a lot is the win is really increasing the time it takes for the attackers to get their work done and decreasing the amount of time it takes for the defenders to get their work done, right? >>Yeah. I I call it increasing the denominator, right? And the ROI equation benefit over or value, right? Equals equals or benefit equals value over cost if you can increase the cost to go go elsewhere, right? Absolutely. And that's the, that's the game. Yeah. You mentioned Ukraine before, what have we learned from Ukraine? I, I remember I was talking to Robert Gates years ago, 2016 I think, and I was asking him, yeah, but don't we have the best cyber technology? Can't we attack? He said, we got the most to lose too. Yeah. And so what have we learned from, from Ukraine? >>Well, I, I think that's part of the key point there, right? Is you know, a great offense essentially can also be for us, you know, deterrent. So in that aspect we have as an, as a company and or excuse me, as a country, as a company as well, but then as partners throughout all parts of the world have really focused on increasing the intelligence sharing and specifically, you know, I mentioned Ukrainian cert. There are so many different agencies and other sorts throughout the world that are doing everything they can to share information to help protect human life there. And so what we've really been concerned with, with is, you know, what cyber warfare elements are going to be used there, not only how does that impact Ukraine, but how does it potentially spread out to other parts of the world critical infrastructure. So you've seen that, you know, I mentioned CS rrb, but cisa, right? >>CISA has done a tremendous job of continuously getting out information and doing everything they can to make sure that we are collaborating at a commercial level. You know, we are sharing information and intelligence more than ever before. So partners like Mania and CrowdStrike, our Intel teams are working together on a daily basis to make sure that we're able to protect not only our clients, but certainly if we've got any information relevant that we can share that as well. And I think if there's any silver lining to an otherwise very awful situation, I think the fact that is has accelerated intelligence sharing is really positive. >>I was gonna ask you about this cause I think, you know, 10 or so years ago, there was a lot of talk about that, but the industry, you know, kind of kept things to themselves, you know, a a actually tried to monetize some of that private data. So that's changing is what I'm hearing from you >>More so than ever more, you know, I've, I mentioned I've been in the field for 20 years. You know, it, it's tough when you have a commercial business that relies on, you know, information to, in order to pay people's salaries, right? I think that has changed quite a lot. We see the benefit of just that continuous sharing. There are, you know, so many more walls broken down between these commercial competitors, but also the work on the public private partnership side has really increased some of those relationships. Made it easier. And you know, I have to give a whole lot of credit and mention sisa, like the fact that during log four J, like they had GitHub repositories, they were using Slack, they were using Twitter. So the government has really started pushing forward with a lot of the newer leadership that's in place to say, Hey, we're gonna use tools and technology that works to share and disseminate information as quickly as we can. Right? That's fantastic. That's helping everybody. >>We knew that every industry, no, nobody's spared of this. But did you notice in the last couple of years, any industries in particular that are more vulnerable? Like I think of healthcare with personal health information or financial services, any industries kind of jump out as being more susceptible than others? >>So I think those two are always gonna be at the forefront, right? Financial services and healthcare. But what's been really top of mind is critical infrastructure, just making sure right? That our water, our power, our fuel, so many other parts of right, the ecosystem that go into making sure that, you know, we're keeping, you know, houses heated during the winter, for example, that people have fresh water. Those are extremely critical. And so that is really a massive area of focus for the industry right now. >>Can I come back to public-private partnerships? My question is relates to regulations because the public policy tends to be behind tech, the technology industry as an understatement. So when you take something like GDPR is the obvious example, but there are many, many others, data sovereignty, you can't move the data. Are are, are, is there tension between your desire as our desire as an industry to share data and government's desire to keep data private and restrict that data sharing? How is that playing out? How do you resolve that? >>Well I think there have been great strides right in each of those areas. So in terms of regulation when it comes to breaches there, you know, has been a tendency in the past to do victim shaming, right? And for organizations to not want to come forward because they're concerned about the monetary funds, right? I think there's been tremendous acceleration. You're seeing that everywhere from the fbi, from cisa, to really working very closely with organizations to, to have a true impact. So one example would be a ransomware attack that occurred. This was for a client of ours within the United States and we had a very close relationship with the FBI at that local field office and made a phone call. This was 7:00 AM Eastern time. And this was an organization that had this breach gone public, would've made worldwide news. There would've been a very big impact because it would've taken a lot of their systems offline. >>Within the 30 minutes that local FBI office was on site said, we just saw this piece of malware last week, we have a decryptor for it from another organization who shared it with us. Here you go. And within 60 minutes, every system was back up and running. Our teams were able to respond and get that disseminated quickly. So efforts like that, I think the government has made a tremendous amount of headway into improving relationships. Is there always gonna be some tension between, you know, competing, you know, organizations? Sure. But I think that we're doing a whole lot to progress it, >>But governments will make exceptions in that case. Especially for something as critical as the example that you just gave and be able to, you know, do a reach around, if you will, on, on onerous regulations that, that ne aren't helpful in that situation, but certainly do a lot of good in terms of protecting privacy. >>Well, and I think there used to be exceptions made typically only for national security elements, right? And now you're seeing that expanding much more so, which I think is also positive. Right. >>Last question for you as we are wrapping up time here. What can organizations really do to stay ahead of the curve when it comes to, to threat actors? We've got internal external threats. What can they really do to just be ahead of that curve? Is that possible? >>Well, it is now, it's not an easy task so I'm not gonna, you know, trivialize it. But I think that one, having relationships with right organizations in advance always a good thing. That's a, everything from certainly a commercial relationships, but also your peers, right? There's all kinds of fantastic industry spec specific information sharing organizations. I think the biggest thing that impacts is having education across your executive team and testing regularly, right? Having a plan in place, testing it. And it's not just the security pieces of it, right? As security responders, we live these attacks every day, but it's making sure that your general counsel and your head of operations and your CEO knows what to do. Your board of directors, do they know what to do when they receive a phone call from Bloomberg, for example? Are they supposed supposed to answer? Do your employees know that those kind of communications in advance and training can be really critical and make or break a difference in an attack. >>That's a great point about the testing but also the communication that it really needs to be company wide. Everyone at every level needs to know how to react. Wendy, it's been so great having, >>Wait one last question. Sure. Do you have a favorite superhero growing up? >>Ooh, it's gotta be Wonder Woman. Yeah, >>Yeah, okay. Yeah, so cuz I'm always curious, there's not a lot of women in, in security in cyber. How'd you get into it? And many cyber pros like wanna save the world? >>Yeah, no, that's a great question. So I joined the Air Force, you know, I, I was a special agent doing computer crime investigations and that was a great job. And I learned about that from, we had an alumni day and all these alumni came in from the university and they were in flight suits and combat gear. And there was one woman who had long blonde flowing hair and a black suit and high heels and she was carrying a gun. What did she do? Because that's what I wanted do. >>Awesome. Love it. We >>Blonde >>Wonder Woman. >>Exactly. Wonder Woman. Wendy, it's been so great having you on the program. We, we will definitely be following unit 42 and all the great stuff that you guys are doing. Keep up the good >>Work. Thanks so much Lisa. Thank >>You. Day our pleasure. For our guest and Dave Valante, I'm Lisa Martin, live in Las Vegas at MGM Grand for Palo Alto Ignite, 22. You're watching the Cube, the leader in live enterprise and emerging tech coverage.

(upbeat music) >> Welcome back everyone to The Cubes coverage here in Seattle, Washington. For AWS's Marketplace Seller Conference. It's the big news within the Amazon partner network, combining with marketplace, forming the Amazon partner organization. Part of a big reorg as they grow to the next level, NextGen cloud, mid-game on the chessboard. Cube's got it covered. I'm John Furry, your host at Cube. Great guests here from Data bricks. Both cube alumni's. Jack Anderson, GM and VP of the Databricks partnership team for AWS. You handle that relationship and Joel Minick vice president of product and partner marketing. You guys have the keys to the kingdom with Databricks and AWS. Thanks for joining. Good to see you again. >> Thanks for having us back. >> Yeah, John, great to be here. >> So I feel like we're at Reinvent 2013. Small event, no stage, but there's a real shift happening with procurement. Obviously it's a no brainer on the micro, you know, people should be buying online. Self-service, Cloud Scale. But Amazon's got billions being sold through their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website, marketplace. Merge our partner organizations, have more synergy and frictionless experiences so everyone can make more money and customer's are going to be happier. >> Yeah, that's right. >> I mean, you're running relationship. You're in the middle of it. >> Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do, is to work with Amazon on these really, you know, unique use cases. >> You know, I interviewed Ali many times over the years. I remember many years ago, maybe six, seven years ago, we were talking. He's like, "we're all in on AWS." Obviously now the success of Databricks, you've got multiple clouds, see that. Customers have choice. But I remember the strategy early on. It was like, we're going to be deep. So this is, speaks volumes to the relationship you have. Years. Jack, take us through the relationship that Databricks has with AWS from a partner perspective. Joel, and from a product perspective. Because it's not like you guys are Johnny come lately, new to the scene. >> Right. >> You've been there, almost president creation of this wave. What's the relationship and how does it relate to what's going on today? >> So most people may not know that Databricks was born on AWS. We actually did our first $100 million of revenue on Amazon. And today we're obviously available on multiple clouds. But we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon, and marketplace broadens our reach. And so, we think of marketplace in three different aspects. We've got the marketplace private offer business, which we've been doing for a number of years. Matter of fact, we were driving well over a hundred percent year over year growth in private offers. And we have a nine figure business. So it's a very significant business. And when a customer uses a private offer, that private offer counts against their private pricing agreement with AWS. So they get pricing power against their private pricing. So it's really important it goes on their Amazon bill. In may we launched our pay as you go, on demand offering. And in five short months, we have well over a thousand subscribers. And what this does, is it really reduces the barriers to entry. It's low friction. So anybody in an enterprise or startup or public sector company can start to use Databricks on AWS, in a consumption based model, and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation, pilots, POCs. They're really learning the value of that first, use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offer, CPPO. Super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with Databricks on behalf of customers. >> So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data, coming in with the buyers you get. And obviously the integration piece all fitting in there. >> Exactly. >> Okay, so those are the offers, that's current, what's in marketplace today. Is that the products... What are people buying? >> Yeah. >> I mean, I guess what's the... Joel, what are people buying in the marketplace? And what does it mean for them? >> So fundamentally what they're buying is the ability to take silos out of their organization. And that is the problem that Databricks is out there to solve. Which is, when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data. And your teams are trying to use all of this data to solve really complicated problems. And as Databricks, as the Lakehouse Company, what we're helping customers do is, how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find, through the marketplace, those rapid adoption use cases where they can get rid of these data warehousing, data lake silos they've had in the past. Get their unstructured and structured data onto one data platform, an open data platform, that is no longer adherent to any proprietary formats and standards and something they can, very much, very easily, integrate into the rest of their data environment. Apply one common data governance layer on top of that. So that from the time they ingest that data, to the time they use that data, to the time they share that data, inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform, with that common governance solution, they'd being able to bring all of those use cases together. Across their real time streaming, their data engineering, their BI, their AI. All of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges they just couldn't solve before. A good example of this, you know, one of the world's now largest data streaming platforms runs on Databricks with AWS. And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses. That they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data, from what the customers are doing with their platform and the recommendations they want to push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex. But by building it on Databricks, they were able to release it in record time and have grown at a record pace to now be the number one platform. >> And this product, it's impacting product development. >> Absolutely. >> I mean, this is like the difference between lagging months of product development, to like days. >> Yes. >> Pretty much what you're getting at. >> Yes. >> So total agility. >> Mm-hmm. >> I got that. Okay, now, I'm a customer I want to buy in the marketplace, but you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from AWS's leadership, Chris, was up there speaking, and Mona was, "Hey, he's a CRO conference chief revenue officer" conversation. Which means someone's getting compensated. So, if I'm the sales rep at Databricks, what's my motion to the customer? Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Or, how do you handle it? >> Well, I'd add what Joel just talked about with, you know, with the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, it's the entire Data Bricks offering. And- >> The flagship, all the, the top stuff. >> Everything, the flagship, the complete offering. So it's not segmented. It's not a sub segment. >> Okay. >> It's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we view this two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend Databricks for the right situation. Same thing with Databricks, our sales force wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get Databricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars. You have $5 million of spend. You put that spend through the flywheel with AWS marketplace, and then you can use that in your negotiations with AWS to get better pricing overall. So that's how we view it. >> So customers are driving. This sounds like. >> Correct. For sure. >> So they're looking at this as saying, Hey, I'm going to just get purchasing power with all my relationships. Because it's a solution architectural market, right? >> Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider. If they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing power. >> Okay, Joel, we're going to date ourselves. At least I will. So back in the old days, (group laughter) It used to be, do a Barney deal with someone, Hey, let's go to market together. You got to get paper, you do a biz dev deal. And then you got to say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for Databricks, or any company is, to go find those partners and do deals, versus now Amazon is the center point for the customer. So you can still do those joint deals, but this seems to be flipping the script a little bit. >> Well, it is, but we still have vars and consulting partners that are doing implementation work. Very valuable work, advisory work, that can actually work with marketplace through the CPPO offering. So the marketplace allows multiple ways to procure your solution. >> So it doesn't change your business structure. It just makes it more efficient. >> That's correct. >> That's a great way to say it. >> Yeah, that's great. >> Okay. So, that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >> Yes. >> Absolutely. >> Economically. >> Economically, it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon. Especially when it comes back to co-selling, right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution. And our teams are working backwards from those use cases, you know, to collaborate and land them. >> Yeah. I want to get that out there. Go ahead, Joel. >> So one of the other things I might add to that too, you know, and why this is advantageous for companies like Databricks to work through the marketplace. Is it makes it so much easier for customers to deploy a solution. It's very, literally, one click through the marketplace to get Databricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. >> You know, it's interesting. I want to bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself, EDI back in the old days, you know, all that craziness. Now this is all the internet, basically through the console. I get the infrastructure side, you know, spin up and provision some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage. A little nuanced. Most enterprises aren't yet there of integrating tech, on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrators dilemma, not an innovator's dilemma. So like, I want to integrate. So now I have integration points with Databricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you got to build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or am I off because, no one's going to be buying software like they used to. They buy software to integrate it. >> Yeah, no- >> Because everything's integrated. >> I think AWS has done a great job at creating a partner ecosystem, right? To give customers the right tools for the right jobs. And those might be with third parties. Databricks is doing the same thing with our partner connect program, right? We've got customer partners like Five Tran and DBT that, you know, augment and enhance our platform. And so you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >> Yeah. It's almost like, you know, bundling and un bundling. I was talking about this with, with Dave Alante about Supercloud. Which is why wouldn't a customer want the best solution in their architecture? Period. In its class. If someone's got API security or an API gateway. Well, you know, I don't want to be forced to buy something because it's part of a suite. And that's where you see things get sub optimized. Where someone dominates a category and they have, oh, you got to buy my version of this. >> Joel and I were talking, we were actually saying, what's really important about Databricks, is that customers control the data, right? You want to comment on that? >> Yeah. I was going to say, you know, what you're pushing on there, we think is extraordinarily, you know, the way the market is going to go. Is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically, I think, really strong places, Databricks and AWS have lined up, is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the Lakehouse, one thing we've always been extremely committed to, as a company, is building the data platform on an open foundation. And we do that primarily through Delta Lake and making sure that, to Jack's point, with Databricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed Databricks to have the breadth of integrations that it has with all the other data tools out there. Because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >> When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what am I foreclosing if I go with something else that's not as open? What's the customer's downside as you think about what's around the corner in the industry? Because if you believe it's going to be open, open source, which I think open source software is the software industry, and integration is a big deal. Because software's going to be plentiful. >> Sure. >> Let's face it. It's a good time to be in software business. But Cloud's booming. So what's the downside, from your Databricks perspective? You see a buyer clicking on Databricks versus that alternative. What's potentially should they be a nervous about, down the road, if they go with a more proprietary or locked in approach? >> Yeah. >> Well, I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also, then, beholden to the pace at which that provider is able to innovate. >> Mm-hmm. >> And I think we've seen lots of times over history where, you know, a proprietary format may run ahead, for a while, on a lot of innovation. But as that market control begins to solidify, that desire to innovate begins to degrade. Whereas in the open formats- >> So extract rents versus innovation. (John laughs) >> Exactly. Yeah, exactly. >> I'll say it. >> But in the open world, you know, you have to continue to innovate. >> Yeah. >> And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you are always going to be at the forefront of what is the latest. >> You know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked with proprietary. >> Yeah. >> You know, SNA and IBM, deck net was digital. You know the rest. And then TCPIP was part of the open systems interconnect. >> Mm-hmm. >> Revolutionary (indistinct) a big part of that, as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. >> Yeah. >> But that helped inter operate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid-game, then you get the end game. You're not there at the end game yet at Cloud. But Cloud- >> There's, always some form of lock in, right? Andy Jazzy will address it, you know, when making a decision. But if you're going to make a decision you want to reduce- You don't want to be limited, right? So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now, is an AI driven business, right? And so it has to do with, can you get that data out of silos? Can you organize it and secure it? And then can you work with data scientists to feed those models? >> Yeah. >> In a very consistent manner. And so the tools of tomorrow will, to Joel's point, will be open and we want interoperability with those tools. >> And choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds, is that they have to compete directly too. Redshift competes directly with a lot of other stuff. But they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're going to be, they're onto it. This is the- >> To Amazon's credit by having these solutions that may compete with native services in marketplace, they are providing customers with choice, low price- >> And access to the core value. Which is the hardware- >> Exactly. >> Which is their platform. Okay. So I want to get you guys thought on something else I see emerging. This is, again, kind of Cube rumination moment. So on stage, Chris unpacked a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing, compensation, workflows, services behind the curtain. And one of those things he mentioned was, they talk about resellers or channel partners, depending upon what you talk about. We believe, Dave and I believe on the Cube, that the entire indirect sales channel of the industry is going to be disrupted radically. Because those players were selling hardware in the old days and software. That game is going to change. You mentioned you guys have a program, let me get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in. Which means that the old reseller channels are going to be rewritten. They're going to be refactored with this new kinds of access. Because you've got scale, you've got money and you've got product. And you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, a value added reseller or VAB or business. >> You've got to evolve. >> You got to, you got to be here. >> Yes. >> Yeah. >> How are you guys working with those partners? Because you say you have a product in your marketplace there. How do I make money if I'm a reseller with Databricks, with Amazon? Take me through that use case. >> Well I'll let Joel comment, but I think it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations. They need expertise from consulting and SI partners. If those consulting and SI partners happen to resell the solution as well. Well, that's another aspect of their business. But I really think it is the expertise that the partners bring to help customers get outcomes. >> Joel, channel big opportunity for Amazon to reimagine this. >> For sure. Yeah. And I think, you know, to your comment about how do resellers take advantage of that, I think what Jack was pushing on is spot on. Which is, it's becoming more and more about the expertise you bring to the table. And not just transacting the software. But now actually helping customers make the right choices. And we're seeing, you know, both SIs begin to be able to resell solutions and finding a lot of opportunity in that. >> Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's going to be the evolution that this goes. >> At the end of the day, it's about services, right? >> For sure. Yeah. >> I mean... >> You've got a great service. You're going to have high gross profits. >> Yeah >> Managed service provider business is alive and well, right? Because there are a number of customers that want that type of a service. >> I think that's going to be a really hot, hot button for you guys. I think being the way you guys are open, this channel, partner services model coming in, to the fold, really kind of makes for kind of that Supercloud like experience, where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on, within Databricks. >> For sure. >> On top of this ecosystem. How does that work? This is kind of like, hasn't been written up in business school and case studies yet. This is new. What is this? >> I think, you know, what it comes down to is, you're seeing ecosystems begin to evolve around the data platforms. And that's going to be one of the big, kind of, new horizons for us as we think about what drives ecosystems. It's going to be around, well, what's the data platform that I'm using? And then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around Databricks in its Lakehouse platform as well. As customers are looking at well, if I'm standing these Lakehouses up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >> I mean you think about ecosystem theory, we're living a whole nother dream. And I'm not kidding. It hasn't yet been written up and for business school case studies is that, we're now in a whole nother connective tissue, ecology thing happening. Where you have dependencies and value proposition. Economics, connectedness. So you have relationships in these ecosystems. >> And I think one of the great things about the relationships with these ecosystems, is that there's a high degree of overlap. >> Yeah. >> So you're seeing that, you know, the way that the cloud business is evolving, the ecosystem partners of Databricks, are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for you. >> Joel, Jack, I love it because you know what it means? The best ecosystem will win, if you keep it open. >> Sure, sure. >> You can see everything. If you're going to do it in the dark, you know, you don't know the outcome. I mean, this is really kind of what we're talking about. >> And John, can I just add that when I was at Amazon, we had a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? >> Yeah. >> And so there's a platform decision being made and that ecosystem is going to evolve around the platform. >> Yeah, and I totally agree. And the word innovation gets kicked around. That's why, you know, when we had our Supercloud panel, it was called the innovators dilemma, with a slash through it, called the integrater's dilemma. Innovation is the digital transformation. So- >> Absolutely. >> Like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating? If APIs are connective tissue, what's automation, what's the service messages look like? I mean, a whole nother set of, kind of thinking, goes on in these new ecosystems and these new products. >> And that thinking is, has been born in Delta Sharing, right? So the idea that you can have a multi-cloud implementation of Databricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud solution. >> Well, Databricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great growing ecosystem. And again, I think a shining example of what every enterprise is going to do. Build on top of something, operating model, get that operating model, driving revenue. >> Mm-hmm. >> Yeah. >> Whether, you're Goldman Sachs or capital one or XYZ corporation. >> S and P global, NASDAQ. >> Yeah. >> We've got, you know, the biggest verticals in the world are solving tough problems with Databricks. I think we'd be remiss because if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions. Whether it's the relationship we have with our engineering and service teams. Our marketing teams, you know, product development. And we're going to be at Reinvent. A big presence at Reinvent. We're looking forward to seeing you there, again. >> Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening. This NextGen Cloud is here. We're seeing this evolve, kind of new economics, new value propositions kind of scaling up. Producing more. So you guys are doing a great job. Thanks for coming on the Cube and taking the time. Joel, great to see you at the check. >> Thanks for having us, John. >> Okay. Cube coverage here. The world's changing as APN comes together with the marketplace for a new partner organization at Amazon web services. The Cube's got it covered. This should be a very big, growing ecosystem as this continues. Billions of being sold through the marketplace. And of course the buyers are happy as well. So we've got it all covered. I'm John Furry. your host of the cube. Thanks for watching. (upbeat music)

>>Welcome back everyone to the cubes coverage here in Seattle, Washington, AWS's marketplace seller conference. It's the big news within the Amazon partner network, combining with marketplaces, forming the Amazon partner organization, part of a big reorg as they grow the next level NextGen cloud mid-game on the chessboard. Cube's got cover. I'm John fur, host of Cub, a great guests here from data bricks, both cube alumnis, Jack Anderson, GM of the and VP of the data bricks partnership team. For ADOS, you handle that relationship and Joel Minick vice president of product and partner marketing. You guys are the, have the keys to the kingdom with data, bricks, and AWS. Thanks for joining. Thanks for good to see you again. Thanks for >>Having us back. Yeah, John, great to be here. >>So I feel like we're at reinvent 2013 small event, no stage, but there's a real shift happening with procurement. Obviously it makes it's a no brainer on the micro, you know, people should be buying online self-service cloud scale, but Amazon's got billions being sold to their marketplace. They've reorganized their partner network. You can see kind of what's going on. They've kind of figured it out. Like let's put everything together and simplify and make it less of a website marketplace merge our partner to have more synergy and friction, less experiences so everyone can make more money and customer's gonna be happier. >>Yeah, that's right. >>I mean, you're run relationship. You're in the middle of it. >>Well, Amazon's mental model here is that they want the world's best ISVs to operate on AWS so that we can collaborate and co architect on behalf of customers. And that's exactly what the APO and marketplace allow us to do is to work with Amazon on these really, you know, unique use cases. >>You know, I interviewed Ali many times over the years. I remember many years ago, I think six, maybe six, seven years ago, we were talking. He's like, we're all in ons. Obviously. Now the success of data bricks, you've got multiple clouds. See that customers have choice, but I remember the strategy early on. It was like, we're gonna be deep. So this is speaks volumes to the, the relationship you have years. Jack take us through the relationship that data bricks has with AWS from a, from a partner perspective, Joel, and from a product perspective, because it's not like you got to Johnny come lately new to the new, to the scene, right? We've been there almost president creation of this wave. What's the relationship and has it relate to what's going on today? >>So, so most people may not know that data bricks was born on AWS. We actually did our first 100 million of revenue on Amazon. And today we're obviously available on multiple clouds, but we're very fond of our Amazon relationship. And when you look at what the APN allows us to do, you know, we're able to expand our reach and co-sell with Amazon and marketplace broadens our reach. And so we think of marketplace in three different aspects. We've got the marketplace, private offer business, which we've been doing for a number of years. Matter of fact, we we're driving well over a hundred percent year over year growth in private offers and we have a nine figure business. So it's a very significant business. And when a customer uses a private offer that private offer counts against their private pricing agreement with AWS. So they get pricing power against their, their private pricing. >>So it's really important. It goes on their Amazon bill in may. We launched our pay as you go on demand offering. And in five short months, we have well over a thousand subscribers. And what this does is it really reduces the barriers to entry it's low friction. So anybody in an enterprise or startup or public sector company can start to use data bricks on AWS and pay consumption based model and have it go against their monthly bill. And so we see customers, you know, doing rapid experimentation pilots, POCs, they're, they're really learning the value of that first use case. And then we see rapid use case expansion. And the third aspect is the consulting partner, private offers C P O super important in how we involve our partner ecosystem of our consulting partners and our resellers that are able to work with data bricks on behalf of customers. >>So you got the big contracts with the private offer. You got the product market fit, kind of people iterating with data coming in with, with the buyers you go. And obviously the integration piece all fitting in there. Exactly. Exactly. Okay. So that's that those are the offers that's current and what's in marketplace today. Is that the products, what are, what are people buying? I mean, I guess what's the Joel, what are, what are people buying in the marketplace and what does it mean for >>Them? So fundamentally what they're buying is the ability to take silos out of their organization. And that's, that is the problem that data bricks is out there to solve, which is when you look across your data landscape today, you've got unstructured data, you've got structured data, you've got real time streaming data, and your teams are trying to use all of this data to solve really complicated problems. And as data bricks as the lake house company, what we're helping customers do is how do they get into the new world? How do they move to a place where they can use all of that data across all of their teams? And so we allow them to begin to find through the marketplace, those rapid adoption use cases where they can get rid of these data, warehousing data lake silos they've had in the past, get their unstructured and structured data onto one data platform and open data platform that is no longer adherent to any proprietary formats and standards and something. >>They can very much, very easily integrate into the rest of their data environment, apply one common data governance layer on top of that. So that from the time they ingest that data to the time they use that data to the time they share that data inside and outside of their organization, they know exactly how it's flowing. They know where it came from. They know who's using it. They know who has access to it. They know how it's changing. And then with that common data platform with that common governance solution, they'd being able to bring all of those use cases together across their real time, streaming their data engineering, their BI, their AI, all of their teams working on one set of data. And that lets them move really, really fast. And it also lets them solve challenges. They just couldn't solve before a good example of this, you know, one of the world's now largest data streaming platforms runs on data bricks with AWS. >>And if you think about what does it take to set that up? Well, they've got all this customer data that was historically inside of data warehouses, that they have to understand who their customers are. They have all this unstructured data, they've built their data science model, so they can do the right kinds of recommendation engines and forecasting around. And then they've got all this streaming data going back and forth between click stream data from what the customers are doing with their platform and the recommendations they wanna push back out. And if those teams were all working in individual silos, building these kinds of platforms would be extraordinarily slow and complex, but by building it on data bricks, they were able to release it in record time and have grown at, at record pace >>To not be that's product platform that's impacting product development. Absolutely. I mean, this is like the difference between lagging months of product development to like days. Yes. Pretty much what you're getting at. Yeah. So total agility. I got that. Okay. Now I'm a customer I wanna buy in the marketplace, but I also, you got direct Salesforce up there. So how do you guys look at this? Is there channel conflict? Are there comp programs? Because one of the things I heard today in on the stage from a Davis's leadership, Chris was up there speaking and, and, and moment I was, Hey, he's a CRO conference, chief revenue officer conversation, which means someone's getting compensated. So if I'm the sales rep at data bricks, what's my motion to the customer. Do I get paid? Does Amazon sell it? Take us through that. Is there channel conflict? Is there or an audio lift? >>Well, I I'd add what Joel just talked about with, with, you know, what the solution, the value of the solution our entire offering is available on AWS marketplace. So it's not a subset, the entire data bricks offering and >>The flagship, all the, the top, >>Everything, the flagship, the complete offering. So it's not, it's not segmented. It's not a sub segment. It's it's, you know, you can use all of our different offerings. Now when it comes to seller compensation, we, we, we view this two, two different ways, right? One is that AWS is also incented, right? Versus selling a native service to recommend data bricks for the right situation. Same thing with data bricks. Our Salesforce wants to do the right thing for the customer. If the customer wants to use marketplace as their procurement vehicle. And that really helps customers because if you get data bricks and five other ISVs together, and let's say each ISV is spending, you're spending a million dollars, you have $5 million of spend, you put that spend through the flywheel with AWS marketplace. And then you can use that in your negotiations with AWS to get better pricing overall. So that's how we, >>We do it. So customers are driving. This sounds like, correct. For sure. So they're looking at this as saying, Hey, I'm gonna just get purchasing power with all my relationships because it's a solution architectural market, right? >>Yeah. It makes sense. Because if most customers will have a primary and secondary cloud provider, if they can consolidate, you know, multiple ISV spend through that same primary provider, you get pricing >>Power, okay, Jill, we're gonna date ourselves. At least I will. So back in the old days, it used to be, do a Barney deal with someone, Hey, let's go to market together. You gotta get paper, you do a biz dev deal. And then you gotta say, okay, now let's coordinate our sales teams, a lot of moving parts. So what you're getting at here is that the alternative for data bricks or any company is to go find those partners and do deals versus now Amazon is the center point for the customer so that you can still do those joint deals. But this seems to be flipping the script a little bit. >>Well, it is, but we still have VAs and consulting partners that are doing implementation work very valuable work advisory work that can actually work with marketplace through the C PPO offering. So the marketplace allows multiple ways to procure your >>Solution. So it doesn't change your business structure. It just makes it more efficient. That's >>Correct. >>That's a great way to say it. Yeah, >>That's great. So that's so that's it. So that's just makes it more efficient. So you guys are actually incented to point customers to the marketplace. >>Yes, >>Absolutely. Economically. Yeah. >>E economically it's the right thing to do for the customer. It's the right thing to do for our relationship with Amazon, especially when it comes back to co-selling right? Because Amazon now is leaning in with ISVs and making recommendations for, you know, an ISV solution and our teams are working backwards from those use cases, you know, to collaborate, land them. >>Yeah. I want, I wanna get that out there. Go ahead, Joel. >>So one of the other things I might add to that too, you know, and why this is advantageous for, for companies like data bricks to, to work through the marketplace, is it makes it so much easier for customers to deploy a solution. It's, it's very, literally one click through the marketplace to get data bricks stood up inside of your environment. And so if you're looking at how do I help customers most rapidly adopt these solutions in the AWS cloud, the marketplace is a fantastic accelerator to that. You >>Know, it's interesting. I wanna bring this up and get your reaction to it because to me, I think this is the future of procurement. So from a procurement standpoint, I mean, again, dating myself EDI back in the old days, you know, all that craziness. Now this is all the, all the internet, basically through the console, I get the infrastructure side, you know, spin up and provision. Some servers, all been good. You guys have played well there in the marketplace. But now as we get into more of what I call the business apps, and they brought this up on stage little nuance, most enterprises aren't yet there of integrating tech on the business apps, into the stack. This is where I think you guys are a use case of success where you guys have been successful with data integration. It's an integrator's dilemma, not an innovator's dilemma. So like, I want to integrate, so now I have integration points with data bricks, but I want to put an app in there. I want to provision an application, but it has to be built. It's not, you don't buy it. You build, you gotta build stuff. And this is the nuance. What's your reaction to that? Am I getting this right? Or, or am I off because no, one's gonna be buying software. Like they used to, they buy software to integrate it. >>Yeah, >>No, I, cause everything's integrated. >>I think AWS has done a great job at creating a partner ecosystem, right. To give customers the right tools for the right jobs. And those might be with third parties, data bricks is doing the same thing with our partner connect program. Right. We've got customer, customer partners like five tra and D V T that, you know, augment and enhance our platform. And so you, you're looking at multi ISV architectures and all of that can be procured through the AWS marketplace. >>Yeah. It's almost like, you know, bundling and unbundling. I was talking about this with, with Dave ante about Supercloud, which is why wouldn't a customer want the best solution in their architecture period. And it's class. If someone's got API security or an API gateway. Well, you know, I don't wanna be forced to buy something because it's part of a suite and that's where you see things get suboptimized where someone dominates a category and they have, oh, you gotta buy my version of this. Yeah. >>Joel, Joel. And that's Joel and I were talking, we're actually saying what what's really important about Databricks is that customers control the data. Right? You wanna comment on that? >>Yeah. I was say the, you know what you're pushing on there we think is extraordinarily, you know, the way the market is gonna go is that customers want a lot of control over how they build their data stack. And everyone's unique in what tools are the right ones for them. And so one of the, you know, philosophically I think really strong places, data, bricks, and AWS have lined up is we both take an approach that you should be able to have maximum flexibility on the platform. And as we think about the lake house, one thing we've always been extremely committed to as a company is building the data platform on an open foundation. And we do that primarily through Delta lake and making sure that to Jack's point with data bricks, the data is always in your control. And then it's always stored in a completely open format. And that is one of the things that's allowed data bricks to have the breadth of integrations that it has with all the other data tools out there, because you're not tied into any proprietary format, but instead are able to take advantage of all the innovation that's happening out there in the open source ecosystem. >>When you see other solutions out there that aren't as open as you guys, you guys are very open by the way, we love that too. We think that's a great strategy, but what's the, what am I foreclosing? If I go with something else that's not as open what what's the customer's downside as you think about what's around the corner in the industry. Cuz if you believe it's gonna be open, open source, which I think opens our software is the software industry and integration is a big deal, cuz software's gonna be plentiful. Let's face it. It's a good time to be in software business, but cloud's booming. So what's the downside from your data bricks perspective, you see a buyer clicking on data bricks versus that alternative what's potentially is should they be a nervous about down the road if they go with a more proprietary or locked in approach? Well, >>I think the challenge with proprietary ecosystems is you become beholden to the ability of that provider to both build relationships and convince other vendors that they should invest in that format. But you're also then beholden to the pace at which that provider is able to innovate. And I think we've seen lots of times over history where, you know, a proprietary format may run ahead for a while on a lot of innovation. But as that market control begins to solidify that desire to innovate begins to, to degrade, whereas in the open format. So >>Extract rents versus innovation. Exactly. >>Yeah, exactly. >>But >>I'll say it in the open world, you know, you have to continue to innovate. Yeah. And the open source world is always innovating. If you look at the last 10 to 15 years, I challenge you to find, you know, an example where the innovation in the data and AI world is not coming from open source. And so by investing in open ecosystems, that means you were always going to be at the forefront of what is the >>Latest, you know, again, not to date myself again, but you look back at the eighties and nineties, the protocol stacked for proprietary. Yeah. You know, SNA at IBM deck net was digital, you know, the rest is, and then TCP, I P was part of the open systems, interconnect, revolutionary Oly, a big part of that as well as my school did. And so like, you know, that was, but it didn't standardize the whole stack. It stopped at IP and TCP. Yeah. But that helped interoperate, that created a nice defacto. So this is a big part of this mid game. I call it the chessboard, you know, you got opening game and mid game. Then you got the end game and we're not there. The end game yet cloud the cloud. >>There's, there's always some form of lock in, right. Andy jazzy will, will address it, you know, when making a decision. But if you're gonna make a decision you want to reduce as you don't wanna be limited. Right. So I would advise a customer that there could be limitations with a proprietary architecture. And if you look at what every customer's trying to become right now is an AI driven business. Right? And so it has to do with, can you get that data outta silos? Can you, can you organize it and secure it? And then can you work with data scientists to feed those models? Yeah. In a, in a very consistent manner. And so the tools of tomorrow will to Joel's point will be open and we want interoperability with those >>Tools and, and choice is a matter too. And I would say that, you know, the argument for why I think Amazon is not as locked in as maybe some other clouds is that they have to compete directly too. Redshift competes directly with a lot of other stuff, but they can't play the bundling game because the customers are getting savvy to the fact that if you try to bundle an inferior product with something else, it may not work great at all. And they're gonna be they're onto it. This is >>The Amazon's credit by having these, these solutions that may compete with native services in marketplace, they are providing customers with choice, low >>Price and access to the S and access to the core value. Exactly. Which the >>Hardware, which is their platform. Okay. So I wanna get you guys thought on something else. I, I see emerging, this is again kind of cube rumination moment. So on stage Chris unpacked, a lot of stuff. I mean this marketplace, they're touching a lot of hot buttons here, you know, pricing compensation, workflows services behind the curtain. And one of the things he mentioned was they talk about resellers or channel partners, depending upon what you talk about. We believe Dave and I believe on the cube that the entire indirect sales channel of the industry is gonna be disrupted radically because those players were selling hardware in the old days and software, that game is gonna change. You know, you mentioned you guys have a program, want to get your thoughts on this. We believe that once this gets set up, they can play in this game and bring their services in which means that the old reseller channels are gonna be rewritten. They're gonna be refactored with this new kinds of access. Cuz you've got scale, you've got money and you've got product and you got customers coming into the marketplace. So if you're like a reseller that sold computers to data centers or software, you know, value added reseller or V or business, >>You've gotta evolve. >>You gotta, you gotta be here. Yes. How are you guys working with those partners? Cuz you say you have a part in your marketplace there. How do I make money? If I'm a reseller with data bricks with eight Amazon, take me through that use case. >>Well I'll let Joel comment, but I think it's, it's, it's pretty straightforward, right? Customers need expertise. They need knowhow. When we're seeing customers do mass migrations to the cloud or Hadoop specific migrations or data transformation implementations, they need expertise from consulting and SI partners. If those consulting SI partners happen to resell the solution as well. Well, that's another aspect of their business, but I really think it is the expertise that the partners bring to help customers get outcomes. >>Joel, channel big opportunity for re re Amazon to reimagine this. >>For sure. Yeah. And I think, you know, to your comment about how to resellers take advantage of that, I think what Jack was pushing on is spot on, which is it's becoming more about more and more about the expertise you bring to the table and not just transacting the software, but now actually helping customers make the right choices. And we're seeing, you know, both SI begin to be able to resell solutions and finding a lot of opportunity in that. Yeah. And I think we're seeing traditional resellers begin to move into that SI model as well. And that's gonna be the evolution that >>This gets at the end of the day. It's about services for sure, for sure. You've got a great service. You're gonna have high gross profits. And >>I think that the managed service provider business is alive and well, right? Because there are a number of customers that want that, that type of a service. >>I think that's gonna be a really hot, hot button for you guys. I think being the way you guys are open this channel partner services model coming in to the fold really kind of makes for kind of that super cloudlike experience where you guys now have an ecosystem. And that's my next question. You guys have an ecosystem going on within data bricks for sure. On top of this ecosystem, how does that work? This is kinda like hasn't been written up in business school and case studies yet this is new. What is this? >>I think, you know, what it comes down to is you're seeing ecosystems begin to evolve around the data platforms and that's gonna be one of the big kind of new horizons for us as we think about what drives ecosystems it's going to be around. Well, what is the, what's the data platform that I'm using and then all the tools that have to encircle that to get my business done. And so I think there's, you know, absolutely ecosystems inside of the AWS business on all of AWS's services, across data analytics and AI. And then to your point, you are seeing ecosystems now arise around data bricks in its Lakehouse platform, as well as customers are looking at well, if I'm standing these Lakehouse up and I'm beginning to invest in this, then I need a whole set of tools that help me get that done as well. >>I mean you think about ecosystem theory, we're living a whole nother dream and I'm, and I'm not kidding. It hasn't yet been written up and for business school case studies is that we're now in a whole nother connective tissue ecology thing happening where you have dependencies and value proposition economics connectedness. So you have relationships in these ecosystems. >>And I think one of the great things about relationships with these ecosystems is that there's a high degree of overlap. Yeah. So you're seeing that, you know, the way that the cloud business is evolving, the, the ecosystem partners of data bricks are the same ecosystem partners of AWS. And so as you build these platforms out into the cloud, you're able to really take advantage of best of breed, the broadest set of solutions out there for >>You. Joel, Jack, I love it because you know what it means the best ecosystem will win. If you keep it open. Sure. You can see everything. If you're gonna do it in the dark, you know, you don't know the outcome. I mean, this is really kind we're talking about. >>And John, can I just add that when I was in Amazon, we had a, a theory that there's buyers and builders, right? There's very innovative companies that want to build things themselves. We're seeing now that that builders want to buy a platform. Right? Yeah. And so there's a platform decision being made and that ecosystem gonna evolve around the >>Platform. Yeah. And I totally agree. And, and, and the word innovation get kicks around. That's why, you know, when we had our super cloud panel was called the innovators dilemma with a slash through it called the integrated dilemma, innovation is the digital transformation. So absolutely like that becomes cliche in a way, but it really becomes more of a, are you open? Are you integrating if APIs are the connective tissue, what's automation, what's the service message look like. I mean, a whole nother set of kind of thinking goes on and these new ecosystems and these new products >>And that, and that thinking is, has been born in Delta sharing. Right? So the idea that you can have a multi-cloud implementation of data bricks, and actually share data between those two different clouds, that is the next layer on top of the native cloud >>Solution. Well, data bricks has done a good job of building on top of the goodness of, and the CapEx gift from AWS. But you guys have done a great job taking that building differentiation into the product. You guys have great customer base, great grow ecosystem. And again, I think in a shining example of what every enterprise is going to do, build on top of something operating model, get that operating model, driving revenue. >>Yeah. >>Well we, whether whether you're Goldman Sachs or capital one or XYZ corporation >>S and P global NASDAQ, right. We've got, you know, these, the biggest verticals in the world are solving tough problems with data breaks. I think we'd be remiss cuz if Ali was here, he would really want to thank Amazon for all of the investments across all of the different functions, whether it's the relationship we have with our engineering and service teams. Yeah. Our marketing teams, you know, product development and we're gonna be at reinvent the big presence of reinvent. We're looking forward to seeing you there again. >>Yeah. We'll see you guys there. Yeah. Again, good ecosystem. I love the ecosystem evolutions happening this next gen cloud is here. We're seeing this evolve kind of new economics, new value propositions kind of scaling up, producing more so you guys are doing a great job. Thanks for coming on the Cuban, taking time. Chill. Great to see you at the check. Thanks for having us. Thanks. Going. Okay. Cube coverage here. The world's changing as APN comes to give the marketplace for a new partner organization at Amazon web services, the Cube's got a covered. This should be a very big growing ecosystem as this continues, billions of being sold through the marketplace. Of course the buyers are happy as well. So we've got it all covered. I'm John furry, your host of the cube. Thanks for watching.

(upbeat music) >> Welcome back to Las Vegas. theCUBE is here, live at AWS re:Invent 2021. Lisa Martin with Dave Nicholson. theCUBE has two sets today, two, not one, two, two live sets, two remote sets, over 100 guests on the program at this event, it's a lot, talking about the next generation of cloud innovation with AWS and its massive ecosystem of partners and we are pleased to welcome Walton Smith to the program, the public sector, director of strategic partnerships for Worldwide Technology, Walton welcome to the program. >> Thank you so much for having me, it's really amazing to be here and look forward to a great conversation. Isn't it great to be in person again? >> It's so nice to be in person, I mean I'm glad everybody's being safe and, and checking vaccine status and whatnot, but it's good to get back and, and, and work with people cause we can really drive innovation when, when we get together. >> Those hallway conversations or those conversations here at events that you just can't replicate by video conferencing, right? Not replicate that, you getting grabbed in the hall and say, hey, have you thought about leveraging XYZ to do something? To me that's what makes this conference great. >> Talk to me about what's going on at WWT. What are some of the, the things that you guys have been working on? >> It's a really exciting time at Worldwide, we're really working closely with AWS to drive innovation to the edge. We're excited about their outpost offering, we actually have one in our data center, Sandy announced it today in a partnership with Intel to, to allow our customers to try to work out use cases, to, to kick the tires, so to speak, to see how it works as well as our partners to get their ISV products certified on the outpost platform. >> So I'm familiar with your ATC in St. Louis, is that what you're referring to? >> That's correct. >> Give us a little, give us a little insight into what goes on there, I know it's pretty amazing from a customer perspective because you are agnostic. because you are agnostic. >> Walton: Correct. >> You're there to serve the customer, but tell me, tell me what happens in the ATC. >> We say we're agnostic, but we have our, our, our preferences because we know- >> sure, sure, okay. what actually works. But our ATC is our crown jewel, it's about a $600 million data center that we built solely for proof of concepts for our customers. So our, our top customers come in and say, I have this problem, how can I solve it? And so with us being the single biggest reseller of just about every ISV is out there, I can stand up a, a, a Dell, I can stand up a, a, a Dell, Dell compute next to NetApp storage with Cisco router on top of it to replicate what my customer has at the VA, for example, and then to be able to plug in an outpost to show how leveraging the outpost can give them a single pane of glass to be able to work on their workload, so the training that our FSI, Federal System Integrators have put into their staff or our government customers on the Amazon platform can now be driven into their data center, so it's really taking the cloud down to where the data is. >> In terms of public sector, what are some of the prominent use cases that you guys are helping customers to solve, especially given the tumultuous times that we're still living in? Sure, so what we saw during COVID especially was how most of the government agencies had the capability to allow say 5% to 10% of their workforce to work remotely. And then with COVID, they went to 95% to a 100% workforce. So, a lot of the time we've spent over the last year is how do we securely allow our government employees to get access to the information, because as we know, the government was more valuable than ever to get us through this pandemic, we had to give them the tools that they needed to be able to make the decisions to, to move the country forward. >> Talk about security if you will for a second, we have seen such a dramatic change in the security landscape, the threat landscape, ransomware as a service, it's, you know, the cyber criminals, lot of money in it, they're becoming far more brazen. What are some of the things that you're seeing specifically with respect to security use cases? >> It's, it's gone from, let me just buy everything that's out there and that'll give me security to, I need to have visibility into my environment, because if, if you look at target, it's a great case studies around that, they had all the tools, they just didn't tie it all together. And so as more and more nation state actors And so as more and more nation state actors try to attack our government, or it's a great way to make money, I mean, in, in this, in the presentation, Sandy's today, they talked about, if you looked at the GDP of what's been taken in ransomware, it's like the 10th biggest country in the world, I mean, it's scary and staggering how much money is lost. So what we think, going back to our ATC, we can stand up their environment, we can work with the top security providers in the world to show those customers how we can give them that visibility, the, the, the protection and the ability to get back up, because there's really only two types of organizations, those who've been hacked and those who don't know they've been hacked, they're going to get in, it's how do we mitigate the damage, how do we get them back up and running and how we protect my customers or have some of the most sensitive data in the world, how do we protect that so our government can keep us safe and keep us moving forward. >> Yeah, cause these days it's a matter of when we get hacked, not if. And of course we are only hearing about the large attacks. >> Walton: Correct. We don't hear about- all of the ones that go on day in and day out, I think, I think I saw a stat recently that a ransomware attack happens like once every 11 seconds. >> Correct, I mean, just walking through here, how many text messages you've gotten? You want a free iPad click here, I mean, they're, they're down to the individual level. It's a whole lot cheaper to give a couple people, really powerful laptops, pizza and beer, and have them go attack, than it is to, to set up a real business and so, unfortunately, as long as there's money in it, there's going to be bad actors out there. We think partnering with AWS and other partners can help build solutions. >> You know, WWT has had an interesting history because you didn't start with the dawn of cloud. >> Walton: Right. So you've been in the business of AT for a long time So you've been in the business of AT for a long time and logistics out of St. Louis in a lot of ways. What does that look like in terms of navigating that divide? You know, there's a, there's a whole storied history of companies that were not able to cross the divide from the mainframe era to the client server era, let alone to cloud. You seem to have, you seem to be doing that pretty well. >> I, I appreciate that, I mean, we're the biggest company no one's ever heard of. We're 14, $15 billion privately held firm, the same two guys that founded it, still run it today and all they want to do is do cool things, they want it to be truly the best place to work. So from day one, they've invested in training our staff, building the ATC to give us the tools we need to be successful and then because we're a trusted partner with Amazon Intel and our other partners out there, they're investing in us to help build solutions, so we have over 6,000 engineers, they get up every day, how do I build something that can help our customers really drive change and innovation? So it's been a really fun ride and the, the best is yet to come. >> Talk to me about your customer focus, you know, when we talk, here we are at reinvent, we always talk with AWS about their, you know, Dave, we talked about this customer obsession, the fact that they're working backwards from the customer, do you share that sort of philosophy? Does WWT share that philosophy with AWS? >> 100%?, if you go to WWT.com we've published everything that we have so you can get full access to our lab to learn about x ISV and go deep to learn about x ISV and go deep and see the million and a half labs we've built around, say Red Hat and go and get access to it. So we think that if we educate our customers, there are going to be customers for life, and they're going to come to us with their biggest problems. And that what's, is what's exciting and what enables us to, to really continue to grow. >> And how did the customers help you innovate? And that's one of the things we, I was thinking yesterday with, with this AWS flywheel of when Adam was introducing, and now we have a, now we have, and it was because he would say, we did this, but you needed more, but you being the customer needed more. >> 100%, it, it's we want our customers to come to us with their biggest problems, because that's when we, the exciting innovation works. And so the ability to sit down with the foremost expert in, in virus control and be able to, in, in virus control and be able to, what are the tools that she need to be able to get ahead of the next change to COVID? How can we give them the tools to do that? That's what we want to do, the scalability, the ability to reach out to others is what Amazon brings. So we can bring the data science, we can bring the understanding of the storage, the security, and the network and then AWS gives that limitless scalability to solve those problems and to bring in someone from Africa, to bring in someone from the European Union to, to work together to solve those problems, that's what's, what's exciting and then coming back to the outpost, to be able to put that in the data center, we know the data center is better than just about anybody out there, so it would be the ability to add innovation to them, to bring those part ISV partners together. It's really exciting that Intel is funding it because they know that if, if customers can see the art of the possible, they're going to push that innovation. >> One of the things we've also sort of thematically Dave and I with guests, and the other has been talking about this week is that every company has to be a data company, whether it's public sector, private sector, if you're not, or if you're not on your way, there's a competitor right here in the rear view mirror ready to take your place. How do you help public sector organizations really develop, embrace an execute a data full course strategy? >> So we have a cadre of over 125 data scientists that work every day to help organizations unlock their most valuable asset, that data, their people and be able to put the data in the right place at the right time and so by investing in those data scientists, investing in the networking folks to be able to look at the holistic picture is how we can bring those solutions to our customers, because the data is the new oil of, of the environment and sorry for my Southern twang on the oil, but it, but it truly is the most valuable asset they have and so, how do we unlock that? How do they pull that data together, secure it? Because now that you're aggregating all that data, you're making it a treasure trove for those bad actors that are out there, so you've got to secure it, but then to be able to learn and, and automate based on, on what you learned from that data. >> You know I, I think with hindsight, it's easy to, it's easy to say, well, of course WWT is where WWT is today. Five years ago, though, I think it would have been an honest question to ask, how are you going to survive in the world of cloud? And here we are, you've got outposts. >> Walton: Sure. >> And, and of course it makes sense because you're focused on customers, sounds like I'm doing a commercial for you, But I'm a fan- >> I'll gladly apreciate that- because I, I, I've worked with you guys in a variety of roles for a long time, seems like yesterday we were testing a bunch of different storage arrays of the ATC and now you've got outposts in cloud and you're integrating it together. It's really more of the same, I'm sure if we had your founders here, they'd tell you, Dave, it's all the same. >> Walton: Correct. It's all the same. >> It's AT, it's where, where's the compute, where's the storage, how do you get access to it and the cloud has given the ability to, to scale and do things you could never imagine. I think it's the reason we're here is because our leadership continues to invest and pushing that envelope to give people the freedom to go out with that crazy idea, what if we did this? And having the tools and the ability to do that is, is what, what drives our innovation and that's what we bring to our customers and our partners, that ability to innovate to, that ability to innovate to, to tackle that next problem. >> So what's the tip of the spear right now for you guys? What are you, what's, what's, what's kind of, what's next? What are you waiting to have delivered to the ATC to racket, stack and cable up? >> Lot's of stuff that I can't tell you about because there, there's things that Amazon is, is always working on that we work with before it, it's, it's made public, so there's a lot of really cool stuff in the pipeline, because the, as you think about moving to the data center, that's one thing, moving to truly to the edge, where you can help that war fighter, where you can help that mission, where you can do disaster recovery, leveraging the snowball family, the outpost family, and custom built tools that really allow for quick response and custom built tools that really allow for quick response to whatever that problem is, is that next front and that's where we've been for a long time, helping our, our war fighters and folks do what needs to be done. Outpost sees that you can leverage big AWS Outpost sees that you can leverage big AWS to build the models, push it down to the edge because you don't have time or the bandwidth to get it back into the big cloud, to be able to put that compute and storage and analytics on the edge to make real time decisions, is what we have to do to stay relevant and that's where the joint partnership is really exciting. >> It's what you have to do to stay relevant, it's also what your customers need, cause one of the things that we've learned in the pandemic is that real-time data and access to it is no longer, longer a nice to have, this is business critical for everything. >> Correct and even if you have a fat pipe to get it, you need to make real time decisions and if you're in a really sandy space, excuse me, making hard decisions, you've got to get the best information to that soldier when, when they need it to, to save our lives or to save the other people's lives so it's, it's, it's not just a nice to have, it's mission critical. >> It is mission critical, Walton, thank you so much, we're out of time, but thank you for joining Dave and me talking about- >> Really enjoyed it. all the stuff going on with, with worldwide, the partnership with AWS, how you're helping really transform the public sector, we appreciate your time and your insights. >> Thank you so much, have a great conference. >> Thanks, you too. >> Okay, thanks. >> All right, from my buddy, Dave Nicholson, I'm Lisa Martin, you're watching theCUBE, the global leader in live tech coverage. (upbeat music)

(bright upbeat music) >> Hello everyone. And we're back at AWS Re:Invent. You're watching theCUBE and we're here, day two. Actually we started Monday night and we got wall-to-wall coverage. We going all the way through Thursday, myself. I'm Dave Volante with the co-host, David Nicholson. Lisa Martin is also here. Of course, John Furrier. Partners, technologists, customers, the whole ecosystem. It's good to be back in the live event. Of course we have hybrid event as well a lot of people watching online. Anshu Sharma is here. He is the co-founder and CEO of Skyflow, new type of privacy company, really interested in this topic. Great to see you. Thanks for coming on. >> Thank you, thanks for bringing me here. >> It's timely, you know. Privacy, security, they're kind of two sides of the same coin. >> Yes. >> Why did you found Skyflow? >> Well, the idea for Skyflow really comes from my background in some ways. I spent my first nine years at Oracle, six years at Salesforce. And whether we were building databases or CRM products, customers would come to us and say, "Hey, you know, I have this very different type of data. It's things like social security numbers, frequent flyer card numbers, card numbers. You know, can you secure it better? Can you help me manage things like GDPR?" And to be honest, there was never a clear answer. There's a lot of technology solutions out there that do one thing at a time, you can walk around the booths here, there's like a hundred companies. And if you use all those hundred things correctly, maybe you could go tell your board that maybe a social security number is not going to be lost anymore. And I was like, "You know, we've simplified everything else. Why is it so hard to protect my social security number? It should be easy. It should be as easy as using Stripe or Twilio." And this idea just never went away and kept coming back till a few years ago, we learned about the Facebook privacy challenges, the Equifax challenges. And I was like, boy, it's the time. It's time to go do it now. >> You started the company in 2019. Right? >> Yes. >> I mean, your timing was pretty good, right? So what are the big sort of Uber trends that you're seeing? Obviously GDPR, the California Consumer Privacy Act. I heard this morning. Did you hear this? That like, if you post a picture on social media now without somebody's permission, you're now violating their privacy. It's like, you can see the smiles on Anshu's face. >> Its like every week, we're like every week, there's a new story that could be like, well, Skyflow. The new story is the question, the answer is Skyflow. But honestly I think what's happened is, the issue is put very simple. You know all we're trying to do is protect people's social security numbers, phone numbers, credit card numbers, things we hold dear. At the same time, it's complex. Like what does it mean to protect your social security number let's say? Does that mean I don't get to use it for filing your taxes? Well, I need your credit card number to process a payment. And we were like, this is just too complicated. Why, how do companies like Apple do it? How do companies like Netflix manage not have as many breaches as my hotel that barely has any data. And the answer is those companies actually have evolved to a completely different architecture, the zero trust data architecture. And that was our inspiration for starting this company. >> Yeah. I mean. How many times have you been asked to give your social security number? And you're like, why? why do you want it? What are you going to do with it? How do you protect it? And they go, "I don't know." >> You know, what's even, my favorite is like, you give your social security number to say TurboTax, how many days of the year do they need to use it? One. How many days of the year do they have it? And the thing is, it's a liability for those CTOs too. >> Yeah right. >> The CTO of Walgreens, the CTO of Intuit. They don't really want that social security number just so they can process your card once a year, or your social security number once a year. It's almost like we're forcing them to hold onto data. And then they have to bear the burden of having these stories. Like, you know, everybody wants to prevent a New York Times story that says, what Robin Hood had a breach, Twitter had a breach. >> So walk us through how Skyflow would address something like that. So take the, you know, take the make a generic version of TurboTax, social security members. There they are right now, they're sitting in a database somewhere. Hopefully there's some security wrapped around it in some way or another. What would you advise a customer like that to do? And what are you actually doing for them? >> So, look, it's very simple. You are not going to put your username passwords in a generic database. You're going to use something like OD Zero or Octa to do it. We're living in a world where we have polyglot data stores. Like there's a key value store. There's a time series database. There is a search database like Elastic. There's a log database like Splunk. But PII data, Somehow we think just fine. If it's in a hundred places and our answer is that we should do the same thing that companies like Apple, Netflix, Google, everybody, does. They take this data. They completely isolate it from the databases. And it gets stored in a custom data store in our case, that would be Skyflow. And essentially we'd give you encrypted tokens back and you can use these encrypted tokens that look like fake social security number. It's called a Format Preserving Encryption. So if you think about all the breakthroughs we've had in homomorphic encryption, on secure elements, like the way your phone works, the credit card number is stored in a secure element. So it's the same idea. There's a secure part of your data stack, which is Skyflow. That basically keeps the data always protected. And because we can compute and search on encrypted data, this is important, everybody can encrypt data at rest. Skyflow is the first company that's come out and said, "Look, you can keep your phone number and social security number, encrypted while I can run an aggregation query." So I can tell you what's the balance of your customer's account balance. And i can run that query without decrypting, a single row of data. The only other company I know that can do that internally is a certain Cupertino based company. >> So think about it. Anybody can walk something up to a certain degree, but allowing frictionless access at the same time. >> While it's encrypted. So how do you make that? Are you, is a strategy to make that a horizontal service? That I can put into my data protection service or my E-commerce service or whatever. >> It's a cloud-based service that runs on AWS and other clouds. We basically given instance just like, you'll get an instance of a post-grad store or you get an API handled to OD Zero. You basically instantiate Skyflow of what gets created. It can be in your AWS environment, dedicated VPC. So it's private to you and then you have a handle and then basically you just start using it. >> So how, how do you, what's the secret sauce? How do you do that? >> The secret source. Well, now that we filed the patents on it, I can reveal the secret sauce. So the holy grail of encryption right now, if you go talk to people at a leading company, is there's something called Fully Homomorphic Encryption. That's fundamentally the foundation on which things like Bitcoin are built actually. But the hard part about Fully Homomorphic Encryption is it works. You can actually do mathematical computations on it without decrypting the data, but it's about a million times slower. >> Yes slower, right. >> So nobody uses it. My insight was that we don't need to do multiplications and additions on phone numbers. You never take my phone number and divide by your social security number. (Dave laughing) These numbers are not numbers, they are data structures. So our insight was if you treat them as specialized data structures, we're all talking about basically about 80 different types of data across the globe. Every human being has an ID, date of birth, height, color of eyes. There's not that many fields. What we can do then is create specialized encryption schemes for each data type. We call this polymorphic data encryption. Poly means multiple. As a result of that, we can actually store the data encrypted and build indexes on it. Since we can index interpret data, it's kind of like, imagine you can run real-time queries on data that's encrypted. Every other data store, When you encrypt the data, it becomes invisible to database. And that's why we had to build this as a full stacked service. Just like the Snowflake guys had to start with the foundation of storage, rethink indexing, and build Snowflake. We did the same thing, except we built it for encrypted indexes Whereas they built it for encrypted, for regular data stores. >> So thinking, if you think about today's tech stack, it's evolving, right? The data protection and security are coming together. Where does this fit? Is it sort of now becoming a fundamental part of the-- >> We think every leading company, whether you're building a new brokerage application or you are the largest bank in the world, and we're talking to some of them right now. They're all going to have an internal service called a PII wall. This wall just like Apple and Google have their own internal walls. You're going to have a wall service in your service oriented architecture, essentially. And it's going to basically be the API. Every other application and database in your company is not going to store my social security number. The SSNs don't belong in 600 databases at a leading bank. They don't belong inside your customer support system. Think about what happened with Robinhood two weeks ago, right? Someone tricked one call center guy into giving the keys up, which is fine happens. But why did the call center guy have access to like a million email addresses? He's never used going to use that. So we think if you isolate the PII, every leading company is going to end up with a PII Wall, as part of their core architecture. Just like today, we have an Alt API, you have a Search API, you have a Logging API, you're going to have a PII API. And that's going to be part of your modern data stack. >> So okay. So this is definitely not a bolt on, right? It's going to be a fundamental company, just like security is, just like backup is. It's now, you got to have it. It's-- >> Yes. I mean, if you think about it, it just logically makes sense. Like you should be isolating this data. You don't keep your money and gold around at home. You put it either in a locker or a bank. I think the same applies for PII. We just haven't done it because companies would pay off a fine for $10,000 or a million dollars. And. >> Yeah. So you've recently raised $45 million to expand your efforts. Obviously that means that people are looking at this and saying there's opportunity, right? What does that look like when you think of growth, where during your go to market strategy at first you're convincing people that it's a good idea to do it. Do you think or hope for, hope one day that there's an inflection point where it's not that people are thinking, you know, let's do this because it's a good idea, but people are like, I have to do this because if I don't, it's irresponsible and I'm going to be penalized for not having it. It becomes something that isn't really a choice. It's something where you just do it. >> So, you know, when we were starting the company, we didn't even have a word to explain what we were trying to do. We would say things like what if there was a cloud service for XYZ. And, but over the last one year, I don't want to take credit for creating this market, but this market has been created in the last year and a half. And you know, we get tons of people, including some of the largest institutions emailing us, saying, "I'm looking to build a PII wall, API service inside my company. Can you tell me why your product meets that need?" And I thought that would take us three to five years to get there. And, you know, we've ended up creating a category, basically just like other companies have. And I think, you know, you don't get, I believe in market permission. You don't get to create a category. The market gives somebody the permission to create a category. Saying, "Look, this makes sense. Something like this should emerge." And if you're there at the right time, like you said. >> Yep. >> You get to take the opportunity. >> So where are you at as a company say for some, some capital is great. When do you scale? >> We're scaling now? So we just doubled our headcount in the last nine to 10 months. We're now 75 people. We think we'll be about 150 to 200 people in the next year. We are hiring across all regions. We just hired a head of Asia pack from segment.com. We just hired our first, you know, lead on international expansion. And in the US, we have an office in Palo Alto. We have an office in Bangalore. We just announced a data residency solution for Europe, data residency solution for India and emerging markets. Because data residency is another one of those things that's just emerging right now. And irrespective of whether you believe in security and privacy. Data residency is one of those things that you are mandated to implement. >> And where are you hiring? Is it combination to go to market? Tell me about your go to market. >> The go to market. We are direct sales organization, but we work with partners. So we haven't announced some of these partnerships, but you're working with some of the companies here who either are large database companies, large security companies. We think there is a win-win relationship between us and some of the partner. >> You're a partner model, partner channel model. >> So, direct sales but partner assisted. >> Yeah. Right. All right. We got to go. Hey, awesome story. Congratulations. Best of luck. >> Very interesting. >> Love to have you back and track the progress. >> Thank you, thank you so much. >> Okay. Thank you for watching theCUBE, the leader in and high-tech coverage. We're at Re-Invent 2021. Be right back (upbeat music)

>>Machine intelligence is everywhere. AI is being embedded into our everyday lives, through applications, process automation, social media, ad tech, and it's permeating virtually every industry and touching everyone. Now, a major issue with machine learning and deep learning is trust in the outcome. That is the black box problem. What is that? Well, the black box issue arises when we can see the input and the output of the data, but we don't know what happens in the middle. Take a simple example of a picture of a cat or a hotdog for you. Silicon valley fans, the machine analyzes the picture and determines it's a cat, but we really don't know exactly how the machine determined that. Why is it a problem? Well, if it's a cat on social media, maybe it isn't so onerous, but what if it's a medical diagnosis facilitated by a machine? And what if that diagnosis is wrong? >>Or what if the machine is using deep learning to qualify an individual for a home loan and that person applying for the loan gets rejected. Was that decision based on bias? If the technology to produce that result is opaque. Well, you get the point. There are serious implications of not understanding how decisions are made with AI. So we're going to dig into the issue and the topic of how to make AI explainable and operationalize AI. And with me are two guests today, Shea speaky, who's the co-founder and COO of cognitive scale and long time friend of the cube and newly minted CEO of cognitive scale. Bob pitchy, Yano, gents. Welcome to the cube, Bob. Good to see you again. Welcome back on. >>Thanks for having us >>Say, let me start with you. Why did you start the company? I think you started the company in 2013. Give us a little history and the why behind cognitive scale. >>Sure. David. So, um, look, I spent some time, um, you know, through multiple startups, but I ended up at IBM, which is where I met Bob. And one of the things that we did was the commercialization of IBM Watson initially. And that led to, uh, uh, thinking about how do you operationalize this because of the, a lot of people thinking about data science and machine learning in isolation, building models, you know, trying to come up with better ways to deliver some kind of a prediction, but if you truly want to operationalize it, you need to think about scale that enterprises need. So, you know, we were in the early days, enamored by ways, I'm still in landed by ways. The application that takes me from point a to point B and our view is look as you go from point a to point B, but if you happen to be, um, let's say a patient or a financial services customer, imagine if you could have a raise like application giving you all the insights that you needed telling you at the right moment, you know, what was needed, the right explanation so that it could guide you through the journey. >>So that was really the sort of the thesis behind cognitive scale is how do you apply AI, uh, to solve problems like that in regulated industries like health care management services, but do it in a way that it's done at scale where you can get, bring the output of the data scientists, application developers, and then those insights that can be powered into those end applications like CRM systems, mobile applications, web applications, applications that consumers like us, whether it be in a healthcare setting or a financial services setting can get the benefit of those insights, but have the appropriate sort of evidence and transparency behind it. So that was the, that was the thesis for. >>Got it. Thank you for that. Now, Bob, I got to ask you, I knew you couldn't stay in the sidelines, my friend. So, uh, so what was it that you saw in the marketplace that Lord you back in to, to take on the CEO role? >>Yeah, so David is an exciting space and, uh, you're right. I couldn't stay on the sideline stuff. So look, I always felt that, uh, enterprise AI had a promise to keep. Um, and I don't think that many enterprises would say, you know, with their experience that yeah, we're getting the value that we wanted out of it. We're getting the scale that we wanted out of it. Um, and we're really satisfied with what it's delivered to us so far. So I felt there was a gap in keeping that promise and I saw cognitive scale as an important company and being able to fill that gap. And the reason that that gap exists is that, you know, enterprise AI, unlike AI, that relates to one particular conversational service or one particular small narrow domain application is really a team sport. You know, it involves all sorts of roles, um, and all sorts of aspects of a working enterprise. >>That's already scaled with systems of engagement, um, and, and systems of record. And we show up in the, with the ability to actually help put all of that together. It's a brown field, so to speak, not a Greenfield, um, and where Shea and Matt and Minosh and the team really focused was on what are the important last mile problems, uh, that an enterprise needs to address that aren't necessarily addressed with any one tool that might serve some members of that team? Because there are a lot of great tools out there in the space of AI or machine learning or deep learning, but they don't necessarily help come together to, to deliver the outcomes that an enterprise wants. So what are those important aspects? And then also, where do we apply AI inside of our platform and our capabilities to kind of take that operationalization to the next level, uh, with, you know, very specific insights and to take that journey and make it highly personalized while also making it more transparent and explainable. >>So what's the ICP, the ideal customer profile, is it, is it highly regulated industries? Is it, is it developers? Uh, maybe you could parse that a little bit. >>Yeah. So we do focus in healthcare and in financial services. And part of the reason for that is the problem is very difficult for them. You know, you're, you're working in a space where, you know, you have rules and regulations about when and how you need to engage with that client. So the bar for trust is very, very high and everything that we do is around trusted AI, which means, you know, thinking about using the data platforms and the model platforms in a way to create marketplaces, where being able to utilize that data is something that's provisioned in permission before we go out and do that assembly so that the target customer really is somebody who's driving digital transformation in those regulated industries. It might be a chief digital officer. It might be a chief client officer, customer officer, somebody who's really trying to understand. I have a very fragmented view of my member or of my patient or my client. And I want to be able to utilize AI to help that client get better outcomes or to make sure that they're not lost in the system by understanding and more holistically understanding them in a more personalized way, but while always maintaining, you know, that that chain of trust >>Got it. So can we get into the product like a little bit more about what the product is and maybe share, you can give us a census to kind of where you started and the evolution of the portfolio >>Look where we started there is, um, the application of AI, right? So look, the product and the platform was all being developed, but our biggest sort of view from the start had been, how do you get into the trenches and apply this to solve problems? And as well, pointed out, one of the areas we picked was healthcare because it is a tough industry. There's a lot of data, but there's a lot of regulation. And it's truly where you need the notion of being able to explain your decision at a really granular level, because those decisions have some serious consequences. So, you know, he started building a platform out and, um, a core product is called cortex. It's the, it's a software platform on top of this. These applications are built, but to our engagements over the last six, seven years, working with customers in healthcare, in financial services, some of the largest banks, the largest healthcare organizations, we have developed a software product to essentially help you scale enterprise AI, but it starts with how do you build these systems? >>Building the systems requires us to provide tooling that can help developers take models, data that exists within the enterprise, bring it together, rapidly, assemble this, orchestrate these different components, stand up. These systems, deploy these systems again in a very complex environment that includes, you know, on-prem systems as well as on the cloud, and then be able to done on APIs that can plug into an application. So we had to essentially think of this entire problem end to end, and that's poor cortex does, but extremely important part of cortex that didn't start off. Initially. We certainly had all the, you know, the, the makings of a trusted AI would be founded the industry wasn't quite ready over time. We've developed capabilities around explainability being able to detect bias. So not only are you building these end to end systems, assembling them and deploying them, you have as a first-class citizen built into this product, the notion of being able to understand bias, being able to detect whether there's the appropriate level of explainability to make a decision and all of that's embedded within the cortex platform. So that's what the platform does. And it's now in its sixth generation as we >>Speak. Yeah. So Dave, if you think about the platform, it really has three primary components. One is this, uh, uh, application development or assembly platform that fits between existing AI tools and models and data and systems of engagement. And that allows for those AI developers to rapidly visualize and orchestrate those aspects. And in that regard were tremendous partners with people like IBM, Microsoft H2O people that provide aspects that are helping develop the data platform, the data fabric, things like the, uh, data science tools to be able to then feed this platform. And then on the front end, really helping transform those systems of engagement into things that are more personalized with better recommendations in a more targeted space with explainable decisions. So that's one element that's called cortex fabric. There's another component called cortex certify. And that capability is largely around the model intelligence model introspection. >>It works, uh, across things that are of cost model driven, but other things that are based on deterministic algorithms, as well as rule-based algorithms to provide that explainability of decisions that are made upstream before they get to the black box model, because organizations are discovering that many times the data has, you know, aspects of dimensions to it and, and, and biases to it before it gets to the model. So they want to understand that entire chain of, of, uh, of decisioning before it gets there. And then there's the notion of some pew, preacher rated applications and blueprints to rapidly deliver outcomes in some key repeating areas like customer experience or like lead generation. Um, those elements where almost every customer we engage with, who is thinking about digital transformation wants to start by providing better client experience. They want to reduce costs. They want to have operational savings while driving up things like NPS and improving the outcomes for the people they're serving. So we have those sets of applications that we built over time that imagine that being that first use application, that starter set, that also trains the customer on how to you utilize this operational platform. And then they're off to the races building out those next use cases. So what we see as one typical insertion place play that returns value, and then they're scaling rapidly. Now I want to cover some secret sauce inside of the platform. >>Yeah. So before you do, I think, I just want to clarify, so the cortex fabric, cause that's really where I wanted to go next, but the cortex fabric, it seems like that's the way in which you're helping people operationalize inject use familiar tooling. It sounds like, am I correct? That the cortex certify is where you're kind of peeling the onion of that complicated, whether it's deep learning or neural networks, which is that's where the black box exists. Maybe you could tell us, you know, is that where the secret sauce lives, if not, where is it? And if >>It actually is in all places right though. So there's some really important, uh, introductions of capabilities, because like I mentioned, many times these, uh, regulated industries have been developed and highly fragmented pillars. Just think about the insurance companies between property casualty and personal lines. Um, many times they have grown through acquisition. So they have these systems of record that are, that are really delivering the operational aspects of the company's products, but the customers are sometimes lost in the scenes. And so they've built master data management capabilities and data warehouse capabilities to try to serve that. But they find that when they then go to apply AI across some of those curated data environments, it's still not sufficient. So we developed an element of being able to rapidly assemble what we call a profile of one. It's a very, very intimate profile around declared data sources, uh, that relate to a key business entity. >>In most cases, it's a person, it's a member, it's a patient, it's a client, but it can be a product for some of our clients. It's real estate. Uh, it's a listing. Um, you know, it can be someone who's enjoying a theme park. It can be someone who's a shopper in a grocery store. Um, it can be a region. So it's any key business entity. And one of the places where we applied our AI knowledge is by being able to extract key information out of these declared systems and then start to make longitudinal observations about those systems and to learn about them. And then line those up with prediction engines that both we supply as well as third parties and the customers themselves supply them. So in this theme of operationalization, they're constantly coming up with new innovations or a new model that they might want to interject into that engagement application. Our platform with this profile of one allows them to align that model directly into that profile, get the benefits of what we've already done, but then also continue to enhance, differentiate and provide even greater, uh, greater value to that client. IBM is providing aspects of those models that we can plug in. And many of our clients are that's really >>Well. That's interesting. So that profile of one is kind of the instantiation of that secret sauce, but you mentioned like master data management data warehouse, and, you know, as well as I do Bob we've we've we've decades of failures trying to get a 360 degree view for example of the customer. Uh, it's just, just not real time. It's not as current as we would want it to be. The quality is not necessarily there. It's a very asynchronous process. Things have changed the processing power. You and I have talked about this a lot. We have much more data now. So it's that, that, that profile one. So, but also you mentioned curated apps, customer experience, and lead gen. You mentioned those two, uh, and you've also talked about digital transformation. So it sounds like you're supporting, and maybe this is not necessarily the case, but I'm curious as to what's going on here, maybe supporting more revenue generation in the early phases than say privacy or compliance, or is it actually, do you have use cases for both? >>It's all, it's all of it. Um, and, and shake and, you know, really talk passionately about some of the things we've helped clients do, like for instance, uh, J money. Why don't you talk about the, the hospital, um, uh, uh, you know, discharge processes. >>Absolutely. So, so, you know, just to make this a bit more real, they, you know, when you talk about a profile on one, it's about understanding of patient, as I said earlier, but it's trying to bring this notion of not just the things that you know about the patient you call that declared information. You can find the system in, you can find this information in traditional EMR systems, right? But imagine bringing in, uh, observed information, things that you observed an interaction with the patient, uh, and then bring in inferences that you can then start drawing on top of that. So to bring this to a live example, imagine at the point of care, knowing when all the conditions are right for the patient to be discharged after surgery. And oftentimes as you know, those, if all the different evidence of the different elements that don't come together, you can make some really serious mistakes in terms of patient discharge, bad things can happen. >>Patient could be readmitted or even worse. That could be a serious outcome. Now, how do you bring that information at the point of care for the person making a decision, but not just looking at the information, you know, but also understanding not just the clinical information, but the social, the socioeconomic information, and then making sure that that decision has the appropriate evidence behind it. So then when you do make that decision, you have the appropriate sort of, uh, you know, the guidance behind it for audit reasons, but also for ensuring that you don't have a bad outcome. So that's the example Bob's talking about, where we have a flight this in real settings, in, in healthcare, but also in financial services and other industries where you can make these decisions based on the machine, telling you with a lot of detail behind it, whether this is the right decision to be made, we call this explainability and the evidence that's needed. >>You know, that's interesting. I, I, I'm imagining a use case in my mind where after a patient leaves, so often there's just a complete disconnect with the patient, unless that patient has problems and goes back, but that patient might have some problems, but they forget it's too much of a pain in the neck to go back, but, but the system can now track this and we could get much more accurate information and that could help in future diagnoses and, and also decision-making for a patient in terms of, of outcomes and probability of success. Um, question, what do you actually sell? So it's a middleware product. It's a, how do I license it? >>It's a, it's a, uh, it's a software platform. So we sell software, um, and it is deployed in the customer's cloud environment of choice. Uh, of course we support complete hybrid cloud capabilities. Um, we support native cloud deployments on top of Microsoft and Amazon and Google. And we support IBM's hybrid cloud initiative with red hat OpenShift as well, which also puts us in a position to both support those public cloud environments, as well as the customer's private cloud environments. So constructed with Kubernetes in that environment, um, which helps the customer also re you know, realize the value of that operational appar operationalization, because they can modify those applications and then redeploy them directly into their cloud environment and start to see those as struck to see those spaces. Now, I want to cover a couple of the other components of the secret sauce, if I could date to make sure that you've got a couple other elements where some real breakthroughs are occurring, uh, in these spaces. >>Um, so Dave, you and I, you know, we're passionate about the semiconductor industry, uh, and you know, we know what is, you know, happening with regard to innovation and broadening the people who are now siliconized their intellectual property and a lot of that's happening because those companies who have been able to figure out how to manufacture or how to design those semiconductors are operationalizing those platforms with our customers. So you have people like apple who are able to really break out of the scene and do things by utilizing utilities and macros their own knowledge about how things need to work. And it's just, it's very similar to what we're talking about doing here for enterprise AI, they're operationalizing that construction, but none of those companies would actually start creating the actual devices until they go through simulation and design. Correct. Well, when you think about most enterprises and how they develop software, they just immediately start to develop the code and they're going through AB testing, but they're all writing code. >>They're developing those assets. They're creating many, many models. You know, some organizations say 90% of the models they create. They never use some say 50, and they think that's good. But when you think about that in terms of, you know, the capital that's being deployed, both on the resources, as well as the infrastructure, that's potentially a lot of waste as well. So one of the breakthroughs is, uh, the creation of what we call synthetic data and simulations inside of our, of our operational platform. So cortex fabric allows someone to actually say, look, this is my data pattern. And because it's sensitive data, it might be, you know, PII. Um, we can help them by saying, okay, what is the pattern of that data? And then we can create synthetic data off of that pattern for someone to experiment with how a model might function or how that might work in the application context. >>And then to run that through a set of simulations, if they want to bring a new model into an application and say, what will the outcomes of this model be before I deployed into production, we allow them to drive simulations across millions or billions of interactions to understand what is that model going to be effective. Was it going to make a difference for that individual or for this application or for the cost savings goal and outcomes that I'm trying to drive? So just think about what that means in terms of that digital transformation officers, having the great idea, being in the C-suite and saying, I want to do this with my business. Oftentimes they have to turn around to the CIO or the chief data officer and say, when can you get me that data? And we all know the answer to that question. They go like this, like the, yeah, I've got a couple other things on the plate and I'll get to that as soon as I can. >>Now we're able to liberate that. Now we're able to say, look, you know, what's the concept that you're trying to develop. Let's create the synthetic data off of that environment. We have a Corpus of data that we have collected through various client directions that many times gets that bootstrapped and then drive that through simulation. So we're able to drive from imagination of what could be the outcome to really getting high confidence that this initiative is going to have a meaningful value for the enterprise. And then that stimulates the right kind of following and the right kind of endorsement, uh, throughout really driving that change to the enterprise and that aspect of the simulations, the ability to plan out what that looks like and develop those synthetic aspects is another important element that the secret sauce inside of cortex fabric, >>Back to the semiconductor innovation, I can do that very cheaply. I think, I think I I'm thinking AWS cloud, I could experiment using graviton or maybe do a little bit of training with some, you know, new processors and, and then containerize it, bring it back to my on-premise state and apply it. Uh, and so, uh, just a as you say, a much more agile environment, um, yeah, >>Speed efficiency, um, and the ability to validate the hypothesis that, that started the process. >>Guys, think about the Tam, the total available market. Can we have that discussion? How big is that? >>I mean, if you think about the spend across, uh, the healthcare space and financial services, we're talking about hundreds of billions, uh, in that, in terms of what the enterprise AI opportunity, as in just those spaces. And remember financial services is a broad spectrum. So one of the things that we're actually starting to roll out today in fact, is a SAS service that we developed. That's based on top of our offerings called trust star trust star.ai, and trust star is a set of personalized insights that get delivered directly to the loan officer inside of, uh, an institution who's trying to, uh, really match, uh, lending to someone who wants to buy a property. Um, and when you think about many of those organizations, they have very, very high demand. They've got a lot of information, they've got a lot of regulation they need to adhere to. >>But many times they're very analytically challenged in terms of the tools they have to be able to serve those needs. So what's happening with new listings, what's happening with my competitors, what's happening. As people move from high tax states, where they want to potentially leave into new, more attractive toxin and opportunity-based environments where they're not known to those lending institutions that maybe, you know, they're, they're trying to be married up with. So we've developed a set of insights that are, is, this is a subscription service trust r.ai, um, which goes directly to the loan officer. And then we use our platform behind the scenes to use things like the home disclosure act, data, MLS data, other data that is typically Isagenix to those sources and providing very customized insights to help that buyer journey. And of course, along the way, we can identify things like are some of the decisions more difficult to explain, are there potential biases that might be involved in that environment as people are applying for mortgages, and we can really drive growth through inclusion for those lending institutions, because they might just not understand that potential client well enough, that we can identify the kind of things that they can do to know them better. >>And the benefit is really to hold there, right? And shale, I'll let you jump in, but to me, it's twofold. There. One is, you know, you want to have accurate decisions. You want to have low risk decisions. And if you want to be able to explain that to an individual that may get rejected, here's why, um, and, and it wasn't because of bias. It was because of XYZ and you need to work on these things, but go ahead shape. >>Now, this is going to add that point here, Dave, which is a double-faced point on the dam. One of the things that, and the reason why, you know, industries like healthcare, financial services spending billions, it's not because they look at AI in isolation, they actually looking at the existing processes. So, you know, established disciplines like CRM or supply chain procurement, whether it is contact center and so on. And the examples that we gave you earlier, it's about infusing AI into those existing applications, existing systems. And that's, what's creating the left because what's been missing so far is the silos of data and you traditional traditional transaction systems, but this notion of intelligence that can be infused into the systems and that's, what's creating this massive market opportunity for us. >>Yeah. And I think, um, I think a lot of people just misunderstood in the, or in the early, early days of the AI, you know, new AI when we came out of the AI winter, if you will, people thought, okay, the incumbents are in big trouble now because they are not, they're not AI developers, but really what you guys are showing is it's not about building your own AI. It's about applying AI and having the tools to do so. The incumbents actually have a huge advantage because they've got the systems in place. They can, if they, if they're smart, they can infuse AI and then extract value out of that for their customers. >>And that's why, you know, companies like, uh, like IBM are an investor in a great partner in this space. Anthem is an investor, uh, you know, of the company, but also, you know, someone who can utilize the capabilities, Microsoft, uh, Intel, um, you know, we've been, we've been, uh, you know, really blessed with a great backing Norwest venture partners, um, obviously is, uh, an investor in us as well. So, you know, we've seen the ability to really help those organizations think about, um, you know, where that future lies. But one of the things that is also, you know, one of the gaps in the promises when a C-suite executive like a digital transformation officer, chief digital chief customer officer, they're having their idea, they want to be accountable to that idea. They're having that idea in the boardroom. And they're saying, look, I think I can improve my customer satisfaction and, uh, by 20 points and decrease the cost of my call center by 20 or 30 or 50 points. >>Um, but they need to be able to measure that. So one of the other things that, uh, we've done a cognitive scale is help them understand the progress that they're making across those business goals. Um, now when you think about this people like Andrew Nang, or just really talking about this aspect of goal oriented AI, don't start with the problem, start with what your business goal is, start with, what outcome you're trying to drive, and then think about how AI helps you along that goal. We're delivering this now in our product, our version six product. So while some people are saying, yeah, this is really the right way to potentially do it. We have those capabilities in the product. And what we do is we identify this notion of the campaign, an AI campaign. So when the case that I just gave you where the chief digital officer is saying, I want to drive customer satisfaction up. >>I want to have more explainable decisions, and I want to drive cost down. Maybe I want to drive, call avoidance. Um, you know, and I want to be able to reduce a handling time, um, to drive those costs down, that is a campaign. And then underneath that campaign, there's all sorts of missions that support that campaign. Some of them are very long running. Some of them are very ephemeral. Some of them are cyclical, and we have this notion of the campaign and then admission planner that supports the goals of that campaign, showing that a leader, how they're doing against that goal by measuring the outcomes of every interaction against that mission and all the missions against the campaign. So, you know, we think accountability is an important part of that process as well. And we've never engaged an executive that says, I want to do this, but I don't want to be accountable to the result, but they're having a hard time identifying I'm spending this money. >>How do I ensure that I'm getting the return? And so we've put our, you know, our secret sauce into that space as well. And that includes, you know, the information around the trustworthiness of those, uh, capabilities. Um, and I should mention as well, you know, when we think about that aspect of the responsible AI capabilities, it's really important. The partnerships that we're driving across that space, no one company is going to have the perfect model intelligence tool to be able to address an enterprise's needs. It's much like cybersecurity, right? People thought initially, well, I'll do it myself. I'll just turn up my firewall. You know, I'll make my applications, you know, uh, you know, roll access much more granular. I'll turn down the permissions on the database and I'll be safe from cybersecurity. And then they realized, no, that's not how it was going to work. >>And by the way, the threats already inside and there's, long-term persistent code running, and you have to be able to scan it, have intelligence around it. And there are different capabilities that are specialized for different components of that problem. The same is going to be turnaround responsible and trustworthy AI. So we're partnered with people like IBM, people like Microsoft and others to really understand how we take the best of what it is that they're doing partner with the best, uh, that they're doing and make those outcomes better for clients. And then there's also leaders like the responsible AI Institute, which is a non-profit independent organization who were thinking about a new rating systems for, um, the space of responsible and trusted AI, thinking about things like certifications for professionals that really drive that notion of education, which is an important component of addressing the problem. And we're providing the integration of our tools directly with those assessments and those certifications. So if someone gets started with our platform, they're already using an ecosystem that includes independent thinkers from across the entire industry, um, including public sector, as well as the private sector, to be able to be on the cutting edge of what it's going to take to really step up to the challenge in that space. >>Yeah. You guys got a lot going on. I mean, you're eight years in now and you've got now an executive to really drive the next scale. You mentioned Bob, some of your investors, uh, Anthem, IBM Norwest, uh, I it's Crunchbase, right? It says you've raised 40 million. Is that the right number? Where are you in fundraising? What can you tell? >>Um, they're a little behind where we are, but, uh, you know, we're staged B and, uh, you know, we're looking forward to now really driving that growth. We're past that startup phase, and now we're into the growth phase. Um, and we're seeing, you know, the focus that we've applied in the industries, um, really starting to pay off, you know, initially it would be a couple of months as a customer was starting to understand what to be able to do with our capabilities to address their challenges. Now we're seeing that happen in weeks. So now is the right time to be able to drive that scalability. So we'll be, you know, looking in the market of how we assemble that, uh, you know, necessary capability to grow. Um, Shay and I have worked, uh, in the past year of, uh, with the board support of building out our go to market around that space. >>Um, and in the first hundred days, it's all about alignment because when you're going to go through that growth phase growth phase, you really have to make sure that things were pointed in the right direction and pointed together in the right direction, simplifying what it is that we're doing for the market. So people could really understand, you know, how unique we are in this space, um, and what they can expect out of an engagement with us. Um, and then, you know, really driving that aspect of designing to go to market. Um, and then scaling that. >>Yeah, I think I, it sounds like you've got, you got, if you're, if you're in down to days or weeks in terms of the ROI, it sounds like you've got product market fit nailed. Now it's about sort of the next phase is you really driving your go to market and the science behind how your dimension and your, your sales productivity, and you can now codify what you've learned in that first phase. I like the approach. A lot of, a lot of times you see companies, of course, this comes out of the west coast, east coast guy, but you see the double, double, triple, triple grow, grow, grow, grow, grow, and then, and then churn becomes that silent killer of the S the software company. I think you guys, it sounds you've, you've taken a much, much more adult-like approach, and now you're ready to really drive that scale. I think it's the new formula really for success for hitting escape velocity. Guys, we got to go, but thanks so much. Uh, uh, Bob, I'll give you the last word, w w w what you mentioned some of your a hundred day priorities. Maybe you can summarize that and what should we be looking for as Martin? >>I mean, I, I think, I think the, you know, the, our measures of success are our clients measure success and the same for our partners. So we're not doing this alone, we're doing it with system integrator partners, and we're doing it with a great technology partners in the market as well. So this is a part about keeping that promise for enterprise AI. And one of the things that I'll say just in the last couple of minutes is, you know, this is not just a company with a great vision and great engineers to develop out this great portfolio, but it's a company with great values, great commitments to its employees and the marketplace and the communities we serve. So I was attracted to the culture of this company, as well as I was, uh, to the, uh, innovation and what they mean to the, to the space of a, >>And I said, I said, I'll give you last word. Actually, I got a question for Shea you Austin based, is that correct? >>But we have a global presence, obviously I'm operating out of Austin, other parts of the U S but, uh, offices in, in, uh, in the UK, as well as in India, >>You're not moving to tax-free Texas. Like everybody else. >>I've got to, I've got an important home, uh, and life in Connecticut cell. I'll be traveling back and forth between Connecticut and Austin, but keeping my home there. >>Thanks for coming on and best of luck, we want to follow your progress and really appreciate your time today. Good luck. >>Thank you, Dave. All right. >>Thank you for watching this cube conversation. This is Dave Volante. We'll see you next time.

>>data by its very nature is distributed and siloed. But most data architectures today are highly centralized. Organizations are increasingly challenged to organize and manage data and turn that data into insights this idea of a single monolithic platform for data, it's giving way to new thinking. We're a decentralized approach with open cloud native principles and Federated governance will become an underpinning underpinning of digital transformations. Hi everybody, this is Day Volonte. Welcome back to HP discover 2021 the virtual version. You're watching the cubes continuous coverage of the event and we're here with Matt Mako is the field C T O for Israel software at H P E. And we're gonna talk about HP software strategy and esmeralda and specifically how to take a I analytics to scale and ensure the productivity of data teams. Matt, welcome to the cube. Good to see you. >>Good to see you again. Dave thanks for having me today. >>You're welcome. So talk a little bit about your role as CTO. Where do you spend your time? >>Yeah. So I spend about half of my time talking to customers and partners about where they are on their digital transformation journeys and where they struggle with this sort of last phase where we start talking about bringing those cloud principles and practices into the data world. How do I take those data warehouses, those data lakes, those distributed data systems into the enterprise and deploy them in a cloud like manner. And then the other half of my time is working with our product teams to feed that information back so that we can continually innovate to the next generation of our software platform. >>So when I remember I've been following HP and HP for a long, long time, the cube is documented. We go back to sort of when the company was breaking in two parts and at the time a lot of people were saying, oh HP is getting rid of the software business to get out of software. I said no, no, no hold on, they're really focusing and and the whole focus around hybrid cloud and and now as a service and so you're really retooling that business and sharpen your focus. So so tell us more about asthma, it's cool name. But what exactly is as moral software, >>I get this question all the time. So what is Israel? Israel is a software platform for modern data and analytics workloads using open source software components. And we came from some inorganic growth. We acquired a company called citing that brought us a zero trust approach to doing security with containers. We bought blue data who came to us with an orchestrator before kubernetes even existed in mainstream. They were orchestrating workloads using containers for some of these more difficult workloads, clustered applications, distributed applications like Hadoop. And then finally we acquired Map are which gave us this scale out, distributed file system and additional analytical capabilities. And so what we've done is we've taken those components and we've also gone out into the marketplace to see what open source projects exist, to allow us to bring those club principles and practices to these types of workloads so that we can take things like Hadoop and spark and Presto and deploy and orchestrate them using open source kubernetes, leveraging Gpu s while providing that zero trust approaches security. That's what Israel is all about. Is taking those cloud practices and principles but without locking you in again using those open source components where they exist and then committing and contributing back to the open source community where those projects don't exist. >>You know, it's interesting. Thank you for that history. And when I go back, I always been there since the early days of big data and Hadoop and so forth. The map are always had the best product. But but they can't get back then. It was like Kumbaya open source and they had this kind of proprietary system, but it worked and that's why it was the best product. And so at the same time they participated in open source projects because everybody that that's where the innovation is going. So you're making that really hard to use stuff easier to use with kubernetes orchestration. And then obviously I'm presuming with the open source chops, sort of leaning into the big trends that you're seeing in the marketplace. So my question is, what are those big trends that you're seeing when you speak to technology executives, which is a big part of what you do? >>Yeah. So the trends I think are a couple of fold and it's funny about Duke, I think the final nails in the coffin have been hammered in with the Hadoop space now. And so that that leading trend of of where organizations are going. We're seeing organizations wanting to go cloud first, but they really struggle with these data intensive workloads. Do I have to store my data in every cloud? Am I going to pay egress in every cloud? Well, what if my data scientists are most comfortable in AWS? But my data analysts are more comfortable in Azure. How do I provide that multi cloud experience for these data workloads? That's the number one question I get asked. And that's the probably the biggest struggle for these Chief Data Officers. Chief Digital Officer XYZ. How do I allow that innovation but maintaining control over my data compliance especially, we talk international standards like G. D. P. R. To restrict access to data, the ability to be forgotten in these multinational organizations. How do I sort of square all of those components and then how do I do that in a way that just doesn't lock me into another appliance or software vendors stack? I want to be able to work within the confines of the ecosystem. Use the tools that are out there but allow my organization to innovate in a very structured, compliant way. >>I mean I love this conversation. And just to me you hit on the key word which is organization. I want to I want to talk about what some of the barriers are. And again, you heard my wrap up front. I I really do think that we've created not only from a technology standpoint and yes, the tooling is important, but so is the organization. And as you said, you know, an analyst might want to work in one environment, a data scientist might want to work in another environment. The data may be very distributed. They maybe you might have situations where they're supporting the line of business. The line of business is trying to build new products. And if I have to go through this, hi this monolithic centralized organization, that's a barrier uh for me. And so we're seeing that change that kind of alluded to it upfront. But what do you see as the big, you know, barriers that are blocking this vision from becoming a reality? >>It very much is organization dave it's the technology is actually no longer the inhibitor here. We have enough technology, enough choices out there. That technology is no longer the issue. It's the organization's willingness to embrace some of those technologies and put just the right level of control around accessing that data because if you don't allow your data scientists and data analysts to innovate, they're going to do one of two things, they're either going to leave and then you have a huge problem keeping up with your competitors or they're gonna do it anyway, and they're gonna do it in a way that probably doesn't comply with the organizational standards. So the more progressive enterprises that I speak with have realized that they need to allow these various analytical users to choose the tools, they want to self provision those as they need to and get access to data in a secure and compliant way. And that means we need to bring the cloud to generally where the data is because it's a heck of a lot easier than trying to bring the data where the cloud is while conforming to those data principles. And that's, that's Hve strategy, you've heard it from our CEO for years now, everything needs to be delivered as a service. It's essential software that enables that capability, such as self service and secure data provisioning, etcetera. >>Again, I love this conversation because if you go back to the early days of the Duke, that was what was profound about. Do bring bring five megabytes of code, do a petabyte of data and it didn't happen. We shoved it all into a data lake and it became a data swamp. And so it's okay, you know, and that's okay. It's a one dato maybe maybe in data is is like data warehouses, data hubs data lake. So maybe this is now a four dot Oh, but we're getting there. Uh, so an open but open source one thing's for sure. It continues to gain momentum. It's where the innovation is. I wonder if you could comment on your thoughts on the role that open source software plays for large enterprises. Maybe some of the hurdles that are there, whether they're legal or licensing or or or just fears. How important is open source software today? >>I think the cloud native development, you know, following the 12 factor applications microservices based, pave the way over the last decade to make using open source technology tools and libraries mainstream, we have to tip our hats to red hat right for allowing organizations to embrace something. So core is an operating system within the enterprise. But what everyone realizes that its support, that's what has to come with that. So we can allow our data scientists to use open source libraries, packages and notebooks. But are we going to allow those to run in production? And so if the answer is no, then that if we can't get support, we're not going to allow that. So where HP es Merrill is taking the lead here is again embracing those open source capabilities, but if we deploy it, we're going to support it or we're going to work with the organization that has the committees to support it. You call HPD the same phone number you've been calling for years for tier 1 24 by seven support and we will support your kubernetes, your spark your presto your Hadoop ecosystem of components were that throat to choke and we'll provide all the way up to break fix support for some of these components and packages giving these large enterprises the confidence to move forward with open source but knowing that they have a trusted partner in which to do so >>and that's why we've seen such success with, say, for instance, managed services in the cloud or versus throwing out all the animals in the zoo and say, okay, figure it out yourself. But of course what we saw, which was kind of ironic was we, we saw people finally said, hey, we can do this in the cloud more easily. So that's where you're seeing a lot of data. A land. However, the definition of cloud or the notion of cloud is changing no longer. Is it just this remote set of services somewhere out there? In the cloud? Some data center somewhere. No, it's, it's moving on. Prem on prem is creating hybrid connections you're seeing, you know, co location facility is very proximate to the cloud. We're talking now about the edge, the near edge and the far edge deeply embedded, you know? And so that whole notion of cloud is, is changing. But I want to ask you, there's still a big push to cloud, everybody is a cloud first mantra. How do you see HP competing in this new landscape? >>I I think collaborating is probably a better word, although you could certainly argue if we're just leasing or renting hardware than it would be competition. But I think again, the workload is going to flow to where the data exists. So if the data is being generated at the edge and being pumped into the cloud, then cloud is prod, that's the production system. If the data is generated, the on system on premises systems, then that's where it's going to be executed, that's production. And so HBs approach is very much coexist, coexist model of if you need to do deaf tests in the cloud and bring it back on premises, fine or vice versa. The key here is not locking our customers and our prospective clients into any sort of proprietary stack, as we were talking about earlier, giving people the flexibility to move those workloads to where the data exists. That is going to allow us to continue to get share of wallet. Mindshare, continue to deploy those workloads and yes, there's going to be competition that comes along. Do you run this on a G C P or do you run it on a green lake on premises? Sure. We'll have those conversations. But again, if we're using open source software as the foundation for that, then actually where you run it is less relevant. >>So a lot of, there's a lot of choices out there when it comes to containers generally and kubernetes specifically, uh, you may have answered this, you get zero trust component, you've got the orchestrator, you've got the, the scale out, you know, peace. But I'm interested in hearing in your words why an enterprise would or should consider s morale instead of alternatives to kubernetes solutions? >>It's a fair question. And it comes up in almost every conversation. We already do kubernetes, so we have a kubernetes standard and that's largely true. And most of the enterprises I speak to their using one of the many on premises distributions of the cloud distributions and they're all fine. They're all fine for what they were built for. Israel was generally built for something a little different. Yes, everybody can run microservices based applications, devoPS based workloads, but where is Meryl is different is for those data intensive and clustered applications. Those sort of applications require a certain degree of network awareness, persistent storage etcetera, which requires either a significant amount of intelligence. Either you have to write in go lang or you have to write your own operators or Israel can be that easy button. We deploy those state full applications because we bring a persistent storage later that came from that bar we're really good at deploying those stable clustered applications and in fact we've open sourced that as a project cube director that came from Blue data and we're really good at securing these using spiffy inspire to ensure that there is that zero trust approach that came from side tail and we've wrapped all of that in kubernetes so now you can take the most difficult, gnarly, complex data intensive applications in your enterprise and deploy them using open source and if that means we have to coexist with an existing kubernetes distribution, that's fine. That's actually the most common scenario that I walk into is I start asking about what about these other applications you haven't done yet? The answer is usually we haven't gotten to him yet or we're thinking about it and that's when we talk about the capabilities of s role and I usually get the response, oh, a we didn't know you existed and be, well, let's talk about how exactly you do that. So again, it's more of a coexist model rather than a compete with model. Dave >>Well, that makes sense. I mean, I think again, a lot of people think, oh yeah, Kubernetes, no big deal, it's everywhere. But you're talking about a solution, I'm kind of taking a platform approach with capabilities, you've got to protect the data. A lot of times these microservices aren't some micro uh and things are happening really fast, You've got to be secure, you've got to be protected. And like you said, you've got a single phone number, you know, people say one throat to choke, Somebody said the other day said no, no single hand to shake, it's more of a partnership and I think that's a proposed for HPV met with your >>hair better. >>So you know, thinking about this whole, you know, we've gone through the pre big data days and the big data was all, you know, the hot buzz where people don't maybe necessarily use that term anymore, although the data is bigger and getting bigger, which is kind of ironic. Um where do you see this whole space going? We've talked about that sort of trends are breaking down the silos, decentralization. Maybe these hyper specialized roles that we've created maybe getting more embedded are lined with the line of business. How do you see it feels like the last, the next 10 years are going to be different than the last 10 years. How do you see it matt? >>I completely agree. I think we are entering this next era and I don't know if it's well defined, I don't know if I would go out on an edge to say exactly what the trend is going to be. But as you said earlier, data lakes really turned into data swamps. We ended up with lots of them in the enterprise and enterprises had to allow that to happen. They had to let each business unit or each group of users collect the data that they needed and I. T. Sort of had to deal with that down the road. And so I think the more progressive organizations are leading the way they are again taking those lessons from cloud and application developments, microservices and they're allowing a freedom of choice there, allowing data to move to where those applications are. And I think this decentralized approach is really going to be king. And you're gonna see traditional software packages, you're gonna see open source, you're going to see a mix of those. But what I think we'll probably be common throughout all of that is there's going to be this sense of automation, this sense that we can't just build an algorithm once released and then wish it luck that we've got to treat these these analytics and these these data systems as living things that there's life cycles that we have to support, which means we need to have devops for our data science. We need a ci cd for our data analytics. We need to provide engineering at scale like we do for software engineering. That's going to require automation and an organizational thinking process to allow that to actually occur. And so I think all of those things that sort of people process product, but it's all three of those things are going to have to come into play. But stealing those best ideas from cloud and application development, I think we're going to end up with probably something new over the next decade or so >>again, I'm loving this conversation so I'm gonna stick with it for a second. I it's hard to predict, but I'll some takeaways that I have matt from our conversation. I wonder if you could, you could comment. I think, you know, the future is more open source. You mentioned automation deV's are going to be key. I think governance as code, security designed in at the point of code creation is going to be critical. It's not no longer to be a bolt on and I don't think we're gonna throw away the data warehouse or the data hubs or the data lakes. I think they become a node. I like this idea and you know, jim octagon. But she has this idea of a global data mesh where these tools lakes, whatever their their node on the mesh, they're discoverable. They're shareable. They're they're governed uh in a way and that really I think the mistake a lot of people made early on in the big data movement, Oh we have data, we have to monetize our data as opposed to thinking about what products that I can I build that are based on data that then I can, you know, can lead to monetization. And I think and I think the other thing I would say is the business has gotten way too technical. All right. It's an alienated a lot of the business lines and I think we're seeing that change. Um and I think, you know, things like Edinburgh that simplify that are critical. So I'll give you the final thoughts based on my rent. >>I know you're ready to spot on. Dave. I think we we were in agreement about a lot of things. Governance is absolutely key. If you don't know where your data is, what it's used for and can apply policies to it, it doesn't matter what technology throw at it, you're going to end up in the same state that you're essentially in today with lots of swamps. Uh I did like that concept of of a note or a data mesh. It kind of goes back to the similar thing with a service smashed or a set of a P I is that you can use. I think we're going to have something similar with data that the trick is always how heavy is it? How easy is it to move about? And so I think there's always gonna be that latency issue. Maybe not within the data center, but across the land, latency is still going to be key, which means we need to have really good processes to be able to move data around. As you said, government determine who has access to what, when and under what conditions and then allow it to be free, allow people to bring their choice of tools, provision them how they need to while providing that audit compliance and control. And then again, as as you need to provision data across those notes for those use cases do so in a well measured and govern way. I think that's sort of where things are going. But we keep using that term governance. I think that's so key. And there's nothing better than using open source software because that provides traceability, the audit ability and this frankly openness that allows you to say, I don't like where this project is going. I want to go in a different direction and it gives those enterprises that control over these platforms that they've never had before. >>Matt. Thanks so much for the discussion. I really enjoyed it. Awesome perspectives. >>Well, thank you for having me. Dave are excellent conversation as always. Uh, thanks for having me again. >>All right. You're very welcome. And thank you for watching everybody. This is the cubes continuous coverage of HP discover 2021 of course, the virtual version next year. We're gonna be back live. My name is Dave a lot. Keep it right there. >>Yeah.

>> Narrator: From around the globe, It's theCUBE. With digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome to theCUBE's digital coverage of IBM Think 2021. I'm Lisa Martin. Next joining me is Leo LaBranche, Director of global strategic initiatives at AWS. Leo, welcome to theCUBE. >> Thank you, happy to be here. >> So talk to me about AWS and IBM what's going on there with their relationship. What are some of the things that are significant for both partners? >> Yeah, absolutely, IBM's relationship really started with us around 2016. I would say it was a little bit more opportunistic at the time. We knew there was an opportunity to go to market together. We knew there were some great things we could do for our customers. But we hadn't quite cracked to crack the code so to speak on when and where and why we were going to partner at that point. You fast forward into this sort of 2017 to 2019 timeframe. And we became, I'd say a lot more intentional about how we were going to go to market, where we were going to invest areas such as SAP, et cetera. Were an early one that we identified and I'd say the ball really started rolling sort of in the 2018 timeframe. A combination of a number of different things occurred, you know, the acquisition of Red Hat, obviously, you know Red Hat is a very significant, was a very significant partner with AWS, prior to the acquisition. And so post acquisition, you combine that with ramping up a workforce, focused on AWS, combined with a number of different competencies that IBM really invested in, around migration as an example, or SAP. And, you know, the, the ball really starting to roll quickly after that, you know, I'd say the last 18 months or so we both invested significantly in the relationship expansion around the world really, and joined resources and capability to make sure that we're going to markets sort of partnered intentional way rather than sort of an opportunistic. >> Oh, go ahead. >> So I'd say so far, that's absolutely been paying off in that we are seeing a number of wins all around the world across a broad set of industries, as well as the broad set of technologies. So, you know, the strength of, of IBM's consulting services in particular, but also their software combined with the strength of our platform has really proven to be successful for our customers. >> So you said started in 2016, really started taking shape in the last couple of years, that Red Hat acquisition. Talk to me about what's in this for customers. I imagine customers that are expanding or needing to move workloads into the cloud, or maybe more of a hybrid cloud approach. What are some of the big benefits that customers are going to gain from this partnership? >> Yeah, absolutely. And the reality is IBM has a long and storied history and relationship with their customers, right? They run and manage many of the workloads. They really know the customer's business incredibly well. They have domain expertise and industry and then the technology expertise from a professional services perspective to really help navigate the waters and determine what the right strategy is around moving to the cloud, right? You combine that with the depth and breadth of the skills and capabilities and services that AWS provides. And the fact that IBM has invested significantly in making sure their professional services are deeply steeped in our technology and capabilities. It's a great combination of really understanding the customer's needs. Plus the art of the possible, honestly, when it comes to technology that we provide, really can accelerate both and mitigate risk when it comes to moving to the cloud. >> That risk mitigation is key. So you guys recently, AWS recently launched if I'm going to get this right. Red Hat OpenShift Service on AWS or ROSA. Can you talk to me a little bit about ROSA? >> Yeah so, Red Hat obviously very well known, and ultimately adopted within the enterprise. We have built a fully managed service around Red Hat on AWS. What that means is you'll have access to essentially the capabilities that that Red Hat would normally provide but all containerized within a solution that allows you to get access to AWS services, right. The other benefit here is normally you would get sort of a multi-vendor with invoicing and cost model, right? Where you get billed from Red Hat, get billed from Amazon. You get billed from IBM. In this case, it's essentially a wholistic service in which there's a single sort of invoicing and vendor relationship, right. So it's combination of capabilities that normally would be provided via Red Hat combined with access to cloud and all the interfaces and capabilities around OpenShift, et cetera, that you could do there. Plus a more interesting and beneficial commercial model. >> So streamlined pricing models, streamlined operating model for customers. Talk to me about some of the customers that have adopted it. Give me a look into some of the industries where you've seen good adoption and some of the results that they're gaining so far. (loud engine buzz in background) >> Yeah one second, sorry, it's like insanely loud. >> Man's voice: No worries, let's just take a pause. We can just, so yeah we'll go right as if Lisa just finished the question. So just take a breather as long as it needs. And then whenever you're ready whenever that's died down, just like give it a beat give it like a second and then just right as if she just asked the question. >> Answer the question then. >> Man's voice: Yeah. >> All right. >> Man's voice: I'll cut it out as if nothing happened. >> Give me two minutes. So actually on your question, I know the answer from things that I've done recently, but was there an official answer Theresa I'm supposed to give on this? >> Teresa: No, not really I mean, I think what you're talking about on Red Hat specifically >> Right, ROSA's early adoption. >> Teresa: Yeah, no I mean, there there's a product page and stuff, it's really about just the ability of customers to be able to run those solutions on the AWS console it is really the, the gist of it. And that it's fully integrated. >> I'm not sure some of the examples I know of are publicly refrenceable. >> Lisa: That's okay, you could just say, you know, customer in XYZ industry, that's totally fair. I'm not so worried about that. >> Teresa: Yeah I don't know if so ROSA. Lisa, ROSA was just launched in March and so it's brand new so I don't have the customer stories yet. So that's why I don't have them listed for Leo. >> Lisa: Oh, that's fine, that's totally fine. Maybe we can talk about, you know, since the launch was just around the corner, some of the things that have been going on, the momentum interest from customers, questions conversations can be more like that as you're launching the GTM. >> Yeah, and there's certainly a couple of industries that they have targeted I'm going to go with that as well as a couple of customers, like, >> Teresa: Thank you, Lisa. >> Lisa: Sure, of course. >> I think they went around the corner. (Lisa laughs) >> Lisa: All right, let me know and I'll re-ask the question. I'll tweak it a little bit. >> Yeah, go ahead. >> Lisa: All right, so talk to me about, ROSA just launched very recently. Talk to me about customer interest, adoption. Maybe some of the industries in particular if you're seeing any industry that's kind of really leading edge here and taking advantage of this new managed service. >> Yeah, absolutely, so no big surprise, right? The the existing customer base that currently uses Red Hat Linux, and some of the options in OpenShift, et cetera that are out today are then the right customers to potentially look at this when it comes to moving forward. You know, industry-wise certainly there are areas within financial services, banking, insurance, et cetera. We're also seeing some around manufacturing, a little less so, but some in media and telco as well. So it's, it's a broad swath of any applicability of Red Hat and OpenShift is somewhat universal but the early customer bases has largely been sort of in those three areas. >> What I'm curious what are the key target audiences are these, Red Hat customers are these AWS customers. IBM all three? >> Yeah. I mean, there isn't necessarily the perfect customer that we're necessarily looking for, as much as if there are existing customers that are currently using Linux or using Red Hat. If there are someone who, a customer who currently has a relationship with either AWS or IBM there's an opportunity to essentially look at it from any of the angles. If you're already on cloud or you've already experienced AWS in some shape or form there's an opportunity to potentially to leverage ROSA, to further expand that capability and also have some more flexibility so to speak. If you're already using IBM as a professional services provider and advisory firm then they absolutely have the expertise and understanding of this product set to help you understand how it could be best leveraged, right. So you can kind of look at it from either of the dimensions. If it's a customer that's completely new to all of us then we're happy to talk to you. But it's something that will definitely take a little bit more explanation to understand as to why you should, or shouldn't consider us with this multicloud OpenShift type solution. >> Got it, let's shift gears a bit and talk about SAP. When we think about customers looking to migrate SAP workloads to the cloud, looking at the right cloud providers those are really big, challenging strategic decisions for leadership to make. Talk to me about why when you're in those conversations AWS is the best choice. >> Absolutely, I mean, really AWS, let's say with SAP and with with many of our services is really looking to give all the options that you could conceivably need or want in order to engage in cloud migration and transformation. press AP specifically, right? There are a number of different options, right. You could go for a lift and shift or upgrade from many databases to a suite on SAP HANA could potentially look to modernize and leverage cloud services, post migration as well. And then the sort of final pinnacle of that is a complete transformation to S four or S four HANA as far as why AWS specifically beyond just choice, you know, from a cost perspective, it's pretty compelling. And we have some pretty compelling business and use cases around ultimately the cost savings that come when you move from an on-premise SAP implementation to cloud beyond that, usually the cloud migration itself is an opportunity to condense or reduce the number of instances you're paying for, from an SAP perspective, which then further reduces cost. From a reliability perspective, you know, AWS is the world's most secure, extensive reliable cloud infrastructure, right? Any of the instances that you put on AWS are instantly I'd say fairly instantly provisioned in such a way that they are provided across multiple what we call Availability Zones which is giving you sort of the resiliency and the stability that really no other cloud provider can provide. On the security front, I mean this is really a unique position in that AWS plus IBM and the security, the depth in security services you know, numerous years of professional services work that IBM has done in the security space. You know, they have roughly 8,000 or so cybersecurity experts within IBM. So the combination of their expertise in security plus the security of our platform is a great combination. I'd say the final one is around performance, right? AWS offers many more cloud native options around certified SAP instances, specifically all the way from 256 gigabyte option all the way up to 24 terabytes which is the largest of its kind. And as those who have implemented SAP know it's a very resource intensive. So having the ability to do that from a performance perspective is a key differentiator for sure. >> Talk to me from your opinion about why IBM for SAP on AWS, why should customers go that direction for their projects? >> Yeah, you know, IBM has over 40 years of experience in implementing SAP for their customers right. And they've done, I think it's over 6,000 SAP migrations, 40,000 global SAP consultants around the world. Right, so from a capability and depth of experience, you know, there's a lot of nuance to doing it. SAP implementation, particularly one that's then moving from on-prem to the cloud. You know, they've got the experience right. Beyond that they have industry specific solutions that are pre-configured. So I think that there's 12 industry specific solutions pre-configured for SAP, it allows, you know roughly 20 to 30% acceleration when it comes to implementation of platforms. So combination of just depth of experience, depth of capability combined with these solutions to accelerate are all key reasons for sure. >> The acceleration you bring up, sorry is interesting because we saw in the last year the acceleration of digital transformation projects and businesses needing to pivot again and again, and again to figure out how to survive and be successful in this very dynamic market in which we're still living. Anything industry-wise specific that you saw that was really driving the acceleration and the use cases for ROSA in the last year? >> Yeah so, you know SAP, we saw an interesting trend as a result of what's everyone's been experiencing in the last year with COVID, et cetera. You know, many organizations postponed large ERP implementations and large SAP migrations, because of what you just said, right. They weren't entirely sure what would need to be done in order to survive either a competitive threats or more just the global threats that were occurring. So what we saw was, really none of the transformations went away. They, were put on hold for a period of time let's say six to nine months ago maybe even a year ago almost. In lieu of I would say more top line revenue generating or innovative type solutions that maybe were focused specifically at, you know, the changing dynamic with COVID. Since then we've seen a combination of those new ideas, right? Combination of the new innovation around healthcare of course, but also public sector and, you know a lot around employment and then engagement there. We've seen a combination of those new ideas and new innovations with the original goal of optimizing transforming SAP ERP, et cetera. And then combining the two to allow access to the data, that sits inside the SAP implementation the SAP. Combine the data in SAP with all these new innovations and then ultimately use that to sort of capitalize on what the future businesses are going to be. That's been huge, it's been very interesting to see some organizations completely change their business model over the course of the last 12 months. In ways they probably had never intended to before right? But it's, absolutely become an opportunity in a time of a lot of challenges. >> Agreed there are silver linings and we've seen a lot of those interesting opportunities to your point that businesses probably would never have come up with had there not been a forcing function like we've been living with. Leo thank you for joining me today. Talking to me about what's going on with IBM and AWS. We'll be excited to follow what happens with ROSA as it continues to roll out. And we appreciate you joining us on the program. >> Absolutely thank you for your time. >> For Leo Labrunch I'm Lisa Martin. You're watching theCUBE's digital coverage of IBM think 2021. (upbeat music)

>>Yeah, yeah. >>Welcome back to session, too. Thoughts about everywhere. Unlock new revenue streams with embedded search and I Today we're joined by our senior director of Global Oh am Rick Dimel, along with speakers from our thoughts about customer Hayes to discuss how thought spot is open for everyone by unlocking unprecedented value through data search in A I, you'll see how thoughts about compound analytics in your applications and hear how industry leaders are creating new revenue streams with embedded search and a I. You'll also learn how to increase app stickiness on how to create an autonomous this experience for your end users. I'm delighted to introduce our senior director of Global OPM from Phillips Spot, Rick DeMARE on then British Ramesh, chief technology officer, and Leon Roof, director of product management, both from Hayes over to you. Rick, >>Thank you so much. I appreciate it. Hi, everybody. We're here to talk to you about Fox Spot everywhere are branded version of our embedded analytics application. It really our analytics application is all about user experience. And in today's world, user experience could mean a lot of things in ux design methodologies. We want to talk about the things that make our product different from an embedded perspective. If you take a look at what product managers and product design people and engineers are doing in this space, they're looking at a couple of key themes when they design applications for us to consume. One of the key things in the marketplace today is about product led growth, where the product is actually the best marketing tool for the business, not even the sales portion or the marketing department. The product, by the word of mouth, is expanding and getting more people onto the system. Why is that important? It's important because within the first few days of any application, regardless of what it is being used binding users, 70% of those users will lose. Interest will stop coming back. Why do they stop coming back? Because there's no ah ha moment through them. To get engaged within the technology, today's technologies need to create a direct relationship with the user. There can't be a gatekeeper between the user and the products, such as marketing or sales or information. In our case. Week to to make this work, we have toe leverage learning models in leverage learning as it's called Thio. Get the user is engaged, and what that means is we have to give them capabilities they already know how to use and understand. There are too many applications on the marketplace today for for users to figure out. So if we can leverage the best of what other APS have, we can increase the usage of our systems. Because in today's world, what we don't want to do from a product perspective is lead the user to a dead end or from a product methodology. Our perspective. It's called an empty state, and in our world we do that all the time. In the embedded market place. If you look at at the embedded marketplace, it's all visualizations and dashboards, or what I call check engine lights in your application's Well, guess what happens when you hit a check engine life. You've got to call the dealer to get more information about what just took place. The same thing happens in the analytic space where we provide visualizations to users. They get an indicator, but they have to go through your gatekeepers to get access to the real value of that data. What am I looking at? Why is it important the best user experiences out on the marketplace today? They are autonomous. If we wanna leverage the true value of digital transformation, we have to allow our developers to develop, not have them, the gatekeepers to the rial, content to users want. And in today's world, with data growing at much larger and faster levels than we've ever seen. And with that shelf life or value of that data being much shorter and that data itself being much more fragmented, there's no developer or analysts that can create enough visualizations or dashboards in the world to keep the consumption or desire for these users to get access to information up to speed. Clients today require the ability to sift through this information on their own to customize their own content. And if we don't support this methodology, our users are gonna end up feeling powerless and frustrated and coming back to us. The gatekeepers of that information for more information. Loyalty, conversely, can be created when we give the users the ability toe access this information on their own. That is what product like growth is all about in thought spot, as you know we're all about search. It's simple. It's guided as we type. It gives a super fast responses, but it's also smart on the back end handling complexities, and it's really safe from a governance and as well as who gets access to what perspective it's unknown learned environment. Equally important in that learned environment is this expectation that it's not just search on music. It's actually gonna recommend content to me on the fly instantly as I try content I might not even thought of before. Just the way Spotify recommends music to us or Netflix recommends a movie. This is a expected learned behavior, and we don't want to support that so that they can get benefit and get to the ah ha moments much quicker. In the end, which consumption layer do you want to use, the one that leads you to the Dead End Street or the one that gets you to the ah ha moment quickly and easily and does it in an autonomous fashion. Needless to say, the benefits of autonomous user access are well documented today. Natural language search is the wave of the future. It is today. By 2004 75% of organizations are going to be using it. The dashboard is dead. It's no longer going to be utilized through search today, I if we can improve customer satisfaction and customer productivity, we're going to increase pretensions of our retention of our applications. And if we do that just a little bit, it's gonna have a tremendous impact to our bottom line. The way we deploy hotspots. As you know, from today's conversations in the cloud, it could be a manage class, not offering or could be software that runs in your own VPC. We've talked about that at length at this conference. We've also talked about the transformation of application delivery from a Cloud Analytics perspective at length here it beyond. But we apply those same principles to your product development. The benefits are astronomical because not only do you get architectural flexibility to scale up and scale down and right size, but your engineers will increase their productivity because their offerings, because their time and effort is not going to be spent on delivering analytics but delivering their offerings. The speed of innovation isn't gonna be released twice a year or four times a year. It's gonna It can happen on a weekly basis, so your time to market in your margins should increase significantly. At this point, I want a hand. The microphone over to Revert. Tesche was going to tell you a little bit about what they're doing. It hes for cash. >>Thanks, Rick. I just want to introduce myself to the audience. My name is Rotational. Mention the CTO Europe ace. I'm joined my today by my colleague Gillian Ruffles or doctor of product management will be demoing what we have built with thoughts about, >>um but >>just to my introduction, I'm going to talk about five key things. Talk about what we do. What hes, uh we have Really, um what we went through the select that spot with other competitors What we have built with that spot very quickly and last but not least, some lessons learned during the implementation. So just to start with what we do, uh, we're age. We are health care compliance and revenue integrity platform were a saas platform voter on AWS were very short of l A. That's it. Use it on these around 1 50 customers across the U. S. On these include large academic Medical Insight on. We have been in the compliant space for the last 30 plus years, and we were traditionally consulting company. But very recently we have people did more towards software platform model, uh, in terms off why we chose that spot. There were three business problems that I faced when I took this job last year. At age number one is, uh, should be really rapidly deliver new functionality, nor platform, and he agile because some of our product development cycles are in weeks and not months. Hey had a lot of data, which we collected traditionally from the SAS platform, and all should be really create inside stretch experience for our customers. And then the third Big one is what we saw Waas large for customers but really demanding self service capabilities. But they were really not going for the static dash boats and and curated content, but instead they wanted to really use the cell service capabilities. Thio mind the data and get some interesting answers during their questions. So they elevated around three products around these problems statements, and there were 14 reasons why we just start spot number one wars off course. The performance and speed to insights. Uh, we had around 800 to a billion robot of data and we wanted to really kind of mind the data and set up the data in seconds on not minutes and hours. We had a lot of out of the box capabilities with that spot, be it natural language search, predictive algorithms. And also the interactive visualization, which, which was which, Which gave us the agility Thio deliver these products very quickly. And then, uh, the end user experience. We just wanted to make sure that I would users can use this interface s so that they can very quickly, um, do some discovery of data and get some insights very quickly. On last but not least, talksport add a lot of robust AP ice around the platform which helped us embed tot spot into are offering. But those are the four key reasons which we went for thoughts part which we thought was, uh, missing in in the other products we evaluated performance and search, uh, the interactive visualization, the end user experience, and last but not least flexible AP ice, which we could customize into our platform in terms of what we built. We were trying to solve to $50 billion problem in health care, which is around denials. Um so every year, around 2, 50 to $300 billion are denied by players thes air claims which are submitted by providers. And we built offering, which we called it US revenue optimizer. But in plain English, what revenue optimizer does is it gives the capability tow our customers to mind that denials data s so that they can really understand why the claims were being denied. And under what category? Recent reasons. We're all the providers and quarters who are responsible for these claims, Um, that were dryland denials, how they could really do some, uh, prediction off. It is trending based on their historical denial reasons. And then last but not least, we also build some functionality in the platform where we could close the loop between insights, action and outcome that Leon will be showing where we could detect some compliance and revenue risks in the platform. On more importantly, we could, uh, take those risks, put it in a I would say, shopping card and and push it to the stakeholders to take corrective action so the revenue optimizer is something which we built in three months from concept to lunch and and that that pretty much prove the value proposition of thoughts. But while we could kind of take it the market within a short period of time Next leopard >>in terms >>off lessons learned during the implementation thes air, some of the things that came to my mind asses, we're going through this journey. The first one is, uh, focus on the use case formulation, outcomes and wishful story boarding. And that is something that hot spot that's really balance. Now you can you can focus on your business problem formulation and not really focus on your custom dash boarding and technology track, etcetera. So I think it really helped our team to focus on the versus problem, to focus on the outcomes from the problem and more importantly, really spend some time on visualizing What story are we say? Are we trying to say to our customers through revenue optimizer The second lesson learned first When we started this implementation, we did not dualistic data volume and capacity planning exercise and we learned it our way. When we are we loaded a lot of our data sets into that spot. And then Aziz were doing performance optimization. XYZ. We figured out that we had to go back and shot the infrastructure because the data volumes are growing exponentially and we did not account for it. So the biggest lesson learned This is part of your architectural er planning, exercise, always future proof your infrastructure and make sure that you work very closely with the transport engineering team. Um, to make sure that the platform can scale. Uh, the last two points are passport as a robust set of AP Ice and we were able to plug into those AP ice to seamlessly ended the top spot software into a platform. And last but not least, one thing I would like to closest as we start these projects, it's very common that the solution design we run into a lot of surprises. The one thing I should say is, along those 12 weeks, we very closely work with the thoughts, part architecture and accounting, and they were a great partner to work with us to really understand our business problem, and they were along the way to kind of government suggested, recommends and workarounds and more importantly, also, helpers put some other features and functionality which you requested in their engineering roadmap. So it's been a very successful partnership. Um, So I think the biggest take of it is please make sure that you set up your project and operating model value ember thoughts what resources and your team to make sure that they can help you as you. It's some obstacles in the projects so that you can meet your time ones. Uh, those are the key lessons learned from the implementation. And with that, I would pass this to my colleague Leon Rough was going to show you a demo off what we go. >>Thanks for Tesh. So when we were looking Thio provide this to our customer base, we knew that not everyone needed do you access or have available to them the same types of information or at the same particular level of information. And we do have different roles within RMD auto Enterprise platform. So we did, uh, minimize some roles to certain information. We drew upon a persona centric approach because we knew that those different personas had different goals and different reasons for wanting to drive into these insights, and those different personas were on three different levels. So we're looking at the executive level, which is more on the C suite. Chief Compliance Officer. We have a denial trending analyses pin board, which is more for the upper, uh, managers and also exact relatives if they're interested. And then really, um, the targeted denial analysis is more for the day to day analysts, um, the usage so that they could go in and they can really see where the trends are going and how they need to take action and launch into the auditing workflow so within the executive or review, Um, and not to mention that we were integrating and implementing this when everyone was we were focused on co vid. So as you can imagine, just without covert in the picture, our customers are concentrated on denials, and that's why they utilize our platform so they could minimize those risks and then throw in the covert factor. Um, you know, those denial dollars increase substantially over the course of spring and the summer, and we wanted to be able to give them ah, good view of the denials in aggregate as well as's we focus some curated pin boards specific to those areas that were accounting for those high developed denials. So on the Executive Overview Board, we created some banner tiles. The banner tiles are pretty much a blast of information for executives thes air, particular areas where there concentrating and their look looking at those numbers consistently so it provides them away to take a good look at that and have that quick snapshot. Um, more importantly, we did offer as I mentioned some curated pin boards so that it would give customers this turnkey access. They wouldn't necessarily have to wonder, You know, what should I be doing now on Day one, but the day one that we're providing to them these curated insights leads the curiosity and increases that curiosity so that they can go in and start creating their own. But the base curated set is a good overview of their denial dollars and those risks, and we used, um, a subject matter expert within our organization who worked in the field. So it's important to know you know what you're targeting and why you're targeting it and what's important to these personas. Um, not everyone is necessarily interests in all the same information, and you want to really hit on those critical key point to draw them and, um, and allowed them that quick access and answer those questions they may have. So in this particular example, the curated insight that we created was a monthly denial amount by functional area. And as I was mentioning being uber focused on co vid, you know, a lot of scrutiny goes back to those organizations, especially those coding and H i M departments, um, to ensure that their coding correctly, making sure that players aren't sitting on, um, those payments or denying those payments. So if I were in executive and I came in here and this was interesting to me and I want to drill down a little bit, I might say, You know, let me focus more on the functional area than I know probably is our main concern. And that's coating and h i M. And because of it hit in about the early winter. I know that those claims came in and they weren't getting paid until springtime. So that's where I start to see a spike. And what's nice is that the executive can drill down, they may have a hunch, or they can utilize any of the data attributes we made available to them from the Remittance file. So all of these data, um, attributes are related to what's being sent on the 8 35 fear familiar with the anti 8 35 file. So in particular, if I was curious and had a suspicion that these were co vid related or just want to concentrate in that area, um, we have particular flag set up. So the confirmed and suspected cases are pulling in certain diagnosis and procedure codes. And I might say 1.27 million is pretty high. Um, toe look at for that particular month, and then they have the ability to drill down even further. Maybe they want to look at a facility level or where that where that's coming from. Furthermore, on the executive level, we did take advantage of Let me stop here where, um also provided some lagged a so leg. This is important to organizations in this area because they wanna know how long does it take before they re submit a claim that was originally denied before they get paid industry benchmark is about 10 days of 10 days is a fairly good, good, um, basis to look at. And then, obviously anything over that they're going to take a little bit more scrutiny on and want to drill in and understand why that is. And again, they have that capabilities in order to drill down and really get it. Those answers that they're looking for, we also for this particular pin board. And these users thought it would be helpful to utilize the time Siri's forecasting that's made available. So again, thes executives need thio need to keep track and forecast where they're trends were going or what those numbers may look like in the future. And we thought by providing the prediction pins and we have a few prediction pins, um would give them that capability to take a look at that and be able to drill down and use that within, um, certain reporting and such for their organization. Another person, a level that I will go to is, um, Mawr on the analyst side, where those folks are utilizing, um, are auditing workflow and being in our platform, creating audits, completing audits, we have it segregated by two different areas. And this is by claim types so professional or institutional, I'm going to jump in here. And then I am going to go to present mode. So in this particular, um, in this particular view or insight, we're providing that analysts view with something that's really key and critical in their organization is denials related Thio HCC s andi. That's a condition category that kind of forecast, the risk of treatment. And, you know, if that particular patient is probably going to be seen again and have more conditions and higher costs, higher health care spending. So in this example, we're looking at the top 15 attending providers that had those HCC denials. And this is, um, critical because at this point, it really peaks in analyst curiosity. Especially, You know, they'll see providers here and then see the top 15 on the top is generating Ah, hide denial rate. Hi, denial. The dollars for those HCC's and that's a that's a real risk to the organization, because if that behavior continues, um, then those those dollars won't go down. That number won't go down so that analysts then can go in and they can drill down um, I'm going to drill down on diagnosis and then look at the diagnosis name because I have a suspicion, but I'm not exactly sure. And what's great is that they can easily do this. Change the view. Um, you know, it's showing a lot of diagnoses, but what's important is the first one is sepsis and substance is a big one. Substances something that those organizations see a lot of. And if they hover, they can see that 49.57 million, um, is attributed to that. So they may want to look further into that. They'd probably be interested in closing that loop and creating an audit. And so what allowed us to be able to do that for them is we're launching directly into our auditing workflow. So they noticed something in the carried insight. It sparked some investigation, and then they don't have to leave that insight to be able to jump into the auditing workflow and complete that. Answer that question. Okay, so now they're at the point where we've pulled back all the cases that attributed to that dollar amount that we saw on the Insight and the users launching into their auditing workflow. They have the ability Thio select be selective about what cases they wanna pull into the audit or if they were looking, um, as we saw with sepsis, they could pull in their 1600 rose, but they could take a sampling size, which is primarily what they would do. They went audit all 1600 cases, and then from this point in they're into, they're auditing workflow and they'd continue down the path. Looking at those cases they just pulled in and being able Thio finalized the audit and determine, you know, if further, um, education with that provider is needed. So that concludes the demo of how we integrated thought spot into our platform. >>Thank you, LeAnn. And thank you. Re test for taking the time to walk us through. Not only your company, but how Thought spot is helping you Power analytics for your clients. At this point, we want to open this up for a little Q and A, but we want to leave you with the fact that thought spot everywhere. Specifically, it cannot only do this for Hayes, but could do it for any company anywhere they need. Analytical applications providing these applications for their customers, their partners, providers or anybody within their network for more about this, you can see that the website attached below >>Thanks, Rick and thanks for tests and Leon that I find it just fascinating hearing what our customers are doing with our technology. And I certainly have learned 100% more about sepsis than I ever knew before this session. So thank you so much for sharing that it's really is great to see how you're taking our software and putting it into your application. So that's it for this session. But do stay tuned for the next session, which is all about getting the most out of your data and amplifying your insights. With the help of A, I will be joined by two thought spot leaders who will share their first hand experiences. So take a quick breather and come right back

>> Voiceover: From around the globe, it's theCUBE with digital coverage of Dell Technologies World Digital Experience brought to you by Dell Technologies. >> Welcome to theCUBE's coverage of Dell Technologies World 2020, the Digital Experience this year. I'm Lisa Martin, pleased to be joined by two CUBE alumni from Dell EMC. Please welcome Joe Caradonna, the VP of Cloud Storage CTO. Joe, good to see you again, even though quite socially distant. >> Yeah, thank you, it's great to be here. >> And Devon Reed is also joining us, the Senior Director of Product Management. Devon, how are you? >> I'm good, how are you doing? >> Good. >> Nice to be here, thank you. >> Nice to be chatting with you guys, although very, very socially distant, following rules. It wouldn't be a Dell Technologies World without having you guys on theCUBE, so we appreciate you joining us. So let's dig in. So much has happened in the world since we last spoke with you. But one of the things that happened last year, around a year ago, was the Dell On Demand program was launched. And now here we are nearly a year later when Michael Dell was just talking about, "Hey, Dell's plan is to go "and deliver everything as a service." We've heard some of your competitors kind of going the same route, some kind of spurned by COVID. Talk to us, Devon, we'll start with you, about what this direction is shift to as-a-service means and what it means specifically for storage. >> Yeah, certainly. So first and foremost, what we talked about last year with respect to On Demand, Dell Technologies On Demand, we've had great success with that program. But before I get into what we're doing with as-a-service, I really want to talk about why we're doing the as-a-service. And when we talk to customers and partners, and when we look at the trends in the market, what we're seeing is that customers are more and more wanting to consume technology infrastructure as a service in an OPEX manner. And analysts are revising those estimates up almost daily. And what we're seeing is one of the things that's driving that is actually why we're here in this remote session as opposed to being in Vegas, doing this. And it's really the global uncertainty around the pandemic. So it's driving the need to free up cash and consume these infrastructure more as a service. Now, as Michael said... Yeah, as Michael said, we have the broadest set of infrastructure offerings in the market and we are number one in most categories. And we're in the process of building out an offer structure that cuts across all the different infrastructure components. But to get real specific on what we're doing with a storage as a service, we are in the process of building out the first true storage or as a service offering for our infrastructure starting with storage. It'll be a private preview as of Q4, by the end of this fiscal year and generally available in the first half of next year. And what we're doing is taking the infrastructure, the Dell Technology's storage and where we're flipping the business model as opposed to buying it outright, the customers actually just consume it as a service. So they have a very simple consumption model where they just pick their outcome, they pick their restored service, they pick their performance, they pick their capacity, and we deliver that service to their on-premise site. >> Let me unpack outcomes of it, 'cause I saw that in some of the information online, outcome driven. What do you mean by that, and can you give us some examples of those outcomes that customers are looking to achieve? >> Yeah, so in today's world, the way people mostly consume infrastructure is, or at least storage, is that they say, "I need a storage product." And what the customers do is they work with our sales representatives and say, "I need a XYZ product. "Maybe it's a PowerStore and I need this much capacity. "I can pick all of the components, "I can pick the number of drives, "the type of drives there are." And that's really from a product perspective. And what we're doing with the, as-a-service, is we're trying to flip the model and really drive to what the business outcome is. So the business outcome here is really, I need block storage, I need this performance level, I need this much capacity. And then we basically ship the infrastructure, we think, that better suits those outcomes. And we're making changes across our entire infrastructure value chain to really deliver these service. So we try to deliver these much quicker for the customer. We actually manage the infrastructure. So it enables customers to spend less time managing their infrastructure and more time actually operating the service, paying attention to their business outcomes. >> Got it, and that's what every customer wants more of is more time to actually deliver this business outcomes and make those course corrections as they need to. Joe, let's talk to you for a bit. Let's talk, what's going on with cloud? The last time we saw you, a lot of change as we talked about, but give us a picture of Dell's cloud strategy. From what you guys are doing on-prem to what you are doing with cloud partners. What is this multi-pronged cloud strategy actually mean? >> Yeah, sure, I mean, our customers want hybrid cloud solutions and we believe that to be the model going forward. And so actually what we're doing is, if you think about it, we're taking the best of public cloud and bringing it on-prem, and we're also taking the best of on-prem and bringing it to the public cloud. So, you know, Devon just talked to you about how we're bringing that public cloud operation model to the data center. But what we've also done is bring our storage arrays to the cloud as a service. And we've done that with PowerStore, we've done that with PowerMax, and we've done that with PowerScale. And in the case of PowerScale for Google cloud, I mean, you get the same performance and capacity scale out in the cloud as you do on-prem. And the systems inter-operate between on-prem and cloud so it makes it easy for fluid data mobility across these environments. And for the first time it enables our customers to get their data to the cloud in a way that they can bring their high performance file workloads to the cloud. >> So talk to me a little bit about, you mentioned PowerScale for Google cloud service, is that a Dell hardware based solution? How does that work? >> Yeah, the adoptions have been great. I mean, we launched back in May and since then we brought on customers in oil and gas and eCommerce and in health as well. And we're growing out the regions, we're going to be announcing a new region in North America soon and we're going to be building out in APJ and EMEA as well. So, customer response has been fantastic, looking forward to growing up. >> Excellent, Devon back to you, let's talk about some of the things that are going on with PowerProtect DD, some new cloud services there too. Can you unpack that for us? >> So Joe, was talking about how we were taking our storage systems and putting them in the cloud. So I just back up in, and kind of introduce real quickly or reintroduce our Dell Technologies Cloud Storage Services. And that's really, we have our primary storage systems from Unity XT, the PowerStore, to PowerScale, to ECS, and that's housed in a co-locations facility right next to hyperscalers. And then that enables us to provide a fully managed service offering to our customers to a multi-cloud. So what we're doing is we're extending the Dell Technologies Cloud Storage Services to include PowerProtect DD. So we're bringing PowerProtect DD into this managed services offering so customers can use it for cloud, longterm retention, backup, archiving, and direct backup from a multicloud environment. So extending what we've already done with the Dell Technologies Cloud Storage Services. >> So is that almost kind of like a cloud based data protection solution for those workloads that are running in the cloud VMs, SaaS applications, physical servers, spiral data, things like that? >> Yeah, there's several use cases. So you could have a primary block storage system on your premises and you could actually be providing direct backup into the cloud. You could have backups that you have on-premise that you could be then replicating with PowerProtect data, data domain replication to cloud. And you could also have data in AWS, or Azure, or Google that you could be backing up directly to the PowerProtect domain into this service. So there's multiple use cases. >> Got it, all right. Joe, let's talk about some of the extensions of cloud you guys have both been talking about the last few minutes. One of the recent announcements was about PowerMax being cloud enabled and that's a big deal to cloudify something like that. Help us understand the nature of that, the impetus, and what that means now and what customers are able to actually use today. >> Yeah sure, I mean, we've launched the PowerMax as a cloud service about a year and a half ago with our partner, Faction. And that's for those customers that want that tier zero enterprise grade data capabilities in the cloud. And not just a cloud, it also offers multicloud capabilities for both file and block. Now, in addition, the Dell Tech World, we're launching additional cloud mobility capabilities for PowerMax, where let's say you have a PowerMax on-prem, you could actually do snapshot shipping to an object repository. And that could be in AWS, that can be in Azure, or it could be locally to our local ECS object store. In addition, in the case of Amazon we go a step further where if you do snapshot shipping into Amazon S3, you can then rehydrate those snapshots directly into EBS. And that way you can do processing on that data in the cloud as well. >> Give us an idea, Joe, the last few months or so what some of your customer conversations have been like? I know you're normally in front of customers all the time. Dell Tech World is a great example. I think last year there was about 14,000 folks there, was huge. And we're all so used to that three dimensional engagement, more challenging to do remotely, but talk to me about some of the customer conversations that you've had, and how they've helped influence some of the recent announcements. >> Yeah sure, customers... It might sound a little cliche, but cloud is a journey. It's a journey for our customers. It's a journey for us too, as we build out our capabilities to best serve them. But their questions are, "I want to take advantage "of that elastic compute in the cloud." But maybe the data storage doesn't keep up with it. In the case of when we go to PowerScale for Google, the reason why we brought that platform to the cloud is 'cause you can get hundreds of gigabytes per second of throughput through that. And for our customers that are doing things like processing genomic sequencing data, they need that level of throughput, and they want to move those workloads into the cloud. The computer's there but the storage systems to keep up with it, were not. So by us bringing a solution like this to the cloud, now they can do that. So we see that with PowerScale, we see a lot of that with file in the cloud because the file services in the cloud aren't as mature as some of the other ones like with block and object. So we're helping filling some of those gaps and getting them to those higher performance tiers. And as I was mentioning, with things like PowerMax and PowerStore, it's extending their on-prem presence into the public cloud. So they can start to make decisions not based on a capability, but more based on the requirements for where they want to run their workloads. >> And let's switch gears to talking about partners now. Dell has a huge partner ecosystem. We always talk with those folks on theCUBE as well, every year. Devon, from a product management perspective, tell me about some of the things that are interesting to partners and what the advantages are for partners with this shift in what, how Dell is going to be delivering, from PCs, to storage, to HCI, for example. >> Yeah exactly, so, Joe mentioned that it's really a journey and Joe talked a lot about how customers aren't maybe not (indistinct) completely going to a hyperscale or to a complete public cloud. And what we're hearing is there's a lot of customers that are actually wanting the cloud-like experience, but wanting it on-prem. And we're hearing from our partners almost on a daily basis. I have a lot of partner customer conversations where they want to be involved in delivering this as a service. Through their customers, they want to maintain that relationship, derive that value, and in some cases even provide the services for them. And that's what we're looking do as the largest infrastructure provider with the broadest base of partnership we have an advantage there. >> Is there any specific partner certification programs that partners can get into to help start rolling this out? >> At this point, we are trying to build it, but at this point we had nothing to announce here but that's something that we're actively working on and stay tuned for that. >> I imagine there will be a lot of virtual conversations at the digital tech world this year, between the partner community when all of these things are announced. And you get those brains collectively together although obviously virtually, to start iterating on ideas and developing things that might be great to programmatize down the road. And, Joe, last question for you, second to last question actually, is this, this year as we talked about a number of times, everyone's remote, everyone's virtual. It's challenging to get that level of engagement. We're all so used to being in-person and all of the hallway conversations even that you have when you're walking around the massive show floor for example, what can participants and attendees expect from your perspective this year at Dell Technologies World? Will they be able to get the education and that engagement that Dell really wants to deliver? >> Yeah, well, clearly we had to scale things back quite, there's no way around that. But we have a lot of sessions that were designed to inform them with a new capabilities we've been building out. And not just for cloud, but across the portfolio. So I hope they get a lot out of that. We have some interactive sessions in there as well, for some interactive Q and A. And you're right, I mean, a challenge for us is connecting with the customer in this virtual reality. We're all at home, right? The customers are at home. So we've been on Zoom, like never before, reaching out to customers to better understand where they want to go, what their challenges are and how we can help them. So I would say we are connecting, it's a little different and requires a little more effort on everyone's part. We just can't all do it in the same day anymore. It is just a little more spread out. >> Well, then it kind of shows the opportunity to consume things on demand. And as consumers, we sort of have this expectation that we can get anything we want on demand. But you mentioned, Joe, in the second to last question, this is the last one. But you mentioned, everybody's at home. You have to tell us about that fantastic guitar behind you. What's the story? >> Every guitar has a story. I'll just say for today, look, this is my tribute to Eddie Van Halen. We're going to miss him for sure. >> And I'll have the audience know, I did ask Joe to play us out. He declined, but I'm going to hold them to that for next time, 'cause we're not sure when we're going to get to see you guys in person again. Joe and Devon, thank you so much for joining me on the program today. It's been great talking to you. Lots of things coming, lots of iterations, lots of influence from the customers, influence from COVID and we're excited to see what is to come. Thanks for your time. >> Both: Thank you so much. >> From my guests, Joe Caradonna and Devon Reed, I'm Lisa Martin. You're watching theCUBE's coverage of Dell Technologies World 2020, the Digital Experience. (soft music)

(upbeat electronic music) >> From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation! >> Hi, everybody, this is Dave Vellante, and welcome to this CUBE conversation. You know, in this COVID-19 pandemic, we've been reaching out to folks that really have good visibility on what's going on out there. Tim Conley is here, he's a principal with the ATS Group, and partner of IBM. Tim, good to see you again man, thanks for comin' on! >> You got it, Dave, how are you today? >> Not too bad, you hangin' in there with all this craziness? How are things where you are? >> Yeah, we sure are, it's like groundhog day everyday, right? >> I know, the family's goin' crazy. They want to get out, and, well summer's comin', so hopefully the pandemic is going to calm down a little bit here, give us a breather. >> I hear that. >> But so, tell us what's goin' on these days with your company, with the ATS Group, what are you seein' in the marketplace? Give us the update. >> Sure, Dave. We've been in business 19 years now as a IBM systems integrator. Doin' a lot of work around storage. There's a lot of shiny new nickels out there these days that we're trying to make sure that we stay ahead of the game on. You know, our customers demand excellence from us, because that's what we've been giving them the last, you know, 19 years. So, they demand that from us, which is actually a great position for us to be in, but you know, with a lot of the new, shiny new nickels out there today, takes a lot of energy to focus on those, make sure we're talkin' to our customer about the right things, at the right times in the marketplace. >> I had Ed Walsh on the other day, and actually a couple times within the last six months, and he shared with us, actually in studio, when we didn't have to be six feet apart, the new announcements, the simplification of the portfolio. Presumably you've seen that. What was your reaction, how do you think the customer will react? >> That's a good question. Like I said, we're always looking to be bleeding edge, that's actually where we got our name from, Advanced Technology Services Group. So, IBM consistently comes out with some really good products and solutions, and we're constantly vetting that in our innovation center, in beta programs and things like that. A couple key things that are working now with us is Hybrid Multicloud. You know, IBM comes out, like I said, with some good solutions. We vet them out, and we're real excited about Spectrum Virtualize for Public Cloud. We've been using that for probably the last 12, 14 months, so trying to get the word out our customers on what it means, for partners as well, we can have a simple 10 minute conversation with our customers and our partners, kind of describe it at a high-level, and then they can gain interest at that point. It can be a little tricky, but we try to take that trickiness out of it, and let our customers know what's really goin' on, how it works for disaster recovery, for data protection to the cloud. Customers always want to talk about those things, but a lot of them really don't know those specifics, so we literally in 10 to 15 minutes can simply it to them, let 'em know how it works, and what scenarios it might work for them. Again, doing tests, and PoCs, things like that, it's really easy for us to do. One of our big federal customers want to call today at 12 o'clock, going over that implementation. They're pretty excited about tryin' it out, 'cause everybody thinks they want to move some things to the cloud, so Spectrum Virtualize allows us to do that pretty transparently. In fact, we used it ourselves last year, 'cause we took the journey to the cloud for SaaS offering. Took us over a year to do it, let me tell ya, it's not easy. You know, people make it sound like goin' to cloud is a snap, you know, spin up some OS instances, some EBS storage, and away we go. It's not that easy. >> I was just talkin' to a software executive who started his company 37 years ago, we both agreed, that's kind of when I started in this business, we both agreed that it just keeps getting more and more complicated. So, firms like yours are, but okay, so you talk about Hybrid Multicloud, of course IBM has cloud, but IBM itself says, "Hey, we hope people put their data into our cloud, "but we know there's other clouds out there." Well, hence Multicloud. So, what do you see as going on in the marketplace, specifically as it relates to Multicloud? And I wonder if we could weave in the COVID-19. Are you seeing people more receptive to cloud? >> Yeah, I'll tell ya, with COVID-19 we've had some opportunities delayed, because customers don't quite know where the market's going to go for themselves. We actually had one customer go out of business. So, that ultimately delayed a deal forever, right? But overall, things aren't that bad, but we do see customers, you know, lookin' to make some things easier for themselves. They might have been thinking about the cloud, but COVID's kind of brought it to the forefront, and they want to make things easier right away. Maybe you can save some money, right? So, we have a calculator we created for our customers to really go measure things to see what actually would it cost to go to cloud? You know, a lot of customers have no clue what it is. We could do that in five minutes for them, really interesting so, again we'll give them that information that hey, going to cloud might be an opportunity that they didn't think might be existent 'til now. >> So, Spectrum Virtualize, otherwise known you know, for those who have been around for a while like I have as kind of the roots of the SVC, the SAN Volume Controller, and the history of that product is software that enables you to virtualize, not just IBM storage, but anybody's storage, and of course one of the major use cases has been migration. So, in downturns, people want to get more value out of existing system. You know, maybe they come off lease, or maybe they want to elongate the life, and they may not have all the function so they can plug it into an SVC, and they get all the wonderful new bells and whistles, and the capabilities there. I wonder if we could talk about that, and again, what you're seeing just in terms of the current, you know, economic situation, and then specifically as it relates to cloud? >> That's a really a good point. So, you're tying to key things in today, right? Customers are looking to save money, because they don't want their financial outlook is based on COVID-19, so being able to help customers, and you nailed it, right? SVCs, Spectrum Virtualize has been around for, gosh probably 11 or 12 years now, 13 years actually. Right? So, we pride ourselves on bringing that to customers. Showing them how they can virtualize their environments in the storage arena. And we have some gigantic customers in the federal space, commercial space, so we don't just bring out white paper, say, "Eh, well it kind of looks good." Right? We actually have distinct customers, and talk to them about how they can drive their storage efficiencies up with IBM technologies, especially virtualization. And then, you know, reducing their overall cost. That's key, especially now. Customers are constantly looking to reduce their costs and whatnot with their storage, so that's a perfect inroad to that, and then bringin' in the Multicloud part of it, you're just extending Spectrum Virtualize to the cloud. You know, it was in IBM cloud first, it was in AWS back June of last year, and now we're working at IBM on puttin' that out into Azure. You know, so we can bring those savings to customers in the cloud, which they didn't know they could do that before. >> All right Tim, talk a little bit more about Multicloud, because you know, a joke recently, up until recently anyway, that Multicloud is more of a symptom of multi vendor, as opposed to a strategy, but with shadow IT, and sort of rogue systems, and the marketing department, the sales, everybody doing their own cloud, essentially Multicloud has become a strategy that the CIO has been asked to come in, "Hey, we got all these clouds." Clean up the crime scene I call it! What are you seeing today around Multicloud? >> That's a great point, I like that term, I'm going to steal it if you don't mind. Multicloud's customers are very much interested in, we have several customers doing Multicloud, IBM, Amazon, Azure. We actually did a study for an Azure customer, where we actually projected him to go to AWS with substantial cost savings. Some of that had to do with right-sizing their environment, where they weren't right-size in azure today. But I got to tell ya, you know, Cloud's not simple. It's not easy, again I mentioned earlier, we took that journey ourselves, spent a lot of time and energy with some really smart guys on my team to take that journey. So, Multicloud is a really great idea, and should be looked at, but I'm tellin ya' it's not quite that easy to just shift around, but there are definitely things to move to different cloud vendors. Again, if we bring it back to the storage arena, right? Spectrum Virtualize today's in IBM and Amazon, it's not in other clouds, so if you want to go that route, perfect opportunity to go Multicloud. >> Yeah, I mean I think you're makin' a good point. Let's face it, for our audience, we're in the early days of Multicloud. Yes, everybody has multiple clouds, everybody talks about having multiple clouds, but to be able to run applications natively in all these different clouds, whether it's the control plane, the data plane, the transport plane, all these disparate systems, and really be able to take native advantage of the local cloud services. That's not only very complex, it's really not fully baked out here today, but you know, we heard this week at IBM saying a lot of talk about Red Hat, containers, and Open Shift. So, we're starting on that journey, and that's really the promise of Multicloud, to be able to ultimately run applications anywhere, but as you point out, that's a very complex situation today for customers. >> Yeah, that's a good point. So, I totally would follow up with you on that, that's Multicloud, customers are looking at it, and their are some distinct advantages to the different cloud vendors. One could even say on-prem is a form of cloud, right? That's just your private cloud. So, keeping things on-prem for certain scenarios makes sense, be able to tie that back to the big cloud vendors, IBM, Amazon, Azure, right? Tying them together is the direction people are looking to go, and are kind of, some of them are there and have done it, but I'd say some, or more of them are in the infancy stage of that. >> What are you seeing in terms of, just kind of switching topics on you, in terms of things like governments, compliance, a lot of talk about cyber resiliency, especially given the pandemic. What are you seeing there with customers? >> Wow, that's a big topic. It's interesting, data classification, you think it'd be that easy, especially for some of our fed' customers, it's not that easy, right? Tryin' to classify the data, they just don't know, they might know the applications, but they don't know the content of that data. Is it able to be, what is it, section 126? Something like that. Is it able to go to the cloud? So, customers have a struggle on their hands tryin' to do that, right? The technology, groups within the customers, the storage folks, the OS folks, the Apps folks, they're all about the cloud, move things to cloud, but at the end of the day, it's the security folks that need to be able to do that data classification to see can the data even go there? Let alone the application or whatnot. Fairly easy to do that kind of stuff, but the data classification, we see that's the hard part. >> Okay, so you talked about shiny new toys at the beginning of this conversation. You know, IBM, you're tryin' to be a shiny old toy, (Tim laughing) they've been around you know, a century. >> Yeah. >> Why IBM though? What is it about IBM that you choose to partner with them? Give us the good, the bad, and the what you'd like to see improve. >> I would say, we've been a partner for IBM a long time, I used to work for IBM a million years ago. At the end of the day, our customers demand excellence from us, and they demand things to work, right? So, for me to put my company, and my resources into an opportunity for my customers, we can count on IBM. One, we have a great relationship with them, they have fantastic solutions, and then we vet them out. Our customers demand that of us, and I can give real world examples of one customer to another. So again, it's not like a white paper, I read it from vendor XYZ, at the end of the day we're implementing these solutions at our customers. A lot of times we're doing em in our lab first to make sure it works as designed, figure out with the shiny new nickels, you know, what's broken with that nickel? Why's it not so shiny? Or is it really as shiny as it appears to be, right? So, being able to do that stuff in-house is great, but at the end of the day, our customers demand excellence, and you know, we have to be bringing solutions to our customers, and IBM provides quite a few solutions, especially around the storage arena, where we live and breathe, that instant marketplace. So, we have to use great solutions that we can trust, and know work. >> So, my last question is what have you learned in the last, you know, couple of months with this pandemic. Now that we start to hopefully come out of it, at least for a little while, what are you learning? What's been accelerated, or pulled forward, and we're obviously not just goin' to 2019. So, how are you seeing your business, and your customers responding, what's the sort of mindset going forward? >> I'd say two things, so there's the COVID stuff, and then I talk about ransomware, cyber security, that could be another whole topic, right? But at the end of the day, I've been on a lot of webinars, and things of last three, four weeks, five weeks, listenin' to vendors talk about their shiny new nickels, and it's, quite frankly it's a bunch of mumbo jumbo, and that's not the world we live in, 'cause that's not what our customers are asking from us. But a lot of customers are really concerned about cyber security, ransomware. I have two customers locally that got hit with ransomware last fall, and let me tell ya, it's not a pretty scene, and they were not prepared for it, right? So, one of our jobs is to really help our customers understand where their gaps are within their organization, so that if they do get hit by cyber crime, or ransomware, that they can actually survive that, and not actually have to pay for it, then be up and running in a very small amount of time, which is key. Like I said, two customers got hit, just of mine, within 20 miles of our business, and they weren't prepared for it. >> I can't leave it there Tim, what do I got to do, if I'm an organization that's concerned about ransomware, probably every organization, what are the steps that I should take, like immediately? >> I would say a health assessment, and it doesn't have to be from ATS, it could be from anybody that's got the experience, and whatnot. We do health checks for customers consistently, and they don't have to be expensive, they don't have to be like, months. People always think, "A health check, oh my god, it's going to take so much time." It really doesn't. It's a quick health check, and we can look at those key things within your organization to see where you might not be prepared. And I'm talking like not prepared, like if you get ransomware tomorrow, you very well could be out of business. It's not hard to see those kinds of things. And you can make it more detailed if customers want that, right? But I would definitely have customers, if you're interested in that, call us, call any other vendor out there that's doin' those kinds of things. But it's fairly easy for folks like us and other vendors to be able to do those health checks, just take a quick look in your environment, see where your gaps are that you could literally go out of business tomorrow. >> Okay so, first pass is you're lookin' for open chest wounds that you got to close immediately and stop the bleeding, and then what? You start implementing things, you know, best practices, air gap. >> Air gap, you stole the word right out of my mind, air gap, right? You have to start, you know, look and see where, what's the requirements? First of all, make sure you can survive the event, and get back up and running in a reasonable amount of time, right? That one customer I mentioned was probably four or five weeks before they were able to restore all their servers, and they were fortunate that a lot of those were test thing that they could kind of wait a little bit long, but the other one they nearly went out of business, 'cause they just weren't prepared for it, right? So yeah, air gapping is a key thing, right? You know, where I put my data that it can't be touched, right? That's a fairly easy thing to start off with. >> Yeah, and then the whole process of recovery, who's on deck, you know, et cetera, et cetera. How communications occurs, there's technology, and of course as always, there's people in process. Well, Tim, I'll give you the last word, bring us home! >> Bring us home. Hey, but Dave, thanks very much for your time today. This is was a great time talking to you about some key things that we've worked with day in and day out over the last couple months. Again, bringing our solutions to our customers, that they demand that excellence from us. Bringin' IBM solutions that we natively know and love, and trust, because we've done 'em many, many times with other customers. So, pretty excited about what's goin' on in the industry, lookin' at all those shiny new nickels, and see which ones are actually shiny at the end of the day. >> All right, Tim, well listen, thanks for comin' back on theCUBE, it's great to see ya. I hope we get to see each other face to face. Stay safe. >> Sounds good Dave, thanks for your time, thank you. >> All right, you're welcome, and thank you for watching, everybody. This is Dave Vellante with theCUBE. Go to http://www.siliconangle.com to check out all the news, for thecube.net, where all these videos live, and http://www.wikibon.com, where I publish weekly. We'll see you next time on theCUBE. (relaxing instrumental music)

(upbeat music) >> Welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE, we have two special guests, Karim Toubba, CEO of Kenna Security, and Caroline Japic, CMO, Kenna Security. Great to see you guys, thanks for coming on, appreciate you taking the time, appreciate it. >> Thanks for having us. >> So RSA is coming up, big show, security's at the top of the list of all companies. You guys have a very interesting company. Risk based vulnerability management is like the core secret sauce, but there's a lot going on. Take a minute to talk about your company. What do you guys do? Why do you exist? >> Yeah, sure. Thanks for having us. Some, the security landscape as you very well know, pretty crowded space, a lot of different vendors, a lot of technologies that enterprises and organisations have to deal with. What we do has a lot of complexity behind it, but in an app practicality for enterprises is actually quite simple. They have many, many data sources that are finding problems for them, mapping to their attack surface, what are misconfigurations? Where are there vulnerabilities in your network or your host, where there vulnerabilities in your applications, we taking all of that data, specifically from 48 different data sources, we map it to what attackers are doing in the wild, run it through a lens of risk, and then enable the collaboration between I.T. and security, on what to focus on at the tip of the spear with a high degree of fidelity and efficacy so that they know that they can't fix everything, but prioritize the things that matter and are going to move the meter the most. >> So you guys have emerged as one of those kind of new models, the new guard of security, it's interesting, it's been around for 10 years, but yet a lot's changed in 10 years but a lot of evolving. Risk based vulnerability management is the buzzword, R-B- >> V-M >> Okay, really comes from the founder of the company. Why is this becoming an important theme? Because you got endpoints, you got all kinds of predictive stuff with data, you got surface area is growing, but what specifically about this approach makes it unique and popular? >> Yeah, I think what's happening is if you, to really answer that question, you have to look at two different ends of the spectrum in terms of the business, the security side and the IT DevOps and application development side. And at the core of that is what was largely traditional tension. If you think about security teams, operations teams, incident response teams, and if you sit down with them and understand what they do on a day to day basis, beyond the incident response and reaction side, they have a myriad of tools and technologies that discover problems, typically millions of issues. Then you go to the IT side, and the application and DevOps side, and they care about building the next application, making sure the systems are up and running. And what happens is they, we've gotten to the point where they can't possibly fix everything security is asking them to fix, and that's created a lot of tension, people have woken up, started to realize that that tension has to give way to collaboration. And the only way you can do that is enable security to detect all the problems, but then very quickly focus and prioritize on the things that matter, and then go to IT and then tell them specifically what to fix so that they have a high degree of precision and understanding, that the needle will be moved relative to what they're asking them to do. >> So is it the timing of the marketplace and the evolution of the business where it used to be IT that handled it, and now security has gotten broader in its scope, that there's now too many cooks in the kitchen, so to speak? >> Yeah, it's gotten broader in its scope, and there's also been a realization that if you think about the security problem statement, they find all the problems, but if you if you peel back the layers, you quickly realize, they own very little the remediation path. Who fixes-- >> John: They being IT? >> They being security. >> John: Okay. >> Yeah, so it's actually quite fascinating. If you think about who fixes a vulnerability on an operating system like Windows or Linux, it's the IT team. If you think about who fixes or upgrades a Java library or rewrites an application it's DevOps or the application developers, but security's finding all the problems. So they're realizing, as they deploy more tools, find more issues, and increase the amount of data, they've got to get very precise and really enable an entirely new way of collaborating with IT so that they can get them to focus on the things that matter the most. >> Karim, I want to dig into some of the complexity, but first want to get the Caroline on the brand, and the marketing challenge because it's almost an easy job in the sense, because there's a lot of security problems out there to solve, but it's also hard on the other side, is that, where's the differentiation? There's so many vendors out, there's a lot of noise. How are you looking at the marketplace? Because you guys are emerging in with nice, lift on the value proposition, you won some recent awards. How do you view the marketplace? RSA is going to be packed with vendors, it's going to be wall to wall, we get put in the corner, we are going to have small space for theCUBE, but there's a lot there and customers are being bombarded. How are you marketing the value proposition? >> You are right. There's so much noise out there, but we are very clear and precise on the value we bring to our customers, we also let our customers tell the story. So whether it's HSBC, or SunTrust, or Levi, we work with them very closely with those CSOs, with their head of IT to understand their challenges, and then to bring those stories to life so we can help other companies because our biggest challenge is that people just don't know that there's a better solution to this problem. This problem's been around a long time, it's getting worse every day, we're reading about the vulnerabilities that are happening on a regular basis, and we're here to let people know we can fix it, and we can do it in a pretty quick and painless way. >> You had mentioned before we came on camera that when you you're getting known, as the brand gets out there, but when you're in the deals, you win. Could you guys share some commentary on why that's the case? Why are you winning? >> Yeah, by the way, just to piggyback off that a little bit, there is a really interesting paradigm happening within the security space, if you look at the latest publications, I don't know, there are 1400 of us all buzzing around with the same words? I think what Caroline and the team have done an exceptional job on, particularly in relative to the positioning is, we don't want to scare people into looking at Kenna. We want to be more ethereal than that and make them understand that we're ushering in a new way away from tension to an era of collaboration with IT, DevOps and application teams. That's very different than telling somebody in your messaging, Hey, did you hear the latest attack that happened at XYZ? >> Yeah. >> That sort of fear and marketing through FUD, is creating a lot of challenges for organizations, and candidly, is making CISOs and other people in security close the door. >> I've definitely heard that, do you think that's happening a lot? >> I think that's happening a lot. I think we're sort of, I like to think that Caroline and the team are sort of at the forefront of leading that initiative, and you can, and we're doing it in every way possible to really sort of tell a much more positive story about how security can be smarter and spin in a positive light, and in fact, the technology is enabling that, so it's consistent. >> We live in dark times. Unfortunately, a lot of people like, if it bleeds, it leads, and that's a really kind of bad way to look at it. But back to your point about tension and collaborations, I think that's an interesting thread. There's a ton of tension out there, that's real, from the CISO's perspective. Because there's too many teams, I mean, you got, Blue Team, Red Team, IT, governance, compliance, full stack developers, app. So you have now too many teams, too many tools that have been bought and it's like, people have all these platforms, they're drowning in this. How do you guys solve that problem? >> Yeah, it's back to that point of collaboration, and what we've really found that's been interesting in solving that problem, because what we're doing if you step back, is, we're bringing in all these data sources, and where that tension comes in, if you unpack it a little bit, is from different people coming in with different data sources. So IT comes to the table about what to fix, with their own point of view, security comes with their own point of view, application teams come with their own point of view, governance and compliance comes with their point of view. What we do is we come in and even though we're technology, we're really aligning people in process. We're saying, "Look, we're going to to amass all that data, "we're going to very quickly use machine learning "and a bunch of algorithms to sift through "millions of pieces of data "and divine what actually matters." It's empirical, it's evidence based, and we align all the organizations around that filter through risks so that there's agreement on how to measure that, what to prioritize, what to action and what the results look like. And when it turns out that when you get a bunch of people across an organization, to get aligned around data that they all agree with as the source of truth, it gets much easier to get them to really focus on the things that ultimately matter. >> It's a single version of the truth, right? It's a single version that they all can work from. Security isn't telling IT, "This should be your priority today," when they say, "You don't know what my priorities are," is actually the data that's telling them what their priorities are by role, and that's really important and really gets past all the, the friction and the fighting in between the teams. >> Yeah, that's great point, back to my other question when I get back to you Caroline, is what is the success formula look like for you guys? Why are you winning? What are the feedback you're hearing from your customers? Because at the end of the day, references are important, but also, success is a tell sign. So what's the reasons behind the success? >> Yeah, I'll let Karim talk about being face to face with customers, because he does that all the time. But what we're saying is that, the customers are resonating with the story that we're telling, they understand they have the problem we're laying out in a very simple way for, to be able to solve their solution, and that's working. We've redone our positioning, our messaging, we've trained our sales team, people understand the value we can bring, and that's what we're communicating, and that's what's working. >> Karim, please add on that, I want to get more into this. >> Yeah, and on the customer side, what we see and I'll give you a pretty classic example for us with a very large bank that's a customer of ours. We actually started on the security side, right? We sold to their deputy CISO to deploy, and then eventually, they doubled down and then deployed globally across 64 countries. And that happened sponsored by the CIO. Now we're a security company, so you ask the question, well, why did that get driven in that structure? And why did that deal go down ultimately in that way? And what was the real value? The value to the security person was clear, I want to aggregate 10 to 12 different data sources, I want to prioritize, I want to collaborate with IT. The value to the CIO was the CIO happens to own all the application developers and all the IT people and the security people on a global basis. And so what they wanted to do, is they wanted to understand what the risk was for each of the lines of businesses they had within organization so that they can hold the business users accountable to paying a small tax for security, not just developing the next billion dollar high net worth application, which is extremely important to those businesses, but at the same time, ensuring that they're secure. And so that leverage when you start with security, and then branch out in other organizations, especially in large, multinational organizations, is really where the the real value comes into the platform. >> So if I hear you correctly, you come in for security, okay, we can get rid of the noise, help you out, check, win, and then the rest of the organization doesn't have security teams per se, >> Karim: Correct. >> Needs security to be built in from day one. >> Karim: Correct. >> You're providing a cross connect of value to the other teams? >> That's right. >> It's almost like, security is code, if you will. >> Karim: That's right. And nowhere is that more evident in our utilization statistics. So we're a SaaS platform, so of course we, like many other SaaS companies do a bunch of analytics on utilization of our customers, more often than not, in our large scale enterprises, we actually have more IT and non security users logging into Kenna, in a self service model, because they're the ones, back to the point you made earlier, that are actually driving the remediation path. >> Take us through how that works. So say I'm interested, okay, you sold me on it, great, I need the pain relief on the security side, I need the enablement and empowerment on the collaboration side, what do I do? Do I just plug my databases into you? Is it API driven? Are you on Amazon? Are you on Azure? What's cloud? What am I dealing with? Take me through the engagement. >> Yeah, so we're 100% cloud based platform. Multi cloud, so we can deploy in AWS, we can deploy in Google et cetera. And then what we do is we effectively through a bunch of API's called connectors that are transparent to the customers, we enable them to bring in their data. So this is everything from traditional scanning data like Qualys, Rapid7, Tenable, more, newer data like CrowdStrike, Tanium, DaaS SaaS, software composition analysis tools, WhiteHat, Veracode, Black Duck, Sonatype, you name it. The list goes on, specifically, there's about 48 of them. All of that is basically helps us understand what the totality of the attack surface is. That's very useful for security because they're using multiple tools. We then overlay what we call exploit and tell, this is the data that tells us about what attackers are doing in the wild. Specifically, we have 5 billion pieces of data that tell us about what vulnerabilities are being popped, what's the rate of change, what malware are they being embedded in? That use, that information is used through machine learning to help us prioritize and risk score each of the findings we get from the customer tools. And then where it pivots over to IT, is we then allow them to take all of that data and that metadata and asset criticality into what we call risk meters. So they're basically aligned with where, how IT operates. So for example, if you own all the Linux infrastructure in the cloud, you log in, you'll only see the risk across the infrastructure you own. Whereas if Caroline owns all the endpoint real estate across Windows, she logs in and understands what her risk is across Windows. And then we of course, integrate in the ticketing systems to drive the remediation and report up to executives and then over to security, about what the workflow you-- >> So you guys really focusing not so much on the security knock or the sock, it's more on indexing, if you will, for lack of a better description, the surface area, >> Karim: Correct. >> And getting that prepared from a visibility standpoint to acquire the data. >> Karim: That's right. >> And then leveraging that across-- >> Across the organizations, yeah. >> Did I get that, right? >> It's exactly right. And if you ask, if you again, double click deeper on that, what's fascinating to watch, so we have a an annual, or bi annual report that we do called prioritization or prediction, or P2P. And this is all of our customer data completely anonymized in a warehouse, and then we run a bunch of reports, and lot of the analytics we ran initially were around security. Now we're starting to pivot in IT. If you look at our latest report, one of the most interesting things I found in my time here is that the average large scale enterprise has actually no more than 10% remediation capacity, right? So what does that tell you? That tells you that 90% of the problems are going to go unsolved, which pinpoints why it's even more important to have specific prioritization on the things that matter. >> They solve the right 10%. >> At the right time too, >> At the right time. >> 10% capacity, operating capacity, assuming some automation that might take care of some of the low hanging fruit >> Exactly. >> Through DevOps or automation. You can focus on those 10% at the right time, which by the way, if you use that capacity for the wrong problems at the wrong time, it's wasted capacity. >> Karim: That's right. >> That's what you guys are trying to get at, right? >> Karim: That's exactly right, work smarter, not harder. >> So Kenna security, what's the vision? What's the next step? Why should someone care about working with you guys? Why is it important to engage you guys? What's the big deal? Is it the risk based vulnerability, kind of origination invention, which is the core or the DNA, or is it something bigger? What's the vision? What's the why? Yeah, well look for us, we started, our company was actually founded by a gentleman by the name Ed Bellis, who's the ex chief security officer at Orbitz, and he founded the company out of a need. We started very early in the traditional pure vulnerability space. This was like calling Classic Qualys, Rapid7, Tenable. We then expanded into the application world. So this is starting to take in, moving up stack if you will full stack, as the environment moves to cloud, as the environment moves to containers, as the environment moves to configuration management as the environment moves to a much more ephemeral state, that will drive an entirely new set of data sources that will drive an entirely different new set of priorities all aligned with the same model of risk. So our view of the future is that we are the platform that enables the organization to understand the totality of the attack surface, that enables collaboration across all the groups that deal with technology within enterprises, and allows them to really prioritize and understand risk in a way that not only fosters the collaboration, but gives you that return on investment that candidly ultimately CIOs are looking for. >> Caroline the story from a marketing perspective, what's the story you're trying to tell? >> We started this space, our founder Ed Bellis is the father of risk based vulnerability management and he loves it when I say that, but it's 100% true. We are continuing down this path, I mean, there are so many companies that have this problem that don't know that there's a better way to solve it. And so for now, our mission is to make sure that we're educating those people, they understand what's possible to do today, and then continuing from there, so. >> Well, I really appreciate you guys coming in and introducing and sharing more about Kenna Security, we've been seeing successes. I'm going to ask you about what you guys think about RSA, I'd love to get both you guys to weigh in. But before we get to the RSA kind of what's coming, take a quick minute to plug the company. What do you guys looking to do? You hiring? You just got some funding? Give the quick pitches. >> Yeah, sure, we did. We just closed $48 million series D round. We had all of our investors and a new investor, Sorenson Ventures come in. We also had two strategic investors, Citi and HSBC, because we do quite well, that very good validation. And we're also quite prominent in the financial services vertical, it helps that. And so for us, it's really about scaling, right? Scaling people, scaling the technology, scaling capabilities-- >> John: Across the board. >> Across the board. >> Engineering, obviously. >> Engineering, sales, geographies, it's really about getting the word out there and then being able to follow that up with the feed on the street that matter. >> We're definitely hiring, but we're also growing through OEMs. So we have a relationship with VMware, they're embedding us into their app defense products, and so if you buy app defense from VMware, you are buying Kenna whether you know it or not. >> So you're going to be an ingredient in other products. >> That's right. >> And or direct or indirect, probably some channel ecosystem opportunities? >> That's right. >> So we're growing on the technology partner OEM front, definitely interested in talking to companies that are interested on that front. >> We should do a whole segment on my fascination with what I call tier two or tier 1B clouds, specialty clouds, security clouds. So maybe do that another time. Okay, final question for you guys. RSA is coming this year 2020, and then a series of other events. Cloud Security has been a hot topic since re:Inforce last year was launched, we were there, kicking off theCUBE in security. What do you guys expect this year at RSA? What do you think the big themes are going to be? The hype? The meat on the bone? What's the real deal? What's the hype? What do you guys think is going to happen? >> Karim: I'll let you start. >> Yeah, I can tell you our theme is the right fight club. Because we are focused on the right fight that you need to have every day inside your enterprise. It's not focused on all the vulnerabilities that are hitting you because they're hundreds of thousands of them, millions of them, and there's going to be more every single day, it's about fighting the right fight. So if you come by our booth, you'll see that, it's going to be very exciting-- >> And of course, don't talk about the Fight Club vulnerabilities. (Karim laughs) >> You know the rules of the fight club. >> The first rule is to talk to Kenna about the right fight club. That is the first rule. >> That's cool. >> Yeah, I mean, it's interesting. Every, as you very well know, every year when people walk away from RSA, there's a few blogs that are written about what was the theme this year, I suspect this year's in security specifically, is going to be about AI driven security. We've been starting to see that for a while, it started to bleed into last year's event. I think for us in particular, we have a very particular point of view, and our book point of view is that doesn't matter if it's ML, if it's AI, or what type of algorithms you're running, the question is, what's the value? What is the value when you have 1400 people all screaming to get in the door of an organization? Everybody really has to begin to answer that question fundamentally. And I think the people that have that position in the market are the people that are going to be able to stand out. It's interesting, as always the hype with AI, but it's interesting, I was just trying to figure out when the term there is no perimeter was kind of first coined in theCUBE, I'm thinking probably about five years ago, it really became a narrative and then more recently, with the cloud, the perimeter is dead. Edge is out there. >> Karim: Right. >> So this is, what's the gestation period of real scalable security post perimeter is dead. It's interesting, is it years, is it seems to be hitting this year. It seems to be the point where, okay, I tried everything, now I've got to be data driven or figure out a way to map the surface area. >> That's right. >> End to end. Well, thanks to Kenna Security coming in, a solution for figuring out the vulnerabilities with a real invention. We're going to be covering security at RSA with Kenna Security and others. Thanks for watching, this is theCUBE. (upbeat music)

>> Announcer: From Miami Beach, Florida, it's theCUBE, covering Acronis Global Cyber Summit 2019. Brought to you by Acronis. >> Hey, welcome back everyone. It's theCUBE's coverage here in Miami Beach, Florida at the Fontainebleau Hotel for Acronis' Global Cyber Summit 2019's inaugural event with cyber protection, the new category that's emerging. It's been really exciting, it's a platform to really protect the data, protect cyber. Data protection's evolving to cyber protection. This is part of the Cloud 2.0 coverage that we've been covering on SiliconANGLE and theCUBE. Over the past year we're seeing more and more modernization of IT and systems. We're here with Ryan Davis, director of enterprise sales for Acronis. He's out on the front lines. This company has a great platform and a great field team out pushing the envelope, educating customers, having great success. I thought it would be great to have you on. Ryan, welcome to theCUBE. >> Ryan: Thank you for having me. >> So one of the things that I've observed and noticed with you guys is that you have a very strong field customer presence, you guys do a great job across the board on a direct touch basis, but also a huge channel operation, so you guys sell a lot through the channel, which is all good stuff, but you still got to talk to the big companies, still got to go to the large enterprises where you're having success. So you're doing that. What are some of the things that you're seeing when you're out pitching clients on Acronis, what are some of the concerns that you're hearing, what are the patterns, what's going on in the general broader market that's teasing out the Acronis value proposition? >> Sure, absolutely. So really where a lot of the focus and a lot of the attention is is on the edge. Five years ago, all the data was generated, produced, and analyzed in the core, in the data centers, whereas now, with the IoT devices, the proliferation of smart devices generating the data, they can't send it all to one central location. So networks are springing up out there in a distributed manner, and they have to be able to secure those smart devices and those edge networks. And that's where Acronis has a really compelling story, especially for enterprise. Because while they have a lot of consistency in the core, there's a lot of diversity on the edge. So it creates challenges for their IT teams to be able to manage it. So we can work with their field teams to provide a platform that can actually secure the devices in place and then protect them as well. >> So what's the pitch? Give us the pitch on that problem that you've just addressed, because that is legit. The edge is springing up, you're seen more and more edge cases and there's the outer edges, wearables, right? But the industrial edge, the company's edge, where you guys have a solution, that's challenging. The surface area for attacks are high, you have data as a challenge, you move compute to the data, you move data across the network, these are all costs, so costs are going up too. So with that problem, what is the pitch? >> Sure, well it really depends on who you're talking to, but there's two levels to it, right? So when you're talking industrial networks, the cost of downtime is huge, you know? You have 1,200 employees, at an automotive plant and you have a key industrial controller goes down, and that plant stops production, the cost is enormous. So at the plant level, they feel that pain, so they recognize the need for disaster recovery and business continuity capabilities. But when you start moving up a level at the executive level, it's what's really compelling and what's sexy for them. And that's really enabling digital transformation. And so I mentioned the concept of diversity a little bit earlier today. It's really hard for IT teams to do things on the edge when they may have 20,000, 40,000 edge devices that are going to run from NT, XP up to the most modern operating systems. It's difficult to implement a solution that's going to touch all of those devices. And backup and disaster recovery is critical for that, because if you're going to touch that many devices, you need the rollback capability. So being able to communicate a path forward to digital transformation on the edge is what is really exciting a lot of our executive customers. >> All right, so pretend I'm a customer for a minute, I'm like, hey Ryan, so hey, love the pitch, but I had XYZ data recovery company just came in earlier, they said they got an amazing platform. Why are you different, why should I not go with them? Why should I go with you? >> Sure, absolutely. Well all the competing vendors, all they know is the data center, right? So Acronis, part of our unique value proposition is not just the technology, it's really people, processes, and technology. So our experience working with industrial companies, pharmaceutical companies, working in compliant GXP, NERC CIP, this allowed us to develop expertise to come in not just with our product and the tech, but with people that know their environments and processes for successful implementation that other vendors can't bring. And our relationship with key automation vendors, we have our partners Honeywell, Emerson that embed our product, these are leading automation vendors that touch thousands of enterprises, and again, those experiences give us an understanding of these environments that other companies don't have. >> All right, so now I can come back and say, okay, well Ryan, you know, I like what you're saying, but I don't want to boil the ocean over. I don't see a path from what you're saying to execution. How can you help me figure this out? What do you offer me, as a client, if I'm the client, how do I get started? Is there a methodology, land, adopt, expand, how do you guys do that? >> Absolutely. Well, again, every customer's going to be different, right? But we don't like to boil the ocean either. What we're talking about is a path to digital transformation. We're not talking about the end result, right? So the first piece, the land, is always backup, right? When you backup the system, that provides a rollback mechanism so that provides an opportunity for you to do a lot more things with the computer. But the first piece is always just an assessment. You have to do an assessment, take stock of what you have, and Acronis is building technologies around discovery to help customers wrap their arms around these environments to make decisions on what they should do. >> So what's in it for me when I hear a platform, I hear about maybe complexity, is the platform really going to be the silver bullet? How do you manage that concern? >> Sure, sure. Well, most enterprises have at least five to seven different data protection solutions out there. So when you start talking about platform, you start talking kind of jargon words like unifying, consolidating their data protection suite. And that's really what Acronis is trying to do but not just in backup, but also offering more services through a single platform, so reducing the overall stack of tools that they're using to manage these environments. And again, going back to the edge, they don't have their big IT team that is versed in managing complex applications, right? You have controls engineers, plant engineers, scientists, that are interacting with these devices just enough to be dangerous. Think of it like a mechanic, so he's been working on cars his whole life, is very familiar with carburetors and brakes but now he gets a Tesla that's got sensors all over the place, and infotainment systems that run diagnostics, that doesn't make him an expert in that computer. So what Acronis is trying to do is provide you an easy-to-use platform that can solve multiple problems so that way a non-IT expert can service their compute infrastructure on the edge. >> So you guys have a good story for the edge. Also one story that's coming up here is ransomware. >> Correct. >> Ransomware is one of those disruptions that wasn't factored into the design of, you know, old-school legacy data protection and recovery systems. Those disruptions were hurricane, floods, some sort of mechanical failure, not a logical vector, in this case, security, which is going up high frequency. More and more every day, ransomware, malware, ZeroDay, others, incidents are on the rise. So more disruption. >> Correct. >> You guys are coming from that angle. >> Well, we're building security first into the platform. And that's a pivot that we made over the last 12 to 24 months. The first piece of that has already been released, which is called Active Protection, which is a module that actually monitors for changes and can prevent unauthorized changes to the file system like encryption. And so we're the only backup application that creates that proactive layer of protection. Everybody else is only going to be able to recover and be reactive. So we're trying to create a layered approach there and improve our customer security posture through an agent that's-- They would need to do the backup anyways. >> All right, so final track I want to chat with you about is take us through the real-life use case of an ideal sales process motion that encapsulates this modern era challenges and opportunities. You don't have to name the customer's name, you can use an anonymized case, but take use through what is a typical motion for you guys where you're successful, and what does it look like? >> Sure, absolutely. So it's pretty consistent, and I would say a pretty simple sales motion. The first piece is you have to do an assessment and a basic inventory in terms of what platforms are you going to have out there, and then, you're going to assess the sites that you have 'cause you need to create a deployment plan. And edge environments, it's not like the data center where you're just going to login to SCCM and push this out to your thousands of devices. They got to go to 40, 60 different plants. So you have to build, typically, a 12-month deployment plan where you're going to hit all of these different sites, build change windows, build maintenance windows. But before you can get to that, we do a POC on-site, where you touch, make sure that you have compatibility with the automation vendors, make sure you have compatibility with these networks, which are, again, very diverse and customized at each plant. Once you have a validated deployment process, you build out a timeline where you go site to site to site to deploy it. >> Take us through a POC. What does that look like, what's a typical POC for you guys? >> Sure, it's very simple based on what the ultimate objectives are. Most of our customers on the edge are primarily interested in business continuity, which would be backup, system recovery, application restore, right? On the edge it's not as much about the data, it's about securing the application that's performing the work, and so we protect the system, allow them to roll it back, once you validate that on the different platforms that they have, they're ready to move forward. >> And workloads are key criteria in all of this, that's a key factor. >> Absolutely, distributed control systems, R and D systems, lab systems, they have a lot of different types of applications you're not going to see in the data center, and we just want to get validated. >> John: So you hit your number? >> Absolutely, every year! (laughs) >> Over quota? >> Every year! >> All right. Ryan, thanks for coming on and sharing stories from the field, really appreciate it. >> Appreciate it, have a great one. >> CUBE Coverage here in Miami Beach, not a bad venue for a conference. This is the first conference that Acronis is putting on around cyber protection, Acronis' Global Cyber Summit 2019. Cyber protection new category emerging from the data protection world, this is the big story here. TheCUBE's covering two days, we'll be back with more after this short break. (electronic music)

>> Narrator: From the Cosmopolitan Hotel in Las Vegas Nevada, it's The Cube. Covering Coupa Inspire 2019. Brought to you by Coupa. >> Hey, welcome to The Cube. Lisa Martin on the ground at the Cosmopolitan in Las Vegas for Coupa Inspire 19. This is a really exciting two day event. We're going to be here covering, talking all about spending smarter. Very pleased to welcome to The Cube for the first time from KPMG, Dipan Karumsi, procurement advisory practice leader. Dipan, welcome to The Cube. >> Thank you very much, glad to be here, appreciate it. >> So this is an interesting event. Coupa in the last few years since becoming a public company really seems to be on this rocket ship. The momentum that CEO Rob Bernshteyn talked about this morning, there's now 1.2 trillion dollars of spend transactions going through the Coupa platform across companies in every industry from manufacturing to health care to retail. Loads of opportunity for businesses of any type to really get that control and visibility on spend. Talk to us about what KPMG is doing with Coupa. You're both a titanium sponsor here at Inspire 19 as well as a partner but give us a little bit of overview of your partnership with Coupa. >> Absolutely, so we've actually been coming to the conference for seven years now, I think since the very beginning and been the top level sponsor since the very beginning so it's been a fantastic relationship where we've helped a number of the customers that they talked about today, a lot of those customers were ours and we've had the opportunity to kind of get them live on the platform and see success by bringing spend through the platform and getting the visibility of those transactions. So we're fortunate enough we have 100 plus clients, globally, that we've been able to bring live on the Coupa platform across 90 plus countries and so we're really excited to be here. >> So some of the things I was reading about Coupa is that a lot of times, in the beginning, last 10 years or so, companies came to them looking for help with procurement or invoices. Now they're able to help companies get that visibility over all spend across procurement, invoices, expenses, travel management, payments. Talk to us about how you help some of those joint customers to really go from that siloed approach, going all right, we've got a few things under control, to getting that visibility because there is a tremendous amount of business impact that can come from getting that visibility into where all of your spend is coming from and where it's going. >> That's right. So I think in the beginning days as you kind of mentioned right, it was important to get the majority of the spend on the platform and so you looked at your indirect spend categories that are most commonly purchased, you get them onto the platform, you start analyzing that, more effective sourcing, drive value out of those categories. And as you look at the different categories that companies are spending in, they're evolving. More services spend, might be different categories in marketing, digital media, et cetera, and so as Coupa has expanded they've focused on some of the other categories and how to bring them in. So they bought companies that focus on contingent labor and those types of things. And so you start bringing all that spend together and all of a sudden you have a very nice pool of data from which you can analyze and from which you can make better decisions upon. So it's going to be a constant kind of proliferation of the tool and it's going to get broader and I think that's fantastic because organizations can see exactly what they're doing in a lot of different areas. >> Wouldn't it be nice if we all had that visibility in our personal lives as well? Well speaking of your relationship, you mentioned this is your seventh year sponsoring Inspire. Let's talk about how the role of procurement is changing, and the role of finance. Going from more tactical to much more strategic. Thinking about some of the disruptors like consumerization. You know, we're all consumers and we have this, we all have Amazon on our phone right, And we have this expectation that in our personal lives we can get anything at any time with the click of a button. And now when consumers are business buyers we want the same thing. Talk to us about what you have seen at KPMG as that procurement role has changed and what makes your implementation with Coupa unique. >> Yeah, that's exactly right, you put it exactly right there. You know, consumers or your employees internal of the organizations, are looking to buy in the way that they buy at home. They're looking to have visibility into when the shipment is, the products are going to arrive, they want to provide ratings as to what they thought of those products, they want to be able to have visibility into what they spent, and in fact where it's going is they want to be alerted when they should be buying something else. I mean, lot of the spend can actually be predicted as to what's going to be happening. And so think about an application that's going to alert you, it's probably about time that you need toner for this printer, or it's probably about time that you need XYZ to come and do this service for you. And so moving to that as you analyze the spend that's going to the platform is exactly what's happening. And I think it makes lives of employees better, easier, and it makes it a little bit more effective to kind of get spend through the application as well. >> When you're talking with customers, whether it's been a man or a woman who's been a CPO for a long time, where are they in terms of being receptive to having these predictive technologies? Is that a big cultural mind shift within whether it's a large manufacturing company or a smaller health care insurance carrier? >> It is, I mean the reality of it is with the data to be predictive there's a lot of things that have to be evaluated in the back. So you have to have clean supplier data, clean spend data, you have different applications that are integrating and you need end to end visibility in order to have a data set that's long enough and accurate enough to be able to predict from. So it's one thing to say okay we're going to go predictive, but it's another thing to be able to have the data to be able to accurately predict. So I think procurement organizations, kind of back to your other question of where are they going, you know historically procurement hasn't been one of the areas that CFOs are the first ones to jump into. And I think what organizations are realizing and was the C-suite is realizing is, this is the one place in the organization where we can see most of our third party spend. And so procurement has to quickly grasp, okay how can I get a handle on that information to be able to make better decisions and so show value to the organization. So that's how procurement's getting into the game, I think that's how they're going to show their value, by making that data set accurate, and that will lead them to kind of that predictive aspect of it. >> So what are those, what's the conversation like in terms of, all right there's many many sources of data, where we all know, you hear all the time data is the new oil, data is gold. It is if you have the ability to, like you said, make sure it's clean, but also be able to extract valuable insights from it faster than your competition. So from an infrastructure perspective, where does KPMG start with implementations with Coupa, are you first doing assessments with customers to understand all of the different data sources, how best to bring them together so that the power of AI can actually be applied to this massive pool of oil? >> That's right. So we start by kind of looking at the target operating model. What is it that the span of control for procurement's going to be? What is it that they want to do, what is it that they have ownership over? Then we identify kind of what are the technologies that are in place to house some of that information to help you make better decisions and to ultimately serve your end customers. And as we identify that architecture of what's going to be needed in the future, that's when we start getting into how we create and develop that oil infrastructure. And so as we look at the gaps in the infrastructure an application like Coupa can plug in with the appropriate procure to pay process, with the contracting process, with sourcing, spend analytics, whatever that may be, and it helps to plug the different gaps that allow you to kind of get all of that data into one place. >> Allowing customers to as Coupa says, spend smarter. I wanted to get your opinion on this BSM category that they are working to develop and lead. Business spend management. You guys recently, KPMG did a study on the future of procurement. Tell us a little bit about some of the interesting insights that came from that study and where you think business spend management is really going to be applicable and a big driver of business value. >> Yeah so, that's great, and I think business spend management, you know it continues to expand. I mean what Coupa's been every year, you've been to these conferences, is continuing to expand their portfolio and the modules that they have in order to kind of attack business spend management. And it's an important factor, a lot of spend happens through procurement and they need to have the application infrastructure to manage that. In the future procurement we talk a little bit about supplier centricity and customer centricity. So how is it that you're being able to work more effectively with your supplier, share information. Can they actually log in to the portal and see what the ratings are on the products that people are buying from them, I mean that's where we're kind of moving to. Customer centricity, giving them that Amazon-like experience so that they can go in on mobile and go in on any which way they want to, buy the things that they want, or be prompted to buy the things that they want. How are you innovating in categories, how are you using external data insights. You know the days of having that 20 year category manager who knows one category, sitting in one place, it's just not possible anymore. There's so much data and information out there you have to be able to leverage all of the external insights. And then of course using the digital platform to bring everything together. And that's where kind of Coupa plays, and the other e-procurement solutions, they're bringing all those insights together, allowing the foundation to be set so that you can execute on the processes that have to happen within it. >> We talk a lot about customer focus, customer centricity, Rob Bernshteyn talked about it this morning. Dig a little bit more into what you talked about with KPMG in terms of supplier centricity and some of the value that all of these suppliers are getting. How is KPMG helping some of these suppliers to really dial up their business, get better insights and really make a bigger impact with what they're delivering? >> Yeah, I mean it's really about visibility into the transactions that are happening and how their clients are using their products or services. So the more you can analyze around spend patterns, about the products that are being purchased, not purchased, the rigor of the catalog environment that's being created for your clients, the more they can analyze around that that allows them to be a little bit more focused in the way that they're dealing with their customers. And so we talk a lot about creating a very content rich environment. I mean if you went to Amazon today and you didn't see a picture, you didn't see ratings, you didn't see a description, would you purchase something? No. And that's what's happening inside organizations. Gone are the days where you have one line item that says this is it, and you don't know what you're buying. And so creating this content rich environment which is allowing and requiring suppliers to get into the environment to create their robust catalogs is really important. And so supplier's going to be a big part of what they're doing in the future to create this kind of appropriate spend management platform where the catalogs are set. >> I'm really getting on board to harness the power of that data. To your point, we have, the consumerization effect is so strong. We have this expectation that we can get anything and one of the things that Coupa was talking about this morning in the general session was not only the data, that they are now harnessing the power for their customers, for their suppliers, but also let's allow companies to go through the Coupa platform and search through software and products and deploy and manage and pay everything through that, bring in that consumerization approach to businesses in any industry. >> That's right. That's every right. So having it in one place makes it a little bit simpler, the visibility's there. I think the other thing that we can see a lot of is just self service. You walk into an airport, you do your own boarding pass. You come out of a parking garage, you pay for your parking and you leave. There's no people involved and frankly consumers like that. So being able to create an environment when you can do self service and things are being pushed to you to make decisions from versus having to go out and do a tremendous amount of research to make decisions is going to be a huge factor. I mean in the area of supplier risk management having bots and things that are mining social media in different areas for what's happening with your supplier so that you can be alerted to an event prior to making a large contractual obligation with them. You know, those are the types of things that we haven't seen in the past which I think we're going to get into now. >> It's so exciting. Dipan, I wish we had more time to get into it but thank you so much for stopping by The Cube and sharing what you guys at KPMG are doing to help customers really extract a tremendous amount of value and spend smarter. We appreciate your time. >> Thank you very much for having me. Appreciate it. >> For Dipan Karumsi, I'm Lisa Martin. You're watching The Cube from Coupa Inspire 19. Thanks for watching. (bright music)

>> Live from Las Vegas, it's theCUBE. Covering Informatica World 2019, brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World here in Las Vegas. I'm your host, Rebecca Knight along with my co-host John Furrier, we are joined by Jitesh Ghai, he is the Senior Vice President and General Manager Data Quality, Security and Governance at Informatica. Thank you so much for coming or returning to the show Jitesh. >> My pleasure, happy to be here. >> So, this is a real moment for data governance, we have the anniversary of GDPR and the California Privacy Act it's a topic at Dabos, there is growing concern among the public and lawmakers over security and privacy, give us the lay of the land from your perspective. >> Right, you know it is a moment for data governance, what's exciting in the space is governance was born out of risk and compliance and managing for risk and compliance, but really what it was mandating was healthy data management practices, how do we give the regulators comfort that our data is of high quality, that we know the lineage of where data is coming from that we know how the business relies on the data what is critical data? And while it was born to give the regulators comfort, what organizations very quickly realized is well when you democratize data, you need to give everybody that comfort, you need to give your data scientists, your data analysts, that same level of contextual understanding of their data right, where did it come from? What's the quality of it? How does the business use it, rely on it? And so that has been a tremendous opportunity for us, we've supported organizations, financial services from a BCBS 239 CCAR, counterparty credit risk, but what's happened is from a data democratization, data scale perspective, self-service analytics perspective, is what moved from terabytes to petabytes. We've moved from data warehouses, to data lakes and you can't democratize data unless there's a governed framework. I don't know, it sounds kind of like wait, democratizing data is supposed to be free data everywhere, but without some governed framework, it's a bit of a mess, and so what we're enabling organizations is the effective consumption and understanding of where their data is, discovering it, so that the right people can consume the data that they care about, the right data scientists can build the right models, the right analysts can build the right reports and the executives get the right confidence on what reports they're getting, what KPI's they're getting. >> One of the things that we talked last year, you had a couple customers on, you had told a great story, you guys had had the benefit as a long-standing company, 25 years in the private for large-customer base, but the markets changed, you mentioned governance I mean we're in the one year-anniversary of GDPR. >> Right. >> And I think everyone's kind of like OK what happened last year? More privacy laws are coming and one of the themes this year is clarity with data, but also in the industry you know access to data, making data addressable, because AI needs data sets, cloud has proven that, SAS business models, using data winning formula, that's clear if you're born in the cloud. Enterprises now want that same kind of SAS-like execution on the applications side, whether it's SAS or using AI for instance, >> Right. >> So when you have more regulation, inherent nature is to oh like more complexity, how are customers dealing with the complexity of this, because they want to free it up, but at the same time they want to make sure that they can respect the laws for individuals, but also governments aren't that smart either so you know, the balance there, what's the strategy? >> And therein lies the challenges with privacy specifically, it's not just about quality counterparty credit risk in like five or seven systems in a data warehouse, it's all the data in your enterprise, it's the data in production, there's the data in your DevOps environment, it's all your data literally, structured all the way to unstructured data like Word, PDFs, Powerpoints. And you need a governing framework around it, you need to enable organizations to be able to discover where is there sensitive information, how is there sensitive information proliferating through the organization? Is it protected? Is it not protected? And what's particularly, you know, we're all consumers, I'm pretty confident some or all of our data has been breached at some point, enabling organizations, what these privacy regulations are doing is they are giving us, as individuals, rights to go to the organizations we transact with and ask them, what are you doing with out data? Forget my data or at least tell me how you're processing it and get my consent for the data. >> Yeah, I mean policy and business models are certainly driving that and with regulation, I see that, but the question is that when you move the impact to the enterprise, you got storage drives. You store it on drives as a storage administrator you've got software abstractions with data, like you guys do. So, it's complicated, so the question is, for you, is what are customers doing now? What's the answer to all this? >> The answer really comes down to you need to scale to the scope of the problem, it's a thousand x-increase, you're going from terabytes to petabytes right? And so, you need an AI, an ML, an intelligent solution that can discover all of this information, but it can map it to John Furrier, this is where John Furrier's information is, it's in the human capital management system, the CRM system, organizations know, may start knowing whether sensitive data is, but hey don't know who it belongs to, so when you go to invoke your right to be forgotten or portability, today, what we're enabling organizations with is hey, we'll help you discover the sensitive information, but we'll also tell you who it belongs to, so that when John shows up or Rebecca, you show up, you just have to punch in their name and we'll tell you all the systems, that it's in. That is something that requires teams of database administrators, lawyers, system administrators that needs to be automated, to truly realize the potential of these privacy regulations, while enabling organizations to continue to innovate and disrupt with data. >> What's your take on whether or not consumers truly understand the scope of these privacy regulations, I mean talking about GDPR and you get the pop-ups that say do you consent and you just say yes, I just need to get to this site and so you blithely, just press yes, yes, yes so you are technically giving your consent, but do you, I mean what's your take, do consumers truly understand what they're doing here? >> You know, I think historically, we've all said yes, yes, yes, over the last, I would say two years with growing regulations and significant breaches, there is a change in customer expectations, you know, there's a stat out there in the event of a data breach, two-thirds of consumers of a particular organization blame the organization for the breach, not the hackers, right, so it's a mindshift in all of us, where you're the custodian of my data I'm counting on you, whatever organization I'm transacting with ,to ensure and preserve my privacy, ensure my data's protected. So, that's a big shift that's happened, so whether you're doing it for regulatory reasons, CCPA North America, there's several other state-wide regulations coming out or GDPR, the consumer expectation, forget regulations, it's brand preservation, it's customer trust, it's customer experience, that organizations are really having to solve for from a privacy standpoint. >> Tell what the news around yesterday around the shift of the trust pieces, because that's a huge deal. Because trust is shifting, expectations are shifting, so when you have shifting expectations, with users and buyers, customers, the experience has to shift. So, take us through what's the new things? >> Well, the new things are, you know, you look at we're enabling organizations to be data-driven, we're enabling organizations to transform, build new products, new services, be more efficient and for that, you need to enable them to get access to data. The counter, the tension on the other end is how do we get them broad-based access while ensuring privacy, right, and that's the balance. How do we enable them to be customer-centric and optimal in engaging with their customers while preserving the privacy of their customers and that really comes down to having a detailed understanding of what your critical data is, where is it in the organization and how an organization is using that data. Enabling an organization to know that they're processing data with the appropriate consent. >> What's interesting to me, when I was with press yesterday, is also the addition of how the cloud players are coming onboard, because you know, one constituent that's not mentioned in that statement is that you guys are kind of keeping an eye on, that are impacted by this, is developers, because you know developers like infrastructures coded with DevOps. Don't want to be provisioning networks and storage, they just write to the API's. Data is kind of going through that similar experience where, if I'm a developer doing an IOT app, I'm just going to use the cloud. I put the data there, I don't need to have a mismatch of mechanisms to deal with some governance compliance rules. >> Correct and that's why it needs to be built-in by design. And you know there's this connotation that- >> Explain that, what does built-in by design mean. >> Well you need to have privacy built-into how you as a business operate, how you as a DevOps team or development team, build products, if that's built-in to how you operate, you enable the innovation without falling into the pitfalls of oh you know what we broke some privacy regulations there we breached our customers trust there, we used data or engaged with them in manner that they weren't comfortable with. >> So, don't retro-fit after the fact? Think holistically on the front-end of the transformation in architecture. >> It's an enabler, in that if you do it right to begin with, you can continue to innovate and engage effectively, versus bolting it on as an afterthought and retro-fitting. >> It really seems like it is this evolution in thinking from this risk and compliance, overdoing this to check all the boxes, versus here are our constraints, but our constraints are actually liberating, is what you're saying. >> Right, but you can't democratize data, without giving the consumers of that data an understanding of the quality of that data, the trustworthiness of that data, the relevance of the data to the business, you give them that and now you're enabling your analytics, your data scientists, your analytics organizations to innovate with that data with confidence and if you do it within a framework of privacy, you're ensuring that you're preserving customer trust while you're automating and building intelligent and engaging customer experiences. >> What I love about the data business right now, is it's exciting because it's real specific examples of impact, security, you know, national security, to hackers, to just general security, privacy of the laws, But, I've seen the development angles interesting too, so when you got these two things moving, customers can ignore this, it's not like back-up and recovery where same kind of ethos is there, you don't want to think about it after the fact, you want to build it in, you know, there's certainly reasons why you do that, in case there's a disaster, but data is highly impactful all the time. This is a challenge, you guys can pull this off. >> Well you know, it's a, with privacy, it's no longer about a few systems, it's all your data and so the scope is the challenge and the scale applies for privacy, the scale applies for making data available enterprise wide and that's where you need and you know we spoke about AI needs data, well data also needs AI. And that's where we're leveraging AI and ML. Building out intelligence, to help organizations solve that problem and not do it manually. >> You know, I've said it on theCUBE, you've probably heard it many times, I say it all the time, scale is the new competitive advantage. Value is the new lock-in. No proprietary software anymore, but technology is needed. I want to ask you, you've been talking about this with some of your customers last year around data is that you need more scale, because AI needs more access to data, because the more visibility into data, the smarter, machine learning and AI applications can become. So Scale is real. What is the, what are you, you guys have some scalosity in your customers, you got the end-to-end, got the catalog and everything is kind of looking good, but you have competition How would you compare to the competition, when people say hey Jitesh, a start-up just popped out or XYZ company's got the solution, why should I go with them or you? What's the difference, what's the competitive angle? >> You know, the way we're thinking the problem is founded on governance is an enabler it's not about locking things down for risk and compliance, because you know, the regulators want to know that this particular warehouse is highly tightly controlled, it's about getting the data out there, it's about enabling end-users to have a contextual understanding when you're doing that for all of your data, within around, that's a thousand X-increase in the data, it's a thousand X-increase in your constituents, you're not supporting, the risk and compliance portions of the organization, you're supporting marketing, you're supporting sales, you're supporting business operations, supply chain, customer-onboarding and so with the problem of scale, practices of the past, which were typically manual laborious, but hey at the risk of non-compliance, we just had to deal with them, don't practically in any way scale, to the requirements of the future which is a thousand X-increase in consumers and that's where intelligence and AI and ML come in. >> The question I have for you is, where should customers store their data? Is there an answer to that on premises or in the cloud? What are they doing? >> The answer is yes, (Knight laughs) the customer should store their data, what we see, the world is going to be hybrid, mainframes are still here, on-premise will still be here many years from now. >> So you're taking the middle of the road here, so >> There's Switzerland. >> You're saying whatever they want on-premise or cloud, is there a preference you see with customers? >> Well, you know it depends on the applications , depends on regulations, historically regulations especially in financial services, have mandated a more on-premise stance, but those regulations, are also evolving and so we see, the global investment banks all of a sudden, we're having all sorts of conversations about enabling them to move select portions of their data estate to the cloud, enabling them to be more agile, so the answer is yes and it will be for a very long time to come. >> Final question, one of the most pressing problems in the technology industry is the skills gap. I want to hear your thoughts on it, how as a Senior Executive at Informatica, how worried are you about finding qualified candidates for your open-roles? >> You know, it is a challenge, good news is, we're a global organization, my teams are globally-distributed. I have teams in Europe, North America and Asia and the good part about that is if you can't find it in the valley, you can certainly find the talent elsewhere, and so while, it is a challenge, we're able to find talented engineers, software developers, data scientists, to help us innovate and build the intelligence capabilities to solve the productivity challenges, the scale challenges of data consumption. >> Jitesh, talk about the skills required for people coming out of school, take your Informatica hat off, put your expertise hat on, data guru hat, knowing that data is going to continue to grow, continue to have more impact across the board, from coding to society affix, whatever, what are some of the key skills in training, classes or courses or areas of expertise that people an dial-up or dig into that might be beneficial to them that may or may not be on the radar curriculum or, say is, part of school curriculum, >> you know we engage with universities in North America, in Europe, in Asia, we have a large development center in India and we're constantly, engaging with them. We're on various boards at various universities, advisory standpoint, big data standpoint and what we're seeing is as we engage with these organizations, we're able to feed back on where the market is going, what the requirements are, the nature of data science, the enabling technologies such as platforms like Spark, languages like Python and so we're working with these schools to share our perspectives, they in turn, are incorporating this into their curriculums and how they train future data scientists. >> When you see a young gun out there that's kicking butt and taking names and data, what are some of the backgrounds? Is it math, is it philosophy, is there a certain kind of pattern that you've seen as the makeup of just the killer data person? >> You know, it's interesting, you mention philosophy, I'm a big, I've hired many philosophy majors that have been some of the best architects, having said that, from a data science perspective, it's all about stats, it's all about math and while that's an important skillset to have, we're also focused on making their lives easier, they're spending 70% of their time, doing data engineering versus data science and so while they are being educated from a stats, from a data science foundation, when they come into the industry, they end up spend 70% of their time doing data engineering, that's where we're helping them as well. >> So study your Socrates and study your stats. >> I like that. (Knight and Furrier laugh) >> Jitesh, thank you so much for coming on theCUBE. >> My pleasure, happy to be here, thank you. >> I'm Rebecca Knight for John Furrier, you are watching theCUBE.