>>Good morning fellow nerds and welcome back to AWS Reinvent. We are live from the show floor here in Las Vegas, Nevada. My name is Savannah Peterson, joined with my fabulous co-host John Furrier. Day two keynotes are rolling. >>Yeah. What do you thinking this? This is the day where everything comes, so the core gets popped off the bottle, all the announcements start flowing out tomorrow. You hear machine learning from swee lot more in depth around AI probably. And then developers with Verner Vos, the CTO who wrote the seminal paper in in early two thousands around web service that becames. So again, just another great year of next level cloud. Big discussion of data in the keynote bulk of the time was talking about data and business intelligence, business transformation easier. Is that what people want? They want the easy button and we're gonna talk a lot about that in this segment. I'm really looking forward to this interview. >>Easy button. We all want the >>Easy, we want the easy button. >>I love that you brought up champagne. It really feels like a champagne moment for the AWS community as a whole. Being here on the floor feels a bit like the before times. I don't want to jinx it. Our next guest, Scott Castle, from Si Sense. Thank you so much for joining us. How are you feeling? How's the show for you going so far? Oh, >>This is exciting. It's really great to see the changes that are coming in aws. It's great to see the, the excitement and the activity around how we can do so much more with data, with compute, with visualization, with reporting. It's fun. >>It is very fun. I just got a note. I think you have the coolest last name of anyone we've had on the show so far, castle. Oh, thank you. I'm here for it. I'm sure no one's ever said that before, but I'm so just in case our audience isn't familiar, tell us about >>Soy Sense is an embedded analytics platform. So we're used to take the queries and the analysis that you can power off of Aurora and Redshift and everything else and bring it to the end user in the applications they already know how to use. So it's all about embedding insights into tools. >>Embedded has been a, a real theme. Nobody wants to, it's I, I keep using the analogy of multiple tabs. Nobody wants to have to leave where they are. They want it all to come in there. Yep. Now this space is older than I think everyone at this table bis been around since 1958. Yep. How do you see Siente playing a role in the evolution there of we're in a different generation of analytics? >>Yeah, I mean, BI started, as you said, 58 with Peter Lu's paper that he wrote for IBM kind of get became popular in the late eighties and early nineties. And that was Gen one bi, that was Cognos and Business Objects and Lotus 1 23 think like green and black screen days. And the way things worked back then is if you ran a business and you wanted to get insights about that business, you went to it with a big check in your hand and said, Hey, can I have a report? And they'd come back and here's a report. And it wasn't quite right. You'd go back and cycle, cycle, cycle and eventually you'd get something. And it wasn't great. It wasn't all that accurate, but it's what we had. And then that whole thing changed in about two, 2004 when self-service BI became a thing. And the whole idea was instead of going to it with a big check in your hand, how about you make your own charts? >>And that was totally transformative. Everybody started doing this and it was great. And it was all built on semantic modeling and having very fast databases and data warehouses. Here's the problem, the tools to get to those insights needed to serve both business users like you and me and also power users who could do a lot more complex analysis and transformation. And as the tools got more complicated, the barrier to entry for everyday users got higher and higher and higher to the point where now you look, look at Gartner and Forester and IDC this year. They're all reporting in the same statistic. Between 10 and 20% of knowledge workers have learned business intelligence and everybody else is just waiting in line for a data analyst or a BI analyst to get a report for them. And that's why the focus on embedded is suddenly showing up so strong because little startups have been putting analytics into their products. People are seeing, oh my, this doesn't have to be hard. It can be easy, it can be intuitive, it can be native. Well why don't I have that for my whole business? So suddenly there's a lot of focus on how do we embed analytics seamlessly? How do we embed the investments people make in machine learning in data science? How do we bring those back to the users who can actually operationalize that? Yeah. And that's what Tysons does. Yeah. >>Yeah. It's interesting. Savannah, you know, data processing used to be what the IT department used to be called back in the day data processing. Now data processing is what everyone wants to do. There's a ton of data we got, we saw the keynote this morning at Adam Lesky. There was almost a standing of vision, big applause for his announcement around ML powered forecasting with Quick Site Cube. My point is people want automation. They want to have this embedded semantic layer in where they are not having all the process of ETL or all the muck that goes on with aligning the data. All this like a lot of stuff that goes on. How do you make it easier? >>Well, to be honest, I, I would argue that they don't want that. I think they, they think they want that, cuz that feels easier. But what users actually want is they want the insight, right? When they are about to make a decision. If you have a, you have an ML powered forecast, Andy Sense has had that built in for years, now you have an ML powered forecast. You don't need it two weeks before or a week after in a report somewhere. You need it when you're about to decide do I hire more salespeople or do I put a hundred grand into a marketing program? It's putting that insight at the point of decision that's important. And you don't wanna be waiting to dig through a lot of infrastructure to find it. You just want it when you need it. What's >>The alternative from a time standpoint? So real time insight, which is what you're saying. Yep. What's the alternative? If they don't have that, what's >>The alternative? Is what we are currently seeing in the market. You hire a bunch of BI analysts and data analysts to do the work for you and you hire enough that your business users can ask questions and get answers in a timely fashion. And by the way, if you're paying attention, there's not enough data analysts in the whole world to do that. Good luck. I am >>Time to get it. I really empathize with when I, I used to work for a 3D printing startup and I can, I have just, I mean, I would call it PTSD flashbacks of standing behind our BI guy with my list of queries and things that I wanted to learn more about our e-commerce platform in our, in our marketplace and community. And it would take weeks and I mean this was only in 2012. We're not talking 1958 here. We're talking, we're talking, well, a decade in, in startup years is, is a hundred years in the rest of the world life. But I think it's really interesting. So talk to us a little bit about infused and composable analytics. Sure. And how does this relate to embedded? Yeah. >>So embedded analytics for a long time was I want to take a dashboard I built in a BI environment. I wanna lift it and shift it into some other application so it's close to the user and that is the right direction to go. But going back to that statistic about how, hey, 10 to 20% of users know how to do something with that dashboard. Well how do you reach the rest of users? Yeah. When you think about breaking that up and making it more personalized so that instead of getting a dashboard embedded in a tool, you get individual insights, you get data visualizations, you get controls, maybe it's not even actually a visualization at all. Maybe it's just a query result that influences the ordering of a list. So like if you're a csm, you have a list of accounts in your book of business, you wanna rank those by who's priorities the most likely to churn. >>Yeah. You get that. How do you get that most likely to churn? You get it from your BI system. So how, but then the question is, how do I insert that back into the application that CSM is using? So that's what we talk about when we talk about Infusion. And SI started the infusion term about two years ago and now it's being used everywhere. We see it in marketing from Click and Tableau and from Looker just recently did a whole launch on infusion. The idea is you break this up into very small digestible pieces. You put those pieces into user experiences where they're relevant and when you need them. And to do that, you need a set of APIs, SDKs, to program it. But you also need a lot of very solid building blocks so that you're not building this from scratch, you're, you're assembling it from big pieces. >>And so what we do aty sense is we've got machine learning built in. We have an LQ built in. We have a whole bunch of AI powered features, including a knowledge graph that helps users find what else they need to know. And we, we provide those to our customers as building blocks so that they can put those into their own products, make them look and feel native and get that experience. In fact, one of the things that was most interesting this last couple of couple of quarters is that we built a technology demo. We integrated SI sensee with Office 365 with Google apps for business with Slack and MS teams. We literally just threw an Nlq box into Excel and now users can go in and say, Hey, which of my sales people in the northwest region are on track to meet their quota? And they just get the table back in Excel. They can build charts of it and PowerPoint. And then when they go to their q do their QBR next week or week after that, they just hit refresh to get live data. It makes it so much more digestible. And that's the whole point of infusion. It's bigger than just, yeah. The iframe based embedding or the JavaScript embedding we used to talk about four or five years >>Ago. APIs are very key. You brought that up. That's gonna be more of the integration piece. How does embedable and composable work as more people start getting on board? It's kind of like a Yeah. A flywheel. Yes. What, how do you guys see that progression? Cause everyone's copying you. We see that, but this is a, this means it's standard. People want this. Yeah. What's next? What's the, what's that next flywheel benefit that you guys coming out with >>Composability, fundamentally, if you read the Gartner analysis, right, they, when they talk about composable, they're talking about building pre-built analytics pieces in different business units for, for different purposes. And being able to plug those together. Think of like containers and services that can, that can talk to each other. You have a composition platform that can pull it into a presentation layer. Well, the presentation layer is where I focus. And so the, so for us, composable means I'm gonna have formulas and queries and widgets and charts and everything else that my, that my end users are gonna wanna say almost minority report style. If I'm not dating myself with that, I can put this card here, I can put that chart here. I can set these filters here and I get my own personalized view. But based on all the investments my organization's made in data and governance and quality so that all that infrastructure is supporting me without me worrying much about it. >>Well that's productivity on the user side. Talk about the software angle development. Yeah. Is your low code, no code? Is there coding involved? APIs are certainly the connective tissue. What's the impact to Yeah, the >>Developer. Oh. So if you were working on a traditional legacy BI platform, it's virtually impossible because this is an architectural thing that you have to be able to do. Every single tool that can make a chart has an API to embed that chart somewhere. But that's not the point. You need the life cycle automation to create models, to modify models, to create new dashboards and charts and queries on the fly. And be able to manage the whole life cycle of that. So that in your composable application, when you say, well I want chart and I want it to go here and I want it to do this and I want it to be filtered this way you can interact with the underlying platform. And most importantly, when you want to use big pieces like, Hey, I wanna forecast revenue for the next six months. You don't want it popping down into Python and writing that yourself. >>You wanna be able to say, okay, here's my forecasting algorithm. Here are the inputs, here's the dimensions, and then go and just put it somewhere for me. And so that's what you get withy sense. And there aren't any other analytics platforms that were built to do that. We were built that way because of our architecture. We're an API first product. But more importantly, most of the legacy BI tools are legacy. They're coming from that desktop single user, self-service, BI environment. And it's a small use case for them to go embedding. And so composable is kind of out of reach without a complete rebuild. Right? But with SI senses, because our bread and butter has always been embedding, it's all architected to be API first. It's integrated for software developers with gi, but it also has all those low code and no code capabilities for business users to do the minority report style thing. And it's assemble endless components into a workable digital workspace application. >>Talk about the strategy with aws. You're here at the ecosystem, you're in the ecosystem, you're leading product and they have a strategy. We know their strategy, they have some stuff, but then the ecosystem goes faster and ends up making a better product in most of the cases. If you compare, I know they'll take me to school on that, but I, that's pretty much what we report on. Mongo's doing a great job. They have databases. So you kind of see this balance. How are you guys playing in the ecosystem? What's the, what's the feedback? What's it like? What's going on? >>AWS is actually really our best partner. And the reason why is because AWS has been clear for many, many years. They build componentry, they build services, they build infrastructure, they build Redshift, they build all these different things, but they need, they need vendors to pull it all together into something usable. And fundamentally, that's what Cient does. I mean, we didn't invent sequel, right? We didn't invent jackal or dle. These are not, these are underlying analytics technologies, but we're taking the bricks out of the briefcase. We're assembling it into something that users can actually deploy for their use cases. And so for us, AWS is perfect because they focus on the hard bits. The the underlying technologies we assemble those make them usable for customers. And we get the distribution. And of course AWS loves that. Cause it drives more compute and it drives more, more consumption. >>How much do they pay you to say that >>Keynote, >>That was a wonderful pitch. That's >>Absolutely, we always say, hey, they got a lot of, they got a lot of great goodness in the cloud, but they're not always the best at the solutions and that they're trying to bring out, and you guys are making these solutions for customers. Yeah. That resonates with what they got with Amazon. For >>Example, we, last year we did a, a technology demo with Comprehend where we put comprehend inside of a semantic model and we would compile it and then send it back to Redshift. And it takes comprehend, which is a very cool service, but you kind of gotta be a coder to use it. >>I've been hear a lot of hype about the semantic layer. What is, what is going on with that >>Semantec layer is what connects the actual data, the tables in your database with how they're connected and what they mean so that a user like you or me who's saying I wanna bar chart with revenue over time can just work with revenue and time. And the semantic layer translates between what we did and what the database knows >>About. So it speaks English and then they converts it to data language. It's >>Exactly >>Right. >>Yeah. It's facilitating the exchange of information. And, and I love this. So I like that you actually talked about it in the beginning, the knowledge map and helping people figure out what they might not know. Yeah. I, I am not a bi analyst by trade and I, I don't always know what's possible to know. Yeah. And I think it's really great that you're doing that education piece. I'm sure, especially working with AWS companies, depending on their scale, that's gotta be a big part of it. How much is the community play a role in your product development? >>It's huge because I'll tell you, one of the challenges in embedding is someone who sees an amazing experience in outreach or in seismic. And to say, I want that. And I want it to be exactly the way my product is built, but I don't wanna learn a lot. And so you, what you want do is you want to have a community of people who have already built things who can help lead the way. And our community, we launched a new version of the SES community in early 2022 and we've seen a 450% growth in the c in that community. And we've gone from an average of one response, >>450%. I just wanna put a little exclamation point on that. Yeah, yeah. That's awesome. We, >>We've tripled our organic activity. So now if you post this Tysons community, it used to be, you'd get one response maybe from us, maybe from from a customer. Now it's up to three. And it's continuing to trend up. So we're, it's >>Amazing how much people are willing to help each other. If you just get in the platform, >>Do it. It's great. I mean, business is so >>Competitive. I think it's time for the, it's time. I think it's time. Instagram challenge. The reels on John. So we have a new thing. We're gonna run by you. Okay. We just call it the bumper sticker for reinvent. Instead of calling it the Instagram reels. If we're gonna do an Instagram reel for 30 seconds, what would be your take on what's going on this year at Reinvent? What you guys are doing? What's the most important story that you would share with folks on Instagram? >>You know, I think it's really what, what's been interesting to me is the, the story with Redshift composable, sorry. No, composable, Redshift Serverless. Yeah. One of the things I've been >>Seeing, we know you're thinking about composable a lot. Yes. Right? It's, it's just, it's in there, it's in your mouth. Yeah. >>So the fact that Redshift Serverless is now kind becoming the defacto standard, it changes something for, for my customers. Cuz one of the challenges with Redshift that I've seen in, in production is if as people use it more, you gotta get more boxes. You have to manage that. The fact that serverless is now available, it's, it's the default means it now people are just seeing Redshift as a very fast, very responsive repository. And that plays right into the story I'm telling cuz I'm telling them it's not that hard to put some analysis on top of things. So for me it's, it's a, maybe it's a narrow Instagram reel, but it's an >>Important one. Yeah. And that makes it better for you because you get to embed that. Yeah. And you get access to better data. Faster data. Yeah. Higher quality, relevant, updated. >>Yep. Awesome. As it goes into that 80% of knowledge workers, they have a consumer great expectation of experience. They're expecting that five ms response time. They're not waiting 2, 3, 4, 5, 10 seconds. They're not trained on theola expectations. And so it's, it matters a lot. >>Final question for you. Five years out from now, if things progress the way they're going with more innovation around data, this front end being very usable, semantic layer kicks in, you got the Lambda and you got serverless kind of coming in, helping out along the way. What's the experience gonna look like for a user? What's it in your mind's eye? What's that user look like? What's their experience? >>I, I think it shifts almost every role in a business towards being a quantitative one. Talking about, Hey, this is what I saw. This is my hypothesis and this is what came out of it. So here's what we should do next. I, I'm really excited to see that sort of scientific method move into more functions in the business. Cuz for decades it's been the domain of a few people like me doing strategy, but now I'm seeing it in CSMs, in support people and sales engineers and line engineers. That's gonna be a big shift. Awesome. >>Thank >>You Scott. Thank you so much. This has been a fantastic session. We wish you the best at si sense. John, always pleasure to share the, the stage with you. Thank you to everybody who's attuning in, tell us your thoughts. We're always eager to hear what, what features have got you most excited. And as you know, we will be live here from Las Vegas at reinvent from the show floor 10 to six all week except for Friday. We'll give you Friday off with John Furrier. My name's Savannah Peterson. We're the cube, the the, the leader in high tech coverage.

(upbeat electronic music) >> Announcer: Live from Las Vegas, it's the CUBE. Covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to the Aria in Las Vegas everybody. This is the CUBE, the leader is live tech coverage. And we're here covering Veritas Vision, #VtasVision. I'm Dave Vellante with Stu Miniman. Bill Coleman is here. He's the CEO of Veritas. Bill, thanks for coming on the CUBE, good to see you. >> My pleasure, thank you for hosting us. >> Well, you're very welcome. And so, hot off the keynote, how do you feel, how's the show going for you so far? >> Well, I'll tell you what. I feel verit-awesome! >> (laughs) Verit-awesome is the watchword here. Get the crowd talk of Verit-awesome. I love that you started out with a little retrospective from last year. You used the term digital twin. We love that term, and you said it's sort of grown up now. I like to think the digital twins are sort of in their adolescent or even teenage years. The data is sort of out of control. We're not hearing today a message of legacy backup. We're hearing a vision of the future. Talk about that and what that vision looks like. >> Our customers obviously need data protection. They need resiliency. They need everything they've needed in the past. But that's not what they're interested in. That's assumed, that has to work. What they're interested in is the power of information. We like to say that our mission is to harness the power of information. And it's what's called digital transformation. Being able to use all that data out on the internet with all of their data, to change how they do business. To change what their products are. To change their supply chain. It's all about machine learning, predictive analytics, and the power of information. >> So I started in this business the same year that Veritas was born. And so I saw the ascendancy of Veritas and the many different forms that the company had taken. But I used to use Veritas as an example. You want to be like Veritas, with no hardware agenda. You want to be the glue that brings things together. And I saw in the conversation today a little bit of BEA-like thinking. The binder, if you will. Binding clouds together. My term, you guys didn't use that term, but to us, that's a critical value-add, and it's all around the data. You guys talked about digital business. To us, digital business means data, and it seems like we sort of share that common belief. >> Absolutely. You know, we've called this the information age for 50 years? But it's not been about information, it's been about technology. We finally have the ability to address that information, and do it over the internet, everywhere and everything. That's really what our vision is. You know, at BEA, we saw the internet emerging. And the world had to distribute, and take advantage of all that power across the whole world. And we invented that. But the key was, when I came up with the first concept of BEA in '93, I said, "You know, by the year 2000, "the network is going to be the computer." The network needs an operating system to make it all work. Well the concept here, and the reason that I actually took this job, is looking ahead ten years. Everything's going to be about information. No organization's going to be able to exist without leveraging the power of that information. Because that's the only way they'll bring their customer the value they need. That's the only way they compete, and without it, their business is just going to go down. >> Yeah, Bill, how are customers going to leverage data? You mentioned it's about the information, it's not about the technology. But you know, I look at customers. They've had storage people, they have network people. You know, "Oh, I'm excited about containers." We spent the last 15 years focused on virtualization. Is it Chief Data Officer? Or is it some other structure that customers, how are some of the leading customers that are going to be able to adopt this, how are they changing to be able to leverage that data and information? >> Well first, you have to understand, the technology has been complex, hard to use, hard to manage. As we saw earlier in the keynotes, it's like building a Rube Goldberg device. They had 27 different software products, and 14 different hardware products to sort of work together. Well, that's all disappearing. With cloud and the internet, it's becoming like a utility. You just subscribe to it. So that goes away. Now what you have to do, what we have to do, is we have to give them the tools that they can easily, visually look at that data, determine what's in that data, be maneuvering it, move it around, like in the movie, uh-- >> Stu: Minority Report? >> Minority Report. And literally, the things we talked about today, the demos we showed can lead to that. With machine learning predictive analytics, our biggest customers are already investing billions of dollars to do that. 'Cause they know if they don't jump ahead, their competition's going to do it. It's the power of information. >> So one of the things I might take away today was not only is Veritas hardware agnostic, but in many respects, you're workload agnostic. In other words, what I mean by that is, a lot of the events that Stu and I and the CUBE goes to, the enterprise companies are talking about on prem and that's where their business is, and much of your business, of course, is on prem. But we heard a message today of, "We really don't care where it lives. "We want to be the innovator "to help you get value out of your data "no matter where it lives." Now a lot of people will say that, but you really don't care where it lives. Is that true? >> And we can't. Look at, data's not just in an enterprise's data centers anymore. They're using clouds. We've surveyed our customers. Our average enterprise customer is using three public clouds already. And they have dozens of SASS applications like Salesforce, Workday, ServiceNow. Their data's in there too. That's really complex. What we've done is we've take and build the products that run in the cloud, across the cloud, to and from the cloud all by one policy orchestration. So you don't have to think about any of that. You can discover the data, categorize the data, manage the data and analyze the data all from one interface, end to end. >> So the obvious hard question follow-up is that what give you confidence that the cloud guys, once they get that workload, aren't going to just sort of usurp that agenda? What do you have to do to maintain that customer delight? >> Well, the first thing is the cloud, the public cloud providers, are our very close partners. You know, the first month we started this, Bill Voss, who heads storage for AWS, and I worked with him and Sun, came down to us and said, "Look, our customers need backup." You know, snapshots are great, but if somebody deletes a snapshot, it's gone. Your data's gone. How are you going to protect that? How are you going to analyze that data? When we want to partner with you? So we partnered with them. But the other thing he said was, "And if we do it exclusively, "the enterprises aren't going to use us." I had the CIO of one of the top five banks in the world tell me right after I started this, "We've got to be using three clouds simultaneously. "We never want to be stuck in the cloud." So the cloud service providers know that the enterprise customers want and demand that portability. And we become their, we're the premier partner for Amazon, for Microsoft, for Google, and for IBM. >> So, it's relationships. >> Right. >> But it's also innovation. >> Absolutely. >> So talk about where you are with R & D. You're purchased by a private equity company. You might have heard the narrative beforehand. A lot of the old private equity model is to suck all the cash out. Kind of the new private equity model is to invest, grow the valuation of the company. I think that's where I see you guys going. But talk about how you're able to innovate. Talk about the R & D mojo that you guys have. >> You had several questions there. >> Yeah (laughs). >> But let me start with that, with the last one. When we carved this company out 19 months ago, it became apparent that we weren't a real player in the cloud. We weren't in some of the more modern workloads. And we had to change rapidly. So, we created a strategy that led to this whole 360 data management integrated platform, software-defined storage. Integrating it with a restful API interface. And then in one year, we built seven new products from scratch that operate in the cloud, on prem, or across cloud. Automated that entire thing. We literally took the startup mentality. Now I've been a startup guy most of my life. I spent the last five and a half years before this funding early-stage startups, and the thing is being agile, and moving fast. We can move faster than anyone around now. We're a big company. Let's take Cloudpoint. We just introduced our Cloud Snapshot. That was a thought in somebody's eye in February. We defined what we needed to do, working with our customers. We put together the team. We built a micro-service end to end archistructure, and we shipped it, supporting the major, all the major cloud snapshot capability in five months, end to end. Totally new product. Now that is a startup mentality. >> Yeah, Bill, can you explain to us a little bit some of the internal plumbing of how you've managed that. On the one hand, Veritas, trusted company, strong engineering culture, product like NetBackup, you know. 15 years, leader in it's space, versus brand new stuff, whole new spaces. What staying the same, what's changing? How do you manage some of those transitions? Because you know, typical company, it's like, "We've got 7500 employees." It's like, "Well, I've got revenue streams "and product lines that I know how to do "and can keep chugging, but I've got the new stuff too." So how do you manage that internally? >> I've have a very simple philosophy of what it takes to lead a major company. You got to have a direction to go in, you have to draw higher-grade people, and you have to organize around the first two. But the key is where are you going? Where's the puck going to be in five to 10 years? And I call that the three V's. WHat's the vision of where the market's going to be? And number two, what's the value that brings to customer? The value that will justify their switching costs. And the third is, what are the values that you build your company on, that customers and partners will be able to trust and count on. So, when you start with that, we created the vision. It has to be a compelling and urgent vision. Ten years from now, all of our products are going to be obsolete. They're going to mostly be obsolete in five years. All of our traditional products. It's all going to be a microservice. Change on the fly, customers never have to upgrade kind of environment, right? There's an urgency there. And customers want to transform. There's an urgency there. The key is, based on your values, you have to develop a culture that embodies the norms to execute your strategy. And then you keep those things and balances. The cultural change has been the most profound and the most important thing we've done in this company. And this company now has a startup, win-in-the-marketplace, customer-first culture. >> So you laid out the vision. In terms of the value to customers you said, when you talk to your CIO customers and other customers, three things came out. Cut costs, deal with governance and compliance, and then help us with the digital transformation. Help us become a digital business, essentially. >> Yeah. >> So those two are pretty clear. Talk about the values that you espouse. What are they? >> So, when you start with values have to be built around what you're providing to a customer. And there's sort of three aspects of that. I'm going to give them the best possible products. I'm going to give them the lowers possible price, or I'm going to give them the best possible service that they can count on. I'm asking our customers to bet their future. So it has to be the third. So it starts with, we produce customer value, right? Then the next aspect of it is, they have to believe that what you're doing is going to be there for them, that it's going to really work. So our next one is, we're going to do that by inventing the future, to bring them the customer value. We're not going to look back and try to add features and functions where we are. We need to help them jump ahead to where they need to be. The third part of that, the pyramid there is customers are going to rely on you. So trust, accountability, ethics, integrity. Those three things come together. Then, we're all about employees, right? So, how do you empower employees to succeed, grow, and be accountable. And you put these values together, and the values will never change. The culture will evolve as strategy moves, and keeping in balance means you're going to have to reorganize on a continual basis around where you are in your strategy. I told this company, we're going to be reorganizing continuously, at least once a year. We're about to do a pretty fundamental reorganization in parts of our company. And this is second time in six months. But you have, you know, you have to be an agile organization. >> Bill, the venture community thinks that this is a hot space. There's a whole number of startups, highly focused. Obviously they're smaller than you, don't have the breadth of products. How do you look at the marketplace? What do you say about that aspect? >> Well, as I said, I spent five and a half years in early-stage venture. >> Yeah. >> We had the highest return fund for our first fund of multiple of any venture capital company. I really love that world. Venture capital is the the center of invention, the center of innovation in this country, in the world. You know, back in the 40s, 50s and 60s, you used to have these big corporate labs. You know, Bell Labs, Sarnoff Labs, et cetera. They don't exist anymore. It's all done by these. So they're inventing the future. Now the difference between the pre-dot-com era and after is, the vast majority of startups are, well, the the vast majority have failed. >> Will fail. (laughs) The vast majority of what's left are acquired, and a few go public, right? So to me, number one, they are the laboratory. They are in the areas that we that are merging, and that we don't necessarily have a core competence, we want to look on how to do that. In BEA, in six years, I did 24 acquisitions to build the company. I never acquired anything that came to us. It was all, here's part of our strategy, we need this competency, we need this time to market. How do we make it work, right? Matter of fact, there was a joke. BEA stood for Built Entirely on Acquisitions. (hosts laugh) >> Well, people used to, Larry Elison himself used to denegrate people for writing checks, not code. And then, of course, he changed the software business with (laughs) some big checks. Well, I wonder if you could talk a little bit more about the team. So when you took over here at Veritas, you mentioned off camera, you started with the team. How did you go about that? Maybe describe, add some color to the team. >> You know, like I said, one of the three pillars of my management is hire great people. And if you're going to transform a company, if you're going to do a turnaround, it has to start with the leadership team. Period, you can't start anywhere else. But you have to have a leadership team that shares the vision, shares the drive, knows how to work hard together. And when they walk in that room, there's not one thought about my organization or my career, or my compensation. Because they all know, if we make this work, all the rest can take care of itself. Now, when you're doing these sort of things, there are certain times in certain organizations, that people's skills are optimal. You know, the group that was managing this as part of Semantec, they weren't necessarily the best people to manage it as a change in culture, change in strategy. So I had to go out, and I brought in a couple of folks that I've worked with before. We brought in some real amazing people. Mike Palmer is just unbelievable at all dimensions of product development. Scott Genereux, he knows sales back, forward. He knows every customer out there by name, and he knows how to really motivate a sales force. Well, every member of my leadership team except Todd Hauschildt, the CIO, has come in with the same vision, the same, and of course that works down the organization as you're building. And that's how you change the culture. With that, here's the vision of where we're going. Here's the values, what we are going to do. This is how we're going to lead it. >> So major objectives. Obviously you want to keep moving fast. >> I presume you're going to, >> Yeah. >> You're reorganizing frequently to support that. But what are the main objectives that we should be looking for as outside observers over the next six, nine, 12, 18 months? We are changing the agenda of the information management industry. The first place is, for digital transformation, corporations have to switch. They have to get off what they're doing today ultimately and go to something new. And in an enterprise, that can only be one platform. You can't have two platforms deleting, moving data asynchronously. So, its going to be a major transformation. Now that has to be a platform. We've put the stake in the ground. We have that platform. Now, this is our battle to lose, because the incumbents in a transformation get to win if they're good enough. You know, in the disruption, only a startup can win. That's how I won at BEA, how we won at Sun. But this isn't disruption. Nobody's going to throw away all their data centers and jump into somebody before who said, "Oh, I've managed 100 terabytes. "Give me your 50 pedabytes." (Dave laughs) You know? And no customer is going to trust them. So this is our battle to win. We're changing the entire agenda with 360 data management. What we, our number one challenge is, we have to change the positioning in our own customers' minds, because they know us as the 30 years of that legacy, backup, recovery and archiving company. And it's really working. But that's number one. That's my number one objective. 'Cause the rest will take care of itself. >> And as a private company, do you feel like you're in a more advantageous position to do that, and why? >> Well, I don't think I could do this as other than a private company. Because it changes the economics dramatically. Also, at the same time, we're switching from mostly licensed revenue, to mostly rateable avenues, we move to subscription. In a public company, that's a, "Oh, our revenue's going to go down for awhile, "and so is our profits, but trust me." >> Hang with us. (laughs) >> Yeah, hang with us. There are companies like adobe that did that flawlessly, but it's not an easy thing to do. >> Yeah, it's not easy. >> And I'll tell you, I have the best partner in the world. When I, when we started this whole carveout, and I figured out, "Whoa, we don't have the right products. "We got to build this whole thing." I went to Carlisle with the strategy and the vision of what we needed to do. And I said, "Look, because pricing pressure is so high, "We're not going to be able to grow based on your plan." How you invested. "But if you want me to do that, "I can do it, and you need to invest this much more. "But I recommend that we invest as fast as we can "to get to digital transformation." They chose the third. They chose to, we're spending 99 million more dollars in R & D and go-to-market this year than was in the original plan. I wouldn't be able to do that in the public markets. >> Yeah. >> You know? But they are the perfect partner. They build for growth. They stay in two to four years after an IPO. Their return is based on multiples of growth, and that's what, so our goals are totally aligned, and aligned with what the customers are going to need. >> Bill, great story, I know you're super busy. A lot of customers to meet. So thanks very much for taking time out and joining us on the CUBE. >> Bill: This has been a pleasure. Thank you, >> You're welcome. >> Bill: you got me all stimulated. >> All right, good deal. All right, keep it right there everybody. Stu and I will be back with our next guest. This is the CUBE. We're live from Veritas Vision 2017. We'll be right back. (electronic rhythmic music)

>> Narrator: Live from Boston, Massachusetts, it's the Cube covering OpenStack Summit 2017. Brought to you by the OpenStack foundation, RedHat, and additional ecosystem support. >> Hi. I'm Stu Miniman here with my cohost John Troyer. Happy to welcome to the program to the program, Carlos Carrera, who's a senior principal product manager with Veritas. Carlos, great to see you. >> Yeah, thank you very much. >> Stu: Alright. >> Great to be here. >> So, so many of the things we talk to here in OpenStack and the Cloud World, is relatively short-lived. The average lifetime of the average Cloud deployment, is like 1.7 years. You've been at Veritas at little bit longer with that, had an opportunity to have a conversation with you about some of your history, so we're going to have to take the abbreviated format of that, but give us a little bit about, you know, your time at Veritas, some of the ebbs and flows of your career. >> Yeah, well, again, thank you for having me here. It's great. Having 16 years with Veritas, as I mentioned before to you, you know, back in 1994, 1995 we created the first file system and volume manager, right. A lot of things happened since then, right. At that point in time, the software defined storage store was not yet there. Back, many years ago, we got some piece of software, running on top of any kind of hardware and we were able to help customers to move workloads from one place to another. In a very agnostic point of view, right. And then we move into clouds and now, three years ago, we started looking into what do we do with OpenStack clouds, because this is going to define... It's going to need something very new, something different. So today, this week, we are very happy because we finally announced hyper scale for open stack, which is a software defined storage solution that has been built for an OpenStack clouds. >> When I look at the industry these days, the term lately is storage services. How we're doing things in software more, open stack is the open source infrastructure piece. You guys are the hipster player in this space. You were doing software defined storage and software services not attached to everything else beforehand so it sounds like openstack's a natural fit. Tell us a little bit more about how Veritas fits into that. >> Well, I think that again, it was a perfect fit but we had to review what we was doing. Okay, because again, I've been many years... I was working with traditional legacy architectures in the past. We had to work class defined system that today can work with 128 notes. But we revisit... Is this what we really need to the new OpenStack clouds, are they going to scale? And as you said is that what I need the storage services. So what do we have to rethink? What do we have to do to provide those storage services to the OpenStack clouds? So three years ago, we had this, we call open flame project that today is Hyperscale. It has been building from scratch. New product, what we call emerging product at Veritas, and finally we got separated from Semantec, and we got all the visibility on the storage gain. And using all the knowhow that we have in history, as I say, we're a very big startup, right? But now, emerging with new products, we need new solutions that have been designed for OpenStack from scratch. >> Could you drill down on the product itself? Is this file block object storage? Is this sitting on top of servers. Laid off in a server-based way? How does it interact with OpenStack drivers? That sort of thing. >> Yeah, that's a good question. So it is senior storage. What we provide is block storage for OpenStack. Something key, it is based on commodity hardware of your choice, so you decided what is the hardware that you want to use. Really, it's 86 servers that you can choose in the market, whatever you want. And one of the key differentiators is that we provide block storage, but we separate the compute plane and the data plane. And this is an architectural decision we had to take three years ago. We said we cannot scale, we cannot provide the storage services that you need in a single layer of storage. Because that is what most of the software defined storage solutions on the market are doing today. And then they're having problems with things like noisy neighbor. They have problems with things like the scalability, like the quality of service, and of course they're having problems with protection. How do I protect my cloud environments with OpenStack? And we as a net pack of company, we have our leading net backup solution, we hear that from our customers. That it is not that we're bringing another solution that is going to bring another noisy neighborhood, so we really have to separate two layers. Compute plane, where you have your first copy, and the data plane, where you use cheaper and deeper storage to keep the second, third copy, and do all the data mining operations. >> That's interesting what you just said there too. Two copies, so you do have a copy that's close to the compute. But then you have another. >> Correct. Because, again, if you take a look to what you have in the market, typically it's one-size-fits-all. So, do you need three copies for everything? And today, you have emerging technologies. You can have things like mySQL, where you need high performance, or you can have things like Cassandra where you need nine copies of them, because the application itself is giving you the resiliency. So if you use a standard solution that for each OpenStack instance, you have three copies, that means you have three copies, three copies, three copies. So nine copies. And it's not only the number of copies. It's that when you make a write, you're writing nine times. And you're writing on the single layer. So we said, we have to separate that. The first thing is that what is the workload? Stop thinking about the storage. Stop thinking this is a pool of SSDs or a pool of HCDs, and then start thinking about the workload. And then we connected that very well with OpenStack because OpenStack, you have the definition of flavors, right? That is how many CPUs do you need? How much memory? But also we extend those flavors to say what do you need in terms of storage? What is the resiliency level that you need? What is the number of copies? What is the minimum performance that you need? What is the maximum performance? It's not only about solving the noisy neighbor with the maximum performance? About limiting, it's about guaranteeing that you are going to have a minimum number of IOs per second. At the end, what you can get, you can have a mySQL running with high performance needs with web servers of the same box without fighting each other. >> Carlos, can you speak a little bit about how customers consume this, how do they buy it, how's it priced? How do you get it to market? We've taught before with Veritas. Storage used to always be in an appliance or an array or things like that and the software cloud world's a little bit differently. How does that fit? >> So today's software only? So you make that decision about what hardware to use. We try to simplify the go to market model. So it's based on subscription. You just pay for the max capacity that you have. And you only pay for what you have at the compute plane. So I think a simple model that we could find to go in the open source projects, and being able to attach to that. >> Okay, could you speak to... When you talk about go to market from a partnership standpoint, it's a big market out there. Veritas, well-known name for many years but what partners are involved in this? Any certifications that are needed? We're working with our typical partners that have some expertise with OpenStack and helping with them. We are now also working with hardware providers. We are working with Supermicro and creating reference architectures with them. So we can have at the end, we have to explain to the customers what they can get from different hardware. So we're working with them. And we're also working with new partners. For example, yesterday with us on the stage, we have Verbanks. Verbanks is an OpenStack ambassador in Netherlands. They have been working with us from the very beginning of the project, on the validation. They understand OpenStack. They understand the issues and they have been doing all the validation with us about, yes guys, this is the right thing. You have to do it from the very beginning. Is this product tuned specifically for OpenStack or will it be available for other kind of private cloud applications. >> We have available for OpenStack, we're going to have it. We'll announce, I think we'll watch with you also, guys, we announced the beta version for Containers. At the end, it's the same thing. It's how do you provide persistent storage for Containers? Ninety percent of the product is all the same. It's that compute plane. It's the data plane. How can I protect my workload from the data plane? Because again, it doesn't matter if it's Container. If it's OpenStack, when I have to protect it, how do I do it? How can I read my data without affecting the performance? And that's where we have the value with the data plane. And, of course, our integration with net backup, our leader of backup solutions in the market, where just with a single click, I'm going to connect OpenStack with NetBackup, and define how my workloads are going to be protected, when and how? >> Here at the show, OpenStack Summit, how has it been working with the community? Sometimes, in the open source world, vendors have to have a certain kind of conversation with that open source community to show that they understand their needs and what they need out of the relationship. How has the week been then? >> So yeah, that's a very good question. And that goes to something that we want to announce hopefully at the end of the year. The first version that we announced this week is based on canonical Ubuntu OpenStack. At the end of the year, we are going to have RedHat, and in our DNA is to be agnostic to the pass, any hardware. And of course now, it's any kind of OpenStack distribution. So we will work with any of them. And something that we want to announce at the end of the year is to have a community edition, for Hyperscale. So again, that is our offering to the community. They can both provide-- >> And would that community edition itself be open source, or just available for the community? >> It would be available for that. >> John: For the community. >> We keep our IP. >> Great. As we get towards the end of the event, I'm sure you've had plenty of interesting customer conversations. Any one, I'm sure you can't mention names, but any interesting anecdote or just a general feel of the community? >> I feel that my anecdote for yesterday, when I had to work presentation, we had a customer on the room. We had been working on a POC with them. We have been very, very helpful customer. We finished. "Do you have any questions?" This guys stands up, went to the microphone and I was thinking, what is he going to ask? He knows everything about the product. And he said, he guys, you are doing the right thing. This is great. I'm fantastic, you are bringing a lot of value here. So I was like, wow. >> In my understanding, it was a big brand name customer who actually said where he was from, which is great validation, something we've heard all week is there's that sharing here with the community, so financial companies who, in the past, wouldn't have done that, TelCos who do that in the past, great to see. Give me the final word, Carlos. >> Yeah, the thing, again, is as you said validation is a key thing. I've been a lot of years in the company. I got this project eight months ago, and all the things I've been doing is validation, talking to customers to I don't know how many analysts I've been talking to in this week. And I love Dan said, yeah, you guys are doing the right thing. This is that direction that we have to move, so happy that finally, emerging again from Veritas, being back here with the community on OpenStack. >> Well, the speed of change, constant learning on new things and helping customers move forward. Big theme we've seen in the show. Carlos Carrera. I appreciate you joining us here. For John and Stu, thanks for watching The Cube here at OpenStack Summit. (mid-tempo electronic music)