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Breaking Analysis: CIOs in a holding pattern but ready to strike at monetization


 

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Recent conversations with IT decision makers show a stark contrast between exiting 2023 versus the mindset when we were leaving 2022. CIOs are generally funding new initiatives by pushing off or cutting lower priority items, while security efforts are still being funded. Those that enable business initiatives that generate revenue or taking priority over cleaning up legacy technical debt. The bottom line is, for the moment, at least, the mindset is not cut everything, rather, it's put a pause on cleaning up legacy hairballs and fund monetization. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we tap recent discussions from two primary sources, year-end ETR roundtables with IT decision makers, and CUBE conversations with data, cloud, and IT architecture practitioners. The sources of data for this breaking analysis come from the following areas. Eric Bradley's recent ETR year end panel featured a financial services DevOps and SRE manager, a CSO in a large hospitality firm, a director of IT for a big tech company, the head of IT infrastructure for a financial firm, and a CTO for global travel enterprise, and for our upcoming Supercloud2 conference on January 17th, which you can register free by the way, at supercloud.world, we've had CUBE conversations with data and cloud practitioners, specifically, heads of data in retail and financial services, a cloud architect and a biotech firm, the director of cloud and data at a large media firm, and the director of engineering at a financial services company. Now we've curated commentary from these sources and now we share them with you today as anecdotal evidence supporting what we've been reporting on in the marketplace for these last couple of quarters. On this program, we've likened the economy to the slingshot effect when you're driving, when you're cruising along at full speed on the highway, and suddenly you see red brake lights up ahead, so, you tap your own brakes and then you speed up again, and traffic is moving along at full speed, so, you think nothing of it, and then, all of a sudden, the same thing happens. You slow down to a crawl and you start wondering, "What the heck is happening?" And you become a lot more cautious about the rate of acceleration when you start moving again. Well, that's the trend in IT spend right now. Back in June, we reported that despite the macro headwinds, CIOs were still expecting 6% to 7% spending growth for 2022. Now that was down from 8%, which we reported at the beginning of 2022. That was before Ukraine, and Fed tightening, but given those two factors, you know that that seemed pretty robust, but throughout the fall, we began reporting consistently declining expectations where CIOs are now saying Q4 will come in at around 3% growth relative to last year, and they're expecting, or should we say hoping that it pops back up in 2023 to 4% to 5%. The recent ETR panelists, when they heard this, are saying based on their businesses and discussions with their peers, they could see low single digit growth for 2023, so, 1%, 2%, 3%, so, this sort of slingshotting, or sometimes we call it a seesaw economy, has caught everyone off guard. Amazon is a good example of this, and there are others, but Amazon entered the pandemic with around 800,000 employees. It doubled that workforce during the pandemic. Now, right before Thanksgiving in 2022, Amazon announced that it was laying off 10,000 employees, and, Jassy, the CEO of Amazon, just last week announced that number is now going to grow to 18,000. Now look, this is a rounding error at Amazon from a headcount standpoint and their headcount remains far above 2019 levels. Its stock price, however, does not and it's back down to 2019 levels. The point is that visibility is very poor right now and it's reflected in that uncertainty. We've seen a lot of layoffs, obviously, the stock market's choppy, et cetera. Now importantly, not everything is on hold, and this downturn is different from previous tech pullbacks in that the speed at which new initiatives can be rolled out is much greater thanks to the cloud, and if you can show a fast return, you're going to get funding. Organizations are pausing on the cleanup of technical debt, unless it's driving fast business value. They're holding off on modernization projects. Those business enablement initiatives are still getting funded. CIOs are finding the money by consolidating redundant vendors, and they're stealing from other pockets of budget, so, it's not surprising that cybersecurity remains the number one technology priority in 2023. We've been reporting that for quite some time now. It's specifically cloud, cloud native security container and API security. That's where all the action is, because there's still holes to plug from that forced march to digital that occurred during COVID. Cloud migration, kind of showing here on number two on this chart, still a high priority, while optimizing cloud spend is definitely a strategy that organizations are taking to cut costs. It's behind consolidating redundant vendors by a long shot. There's very little evidence that cloud repatriation, i.e., moving workloads back on prem is a major cost cutting trend. The data just doesn't show it. What is a trend is getting more real time with analytics, so, companies can do faster and more accurate customer targeting, and they're really prioritizing that, obviously, in this down economy. Real time, we sometimes lose it, what's real time? Real time, we sometimes define as before you lose the customer. Now in the hiring front, customers tell us they're still having a hard time finding qualified site reliability engineers, SREs, Kubernetes expertise, and deep analytics pros. These job markets remain very tight. Let's stay with security for just a moment. We said many times that, prior to COVID, zero trust was this undefined buzzword, and the joke, of course, is, if you ask three people, "What is zero trust?" You're going to get three different answers, but the truth is that virtually every security company that was resisting taking a position on zero trust in an attempt to avoid... They didn't want to get caught up in the buzzword vortex, but they're now really being forced to go there by CISOs, so, there are some good quotes here on cyber that we want to share that came out of the recent conversations that we cited up front. The first one, "Zero trust is the highest ROI, because it enables business transformation." In other words, if I can have good security, I can move fast, it's not a blocker anymore. Second quote here, "ZTA," zero trust architecture, "Is more than securing the perimeter. It encompasses strong authentication and multiple identity layers. It requires taking a software approach to security instead of a hardware focus." The next one, "I'd love to have a security data lake that I could apply to asset management, vulnerability management, incident management, incident response, and all aspects for my security team. I see huge promise in that space," and the last one, I see NLP, natural language processing, as the foundation for email security, so, instead of searching for IP addresses, you can now read emails at light speed and identify phishing threats, so, look at, this is a small snapshot of the mindset around security, but I'll add, when you talk to the likes of CrowdStrike, and Zscaler, and Okta, and Palo Alto Networks, and many other security firms, they're listening to these narratives around zero trust. I'm confident they're working hard on skating to this puck, if you will. A good example is this idea of a security data lake and using analytics to improve security. We're hearing a lot about that. We're hearing architectures, there's acquisitions in that regard, and so, that's becoming real, and there are many other examples, because data is at the heart of digital business. This is the next area that we want to talk about. It's obvious that data, as a topic, gets a lot of mind share amongst practitioners, but getting data right is still really hard. It's a challenge for most organizations to get ROI and expected return out of data. Most companies still put data at the periphery of their businesses. It's not at the core. Data lives within silos or different business units, different clouds, it's on-prem, and increasingly it's at the edge, and it seems like the problem is getting worse before it gets better, so, here are some instructive comments from our recent conversations. The first one, "We're publishing events onto Kafka, having those events be processed by Dataproc." Dataproc is a Google managed service to run Hadoop, and Spark, and Flank, and Presto, and a bunch of other open source tools. We're putting them into the appropriate storage models within Google, and then normalize the data into BigQuery, and only then can you take advantage of tools like ThoughtSpot, so, here's a company like ThoughtSpot, and they're all about simplifying data, democratizing data, but to get there, you have to go through some pretty complex processes, so, this is a good example. All right, another comment. "In order to use Google's AI tools, we have to put the data into BigQuery. They haven't integrated in the way AWS and Snowflake have with SageMaker. Moving the data is too expensive, time consuming, and risky," so, I'll just say this, sharing data is a killer super cloud use case, and firms like Snowflake are on top of it, but it's still not pretty across clouds, and Google's posture seems to be, "We're going to let our database product competitiveness drive the strategy first, and the ecosystem is going to take a backseat." Now, in a way, I get it, owning the database is critical, and Google doesn't want to capitulate on that front. Look, BigQuery is really good and competitive, but you can't help but roll your eyes when a CEO stands up, and look, I'm not calling out Thomas Kurian, every CEO does this, and talks about how important their customers are, and they'll do whatever is right by the customer, so, look, I'm telling you, I'm rolling my eyes on that. Now let me also comment, AWS has figured this out. They're killing it in database. If you take Redshift for example, it's still growing, as is Aurora, really fast growing services and other data stores, but AWS realizes it can make more money in the long-term partnering with the Snowflakes and Databricks of the world, and other ecosystem vendors versus sub optimizing their relationships with partners and customers in order to sell more of their own homegrown tools. I get it. It's hard not to feature your own product. IBM chose OS/2 over Windows, and tried for years to popularize it. It failed. Lotus, go back way back to Lotus 1, 2, and 3, they refused to run on Windows when it first came out. They were running on DEC VAX. Many of you young people in the United States have never even heard of DEC VAX. IBM wanted to run every everything only in its cloud, the same with Oracle, originally. VMware, as you might recall, tried to build its own cloud, but, eventually, when the market speaks and reveals what seems to be obvious to analysts, years before, the vendors come around, they face reality, and they stop wasting money, fighting a losing battle. "The trend is your friend," as the saying goes. All right, last pull quote on data, "The hardest part is transformations, moving traditional Informatica, Teradata, or Oracle infrastructure to something more modern and real time, and that's why people still run apps in COBOL. In IT, we rarely get rid of stuff, rather we add on another coat of paint until the wood rots out or the roof is going to cave in. All right, the last key finding we want to highlight is going to bring us back to the cloud repatriation myth. Followers of this program know it's a real sore spot with us. We've heard the stories about repatriation, we've read the thoughtful articles from VCs on the subject, we've been whispered to by vendors that you should investigate this trend. It's really happening, but the data simply doesn't support it. Here's the question that was posed to these practitioners. If you had unlimited budget and the economy miraculously flipped, what initiatives would you tackle first? Where would you really lean into? The first answer, "I'd rip out legacy on-prem infrastructure and move to the cloud even faster," so, the thing here is, look, maybe renting infrastructure is more expensive than owning, maybe, but if I can optimize my rental with better utilization, turn off compute, use things like serverless, get on a steeper and higher performance over time, and lower cost Silicon curve with things like Graviton, tap best of breed tools in AI, and other areas that make my business more competitive. Move faster, fail faster, experiment more quickly, and cheaply, what's that worth? Even the most hard-o CFOs understand the business benefits far outweigh the possible added cost per gigabyte, and, again, I stress "possible." Okay, other interesting comments from practitioners. "I'd hire 50 more data engineers and accelerate our real-time data capabilities to better target customers." Real-time is becoming a thing. AI is being injected into data and apps to make faster decisions, perhaps, with less or even no human involvement. That's on the rise. Next quote, "I'd like to focus on resolving the concerns around cloud data compliance," so, again, despite the risks of data being spread out in different clouds, organizations realize cloud is a given, and they want to find ways to make it work better, not move away from it. The same thing in the next one, "I would automate the data analytics pipeline and focus on a safer way to share data across the states without moving it," and, finally, "The way I'm addressing complexity is to standardize on a single cloud." MonoCloud is actually a thing. We're hearing this more and more. Yes, my company has multiple clouds, but in my group, we've standardized on a single cloud to simplify things, and this is a somewhat dangerous trend, because it's creating even more silos and it's an opportunity that needs to be addressed, and that's why we've been talking so much about supercloud is a cross-cloud, unifying, architectural framework, or, perhaps, it's a platform. In fact, that's a question that we will be exploring later this month at Supercloud2 live from our Palo Alto Studios. Is supercloud an architecture or is it a platform? And in this program, we're featuring technologists, analysts, practitioners to explore the intersection between data and cloud and the future of cloud computing, so, you don't want to miss this opportunity. Go to supercloud.world. You can register for free and participate in the event directly. All right, thanks for listening. That's a wrap. I'd like to thank Alex Myerson, who's on production and manages our podcast, Ken Schiffman as well, Kristen Martin and Cheryl Knight, they helped get the word out on social media, and in our newsletters, and Rob Hof is our editor-in-chief over at siliconangle.com. He does some great editing. Thank you, all. Remember, all these episodes are available as podcasts wherever you listen. All you've got to do is search "breaking analysis podcasts." I publish each week on wikibon.com and siliconangle.com where you can email me directly at david.vellante@siliconangle.com or DM me, @Dante, or comment on our LinkedIn posts. By all means, check out etr.ai. They get the best survey data in the enterprise tech business. We'll be doing our annual predictions post in a few weeks, once the data comes out from the January survey. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, everybody, and we'll see you next time on "Breaking Analysis." (upbeat music)

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Scott Castle, Sisense | AWS re:Invent 2022


 

>>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.

Published Date : Nov 29 2022

SUMMARY :

We are live from the show floor here in Las Vegas, Nevada. Big discussion of data in the keynote bulk of the time was We all want the How's the show for you going so far? the excitement and the activity around how we can do so much more with data, I think you have the coolest last name of anyone we've had on the show so far, queries and the analysis that you can power off of Aurora and Redshift and everything else and How do you see Siente playing a role in the evolution there of we're in a different generation And the way things worked back then is if you ran a business and you wanted to get insights about that business, the tools to get to those insights needed to serve both business users like you and me the muck that goes on with aligning the data. And you don't wanna be waiting to dig through a lot of infrastructure to find it. What's the alternative? and data analysts to do the work for you and you hire enough that your business users can ask questions And how does this relate to embedded? Maybe it's just a query result that influences the ordering of a list. And SI started the infusion term And that's the whole point of infusion. That's gonna be more of the integration piece. And being able to plug those together. What's the impact to Yeah, the And most importantly, when you want to use big pieces like, Hey, I wanna forecast revenue for And so that's what you get withy sense. How are you guys playing in the ecosystem? And the reason why is because AWS has been clear for That was a wonderful pitch. the solutions and that they're trying to bring out, and you guys are making these solutions for customers. 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. And the semantic layer translates between It's So I like that you actually talked about it in And I want it to be exactly the way my product is built, but I don't wanna I just wanna put a little exclamation point on that. And it's continuing to trend up. If you just get in the platform, I mean, business is so What's the most important story that you would share with One of the things I've been Seeing, we know you're thinking about composable a lot. right into the story I'm telling cuz I'm telling them it's not that hard to put some analysis on top And you get access to better data. And so it's, it matters a lot. What's the experience gonna look like for a user? see that sort of scientific method move into more functions in the business. And as you know, we will be live here from Las Vegas at reinvent from the show floor

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Breaking Analysis: What to Expect in Cloud 2022 & Beyond


 

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante you know we've often said that the next 10 years in cloud computing won't be like the last ten cloud has firmly planted its footprint on the other side of the chasm with the momentum of the entire multi-trillion dollar tech business behind it both sellers and buyers are leaning in by adopting cloud technologies and many are building their own value layers on top of cloud in the coming years we expect innovation will continue to coalesce around the three big u.s clouds plus alibaba in apac with the ecosystem building value on top of the hardware saw tooling provided by the hyperscalers now importantly we don't see this as a race to the bottom rather our expectation is that the large public cloud players will continue to take cost out of their platforms through innovation automation and integration while other cloud providers and the ecosystem including traditional companies that buy it mine opportunities in their respective markets as matt baker of dell is fond of saying this is not a zero sum game welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll update you on our latest projections in the cloud market we'll share some new etr survey data with some surprising nuggets and drill into this the important cloud database landscape first we want to take a look at what people are talking about in cloud and what's been in the recent news with the exception of alibaba all the large cloud players have reported earnings google continues to focus on growth at the expense of its profitability google reported that it's cloud business which includes applications like google workspace grew 45 percent to five and a half billion dollars but it had an operating loss of 890 billion now since thomas curion joined google to run its cloud business google has increased head count in its cloud business from 25 000 25 000 people now it's up to 40 000 in an effort to catch up to the two leaders but playing catch up is expensive now to put this into perspective let's go back to aws's revenue in q1 2018 when the company did 5.4 billion so almost exactly the same size as google's current total cloud business and aws is growing faster at the time at 49 don't forget google includes in its cloud numbers a big chunk of high margin software aws at the time had an operating profit of 1.4 billion that quarter around 26 of its revenues so it was a highly profitable business about as profitable as cisco's overall business which again is a great business this is what happens when you're number three and didn't get your head out of your ads fast enough now in fairness google still gets high marks on the quality of its technology according to corey quinn of the duck bill group amazon and google cloud are what he called neck and neck with regard to reliability with microsoft azure trailing because of significant disruptions in the past these comments were made last week in a bloomberg article despite some recent high-profile outages on aws not surprisingly a microsoft spokesperson said that the company's cloud offers industry-leading reliability and that gives customers payment credits after some outages thank you turning to microsoft and cloud news microsoft's overall cloud business surpassed 22 billion in the december quarter up 32 percent year on year like google microsoft includes application software and sas offerings in its cloud numbers and gives little nuggets of guidance on its azure infrastructure as a service business by the way we estimate that azure comprises about 45 percent of microsoft's overall cloud business which we think hit a 40 billion run rate last quarter microsoft guided in its earning call that recent declines in the azure growth rates will reverse in q1 and that implies sequential growth for azure and finally it was announced that the ftc not the doj will review microsoft's announced 75 billion acquisition of activision blizzard it appears ftc chair lena khan wants to take this one on herself she of course has been very outspoken about the power of big tech companies and in recent a recent cnbc interview suggested that the u.s government's actions were a meaningful contributor back then to curbing microsoft's power in the 90s i personally found that dubious just ask netscape wordperfect novell lotus and spc the maker of harvard presentation graphics how effective the government was in curbing microsoft power generally my take is that the u s government has had a dismal record regulating tech companies most notably ibm and microsoft and it was market forces company hubris complacency and self-inflicted wounds not government intervention these were far more effective than the government now of course if companies are breaking the law they should be punished but the u.s government hasn't been very productive in its actions and the unintended consequences of regulation could be detrimental to the u.s competitiveness in the race with china but i digress lastly in the news amazon announced earnings thursday and the company's value increased by 191 billion dollars on friday that's a record valuation gain for u.s stocks aws amazon's profit engine grew 40 percent year on year for the quarter it closed the year at 62 billion dollars in revenue and at a 71 billion dollar revenue run rate aws is now larger than ibm which without kindrel is at a 67 billion dollar run rate just for context ibm's revenue in 2011 was 107 billion dollars now there's a conversation going on in the media and social that in order to continue this growth and compete with microsoft that aws has to get into the sas business and offer applications we don't think that's the right strategy for amp from for amazon in the near future rather we see them enabling developers to compete in that business finally amazon disclosed that 48 of its top 50 customers are using graviton 2 instances why is this important because aws is well ahead of the competition in custom silicon chips is and is on a price performance curve that is far better than alternatives especially those based on x86 this is one of the reasons why we think this business is not a race to the bottom aws is being followed by google microsoft and alibaba in terms of developing custom silicon and will continue to drive down their internal cost structures and deliver price performance equal to or better than the historical moore's law curves so that's the recent news for the big u.s cloud providers let's now take a look at how the year ended for the big four hyperscalers and look ahead to next year here's a table we've shown this view before it shows the revenue estimates for worldwide is and paths generated by aws microsoft alibaba and google now remember amazon and alibaba they share clean eye ass figures whereas microsoft and alphabet only give us these nuggets that we have to interpret and we correlate those tidbits with other data that we gather we're one of the few outlets that actually attempts to make these apples to apples comparisons there's a company called synergy research there's another firm that does this but i really can't map to their numbers their gcp figures look far too high and azure appears somewhat overestimated and they do include other stuff like hosted private cloud services but it's another data point that you can use okay back to the table we've slightly adjusted our gcp figures down based on interpreting some of alphabet's statements and other survey data only alibaba has yet to announce earnings so we'll stick to a 2021 market size of about 120 billion dollars that's a 41 growth rate relative to 2020 and we expect that figure to increase by 38 percent to 166 billion in 2022 now we'll discuss this a bit later but these four companies have created an opportunity for the ecosystem to build what we're calling super clouds on top of this infrastructure and we're seeing it happen it was increasingly obvious at aws re invent last year and we feel it will pick up momentum in the coming months and years a little bit more on that later now here's a graphical view of the quarterly revenue shares for these four companies notice that aws has reversed its share erosion and is trending up slightly aws has accelerated its growth rate four quarters in a row now it accounted for 52 percent of the big four hyperscaler revenue last year and that figure was nearly 54 in the fourth quarter azure finished the year with 32 percent of the hyper scale revenue in 2021 which dropped to 30 percent in q4 and you can see gcp and alibaba they're neck and neck fighting for the bronze medal by the way in our recent 2022 predictions post we said google cloud platform would surpass alibaba this year but given the recent trimming of our numbers google's got some work to do for that prediction to be correct okay just to put a bow on the wikibon market data let's look at the quarterly growth rates and you'll see the compression trends there this data tracks quarterly revenue growth rates back to 20 q1 2019 and you can see the steady downward trajectory and the reversal that aws experienced in q1 of last year now remember microsoft guided for sequential growth and azure so that orange line should trend back up and given gcp's much smaller and big go to market investments that we talked about we'd like to see an acceleration there as well the thing about aws is just remarkable that it's able to accelerate growth at a 71 billion run rate business and alibaba you know is a bit more opaque and likely still reeling from the crackdown of the chinese government we're admittedly not as close to the china market but we'll continue to watch from afar as that steep decline in growth rate is somewhat of a concern okay let's get into the survey data from etr and to do so we're going to take some time series views on some of the select cloud platforms that are showing spending momentum in the etr data set you know etr uses a metric we talked about this a lot called net score to measure that spending velocity of products and services netscore basically asks customers are you spending more less or the same on a platform and a vendor and then it subtracts the lesses from the moors and that yields a net score this chart shows net score for five cloud platforms going back to january 2020. note in the table that the table we've inserted inside that chart shows the net score and shared n the latter metric indicates the number of mentions in the data set and all the platforms we've listed here show strong presence in the survey that red dotted line at 40 percent that indicates spending is at an elevated level and you can see azure and aws and vmware cloud on aws as well as gcp are all nicely elevated and bounding off their october figures indicating continued cloud momentum overall but the big surprise in these figures is the steady climb and the steep bounce up from oracle which came in just under the 40 mark now one quarter is not necessarily a trend but going back to january 2020 the oracle peaks keep getting higher and higher so we definitely want to keep watching this now here's a look at some of the other cloud platforms in the etr survey the chart here shows the same time series and we've now brought in some of the big hybrid players notably vmware cloud which is vcf and other on-prem solutions red hat openstack which as we've reported in the past is still popular in telcos who want to build their own cloud we're also starting to see hpe with green lake and dell with apex show up more and ibm which years ago acquired soft layer which was really essentially a bare metal hosting company and over the years ibm cobbled together its own public cloud ibm is now racing after hybrid cloud using red hat openshift as the linchpin to that strategy now what this data tells us first of all these platforms they don't have the same presence in the data set as do the previous players vmware is the one possible exception but other than vmware these players don't have the spending velocity shown in the previous chart and most are below the red line hpe and dell are interesting and notable in that they're transitioning their early private cloud businesses to dell gr sorry hpe green lake and dell apex respectively and finally after years of kind of staring at their respective navels in in cloud and milking their legacy on-prem models they're finally building out cloud-like infrastructure for their customers they're leaning into cloud and marketing it in a more sensible and attractive fashion for customers so we would expect these figures are going to bounce around for a little while for those two as they settle into a groove and we'll watch that closely now ibm is in the process of a complete do-over arvin krishna inherited three generations of leadership with a professional services mindset now in the post gerschner gerstner era both sam palmisano and ginny rometty held on far too long to ibm's service heritage and protected the past from the future they missed the cloud opportunity and they forced the acquisition of red hat to position the company for the hybrid cloud remedy tried to shrink to grow but never got there krishna is moving faster and with the kindred spin is promising mid-single-digit growth which would be a welcome change ibm is a lot of work to do and we would expect its net score figures as well to bounce around as customers transition to the future all right let's take a look at all these different players in context these are all the clouds that we just talked about in a two-dimensional view the vertical axis is net score or spending momentum and the horizontal axis is market share or presence or pervasiveness in the data set a couple of call-outs that we'd like to make here first the data confirms what we've been saying what everybody's been saying aws and microsoft stand alone with a huge presence many tens of billions of dollars in revenue yet they are both well above the 40 line and show spending momentum and they're well ahead of gcp on both dimensions second vmware while much smaller is showing legitimate momentum which correlates to its public statements alibaba the alibaba in this survey really doesn't have enough sample to make hardcore conclusions um you can see hpe and dell and ibm you know similarly they got a little bit more presence in the data set but they clearly have some work to do what you're seeing there is their transitioning their legacy install bases oracle's the big surprise look what oracle was in the january survey and how they've shot up recently now we'll see if this this holds up let's posit some possibilities as to why it really starts with the fact that oracle is the king of mission critical apps now if you haven't seen video on twitter you have to check it out it's it's hilarious we're not going to run the video here but the link will be in our post but i'll give you the short version some really creative person they overlaid a data migration narrative on top of this one tooth guy who speaks in spanish gibberish but the setup is he's a pm he's a he's a a project manager at a bank and aws came into the bank this of course all hypothetical and said we can move all your apps to the cloud in 12 months and the guy says but wait we're running mission critical apps on exadata and aws says there's nothing special about exadata and he starts howling and slapping his knee and laughing and giggling and talking about the 23 year old senior engineer who says we're going to do this with microservices and he could tell he was he was 23 because he was wearing expensive sneakers and what a nightmare they encountered migrating their environment very very very funny video and anyone who's ever gone through a major migration of mission critical systems this is gonna hit home it's funny not funny the point is it's really painful to move off of oracle and oracle for all its haters and its faults is really the best environment for mission critical systems and customers know it so what's happening is oracle's building out the best cloud for oracle database and it has a lot of really profitable customers running on-prem that the company is migrating to oracle cloud infrastructure oci it's a safer bet than ripping it and putting it into somebody else's cloud that doesn't have all the specialized hardware and oracle knowledge because you can get the same integrated exadata hardware and software to run your database in the oracle cloud it's frankly an easier and much more logical migration path for a lot of customers and that's possibly what's happening here not to mention oracle jacks up the license price nearly doubles the license price if you run on other clouds so not only is oracle investing to optimize its cloud infrastructure it spends money on r d we've always talked about that really focused on mission critical applications but it's making it more cost effective by penalizing customers that run oracle elsewhere so this possibly explains why when the gartner magic quadrant for cloud databases comes out it's got oracle so well positioned you can see it there for yourself oracle's position is right there with aws and microsoft and ahead of google on the right-hand side is gartner's critical capabilities ratings for dbms and oracle leads in virtually all of the categories gartner track this is for operational dvms so it's kind of a narrow view it's like the red stack sweet spot now this graph it shows traditional transactions but gartner has oracle ahead of all vendors in stream processing operational intelligence real-time augmented transactions now you know gartner they're like old name framers and i say that lovingly so maybe they're a bit biased and they might be missing some of the emerging opportunities that for example like snowflake is pioneering but it's hard to deny that oracle for its business is making the right moves in cloud by optimizing for the red stack there's little question in our view when it comes to mission critical we think gartner's analysis is correct however there's this other really exciting landscape emerging in cloud data and we don't want it to be a blind spot snowflake calls it the data cloud jamactagani calls it data mesh others are using the term data fabric databricks calls it data lake house so so does oracle by the way and look the terminology is going to evolve and most of the action action that's happening is in the cloud quite frankly and this chart shows a select group of database and data warehouse companies and we've filtered the data for aws azure and gcp customers accounts so how are these accounts or companies that were showing how these vendors were showing doing in aws azure and gcp accounts and to make the cut you had to have a minimum of 50 mentions in the etr survey so unfortunately data bricks didn't make it just not enough presence in the data set quite quite yet but just to give you a sense snowflake is represented in this cut with 131 accounts aws 240 google 108 microsoft 407 huge [ __ ] 117 cloudera 52 just made the cut ibm 92 and oracle 208. again these are shared accounts filtered by customers running aws azure or gcp the chart shows a net score lime green is new ads forest green is spending more gray is flat spending the pink is spending less and the bright red is defection again you subtract the red from the green and you get net score and you can see that snowflake as we reported last week is tops in the data set with a net score in the 80s and virtually no red and even by the way single digit flat spend aws google and microsoft are all prominent in the data set as is [ __ ] and snowflake as i just mentioned and they're all elevated over the 40 mark cloudera yeah what can we say once they were a high flyer they're really not in the news anymore with anything compelling other than they just you know took the company private so maybe they can re-emerge at some point with a stronger story i hope so because as you can see they actually have some new additions and spending momentum in the green just a lot of customers holding steady and a bit too much red but they're in the positive territory at least with uh plus 17 percent unlike ibm and oracle and this is the flip side of the coin ibm they're knee-deep really chest deep in the middle of a major transformation we've said before arvind krishna's strategy and vision is at least achievable prune the portfolio i.e spin out kindrel sell watson health hold serve with the mainframe and deal with those product cycles shift the mix to software and use red hat to win the day in hybrid red hat is working for ibm's growing well into the double digits unfortunately it's not showing up in this chart with little database momentum in aws azure and gcp accounts zero new ads not enough acceleration and spending a big gray middle in nearly a quarter of the base in the red ibm's data and ai business only grew three percent this last quarter and the word database wasn't even mentioned once on ibm's earnings call this has to be a concern as you can see how important database is to aws microsoft google and the momentum it's giving companies like snowflake and [ __ ] and others which brings us to oracle with a net score of minus 12. so how do you square the momentum in oracle cloud spending and the strong ratings and databases from gartner with this picture good question and i would say the following first look at the profile people aren't adding oracle new a large portion of the base 25 is reducing spend by 6 or worse and there's a decent percentage of the base migrating off oracle with a big fat middle that's flat and this accounts for the poor net score overall but what etr doesn't track is how much is being spent rather it's an account based model and oracle is heavily weighted toward big spenders running mission critical applications and databases oracle's non-gaap operating margins are comparable to ibm's gross margins on a percentage basis so a very profitable company with a big license and maintenance in stall basin oracle has focused its r d investments into cloud erp database automation they've got vertical sas and they've got this integrated hardware and software story and this drives differentiation for the company but as you can see in this chart it has a legacy install base that is constantly trying to minimize its license costs okay here's a little bit of different view on the same data we expand the picture with the two dimensions of net score on the y-axis and market share or pervasiveness on the horizontal axis and the table insert is how the data gets plotted y and x respectively not much to add here other than to say the picture continues to look strong for those companies above the 40 line that are focused and their focus and have figured out a clear cloud strategy and aren't necessarily dealing with a big install base the exception of course is is microsoft and the ones below the line definitely have parts of their portfolio which have solid momentum but they're fighting the inertia of a large install base that moves very slowly again microsoft had the advantage of really azure and migrating those customers very quickly okay so let's wrap it up starting with the big three cloud players aws is accelerating and innovating great example is custom silicon with nitro and graviton and other chips that will help the company address concerns related to the race to the bottom it's not a race to zero aws we believe will let its developers go after the sas business and for the most part aws will offer solutions that address large vertical markets think call centers the edge remains a wild card for aws and all the cloud players really aws believes that in the fullness of time all workloads will run in the public cloud now it's hard for us to imagine the tesla autonomous vehicles running in the public cloud but maybe aws will redefine what it means by its cloud microsoft well they're everywhere and they're expanding further now into gaming and the metaverse when he became ceo in 2014 many people said that satya should ditch xbox just as an aside the joke among many oracle employees at the time was that safra katz would buy her kids and her nieces and her nephews and her kids friends everybody xbox game consoles for the holidays because microsoft lost money for everyone that they shipped well nadella has stuck with it and he sees an opportunity to expand through online gaming communities one of his first deals as ceo was minecraft now the acquisition of activision will make microsoft the world's number three gaming company by revenue behind only 10 cent and sony all this will be powered by azure and drive more compute storage ai and tooling now google for its part is battling to stay relevant in the conversation luckily it can afford the massive losses it endures in cloud because the company's advertising business is so profitable don't expect as many have speculated that google is going to bail on cloud that would be a huge mistake as the market is more than large enough for three players which brings us to the rest of the pack cloud ecosystems generally and aws specifically are exploding the idea of super cloud that is a layer of value that spans multiple clouds hides the underlying complexity and brings new value that the cloud players aren't delivering that's starting to bubble to the top and legacy players are staying close to their customers and fighting to keep them spending and it's working dell hpe cisco and smaller predominantly on-plan prem players like pure storage they continue to do pretty well they're just not as sexy as the big cloud players the real interesting activity it's really happening in the ecosystem of companies and firms within industries that are transforming to create their own digital businesses virtually all of them are running a portion of their offerings on the public cloud but often connecting to on-premises workloads and data think goldman sachs making that work and creating a great experience across all environments is a big opportunity and we're seeing it form right before our eyes don't miss it okay that's it for now thanks to my colleague stephanie chan who helped research this week's topics remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast check out etr's website at etr dot ai and also we publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me email me at david.velante siliconangle.com you can dm me at divalante or comment on my linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time [Music] you

Published Date : Feb 7 2022

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Breaking Analysis: What Could Disrupt Amazon?


 

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante five publicly traded u.s based companies have market valuations over or just near a trillion dollars as of october 29th apple and microsoft topped the list each with 2.5 trillion followed by alphabet at 2 trillion amazon at 1.7 and facebook now meta at just under a trillion off from a tie of 1.1 trillion prior to its recent troubles these companies have reached extraordinary levels of success and power what if anything could disrupt their market dominance in his book seeing digital author david micheller made three key points that i want to call out first in the technology industry disruptions of the norm the waves of mainframes minis pcs mobile and the internet all saw new companies emerge and power structures that dwarfed previous eras of innovation is that dynamic changing second every industry has a disruption scenario not just the technology industry and third silicon valley broadly defined to include seattle or at least amazon has a dual disruption agenda the first being horizontally disrupting the technology industry and the second as digital disruptors in virtually any industry how relevant is that to the future power structure of the digital industry generally in amazon specifically hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we welcome in author speaker researcher and thought leader david michela to assess what could possibly disrupt today's trillionaire companies and we're going to start with amazon dave good to see you welcome thanks dave good to see you yeah so dave approached us about a month or so ago he was working on these disruption scenarios and we agreed to make this a community research project where we're going to tap the knowledge of the cube crowd and its adjacent communities and to that end we're initiating a community survey that asks folks to rate the likelihood of seven plus one disruption scenarios so we have a slide here that sort of shows what that survey structure is going to look like and so as i say there's seven plus another one which is kind of an open open-ended and we're going to start with amazon as the disruptee so dave you've been writing about the technology industry for decades and digital disruption and china and automation and hundreds of other topics what prompted you to start this project yeah it's a great question you know as you said that the whole history of our business has been you know every decade or so you have a new set of leaders ibm digital microsoft the internet companies etc but when i started looking at it you know that seems in some ways to have actually stopped that you know microsoft is now 40 years old amazon is what 1995 is getting towards 30. you know google's been a dominant company for 20 years and you know apple of course and facebook more recently so so whatever reason this sort of longevity of these firms has been longer than we've seen in the past so i sort of say well is there anything that's going to change that so part of it and we'll get into it is what could happen to disrupt those big five but then the sort of second question was well maybe the uh disruptive energies of the of the tech business have moved elsewhere they've moved to crypto currencies or they've moved to tesla and so you start to sort of broaden your sense of disruption and when you talked about that dual disruption agenda that whole ability of tech to disrupt other sectors banking health care insurance automobiles whatever is sort of a second wave of disruption so uh we started coming out all right what sort of scenarios are we really looking at over say for the 2020s what might shake up the big five as we know them and how might disruption spread to sort of more industry specific parts of the world and that was really the the genesis of the project and really just my own thinking of all right what scenarios can i come up with and then reaching out to companies like yourselves to figure out okay how can we get more input on that how can we crowdsource it how can we get a sense of of what the community thinks of all this it's great love it and as you know we're very open to do that so we're going to crowdsource this we're going to open it up to virtually anyone and use multiple channels so let's go through some of the scenarios all of them actually and explain the reasoning behind their inclusion the first one the govern government mandated separation divestment and or limits on amazon's cloud computing retail media credit card and or in-house product groups it probably no coincidence that this was the first one you chose today but why start here well i think the government interest in doing something to get back at big tech is is pretty clear and probably one of the few things that has bipartisan support in washington these days and also government interventions have always been an enormous part of the tech industry's history the the antitrust efforts against ibm and att in particular and more recently microsoft a smaller one but it's it's always been there there's a vibe to do it now and when you look at all the big ones but particularly amazon you can see that potential divestments and breakups are sitting there right in front of you the separation of retail and aws uh perhaps breaking out credit card or music or media businesses these sorts of things are all on the surface at least relatively clean things to do and i think when you look at the formation of an alphabet or a meta those companies themselves are starting to see their own businesses as consisting of multiple firms yeah so i just want to kind of drill into the cloud piece just to emphasize the importance of aws in the context of amazon amazon announced earnings thursday night after the close aws is now a 64 billion revenue run rate company and they're growing at 39 percent year over year that's actually an accelerated growth rate from q3 2020 when the company was grew at 29 it's astounding think about a company this size moreover aws accounted for more than actually but 100 of amazon's operating profit last quarter so the aws cloud is obviously crucial as a funding vehicle and ecosystem accelerant for amazon and i just wanted to share some data points dave before we move on to these other scenarios yeah and just on that uh i think that is the fundamental point it's very easy to see aws on its own as a powerhouse but i think you know if you figure how much freedom aws money has given the retail business or the credit card business or the music businesses to launch themselves and to essentially make no money for very long periods of time uh you see that you know if you're a walmart trying to compete with amazon as a retailer well that money from aws is is an awful big problem and and so when they look at separation that's the sort of stuff people talk about right so i just want to i want to put that into context just in in terms of the the cloud business so this chart is one from our etr surveys that isolates the four hyperscale cloud providers and adds in oracle and ibm we both own public clouds but don't you know don't have nearly the the scale we don't have apple or facebook they have clouds as well and we can talk about that in a moment but the chart shows net score or spending momentum on the vertical axis and market share or pervasiveness in the survey on the horizontal axis it's it's really mentioned share not dollar market share but it's an indicator and the red line is an indicator of elevated spending momentum and you can see azure and aws they're up and to the right i mean amazon is 64 billion you know uh azure will claim larger because they're including their application business but just their their their i asked business obviously smaller than amazon's but you can see in the survey the respondents define cloud they include that sas business so they they both impressively have this high spending momentum on the vertical axis well above that 40 line despite their size google obviously well behind those to the left and then alibaba which has a small sample in the etr survey it's you know it's not as prominent in china but even though it's ias cloud businesses larger than google's by probably a couple billion dollars now the point is these four hyperscalers and there really are only four in my view anyway they have a presence that allows them to build new businesses and disrupt ecosystems and enact that dual disruption agenda should they choose to do so at least in the case of amazon oracle and ibm are not in a position to do that it's not part of their agenda they don't they don't have that scale but dave can you talk about your dual disruption scenario very clearly amazon fits in there and i would think alibaba as well but what about microsoft facebook apple google yeah i mean you know people often say what's the biggest difference between microsoft and amazon from from a cloud point of view and the answer is pretty clear that microsoft goes out of its way to assure its customers that it really doesn't have any interest in competing directly about them so you don't see microsoft going into the retail business or the banking business or the healthcare business all that seriously in contrast that's really what amazon is all about is taking its capabilities to essentially any industry it likes and therefore as one is as great as the service aws provides it's often being provided to people who amazon is actually competing with at least some degree or another and you know that's a huge part of microsoft's sales pitch and it's certainly a potential vulnerability down the road uh it's very hard in the end to be an essential supplier and a direct competitor at the same time but so far they've managed to do that yeah so we put together just another sort of aside here this little thought experiment to see what aws would look like as a separate entity and so it's a chart that looks at a number of tech companies and lays out their revenue run rate the growth rates gross margin probably should have done operating margin might have been more relevant but market cap and revenue multiple again given the size of aws at 64 billion run rate and accelerating growth trajectory it's just it's remarkable and so we we figured this out based on industry norms and today's valuations it's not inconceivable that aws could be you know in the trillionaire club or close to it so based on that discussion we had earlier amazon amazon's dual disruption agenda being funded by empowered by aws as we just discussed dave yeah and just keep in mind nothing that you or i are saying are predictions or saying that anything is going to happen they are possible scenarios of what might happen that seem to make some plausible sense so that when amazon is making the sort of profits that it's making aws naturally that's going to attract other companies because there's margin to to be had there and similarly you know look at uh you look at microsoft for all those years the profits it made in windows or in office software allowed it to do all kinds of other things and essentially that's what amazon is doing today but if a google or a microsoft could cut into those profits through some sort of aggressive pricing and perhaps we'll talk about that you know that would have a lot of impact on amazon as a whole all right so let's quickly go through the other description scenarios and maybe make some comments the next one sort of major companies increasingly choose to do their own cloud computing and or sell their products directly for competitive cost security or other reasons so dave i saw this and look at a company like walmart and others no way they're going to run their business on aws walmart as we know is building out its own cloud and maybe it doesn't have the size of a hyperscaler but it's very large it's got the technical chops it can most likely do it a lot cheaper than renting cloud space what was your thinking in this scenario yeah the broader thing here is essentially one of that computing paradigms have been proven to go in cycles you know a long time ago people shared computers and called timeshare and then people ran their own and now they're sharing again through the cloud and who knows it's possible that the cycle could shift again through some innovation and you know a lot of companies today look at the bills they're getting for cloud or for various sas services and some of them are pretty high and a lot of them will look at and say hey maybe we actually can do some of this stuff cheaper so the scenario is that essentially the the cycle shifts once again uh and it makes more sense to do stuff in-house again that's not a prediction but uh certainly something that's happened before and couldn't plausibly happen again yeah there's a lot of discussion about that in the industry of martine casado and sarah wong wrote that piece about the you know the trillion dollar basically sucking sound basically saying the the scenario was the the the premise rather was the that that sas companies their cost of goods sold are increasingly going to be you know chewed up by cloud costs and then of course mark andreessen says every company is going to be a sas company so as the sassification of business occurs that's something to consider okay next scenario is environmental policies raise costs change packaging delivery recycling rules and or consumer preferences can you comment dave on your thinking on this scenario yeah first i'll just back up a bit we're used to thinking of technology is the great disrupter and clearly that's still important but there are now other forces out there china which will talk about uh the environment uh various cultural forces and and here with the environment you see all kinds of things that could change that you know if you look at amazon and its model of very high levels of packaging lots of delivery vehicles and all the things it is doing are those necessarily the best environmentally and will there potentially be various taxes carbon metrics or things that might work against that model and tend to favor more traditional stores where people go to pick them up that seems to be a plausible scenario and i think everybody here knows that desire to do something in the in the climate environmental spaces is pretty strong and you know if you look at you know just throws aside the recycling industry itself has arguably been quite a failure in that much of what is so-called recycled is basically put in tankers and shipped to the third world which no longer wants it uh and so the backlog of packaging and concerns about packaging and uh what to do with all that you know those those issues are rising and and will be real and i i don't know whether amazon has a good answer to that they're you know they obviously are very aware of it they're working very hard to do everything they can in that space but their fundamental model of essentially packaging every good in its own little box or envelope or whatever is arguably not the greenest way of doing business got it thank you so okay so the next one is price in slash trade wars with the u.s and or china cloud and e-commerce giant so protectionism favors national players so we talking here about for example google bombing prices or alibaba or trade policy making it difficult for amazon to do business in certain parts of the world can you add some color on this one yeah all those things and i would just start with with china itself you know you could argue that covet has been the biggest disruptor of the last couple years but if you look out the next five or eight you had to look at all these things you'd probably say china the size of the chinese market the power of its vendors players like alibaba clearly can rival amazon in many different ways uh you know it's no secret that it'd be hard for amazon to they're not going to be a big success in china uh but you can see it in harder ways that you imagine across asia or other markets where alibaba is strong and you're in today's sort of environment where there's scarce goods and maybe certain products well maybe they go chinese may probably go to alibaba first and you want to buy that product well amazon doesn't have it but alibaba has it you know those sort of scenarios if you get into a sharp trade war with china or even if the current tensions continue it's quite easy to see how that could uh play some havoc with amazon's supply chains in many ways the whole amazon retail model is based on a steady flow of goods manufactured in china and that clearly is not as stable as it was right got it the next one actually caught my attention and this is a big part of the reason why we want to survey the community to see how plausible folks think this is in its its technology related scenario so that would potentially disrupt aws and by fault by default hit amazon so that's major computing innovations such as quantum edge machine machine would obsolete today's cloud architectures okay so so here what you're thinking just as aws changed the game in i.t some future innovations or new business models that we haven't conceived yet could disrupt the prevailing cloud computing model right yeah absolutely i mean you know again we'll go back to where we started that new technologies have always been the main disruptors and here we're looking at some potentially very powerful uh new technologies you know your guess is good in mind about what's gonna happen with quantum is clearly a very different way of computing quite possibly led by other vendors possibly even led by china which would be a huge issue you look at the cloud well cloud's not very good at sort of edge stuff or machine to a machine stuff or sort of near field things out cars in the highway talking to each other uh you know again amazon's totally aware of these things and they are working on it but they have a huge investment in other ways of doing things and historically that inertia that need to protect existing bases of activity and practices has made it difficult for a lot of companies to adjust to new things and so that could happen again uh and there's certainly a puzzle but yeah in all these cases so far amazon has been aware of it is trying to do it but you can still see the scenario playing out and in a truly disruptive technology it's not always possible for the incumbent to effectively cope with it okay the next scenario speaks to i think some of the work that you've done in automation and related areas software replaces centralized warehouses as delivery services are directly connected to suppliers and factories so dave this is like cut out the middle man right software and automation changes the nature of the route absolutely i mean you know in a world of ubiquitous delivery services and product standardization metrics and products being built and shipped from all over the world the concept of running them all through a centralized warehouse is at least at a minimum uh seems like something that might be uh obsoleted and replaced and you know imagine if google built a significant taxonomy of of core products that could be traced directly to where they are either manufactured supplied or brought into the country from whatever company that tries to sell them and the delivery service connected directly to that uh and so that model has always been out there i think at various times people have looked at it it hasn't happened so far and i think amazon itself is is is looking at this particularly as it gets more into food that the idea of shipping all fresh food any sort of centralized warehouse is a pretty bad idea uh and so you know that model of software essentially replacing giant automated warehouses uh is out there and and seems to me uh likely and i just say that you know alibaba for the record doesn't really use that warehouse model it uses a network of suppliers and does it that way and and there do seem to be uh some efficiencies that would likely come with that the next one is was really interesting from a historian's perspective and it's the penultimate uh scenario and that's the proverbial self-inflicted wound and you and i certainly remember ibm's you know fateful decision to outsource the microprocessor and operating system to intel and and and and and microsoft sorry ibm's decision to do that lotus you might recall it refused to allow 123 to run on windows back in the day novell buying word perfect jim barksdale a lot of young people the audience won't of course remember this but jim barksdale poo-pooing microsoft's decision to bundle internet explorer into the operating system all those were kind of self-inflicted or blind spots so this one is complacency arrogance blindness abuse of power loss of trust so much more than the examples i gave consumer and or employee backlash you're seeing some of that at facebook now and i guess this is taking their eye off the customer ball losing the day zero in amazon's case forgetting that customer obsession formula they're working backwards culture and i think this is a big reason why andy jassy was put in charge so this wouldn't happen but we've seen time and time again as the examples i just gave blind spots have absolutely killed companies haven't they dave absolutely he listed many of the most famous but perhaps my favorite of all was kennels and the founder of digital equipment corporation one of the great tech visionaries of his time who stated over and over again why would anybody want a home computer or eunuch's snake oil was his other beautiful all of those things and and so there's the blindness uh there's the area ibm who just came to the view that they and att both came to the view that they were invincible and nothing could ever crack their control of their customer base so we've seen all that i think uh more recently i think some of these things can actually go from the bottom up and you know what's happening to facebook today well they're being hurt by former employees speaking out uh you know this never really happened too much to in the ibm and t days but people calling into question amazon's work labor practices and such things is certainly a possible scenario and the whole sort of you know in the end you know people talk about a cultural backlash against technology i'm not sure i believe it'll happen but it certainly is possible that people will start to rebel against these firms you see it more likely with facebook is fairly well along there uh amazon's still popular but you know in the end and as you i think you said the the core thing that companies routinely fail on is they lose their customer focus and they get caught up in other things their financial numbers their their power inside their position of their company but they they lose track of staying close to the customer has need and terrific job of staying close to the customers over the years uh so if anyone you know was maybe less vulnerable that they they would be well along that that line but it can happen to anyone and new management is often you know one of the real tests and there's many examples of that through history when a new executive comes in will they have that same focus that same thing particularly you know as the first generation's employees get wealthy and retired in a new set of people come in you know you look at microsoft the new people who came in well they're not going to be multi-millionaires they may have missed the great runs they're there to work and and the culture of companies changes when you get to that state the m is not that there yet but you can envision that comings soon enough so you know cultural issues have always been a factor and it's hard to imagine there won't be some sort of factor going forward well and you know you talk about that the the succession of founders and ceos i mean that's what to me makes microsoft so astounding because during the bomber years it was unclear that they were ever going to become relevant again and so nadella has done a masterful job but of course they had the margins from the pc software business that allowed them to buy that time but look at intel and the troubles it's going through uh and so many other examples of companies that just sort of said all right well we're going to pack it in and either sell the company or which is again what i think makes think companies like oracle and dell which you know founder-led ceos not ceo in the case of oracle but still running the business uh so quite uh significant yeah yeah and you know we've talked a lot about things that might hurt answers but you gotta recognize how in many ways how amazing they are and most tech companies a lot of them anyways have essentially been one trick ponies i mean google still makes overwhelming amount of its money selling ads and the things it's tried to do in cars and healthcare and various things you know they've often struggled you know apple still makes the core of its money around it's it's cell phone platform amazon's one of the few that continually generates entirely new huge businesses and and you have to give them an enormous amount of credit for that you know microsoft uh was a they failed repeatedly over and over again with internet stuff and phone stuff and all these things and it really wasn't until you know satya came in and really focused on their customers and their need for enterprise services that he that he really got the company on the right track so you know amazon has always been good listeners customers and if they continue to do so it bodes well but history says other stuff comes along okay and the last scenario is open-ended dave included uh you know what did we miss is there another scenario that we haven't put forth that you could feel it could be disruptive to amazon right i mean you've got to have the at least what'd we miss yeah i mean you know these are things that me and you and i just sort of made up the top of our head these are things we see that that might happen but you know in your huge audience of people in this community every day i'm sure there are other people out there who have thoughts of what might shake things up or even doing things that might shake things up already uh and you know one of the things you do for you guys is get this sort of material out there and and see what ideas surface so hopefully people will uh participate in this and we'll see what comes out of it all right so what happens from here is we're going to publish the the link to the survey in this video description and in our posts we ask you to take the survey please tell your friends we're going to publish the results as always we do in an open and free david michelle thanks so much for putting your brain power on this and collaborating with us i'm really excited to see the results and and and run through the other giants with you as well once we see what this survey says yeah thanks david great and yeah if we can make this one work be fun to do it for for google and microsoft and facebook and apple and see where it all goes thanks a lot all right okay that's it for today remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast i publish each week on wikibon.com and siliconangle.com etr.plus is where all the cool survey data lives they just dropped their october survey with some great findings so do check that out you can reach me on twitter at d velante he's at d michelle or comment on my linkedin post or email me at david.vellante at siliconangle.com this is dave vellante for dave michelle thanks for watching thecube insights powered by etr be well and we'll see you next time

Published Date : Nov 1 2021

SUMMARY :

the highway talking to each other uh you

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Sidney Madison Prescott, MBA, Spotify | UiPath FORWARD IV


 

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by UI path. >>It's the Q we are live in Las Vegas at the Bellagio. Lisa Martin, with Dave Volante, we're covering UI path forward for this is our second day of coverage. We've had a lot of great conversations with customers at UI path partners, their senior leaders. And next up, we're going to be talking to, I'm going to say the queen of citizen developer nests. We're not just going to create that title for you. Sydney, Madison Prescott. She's the global head of intelligent automation at Spotify Sydney. Welcome to the program. I >>Am so excited >>To be here. We're excited to have you. So one of my, as we were talking before we went live, we both are big fans of Spotify. I don't know what we would do without it in our personal lives. But talk to me a little bit about Spotify automation, UI path. And I don't want to get into you your book, what you've done for citizen developers. >>Perfect. So Spotify is on a very interesting journey. Uh, we began the journey during the pandemic and we were speaking about this a little bit earlier. And so our journey began with trying to understand how we would tackle, uh, still wanting to upskill our employees, despite the fact that we were in the middle of this kind of global crisis. And so through that endeavor, we decided to actually split out our different, uh, automation capabilities into citizen developer and unattended automation. And we did all of this through a center of excellence. So a centralized, uh, COE, which would facilitate the growth of the automations, uh, whether on the citizen developer side or the unattended side. And through this programs, we set up, uh, several different trainings where we could facilitate the growth of the citizen developer community through five day, what we call bot boot camps and the bot boot camp is in essence, um, five day training, about four and a half, five hours a day, where we take anyone at Spotify who would like to upskill in this type of automation. And we teach them everything from the basics of robotic process automation, all the way to, you know, what are all of the Spotify specific things that you have to do in order to maintain a robust, uh, citizen developer footprint within your team. And so through that, uh, that entire journey, it's been quite amazing. We started with a very small footprint in our accounting team, and we have scaled now to over 100 citizen developers, uh, in a variety of functions within Spotify. >>And what was the role that you came to Spotify to do? Cause you came there, went there right before the everything happened. >>Yes. So I was actually, uh, brought into Spotify to stand up and scale out our intelligent automation center of excellence. >>So the center of excellence is, is sort of the main spring of knowledge, training innovation. And then the, the citizen developer piece, it sounds like you're pushing out distributing that knowledge. Right. And so I'm interested in that sort of architecture of automation is that you've got a combination of centralized expertise and decentralized innovation. Can you talk about that a little bit? >>Yeah. So it's very interesting actually. So we facilitate the citizen developer program through the center of excellence. So you can think of the center of excellence as the foundation of that knowledge. And our goal is to democratize that knowledge throughout the enterprise. And the way we do that is through the training. Uh, we facilitate the governance of the program. So making sure that all of the infrastructure is properly set up, uh, enabling the citizens, if they need support, just talking about ideation, uh, even so far as up-skilling as well. So upskilling all the way to a power user, uh, whereby those users could become true innovators and facilitate a wide variety of automations within their teams. And was it >>The events of the last 18 months? It really catalyzed this and kind of led you to really become a big advocate for citizen led development. >>It did. So we initially were starting with just the center of excellence and an unintended footprint, and we quickly pivoted and realized that we needed to in order to scale, uh, significantly given the, the situation working virtually, uh, we are a distributed team around the world that it was critical for our success that we could, uh, really distribute to this workout. And we felt that the best way to do that was through standing up a citizen developer program. >>The things that I'm trying to understand is the relationship between automation and data. And I look at Spotify in many respects is a data company, at least a company who really understands data. And I see you building all these awesome data products. I'm a subscriber as well, but you know, you've added podcasts, you've got contributors to those podcasts. You've obviously got artists and you know, these people obviously have to be paid. You have this sort of interesting ecosystem and these are all data products, if you will, that you guys build. And it's very cool sort of business model. What's the relationship between data and automation? >>Well, it is a big relationship. I would actually say it is probably the pivotal relationship because in order to tell that compelling story of digital transformation, we have to understand the data behind all of the automations that we're generating. Um, and this is whether it says in developer or COE built. Um, and so for us, it's, it's a critical component of our success that we can pinpoint those key metrics that we are looking at and tracking, you know, what does success mean for our center of excellence? What does it mean for our citizen led program? And this is everything from, you know, increased data quality to risk mitigation of different internal regulatory risk. Uh, it could be something as simple as our saved on automation. So it's, uh, a wide variety of attributes that we're looking at to really pinpoint where the successes are coming from and where we can improve maybe where we need to improve our automation footprint in a given business. >>Why did you write this book? >>Great question. So I believe in citizen development, I think it is a very unique approach to spreading out the way that you can transform your business. And so I saw a lot of struggles as I've gone through I'm in the industry with understanding citizen development, uh, the premise of it, and also understanding the technology behind it. Um, I am a big fan of studio X. And so the book specifically focuses on studio X. Um, it really introducing users to what is studio X and how really teaching individuals, how to upskill themselves, um, just through the use of the book, very intuitive and hopefully taking away some of the fear that the users may have about walking through a platform like studio S >>So what do I have to know to actually, can I read your book and then start coding? Is it by >>That is the goal. Yes. So the goal for the book is very hands-on. So it is, it is a book for, um, the novice business user, uh, someone who is not familiar with RPA, someone who may not even be familiar with UI path, they would be able to pick up this book, go through the set of exercises. It's very robust out over 400 pages. So it really packed a lot of knowledge in there, but the goal would be by the time you walk through every single exercise and complete the book, you would not only understand RPA. You would also understand UI path as a, as a service provider platform. You'd also understand the nuances of studio X. >>So in theory, someone like myself could get your book, download the community edition, start building automations, right? >>Yes, exactly. Exactly. >>You have to Google a few things, but yeah. >>Yes. And it comes with a very robust code code set up. They're able to actually look at the code and review, uh, examples of the code, uh, in a source code repository. So again, it's very novice users it's meant for, to help facilitate just the learning of someone who is maybe curious about RPA, curious about UI path, or just curious about studio app. >>I already have the use case. >>You do have these guys I'm interested in doing it too. I mean, I can tell that it's a passion project of yours that you fundamentally believe in. You know, we saw this morning data from IDC and we've seen lots of different data sources that talk about, oh, automation taking jobs, people being fearful, organizations, not being ready at the same time. We've had such a tumultuous last 18 months that organizations that weren't digital are probably gone and organizations that aren't, how did there was this massive uptake in automation because suddenly you couldn't get bodies into buildings. So tell me about how this book is a facility, first of all, tell us the name of it. And then as a facilitator of those employees who might be worried about their jobs being taken by bots, >>That is a great question. So the, the name of the book is robotic process automation, a citizen developers guide to hyper automation using UI path studio X. And I would say I've heard a lot of the conversation surrounding the loss of jobs, the potential fear, uh, we all we know as humans, we are generally unfortunately, a little resistant to change and, you know, the, I'll say the digital revolution that we're going through, uh, within the workforce, whether it is hybrid work, whether it is completely virtual work, it is a bit daunting. And I understand that fear, I think in alignment with the conversation that we had heard about earlier at forward there, RPA has the ability to generate a massive amount of not only improvements within different industries, but jobs as well. Right? And for someone who is looking at this kind of ever changing landscape, and they're wondering, where do I fit in? >>Am I going to get pushed out of a, of a general, you know, uh, industry? I would say that that fear turned that into power, turned that into ambition. Um, the level of upskilling that you can do on your own, whether it's using UiPath academy, whether it's reaching out to your center of excellence, it's incredible. Um, there's a wide variety of different ways that you can upskill yourself. And in essence, you become, um, a powerful player in your environment because not only do you have the business acumen, you now have the technical acumen, and that is everything. I mean, when we talk about transformation, we talk about where our industry's going. Um, there's a saying that, you know, every company now must be a technology company, right? And so this is the key, even as workers, even as employees, we all must be technologists. And so the real question is, think of yourself and think of this concept. I like to call human augmentation. How can you augment yourself through UI path, through the use of RPA to become that up-skilled worker, that next level worker who will be integral to the success of any company moving from, >>We talk a lot about upscaling. Now, of course, part of that upskilling I presume is learning how to use robotic process automation and the tooling, but it seems that there's more to it than that. And, and you just strike me as a person that's creative, you have a power persona. So what are these sort of intangible skills that, that I need to succeed in this new world? And can I learn them? >>That's a great question. I think one of the biggest skills, being able to think outside of the box, that is huge. Uh, and again, this goes back to at least question about what does it take and what should you, you should really think outside of the box about your own career, about your team, about your company, um, how you can improve upon what is already there, um, or how can you build something completely new that has never been thought of before. And so I think that's the biggest skill. The ability to, um, innovate, think, think innovatively and think outside of the box. Um, I believe it's, it's something that is maybe a little intuitive to some individuals, but you can also learn, you can learn to, um, get out of your own way, so to speak, uh, so that you can actually start to come up with these really creative ways to address, uh, whether it's complex business problems, uh, whether it's at an industry level or even just within your internal enterprise. >>And creativity is actually one of the attributes. And I guess it might not be in your DNA, but if you, you know, it's like humor, humor, right? If you hang out with funny people, you know, if you hang out with creative people, you can, you can learn about apply. >>That's right. That's right. But in the beginning of the pandemic, you know, one of the things that I think we all want, you seem to have a ton of motivation and ambition as Dave was saying. And, and I'm someone that normally has that too, but in the first year of pandemic, that was hard. It's hard to get motivated. It was hard to know where do I fit in? How do you advise? And now of course, when you publish the book six months ago, we're about a year into the pandemic. Things are looking better because here we are in Las Vegas at an in-person event with humans. But how do you, how do you see, how do you recommend to folks that are, that don't have technology backgrounds like you don't, I don't to motivate themselves to go, you can take the control, take it. And everybody don't, we all want control as people and take control of your career path. There are a lot of opportunities out there. How do you advise people navigating this challenging sort of mental state with there's so many opportunities sitting right here? Yes >>That's so I think it, it goes back to the getting out of your own way. It also goes back to really taking a look at assess assessing your own skillset, um, assessing your own personal drivers. What motivates you, uh, whether that is in your personal life, whether that is in your professional life, and then taking a look also at those motivators, how can I look at those and what use can I get out of those to help me to transform my own personal skill set and really grow out, uh, my, my capabilities, right, as a professional it's, it's all about really thinking through, uh, your, I'll say your professional background or role as ever-changing ever-growing. And as long as you approach it with a mindset of constantly growing constantly upskilling, I mean, honestly, the sky is truly the limit. >>I a weird question. If, if, if, if mastering word is a one and let's say learning, um, learning how to use Excel, macros is let's call it a three. Uh, all in the spectrum goes out to a, be a building, a complex, uh, you know, uh, AI model, data science kind of ML model. If that's a 10, where does learning how to code RPA as a citizen developer fit on that spectrum? Good question. >>Oh, that's a great question. I would say somewhere between, Hmm. I would say somewhere between maybe three and four around there, because you there. So again, we, we have so many tools that we can use to help upscale the set of sense at this point that we can really walk them through the nuances, uh, at a pace that is conducive to really retaining the knowledge. So I don't think it's, it's definitely not the level of, let's say, building out a complex, like machine learning model or something of that nature. It may be a little bit more in alignment with, um, if someone is up-skilled and macros, or you may be up-skilled in some other type of scripting, uh, language similar to that, I might even say sometimes a little bit, maybe a little bit less difficult than that, uh, depending on what you're trying to automate, right. The process you're trying to automate the company, >>But inside of a day, I can do something fairly simple, right? Yeah. >>Yes. So we actually, the, the training that we have at Spotify, we train our users from novice. Absolutely no understanding, no knowledge of RPA to building able, being able to build a bot in five days. And those are five half days sessions that the citizen developers attend. And by the morning of the fifth day, they actually have built a bot. And so it's, and it's very powerful, uh, being able to, to upskill someone and show them, I can take you from, you know, absolutely no understanding of RPA to actually having something, a bot that you can showcase that you can run within as little as five half days. I mean, it's very compelling to any business user, right? >>The business impact. Soon as you guys are too young to remember, but there's this thing called Lotus 1, 2, 3, we used to have to go to Lotus class slash file retrieve for you folks who remember this was all keyboard based, but it was game changing in terms of your personal productivity. And it sounds like there's a similar but much, much larger impact with RPA >>Impact. Talk to me about the impact of the program, especially in the last, this year, here we are in October, you mentioned started small, and now there's about a hundred folks. Talk to me about the appetite of that as we've seen this massive acceleration and the need to automate for everyday things that we expect as consumers, whether we're ordering food or buying something online. >>Hmm. So it really is a different mindset in terms of thinking through the way that we work differently. And so we really approached it with, if you're an accountant, think of what is the future role and responsibility of an accountant in this new digital, uh, I'll say environment. And through that, we have been able to really push this idea or this concept of up-skilling as a key element of personal professional success and also team success. Um, and that has been a game changer. So there's a lot of value that comes out of the cohesiveness between the personal desire to upskill and continue to, uh, be a, you know, a consummate professional in whatever role you're in, but also to help your team right, to be, to be, you know, a standout, uh, team player in terms of the skills that you're bringing to the table as both an accountant and someone that has now the power of automation within your skillset. Okay. >>And ask you one more question. And that is something that Dave brought up yesterday as we were, he was sitting on a panel with, and he was the only male, which is not common in our industry. How have you seen the role of females in technology changing? And I'm imagine you do work in stem. Imagine you're a motivational speaker you should be if you're not. Um, but how have you seen the role of females in technology changing in since there's so much opportunity there? >>Yes. That is a great question. I believe that RPA specifically, uh, is an incredible driver of women and influencing more women to enter into stem fields, primarily because it is such an innovative technology. There are so many roles he said that are open, just opening up. Uh, probably I've heard different numbers in terms of acceleration of growth over the next five to 10 years. So we're looking at a plethora of opportunities and these are brand new roles that women who are curious about stem, curious about being a technologist can dive right into from wherever they are. So whether they are a tax professional today, whether they are working within, you know, uh, counting, whether they're working with an internal audit, they have the opportunity now to test the waters. Um, and quite often it is such a, it's such a fascinating field. And as I said, there's so much potential around it and for growth and just for changing, uh, different industries, that it's a great driver for women to actually enter into, uh, stem technology, uh, and really drive change, facilitate change, and have more women at the table, so to speak. Okay. >>And you didn't, you didn't start in tech, in stem, right? I did not. Do you have a law degree or no, you have a Ms. >>So yes, little studies and then I actually, I'm a philosopher. So I started by my degree is in philosophy. I love >>This logic. Yes. I love how you've applied that to >>Yeah. Yes. I was not initially in stem and it was actually through an internship at a technology firm, uh, while I was in college that I don't first open to technology. And it just immediately captivated me just in terms of working, you know, that the speed, the pace, uh, just being able to solve these complex business problems at scale around the world. It was absolutely fascinating to me, obviously still is, but I think testing the waters in that way, um, as I was just talking before, it helped me to understand, I had never envisioned a career in technology, but having an opportunity to test the waters really enabled me to see that, wow, this is something where I have a skillset and it brings out a passion within me that I didn't know that I had. So it was a, it was a win-win. >>That's awesome. No worries. Last question. Where can folks go to get your book? >>Yes. So anywhere books are sold, uh, definitely on Amazon. Uh, we, if you are here at forward, we also are, have a book signing, so you can come find me. I'll be on the patio signing books and, uh, yeah, it's, it's everywhere. And I would love to hear feedback. And we're thinking about a second one. So please let us know how you like the, uh, the activities that are in there. >>Thank you. Congratulations. And Dave's going to pick one up so he can start. >>Yeah. The use case. I'm dying to dig >>In, do a breathing analysis on it, and he was great to have you on the program. Your energy is fantastic. You really open up opportunities for people. I hope that more people will watch this and understand that while the really the sky is really the limit. And, uh, thank you for your time. Absolutely. >>Thank you. It's a pleasure >>For Dave Volante. I'm Lisa Martin. We are live in Vegas at the Bellagio UI path forward for you right back with our next guest.

Published Date : Oct 6 2021

SUMMARY :

UI path forward for brought to you by UI path. It's the Q we are live in Las Vegas at the Bellagio. And I don't want to get into you all the way to, you know, what are all of the Spotify specific things that you have to do in And what was the role that you came to Spotify to do? intelligent automation center of excellence. And so I'm interested in that sort And the way we do that is through the training. It really catalyzed this and kind of led you to really And we felt that the best way to do that was through And I see you building all these awesome data products. that we are looking at and tracking, you know, what does success mean for our center of excellence? unique approach to spreading out the way that you can transform So it really packed a lot of knowledge in there, but the goal would be by the time you walk So again, it's very novice users it's meant for, to help facilitate that aren't, how did there was this massive uptake in automation because suddenly you couldn't get bodies into buildings. the loss of jobs, the potential fear, uh, we all we know as humans, Am I going to get pushed out of a, of a general, you know, uh, industry? And, and you just strike me as a person that's creative, so to speak, uh, so that you can actually start to come up with these really creative ways And creativity is actually one of the attributes. But in the beginning of the pandemic, you know, one of the things that I think we And as long as you approach it with a mindset of constantly growing constantly upskilling, a complex, uh, you know, uh, AI model, data science kind of ML or you may be up-skilled in some other type of scripting, uh, language similar But inside of a day, I can do something fairly simple, right? that you can run within as little as five half days. we used to have to go to Lotus class slash file retrieve for you folks who remember here we are in October, you mentioned started small, uh, be a, you know, a consummate professional in whatever role you're in, but also to help your team And I'm imagine you do work in stem. you know, uh, counting, whether they're working with an internal audit, they have the opportunity And you didn't, you didn't start in tech, in stem, right? So I started by my degree you've applied that to you know, that the speed, the pace, uh, just being able to solve these complex business problems at Where can folks go to get your book? we also are, have a book signing, so you can come find me. I'm dying to dig And, uh, thank you for your time. It's a pleasure you right back with our next guest.

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Breaking Analysis: Google's Antitrust Play Should be to get its Head out of its Ads


 

>> From the CUBE studios in Palo Alto in Boston, bringing you data-driven insights from the CUBE in ETR. This is breaking analysis with Dave Vellante. >> Earlier these week, the U S department of justice, along with attorneys general from 11 States filed a long expected antitrust lawsuit, accusing Google of being a monopoly gatekeeper for the internet. The suit draws on section two of the Sherman antitrust act, which makes it illegal to monopolize trade or commerce. Of course, Google is going to fight the lawsuit, but in our view, the company has to make bigger moves to diversify its business and the answer we think lies in the cloud and at the edge. Hello everyone. This is Dave Vellante and welcome to this week's Wiki Bond Cube insights powered by ETR. In this Breaking Analysis, we want to do two things. First we're going to review a little bit of history, according to Dave Vollante of the monopolistic power in the computer industry. And then next, we're going to look into the latest ETR data. And we're going to make the case that Google's response to the DOJ suit should be to double or triple its focus on cloud and edge computing, which we think is a multi-trillion dollar opportunity. So let's start by looking at the history of monopolies in technology. We start with IBM. In 1969 the U S government filed an antitrust lawsuit against Big Blue. At the height of its power. IBM generated about 50% of the revenue and two thirds of the profits for the entire computer industry, think about that. IBM has monopoly on a relative basis, far exceeded that of the virtual Wintel monopoly that defined the 1990s. IBM had 90% of the mainframe market and controlled the protocols to a highly vertically integrated mainframe stack, comprising semiconductors, operating systems, tools, and compatible peripherals like terminal storage and printers. Now the government's lawsuit dragged on for 13 years before it was withdrawn in 1982, IBM at one point had 200 lawyers on the case and it really took a toll on IBM and to placate the government during this time and someone after IBM made concessions such as allowing mainframe plug compatible competitors to access its code, limiting the bundling of application software in fear of more government pressure. Now the biggest mistake IBM made when it came out of antitrust was holding on to its mainframe past. And we saw this in the way it tried to recover from the mistake of handing its monopoly over to Microsoft and Intel. The virtual monopoly. What it did was you may not remember this, but it had OS/2 and Windows and it said to Microsoft, we'll keep OS/2 you take Windows. And the mistake IBM was making with sticking to the PC could be vertically integrated, like the main frame. Now let's fast forward to Microsoft. Microsoft monopoly power was earned in the 1980s and carried into the 1990s. And in 1998 the DOJ filed the lawsuit against Microsoft alleging that the company was illegally thwarting competition, which I argued at the time was the case. Now, ironically, this is the same year that Google was started in a garage. And I'll come back to that in a minute. Now, in the early days of the PC, Microsoft they were not a dominant player in desktop software, you had Lotus 1-2-3, WordPerfect. You had this company called Harvard Presentation Graphics. These were discreet products that competed very effectively in the market. Now in 1987, Microsoft paid $14 million for PowerPoint. And then in 1990 launched Office, which bundled Spreadsheets, Word Processing, and presentations into a single suite. And it was priced far more attractively than the some of the alternative point products. Now in 1995, Microsoft launched Internet Explorer, and began bundling its browser into windows for free. Windows had a 90% market share. Netscape was the browser leader and a high flying tech company at the time. And the company's management who pooed Microsoft bundling of IE saying, they really weren't concerned because they were moving up the stack into business software, now they later changed that position after realizing the damage that Microsoft bundling would do to its business, but it was too late. So in similar moves of ineptness, Lotus refuse to support Windows at its launch. And instead it wrote software to support the (indistinct). A mini computer that you probably have never even heard of. Novell was a leader in networking software at the time. Anyone remember NetWare. So they responded to Microsoft's move to bundle network services into its operating systems by going on a disastrous buying spree they acquired WordPerfect, Quattro Pro, which was a Spreadsheet and a Unix OS to try to compete with Microsoft, but Microsoft turned the volume and kill them. Now the difference between Microsoft and IBM is that Microsoft didn't build PC hardware rather it partnered with Intel to create a virtual monopoly and the similarities between IBM and Microsoft, however, were that it fought the DOJ hard, Okay, of course. But it made similar mistakes to IBM by hugging on to its PC software legacy. Until the company finally pivoted to the cloud under the leadership of Satya Nadella, that brings us to Google. Google has a 90% share of the internet search market. There's that magic number again. Now IBM couldn't argue that consumers weren't hurt by its tactics. Cause they were IBM was gouging mainframe customers because it could on pricing. Microsoft on the other hand could argue that consumers were actually benefiting from lower prices. Google attorneys are doing what often happens in these cases. First they're arguing that the government's case is deeply flawed. Second, they're saying the government's actions will cause higher prices because they'll have to raise prices on mobile software and hardware, Hmm. Sounds like a little bit of a threat. And of course, it's making the case that many of its services are free. Now what's different from Microsoft is Microsoft was bundling IE, that was a product which was largely considered to be crap, when it first came out, it was inferior. But because of the convenience, most users didn't bother switching. Google on the other hand has a far superior search engine and earned its rightful place at the top by having a far better product than Yahoo or Excite or Infoseek or even Alta Vista, they all wanted to build portals versus having a clean user experience with some non-intrusive of ads on the side. Hmm boy, is that part changed, regardless? What's similar in this case with, as in the case with Microsoft is the DOJ is arguing that Google and Apple are teaming up with each other to dominate the market and create a monopoly. Estimates are that Google pays Apple between eight and $11 billion annually to have its search engine embedded like a tick into Safari and Siri. That's about one third of Google's profits go into Apple. And it's obviously worth it because according to the government's lawsuit, Apple originated search accounts for 50% of Google search volume, that's incredible. Now, does the government have a case here? I don't know. I'm not qualified to give a firm opinion on this and I haven't done enough research yet, but I will say this, even in the case of IBM where the DOJ eventually dropped the lawsuit, if the U S government wants to get you, they usually take more than a pound of flesh, but the DOJ did not suggest any remedies. And the Sherman act is open to wide interpretation so we'll see. What I am suggesting is that Google should not hang too tightly on to it's search and advertising past. Yes, Google gives us amazing free services, but it has every incentive to appropriate our data. And there are innovators out there right now, trying to develop answers to that problem, where the use of blockchain and other technologies can give power back to us users. So if I'm arguing that Google shouldn't like the other great tech monopolies, hang its hat too tightly on the past, what should Google do? Well, the answer is obvious, isn't it? It's cloud and edge computing. Now let me first say that Google understandably promotes G Suite quite heavily as part of its cloud computing story, I get that. But it's time to move on and aggressively push into the areas that matters in cloud core infrastructure, database, machine intelligence containers and of course the edge. Not to say that Google isn't doing this, but there are areas of greatest growth potential that they should focus on. And the ETR data shows it. But let me start with one of our favorite graphics, which shows the breakdown of survey respondents used to derive net score. Net score remembers ETR's quarterly measurement of spending velocity. And here we show the breakdown for Google cloud. The lime green is new adoptions. The forest green is the percentage of customers increasing spending more than 5%. The gray is flat and the pinkish is decreased by 6% or more. And the bright red is we're replacing or swapping out the platform. You subtract the reds from the greens and you get a net score at 43%, which is not off the charts, but it's pretty good. And compares quite favorably to most companies, but not so favorite with AWS, which is at 51% and Microsoft which is at 49%, both AWS and Microsoft red scores are in the single digits. Whereas Google's is at 10%, look all three are down since January, thanks to COVID, but AWS and Microsoft are much larger than Google. And we'd like to see stronger across the board scores from Google. But there's good news in the numbers for Google. Take a look at this chart. It's a breakdown of Google's net scores over three survey snapshots. Now we skip January in this view and we do that to provide a year of a year context for October. But look at the all important database category. We've been watching this very closely, particularly with the snowflake momentum because big query generally is considered the other true cloud native database. And we have a lot of respect for what Google is doing in this area. Look at the areas of strength highlighted in the green. You've got machine intelligence where Google is a leader AI you've got containers. Kubernetes was an open source gift to the industry, and linchpin of Google's cloud and multi-cloud strategy. Google cloud is strong overall. We were surprised to see some deceleration in Google cloud functions at 51% net scores to be on honest with you, because if you look at AWS Lambda and Microsoft Azure functions, they're showing net scores in the mid to high 60s. But we're still elevated for Google. Now. I'm not that worried about steep declines, and Apogee and Looker because after an acquisitions things kind of get spread out around the ETR taxonomy so don't be too concerned about that. But as I said earlier, G Suite may just not that compelling relative to the opportunity in other areas. Now I won't show the data, but Google cloud is showing good momentum across almost all interest industries and sectors with the exception of consulting and small business, which is understandable, but notable deceleration in healthcare, which is a bit of a concern. Now I want to share some customer anecdotes about Google. These comments come from an ETR Venn round table. The first comment comes from an architect who says that "it's an advantage that Google is "not entrenched in the enterprise." Hmm. I'm not sure I agree with that, but anyway, I do take stock in what this person is saying about Microsoft trying to lure people away from AWS. And this person is right that Google essentially is exposed its internal cloud to the world and has ways to go, which is why I don't agree with the first statement. I think Google still has to figure out the enterprise. Now the second comment here underscores a point that we made earlier about big query customers really like the out of the box machine learning capabilities, it's quite compelling. Okay. Let's look at some of the data that we shared previously, we'll update this chart once the company's all report earnings, but here's our most recent take on the big three cloud vendors market performance. The key point here is that our data and the ETR data reflects Google's commentary in its earning statements. And the GCP is growing much faster than its overall cloud business, which includes things that are not apples to apples with AWS the same thing is true with Azure. Remember AWS is the only company that provides clear data on its cloud business. Whereas the others will make comments, but not share the data explicitly. So these are estimates based on those comments. And we also use, as I say, the ETR survey data and our own intelligence. Now, as one of the practitioners said, Google has a long ways to go as buddy an eighth of the size of AWS and about a fifth of the size of Azure. And although it's growing faster at this size, we feel that its growth should be even higher, but COVID is clear a factor here so we have to take that into consideration. Now I want to close by coming back to antitrust. Google spends a lot on R&D, these are quick estimates but let me give you some context. Google shells out about $26 billion annually on research and development. That's about 16% of revenue. Apple spends less about 16 billion, which is about 6% of revenue, Amazon 23 billion about 8% of the top line, Microsoft 19 billion or 13% of revenue and Facebook 14 billion or 20% of revenue, wow. So Google for sure spends on innovation. And I'm not even including CapEx in any of these numbers and the hype guys as you know, spend tons on CapEx building data centers. So I'm not saying Google cheaping out, they're not. And I got plenty of cash in there balance sheet. They got to run 120 billion. So I can't criticize they're roughly $9 billion in stock buybacks the way I often point fingers at what I consider IBM's overly wall street friendly use of cash, but I will say this and it was Jeff Hammerbacher, who I spoke with on the Cube in the early part of last decade at a dupe world, who said "the best minds of my generation are spending there time, "trying to figure out how to get people to click on ads." And frankly, that's where much of Google's R&D budget goes. And again, I'm not saying Google doesn't spend on cloud computing. It does, but I'm going to make a prediction. The post cookie apocalypse is coming soon, it may be here. iOS 14 makes you opt in to find out everything about you. This is why it's such a threat to Google. The days when Google was able to be the keeper of all of our data and to house it and to do whatever it likes with that data that ended with GDPR. And that was just the beginning of the end. This decade is going to see massive changes in public policy that will directly affect Google and other consumer facing technology companies. So my premise is that Google needs to step up its game and enterprise cloud and the edge much more than it's doing today. And I like what Thomas Kurian is doing, but Google's undervalued relative to some of the other big tech names. And I think it should tell wall street that our future is in enterprise cloud and edge computing. And we're going to take a hit to our profitability and go big in those areas. And I would suggest a few things, first ramp up R&D spending and acquisitions even more. Go on a mission to create cloud native fabric across all on-prem and the edge multicloud. Yes, I know this is your strategy, but step it up even more forget satisfying investors. You're getting dinged in the market anyway. So now's the time the moon wall street and attack the opportunity unless you don't see it, but it's staring you right in the face. Second, get way more cozy with the enterprise players that are scared to death of the cloud generally. And they're afraid of AWS in particular, spend the cash and go way, way deeper with the big tech players who have built the past IBM, Dell, HPE, Cisco, Oracle, SAP, and all the others. Those companies that have the go to market shops to help you win the day in enterprise cloud. Now, I know you partner with these companies already, but partner deeper identify game-changing innovations that you can co-create with these companies and fund it with your cash hoard. I'm essentially saying, do what you do with Apple. And instead of sucking up all our data and getting us to click on ads, solve really deep problems in the enterprise and the edge. It's all about actually building an on-prem to cloud across cloud, to the edge fabric and really making that a unified experience. And there's a data angle too, which I'll talk about now, the data collection methods that you've used on consumers, it's incredibly powerful if applied responsibly and correctly for IOT and edge computing. And I don't mean to trivialize the complexity at the edge. There really isn't one edge it's Telcos and factories and banks and cars. And I know you're in all these places Google because of Android, but there's a new wave of data coming from machines and cars. And it's going to dwarf people's clicks and believe me, Tesla wants to own its own data and Google needs to put forth a strategy that's a win-win. And so far you haven't done that because your head is an advertising. Get your heads out of your ads and cut partners in on the deal. Next, double down on your open source commitment. Kubernetes showed the power that you have in the industry. Ecosystems are going to be the linchpin of innovation over the next decade and transcend products and platforms use your money, your technology, and your position in the marketplace to create the next generation of technology leveraging the power of the ecosystem. Now I know Google is going to say, we agree, this is exactly what we're doing, but I'm skeptical. Now I think you see either the cloud is a tiny little piece of your business. You have to do with Satya Nadella did and completely pivot to the new opportunity, make cloud and the edge your mission bite the bullet with wall street and go dominate a multi-trillion dollar industry. Okay, well there you have it. Remember, all these episodes are available as podcasts, so please subscribe wherever you listen. I publish weekly on Wikibond.com and Siliconangle.com and I post on LinkedIn each week as well. So please comment or DM me @DVollante, or you can email me @David.Vollante @Siliconangle.com. And don't forget to check out etr.plus that's where all the survey action is. This is Dave Vollante for the Cube Insights powered by ETR. Thanks for watching everybody be well. And we'll see you next. (upbeat instrumental)

Published Date : Oct 23 2020

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Chellappan Narayanan, HPE & Dr. Rajesh Srinivasan, TCS Cloud | HPE Discover 2020


 

>>from around the globe. It's the Cube covering HP Discover virtual experience brought to you by HP. >>Welcome to the Cube's coverage of HP Discover 2020. This is the virtual experience. I'm Lisa Martin with the Cube, and I'm joined by a couple of guys who were gonna talk through one of HPC ease. Longest partnerships. We've got shells. No Ryan and the Senior director Ecosystem Sales or North America at HP And Dr Rajesh, It's really a Boston. The global head of sales and solutions for the TCS. Gentlemen, welcome to the Cube. >>Yeah, Thank you. >>So, first question for you is I mentioned HP and TCS have been partners for over 30 years. Talk to our audience about the partnership and how it has evolved to where it is today. >>Yeah. Thank you, Lisa. Firstly, you know, I'm pretty excited to be part of this Cube interview with garages. You know, I know him personally for over five years through various interactions globally and this new role for North America. This is our strategy and global system integrator partner. And this is a longstanding partnership between HP and this years has grown multi falls over the last 30 years. Ah, we you know, pretty much enjoyed every single I would say transactions or the business engagements, what we've had so far. And we liberate each other for our internal I T requirements and also to drive joint, go to market initiatives across the world. That's making this a truly 3 60 degree partnership. There is a lot of heritage, a mutual trust and respect between both organizations at all levels and the complimentary offerings. You know what you will hear a lot more in the next couple of questions. Uh, we bring to the table together are very unique and very differentiating to the clients which are >>excellent. Dr. Rajesh, walk us through some of those joint offerings that TCS cloud in h e or delivering. >>Yeah, so far. So far. Thanks. I just want to thank the HP team for giving me the opportunity to up to a larger audience. Andi, This new normal. This is the first time I'm doing an interview like this. Thanks for that experience. Actually, as Jules mentioned, this relationship goes a long way. I am talking about the larger PCs were a long relationship, Andi, specifically on the easiest load we started this journey in a very, very practical way. Five years back it was it was started in a very, very small trial and error basis. We started this relationship RPC explode. But at this point in time after So yes, we have taken this into ah, new norm, actually. So I'll give you a couple of examples. One of the examples We have a very major retailer in Germany, which we work so that it was a $1,000,000 deals. Our busiest on GHB. Yes, you wanna unique offering to the customer s AP and a space on that is really growing a lot. And that's the one offering I would like to tell the audience that really has picked up and spent on the relationship in the German region. Right now we are trying to take that up, offering across on other other regions also, so that is one of the key offerings that we are doing it. The other offerings are multiple offerings we are doing. But again, I want to highlight the storage as a service offering. Great. It's everybody in the industry today, Andi, we are experimenting that in the initial stages in Australia we started in Australia a small offering. And now we are expanding it in the US geography in a big way. And this year we are going to make that as a unique offering. And we're going to offer they're all over cloud customers as a storage as a service offering. Also multiple other offering, Lisa. But I just thought that I like this tool which are making our business. We're making a lot of business together with these two offerings >>is the, uh, s AP opportunity that you mentioned is that the Hana as a service that TCS is delivered? >>That's correct. So it's ah, it's a service. But the uniqueness of that particular offering is we jointly created the architecture so that the customer can use that, like a database as a service model. Right? So it was It was not available that time in the industry so easily like what we offered at that point in time to do enough years back. We offer that particular said we spoke a summer and interestingly, that particular offering the customer was using s AP themselves as a service initially, and they migrated their to us actually from Maybe that's a reason they bought HP and TCS. There is like a summer on this API and a platform. So that's the That's the interesting story under, >>if we didn't do that just a little bit further, I wanted the audience to understand the impact that this partnership has H p E and TCS delivering Hana as a service or your customers. What are the benefits there than what the customer, as you said was doing previously? >>Yeah, yeah, I think I just want to highlight the three or four points that make that this offering very unique, and that helps the customer number one is associated with model. So the customer has got the complete flexibility off going up and down like a true cloud model, right? And so it is a really a unique proposition at that point in time, where the customer not a story about using less for some time and then using more sometimes so it's kind of a complete, flexible model that we offered at the time. Number two is, it's a complete customization is possible. It is not like a fixed architecture. The architecture is so flexible so that the customer business needs can be met through the architectural changes. So it's not like normally people think that lotus highly standardized architecture, right? So that has gone out, and we were given a flexible architecture for the customer. That is the number two number three, obviously the cost end of the day. There's a business case which we need to make it work right for the customer. So obviously, with the PCs and HP coming together, we were able to do the costarred, want age with a customer that is the third advantage of that. The last, but not the least, is the quality of service it is it is all about. I always used to tell my partners that selling is easy. Delivering it is what it's important it is, which will make the customer to stick with you, right? The were given and delivery quality experience who our customer s so that I think that makes a very unique proposition from a technology perspective from a pricing. But but from an architecture and also from the delivery perspective. So those are the few few things I just thought that I violated. >>Excellent. So a couple of words that you mentioned popped into my mind as really even more well, have a different meeting as we're in summer 2020 flexibility and unique offering chills back to you from a go to market perspective. How is that relationship with HP? And he says, changing in the Koven era. >>Yeah, it's pretty interesting, and I would like to call it an example off. You know, what we see is is that you themselves during the corporate times, you know, it also came in the in the pets close to 90% of the workforce. We're 100% productive. Uh, and, uh, they have a plan to go 75% of the employees, you know, go being remote by 2025. Right? So that's the journey they're taking on. And another thing that you notice there's a lot of the, you know, During the corporate times, many of the customers were looking for solutions like virtual desktop infrastructure. So they wanted their employees to be productive, bi directional and in the other area of focus was like a TCP, you know, how do I kind of make sure on the applications are available to you? The customers and also do their internal organizations. So we've seen a lot off. I would say engagement with that is I could picture team and also the solution team toe address This requirements off the market joint >>when we look at certain things that now might even be more important with this new normal, if you will, that the fact that most companies are still in phase one of this work, everyone works from home trying to get to a phase to that might see some some maybe by function groups coming back to the office and then getting to this third. Maybe it's the new nirvana of some hybrid workforce, where there's gonna be some that come back permanently, and some that Don't and Tony Unirea chose, I saw was quoted last month as saying he thinks that 50% of the workforce will only 50% will come back. So in this new not only hybrid I T environment in which your customers love it now, this new pending hybrid workforce environment how are you addressing some of the concerns together with respect to the network connectivity security, >>I will just take the cost anything. It's a very, very interesting at least when we all ended up in this pandemic in March. We really very, very nervous, actually, because everyone has to operate remotely on we are. We are dealing with the customer data. It's ah, it's very, very important that we have a secure environment to access the information and at the same time maintain the integrity of the data and also the quality off the plate. Those other two primary objective for us. We don't want to compromise on quality. We don't want to compromise on security from a cloud perspective. So the solution we have put in really, I just give you one example there was on the airline Ah, UK based the airline industry airline company which they need that workforce overnight. They want everybody to go remote because you know you cape on. They just put up condition that nobody can work from the office overnight and then terror ports as toe work from home purchases, implement the solution for them on our clothes overnight and make that 1000 employees store from home the next day morning. All of them started working with full quality of services and also with a full security aspect of it, has been taken care ornate on the solution. We are deployed. Very interesting case study on The important thing we have done is use the technology to the port. Use all kinds of technology to make sure that the employees that work from home we took care of the network connectivity. We took our eye off the security aspects off the data from security aspects. We've implemented all the security functions from really APIs. But people, Children stop perspective. Andi, make the workforce enable that. But now you are talking about millions off millions of workers going to work from home. Right? Because it is one example for one company we have done that now the easiest themselves has got more than 400 1000 employees. And we are talking about millions off our pores, going to work from home on going forward. So that is I'm seeing this as a big opportunity. It's not that everybody has are just this at this point in time, I'm seeing this as an opportunity where on the cloud easiest cloud kind off. The solution is going to help them to achieve this. And this is a great opportunity for not only for PCs, but also for HP because the solution we're putting together with the HP is more on the digital or course how we can enable the people to work from home, not compromising on as I mentioned from a security you're in from millions perspective. So I'm seeing this as an opportunity for both the organization, and it's a long way to go is we need to work on this. It's not. We don't have a magic want to make the millions off workers to work from home, but it is going to have all soon and probably in the next step. Yeah, so we may achieve this, impair people off. The workforce is going to go remotely on this list. So that's that. And my take on this >>is so the impact that HP and TCS Herb being able to make for customers who have had to massively transform their entire workforce overnight, as he said, to work from home to talk about some of the new maybe new solutions or new business opportunities that HPC is partnering with TCS shells, we'll start with you in this new era, >>Yeah, so if you look at it, I just taking it again on extension off of the projects. What he just mentioned about the percentage of employees going remote Lisa across industries today. I would say less than 20% of the employees are actually working remote or they have the ability. But the organizations have the ability to support the employees going, and if you have to take it to 50% so you can look at the kind of opportunity we have both as HP and as PCs. So we bring in a lot of best in breed infrastructure from for enabling the employee workforce to know where it is. I would say capacity off workloads and it's all workload specific. And what business does this or when people Pretty easy as we kind of bundle that creating a reference architecture or a giant architect picture addressing the customers by industry word. So because one what suits for one vertical may not be really suiting well for a different world, right? For example, if you take a banking sector are playing, a workstation solution would look very different from somebody's doing remote work in retail, so we kind of continuously engage with the PCs, and that's where both of us have joint lab as well, where our technologies and pieces technologies come together, working on joint solutions and assisting the market in terms of the opportunity lights. And we offer this as part of A C is our digital workplace offerings. >>Are your conversations Dr Additional go to you or your conversations when you're jointly selling, changing in terms of who your audience is? Is this now a C level conversation? Since these leaders and we've heard leaders of Google and Facebook already last month saying Work from home extended still 2021. Is this now at the C suite level, where you guys are helping them really understand how to completely change and digitize their entire way of doing business? >>Absolutely. I think it's a great question, and it's actually the opportunity goes beyond the work from home solution. As you rightly I want to know that it is. It is all about digitization. It is all about digitizing their whole business process. It is not anymore infrastructure. Our application solution. It is more about really finding that business process be defending. The way the business is going to operate in future is the discussion we are having so a lot of these discussions are happening at a very, very high level and with the business team also directly so earlier, you used to interact with the technology partners off our organization. But now we are interacting directly with the head of business are the C level except of the company. And that is the reason the exact reason is Ah, you. If you want your ports to be productive remotely, you can't just offer them on network on. You can't offer them just a solution to work from home. But you need to really find your whole business process you need. You need to digitize your infrastructure. You need to digitize your application. You need to rethink your whole process off. You're operating on it, so that's what I'm seeing. It's not only an opportunity for our players like a business cloud, but it is the opportunity for a bigger opportunity for PCs. And it should be not only in terms off on infrastructure in our cloud business, it goes beyond that. So that is that is the kind of an opportunity we're seeing, especially in the in the sectors of healthcare you're seeing major reforms are happening in the healthcare industry as we speak, and obviously manufacturing is going to go through a lot of changes. Also from that. And retail obviously has gone through a lot of changes already in terms of online, uh, stuff, but know that also going to go through changes in this new era? Yes, >>I have to ask you shelled, talking about redefining? That's a word that we've seen so many years in a row at tech conferences, right, this technology redefining this business or that industry. And now, of course, we're being redefined by an invisible virus. But how? How is the sales process being redefined? Is it a lot more accelerated because businesses have to put together new plans to continue operations? >>Yeah, again, a great question. Is this how you have? You know, I would say it's divided by industry body. It's not a uniform thing by, as not British was saying, every industry has got its own, its own set of challenges and its own set of opportunities, and some of them are really actually doing well even in times like and some of them have seen, Really. I mean, like, travel our transportation or you know some of those industries are, and even hospitality that's kind of affected big time. So our view of you know, the entire sales engagement of the processes we're spending more time on there. We really need to focus and which can help improve the businesses. Right? So the conversation's ready from How do I take the cost out in terms of how can I make a little more investment to get greater returns from the business? So it's like it's completely, I would say, an interesting pain and engaging compositions and decisions are happening. So we, if you look at us from an automatic perspective, the Internet to the sales team is armed with various virtual tools like we know you zoom views Skype using SMS teens. So all the tools available to make sure that we're able to connect with all our partners and customers on do enable joint business together. >>I just want oh, I add to it, Lisa, 111 point. I want bad, Really interesting change I'm seeing on the sales is normally we respond to it. I asked from a customer that is a sales happens. I want this many days. Do it and then what you can do with a solution that is a normal sales process. What I have seen that has changed completely. Yes, we go and tell the customer, Is this what you need Actually, to make you yourself your business? Better? This is the new offerings I'm having good. And this offering is going to help you to solve the problem what you are having today. So we are engaging a different level off sales conversation today with our customers. We know the problem of the customer because we are working with them for many years and we know exactly what they're going through. And we also know what new offerings we are having in this. So we are engaging the discussion with the customer doing that. This is my new offering. This is going to help you to solve this problem. But that is a different angle of sales we have seen nowadays they spend on it. >>The last question shells to you. We started our interview today talking about the HP TCS relationship. You talked about how it's evolved. Last question. You talked to me about H B's strategy. How does it match TCS Alfa Cloud offering. >>Yeah, so again, a great question, Lisa, if you look at our strategy, is to accelerate the enterprises with it. Centric and cloud enable solutions which are workload up, optimized and delivered everything as a service. And whatever you heard from Dr Rogers through this entire conversation was about how do we give as a service model you gave an example of honor. You gave an example off, you know, going how optimizing workloads for video and getting employees to be able to be productive remotely and all of that kind of extremely resonate well with, you know, what we see is confined to price. Cloud offering is bringing to the table for the customer and the underlying platform. You know, we kind of elaborate extensively and closely with the easiest architecture. Seem to have the HP portfolio off. You know, the compute and storage portfolio integrated as part of their offering, and we go together to market, you know, and addressing and kind of an ask service model. 1,000,000,000. >>Excellent. Well, shells Dr. Rajesh, pleasure talking with you both today about what UCS and H e are doing together and some of the ways that you're really helping businesses move forward in these uncertain times, we appreciate your time. >>Thank you. Thank you for represents. Thanks. Thank >>you. Dr Rajesh. >>My guest. I'm Lisa Martin. You're watching the Cube's coverage of HP Discover 2020. The virtual experience. Thanks for watching. >>Yeah, yeah, yeah.

Published Date : Jun 23 2020

SUMMARY :

It's the Cube covering HP This is the virtual experience. Talk to our audience about the partnership and how it has evolved to where it is today. Ah, we you know, pretty much enjoyed every single I would say transactions in h e or delivering. also, so that is one of the key offerings that we are doing it. But the uniqueness of that particular offering is we What are the benefits there than what the customer, as you said was doing previously? The architecture is so flexible so that the customer business needs So a couple of words that you mentioned popped into my mind as really even more during the corporate times, you know, it also came in the in the pets close Maybe it's the new nirvana of some hybrid workforce, So the solution we have put in really, I just give you one example there But the organizations have the ability to support the employees suite level, where you guys are helping them really understand how to completely are happening in the healthcare industry as we speak, and obviously manufacturing is going to go I have to ask you shelled, talking about redefining? the Internet to the sales team is armed with various virtual tools like we know you zoom views We know the problem of the customer because we are working with them The last question shells to you. and we go together to market, you know, and addressing and kind of an in these uncertain times, we appreciate your time. Thank you for represents. you. The virtual experience.

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Chellappan Narayanan, HPE & Dr. Rajesh Srinivasan, TCS Cloud | HPE Discover 2020


 

>>from around the globe. It's the Cube covering HP Discover virtual experience brought to you by HP. >>Welcome to the Cube's coverage of HP Discover 2020. This is the virtual experience. I'm Lisa Martin with the Cube, and I'm joined by a couple of guys who were gonna talk through one of HPC ease. Longest partnerships. We've got shells. No Ryan and the senior director Ecosystem sales for North America at HP and Dr Rajesh Boston, the global head of sales and solutions for the TCS. Wow. Gentlemen, welcome to the Cube. >>Thank you. >>So, first question for you, as I mentioned, HP and TCS have been partners for over 30 years. Talk to our audience about the partnership and how it has evolved to where it is today. >>Yeah. Thank you, Lisa. Firstly, you know, I'm pretty excited to be part of this Cube interview with garages. I know. I know him personally for over five years through various interactions globally and this new role for North America. This is our strategy and global system integrator partner. And this is a longstanding partnership between HP and this years has grown multi falls over the last 30 years. We you know, pretty much enjoyed every single I would say transactions or the business engagements, what we've had so far. And we liberate each other for our internal I T requirements and also to drive joint, go to market initiatives across the world. That's making this a truly a 3 60 degree partnership. There is a lot of heritage, a mutual trust and respect between both organizations at all levels and the complimentary offerings. You know what you will hear a lot more in the next couple of questions we bring to the table together are very unique and very differentiating to the clients, which are >>excellent. Dr. Rajesh walk us through some of those joint offerings that TCS cloud in h e or delivering. >>Yeah, so far so far. Thanks. I just want to thank the HP team for giving me the opportunity to off to a larger audience. Andi, This new normal. This is the first time I'm doing an interview like this. Thanks for that experience. Actually, as James mentioned, this relationship goes a long way. I am talking about the larger PCs were a long relationship. Andi, specifically on the easiest flowed. We started this journey in a very, very practical way. Five years back it was it was started in a very, very small trial and error basis. We started this relationship RPC explode. But at this point in time after So yes, we have taken this into, ah, new norm, actually. So I'll give you a couple of examples. One of the examples We have a very major retailer in Germany, which we work so that it was a multi $1,000,000 deals, our busiest on GHB. He has been a unique offering to the customer s AP, and a space on that is really growing a lot. And that's the one offering I would like to tell the audience that really has picked up and spent on the relationship in the German region. Right now we are trying to take that up, offering across on other other regions also, so that is one of the key offerings that we are doing it. The other offerings are multiple offerings we are doing, but again, I want to highlight the storage as a service offering. Great. It's everybody in the industry today, Andi, we are experimenting that in the initial stages in Australia, we started in Australia a small offering. And now we are expanding it in the US geography in a big way. And this year we are going to make that as a unique offering. And we're going to offer they're all over cloud customers as a storage as a service offering. Also, multiple other offering. Lisa. But I just thought that I like this tool which are making our business. We're making a lot of business together with these two offerings >>is the, uh, s AP opportunity that you mentioned is that the Hana as a service that TCS is delivered? >>That's correct. So it's ah, it's a service. But the uniqueness of that particular offering is be jointly created the architecture so that the customer can use that, like a database as a service model. Right? So it was It was not available that time in the industry so easily like what we offered at that point in time to do enough years back. We offer that particular said we spoke a summer and interestingly, that particular offering the customer was using s AP themselves as a service initially, and they migrated their to us actually from Maybe that's a reason they bought HP and PCs. That is like a summer on this API and a platform. So that's the That's the interesting story under, >>if we didn't do that just a little bit further, I wanted the audience to understand the impact that this partnership has H p E and TCS delivering Hana as a service for your customers. What are the benefits there than what the customer, as you said was doing previously? >>Yeah, yeah, I think I just want to relay the three or four points that make that this offering very unique, and that helps the customer number one is associated with model. So the customer has got the complete flexibility off going up and down like a true cloud model, right? And so it is a really a unique proposition at that point in time, where the customer not a story about using less for some time and then using more sometimes. So it's kind of a complete, flexible model that we offered at the time. Number two is, it's a complete customization is possible. It is not like a fixed architecture. The architecture is so flexible so that the customer business needs can be met through the architectural changes. So it's not like normally people think that lotus highly standardized architecture, right? So that has gone out, and we were given a flexible architecture for the customer. That is the number two number three, obviously the cost end of the day. There's a business case which we need to make it work right for the customer. So obviously, with the PCs and HP coming together, we were able to do the costarred, want age with a customer that is the third advantage of that. The last, but not the least, is the quality of service it is it is all about. I always used to tell my partners that selling is easy. Delivering it is what it's important it is, which will make the customer to stick with you, right? The were given and delivery quality experience who our customer s so that I think that makes a very unique proposition from a technology perspective from a pricing, but from an architecture and also from the delivery perspective. So those are the few few things I just thought that I violated. >>Excellent. So a couple of words that you mentioned popped into my mind as really even more well have a different meeting as we're in summer 2020 flexibility and unique. Offering chills back to you from a go to market perspective. How is that relationship with HP? And he says, changing in the Koven era. >>Yeah, it's pretty interesting, and I would like to call it an example off. You know, what we see is is that you themselves during the corporate times, you know, it also came in the pets close to 90% of the workforce. We're 100% productive. Uh, and, uh, they have a plan to go 75% of the employees, you know, but go being remote by 2025. So that's the journey they're taking on. And another thing that you notice there's a lot of the, you know, During the corporate times, many of the customers were looking for solutions like virtual desktop infrastructure. So they wanted their employees to be productive, bi directional and in the other area of focus was like a TCP, you know, how do I kind of make sure on the applications are available to you, the customers and also do their internal organizations? So we've seen a lot off. I would say engagement with that is I could picture team and also the solution team toe address This requirements off the market jointly >>when we look at certain things that now might even be more important with this new normal, if you will, that the fact that most companies are still in phase one of this work, everyone works from home trying to get to a face to that might see some some maybe by function groups coming back to the office and then getting to this third. Maybe it's the new nirvana of some hybrid workforce, where there's gonna be some that come back permanently, and some that Don't and Tony Unirea chose, I saw was quoted last month as saying, I think that 50% of the workforce will only 50% will come back. So in this new not only hybrid I T environment in which your customers love, but now this new pending hybrid workforce environment, how are you addressing some of the concerns together with respect to the network connectivity security, >>I I'll just take the cost anything. It's a very, very interesting at least when we all ended up in this pandemic in March. We really very, very nervous, actually, because everyone has to operate remotely on we are. We are dealing with the customer data. It's ah, it's very, very important that we have a secure environment to access the information and at the same time maintain the integrity of the data and also the quality off the plate. Those other two primary objective for us. We don't want to compromise on quality. We don't want to compromise on security from a cloud perspective. So the solution we have put in really I just give you one example there was on the airline Ah, UK basically are living in the spirit of the company which they need that workforce overnight. They want everybody to go remote because you know you cape on. They just put up a condition that nobody can work from the office overnight on the entire or ports as toe work from home, PTC is implemented the solution for them on our clothes overnight and make that 1000 employees store from home the next day morning all of them started working with the full quality of services and also with a full security aspect of it has been taken care or made on the solution. We are deployed. Very interesting case study on The important thing we have done is use the technology to the poor. Use all kinds of technology to make sure that the employees that work from home we took care of the network connectivity. We took our eye off the security aspects off the data from security aspects. We've implemented all the security functions from a media perspective. Actually stop perspective, Andi. Make the workforce enable that. But now you are talking about millions off millions of workers going to work from home. Right, Because it is one example for one company we have done that note easiest themselves has got more than 400 1000 employees, and we are talking about millions off work force going to work from home on going forward. So that is, I'm seeing this as a big opportunity. It's not that everybody has are just this. At this point in time, I'm seeing this as an opportunity where on the cloud easiest cloud kind off. The solution is going to help them to achieve this, and this is a great opportunity for not only for PCs but also for HP because the solution we're putting together with the HP is more on the digital or course how we can enable the people to work from home, not compromising on as I mentioned from a security you're in from millions perspective. So I'm seeing this as an opportunity for both the organization, and it's a long way to go is we need to work on this. It's not. We don't have a magic want to make the millions off workers to work from home, but it is going to have all soon and probably in the next step. Yeah, so we may achieve this. Impair people's off. The workforce is going to go remotely on this list. So that's that. And my take on this >>is so the impact that HP and TCS herb being able to make for customers who have had to massively transform their entire workforce overnight, as he said, to work from home to talk about some of the new maybe new solutions or new business opportunities that HPC is partnering with TCS shells, we'll start with you in this new era, >>Yeah, so if you look at it, I just taking it again on extension, offered up by just what you just mentioned about the percentage of employees going Lisa across industries today. I would say less than 20% of the employees are actually working remote or they have the ability. But the organizations have the ability to support the employees going, and if you have to take it to 50% so you can look at the kind of opportunity we have both as HP and as PCs. So we bring in a lot of best in breed infrastructure from for enabling the employee workforce to know where it is. I would say capacity off workloads and it's all workload specific. And what business does is over when people pretty easy as we kind of bundle that creating a reference architecture or a giant architect architecture addressing the customers by industry body. So because one what suits for one vertical may not be really suiting well for a different world, right? For example, if you take a banking sector, our traded workstation solution would look very different from somebody's doing remote in a retail. So we kind of continuously engage with the PCs, and that's where both of us have joint lab as well, where our technologies and pieces technologies come together, working on joint solutions and assisting the market in terms of the opportunity lights. And we offer this as part of A C is our digital workplace offerings. >>Are your conversations Dr Additional go to you or your conversations when you're jointly selling, changing in terms of who your audience is? Is this now a C level conversation? Since these leaders and we've heard leaders of Google and Facebook already last month saying Work from home extended still 2021. Is this now at the C suite level, where you guys are helping them really understand how to completely change and digitize their entire way of doing business? >>Absolutely. I think it's a great question, and it's actually the opportunity goes beyond the work from home solution. As you rightly I want to know that it is. It is all about digitization. It is all about digitizing their whole business process. It is not anymore infrastructure. Our application solution. It is more about really finding that business process be defending. The way the business is going to operate in future is the discussion we are having so a lot of these discussions are happening at a very, very high level on with the business team. Also directly, so earlier you used to interact with the technology partners off our organization. But now we are interacting directly with the head of business are the C level except of the company. And that is the reason the exact reason is Ah, you. If you want your ports to be productive remotely, you can't just offer them on network on. You can't offer them just a solution to work from home, But you need to really find your whole business process you need. You need to digitize your infrastructure. You need to digitize your application. You need to rethink your whole process off. You're operating on it, so that's what I'm seeing. It's not only an opportunity for our players like PCs cloud, but it is the opportunity for a bigger opportunity for PCs and be not only in terms off on infrastructure in our cloud business, it goes beyond that. So that is that is the kind of an opportunity we're seeing, especially in the in the sectors of healthcare you're seeing major reforms are happening in the healthcare industry as we speak on, obviously, manufacturing is going to go through a lot of changes. Also from that. And retail obviously has gone through a lot of changes already in terms of online, uh, stuff, but know that also going to goto changes in this new era? Yes, >>I have to ask you shelled talking about redefining? That's a word that we've seen so many years in a row at tech conferences, right, this technology redefining this business or that industry. And now, of course, we're being redefined by an invisible virus. But how is how is the sales process being redefined? Is it a lot more accelerated because businesses have to put together new plans to continue operations? >>Yeah, again, a great question. Is this how you have? You know, I would say it's divided by industry body. It's not a uniform thing. By, as the British was saying, every industry has got its own, its own set of challenges and its own set of opportunities, and some of them are really actually doing well even in times like and some of them have seen, Really. I mean, like, travel our transportation or, you know, some of those industries are and even hospitality that's kind of affected big time. So our view of you know, the entire sales engagement of the processes we're spending more time on there. We really need to focus and which can help improve the businesses. Right? So the conversation's ready from How do I take the cost out in terms of how can I make a little more investment to get greater returns from the business? So it's like it's a completely I would say, an interesting pain and engaging compositions and decisions are happening. So we, if you look at us from an automatic perspective, the sales team is armed with various virtual tools, like We know you zoom views Skype using SMS teens. So all the tools available to make sure that we're able to connect with all our partners and customers on do enable joint business together. >>I just want oh, I add to it, Lisa, 111 point. I want to ride Really interesting change I'm seeing on the sales is normally we respond to ask from a customer that is a sales happens. I want this many days do it and then what you can do with a solution That is the normal sales process. What I have seen that has changed completely. Yes, we go and tell the customer, Is this what you need Actually, to make you yourself your business? Better? This is the new offerings I'm having good. And this offering is going to help you to solve the problem what you are having today. So we are engaging a different level off sales conversation today with our customers. We know the problem of the customer because we are working with them for many years and we know exactly what they're going through. And we also know what new offerings we are having in this. So we are engaging the discussion with the customer doing that. This is my new offering. This is going to help you to solve this problem. But that is a different angle of sales we have seen nowadays in this. A friend of it, >>the last question shells to you. We started our interview today talking about the HP TCS relationship. You talked about how it's evolved. Last question. You talked to me about H B's strategy. How does it match TCS Alfa Cloud offering? >>Yeah, so again, a great question, Lisa, if you look at our strategy is to accelerate the enterprises with it. Centric and cloud enable solutions which are workload optimized and delivered everything as a service. And whatever you heard from Dr Rogers through this entire conversation was about how do we give as a service model you gave an example of Hana? You give an example off, you know, going optimizing workloads for VD I and getting employees to be able to be productive remotely and all of that kind of extremely resonate well with you know, what pieces are defined to. Price cloud offering is bringing to the table for the customer and the underlying platform. You know, we can have yeah, extensively and closely with the easiest architecture being tohave the HP portfolio off. You know, the compute and storage portfolio integrated as part of their offering, and we go together to market, you know, addressing and kind of an ask service model. 1,000,000,000. >>Excellent. Well, shells Dr Rajesh, pleasure talking with you both today about what UCS and H e are doing together in some of the ways that you're really helping businesses move forward in these uncertain times, we appreciate your time. >>Thank you. Thank you. For instance. Thanks. >>Thank you. Dr Rajesh. >>My guest. I'm Lisa Martin. You're watching the Cube's coverage of HP Discover 2020. The virtual experience. Thanks for watching. >>Yeah, Yeah, yeah, yeah, yeah.

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Chris Betz & Chris Smith, CenturyLink | RSAC USA 2020


 

>>live from San Francisco. It's the queue covering our essay conference 2020 San Francisco Brought to you by Silicon Angle Media >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're in our 2020 the biggest security conference in the country, if not the world. I guess there's got to be 50,000 people. We'll get the official word tomorrow. It's our sixth year here and we're excited to be back. I'm not sure why. It's 2020. We're supposed to know everything at this point in time with the benefit on inside. We got two people that do. You know a lot. We're excited to have him. My left is Chris Bets is the SVP and chief security officer for Centurylink. Chris, Great to see you. And to his left is Chris Smith, VP Global security Services for Centurylink. Welcome. >>Thank you for having me. >>Absolutely. You guys just flew into town >>just for the conference's great To be here is always a really exciting space with just a ton of new technology coming out. >>So let's just jump into it. What I think is the most interesting and challenging part of this particular show we go to a lot of shows you 100 shows a year. I don't know that there's one that's got kind of the breadth and depth of vendors from the really, really big the really, really small that you have here. And, you know, with the expansion of Moscone, either even packing more women underneath Howard Street, what advice do you give to people who are coming here for the first time? Especially on more than the buyer side as to how do you navigate this place >>when I when I come here and see So I'm always looking at what the new technologies are. But honestly, having a new technology is not good enough. Attackers are coming up with new attacks all the time. The big trick for me is understanding how they integrate into my other solutions. So I'm not so I'm not just focused on the technology. I'm focused on how they all fit together. And so the vendors that have solutions that fit together that really makes a difference in my book. So I'm looking for for products that are designed to work with each other, not just separate >>from a practice standpoint. The theme of IRA say this year is the human element, and for us, if you look at this floor, it's overwhelming. And if you're a CSO of an average enterprise, it's hard to figure out what you need to buy and how to build a practice with all of the emerging tools. So for us core to our practice, I think any mature, 30 security practices having a pro services capability and consulting capability that can be solved this all together, that helps you understand what to buy, what things to piece together and how to make it all work >>right. And it's funny, the human element that is the kind of the global theme. And what's funny is for all the technology it sounds like. Still, the easiest way in is through the person, whether it's a phishing attack or there's a myriad of ways that people are getting him to the human. So that's kind of a special challenge or trying to use technology to help people do a better job. At the end of the day, sometimes you're squishy ISS or easier access point is not a piece of technology, but it's actually a person. It's >>often because We asked people to do the wrong things. We're having them. Focus on security steps. Use email. Security is an easy to grasp example way all go through training every year to teach folks how to make sure that they avoid clicking on the wrong emails for us more often than a year. So the downside of that is arresting people to take a step away from their job and try to figure out how to protect themselves. And is this a bad emails that are really focusing on the job? So that's why it's so important to me to make sure that we've got solutions that help make the human better and frankly, even worse in security. We don't have the staff that we need. And so how do we help Make sure that the right tools are there, that they work together. They automate because asking everybody to take those steps, it's just it's a recipe for disaster because people are going to make mistakes >>right? Let's go a little deeper into the email thing. A friend of mines and commercial real estate, and he was describing an email that he got from his banker describing a wire transfer from one of his suppliers that he has a regular, ongoing making relationship with. You know, it's not the bad pronunciation and bad grammar and kind of the things that used to jump out is an obvious. But he said it was super good to the point where thankfully, you know, it was just this time. But, you know, he called the banker like, did you just send me this thing? So you know where this as the sophistication of the bad guys goes up specifically targeting people, how do you try to keep up with how do you give them the tools to know Woe versus being efficient? I'm trying to get my job done. >>Yeah, for me, it starts with technology. That takes a look. We've only got so many security practitioners in the company. Actually. Defend your email example. We've got to defend every user from those kinds of problems. And so how do I find technology solutions that help take the load off security practitioners so they can focus on the niche examples that really, really well crafted emails and help take that load off user? Because users just not gonna be able to handle that right? It's not fair to ask them. And like you said, it was just poorly time that helped attack. So how do we help? Make sure that we're taking that technology load off, identify the threats in advance and protect them. And so I think one of the biggest things that Chris and I talk a lot about is how to our solutions help make it easier for people to secure themselves instead of just providing only technology technology advantage, >>our strategy for the portfolio and it sort of tied to the complexity. CN This floor is simplicity. So from our perspective, our goal is a network service provider is to deliver threat free traffic to our customers even before it gets to the human being. And we've got an announcement that we launched just a week ago in advance of the show called Rapid Threat Defense. And the idea is to take our mature threat Intel practice that Chris has a team of folks focused on that. We branded black Lotus labs and Way built a machine learning practice that takes all the bad things that we see out in the network and protects customers before it gets to their people. >>So that's an interesting take. You have the benefit of seeing a lot of network traffic from a lot of customers and not just the stuff that's coming into my building. So you get a much more aggregated approach, so tell us a little bit more about that. And what is the Black Lotus Labs doing? And I'm also curious from an industry point of view, you know, it's just a collaboration with the industry cause you guys are doing a lot of traffic. There's other big network providers carrying a lot of traffic. How well do you kind of work together when you identify some nasty new things that you're doing the horizon? And where do you draw the line between better together versus still independent environment? >>When we're talking about making the Internet safer, it's not really to me a lot about competitive environment. It's really about better together. That's one of things I love about the security community. I'm sure you see it every year when you're here. You're talking security practitioners how across every industry security folks work together to accomplish something that's meaningful. So as the largest world's largest global I P we get to see a ton of traffic, and it's really, really interesting we'll be able to put together, you know, at any given point in time. We're watching many tens of thousands of probable malware networks. We're protecting our customers from that. But we're also able to ourselves take down nearly 65 now where networks every month just knock them off the Internet. So identify the command and control, and we take it off the Internet. We work with our partners. We go talk to hosting providers, maybe competitors of ours. And we say, Hey, here's a bad, bad actors bad server that's being used to control now where? Going shut it down. And so the result of that is not only protecting our customers, but more importantly, protecting tens of thousands of customers every month. By removing now where networks that were attacking, that really makes a difference. To me, that's the biggest impact we bring. And so it really is a better together. It's a collaboration story and, of course, for said, we get the benefit of that information as we're developing it as we're building it, we can protect our customers right away while we're building the confidence necessary to take something as dramatic and action as shutting down on our network. Right. Unilaterally, >>Citrix. I was gonna ask you kind of the impact of I o t. Right in this in this crazy expansion of the tax services, when you hear about all the time with my favorite example, somebody told the story of attacking a casino through the connected thermometer in the fish tank in the lobby, which may or may not be true, is still a great story. Great story. But I'm curious, you know, looking at the network, feeding versus the devices connecting that's really in an interesting way to attack this proliferation of attack services. You're getting it before it necessarily gets to all these new points of presence doing it based on the source. For >>us, that's the only way to make it scalable. It is true that automation blocking it before it gets to the azure to a device. It is what will create simplicity and value for our customers. >>Right on the other piece of the automation. Of course, that we hear about all the time is there just aren't enough security professionals, period. So if you don't have the automation. You don't have the machine learning, as you said, to filter low hanging fruit and the focus your resource. If they need to be, you're not going to do it. The bad news is the bad guys, similar tools. So as you look at kind of the increase in speed of automation, the increase in automated connectivity between these devices making decisions amongst each other, how do you see that kind of evolving? But you're kind of role and making sure you stay a step ahead of the bad guys. For >>me, it's not about just automation. It's about allowing smart people to put their brains against hard problems, hard impactful problems and so on. So simply automating is not enough. It's making sure that automation is reducing the the load on people so that they're able to focus on those hard, unique problems really solve all those solutions and, yes, Attackers, Attackers build automation as well. And so if we're not building faster and better than we're falling behind, so like every other part of this race, it's about getting better, faster and why it's so important that technology work together because we're constantly throwing out more tools and if they don't work better together, even if we got incremental automation, these place way still miss overall because it's end to end that we need to defend ourselves and our customers >>layered on what he said. For the foreseeable future, you're gonna need smart security people that help protect your practice. Our goal in automation is take the road tasks out of out of the gate. They live so they can focus on the things that provide the most value protecting their enterprise. >>Right when you're looking, you talked about making sure things work together, for you talked about making sure things work together. How do you decide what's kind of on the top of the top of the stack, where everybody wants to own the single pane of glass? Everybody wants to be the control plane. Everybody wants to be that thing that's on your computer all the time, which is how you work your day to day. How do you kind of dictate what are the top level tools while still going out? And, he said, exploring some of these really cutting edge things out around the fringe, which don't necessarily have a full stack solution that you're going to rely on but might have some cool kind of point solutions if you will, or point products to help you plug some new and emerging holes. Yeah, >>yeah. So for us, yeah, we take security capabilities and we build them into the other things that we sell. So it's not a bolt on. So when you buy things from us, whether whether it's bandwidth or whether its SD wan and security comes baked in, so it's not something you have to worry about integrating later. It's an ingredient of the things that we sell in all of the automation that we build is built into our practice, So it's simple for our customers to understand, like, simple and then layered. On top of that, we've got a couple different ways that we bring pro services and consulting to our practice. So we've got a smart group of folks that could lean into staff, augment and sit on site, do just about anything to help customers build a practice from day zero to something more mature. But now we're toying with taking those folks in building them into products and services that we sell for 10 or 20 hours a month as an ingredient. So you get that consulting wrapper on top of the portfolio that we sell as a service provider. >>Get your take on kind of budgets and how people should think about their budgets. And when I think of security, I can't help but think of like insurance because you can't spend all your money on security. But you want to spend the right amount on security. But at the end of the day, you can't be 100% secure, right? So it's kind of kind of working the margins game, and you have to make trade offs in marketing, wants their money and product development, wants their money and sales, wants their money. So what people are trying to assess kind of the risk in their investment trade offs. What are some of the things they should be thinking about to determine what is the proper investment on security? Because it can't just be, you know, locker being 100% it's not realistic, and then all the money they help people frame that. >>Usually when companies come to us in, Centurylink plays in every different segment, all the way down to, you know, five people company all the way to the biggest multinationals on the planet. So that question is, in the budget is a little bit different, depending on the type of customer, the maturity and the lens are looking at it. So, typically, way have a group of folks that we call security account managers those our consultants and we bring them in either in a dedicated or a shared way. Help companies that's us, wear their practices today in what tool sets for use again things that they need to purchase and integrate to get to where they need to be >>really kind of a needs analysis based on gaps as much as anything else. >>That's part of the reason why we try to build prisons earlier, so many of the technologies into our solution so that so that you buy, you know, SD wan from us, and you get a security story is part of it is that that allows you to use the customer to save money and really have one seamless solution that provides that secure experience. We've been building firewalls and doing network based security for going on two decades now, in different places. So at this point, that is a good place that way, understand? Well, we can apply automation against it. We can dump, tail it into existing services and then allow focused on other areas of security. So it helps. From a financial standpoint, it also helps customers understand from where they put their talent. Because, as you talked about, it's all about talents even more so than money. Yes, we need to watch our budgets. But if you buy these tools, how do you know about the talent to deploy them? And easier You could make it to do that simpler. I think the better off right >>typical way had the most success selling security practices when somebody is either under attacker compromised right, then the budget opens right up, and it's not a problem anymore. So we thought about how to solve that commercially, and I'll just use Vitas is an example. We have a big D dos global DDOS practice that's designed to protect customers that have applications out on the Internet that are business critical, and if they go down, whether it's an e commerce or a trading site losing millions of dollars a day, and some companies have the money to buy that up front and just have it as a service. And some companies don't purchase it from us until they're under attack. And the legacy telco way of deploying that service was an order and a quote. You know, some days later, we turned it up. So we've invested with Christine the whole orchestration layer to turn it up in minutes and that months so you can go to our portal. You can enter a few simple commercial terms and turn it on when you need it. >>That's interesting. I was gonna ask you kind of how has cloud kind of changed the whole go to market and the way people think about it. And even then you hear people have stuff that's secure in the cloud, but they mis configured a switch left something open. But you're saying, too it enables you to deploy in a very, very different matter based on you know, kind of business conditions and not have that old, you know, get a requisite get a p o requisition order, install config. Take on another kind of crazy stuff. Okay, so before I let you go, last question. What are your kind of priorities for this show for Centurylink when it's top of mind, Obviously, you have the report and the Black Lotus. What do you guys really prioritizing for this next week? Here for Cisco. >>We're here to help customers. We have a number of customers, a lot of learning about our solutions, and that's always my priority. And I mentioned earlier we just put out a press release for rapid threat defense. So we're here to talk about that, and I think the industry and what we're doing this little bit differently. >>I get to work with Chris Motions Week with customers, which is kind of fun. The other part that I'm really excited about, things we spent a bunch of time with partners and potential partners. We're always looking at how we bring more, better together. So one of the things that we're both focused on is making sure that we're able to provide more solutions. So the trick is finding the right partners who are ready to do a P I level integration. The other things that Chris was talking about that really make this a seamless and experience, and I think we've got a set of them that are really, really interested in that. And so those conversations this week will be exceptionally well, I think that's gonna help build better technology for our customers even six months. >>Alright, great. Well, thanks for kicking off your week with the Cube and have a terrific week. Alright. He's Chris. He's Chris. I'm Jeff. You're watching the Cube. Where? The RSA Conference in downtown San Francisco. Thanks for watching. See you next time. >>Yeah, yeah.

Published Date : Feb 26 2020

SUMMARY :

our essay conference 2020 San Francisco Brought to you by Silicon We're in our 2020 the biggest security You guys just flew into town just for the conference's great To be here is always a really exciting space with just a ton of new technology Especially on more than the buyer side as to how do you navigate this place So I'm not so I'm not just focused on the technology. an average enterprise, it's hard to figure out what you need to buy and how to build And it's funny, the human element that is the kind of the global theme. So the downside of that is arresting people to take So you know where this as the sophistication of the bad guys goes up specifically And so I think one of the biggest things that Chris and I talk a lot about is how to our solutions And the idea is to take our mature threat Intel practice that Chris has a team of folks And I'm also curious from an industry point of view, you know, it's just a collaboration with the industry cause you So identify the command and control, and we take it off the Internet. I was gonna ask you kind of the impact of I o t. Right in this in this crazy expansion of the the azure to a device. You don't have the machine learning, as you said, to filter low hanging fruit and the focus the the load on people so that they're able to focus on those hard, take the road tasks out of out of the gate. cool kind of point solutions if you will, or point products to help you plug some new It's an ingredient of the things that we sell in all of the automation that we build is built into But at the end of the day, you can't be 100% secure, all the way down to, you know, five people company all the way to the biggest multinationals on the planet. into our solution so that so that you buy, you know, and some companies have the money to buy that up front and just have it as a service. I was gonna ask you kind of how has cloud kind of changed the whole go And I mentioned earlier we just put out a press release So one of the things that we're both focused on is making sure that we're able to See you next time.

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Tony Higham, IBM | IBM Data and AI Forum


 

>>live from Miami, Florida It's the Q covering IBM is data in a I forum brought to you by IBM. >>We're back in Miami and you're watching the cubes coverage of the IBM data and a I forum. Tony hi. Amiss here is a distinguished engineer for Ditch the Digital and Cloud Business Analytics at IBM. Tony, first of all, congratulations on being a distinguished engineer. That doesn't happen often. Thank you for coming on the Cube. Thank you. So your area focus is on the B I and the Enterprise performance management space. >>Um, and >>if I understand it correctly, a big mission of yours is to try to modernize those make himself service, making cloud ready. How's that going? >>It's going really well. I mean, you know, we use things like B. I and enterprise performance management. When you really boil it down, there's that's analysis of data on what do we do with the data this useful that makes a difference in the world, and then this planning and forecasting and budgeting, which everyone has to do whether you are, you know, a single household or whether you're an Amazon or Boeing, which are also some of our clients. So it's interesting that we're going from really enterprise use cases, democratizing it all the way down to single user on the cloud credit card swipe 70 bucks a month >>so that was used to be used to work for Lotus. But Cognos is one of IBM's largest acquisitions in the software space ever. Steve Mills on his team architected complete transformation of IBM is business and really got heavily into it. I think I think it was a $5 billion acquisition. Don't hold me to that, but massive one of the time and it's really paid dividends now when all this sort of 2000 ten's came in and said, Oh, how Duke's gonna kill all the traditional b I traditional btw that didn't happen, that these traditional platforms were a fundamental component of people's data strategies, so that created the imperative to modernize and made sure that there could be things like self service and cloud ready, didn't it? >>Yeah, that's absolutely true. I mean, the work clothes that we run a really sticky were close right when you're doing your reporting, your consolidation or you're planning of your yearly cycle, your budget cycle on these technologies, you don't rip them out so easily. So yes, of course, there's competitive disruption in the space. And of course, cloud creates on opportunity for work loads to be wrong, Cheaper without your own I t people. And, of course, the era of digital software. I find it myself. I tried myself by it without ever talking to a sales person creates a democratization process for these really powerful tools that's never been invented before in that space. >>Now, when I started in the business a long, long time ago, it was called GSS decision support systems, and they at the time they promised a 360 degree view with business That never really happened. You saw a whole new raft of players come in, and then the whole B I and Enterprise Data Warehouse was gonna deliver on that promise. That kind of didn't happen, either. Sarbanes Oxley brought a big wave of of imperative around these systems because compliance became huge. So that was a real tailwind for it. Then her duke was gonna solve all these problems that really didn't happen. And now you've got a I, and it feels like the combination of those systems of record those data warehouse systems, the traditional business intelligence systems and all this new emerging tech together are actually going to be a game changer. I wonder if you could comment on >>well so they can be a game changer, but you're touching on a couple of subjects here that are connected. Right? Number one is obviously the mass of data, right? Cause data has accelerated at a phenomenal pace on then you're talking about how do I then visualize or use that data in a useful manner? And that really drives the use case for a I right? Because A I in and of itself, for augmented intelligence as we as we talk about, is only useful almost when it's invisible to the user cause the user needs to feel like it's doing something for them that super intuitive, a bit like the sort of transition between the electric car on the normal car. That only really happens when the electric car can do what the normal car can do. So with things like Imagine, you bring a you know, how do cluster into a B. I solution and you're looking at that data Well. If I can correlate, for example, time profit cost. Then I can create KP eyes automatically. I can create visualizations. I know which ones you like to see from that. Or I could give you related ones that I can even automatically create dashboards. I've got the intelligence about the data and the knowledge to know what? How you might what? Visualize adversity. You have to manually construct everything >>and a I is also going to when you when you spring. These disparage data sets together, isn't a I also going to give you an indication of the confidence level in those various data set. So, for example, you know, you're you're B I data set might be part of the General ledger. You know of the income statement and and be corporate fact very high confidence level. More sometimes you mention to do some of the unstructured data. Maybe not as high a confidence level. How our customers dealing with that and applying that first of all, is that a sort of accurate premise? And how is that manifesting itself in terms of business? Oh, >>yeah. So it is an accurate premise because in the world in the world of data. There's the known knowns on the unknown knowns, right? No, no's are what you know about your data. What's interesting about really good B I solutions and planning solutions, especially when they're brought together, right, Because planning and analysis naturally go hand in hand from, you know, one user 70 bucks a month to the Enterprise client. So it's things like, What are your key drivers? So this is gonna be the drivers that you know what drives your profit. But when you've got massive amounts of data and you got a I around that, especially if it's a I that's gone ontology around your particular industry, it can start telling you about drivers that you don't know about. And that's really the next step is tell me what are the drivers around things that I don't know. So when I'm exploring the data, I'd like to see a key driver that I never even knew existed. >>So when I talk to customers, I'm doing this for a while. One of the concerns they had a criticisms they had of the traditional systems was just the process is too hard. I got to go toe like a few guys I could go to I gotta line up, you know, submit a request. By the time I get it back, I'm on to something else. I want self serve beyond just reporting. Um, how is a I and IBM changing that dynamic? Can you put thes tools in the hands of users? >>Right. So this is about democratizing the cleverness, right? So if you're a big, broad organization, you can afford to hire a bunch of people to do that stuff. But if you're a startup or an SNB, and that's where the big market opportunity is for us, you know, abilities like and this it would be we're building this into the software already today is I'll bring a spreadsheet. Long spreadsheets. By definition, they're not rows and columns, right? Anyone could take a Roan Collin spreadsheet and turn into a set of data because it looks like a database. But when you've got different tabs on different sets of data that may or may not be obviously relatable to each other, that ai ai ability to be on introspect a spreadsheet and turn into from a planning point of view, cubes, dimensions and rules which turn your spreadsheet now to a three dimensional in memory cube or a planning application. You know, the our ability to go way, way further than you could ever do with that planning process over thousands of people is all possible now because we don't have taken all the hard work, all the lifting workout, >>so that three dimensional in memory Cuba like the sound of that. So there's a performance implication. Absolutely. On end is what else? Accessibility Maw wraps more users. Is that >>well, it's the ability to be out of process water. What if things on huge amounts of data? Imagine you're bowing, right? Howdy, pastors. Boeing How? I don't know. Three trillion. I'm just guessing, right? If you've got three trillion and you need to figure out based on the lady's hurricane report how many parts you need to go ship toe? Where that hurricane reports report is you need to do a water scenario on massive amounts of data in a second or two. So you know that capability requires an old lap solution. However, the rest of the planet other than old people bless him who are very special. People don't know what a laugh is from a pop tart, so democratizing it right to the person who says, I've got a set of data on as I still need to do what if analysis on things and probably at large data cause even if you're a small company with massive amounts of data coming through, people click. String me through your website just for example. You know what if I What if analysis on putting a 5% discount on this product based on previous sales have that going to affect me from a future sales again? I think it's the democratizing as the well is the ability to hit scale. >>You talk about Cloud and analytics, how they've they've come together, what specifically IBM has done to modernize that platform. And I'm interested in what customers are saying. What's the adoption like? >>So So I manage the Global Cloud team. We have night on 1000 clients that are using cloud the cloud implementations of our software growing actually so actually Maur on two and 1/2 1000. If you include the multi tenant version, there's two steps in this process, right when you've got an enterprise software solution, your clients have a certain expectation that your software runs on cloud just the way as it does on premise, which means in practical terms, you have to build a single tenant will manage cloud instance. And that's just the first step, right? Because getting clients to see the value of running the workload on cloud where they don't need people to install it, configure it, update it, troubleshoot it on all that other sort of I t. Stuff that subtracts you from doing running your business value. We duel that for you. But the future really is in multi tenant on how we can get vast, vast scale and also greatly lower costs. But the adoptions been great. Clients love >>it. Can you share any kind of indication? Or is that all confidential or what kind of metrics do you look at it? >>So obviously we look, we look a growth. We look a user adoption, and we look at how busy the service. I mean, let me give you the best way I can give you is a is a number of servers, volume numbers, right. So we have 8000 virtual machines running on soft layer or IBM cloud for our clients business Analytics is actually the largest client for IBM Cloud running those workloads for our clients. So it's, you know, that the adoption has been really super hard on the growth continues. Interestingly enough, I'll give you another factoid. So we just launched last October. Cognos Alex. Multi tenant. So it is truly multi infrastructure. You try, you buy, you give you credit card and away you go. And you would think, because we don't have software sellers out there selling it per se that it might not adopt as much as people are out there selling software. Okay, well, in one year, it's growing 10% month on month cigarette Ally's 10% month on month, and we're nearly 1400 users now without huge amounts of effort on our part. So clearly this market interest in running those softwares and then they're not want Tuesdays easer. Six people pretending some of people have 150 people pretending on a multi tenant software. So I believe that the future is dedicated is the first step to grow confidence that my own premise investments will lift and shift the cloud, but multi tenant will take us a lot >>for him. So that's a proof point of existing customer saying okay, I want to modernize. I'm buying in. Take 1/2 step of the man dedicated. And then obviously multi tenant for scale. And just way more cost efficient. Yes, very much. All right. Um, last question. Show us a little leg. What? What can you tell us about the road map? What gets you excited about the future? >>So I think the future historically, Planning Analytics and Carlos analytics have been separate products, right? And when they came together under the B I logo in about about a year ago, we've been spending a lot of our time bringing them together because, you know, you can fight in the B I space and you can fight in the planning space. And there's a lot of competitors here, not so many here. But when you bring the two things together, the connected value chain is where we really gonna win. But it's not only just doing is the connected value chain it and it could be being being vice because I'm the the former Lotus guy who believes in democratization of technology. Right? But the market showing us when we create a piece of software that starts at 15 bucks for a single user. For the same power mind you write little less less of the capabilities and 70 bucks for a single user. For all of it, people buy it. So I'm in. >>Tony, thanks so much for coming on. The kid was great to have you. Brilliant. Thank you. Keep it right there, everybody. We'll be back with our next guest. You watching the Cube live from the IBM data and a I form in Miami. We'll be right back.

Published Date : Oct 23 2019

SUMMARY :

IBM is data in a I forum brought to you by IBM. is on the B I and the Enterprise performance management How's that going? I mean, you know, we use things like B. I and enterprise performance management. so that created the imperative to modernize and made sure that there could be things like self service and cloud I mean, the work clothes that we run a really sticky were close right when you're doing and it feels like the combination of those systems of record So with things like Imagine, you bring a you know, and a I is also going to when you when you spring. that you know what drives your profit. By the time I get it back, I'm on to something else. You know, the our ability to go way, way further than you could ever do with that planning process So there's a performance implication. So you know that capability What's the adoption like? t. Stuff that subtracts you from doing running your business value. or what kind of metrics do you look at it? So I believe that the future is dedicated What can you tell us about the road map? For the same power mind you write little less less of the capabilities and 70 bucks for a single user. The kid was great to have you.

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Jon Roskill, Acumatica & Melissa Di Donato, SUSE | IFS World 2019


 

>> Announcer: Live from Boston, Massachusetts, it's theCube. Covering IFS World Conference 2019. Brought to you by IFS. >> Welcome back to Boston everybody you're watching theCube, the leader in live tech coverage. This is day one of the IFS World Conference. I'm Dave Vallante with my co-host Paul Gillen. Melissa Di Donato is here, she's the CEO of SUSE and Jon Roskill is the CEO of Acumatica. Folks, welcome to theCube. >> Thank you so much. >> So you guys had the power panel today? Talking about digital transformation. I got a question for all of you. What's the difference between a business and a digital business? Melissa, I'll give you first crack. >> Before a regular old business and a digital business? Everyone's digital these days, aren't they? I was interviewing the, one of the leaders in Expedia and I said, "Are you a travel company "or are you a digital company? "Like where do you lead with?" And she said to me, "No no, we're a travel company "but we use digital." So it seems like the more and more we think about what the future means how we service our customers, customers being at the core everyone's a digital business. The way you service, the way you communicate the way you support. So whether you're a business or none you're always got to be a digital business. >> You better be a digital business and so-- >> I'm going to take a slightly different tact on that which is, we talk about digital and analog businesses and analog businesses are ones that are data silos they have a lot of systems, so they think they're digital but they're disconnected. And, you know, part of a transformation is connecting all the systems together and getting them to work like one. >> But I think the confict other common thread is data, right? A digital business maybe puts data at the core and that's how they get competitive advantage but, I want to ask you guys about your respective businesses. So SUSE, obviously you compete with the big whale RedHat, you know, the big news last year IBM $34 billion. How did that or will that in your view affect your business? >> It's already affecting our business. We've seen a big big uptake in interest in SUSE and what we're doing. You know, they say that a big part of the install based customers that RedHat and IBM currently have are unhappy about the decision to be acquired by IBM. Whether they're in conflict because we're a very big heavily channel business, right? So a lot of the channel partners are not quite happy about having one of their closest competitors now be, you know, part of the inner circle if you will. And other customers are just not happy. I mean, RedHat had fast innovation, fast pace and thought leadership and now all of a sudden they're going to be buried inside of a large conglomerate and they're not happy about that. So when we look at what's been happening for us particularly since March, we became an independent company now one of the world's largest independent open source company in the world. Since IBM has been taking over from RedHat. And, you know, big big uptake. Since March we became independent we've been getting a lot of questioning. "Where are we, where are we going, what are we doing?" And, " Hey, you know, I haven't heard about SUSE a while "what are you doing now?" So it's been really good news for us really, really good news. >> I mean, we're huge fans of RedHat. We do a lot of their events and-- >> Melissa: I'm a huge fan myself. >> But I tell you, I mean, we know from first hand IBM has this nasty habit of buying companies tripling the price. Now they say they're going to leave RedHat alone, we'll see. >> Yeah, like they said they'd leave Lotus alone and all the others. >> SPSS, you saw that, Ustream, you know one of our platforms. >> What's your view, how do you think it's going to go? >> I don't think it's about cloud I think it's about services and I think that's the piece that we don't really have great visibility on. Can IBM kind of jam OpenShift into its customers you know, businesses without them even really knowing it and that's the near-term cash flow play that they're trying to, you know, effect. >> Yeah, but it's not working for them, isn't though? Because when you look at the install base 90% of their business it's been Linux open source environment and OpenShift is a tag-along. I don't know if that's a real enabler for the future rather than, you know, an afterthought from the past. >> Well, for $34 billion it better be. >> I want to ask you about the cost of shifting because historically, you know if you were IBM, you were stuck with IBM forever. What is involved in customers moving from RedHat to SUSE presumably you're doing some of those migrations style. >> We are, we are doing them more and more in fact, we're even offering migration services ourself in some applications. It depends on the application layer. >> How simple is that? >> It depends on the application. So, we've got some telco companies is very very complex 24/7, you know, high pays, big fat enterprise applications around billing, for example. They're harder to move. >> A lot of custom code. >> A lot of custom code, really deep, really rich they need, you know, constant operation because it's billing, right? Big, fat transactions, those are a little bit more complex than say, the other applications are. Nonetheless, there is a migration path and in fact, we're one of the only open source companies in the world that provides support for not just SUSE, but actually for RedHat. So, if you're a RedHat, for or a well customer that want to get off an unsupported version of RedHat you can come over to SUSE. We'll not just support your RedHat system but actually come up with a migration plan to get you into a supported version of SUSE. >> If it's a package set of apps and you have to freeze the code it's actually not that bad-- >> It's not that bad, no. >> To migrate. All right, Jon I got to ask you, so help us understand Acumatica and IFS and the relationship you're like sister companies, you both the ERP providers. How do you work together or? >> Yeah, so we're both owned by a private equity firm called EQT. IFS is generally focused on $500 million and above company so more enterprise and we're focused on core mid-market. So say, $20 million to $500 million. And so very complementary in that way. IFS is largely direct selling we're a 100% through channels. IFS is stronger in Europe, we're stronger in North America and so they see these as very complementary assets and rather than to, perhaps what's going on with the IBM, RedHat discussion here. Slam these big things together and screw them up they're trying to actually keep us independent. So they put us in a holding company but we're trying to leverage much of each other's goodness as we can. >> Is there a migration path? I mean, for customers who reach the top end of your market can they smoothly get to IFS? >> Yeah, it's not going to be like a smooth you know, turn a switch and go. But it absolutely is a migration option for customers and we do have a set of customers that are outgrowing us you know, we have a number of customers now over a billion dollars running on Acumatica and you know, for a company, we've got one that we're actually talking to about this right now operating in 41 countries global, they need 24/7 support we're not the right company to be running their ERP system. >> On your panel today guys you were talking about, a lot about digital transformations kind of lessons learned. What are the big mistakes you see companies making and kind of what's your roadmap for success? >> I think doing too much too fast. Everyone talks about the digital innovation digital transformation. It's really a business transformation with digital being the underpinning the push forward that carries the business forward, right? And I think that we make too many mistakes with regards to doing too much, too fast, too soon, that's one. Doing and adopting technology for technology's sake. "Oh, it's ML, it's AI." And everyone loves these big buzz words, right? All the code words for what technology is? So they tend to bring it on but they don't really know the outcome. Really really important at SUSE were absolutely obsessed with our customers and during a digital transformation if you remain absolutely sick of anything about your customer at the core of every decision you make and everything you do. Particularly with regards to digital transformation you want to make sure that business outcome is focused on them. Having a clear roadmap with milestones along the journey is really important and ensuring it's really collaborative. We talked this morning about digital natives you know, we're all young, aren't we? Me in particular, but, you know I think the younger generation of digital natives think a little bit differently perhaps than we were originally thinking when we were their age. You know, I depend on that thinking I depend on that integration of that thought leadership infused into companies to help really reach customers in different ways. Our customers are buying differently our customers have different expectations they have different deliverables they require and they expect to be supported in different way. And those digital natives, that young talent can really aid in that delivery of good thought leadership for our businesses. >> So Jon, we're seeing IT spending at the macro slow down a little bit. You know, a lot of different factors going on it's not a disaster, it's not falling off the cliff but definitely pre-2018 levels and one of the theories is that you had this kind of spray-and-pray kind of like Melissa was say, deal was going too fast trying everything and now we're seeing more of a narrow focus on things that are going to give a return. Do you see that happening out there? >> Yeah, definitely some, I mean people are looking for returns even in what's been a really vibrant economy but, you know, I agree with Melissa's point there's a lot of ready, shoot, aim projects out there and, you know, the biggest thing I see is the ones that aren't, the fail that aren't the ones that aren't led by the leadership. They're sort of given off to some side team often the IT team and said, "Go lead digital transformation of the company." And digital transformation you know, Melissa said this morning it's business transformation. You've got to bring the business part of it to the table and you've got to think about, it's got to be led by the CEO or the entire senior leadership team has to be on board and if not, it's not going to be successful. >> So, pragmatism would say, okay, you get some quick hits get some wins and then you got kind of the, you know, Bezos, Michael Dell mindset go big or go home, so what's your philosophy? Moonshots or, you know, quick hits? >> I always think starting you know, you've got to understand your team's capabilities. So starting is something that you can get a gauge of that you know, particularly if you're new and you're walking into an organization, you know. Melissa, I don't know how long you've been in your role now? >> Melissa: 65 days. >> Right, so there you go. So it's probably a good person to ask what, you know, what you're finding out there but I think, you know, getting a gauge of what your resources are. I mean, one of the things you see around here is there are, you know, dozens of partner firms that are, or can be brought into, you know supplement the resources you have in your own team. So being thoughtful in that is part of the approach. And then having a roadmap for what you're trying to do. Like we talked this morning about a customer that Linda had been talking about. Have been working on for six or seven years, right? And you're saying, for an enterprise a very large enterprise company taking six or seven years to turn the battleship maybe isn't that long. >> Okay, so you got the sister company going on. Do you have a commercial relationship with IFS or you just here as kind of an outside speaker and a thought leader? >> I'm here as an outside speaker thought leader. There is talk that perhaps we can you know, work together in the future we're trying to work that out right now. >> I want to ask you about open source business models. We still see companies sort of struggling to come up with, not profitable but, you know, insanely profitable business models based on open source software. What do you see coming out of all this? Is there a model that you think is going to work in the long term? >> I think the future is open source for sure and this is coming from a person who spent 25 years in proprietary software having worked for the larger piece here in vendors. 100% of my life has been dedicated to proprietary software. So whilst that's true I came at SUSE and the open source environment in a very different way as a customer running my proprietary applications on open source Linux based systems. So I come with a little bit different of a, you know, of an approach I would say. The future's open source for sure the way that we collaborate, the innovation the borderless means of which we deliver you know, leadership within our business is much much different than proprietary software. You would think as well that, you know the wall that we hide behind an open source being able to access software anywhere in a community and be able to provide thought leadership masks and hides who the developers and engineers are and instead exacerbates the thought leadership that comes out of them. So it provides for a naturally inclusive and diverse environment which leads to really good business results. We all know the importance of diversity and inclusion. I think there is definitely a place for open source in the world it's a matter providing it in such a way that creates business value that does enable and foster that growth of the community because nothing is better than having two or three or four or five million developers hacking away at my software to deliver better business value to my customers. The commercial side is going to be around the support, right? The enterprise customers would want to know that when bump goes in the night I've got someone I can pay to support my systems. And that's really what SUSE is about protecting our install base. Ensuring that we get them live, all the time every day and keep them running frictionlessly across their IT department. >> Now there's another model, the so-called open core model that holds that, the future is actually proprietary on top of an open base. So are you saying that you don't think that's a good model? >> I don't know, jury's out. Next time that you come to our event which is going to be in March, in Dublin. We're doing our SUSECON conference. Leave that question for me and I'll have an answer for you. I'm pontificating. >> Well I did and-- >> It's a date. The 12th of March. >> It's certainly working for Amazon. I mean, you know, Amazon's criticized for bogarting open source but Redshift is built on open source I think Aurora is built on open source. They're obviously making a lot of money. Your open core model failed for cloud era. Hortonworks was pure, Hortonworks had a model like, you know, you guys and RedHat and that didn't work and now that was kind of profitless prosperity of Hadoop and maybe that was sort of an over head-- >> I think our model, the future's open-source no question. It's just what level of open source within the sack do we keep proprietary or not, it's the case maybe, right? Do we allow open source in the bottom or the top or do we put some proprietary components on top to preserve and protect like an umbrella the core of which is open source. I don't know, we're thinking about that right now. We're trynna think what our future looks like. What the model should look like in the future for the industry. How can we service our customers best. At the end of the day, it's satisfying customer needs and solving business problems. If that's going to be, pure open source or open source with a little bit of proprietary to service the customer best that's what we're all going to be after, aren't we? >> So, there's no question that the innovation model is open source. I mean, I don't think that's a debate, the hard part is. Okay, how do you make money? A bit of open source for you guys. I mean, are you using open source technologies presumable you are, everybody is but-- >> So we're very open API's, who joined three years ago. We joined openapi.org. And so we've been one of the the leading ERP companies in the industry on publishing open API's and then we do a lot of customization work with our community and all of that's going on in GitHub. And so it's all open source, it's all out there for people who want it. Not everybody wants to be messing around in the core of a transaction engine and that's where you get into you know, the sort of the core argument of, you know which pieces should be people modifying? Do you want people in the kernel? Maybe, maybe not. And, you know, this is not my area of expertise so I'll defer to Melissa. Having people would be able to extend things in an open source model. Having people be able to find a library of customizations and components that can extend Acumatica, that's obviously a good thing. >> I mean, I think you hit on it with developers. I mean, that to me is the key lever. I mean, if I were a VM where I'd hire you know, 1000, 2000 open source software developers and say, "Go build next-generation apps and tools "and give it away." And then I'd say, "Okay, Michael Dell make you a hardware "run better in our software." That's a business model, you can make a lot of money-- >> 100% and we're, you know, we're going to be very acquisitive right now, we're looking for our future, right? We're looking to make a mark right now and where do we go next? How can we help predict the outcome next step in the marketplace when it pertains to, you know, the core of applications and the delivery mechanism in which we want to offer. The ease of being able to get thousands of mainframe customers with complex enterprise applications. Let's say, for example to the cloud. And a part of that is going to be the developer network. I mean, that's a really really big important segment for us and we're looking at companies. Who can we acquire? What's the business outcome? And what the developer networks look like. >> So Cloud and Edge, here got to be two huge opportunities for you, right? Again, it's all about developers. I think that's the right strategy at the Edge. You see a lot of Edge activity where somebody trying to throw a box at the Edge with the top down, in a traditional IT model. It's really the devs up, where I think-- >> It is, it is the dev ups, you're exactly right. Exactly right. >> Yeah, I mean, Edge is fascinating. That's going to be amazing what happens in the next 10 years and we don't even know, but we ship a construction edition we've got a customer that we're working with that's instrumenting all of their construction machinery on something like a thousand construction sites and feeding the sensor data into a Acumatica and so it's a way to keep track of all the machines and what's going on with them. You know, obviously shipping logistics the opportunity to start putting things like, you know, RFID tags on everything an instrument to all of that, out at the Edge. And then the issue is you get this huge amount of data and how do you process that and get the intelligence out of it and make the right decisions. >> Well, how do you? When data is plentiful, insights, you know, aren't is-- >> Yeah, well I think that's where the machine learning breakthroughs are going to happen. I mean, we've built out a team in the last three years on machine learning, all the guys who've been talking about Amazon, Microsoft, Google are all putting out machine learning engines that companies can pick up and start building models around. So we're doing one's around, you know inventory, logistics, shipping. We just release one on expense reports. You know, that really is where the innovation is happening right now. >> Okay, so you're not an inventor of AI you're going to take those technologies apply 'em to your business. >> Yeah, we don't want to be the engine builder we want to be the guys that are building the models and putting the insight for the industry on top that's our job. >> All right Melissa, we'll give you the final word and IFS World 2019, I think, is this your first one? >> It's my first one, yeah-- >> We say bumper sticker say when your truck's are pulling away or-- (laughs) >> A bumper sticker would say, "When you think about the future of open source "think about SUSE." (laughing) >> Dave: I love it. >> I'd say in the event, I mean, I'm super-impressed I think it's the group that's here is great the customers are really enthused and you know, I have zero bias so I'm just giving you my perspective. >> Yeah, I mean the ecosystem is robust here, I have to say. I think they said 400 partners and I was pleasantly surprised when I was walking around last-- >> This is your second one, isn't it? >> It's theCubes second one, my first. >> Oh your first, all right, well done. And so what do you think? Coming back? >> I would love to come back. Especially overseas, I know you guys do a bunch of stuff over seas. >> There you go, he wants to travel. >> Dublin in March? >> March the 12th. >> Dublin is a good place for sure so you're doing at the big conference? >> Yep, the big conference center and it's-- >> That is a great venue. >> And not just because the green thing but it's actually because (laughs). >> No, that's a really nice venue, it's modern It's got, I think three or four floors. >> It does, yeah yeah, we're looking forward to it. >> And then evening events at the, you know, the Guinness Storehouse. >> There you go. >> Exactly right. So we'll look forward to hosting you there. >> All right, great, see you there. >> We'll come with our tough questions for you. (laughing) >> Thanks you guys, I really appreciate your time. >> Thanks very much. >> Thank you for watching but right back, right after this short break you're watching theCube from IFS World in Boston be right back. (upbeat music)

Published Date : Oct 8 2019

SUMMARY :

Brought to you by IFS. and Jon Roskill is the CEO of Acumatica. So you guys had the power panel today? the way you support. And, you know, part of a transformation RedHat, you know, the big news last year IBM $34 billion. now be, you know, part of the inner circle if you will. I mean, we're huge fans of RedHat. Now they say they're going to leave RedHat alone, we'll see. and all the others. SPSS, you saw that, Ustream, you know that they're trying to, you know, effect. rather than, you know, an afterthought from the past. I want to ask you about the cost of shifting It depends on the application layer. 24/7, you know, high pays, big fat they need, you know, constant operation How do you work together or? and so they see these as very complementary assets and you know, for a company, we've got one What are the big mistakes you see companies making and everything you do. is that you had this kind of spray-and-pray and, you know, the biggest thing I see So starting is something that you can get a gauge of that I mean, one of the things you see around here Okay, so you got the sister company going on. you know, work together in the future I want to ask you about open source business models. of a, you know, of an approach I would say. So are you saying that you don't think that's a good model? Next time that you come to our event The 12th of March. I mean, you know, Amazon's criticized in the future for the industry. I mean, are you using open source technologies and that's where you get into I mean, I think you hit on it with developers. 100% and we're, you know, we're going to be very acquisitive So Cloud and Edge, here got to be It is, it is the dev ups, you're exactly right. and how do you process that So we're doing one's around, you know apply 'em to your business. and putting the insight for the industry on top "When you think about the future of open source and you know, I have zero bias Yeah, I mean the ecosystem is robust here, I have to say. And so what do you think? Especially overseas, I know you guys And not just because the green thing It's got, I think three or four floors. at the, you know, the Guinness Storehouse. So we'll look forward to hosting you there. We'll come with our tough questions for you. Thank you for watching

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theCUBE Insights | IBM CDO Summit 2019


 

>> Live from San Francisco, California, it's theCUBE covering the IBM Chief Data Officer Summit. Brought to you by IBM. >> Hi everybody, welcome back to theCUBE's coverage of the IBM Chief Data Officer Event. We're here at Fisherman's Wharf in San Francisco at the Centric Hyatt Hotel. This is the 10th anniversary of IBM's Chief Data Officer Summits. In the recent years, anyway, they do one in San Francisco and one in Boston each year, and theCUBE has covered a number of them. I think this is our eighth CDO conference. I'm Dave Vellante, and theCUBE, we like to go out, especially to events like this that are intimate, there's about 140 chief data officers here. We've had the chief data officer from AstraZeneca on, even though he doesn't take that title. We've got a panel coming up later on in the day. And I want to talk about the evolution of that role. The chief data officer emerged out of kind of a wonky, back-office role. It was all about 10, 12 years ago, data quality, master data management, governance, compliance. And as the whole big data meme came into focus and people were realizing that data is the new source of competitive advantage, that data was going to be a source of innovation, what happened was that role emerged, that CDO, chief data officer role, emerged out of the back office and came right to the front and center. And the chief data officer really started to better understand and help companies understand how to monetize the data. Now monetization of data could mean more revenue. It could mean cutting costs. It could mean lowering risk. It could mean, in a hospital situation, saving lives, sort of broad definition of monetization. But it was really understanding how data contributed to value, and then finding ways to operationalize that to speed up time to value, to lower cost, to lower risk. And that required a lot of things. It required new skill sets, new training. It required a partnership with the lines of business. It required new technologies like artificial intelligence, which have just only recently come into a point where it's gone mainstream. Of course, when I started in the business several years ago, AI was the hot topic, but you didn't have the compute power. You didn't have the data, you didn't have the cloud. So we see the new innovation engine, not as Moore's Law, the doubling of transistors every 18 months, doubling of performance. Really no, we see the new innovation cocktail as data as the substrate, applying machine intelligence to that data, and then scaling it with the cloud. And through that cloud model, being able to attract startups and innovation. I come back to the chief data officer here, and IBM Chief Data Officer Summit, that's really where the chief data officer comes in. Now, the role in the organization is fuzzy. If you ask people what's a chief data officer, you'll get 20 different answers. Many answers are focused on compliance, particularly in what emerged, again, in those regulated industries: financial service, healthcare, and government. Those are the first to have chief data officers. But now CDOs have gone mainstream. So what we're seeing here from IBM is the broadening of that role and that definition and those responsibilities. Confusing things is the chief digital officer or the chief analytics officer. Those are roles that have also emerged, so there's a lot of overlap and a lot of fuzziness. To whom should the chief data officer report? Many say it should not be the CIO. Many say they should be peers. Many say the CIO's responsibility is similar to the chief data officer, getting value out of data, although I would argue that's never really been the case. The role of the CIO has largely been to make sure that the technology infrastructure works and that applications are delivered with high availability, with great performance, and are able to be developed in an agile manner. That's sort of a more recent sort of phenomenon that's come forth. And the chief digital officer is really around the company's face. What does that company's brand look like? What does that company's go-to-market look like? What does the customer see? Whereas the chief data officer's really been around the data strategy, what the sort of framework should be around compliance and governance, and, again, monetization. Not that they're responsible for the monetization, but they responsible for setting that framework and then communicating it across the company, accelerating the skill sets and the training of existing staff and complementing with new staff and really driving that framework throughout the organization in partnership with the chief digital officer, the chief analytics officer, and the chief information officer. That's how I see it anyway. Martin Schroeder, the senior vice president of IBM, came on today with Inderpal Bhandari, who is the chief data officer of IBM, the global chief data officer. Martin Schroeder used to be the CFO at IBM. He talked a lot, kind of borrowing from Ginni Rometty's themes in previous conferences, chapter one of digital which he called random acts of digital, and chapter two is how to take this mainstream. IBM makes a big deal out of the fact that it doesn't appropriate your data, particularly your personal data, to sell ads. IBM's obviously in the B2B business, so that's IBM's little back-ended shot at Google and Facebook and Amazon who obviously appropriate our data to sell ads or sell goods. IBM doesn't do that. I'm interested in IBM's opinion on big tech. There's a lot of conversations now. Elizabeth Warren wants to break up big tech. IBM was under the watchful eye of the DOJ 25 years ago, 30 years ago. IBM essentially had a monopoly in the business, and the DOJ wanted to make sure that IBM wasn't using that monopoly to hurt consumers and competitors. Now what IBM did, the DOJ ruled that IBM had to separate its applications business, actually couldn't be in the applications business. Another ruling was that they had to publish the interfaces to IBM mainframes so that competitors could actually build plug-compatible products. That was the world back then. It was all about peripherals plugging into mainframes and sort of applications being developed. So the DOJ took away IBM's power. Fast forward 30 years, now we're hearing Google, Amazon, and Facebook coming under fire from politicians. Should they break up those companies? Now those companies are probably the three leaders in AI. IBM might debate that. I think generally, at theCUBE and SiliconANGLE, we believe that those three companies are leading the charge in AI, along with China Inc: Alibaba, Tencent, Baidu, et cetera, and the Chinese government. So here's the question. What would happen if you broke up big tech? I would surmise that if you break up big tech, those little techs that you break up, Amazon Web Services, WhatsApp, Instagram, those little techs would get bigger. Now, however, the government is implying that it wants to break those up because those entities have access to our data. Google's got access to all the search data. If you start splitting them up, that'll make it harder for them to leverage that data. I would argue those small techs would get bigger, number one. Number two, I would argue if you're worried about China, which clearly you're seeing President Trump is worried about China, placing tariffs on China, playing hardball with China, which is not necessarily a bad thing. In fact, I think it's a good thing because China has been accused, and we all know, of taking IP, stealing IP essentially, and really not putting in those IP protections. So, okay, playing hardball to try to get a quid pro quo on IP protections is a good thing. Not good for trade long term. I'd like to see those trade barriers go away, but if it's a negotiation tactic, okay. I can live with it. However, going after the three AI leaders, Amazon, Facebook, and Google, and trying to take them down or break them up, actually, if you're a nationalist, could be a bad thing. Why would you want to handcuff the AI leaders? Third point is unless they're breaking the law. So I think that should be the decision point. Are those three companies, and others, using monopoly power to thwart competition? I would argue that Microsoft actually did use its monopoly power back in the '80s and '90s, in particular in the '90s, when it put Netscape out of business, it put Lotus out of business, it put WordPerfect out of business, it put Novell out of the business. Now, maybe those are strong words, but in fact, Microsoft's bundling, its pricing practices, caught those companies off guard. Remember, Jim Barksdale, the CEO of Netscape, said we don't need the browser. He was wrong. Microsoft killed Netscape by bundling Internet Explorer into its operating system. So the DOJ stepped in, some would argue too late, and put handcuffs on Microsoft so they couldn't use that monopoly power. And I would argue that you saw from that two things. One, granted, Microsoft was overly focused on Windows. That was kind of their raison d'etre, and they missed a lot of other opportunities. But the DOJ definitely slowed them down, and I think appropriately. And if out of that myopic focus on Windows, and to a certain extent, the Department of Justice and the government, the FTC as well, you saw the emergence of internet companies. Now, Microsoft did a major pivot to the internet. They didn't do a major pivot to the cloud until Satya Nadella came in, and now Microsoft is one of those other big tech companies that is under the watchful eye. But I think Microsoft went through that and perhaps learned its lesson. We'll see what happens with Facebook, Google, and Amazon. Facebook, in particular, seems to be conflicted right now. Should we take down a video that has somewhat fake news implications or is a deep hack? Or should we just dial down? We saw this recently with Facebook. They dialed down the promotion. So you almost see Facebook trying to have its cake and eat it too, which personally, I don't think that's the right approach. I think Facebook either has to say damn the torpedoes. It's open content, we're going to promote it. Or do the right thing and take those videos down, those fake news videos. It can't have it both ways. So Facebook seems to be somewhat conflicted. They are probably under the most scrutiny now, as well as Google, who's being accused, anyway, certainly we've seen this in the EU, of promoting its own ads over its competitors' ads. So people are going to be watching that. And, of course, Amazon just having too much power. Having too much power is not necessarily an indication of abusing monopoly power, but you know the government is watching. So that bears watching. theCUBE is going to be covering that. We'll be here all day, covering the IBM CDO event. I'm Dave Vallente, you're watching theCUBE. #IBMCDO, DM us or Tweet us @theCUBE. I'm @Dvallente, keep it right there. We'll be right back right after this short break. (upbeat music)

Published Date : Jun 24 2019

SUMMARY :

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Frank Gens, IDC | Actifio Data Driven 2019


 

>> From Boston, Massachusets, it's The Cube. Covering Actifio 2019: Data Driven, Brought to you by Actifio. >> Welcome back to Boston, everybody. We're here at the Intercontinental Hotel at Actifio's Data Driven conference, day one. You're watching The Cube. The leader in on-the-ground tech coverage. My name is is Dave Valante, Stu Minamin is here, so is John Ferrer, my friend Frank Gens is here, he's the Senior Vice President and Chief Analyst at IDC and Head Dot Connector. Frank, welcome to The Cube. >> Well thank you Dave. >> First time. >> First time. >> Newbie. >> Yep. >> You're going to crush it, I know. >> Be gentle. >> You know, you're awesome, I've watched you over the many years, of course, you know, you seem to get competitive, and it's like who gets the best rating? Frank always had the best ratings at the Directions conference. He's blushing but I could- >> I don't know if that's true but I'll accept it. >> I could never beat him, no matter how hard I tried. But you are a phenomenal speaker, you gave a great conversation this morning. I'm sure you drew a lot from your Directions talk, but every year you lay down this, you know, sort of, mini manifesto. You describe it as, you connect the dots, IDC, thousands of analysts. And it's your job to say okay, what does this all mean? Not in the micro, let's up-level a little bit. So, what's happening? You talked today, You know you gave your version of the wave slides. So, where are we in the waves? We are exiting the experimentation phase, and coming in to a new phase that multiplied innovation. I saw AI on there, block-chain, some other technologies. Where are we today? >> Yeah, well I think having mental models of the6 industry or any complex system is pretty important. I mean I've made a career dumbing-down a complex industry into something simple enough that I can understand, so we've done it again now with what we call the third platform. So, ten years ago seeing the whole raft of new technologies at the time were coming in that would become the foundation for the next thirty years of tech, so, that's an old story now. Cloud, mobile, social, big data, obviously IOT technologies coming in, block-chain, and so forth. So we call this general era the third platform, but we noticed a few years ago, well, we're at the threshold of kind of a major scale-up of innovation in this third platform that's very different from the last ten or twelve years, which we called the experimentation stage. Where people were using this stuff, using the cloud, using mobile, big data, to create cool things, but they were doing it in kind of a isolated way. Kind of the traditional, well I'm going to invent something and I may have a few friends help me, whereas, the promise of the cloud has been , well, if you have a lot of developers out on the cloud, that form a community, an ecosystem, think of GitHub, you know, any of the big code repositories, or the ability to have shared service as often Amazon, Cloud, or IBM, or Google, or Microsoft, the promise is there to actually bring to life what Bill Joy said, you know, in the nineties. Which was no matter how smart you are, most of the smart people in the world work for someone else. So the questions always been, well, how do I tap into all those other smart people who don't work for me? So we can feel that where we are in the industry right now is the business model of multiplied innovation or if you prefer, a network of collaborative innovation, being able to build something interesting quickly, using a lot of innovation from other people, and then adding your special sauce. But that's going to take the scale of innovation just up a couple of orders of magnitude. And the pace, of course, that goes with that, is people are innovating much more rapid clip now. So really, the full promise of a cloud-native innovation model, so we kind of feel like we're right here, which means there's lots of big changes around the technologies, around kind of the world of developers and apps, AI is changing, and of course, the industry structure itself. You know the power positions, you know, a lot of vendors have spent a lot of energy trying to protect the power positions of the last thirty years. >> Yeah so we're getting into some of that. So, but you know, everybody talks about digital transformation, and they kind of roll their eyes, like it's a big buzzword, but it's real. It's dataware at a data-driven conference. And data, you know, being at the heart of businesses means that you're seeing businesses transition industries, or traverse industries, you know, Amazon getting into groceries, Apple getting into content, Amazon as well, etcetera, etcetera, etcetera, so, my question is, what's a tech company? I mean, you know, Bennyhoff says that, you know, every company's a sass company, and you're certainly seeing that, and it's got to be great for your business. >> Yeah, yeah absolutely >> Quantifying all those markets, but I mean, the market that you quantify is just it's every company now. Banks, insurance companies, grocers, you know? Everybody is a tech company. >> I think, yeah, that's a hundred percent right. It is that this is the biggest revolution in the economy, you know, for many many decades. Or you might say centuries even. Is yeah, whoever put it, was it Mark Andreson or whoever used to talk about software leading the world, we're in the middle of that. Only, software now is being delivered in the form of digital or cloud services so, you know, every company is a tech company. And of course it really raises the question, well what are tech companies? You know, they need to kind of think back about where does our value add? But it is great. It's when we look at the world of clouds, one of the first things we observed in 2007, 2008 was, well, clouds wasn't just about S3 storage clouds, or salesforce.com's softwares and service. It's a model that can be applied to any industry, any company, any offering. And of course we've seen all these startups whether it's Uber or Netflix or whoever it is, basically digital innovation in every single industry, transforming that industry. So, to me that's the exciting part is if that model of transforming industries through the use of software, through digital technology. In that kind of experimentation stage it was mainly a startup story. All those unicorns. To me the multiplied innovation chapter, it's about- (audio cuts out) finally, you know, the cities, the Procter & Gambles, the Walmarts, the John Deere's, they're finally saying hey, this cloud platform and digital innovation, if we can do that in our industry. >> Yeah, so intrapreneurship is actually, you know, starting to- >> Yeah. >> So you and I have seen a lot of psychos, we watched the you know, the mainframe wave get crushed by the micro-processor based revolution, IDC at the time spent a lot of time looking at that. >> Vacuum tubes. >> Water coolant is back. So but the industry has marched to the cadence of Moore's Law forever. Even Thomas Friedman when he talks about, you know, his stuff and he throws in Moore's Law. But no longer Moore's Law the sort of engine of innovation. There's other factors. So what's the innovation cocktail looking forward over the next ten years? You've talked about cloud, you know, we've talked about AI, what's that, you know, sandwich, the innovation sandwich look like? >> Yeah so to me I think it is the harnessing of all this flood of technologies, again, that are mainly coming off the cloud, and that parade is not stopping. Quantum, you know, lots of other technologies are coming down the pipe. But to me, you know, it is the mixture of number one the cloud, public cloud stacks being able to travel anywhere in the world. So take the cloud on the road. So it's even, I would say, not even just scale, I think of, that's almost like a mount of compute power. Which could happen inside multiple hyperscale data centers. I'm also thinking about scale in terms of the horizontal. >> Bringing that model anywhere. >> Take me out to the edge. >> Wherever your data lives. >> Take me to a Carnival cruise ship, you know, take me to, you know, an apple-powered autonomous car, or take me to a hospital or a retail store. So the public cloud stacks where all the innovation is basically happening in the industry. Jail-breaking that out so it can come, you know it's through Amazon, AWS Outpost, or Ajerstack, or Google Anthos, this movement of the cloud guys, to say we'll take public cloud innovation wherever you need it. That to me is a big part of the cocktail because that's you know, basically the public clouds have been the epicenter of most tech innovation the last three or four years, so, that's very important. I think, you know just quickly, the other piece of the puzzle is the revolution that's happening in the modularity of apps. So the micro services revolution. So, the building of new apps and the refactoring of old apps using containers, using servos technologies, you know, API lifecycle management technologies, and of course, agile development methods. Kind of getting to this kind of iterative sped up deployment model, where people might've deployed new code four times a year, they're now deploying it four times a minute. >> Yeah right. >> So to me that's- and kind of aligned with that is what I was mentioning before, that if you can apply that, kind of, rapid scale, massive volume innovation model and bring others into the party, so now you're part of a cloud-connected community of innovators. And again, that could be around a Github, or could be around a Google or Amazon, or it could be around, you know, Walmart. In a retail world. Or an Amazon in retail. Or it could be around a Proctor & Gamble, or around a Disney, digital entertainment, you know, where they're creating ecosystems of innovators, and so to me, bringing people, you know, so it's not just these technologies that enable rapid, high-volume modular innovation, but it's saying okay now plugging lots of people's brains together is just going to, I think that, here's the- >> And all the data that throws off obviously. >> Throws a ton of data, but, to me the number we use it kind of is the punchline for, well where does multiplied innovation lead? A distributed cloud, this revolution in distributing modular massive scale development, that we think the next five years, we'll see as many new apps developed and deploye6d as we saw developed and deployed in the last forty years. So five years, the next five years, versus the last forty years, and so to me that's, that is the revolution. Because, you know, when that happens that means we're going to start seeing that long tail of used cases that people could never get to, you know, all the highly verticalized used cases are going to be filled, you know we're going to finally a lot of white space has been white for decades, is going to start getting a lot of cool colors and a lot of solutions delivered to them. >> Let's talk about some of the macro stuff, I don't know the exact numbers, but it's probably three trillion, maybe it's four trillion now, big market. You talked today about the market's going two x GDP. >> Yeah. >> For the tech market, that is. Why is it that the tech market is able to grow at a rate faster than GDP? And is there a relationship between GDP and tech growth? >> Yeah, well, I think, we are still, while, you know, we've been in tech, talk about those apps developed the last forty years, we've both been there, so- >> And that includes the iPhone apps, too, so that's actually a pretty impressive number when you think about the last ten years being included in that number. >> Absolutely, but if you think about it, we are still kind of teenagers when you think about that Andreson idea of software eating the world. You know, we're just kind of on the early appetizer, you know, the sorbet is coming to clear our palates before we go to the next course. But we're not even close to the main course. And so I think when you look at the kind of, the percentage of companies and industry process that is digital, that has been highly digitized. We're still early days, so to me, I think that's why. That the kind of the steady state of how much of an industry is kind of process and data flow is based on software. I'll just make up a number, you know, we may be a third of the way to whatever the steady state is. We've got two-thirds of the way to go. So to me, that supports growth of IT investment rising at double the rate of overall. Because it's sucking in and absorbing and transforming big pieces of the existing economy, >> So given the size of the market, given that all companies are tech companies. What are your thoughts on the narrative right now? You're hearing a lot of pressure from, you know, public policy to break up big tech. And we saw, you know you and I were there when Microsoft, and I would argue, they were, you know, breaking the law. Okay, the Department of Justice did the right thing, and they put handcuffs on them. >> Yeah. >> But they never really, you know, went after the whole breakup scenario, and you hear a lot of that, a lot of the vitriol. Do you think that makes sense? To break up big tech and what would the result be? >> You don't think I'm going to step on those land mines, do you? >> Okay well I've got an opinion. >> Alright I'll give you mine then. Alright, since- >> I mean, I'll lay it out there, I just think if you break up big tech the little techs are going to get bigger. It's going to be like AT&T all over again. The other thing I would add is if you want to go after China for, you know, IP theft, okay fine, but why would you attack the AI leaders? Now, if they're breaking the law, that should not be allowed. I'm not for you know, monopolistic, you know, illegal behavior. What are your thoughts? >> Alright, you've convinced me to answer this question. >> We're having a conversation- >> Nothing like a little competitive juice going. You're totally wrong. >> Lay it out for me. >> No, I think, but this has been a recurring pattern, as you were saying, it even goes back further to you know, AT&T and people wanting to connect other people to the chiraphone, and it goes IBM mainframes, opening up to peripherals. Right, it goes back to it. Exactly. It goes back to the wheel. But it's yeah, to me it's a valid question to ask. And I think, you know, part of the story I was telling, that multiplied innovation story, and Bill Joy, Joy's Law is really about platform. Right? And so when you get aggregated portfolio of technical capabilities that allow innovation to happen. Right, so the great thing is, you know, you typically see concentration, consolidation around those platforms. But of course they give life to a lot of competition and growth on top of them. So that to me is the, that's the conundrum, because if you attack the platform, you may send us back into this kind of disaggregated, less creative- so that's the art, is to take the scalpel and figure out well, where are the appropriate boundaries for, you know, putting those walls, where if you're in this part of the industry, you can't be in this. So, to me I think one, at least reasonable way to think about it is, so for example, if you are a major cloud platform player, right, you're providing all of the AI services, the cloud services, the compute services, the block-chain services, that a lot of the sass world is using. That, somebody could argue, well, if you get too strong in the sass world, you then could be in a position to give yourself favorable position from the platform. Because everyone in the sass world is depending on the platform. So somebody might say you can't be in. You know, if you're in the sass position you'll have to separate that from the platform business. But I think to me, so that's a logical way to do it, but I think you also have to ask, well, are people actually abusing? Right, so I- >> I think it's a really good question. >> I don't think it's fair to just say well, theoretically it could be abused. If the abuse is not happening, I don't think you, it's appropriate to prophylactically, it's like go after a crime before it's committed. So I think, the other thing that is happening is, often these monopolies or power positions have been about economic power, pricing power, I think there's another dynamic happening because consumer date, people's data, the Facebook phenomenon, the Twitter and the rest, there's a lot of stuff that's not necessarily about pricing, but that's about kind of social norms and privacy that I think are at work and that we haven't really seen as big a factor, I mean obviously we've had privacy regulation is Europe with GDPR and the rest, obviously in check, but part of that's because of the social platforms, so that's another vector that is coming in. >> Well, you would like to see the government actually say okay, this is the framework, or this is what we think the law should be. I mean, part of it is okay, Facebook they have incentive to appropriate our data and they get, okay, and maybe they're not taking enough responsibility for. But I to date have not seen the evidence as we did with, you know, Microsoft wiping out, you know, Lotus, and Novel, and Word Perfect through bundling and what it did to Netscape with bundling the browser and the price practices that- I don't see that, today, maybe I'm just missing it, but- >> Yeah I think that's going to be all around, you know, online advertising, and all that, to me that's kind of the market- >> Yeah, so Google, some of the Google stuff, that's probably legit, and that's fine, they should stop that. >> But to me the bigger issue is more around privacy.6 You know, it's a social norm, it's societal, it's not an economic factor I think around Facebook and the social platforms, and I think, I don't know what the right answer is, but I think certainly government it's legitimate for those questions to be asked. >> Well maybe GDPR becomes that framework, so, they're trying to give us the hook but, I'm having too much fun. So we're going to- I don't know how closely you follow Facebook, I mean they're obviously big tech, so Facebook has this whole crypto-play, seems like they're using it for driving an ecosystem and making money. As opposed to dealing with the privacy issue. I'd like to see more on the latter than the former, perhaps, but, any thoughts on Facebook and what's going on there with their crypto-play? >> Yeah I don't study them all that much so, I am fascinated when Mark Zuckerberg was saying well now our key business now is about privacy, which I find interesting. It doesn't feel that way necessarily, as a consumer and an observer, but- >> Well you're on Facebook, I'm on Facebook, >> Yeah yeah. >> Okay so how about big IPOs, we're in the tenth year now of this huge, you know, tail-wind for tech. Obviously you have guys like Uber, Lyft going IPO,6 losing tons of money. Stocks actually haven't done that well which is kind of interesting. You saw Zoom, you know, go public, doing very well. Slack is about to go public. So there's really a rush to IPO. Your thoughts on that? Is this sustainable? Or are we kind of coming to the end here? >> Yeah so, I think in part, you know, predicting the stock market waves is a very tough thing to do, but I think one kind of secular trend is going to be relevant for these tech IPOs is what I was mentioning earlier, is that we've now had a ten, twelve year run of basically startups coming in and reinventing industries while the incumbents in the industries are basically sitting on their hands, or sleeping. So to me the next ten years, those startups are going to, not that, I mean we've seen that large companies waking up doesn't necessarily always lead to success but it feels to me like it's going to be a more competitive environment for all those startups Because the incumbents, not all of them, and maybe not even most of them, but some decent portion of them are going to wind up becoming digital giants in their own industry. So to me I think that's a different world the next ten years than the last ten. I do think one important thing, and I think around acquisitions MNA, and we saw it just the last few weeks with Google Looker and we saw Tab Low with Salesforce, is if that, the mega-cloud world of Microsoft, Ajer, and Amazon, Google. That world is clearly consolidating. There's room for three or four global players and that game is almost over. But there's another power position on top of that, which is around where did all the app, business app guys, all the suite guys, SAP, Oracle, Salesforce, Adobe, Microsoft, you name it. Where did they go? And so we see, we think- >> Service Now, now kind of getting big. >> Absolutely, so we're entering a intensive period, and I think again, the Tab Low and Looker is just an example where those companies are all stepping on the gas to become better platforms. So apps as platforms, or app portfolio as platforms, so, much more of a data play, analytics play, buying other pieces of the app portfolio, that they may not have. And basically scaling up to become the business process platforms and ecosystems there. So I think we are just at the beginning of that, so look for a lot of sass companies. >> And I wonder if Amazon could become a platform for developers to actually disrupt those traditional sass guys. It's not obvious to me how those guys get disrupted, and I'm thinking, everybody says oh is Amazon going to get into the app space? Maybe some day if they happen to do a cam expans6ion, But it seems to me that they become a platform fo6r new apps you know, your apps explosion.6 At the edge, obviously, you know, local. >> Well there's no question. I think those appcentric apps is what I'd call that competition up there and versus kind of a mega cloud. There's no question the mega cloud guys. They've already started launching like call center, contact center software, they're creeping up into that world of business apps so I don't think they're going to stop and so I think that that is a reasonable place to look is will they just start trying to create and effect suites and platforms around sass of their own. >> Startups, ecosystems like you were saying. Alright, I got to give you some rapid fire questions here, so, when do you think, or do you think, no, I'm going to say when you think, that owning and driving your own car will become the exception, rather than the norm? Buy into the autonomous vehicles hype? Or- >> I think, to me, that's a ten-year type of horizon. >> Okay, ten plus, alright. When will machines be able to make better diagnosis than than doctors? >> Well, you could argue that in some fields we're almost there, or we're there. So it's all about the scope of issue, right? So if it's reading a radiology, you know, film or image, to look for something right there, we're almost there. But for complex cancers or whatever that's going to take- >> One more dot connecting question. >> Yeah yeah. >> So do you think large retail stores will essentially disappear? >> Oh boy that's a- they certainly won't disappear, but I think they can so witness Apple and Amazon even trying to come in, so it feels that the mix is certainly shifting, right? So it feels to me that the model of retail presence, I think that will still be important. Touch, feel, look, socialize. But it feels like the days of, you know, ten thousand or five thousand store chains, it feels like that's declining in a big way. >> How about big banks? You think they'll lose control of the payment systems? >> I think they're already starting to, yeah, so, I would say that is, and they're trying to get in to compete, so I think that is on its way, no question. I think that horse is out of the barn. >> So cloud, AI, new apps, new innovation cocktails, software eating the world, everybody is a tech company. Frank Gens, great to have you. >> Dave, always great to see you. >> Alright, keep it right there buddy. You're watching The Cube, from Actifio: Data Driven nineteen. We'll be right back right after this short break. (bouncy electronic music)

Published Date : Jun 18 2019

SUMMARY :

Brought to you by Actifio. We're here at the Intercontinental Hotel at many years, of course, you know, You know you gave your version of the wave slides. an ecosystem, think of GitHub, you know, I mean, you know, Bennyhoff says that, you know, that you quantify is just it's every company now. digital or cloud services so, you know, we watched the you know, the mainframe wave get crushed we've talked about AI, what's that, you know, sandwich, you know, it is the mixture of number one the cocktail because that's you know, and so to me, bringing people, you know, are going to be filled, you know we're going to I don't know the exact numbers, but it's probably Why is it that the tech market is able to grow And that includes the iPhone apps, too, And so I think when you look at the and I would argue, they were, you know, breaking the law. But they never really, you know, Alright I'll give you mine then. the little techs are going to get bigger. Nothing like a little competitive juice going. so that's the art, is to take the scalpel I don't think it's fair to just say well, as we did with, you know, Microsoft wiping out, you know, Yeah, so Google, some of the Google stuff, and the social platforms, and I think, I don't know I don't know how closely you follow Facebook, I am fascinated when Mark Zuckerberg was saying of this huge, you know, tail-wind for tech. Yeah so, I think in part, you know, predicting the buying other pieces of the app portfolio, At the edge, obviously, you know, local. and so I think that that is a reasonable place to look Alright, I got to give you some rapid fire questions here, diagnosis than than doctors? So if it's reading a radiology, you know, film or image, But it feels like the days of, you know, I think that horse is out of the barn. software eating the world, everybody is a tech company. We'll be right back right after this short break.

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Stephanie McReynolds, Alation | theCUBE NYC 2018


 

>> Live from New York, It's theCUBE! Covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media and its ecosystem partners. >> Hello and welcome back to theCUBE live in New York City, here for CUBE NYC. In conjunct with Strata Conference, Strata Data, Strata Hadoop This is our ninth year covering the big data ecosystem which has evolved into machine learning, A.I., data science, cloud, a lot of great things happening all things data, impacting all businesses I'm John Furrier, your host with Dave Vellante and Peter Burris, Peter is filling in for Dave Vellante. Next guest, Stephanie McReynolds who is the CMO, VP of Marketing for Alation, thanks for joining us. >> Thanks for having me. >> Good to see you. So you guys have a pretty spectacular exhibit here in New York. I want to get to that right away, top story is Attack of the Bots. And you're showing a great demo. Explain what you guys are doing in the show. >> Yah, well it's robot fighting time in our booth, so we brought a little fun to the show floor my kids are.. >> You mean big data is not fun enough? >> Well big data is pretty fun but occasionally you got to get your geek battle on there so we're having fun with robots but I think the real story in the Alation booth is about the product and how machine learning data catalogs are helping a whole variety of users in the organization everything from improving analyst productivity and even some business user productivity of data to then really supporting data scientists in their work by helping them to distribute their data products through a data catalog. >> You guys are one of the new guard companies that are doing things that make it really easy for people who want to use data, practitioners that the average data citizen has been called, or people who want productivity. Not necessarily the hardcore, setting up clusters, really kind of like the big data user. What's that market look like right now, has it met your expectations, how's business, what's the update? >> Yah, I think we have a strong perspective that for us to close the final mile and get to real value out of the data, it's a human challenge, there's a trust gap with managers. Today on stage over at STRATA it was interesting because Google had a speaker and it wasn't their chief data officer it was their chief decision scientist and I think that reflects what that final mile is is that making decisions and it's the trust gap that managers have with data because they don't know how the insides are coming to them, what are all the details underneath. In order to be able to trust decisions you have to understand who processed the data, what decision making criteria did they use, was this data governed well, are we introducing some bias into our algorithms, and can that be controlled? And so Alation becomes a platform for supporting getting answers to those issues. And then there's plenty of other companies that are optimizing the performance of those QUERYS and the storage of that data, but we're trying to really to close that trust gap. >> It's very interesting because from a management standpoint we're trying to do more evidence based management. So there's a major trend in board rooms, and executive offices to try to find ways to acculturate the executive team to using data, evidence based management healthcare now being applied to a lot of other domains. We've also historically had a situation where the people who focused or worked with the data was a relatively small coterie of individuals that crave these crazy systems to try to bring those two together. It sounds like what you're doing, and I really like the idea of the data scientists, being able to create data products that then can be distributed. It sounds like you're trying to look at data as an asset to be created, to be distributed so they can be more easily used by more people in your organization, have we got that right? >> Absolutely. So we're now seeing we're in just over a hundred production implementations of Alation, at large enterprises, and we're now seeing those production implementations get into the thousands of users. So this is going beyond those data specialists. Beyond the unicorn data scientists that understand the systems and math and technology. >> And business. >> And business, right. In business. So what we're seeing now is that a data catalog can be a point of collaboration across those different audiences in an enterprise. So whereas three years ago some of our initial customers kept the data catalog implementations small, right. They were getting access to the specialists to this catalog and asked them to certify data assets for others, what were starting to see is a proliferation of creation of self service data assets, a certification process that now is enterprise-wide, and thousands of users in these organizations. So Ebay has over a thousand weekly logins, Munich Reinsurance was on stage yesterday, their head of data engineering said they have 2,000 users on Alation at this point on their data lake, Fiserv is going to speak on Thursday and they're getting up to those numbers as well, so we see some really solid organizations that are solving medical, pharmaceutical issues, right, the largest re insurer in the world leading tech companies, starting to adopt a data catalog as a foundation for how their going to make those data driven decisions in the organization. >> Talk about how the product works because essentially you're bringing kind of the decision scientists, for lack of a better word, and productivity worker, almost like a business office suite concept, as a SAS, so you got a SAS model that says "Hey you want to play with data, use it but you have to do some front end work." Take us through how you guys roll out the platform, how are your customers consuming the service, take us through the engagement with customers. >> I think for customers, the most interesting part of this product is that it displays itself as an application that anyone can use, right? So there's a super familiar search interface that, rather than bringing back webpages, allows you to search for data assets in your organization. If you want more information on that data asset you click on those search results and you can see all of the information of how that data has been used in the organization, as well as the technical details and the technical metadata. And I think what's even more powerful is we actually have a recommendation engine that recommends data assets to the user. And that can be plugged into Tablo and Salesworth, Einstein Analytics, and a whole variety of other data science tools like Data Haiku that you might be using in your organization. So this looks like a very easy to use application that folks are familiar with that you just need a web browser to access, but on the backend, the hard work that's happening is the automation that we do with the platform. So by going out and crawling these source systems and looking at not just the technical descriptions of data, the metadata that exists, but then being able to understand by parsing the sequel weblogs, how that data is actually being used in the organization. We call it behavior I.O. by looking at the behaviors of how that data's being used, from those logs, we can actually give you a really good sense of how that data should be used in the future or where you might have gaps in governing that data or how you might want to reorient your storage or compute infrastructure to support the type of analytics that are actually being executed by real humans in your organization. And that's eye opening to a lot of I.T. sources. >> So you're providing insights to the data usage so that the business could get optimized for whether it's I.T. footprint component, or kinds of use cases, is that kind of how it's working? >> So what's interesting is the optimization actually happens in a pretty automated way, because we can make recommendations to those consumers of data of how they want to navigate the system. Kind of like Google makes recommendations as you browse the web, right? >> If you misspell something, "Oh did you mean this", kind of thing? >> "Did you mean this, might you also be interested in this", right? It's kind of a cross between Google and Amazon. Others like you may have used these other data assets in the past to determine revenue for that particular region, have you thought about using this filter, have you thought about using this join, did you know that you're trying to do analysis that maybe the sales ops guy has already done, and here's the certified report, why don't you just start with that? We're seeing a lot of reuse in organizations, wherein the past I think as an industry when Tablo and Click and all these B.I tools that were very self service oriented started to take off it was all about democratizing visualization by letting every user do their own thing and now we're realizing to get speed and accuracy and efficiency and effectiveness maybe there's more reuse of the work we've already done in existing data assets and by recommending those and expanding the data literacy around the interpretation of those, you might actually close this trust gap with the data. >> But there's one really important point that you raised, and I want to come back to it, and that is this notion of bias. So you know, Alation knows something about the data, knows a lot about the metadata, so therefore, I don't want to say understands, but it's capable of categorizing data in that way. And you're also able to look at the usage of that data by parsing some of sequel statements and then making a determination of the data as it's identified is appropriately being used based on how people are actually applying it so you can identify potential bias or potential misuse or whatever else it might be. That is an incredibly important thing. As you know John, we had an event last night and one of the things that popped up is how do you deal with emergence in data science in A.I, etc. And what methods do you put in place to actually ensure that the governance model can be extended to understand how those things are potentially in a very soft way, corrupting the use of the data. So could you spend a little bit more time talking about that because it's something a lot of people are interested in, quite frankly we don't know about a lot of tools that are doing that kind of work right now. It's an important point. >> I think the traditional viewpoint was if we just can manage the data we will be able to have a govern system. So if we control the inputs then well have a safe environment, and that was kind of like the classic single source of truth, data warehouse type model. >> Stewards of the data. >> What we're seeing is with the proliferation of sources of data and how quickly with IOT and new modern sources, data is getting created, you're not able to manage data at that point of that entry point. And it's not just about systems, it's about individuals that go on the web and find a dataset and then load it into a corporate database, right? Or you merge an Excel file with something that in a database. And so I think what we see happening, not only when you look at bias but if you look at some of the new regulations like [Inaudible] >> Sure. Ownership, [Inaudible] >> The logic that you're using to process that data, the algorithm itself can be biased, if you have a biased training data site that you feed it into a machine learning algorithm, the algorithm itself is going to be biased. And so the control point in this world where data is proliferating and we're not sure we can control that entirely, becomes the logic embedded in the algorithm. Even if that's a simple sequel statement that's feeding a report. And so Alation is able to introspect that sequel and highlight that maybe there is bias at work and how this algorithm is composed. So with GDPR the consumer owns their own data, if they want to pull it out from a training data set, you got to rerun that algorithm without that consumer data and that's your control point then going forward for the organization on different governance issues that pop up. >> Talk about the psychology of the user base because one of the things that shifted in the data world is a few stewards of data managed everything, now you've got a model where literally thousands of people of an organization could be users, productivity users, so you get a social component in here that people know who's doing data work, which in a way, creates a new persona or class of worker. A non techy worker. >> Yeah. It's interesting if you think about moving access to the data and moving the individuals that are creating algorithms out to a broader user group, what's important, you have to make sure that you're educating and training and sharing knowledge with that democratized audience, right? And to be able to do that you kind of want to work with human psychology, right? You want to be able to give people guidance in the course of their work rather than have them memorize a set of rules and try to remember to apply those. If you had a specialist group you can kind of control and force them to memorize and then apply, the more modern approach is to say "look, with some of these machine learning techniques that we have, why don't we make a recommendation." What you're going to do is introduce bias into that calculation. >> And we're capturing that information as you use the data. >> Well were also making a recommendation to say "Hey do you know you're doing this? Maybe you don't want to do that." Most people are using the data are not bad actors. They just can't remember all the rule sets to apply. So what were trying to do is cut someone behaviorally in the act before they make that mistake and say hey just a bit of a reminder, a bit of a coaching moment, did you know what you're doing? Maybe you can think of another approach to this. And we've found that many organizations that changes the discussion around data governance. It's no longer this top down constraint to finding insight, which frustrates an audience, is trying to use that data. It's more like a coach helping you improve and then social aspect of wanting to contribute to the system comes into play and people start communicating, collaborating, the platform and curating information a little bit. >> I remember when Microsoft Excel came out, the spreadsheet, or Lotus 123, oh my God, people are going to use these amazing things with spreadsheets, they did. You're taking a similar approach with analytics, much bigger surface area of work to kind of attack from a data perspective, but in a way kind of the same kind of concept, put the hands of the users, have the data in their hands so to speak. >> Yeah, enable everyone to make data driven decisions. But make sure that they're interpreting that data in the right way, right? Give them enough guidance, don't let them just kind of attack the wild west and fair it out. >> Well looking back at the Microsoft Excel spreadsheet example, I remember when a finance department would send a formatted spreadsheet with all the rules for how to use it out of 50 different groups around the world, and everyone figured out that you can go in and manipulate the macros and deliver any results they want. And so it's that same notion, you have to know something about that, but this site, in many respects Stephanie you're describing a data governance model that really is more truly governance, that if we think about a data asset it's how do we mediate a lot of different claims against that set of data so that its used appropriately, so its not corrupted, so that it doesn't effect other people, but very importantly so that the out6comes are easier to agree upon because there's some trust and there's some valid behaviors and there's some verification in the flow of the data utilization. >> And where we give voice to a number of different constituencies. Because business opinions from different departments can run slightly counter to one another. There can be friction in how to use particular data assets in the business depending on the lens that you have in that business and so what were trying to do is surface those different perspectives, give them voice, allow those constituencies to work that out in a platform that captures that debate, captures that knowledge, makes that debate a knowledge of foundation to build upon so in many ways its kind of like the scientific method, right? As a scientist I publish a paper. >> Get peer reviewed. >> Get peer reviewed, let other people weigh in. >> And it becomes part of the canon of knowledge. >> And it becomes part of the canon. And in the scientific community over the last several years you see that folks are publishing their data sets out publicly, why can't an enterprise do the same thing internally for different business groups internally. Take the same approach. Allow others to weigh in. It gets them better insights and it gets them more trust in that foundation. >> You get collective intelligence from the user base to help come in and make the data smarter and sharper. >> Yeah and have reusable assets that you can then build upon to find the higher level insights. Don't run the same report that a hundred people in the organization have already run. >> So the final question for you. As you guys are emerging, starting to do really well, you have a unique approach, honestly we think it fits in kind of the new guard of analytics, a productivity worker with data, which is we think is going to be a huge persona, where are you guys winning, and why are you winning with your customer base? What are some things that are resonating as you go in and engage with prospects and customers and existing customers? What are they attracted to, what are they like, and why are you beating the competition in your sales and opportunities? >> I think this concept of a more agile, grassroots approach to data governance is a breath of fresh air for anyone who spend their career in the data space. Were at a turning point in industry where you're now seeing chief decision scientists, chief data officers, chief analytic officers take a leadership role in organizations. Munich Reinsurance is using their data team to actually invest and hold new arms of their business. That's how they're pushing the envelope on leadership in the insurance space and were seeing that across our install base. Alation becomes this knowledge repository for all of those mines in the organization, and encourages a community to be built around data and insightful questions of data. And in that way the whole organization raises to the next level and I think its that vision of what can be created internally, how we can move away from just claiming that were a big data organization and really starting to see the impact of how new business models can be creative in these data assets, that's exciting to our customer base. >> Well congratulations. A hot start up. Alation here on theCUBE in New York City for cubeNYC. Changing the game on analytics, bringing a breath of fresh air to hands of the users. A new persona developing. Congratulations, great to have you. Stephanie McReynolds. Its the cube. Stay with us for more live coverage, day one of two days live in New York City. We'll be right back.

Published Date : Sep 12 2018

SUMMARY :

Brought to you by SiliconANGLE Media the CMO, VP of Marketing for Alation, thanks for joining us. So you guys have a pretty spectacular so we brought a little fun to the show floor in the Alation booth is about the product You guys are one of the new guard companies is that making decisions and it's the trust gap and I really like the idea of the data scientists, production implementations get into the thousands of users. and asked them to certify data assets for others, kind of the decision scientists, gaps in governing that data or how you might want to so that the business could get optimized as you browse the web, right? in the past to determine revenue for that particular region, and one of the things that popped up is how do you deal and that was kind of like the classic it's about individuals that go on the web and find a dataset the algorithm itself is going to be biased. because one of the things that shifted in the data world And to be able to do that you kind of They just can't remember all the rule sets to apply. have the data in their hands so to speak. that data in the right way, right? and everyone figured out that you can go in in the business depending on the lens that you have And in the scientific community over the last several years You get collective intelligence from the user base Yeah and have reusable assets that you can then build upon and why are you winning with your customer base? and really starting to see the impact of how new business bringing a breath of fresh air to hands of the users.

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Ben Evans, Cisco & Connie Tang, Cisco | Google Cloud Next 2018


 

>> Live from San Francisco, it's theCUBE, covering Google Cloud Next 2018. Brought to you by Google Cloud and its ecosystem partners. >> Hello everyone, welcome back. It's theCUBE here in San Francisco, live coverage of Google Cloud Next 2018. I'm John Furrier, Dave Vellante, our next guest is Ben Evans, who is the director of strategic alliances at Cisco, and Connie Tang, director of product management at Cisco here to talk about the alliance with Google Cloud and the relevance of the partnership around the collab. Welcome to theCUBE, thanks for joining us. >> My pleasure to be here. >> So, we've been covering Cisco for a long time, most recently with theCUBE in Orlando, and DevNet creates huge surge of developer action going on across the Cisco ecosystem, not just network engineering stuff, the normal Cisco greatness, but up the stack with the collaboration side just cloud natives attracting and really giving a lot of energy to the developers and customers at Cisco. So, the partnership with Google is interesting. So, can you guys just share the big news, the Cisco news and how that relates to the Google Cloud. >> Yeah, absolutely, so firstly, Connie and myself have been working on this partnership for quite a while. And, as you'd said, there's multi, kind of, facets to this. There's the developer piece, so the SDKs are announcing around Android and the way that developers can now imbed calling and meeting and messaging inside their specific applications, their vertical applications. And, then there's also native integrations we're getting into around scheduling meetings from calenderings. I can go in and schedule a Webex meeting very easily. It was talked about on stage, 74 percent of, sort of, document collaboration involves some sort of co-collaboration, so it's a very kind of peanut butter and chocolate as you think about Cisco's portfolio of real time communications and meetings and how this is evolving into the team collaboration experience. Together with Google's portfolio in terms of AI and how that fits in to ultimate these work flows and make life easier for users. And, also just how this comes together in a very seamless way to enable this kind of real time collaboration and creation of documents. >> So, take us inside the partnership. How did it start? I mean, it seems like a match made in heaven. You guys aren't trying to create your own infrastructures of service. Google needs an enterprise presence, so obviously Cisco has a huge enterprise presence. But, how did it start and where did it start? >> We actually started engaging with Cisco over a year ago, and different groups start engaging because there's actually customer demand from our corporate enterprise customers wanting better integration of a collab portfolio into various aspects of G Suite. So, we worked with the calendering team because they're coming up with a brand new architecture, and so we're actually one of four front partners who work directly with them providing them feedback in what enterprises what, and then integrating our scheduling capabilities of Webex meetings directly into Google Calender. So that's one piece, and then we also work with the Chromebook group because more and more customers are starting to use and deploy Chromebook, and so they want to have an ability to start Webex meetings and be able to share content and actually join Webex meetings directly on Chromebook. So, there's another effort that went on separately. And then there's a third effort that goes on with the Chrome group where we're leveraging the WebRTC within Chrome, so that people can join Webex meeting directly without having to do download any client. So, they just open the web browser. They can have audio. They can have HD video. They can see the share. They can share content just on Chrome. >> When? >> This is what we've been waiting for with cloud. This is really, I want to expand on this notion of services. >> Yes. >> And service centric view because it has to be clean whether it's an EPI, a message que, or an event. The user experience's got to be integrated very cleanly. >> Yes. >> This is really kind of, the ah-ha moment of when people taste the Cloud, and that's the benefit. Can, because this is really interesting. You've got Webex, you've got G Suite. Two different applications. >> Very different, yes. >> This is the benefit of the services. Can you just explain the importance and why IT and why enterprises want this. >> Enterprises want ease of use. Ease of use, ease of access, and ease of deployment. So, Chrome solves that problem. There's no deployment required, right? It's already there, it's available on every desktop. And, the one simple click to join and schedule a meeting makes it easy to use, so with that combination, end use is adopted really, really quickly. So, we're seeing some of the fastest adoption of web clients based on those kind of ease of use and ease of joining. >> How has the product uptake been? Because if you have a seamless user experience, you're probably getting more customers coming in, integrating in... >> Yes. >> From G Suite and vice versa. They're getting lift. How is that partnership working? Can you share some color around that? >> Yes, as Connie said, we've really seen it's accelerating. One stat I'll share is during March, we were adding around 11 hundred new G Cal integrations every day, so we were seeing customers that were using Webex meeting, they were using G cal, and they wanted those things to work better together. So, integrating those calendars to make it easier to schedule and join meetings. So, yeah, that's 11 hundred a day. It's pretty good uptake considering we weren't really promoting it. It was just there and available to that existing customer base, so. >> What can you guys share to enterprise IT, application developers, or managers who have traditionally lived in a stone pipe world of like, let's build an app, and we'll distribute the app, and you log in, you do all the things, monolithic app. To a world that's services lead are service centric where you still do an app, but you got to think differently around some of the design criteria around integrating in with other apps. What's some of the best practices that you guys have found? Because you've seen the network all the way up to the application stack issues. You've got Kubernetes and all these new things. What are some of the best practices that companies should be developing around? >> So, what I've seen companies most concerned about is applications affecting other applications on the desktop, and hence, breaking some of their services. The web services kind of completely remove that. Because there's a web browser, they don't have to worry about it impacting any of their installed applications. And so, what we find out as IT looks into this mode of deployment, it's not really a deployment, it's an enablement. They actually really advertise it to their end users. They actually rather end users use the web client than to have to install, and they have to test and slow the roll out. >> What do you guys see as, I mean, I'm old enough to remember when Lotus Notes was the state of the art collaboration. (laughs) >> That's real old. Man, that's old. >> I was digging myself. So, now you're talking a lot about integration, simplifying the experience, obviously video has come into play. >> Yes. What do you guys see as the mega trends and maybe give us a little glimpse of the road map as to what we can expect going forward whether it's AI or other data? Where does that all fit in? >> Yeah, I think you nailed it. So, there's this kind of better together, easy join, it's just table stakes right now. The ability for me to easily join a meeting, but where that's really rapidly going is the AI space. So, how can I augment that meeting? Before I join, how do I know about you as individuals, what you care about, what's happening with your company? So, a company acquisition we did recently, you know, fits into that in terms of how do we start surfacing information about the people. If I'm in the meeting, if I want to be able to click on someone and get more context about them. What happened in my previous engagements, what have we previously talked about? How do we surface that up in a timely fashion? And, when again you think about Google Calender and the information it knows about you as an individual, Cisco with the kind of matrix of who you're calling and what meetings have taken place, there's kind of a tantalizing thing there about how you blend that together. So, you surface the information, you automate this kind of, the repetitive, more mundane tasks, and free the people up to focus more on innovation and collaboration relationships. >> And the analytics opportunity is pretty big. >> Yeah, absolutely. >> I mean Diane Green said in her keynote, security is the number one worry, AI is the number one opportunity. By freeing up the mundane tasks, automating that away, the value will shift to up the stack. We were using a metaphor with Jennifer Lynd from Google. You know, when the horse and buggy was, you know, killed by the car, those jobs went away. There was no need for stuff, you know, the horse, the hay, and all that stuff. IT, same thing. Things are shifting, operations are changing. >> Yeah. >> This is fundamental. >> Context is a great example of that. You know, if you look at what's happening in that market, you know, the predictions that they're call flows are going to decrease isn't really happening. What's happening is you're going to multi-channel, and people are doing the more basic stuff online, just fixing issues, but when it becomes complex, when it becomes relationship, it becomes high enough value, then you want the personal interaction, so I think the way personally I look at AI is it will free up computers. They're doing this kind of more repetitive finding patterns, but when it comes to talking to the doctor about, you know, your condition or you're trying to build relationships, there's things that people just naturally do very well. And, plowing through lots of data to find patterns, we don't do great, so. >> It's actually quite amazing when you look at the trends over the last decade or so in terms of collaboration. I mean, it used to be, I was joking about Lotus Notes, but it used to be you'd request people to show up 15 minutes early so you could sort out all the problems. And now today, if you're like a minute late, people are like texting you, "Where are you? Let's go." So, we become so much more productive, and the protocol has changed. So, when you think about how machine intelligence is going to affect productivity going forward, it's potentially massive. >> Yeah, we see massive opportunities. As you know, to really get the benefit from AI, you need some pretty big data sets, so again, just thinking about Webex for a second, six billion minutes a month in meetings. I'm not saying we're going to push all that straight into Google, but when you think about what's tied up in those six billion minutes. >> A lot of video. >> What's been discussed, how easily can I unlock that? How do I get insights from it? How do I train models? It's like, again, the combination of huge data sets. >> AI would be just amazing. You just go, "Hey, I missed that Webex. Give me the highlight reel." >> Yes. >> Exactly. >> That would be great. >> Not only that, but how do you customize that for the individuals? >> Or if I missed the first ten minutes, can I go scroll back? Can I actually review, get the transcription? And, if I need some additional information, can I just pull it up and it shows up, you know, for me within the meeting, right? So, there's just massive opportunities that we're looking at. >> And, the user expectations, the new experience, that's what people are really designing around, what they're expectations should be. >> Yes. >> And they're making that user... Okay, Connie and Ben, I want to get one last question in before we break. Two parts, for each of you. What's the most important story from your perspective here at the show this week that you're talking about and sharing, and what's next for you guys? Ben, we'll start with you. >> So, yeah, my two answers are firstly, the initial kind of integrations we're putting together. People should go check that out because, you know, there's some very compelling use cases that we're fixing there. But, the big item is Cisco and Google working together to really tackle this kind of future of work, and the combination of those two portfolios is going to unlock some really interesting opportunities, and that's what the teams are kind of getting together, working on, defining, and stay tuned to kind of see those phase two, phase three deliverables. >> Future words. Great, Connie, from a product perspective, what's the hottest things that you've been talking about here, most important, and then what's next. >> Yeah, for us, it's really the Google and Cisco coming together in a collaboration space, working together to make it much easier and simpler for customers to deploy and use the products. And, also to explore new opportunities in transcription and AI, leveraging Google Assist right to, and just make it even better in the future. >> Scale up the experience. >> Yes. >> Probably expect some great developer opportunities going on. >> Yes. >> Exploring and reinventing the enterprise. That was Diane Green's theme. She'll be here on theCUBE breaking it down. I'm John Furrier with Dave Vellante. Live coverage, here we have Cisco collaboration inside theCUBE, big relationship, expansion with Google. New product integrations, the value of the services within the cloud. The new model for development and user experience. theCUBE bringing you all the content here on the floor. Stay with us for more live coverage after the short break. (upbeat music)

Published Date : Jul 24 2018

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Dinesh Nirmal, IBM | CUBEConversation


 

(upbeat music) >> Hi everyone. We have a special program today. We are joined by Dinesh Nirmal, who is VP of Development and Analytics, for Analytics at the IBM company and Dinesh has an extremely broad perspective on what's going on in this part of the industry, and IBM has a very broad portfolio. So, between the two of us, I think we can cover a lot of ground today. So, Dinesh, welcome. >> Oh thank you George. Great to be here. >> So just to frame the discussion, I wanted to hit on sort of four key highlights. One is balancing the compatibility across cloud on-prem, and edge versus leveraging specialized services that might be on any one of those platforms. And then harmonizing and simplifying both the management and the development of services across these platforms. You have that trade-off between: do I do everything compatibly; or can I take advantage of platforms, specific stuff? And then, we've heard a huge amount of noise on Machine Learning. And everyone says they're democratizing it. We want to hear your perspective on how you think that's most effectively done. And then, if we have time, the how to manage Machine Learning feedback, data feedback loops to improve the models. So, having started with that. >> So you talked about the private cloud and the public cloud and then, how do you manage the data and the models, or the other analytical assets across the hybrid nature of today. So, if you look at our enterprises, it's a hybrid format that most customers adopt. I mean you have some data in the public side; but you have your mission critical data, that's very core to your transactions, exist in the private cloud. Now, how do you make sure that the data that you've pushed on the cloud, that you can go use to build models? And then you can take that model deployed on-prem or on public cloud. >> Is that the emerging sort of mainstream design pattern, where mission critical systems are less likely to move, for latency, for the fact that they're fused to their own hardware, but you take the data, and the researching for the models happens up in the cloud, and then that gets pushed down close to where the transaction decisions are. >> Right, so there's also the economics of data that comes into play, so if you are doing a, you know, large scale neural net, where you have GPUs, and you want to do deep learning, obviously, you know, it might make more sense for you to push it into the cloud and be able to do that or one of the other deep learning frameworks out there. But then you have your core transactional data that includes your customer data, you know, or your customer medical data, which I think some customers might be reluctant to push on a public cloud, and then, but you still want to build models and predict and all those things. So I think it's a hybrid nature, depending on the sensitivities of the data. Customers might decide to put it on cloud versus private cloud which is in their premises, right? So then how do you serve those customer needs, making sure that you can build a model on the cloud and that you can deploy that model on private cloud or vice versa. I mean, you can build that model on private cloud or only on private, and then deployed on your public cloud. Now the challenge, one last statement, is that people think, well, once I build a model, and I deploy it on public cloud, then it's easy, because it's just an API call at that time, just to call that model to execute the transactions. But that's not the case. You take support vector machine, for example, right, that still has vectors in there, that means your data is there, right, so even though you're saying you're deploying the model, you still have sensitive data there, so those are the kind of things customers need to think about before they go deploy those models. >> So I might, this is a topic for our Friday interview with a member of the Watson IT family, but it's not so black and white when you say we'll leave all your customer data with you, and we'll work on the models, because it, sort of like, teabags, you know, you can take the customer's teabag and squeeze some of the tea out, in your IBM or public cloud, and give them back the teabag, but you're getting some of the benefit of this data. >> Right, so like, it depends, depends on the algorithms you build. You could take a linear regression, and you don't have the challenges I mentioned, in support of retro machine, because none of the data is moving, it's just modeled. So it depends, I think that's where, you know, like Watson has done, will help tremendously because the data is secure in that sense. But if you're building on your own, it's a different challenge, you've got to make sure you pick the right algorithms to do that. >> Okay, so let's move on to the modern sort of what we call operational analytic pipeline, where the key steps are ingest, process, analyze, predict, serve, and you can drill down on those more. Today there's, those pipelines are pretty much built out of multi-vendor components. How do you see that evolving under pressures of, or tension between simplicity, coming from one vendor, and the pieces all designed together, and the specialization, where you want to have a, you know, unique tool in one component. >> Right, so you're exactly right. So you can take a two prong approach. One is, you can go to a cloud provider, and get each of the services, and you stitch it together. That's one approach. A challenging approach, but that has its benefits, right, I mean, you bring some core strengths from each vendor into it. The other one is the integrate approach, where you ingest the data, you shape or cleanse the data, you get it prepared for analytics, you build the model, you predict, you visualize. I mean, that all comes in one. The benefit there is you get the whole stack in one, you have one you have a whole pipeline that you can execute, you have one service provider that's giving them services, it's managed. So all those benefits come with it, and that's probably the preferred way for it integrated all together in one stack, I think that's the path most people go towards, because then you have the whole pipeline available to you, and also the services that comes with it. So any updates that comes with it, and how do you make sure, if you take the first round, one challenge you have is how do you make sure all these services are compatible with each other? How do you make sure they're compliant? So if you're an insurance company, you want it to be HIPAA compliant. Are you going to individually make sure that each of these services are HIPAA compliant? Or would you get from one integrated provider, you can make sure they are HIPAA compliant, tests are done, so all those benefits, to me, outweigh you going, putting unmanaged service all together, and then creating a data link to underlay all of it. >> Would it be fair to say, to use an analogy, where Hadoop, being sort of, originating in many different Apache products, is a quasi-multi vendor kind of pipeline, and the state of, the state of the machine learning analytic pipeline, is still kind of multi-vendor today. You see that moving toward single vendor pipeline, who do you see as the sort of last man standing? >> So, I mean, I can speak from an IBM perspective, I can say that the benefit that a company, a vendor like IBM brings forward, is like, so the different, public or private cloud or hybrid, you obviously have the choice of going to public cloud, you can get the same service on public cloud, so you get a hybrid experience, so that's one aspect of it. Then, if you get the integrated solution, all the way from ingest to visualization, you have one provider, it's tested, it's integrated, you know, it's combined, it works well together, so I would say, going forward, if you look at it purely from an enterprise perspective, I would say integrated solutions is the way to go, because that what will be the last man standing. I'll give you an example. I was with a major bank in Europe, about a month ago, and I took them through our data science experience, our machine learning project and all that, and you know, the CTO's take was that, Dinesh, I got it. Building the model itself, it only took us two days, but incorporating our model into our existing infrastructure, it has been 11 months, we haven't been able to do it. So that's the challenge our enterprises face, and they want an integrated solution to bring that model into their existing infrastructure. So that's, you know, that's my thought. >> Today though, let's talk about the IBM pipeline. Spark is core, Ingest is, off the-- >> Dinesh: Right, so you can do spark streaming, you can use Kafka, or you can use infostream which is our proprietary tool. >> Right, although, you wouldn't really use structured streaming for ingest, 'cause of the back pressure? >> Right, so they are-- >> The point that I'm trying to make is, it's still multi-vendor, and then the serving side, I don't know, where, once the analysis is done and predictions are made, some sort of sequel database has to take over, so it's, today, it's still pretty multi vendor. So how do you see any of those products broadening their footprints so that the number of pieces decreases. >> So good question, they are all going to get into end pipeline, because that's where the value is, unless you provide an integrated end to end solution for a customer, especially parts customer it's all about putting it all together, and putting these pieces together is not easy, even if you ingest the data, IOP kind of data, a lot of times, 99% of the time, data is not clean, unless you're in a competition where you get cleansed data, in real world, that never happens. So then, I would say 80% of a data scientists time is spent on cleaning the data, shaping the data, preparing the data to build that pipeline. So for most customers, it's critical that they get that end to end, well oiled, well connected solution integrated solution, than take it from each vendor, every isolated solution. To answer your question, yes, every vendor is going to move into the ingest, data cleansing phase, transformation, and the building the pipeline and then visualization, if you look at those five steps, has to be developed. >> But just building the data cleansing and transformation, having it in your, native to your own pipeline, that doesn't sound like it's going to solve the problem of messy data that needs, you know, human supervision to correct. >> I mean, so there is some level of human supervision to be sure, so I'll give you an example, right, so when data from an insurance company goes, a lot of times, the gender could be missing, how do you know if it's a male or female? Then you got to build another model to say, you know, this patient has gone for a prostate exam, you know, it's a male, gynecology is a female, so you have to do some intuitary work in there, to make sure that the data is clean, and then there's some human supervision to make sure that this is good to build models, because when you're executing that pipeline in real time, >> Yeah. >> It's all based on the past data, so you want to make sure that the data is as clean as possible to train and model, that you're going to execute on. >> So, let me ask you, turning to a slide we've got about complexity, and first, for developers, and then second, for admins, if we take the steps in the pipeline, as ingest, process, analyze, predict, serve, and sort of products or product categories as Kafka, Spark streaming and sequel, web service for predict, and MPP sequel, or no sequel for serve, even if they all came from IBM, would it be possible to unify the data model, the addressing and name space, and I'm just kicking off a few that I can think of, programming model, persistence, transaction model, workflow, testing integration, there's one thing to say it's all IBM, and then there's another thing, so that the developer working with it, sees as it as one suite. >> So it has to be validated, and that's the benefit that IBM brings already, because we obviously test each segment to make sure it works, but when you talk about complexity, building the model is one, you know, development of the model, but now the complexity also comes in the deployment of the model, now we talk about the management of the model, where, how you monitor it? When was the model deployed, was it deployed in tests, was it deployed in production, and who changed that model last, what was changed, and how is it scoring? Is it scoring high or low? You want to get notification when the model starts going low. So complexity is all the way across, all the way from getting the data, in cleaning the data, developing the model, it never ends. And the other benefit that IBM has added is the feedback loop, where when you talk about complexity, it reduces the complexity, so today, if the model scores low, you have to take it offline, retrain the model based on the new data, and then redeploy it. Usually for enterprises, there is slots where you can take it offline, put it back online, all these things, so it's a process. What we have done is created a feedback loop where we are training the model in real time, using real time data, so the model is continuously-- >> Online learning. >> Online learning. >> And challenger, champion, or AB testing to see which one is more robust. >> Right, so you can do that, I mean, you could have multiple models where you can do AB testing, but in this case, you can condition, train the model to say, okay, this model scores the best. And then, another benefit is that, if you look at the whole machine learning process, there's the data, there's development, there's deployment. On development side, more and more it's getting commoditized, meaning picking the right algorithm, there's a lot of tools, including IBM, where he can say, question what's the right one to use for this, so that piece is getting a little, less complex, I don't want to say easier, but less complex, but the data cleansing and the deployment, these are two enterprises, when you have thousands of models how do you make sure that you deploy the right model. >> So you might say that the pipeline for managing the model is sort of separate from the original data pipeline, maybe it includes the same technology, or as much of the same technology, but once your pipeline, your data pipeline is in production, the model pipeline has to keep cycling through. >> Exactly, so the data pipeline could be changing, so if you take a lone example, right, a lot of the data that goes in the model pipeline, is static, I mean, my age, it's not going to change every day, I mean, it is, but you know, the age that goes into my salary, my race, my gender, those are static data that you can take from data and put it in there, but then there's also real time data that's coming, my loan amount, my credit score, all those things, so how do you bring that data pipeline between real time and static data, into the model pipeline, so the model can predict accurately and based on the score dipping, you should be able to re-try the model using real time data. >> I want to take, Dinesh, to the issue of a multi-vendor stack again, and the administrative challenges, so here, we look at a slide that shows me just rattling off some of the admin challenges, governance, performance modeling, scheduling orchestration, availability, recovering authentication, authorization, resource isolation, elasticity, testing integration, so that's the Y-axis, and then for every different product in the pipeline, as the access, say Kafka, Spark, structured streaming MPP, sequel, no sequel, so you got a mess. >> Right. >> Most open source companies are trying to make life easier for companies by managing their software as a service for the customer, and that's typically how they monetize. But tell us what you see the problem is, or will be with that approach. >> So, great question. Let me take a very simple example. Probably most of our audience know about GDPR, which is the European law to write to forget. So if you're an enterprise, and say, George, I want my data deleted, you have to delete all of my data within a period of time. Now, that's where one of the aspects you talked about with governance comes in. How do you make sure you have governance across not just data but your individual assets? So if you're using a multi-vendor solution, in all of that, that state governance, how do I make sure that data get deleted by all these services that's all tied together. >> Let me maybe make an analogy. On CSI, when they pick up something at the crime scene, they got to make sure that it's bagged, and the chain of custody doesn't lose its integrity all the way back to the evidence room. I assume you're talking about something like that. >> Yeah, something similar. Where the data, as it moves between private cloud, public cloud, analytical assets, is using that data, all those things need to work seamlessly for you to execute that particular transaction to delete data from everywhere. >> So that's, it's not just administrative costs, but regulations that are pushing towards more homogenous platforms. >> Right, right, and even if you take some of the other things on the stack, monitoring, logging, metering, provides some of those capabilities, but you have to make sure when you put all these services together, how are they going to integrate all together? You have one monitoring stack, so if you're pulling you know, your IOT kind of data into a data center, or your whole stack evaluation, how do you make sure you're getting the right monitoring data across the board? Those are the kind of challenges that you will have. >> It's funny you mention that, because we were talking to an old Lotus colleague of mine, who was CTO of Microsoft's IT organization, and we were talking about how the cloud vendors can put machine learning application, machine learning management application across their properties, or their services, but he said one of the first problems he'll encounter is the telemetry, like it's really easy on hardware, CPUs, utilization, memory utilization, a noise enabler for iO, but as you get higher up in the application services, it becomes much more difficult to harmonize, so that a program can figure out what's going wrong. >> Right, and I mean, like anomaly detection, right? >> Yes. >> I mean, how do you make sure you're seeing patterns where you can predict something before it happens, right? >> Is that on the road map for...? >> Yeah, so we're already working with some big customers to say, if you have a data center, how do you look at outage to predict what can go wrong in the future, root cause analysis, I mean, that is a huge problem solved. So let's say customer hit a problem, you took an outage, what caused it? Because today, you have specialists who will come and try to figure out what the problem is, but can we use machine learning or deep learning to figure out, is it a fix that was missing, or an application got changed that caused a CPU spike, that caused the outage? So that whole cost analysis is the one that's the hardest to solve, because you are talking about people's decades worth of knowledge, now you are influencing a machine to do that prediction. >> And from my understanding, root cause analysis is most effective when you have a rich model of how your, in this case, data structure and apps are working, and there might be many little models, but they're held together by some sort of knowledge graph that says here is where all the pieces fit, these are the pieces below these, sort of as peers to these other things, how does that knowledge graph get built in, and is this the next generation of a configuration management database. >> Right, so I call it the self-healing, self-managing, self-fixing data center. It's easy for you to turn up the heat or A/C, the temperature goes down, I mean, those are good, but the real value for a customer is exactly what you mentioned, building up that knowledge graft from different models that all comes together, but the hardest part, is, how do you, predicting an anomaly is one thing, but getting to the root cause is a different thing, because at that point, now you're saying, I know exactly what's caused this problem, and I can prevent it from happening again. That's not easy. We are working with our customers to figure out how do we get to the root cause analysis, but it's all about building the knowledge graph with multiple models coming from different systems, today, I mean enterprises have different systems from multi-vendors. We have to bring all that monitoring data into one source, and that's where that knowledge comes in, and then different models will feed that data, and then you need to prime that data, using deep learning algorithms to say, what caused this? >> Okay, so this actually sounds extremely relevant, although we're probably, in the interest of time, going to have to dig down on that one another time, but, just at a high level, it sounds like the knowledge graph is sort of your web or directory, into how local components or local models work, and then, knowing that, if it sees problems coming up here, it can understand how it affects something else tangentially. >> So think of knowledge graph as a neural net, because it's just building new neural net based on the past data, and it has that built-in knowledge where it says, okay, these symptoms seem to be a problem that I have encountered in the past. Now I can predict the root cause because I know this happened in the past. So it's kind of like you putting that net to build new problem determinations as it goes along. So it's a complex task. It's not easy to get to root cause analysis. But that's something we are aggressively working on developing. >> Okay, so let me ask, let's talk about sort of democratizing machine learning and the different ways of doing that. You've actually talked about the big pain points, maybe not so sexy, but that are critical, which is operationalizing the models, and preparing the data. Let me bounce off you some of the other approaches. One that we have heard from Amazon is that they're saying, well, data expunging might be an issue, and operationalizing the models might be an issue, but the biggest issue in terms of making this developer ready, is we're going to take the machine learning we use to run our business, whether it's merchandising fashion, running recommendation engines, managing fulfillment or logistics, and just like I did with AWS, they're dog-fooding it internally, and then they're going to put it out on AWS as a new layer of a platform. Where do you see that being effective, and where less effective? >> Right, so let me answer the first part of your question, the democratization of learning. So that happens when for example, a real estate agent who has no idea about machine learning, be able to come and predict the house prices in this area. That's to me, is democratizing. Because at that time, you have made it available to everyone, everyone can use it. But that comes back to our first point, which is having that clean set of data. You can build all the pre-canned pipelines out there, but if you're not feeding the set of data into, none of this, you know. Garbage in, garbage out, that's what you're going to get. So when we talk about democratization, it's not that easy and simple because you can build all this pre-canned pipelines that you have used in-house for your own purposes, but every customer has many unique cases. So if I take you as a bank, your fraud detection methods is completely different than me as a bank, my limit for fraud detection could be completely different. So there is always customization that's involved, the data that's coming in is different, so while it's a buzzword, I think there's knowledge that people need to feed it, there's models that needs to be tuned and trained, and there's deployment that is completely different, so you know, there is work that has to be done. >> So then what I'm taking away from what you're saying is, you don't have to start from ground zero with your data, but you might want to add some of your data, which is specialized, or slightly different from what the pre-trained model is, you still have to worry about operationalizing it, so it's not a pure developer ready API, but it uplevels the skills requirement so that it's not quite as demanding as working with TensorFlow or something like that. >> Right, I mean, so you can always build pre-canned pipelines and make it available, so we have already done that. For example, fraud detection, we have pre-canned pipelines for IT analytics, we have pre-canned pipelines. So it's nothing new, you can always do what you have done in house, and make it available to the public or the customers, but then they have to take it and have to do customization to meet their demands, bring their data to re-train the model, all those things has to be done, it's not just about providing the model, but every customer use case is completely different, whether you are looking at fraud detection from that one bank's perspective, not all banks are going to do the same thing. Same thing for predicting, for example, the loan, I mean, your loan approval process is going to be completely different than me as a bank loan approval process. >> So let me ask you then, and we're getting low on time here, but what would you, if you had to characterize Microsoft, Azure, Google, Amazon, as each bringing to bear certain advantages and disadvantages, and you're now the ambassador, so you're not a representative of IBM, help us understand the sweet spot for each of those. Like you're trying to fix the two sides of the pipeline, I guess, thinking of it like a barbell, you know, where are the others based on their data assets and their tools, where do they need to work. >> So, there's two aspects of it, there's enterprise aspect, so as an enterprise, I would like to say, it's not just about the technology, but there's also the services aspect. If my model goes down in the middle of the night, and my banking app is down, who do I call? If I'm using a service that is available on the cloud provider which is open source, do I have the right amount of coverage to call somebody and fix it. So there's the enterprise capabilities, availabilities, reliability, that is different, than a developer comes in, has a CSV file that he or she wants to build a model to predict something, that's different, this is different, two different aspects. So if you talk about, you know, all these vendors, if I'm bearing an enterprise card, some of the things I would look is, can I get an integrated solution, end to end on the machine learning platform. >> And that means end to end in one location, >> Right. >> So you don't have network issues or latency and stuff like that. >> Right, it's an integrated solution, where I can bring in the data, there's no challenges to latency, those kinds of things, and then can I get the enterprise level service, SLA all those things, right? So, in there, the named vendors obviously have an upper hand, because they are preferred to enterprises than a brand new open source that will come along, but then there is, within enterprises, there are a line of businesses building models, using some of the open source vendors, which is okay, but eventually they'd have to get deployed and then how do you make sure you have that enterprise capabilities up there. So if you ask me, I think each vendor brings some capabilities. I think the benefit IBM brings in is, one, you have the choice or the freedom to bring in cloud or on-prem or hybrid, you have all the choices of languages, like we support R, Python Spar, Spark, I mean, SPS, so I mean, the choice, the freedom, the reliability, the availability, the enterprise nature, that's where IBM comes in and differentiates, and that's for our customers, a huge plus. >> One last question, and we're really out of time, in terms of thinking about a unified pipeline, when we were at Spark Summit, sitting down with Matei Zaharia and Reynold Shin, the question came up, the data breaks has an incomplete pipeline, no persistence, no ingest, not really much in the way of serving, but boy are they good at, you know, data transmigration, and munging and machine learning, but they said they consider it part of their ultimate responsibility to take control. And on the ingest side it's Kafka, the serving side, might be Redis or something else, or the Spark databases like Snappy Data and Splice Machine. Spark is so central to IBM's efforts. What might a unified Spark pipeline look like? Have you guys thought about that? >> It's not there, obviously they probably could be working on it, but for our purpose, Spark is critical for us, and the reason we invested in Spark so much is because of the executions, where you can take a tremendous amount of data, and, you know, crunch through it in a very short amount of time, that's the reason, we also invented Spark Sequel, because we have a good chunk of customers still use Sequel heavily, We put a lot of work into the Spark ML, so we are continuing to invest, and probably they will get to and integrated into a solution, but it's not there yet, but as it comes along, we'll adapt. If it meets our needs and demands, and enterprise can do it, then definitely, I mean, you know, we saw that Spark's core engine has the ability to crunch a tremendous amount of data, so we are using it, I mean, 45 of our internal products use Spark as our core engine. Our DSX, Data Science Experience, has Spark as our core engine. So, yeah, I mean, today it's not there, but I know they're probably working on it, and if there are elements of this whole pipeline that comes together, that is convenient for us to use, and at enterprise level, we will definitely consider using it. >> Okay, on that note, Dinesh, thanks for joining us, and taking time out of your busy schedule. My name is George Gilbert, I'm with Dinesh Nirmal from IBM, VP of Analytics Development, and we are at the Cube studio in Palo Alto, and we will be back in the not too distant future, with more interesting interviews with some of the gurus at IBM. (peppy music)

Published Date : Aug 22 2017

SUMMARY :

So, between the two of us, I think Oh thank you George. the how to manage Machine Learning feedback, that you can go use to build models? but you take the data, and the researching for and that you can deploy that model on private cloud but it's not so black and white when you say and you don't have the challenges I mentioned, and the specialization, where you want to have and get each of the services, and you stitch it together. who do you see as the sort of last man standing? So that's, you know, that's my thought. Spark is core, Ingest is, off the-- Dinesh: Right, so you can do spark streaming, so that the number of pieces decreases. and then visualization, if you look at those five steps, of messy data that needs, you know, human supervision so you want to make sure that the data is as clean as in the pipeline, as ingest, process, analyze, if the model scores low, you have to take it offline, to see which one is more robust. Right, so you can do that, I mean, you could have So you might say that the pipeline for managing I mean, it is, but you know, the age that goes MPP, sequel, no sequel, so you got a mess. But tell us what you see the problem is, Now, that's where one of the aspects you talked about and the chain of custody doesn't lose its integrity for you to execute that particular transaction to delete but regulations that are pushing towards more Those are the kind of challenges that you will have. It's funny you mention that, because we were to say, if you have a data center, how do you look at most effective when you have a rich model and then you need to prime that data, using deep learning but, just at a high level, it sounds like the knowledge So it's kind of like you putting that net Let me bounce off you some of the other approaches. pipelines that you have used in-house for your own purposes, the pre-trained model is, you still have to worry So it's nothing new, you can always do what you have So let me ask you then, and we're getting low on time So if you talk about, you know, all these vendors, So you don't have network issues or latency and then how do you make sure you have that but boy are they good at, you know, where you can take a tremendous amount of data, of the gurus at IBM.

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Reuven Cohen, Aporeto & Huffington Post - Mobile World Congress 2017 - #MWC17 - #theCUBE


 

(light techno music) >> Hello and welcome to our special Mobile World Congress '1, #MWC17. I'm John Furrier inside theCUBE Studio breaking down all the analysis we're going to be covering at Mobile World Congress. We kind of know some news is coming out, that's Monday and Tuesday all day coverage. We're here with @rUvreuv, Reuv Cohen, an entrepreneur I've known for years. Going back to when we first met in the cloud days back in '08 timeframe, '09, when dev ops was really the beginning of the movement. You've been an entrepreneur, you've sold multiple companies, multi-time successful entrepreneur. But you've been deep in the cloud game. Welcome to theCUBE special coverage of Mobile World Congress. >> Thanks for inviting me, I'm happy to be here. >> The other thing, too, is we just tried to get the Periscope thing working so we have our little Periscopes going here. But this is really the media landscape that's going to be one of the themes at Mobile World Congress that certainly will be front and center. These service providers have to have a business model. And media entertainment has been on their to-do list. Just a lot of the plumbing hasn't gotten done. And the new trend that's going to be really front and center is AI. We were joking about that. But seriously, you're doing a lot of discussions around AI. And then Intel's 5G now, which they pre-announced this week, prior to Mobile World Congress with 5G. Their positioning is a step-up game changer. So you got 5G overlay network, you have real plumbing that's getting done with NFV, Network Functions Virtualization. You have the app market exploding. Will the service providers ever make it? Will the telco's actually figure out a business model? >> Well, you know, they're always the pipes, and you're always going to need pipes. There's an endless amount of opportunities for those people figuring out what to do with those pipes. I don't know, this is the question we've been asked for 20 years. Do they want to be more than dumb pipes, right? >> Well, they've yet to find a business model. I mean, I think one of the things, I was looking at the Intel announcement, was, is 5G a technology looking for a problem, or does it really actually create a step-up function in terms of capability. I mean 4G is just an evolution of 3G, LTE is getting some speeds there. But, I mean, my family hits their caps on all the data we're doing. People are hitting their data caps, we need more data. So the question is, is that going to be ready for prime time? Your thoughts on? >> Well, there's almost like a Moore's law of data, right. The more data you have available to use, the more things you can do with it. You know, Periscope's a prime example. Now they're doing a whole variety of different video-related things, Facebook lives, there's a YouTube lives, everyone wants to do live. And all that requires massive amounts of data, especially if you want to do high definition related things. We were actually trying to set up a Periscope before the broadcast this morning. And one of the first things that became apparent was we had to limit our bit rate to 800 kilobits, which is relatively small when you think about it. >> Yeah, that's the bandwidth issues. I mean, at the end of the day it comes down to the last miles, we always say. But let's get into some of the analysis of Mobile World Congress and let's get down under the hood. Is could truly ready for prime time? And when I say cloud, I mean, obviously, full-stack infrastructure because network virtualization has been one of those kind of shifting sands, if you will. NFV has been one of those things that's been kind of evolving. OpenStack is seen to be much more of a telco use case at some of the OpenStack summits we've covered. Your thoughts on the progress of cloud-ready telcos? >> You know it comes down to, if you're going to build an application, whether you're an enterprise, whether you're an individual developer or something in between, you're probably not going to build it in your own data center. Whether that's a closet in the back of your office, or your own... You're probably going to go and build something that's quick and fast and efficient. And that really is starting to look like things that are server-less, things that are event-driven and that isn't really sitting in your own data center anymore. >> So what's your take on the ecosystem? Do you think that the ecosystem play for the Mobile World Congress is going to shift at all? I mean, I was commenting to Dave Vellante just last week and Jeff Frick, here on theCUBE team that CES, which we don't go to anymore because it's gotten too big. But this year we did cover it here in the studio like we're doing with Mobile World Congress. It just seems that CES is no longer a consumer electronics show, it's more of a car show. Autonomous vehicles are, obviously, front and center, that's the glam, that's the eye candy. Mobile World Congress doesn't seem to be a device show anymore, or it's shifting away. Last year Mark Zuckerberg gave the keynote speech, and you saw that shift. What's Mobile World Congress turning into, in your opinion? >> It's an app show. So, where CES still sort of has this focus on the actual physical things that you can touch and build. The mobile apps of the world are now the things that dominate mobility. Is a phone interesting? Not really. (John laughs) What you do on your phone is definitely interesting. >> It's interesting to look at also, and talking to folks about, Mobile World Congress is one of those shows, it's a biz dev show, too. A lot of people who fly over to Barcelona don't really go for the pure content. There's more business deals going on. All the top executives of the big technology companies go there. Your thoughts on landscape of the vendors out there that are suppliers to this new consumerized market. You see deals happening that you think would be interesting? Where do you see the formation of the industry lining up? Obviously, some things have to get done at a technical level. 5G's great, great hope for that. But some companies are trying to transform look at Cisco, companies like Cisco, companies like Hewlett-Packard Enterprise, VM Ware, AWS, Google, Intel, Qualcomm. I mean there seems to be a feeling of posturing and a reef-set, if you will. >> 2017, so far, is shaping up to be the year of Snapchat, if you ask me. With a pending IPO they're saying that their revenues are going to be increasing 5x. It looks like everything we've been talking about, the app-based world, is sort of culminating in this Snapchat thing. So the question is, is Snapchat going to live up to all the hype that's surrounding them as this sort of, next generation of you know, the next Facebook, the next Google, the next whatever. >> Well it's interesting, Snapchat brings up the conversation of, the people who have their head in the sand versus people who are riding this wave. Facebook was totally pooh-pooh'ed during the IPO. I remember leading up to the IPO, it was like, oh my God, there's no way they can do it. They can never be the next Google, that was kind of the comparison. Google was compared to Microsoft, and then Facebook was compared to Google. And then everyone was like, no frickin' way that's going to happen. Why would anyone want to seed that company? It's a social net for college kids, and now some adults are coming on. And then look what happened, so the world changed. Snapchat's the same way, so it's interesting, it's not what you think. The core competency shifts and the user consumption becomes democratized. So the question is, what does Snapchat mean for telcos? Does that mean that they're just pipes? What do they do? How do they get in front of this? You got Netflix, you got Amazon out there with, now, the video stuff. >> People want content and they want it fast, they want it in high quality and they want it on the go. So, yeah it is the question. I think that the challenge that a lot of these telco's are having is the fact that they still have a bit of a monopoly in many parts of the world and they use that monopoly to inflict quite a bit of pain. So it's, I don't think that's something that they're going to be able to get away with very much longer. >> So what's your take on AI? Since you've been doing a lot of AI. And obviously, AI's been around. In the 80's when I got my CS degree, LISP was out there, neural networks, object-oriented programming was hitting the scene. You know, you had this kind of mind-set, and it was still, AI was this elusive academic mental model and some coding. Now it's all the rage, when you look at autonomous vehicles and you look at IOT, drones, a new landscape is here, connected consumer. Your thoughts on where AI, is it, right now, certainly it's hyped, we all agree on that. >> There's been several iterations of AI over the last 40 years. Every time technology appears you hear about AI. In the 70's you saw things like Space Odyssey and there was this rush to AI-related activities around the first generation of computing. Then that sort of, we realized it wasn't really possible and it disappeared for 25 years. Then it reemerged in your early days of internet, oh, it was still too early. (John laughs) So now 15, 20 years later, again, we are in this, another dawn of AI. But there is some critical differences. Now there are tooling that allows you to do the sorts of things that we had only dreamt of before, whether it's natural language processing, generation of information and other various forms of analytics. So all these things are culminating in these opportunities that were really never possible until now, including things like cloud computing. >> Machine learning certainly is the center of that. I love the machine learning rates. But machine learning's been around for a long time as well. I mean machine learning isn't necessarily new, it's mostly software that has to do with algorithms. But now you have data to compute. This is the new thing, right? Data's available and you got tons to compute. >> Yeah, it was hard >> Yeah. >> It was really, really hard. And anyone that's actually tried to go out and do a machine learning system, neural net, realized quite quickly that you had to be a phD to figure out how to use these tools. So now all these tools are being put together into platforms and end-user applications. So no longer do I have to go and try to put together a Lego, you know, erector set of stuff. I can go, I can get mostly everything I need to solve a problem and I can be off to the races quite quickly. >> So what's your up work you're doing now, Reuv? You've been an entrepreneur, give us the latest update on what's in your world right now. You were, obviously, instrumental in a lot of cloud ventures and, obviously, you've been in the industry, certainly as an influencer as well, you've got the little blue check on Twitter, which I don't have yet. Twitter rejected me twice, I got to get to the... Stu has it, Stu Miniman on our team. In all seriousness, this is a new world and you're on the front lines both as a media producer, you've got a great podcast, but also you're in the industry. Where is cloud going and where's that top of the stack action because that really is, you mentioned apps, that's where the action is right now. What do you see happening and what are you up to these days? >> Well, you know, a couple areas. One of the things they don't tell you is, after you sell your business, you lose a little bit of your purpose. (laughs) Personal problem, for sure, but. >> You make some good cash. >> Yeah, exactly. Put it in the bank there, bank some cash. >> Yeah, so after Anomaly and Virtual Stream exited there was this period where I get to do things that I want to do. And investing in other start ups was, you know, the thing that apparently, you do. I focused heavily on AI-related companies. Actually I just recently did an investment in a company called Zoom.AI, which is really doing some cool stuff around enterprise-focused AI work. Also, I've got a day job as well outside that. I recently joined a company here in San Jose that focuses on security for containerized environments. So, sort of policy-based security, very low level stuff. >> At the orchestration layer, or at the docker layer or where would you...? >> It's at, it's even lower than that. It essentially orchestrates the policy around things like system calls and networking itself. So, rather than having to focus on the complexities of all the various parts of an environment, what we do is we basically say, hey, look at the tags that exist and things like Kubernetes. And then those tags define the policies in which things can communicate with one another. Let's say it's a layer three network, or what has read or write access to the system calls themselves. >> Is that a new company for you, that you guys launched? >> Well, we're in the process of launching. >> So stealth? >> It's stealthy, I'm telling you about it right now. (both laugh) >> What's the name? >> Appareto. >> Appareto, so there it is. We're launching on theCUBE here, on Periscope, pre-recorded for our Mobile World Congress special coverage. Alright so this is, basically, this is the cloud native goes to full scale cloud, for apps. >> Exactly, so containers, we've come full circle. Anyone that's been around for a while knows containers is certainly not a new trend. Solaris, you know, 25 years ago doing containers. The implementation of it around micro-services and the tooling around dev ops and docker and other various Kubernetes-types deployments have made it much more readily attainable, in terms of using it within an enterprise or a run of the mill application. >> We were talking with a lot of folks leading up to Mobile World Congress prep for our special coverage and micro-services comes up heavily, and micro-services as an integration layer. And one of the things that we're seeing, I want to get your thoughts on this, is you see IBM just announced this week here in San Francisco at their IBM Connect event, oh, it's our Lotus Domino and Verved, which is their collaborative software. But the key to all this collaborative software, even to the Oracle's of the world and to Amazon, is integration with third party apps. And micro-services and containers become a critical component of that. So, for entrepreneurs and/or app developers, a new kind of third party developer is emerging and they need to integrate. What is the role micro-services play in all of this? This is a really key point, because this will point right at the telcos. Because whoever can embrace an ecosystem of app developers from an integrations standpoint will win, in my opinion. Your thoughts, do you see it in the same way? And how does micro-services and all this stuff play into that? >> Well, there's two... >> It's the glue layer? >> Yeah, it's the glue. Lego is, again, is kind of the thing that pops in my mind. There are these two, sort of, battling schools of thought. One is micro-services which allows you to easily plug and play these various components. The other is server-less, these things that are very event-driven, they're transient. They allow you to, again, act as a kind of glue that puts everything together. One's based on, predominantly, the idea of containers which is kind of a lightweight OS. And the other is basically saying, I don't need an OS. All I need is the functions that I need, when I need them, and I put them together and I'm off to the races. I think that most applications aren't ready for a whole choice of just doing one or the other, it's kind of a combination. So the exciting thing now, is you can do what used to take weeks or months, in a matter of days with these types of technologies. >> So your final thought on Mobile World Congress. What do you expect to see in the hype cycle noise and where's the signal? Where do you see this event happening, what's your thoughts? >> I think we're going to see a lot more in the focus of things like media and convergence. I think video-related activities is certainly going to remain to be hot. I think the tooling around enabling that type of high definition video focus is going to be a priority for a lot of these companies and the tooling around that will be a priority. >> We're here with Reuv breaking down the Mobile World Congress analysis and preview and all of what's happening in the news. Obviously, Intel, with the 5G, big announcement. I think they raised the curtain early. Obviously, they're competing with Qualcomm which has a different licensing agreement than Intel. Which is, you know, you see Apple as a big customer of Qualcomm and Intel. Interesting because as the price of the hardware goes down the chip guys want more cash, Qualcomm wants more cash than Intel. Very interesting dynamic, I think this ecosystem is going to be something that's going to watch. I think there's going to be a battle. I'm predicting that at Mobile World Congress we'll see a battle of the ecosystem. You're going to see whoever can make the market and shift the game, will be the winner. Reuv, thanks for spending the time, appreciate it. This is SiliconANGLE broadcasting here in Palo Alto for Mobile World Congress '17, special coverage. Thanks for watching. (light techno music)

Published Date : Feb 27 2017

SUMMARY :

the beginning of the movement. Just a lot of the plumbing hasn't gotten done. Well, you know, they're always the pipes, So the question is, is that going the more things you can do with it. I mean, at the end of the day it comes down Whether that's a closet in the back of your office, the Mobile World Congress is going to shift at all? the actual physical things that you can touch and build. I mean there seems to be a feeling So the question is, is Snapchat going to live up So the question is, what does Snapchat mean for telcos? in many parts of the world and they use that monopoly Now it's all the rage, when you look at autonomous vehicles In the 70's you saw things like Space Odyssey I love the machine learning rates. realized quite quickly that you had to be a phD the stack action because that really is, you mentioned apps, One of the things they don't tell you is, Put it in the bank there, bank some cash. you know, the thing that apparently, you do. At the orchestration layer, or at the docker layer of all the various parts of an environment, It's stealthy, I'm telling you about it right now. goes to full scale cloud, for apps. and the tooling around dev ops and docker But the key to all this collaborative software, So the exciting thing now, is you can do what used Where do you see this event happening, what's your thoughts? and the tooling around that will be a priority. and shift the game, will be the winner.

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Mike Scarpelli | ServiceNow Knowledge14


 

but cute at servicenow knowledge 14 is sponsored by service now here are your hosts Dave vellante and Jeff trick okay we're back this is Dave vellante with Jeff Frick were here live at moscone south and this is the knowledge 14 conference 6600 people here growing was about 4,000 last year you seen this conference grow and about the same pace as a services service now stop line they're growing at sixty percent plus on pace to do over 600 million in revenue this year on pace to be a billion-dollar company and we have the CFO here Mike Scarpelli cube alum Mike great to see you again thank you so this is amazing I mean Moscone is a great venue of the aria last year's kind of intimate you know and now you're really sort of blowing it out I would expect next year you're going to be in the into the big time of conferences well I got a budget for that Tiffany I'm a budget I know it's going to cost more just like the attendance is going up fifty sixty percent the costs are going up as well too but our partners are really important and our partners offset a lot of those costs will get over eight million in sponsorship revenue to offset that so when we expect next year will see a corresponding increase in the sponsorship revenue as well well it's impressive you have a lot of strong partners particularly the system integrator consultancy types you know we saw I hope it will miss somebody definitely saw sent you there last night we start Ernie young giving a presentation k p.m. ET le is about so cloud sherpas yeah the cloud shippers and so we had them on earlier she have a lot of these facilitators which is a great sign for you and they're realizing okay there's there's money to be made around the ServiceNow ecosystem helping customers implement so that's going to make you really happy no you know one of the things that's really important for us with the system integrators is today they haven't really brought us any deals but they've been very influential in accelerating deals and we think that theme is going to continue and based upon what they're seeing they're able to do in the ServiceNow ecosystem in terms of professional service consulting engagement we think that's going to start to motivate them to now bring us into deals that we were never in before but what they have been able to do as well besides just accelerate is have the deals grow beyond IT and we see that numerous on global 2000 accounts for us and you're not trying to land grab the professional services business that's clear effect when you talk to some of your customers when I've ever last year when your customer scoop is complaining that your your price is real high on the surface of suck which it probably makes you happy because it leaves more room for you for your partners and that's really not a long-term piece of your revenue II think you've said publicly you want to be less than fifteen percent of your business right yes yes we have a little bit of a ongoing debate internally my preference is not to see the professional service organization grow in terms of headcount with the pure implementation people the area that I would like to see it grow is more on the training side unfortunately some of our customers they insist that we are part of the professional service engagement so those are more the ones that we're going to be involved and if a customer is looking for a lower-cost alternative we want to make it fair for our partner so that we're not competing with them so they can come up with a lower price to offer a good quality service is important though that it's not going for the lowest price our partners need to make investment so it can be a quality implementations this is a number of early implementations that were done by partners that were some of our smaller partners where they really didn't meet the the expectations of those customers that we've had to go in and fix some of those engagements so the number one goal for our professional service is to ensure we have happy customers because happy customers renew and buy more which are two of the key drivers for our growth so you keep growing like crazy blew it out last quarter to get a 181 million in Billings revenues up 60-plus percent you're throwing off cash hitting all your metrics of course the stock went down oh there you go not much more you could do but you got to really be pleased with the consistent performance and really predictability it seems of the company yeah no I'm since I've been the CFO company it's going to be coming on three years suit in the summer the one thing that I will say about this business model is it's extremely predictable in terms of the the forecasting and what helps with that is the fact that we have such high renewal rates that really helps because we really since I've been here we've never lost any major accounts I think our renewal rate has been averaging north of ninety-five percent and in terms of our upsells or up sells have been very consistent on average they run about a third of our business every quarter and that was Frank has made comments before too that if we don't sign on another customer we can still grow twenty-five percent per year plus just based upon the upsell business opportunity that we have within our existing installed base of customers that's penetrating accounts deeper more seats more licenses more processes and applications yeah the main grower of our upsells are the main contributor to our upsells within our customers really has been additional seat licenses because many of our customers we still have even fully penetrated IT and as we roll out more applications or make our applications more feature-rich as we talked about as Frank his keynote he talked a little bit today aitee costing we've always had that as an application but that's going to be coming out as a much more feature-rich application it's going to be a lot more usable to some of our customers when that goes live that's going to drive more licenses because many times it's different people with an IT that are the process users behind that and then it's going outside of IT as well with the adoption of people enterprise service management concept that Frank's been talking about that will drive incremental users as well too we do have some additional products such as orchestration discovery with a vast majority of our growth and customers is additional licensing so very consistent performance like I say the stock pull back a little bits interesting you guys worked a Splunk tableau smoking hot stocks of all pullback obviously it's almost like you trade as a groupie even though completely different companies completely different business models you don't compete really at all but so you kind of got to be flattering to be in that yeah obviously but it's I looked at as X this is good in a way this is a healthy you know pull back it's maybe a buying opportunity for people that wanted to get in and there are a lot of folks that I'm sure they're looking at that do you I mean how much attention do you even pay for it i know most CFOs i took a say look we can't control it all we can control is you know what we can control and that's what we focus on but you even look at things like that you order your thoughts on you know and unfortunately there is a little bit of a psychology going on here with some of our employees and they're always asking and my comment to them is the only price that matters is the day you sell and this pullback that we've seen recently this is not uncommon was I expecting it to happen right now you know I don't if I if I could predict those things a lot of different line of business but what I will say history is the best indicator of the future and even a company like salesforce com one of our large investors last week he sent me an email and said you do realize that in the first five years of sales force being a public it had forgot if it was four or five fifty percent pullbacks in the stock price so this this happens it will happen I guarantee it will happen again sometime in the future but not just with us with all the other companies I'd be more concerned if it was we were the only company that traded down and everyone stayed up but we're all trading down we all came back today it's interesting and you kind of burned the shorts last year and they've made some money now but but you know Peter Lynch they don't ever short great companies and it's very hard to too short great companies your timing has to be perfect so and your core business you know like for instance a workday is is fundamentally very profitable or you know it should be right and because you're spending like crazy on sales and marketing you're expanding into into AP you're expanding your total available market and you're still throwing off cash what if you can talk about that a little bit you had said off camera your goal is to really be you know so throw off little cash basically be cash flow breakeven yes yes so you know you can only grow at a certain pace last quarter we added 150 new people into our sales and marketing organization that was the the largest number that we've ever added in one quarter we actually added 273 net new employees in q1 that was the most we've ever added in a quarter and even with all those ads we still had very good positive cash flow so it's pretty hard to add at any faster pace than what we're doing right now and so you know I just I don't see us being cashflow negative anytime in the future right now unless something happened and write it have to be a pretty major catastrophe thing and it's not going to be specific to service now it will be kind of across the board we're all CIOs stop spending and the other thing I learned here I thought maybe I just wasn't paying attention to earlier conference calls but the AP focus a large percentage of the global 2000 is in asia-pacific so you're out nation-building right I won't if he could talk about that sure so in two thousand and from March 31st 2013 till March 31st 2014 we open up in 10 new countries most of those were in asia-pacific there's still more countries we're going to be going into an asia-pacific and why are we going into these countries we're going into these countries because that's where the global 2000 accounts are that is our strategy because we focus on quality of customers not quantity of customers what I mean by quality of quality customers one that can grow over time to be a very large customer and even in 2013 we went into Italy and people said at the time well why are you going into Italy we went to Italy because they have global 2000 have 30-something global 2000 accounts even though the Italian economy wasn't doing well global 2000 customers still spend it's not specific to that country their global we signed to global 2000 counts in Italy last quarter so we have a history of showing that if we go into those countries we will be successful in winning those global 2000 and will continue there are some global 2000 so in geographies where it's going to take some time before we actually have a physical presence such as mainland China we do not have any sales people in mainland China today Russia we did not have any people in Russia today how about Ukraine you know we have no one in Ukraine today good thing about Hitler you get to go visit there that's your country I wanted to talk about the TAM yesterday last year we had I kind of watched it but but I was asking Colombo questions about the team because it was you know very interesting I saw a lot of potential want to try to understand how big it could be you and I talked about you had said its north eight billion of course the the stock took off i think it probably 10 billion from a value standpoint I didn't my own tam of mid year I did a blog post I had it up to 30 billion so I started to understand it was a top down it wasn't a bottom up but you guys are starting to sort of communicate to him a little bit differently you got had the help desk and then beyond that the IT Service Management and then you you've essentially got the operations strike the operations management and even now sort of enterprise and business management so I wonder if you could talk about how you look at the the tam and any attempts that you've made to quantify it sure so there's really four markets we play in that really intersect with one another in the core of our market is the IT Service Management that's kind of our beachhead and how we go into accounts in that market right now when historically when we went public gartner groups of the world they looked at it as a helpdesk replacement market they were saying as a 1.4 to 1.6 billion dollar market what they were missing is there's many other things in that space IT service management such as ppm such as our cmdb such as asset management a lot of these things aren't in your traditional help desk we think based upon the rate at which we've been extracting from the market that somewhere we can afford a six billion dollar market opportunity just IT Service Management and then IT Service Management is a subset of the overall enterprise service management market that Frank has been talking about we talked about in our analyst state we think that is potentially as high as 10x the size of our IT Service Management so that can get you up to say that 40 billion dollar plus and then you as well have the IT operations management space IT Service Management you just have the legacy vendors down there nothing innovative happening down there service relationship a lot of white space a lot of stuff that's being done in email lotus notes microsoft access sharepoint those are the markets were going after there really are no true systems in and that's in that space it's those one-off custom apps IT operations management there is a lot of innovation happening down that in that space it is very crowded with some new vendors as well as the legacy vendors the area that will plan might be the whole 18 billion dollar market at IDC talks about you know it's still early innings but it's at least two billion of that market 24 billion will be going after and then Frank brought up this concept of the whole business analytics as well too we talked about we did our acquisition in mirror 42 in 2013 and the business analytics kind of sits at the top of enterprise service relationship management the market we can go after in there that's a that's a whole market into itself at least as big as the enterprise service management but we're not going after that whole market it's just the business analytics to the extent it relates to enterprise service management so that's at least a couple billion more unfortunately this is what we believe there is no published reports out there and times going to is going to tell it similar to when Salesforce went public no one believed the opportunity in front of it and now look how big that come have a 30 billion dollar plus company valuations are depends on what time of year it is what the markets doing but over the long term you know you can sort of do valuation analysis it in the CFO world is there some kind of thought in terms of the ratio between an organization's tan and it's in its valuation you know I mean these other things raid obviously the leadership etc but but for the top companies there a relationship I personally don't get wrapped up in valuation you know I can't control that I can't control public company multiples the only thing we have control over is running our own business and we're going to stay very focused on running our business and let other we'll take care of the valuation good business you picked a good one yes no I I'm very pleased with this one excellent all right Mike well listen thanks very much for coming on the cube we're up against the clock and I always appreciate you thank you Dave time up alrighty bryce bravely request with our next guest we're live from tony south this is dave vellante with jeff record right back

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Adi Krishnan & Ryan Waite | AWS Summit 2014


 

>>Hey, welcome back everyone. We're here live here in San Francisco for Amazon web services summit. This is the smaller event compared to reinvent the big conference in Vegas, which we were broadcasting live. I'm John furry, the founder's SiliconANGLE. This is the cube. Our flagship program where we go out to the events district to see live from the noise and a an Amazon show would not be complete without talking to the Amazon guys directly about what's going on under the hood. And our next guest is ADI Krishnan and Ryan Wade have run the Canisius teams. Guys, welcome to the cube. So we, Dave Vellante and I was not here unfortunately. He has another commitment but we were going Gaga over the says we'd love red shift in love with going with the data. I see glaciers really low cost options, the store stuff, but when you start adding on red shift and you know can, he says you're adding in some new features that really kind of really pointed where the market's game, which is I need to deal with real time stuff. >>I'll need to deal with a lot of data. I need to manage it effectively at a low latency across any work use case. Okay. So how the hell do you come up with an ISA? Give us the insight into how it all came together. We'd love the real time. We'd love how it's all closing the loop if you will for developer. Just take us through how it came about. What are some of the stats now post re-invent share with us will be uh, the Genesis for Canisius was trying to solve our metering problem. The metering problem inside of AWS is how do we keep track with how our customers are using our products. So every time a customer does a read out of dynamo DB or they read a file out of S3 or they do some sort of transaction with any of our products, that generates a meeting record, it's tens of millions of records per second and tens of terabytes per hour. >>So it's a big workload. And what we were trying to do is understand how to transition from being a batch oriented processing where we using large hitting clusters to process all that data to a continuous processing where we could read all of that data in real time and make decisions on that data in real time. So you basically had created an aspirin for yourself is Hey, a little pain point internally, right? Yeah. It's kind of an example of us building a product to solve some of our own problems first and then making that available to the public. Okay. So when you guys do your Amazon thing, which I've gotten to know about it a little bit, the culture there, you guys kind of break stuff, kind of the quote Zuckerberg, you guys build kind of invented that philosophy, you know stuff good. Quickly iterating fast. So you saw your own problem and then was there an aha moment like hell Dan, this is good. We can bring it out in the market. What were customers asking for at the same time was kind of a known use case. Did you bring it to the market? What happened next? >>We spend a lot of time talking to a lot of customers. I mean that was kind of the logistical, uh, we had customers from all different sorts of investigative roles. Uh, financial services, consumer online services from manufacturing conditional attic come up to us and say, we have this canonical workflow. This workflow is about getting data of all of these producers, uh, the sources of data. They didn't have a way to aggregate that data and then driving it through a variety of different crossing systems to ultimately light up different data stores. Are these data source could be native to AWS stores like S3 time would be be uh, they could be a more interesting, uh, uh, higher data warehousing services like Gretchen. But the key thing was how do we deal with all this massive amount of data that's been producing real time, ingested, reliably scale it elastically and enable continuous crossing in the data. >>Yeah, we always loved the word of last tickets. You know, a term that you guys have built your business around being elastic. You need some new means. You have a lot of flexibility and that's a key part of being agile. But I want you guys at while we're here in the queue, define Kenny SIS for the folks out there, what the hell is it? Define it for the record. Then I have some specific questions I want to ask. Uh, so Canisius is a new service for processing huge amounts of streaming data in real time. Shortens and scales elastically. So as your data volume increases or decreases the service grows with you. And so like a no JS error log or an iPhone data. This is an example of this would be example of streaming. Yeah, exactly. You can imagine that you were tailing a whole bunch of logs coming off of servers. >>You could also be watching event streams coming out of a little internet of things type devices. Um, one of our customers we're talking about here is a super cell who's capturing in gain data from their game, Pasha, the plans. So as you're playing clash of the plans, you're tapping on the screen. All of that data is captured in thesis and then processed by my super Supercell. And this is validated. I mean obviously you mentioned some of the use cases you needed of things, just a sensor network to wearable computers or whatever. Mobile phones, I'll see event data coming off machines. So you've got machine data, you've got human data, got application data. That's kind of the data sets we're seeing with Kinesis, right? Traverse set. Um, also attraction with trends like spark out of Berkeley. You seeing in memory does this kind of, is this in your wheelhouse? >>How does that all relate to, cause you guys have purpose-built SSDs now in your new ECQ instances and all this new modern gear we heard in the announcements. How does all the in-memory stuff affect the Canisius service? It's a great question. When you can imagine as Canisius is being a great service for capturing all of that data that's being generated by, you know, hundreds of thousands or millions of sources, it gets sent to Canisius where we replicated across three different availability zones. That data is then made available for applications to process those that are processing that data could be Hadoop clusters, they could be your own Kaloosas applications. And it could be a spark cluster. And so writing spark applications that are processing that data in real time is a, it's a great use case and the in memory capabilities and sparker probably ideal for being able to process data that's stored in pieces. >>Okay. So let's talk about some of the connecting the dots. So Canisius works in conjunction with what other services are you seeing that is being adopted most right now? Now see I mentioned red shift, I'm just throwing that in there. I'll see a data warehousing tool seeing a lot of business tells. So basically people are playing with data, a lot of different needs for the data. So how does connect through the stack? I think they are the number one use case we see is customers capturing all of this data and then archiving all of it right away to S3 just been difficult to capture everything. Right. And even if you did, you probably could keep it for a little while and then you had to get, do you have to get rid of it? But, uh, with the, the prices for us three being so low and Canisius being so easy to capture tiny rights, these little tiny tales of log data, they're coming out of your servers are little bits of data coming off of mobile devices capture all of that, aggregate it and put it in S3. >>That's the number one use case we see as customers are becoming more sophisticated with using Kinesis, they then begin to run real time dashboards on top of Kinesis data. So you could, there's all the data into dynamo DB where you could push all that data into even something like Redshift and run analytics on top of that. The final cases, people in doing real time decision making based on PISA. So once you've got all this data coming in, putting it into a dynamo DB or Redshift or EMR, you then process it and then start making decisions, automated decisions that take advantage of them. So essentially you're taking STEM the life life cycle of kind of like man walking the wreck at some point. Right? It's like they start small, they store the data, usually probably a developer problem just in efficiencies. Log file management is a disaster. >>We know it's a pain in the butt for developers. So step one is solve that pain triage, that next step is okay I'm dashboard, I'm starting to learn about the data and then three is more advanced like real time decision making. So like now that I've got the data coming in in real time and not going to act. Yeah, so when I want to bring that up, this is more of a theoretical kind of orthogonal conversation is where you guys are basically doing is we look, we like that Silicon angles like the point out to kind of what's weird in the market and kind of why it's important and that is the data things. There's something to do with data. It really points to a new developer. Fair enough. And I want to give you guys comments on this. No one's really come out yet and said here's a development kit or development environment for data. >>You see companies like factual doing some amazing stuff. I don't know if you know those guys just met with um, new Relic. They launched kind of this data off the application. So you seeing, you seeing what you guys are doing, you can imagine that now the developer framework is, Hey I had to deal with as a resource constraint so you haven't seen it. So I want to get your thoughts. Do you see that happening in that direction? How will data be presented to developers? Is it going to be abstracted away? Will there be development environments? Is it matter? And just organizing the data, what's your vision around? So >>that's really good person because we've got customers that come up to us and say I want to mail real time data with batch processing or I have my data that is right now lots of little data and now I want to go ahead and aggregate it to make sense of it over a longer period of time. And there's a lot of theory around how data should be modeled, how we should be represented. But the way we are taking the evolution set is really learning from our customers and customers come up and say we need the ability to capture data quickly. But then what I want to do is apply my existing Hadoop stack and tools to my data because then you won't understand that. And as a response to that classroom demand, uh, was the EMR connect. Somehow customers can use say hi queries or cascading scripts and apply that to real time data. That can means is ingesting. Another response to pass was, was the, that some customers that would really liked the, the, the stream processing construct a storm. And so on, our step over there was to say, okay, we shipped the Canisius storm spout, so now customers can bring their choice of matter Dame in and mail back with Canisius. So I think the, the short answer there right now is that, >>you know, it's crazy. It's really early, right? I would also add like, like just with, uh, as with have you, there's so many different ways to process data in the real time space. They're going to be so many different ways that people process that data. There's never going to be a single tool that you use for processing real time data. It's a lot of tools and it adapts to the way that people think about data. So this also brings us back to the dev ops culture, which you guys essentially founded Amazon early in the early days and you know I gotta give you credit for that and you guys deserve it. Dev ops was really about building from the ground good cloud, which post.com bubble. Really the thing about that's Amazon's, you've lived your own, your own world, right? To survive with lesson and help other developers. >>But that brings up a good point, right? So okay, data's early and I'm now going to be advancing slowly. Can there be a single architecture for dealing with data or is it going to be specialized systems? You're seeing Oracle made some mates look probably engineered systems. You seeing any grade stacks work? What's the take on the data equation? I'm not just going to do because of the data out the internet of things data. What is the refer architecture right now? I think what we're going to see is a set of patterns that we can do alone and people will be using those patterns for doing particular types of processing. Uh, one of the other teams that I run at is the fraud detection team and we use a set of machine learning algorithms to be able to continuously monitor usage of the cloud, to identify patterns of behavior which are indicative of fraud. >>Um, that kind of pattern of use is very different than I'm doing clickstream analysis and the kind of pattern that we use for doing that would naturally be different. I think we're going to see a canonical set of patterns. I don't know if we're going to see a very particular set of technologies. Yeah. So that brings us back to the dev ops things. So how do I want to get your take on this? Because dev ops is really about efficiencies. Software guys don't want to be hardware guys the other day. That's how it all started. I don't want to provision the network. I don't want a stack of servers. I just want to push code and then you guys have crazy, really easy ways to make that completely transparent. But now you joke about composite application development. You're saying, Hey, I'm gonna have an EMR over here for my head cluster and then a deal with, so maybe fraud detection stream data, it's going to be a different system than a Duke or could be a relational database. >>Now I need to basically composite we build an app. That's what we're talking about here. Composite construction resource. Is that kind of the new dev ops 2.0 maybe. So we'll try to tease out here's what's next after dev ops. I mean dev ops really means there's no operations. And how does a developer deal with these kinds of complex environments like fraud detection, maybe application here, a container for this bass. So is it going to be fully composite? Well, I don't know if we run the full circuit with the dev ops development models. It's a great model. It's worked really well for a number of startups. However, making it easy to be able to plug different components together. I get just a great idea. So, like as ADI mentioned just a moment ago, our ability to take data and Kinesis and pump that right into a elastic MapReduce. >>It's great. And it makes it easy for people to use their existing applications with a new system like pieces that kind of composing of applications. It's worth well for a long time. And I think you're just going to see us continuing to do more and more of that kind of work. So I'm going to ask both of you guys a question. Give me an example of when something broke internally. This is not in a sound, John, I don't go negative here, but you got your, part of your culture is, is to move fast, iterate. So when you, these important projects like Canisius give me an example of like, that was a helpful way in which I stumbled. What did you learn? What was the key pain points of the evolution of getting it out the door and what key things did you learn from media success or kind of a speed bump or a failure along the way? >>Well, I think, uh, I think one of the first things we learned right after we chipped and we were still in a limited previous and we were trying it out with our customers who are getting feedback and learning with, uh, what they wanted to change in the product. Uh, one of the first things that we learned was that the, uh, the amount of time that it took to put data into Canisius and receive a return code was too high for a lot of our customers. It was probably around a hundred milliseconds for the, that you put the data in to the time that we've replicated that data across multiple availability zones and return success to the client. Uh, that was, that was a moment for us to really think about what it meant to enable people to be pushing tons of data into pieces. And we went back a hundred milliseconds. >>That's low, no bad. But right away we went back and doubled our efforts and we came back in around, you know, somewhere between 30 and 40 milliseconds depending on your network connectivity. Hey, the old days, that was, that was the spitting disc of the art. 10, 20 Meg art. It's got a VC. That's right. Those Lotus files out, you know, seeing those windows files. So you guys improve performance. So that's an example. You guys, what's the biggest surprise that you guys have seen from a customer use case that was kind of like, wow, this is really something that we didn't see happening on a, on a larger scale that caught me by surprise. >>Uh, I is in use case it'd be a corner use case. Like, well, I'd never figured that, you know, I would say like, uh, some of the one thing that actually surprised us was how common it is for people to have multiple applications reading out of the same stream. Uh, like again, the basic use case for so many customers is I'm going to take all this data and I'm just going to throw it into S3. Uh, and we kind of envisioned that there might be a couple of different applications reading data of that stream. We have a couple of customers that actually have uh, as many as three applications that are reading that stream of events that are coming out of Kinesis. Each one of them is reading from a different position in the stream. They're able to read from different locations, process that data differently. >>But uh, but the idea that cleanses is so different from traditional queuing systems and yet provides, uh, a real time emotionality and that multiple applications can read from it. That was, that was a bit of a versa. The number one use case right now, who's adopting, can you sit there, watch folks watching out there, did the Canisius brain trust right here with an Amazon? Um, what are the killer no brainer scenarios that you're seeing on the uptake side right now that people should be aware of that they haven't really kicked the tires on Kinesis where they should be? What should they be looking at? I think the number one use case is log and ingestion. So like I'm tailing logs that are coming off of web servers, my application servers, uh, data that's just being produced continuously who grab all that data. And very easily put it into something like us through the beauty of that model is I now have all the logo that I got it off of all of my hosts as quickly as possible and I can go do log nights later if there's a problem that is the slam dunk use case for using crisis. >>Uh, there are other scenarios that are beginning to emerge as well. I don't know audio if you want to talk, that's many interesting and lots of customers are doing so already is emit data from all sorts of devices. So this is, these devices are not just your smartphones and tablets that are practically food computing machines, but also seemingly low power, seemingly dumb devices. And the design remains the same. There are millions of these out there and having the ability to capture that in a day produce in real time is, you know, I think just, uh, just to highlight that, one of things I'm hearing on the cube interviews, all the customers we talk to is the number one thing is I just got to scroll the date. I know what I want to do with it yet. Now that's a practice that's a hangover from the BI data warehouse in business of just store from a compliance reasons now, which is basically like, that's like laser as far as I'm concerned. >>Traditional business intelligence systems are like their version of Galatians chipped out somewhere and give me those reports. Five weeks later they come back. But that's different. Now you see people store that data and they realize that I need to touch it faster. I don't know yet when, that's why I'm teasing out this whole development 2.0 model because I'm just seeing more and more people want the data hanging around but not fully parked out in Malaysia or some sort of, you know, compliance storage. So there's, you know, I think, I think I kind of understand where you're going. There's a, I'm going to use a model for like how we used to do BI analytics and our own internal data warehouse. I also run the data warehouse for AWS. Um, and the classic BI model there is somebody asks a question, we go off and we just do some analysis and if it's a question that we're going to ask repeatedly, we don't, you know, a special fact table or a dimensional view or something to be able to grind through that particular view and do it very quickly. >>A Kunis is offers a different kind of data processing model, which is I'm collecting all of the data and make it easy to capture everything, but now I can start doing things like, Oh, there's, there's certain pieces of data that I want to respond to you quickly. Just like we would create dimensional views that would give us access to particular sets of data and very quick pace. We can now also respond to when those events are generated very quickly. Well, you guys are the young guns in the industry now. I'm a little bit older and the gray hair showing, we actually use the word data processing back in the day. The data processing that the DP department or the MIS department, if you remember those those days, MIS was the management information. Are we going back to those terms? I mean we're looking at look what's happening. >>Is it the software mainframe in the cloud? I mean these are some of the words you're using. Just data processing data pipeline. Well, I my S that's my work, but I mean we're back to those old school stuff but different, well and I think those kinds of very generic terms make a lot of sense for what we're doing is we, especially as we move into these brand new spaces like wow, what do I do with real time data? Like real time data processing is kind of the third type of big data processing or data warehousing was the first time I know what my data looks like. I've created indices like a pre computation of the data, uh, uh, Hadoop clusters and the MapReduce model was kind of the second wave of big data processing and realtime processing I think will be the third way. I think our process, well, I'm getting the hook here, but I got to just say, you guys are doing an amazing job. >>We're big fans of Amazon. I always say that, uh, you know, it was very rare in the history the world. We look at innovations like the printing press, the Wright brothers discover, you know, flying and things like we, Amazon with cloud. You guys have done something that's pretty amazing. But what I find fascinating is it's very rare to see a company that's commoditizing and disrupting and innovating at the same time. And it's really a unique value proposition and the competition is responding. IBM, Google. So you guys have a lot of targets painted on your back by a lot of big players. So, uh, one congratulations on your success, which means that you, you know, you're not going to go in the open field and fight the, the British if they said use the American revolution analogy. You've got to continue to compete. So what's your view of that? >>I mean, and I'm sure you don't talk about competition. You'd probably told him not to talk about it, but I mean, you got to know that all the guns are on you right now. The big guys are putting up the sea wall for your wave of innovation. How do you guys deal with that? It's just cause it's not like we, we ignore our competitors but we obsess about our customers, right? Like it's just constantly looking for what are people trying to do and how can we help them and can seem like a very simple strategy. But the strategy is built with people want and we get a lot of great feedback on how we can make our products better. And it certainly will force you to up your game when you have the competition citing on you. You've got more focused on the customer, which is cool. >>But like you guys kind of aware of like games on, I mean Amazon is at any given a little pep talk, Hey, game is on guys. Let's rock and roll. Right? You guys are aware, right? I think we're totally wearing, I think we're actually sometimes a little surprised at how long it's taken to our competitors to kind of get into this industry with us. So, uh, again, as Andy talked about earlier today, we've had eight years in the cloud computing market. It's been a great eight years and we have a lot of work to do, a lot of stuff that we're going to be almost ready for middle school. Um, final final question for you guys and give you the final word here. Share the photos on the last word is why is this show so important, right this point in time in this market. Why is this environment of the thousands of people that are here learning about Amazon, why, what should they know about why this is such an important advance? I think our summits are a great opportunity for us to share with customers how to use our AWS services. Learn firsthand from not only our hands on labs, but also our partners that are providing information about how they use AWS resources. It's, it's a great opportunity to meet a lot of people that are taking advantage of the cloud computing wave and see how to use the cloud most effectively. >>It's a great time to be in the cloud right now and the Olin's amazing services coming up. There's no better mind now of people coming together and so that's probably as good reasons. Then you guys are doing a great job disrupting change in the future. Modern enterprise and modern business, modern applications. Excited to watch it. If you guys keep focusing on your customer, but that customer base, you keep up the pace that's sick. That question, can you finish the race? That's what I always tell Dave a lot. They, I know Jay's watching Dave. Shout out to Dave Volante, who's on the mobile app right now is traveling. Guys, thanks for coming inside. Can he says great stuff. Closing the loop real time. Amazon really building it out. Thanks for coming on. If you'd be right back with our next guest after this short break. Thank you.

Published Date : Mar 26 2014

SUMMARY :

the store stuff, but when you start adding on red shift and you know can, he says you're adding in some new features So how the hell do you come up with an ISA? the culture there, you guys kind of break stuff, kind of the quote Zuckerberg, you guys build kind of invented that philosophy, I mean that was kind of the logistical, You know, a term that you guys have built your business around being elastic. That's kind of the data sets we're seeing with Kinesis, of that data that's being generated by, you know, hundreds of thousands or millions of sources, it gets with what other services are you seeing that is being adopted most right now? That's the number one use case we see as customers are becoming more sophisticated with using Kinesis, And I want to give you guys comments on this. I don't know if you know those guys just met with But the way we are taking the evolution set is So this also brings us back to the dev ops culture, which you guys essentially founded Amazon early in the early days So okay, data's early and I'm now going to be I just want to push code and then you So is it going to be fully composite? So I'm going to ask both of you guys a question. Uh, one of the first things that we learned So you guys improve performance. of the one thing that actually surprised us was how common it is for people to have multiple applications So like I'm tailing logs that are coming off of web capture that in a day produce in real time is, you know, I think just, uh, just to highlight that, So there's, you know, I think, I think I kind of understand where you're going. The data processing that the DP department or the MIS department, if you remember those those days, you guys are doing an amazing job. So you guys have a lot of targets painted on your back by a lot of big players. And it certainly will force you to up your game when But like you guys kind of aware of like games on, I mean Amazon is If you guys keep focusing on your customer, but that customer base, you keep up the pace that's

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James Kobielus - IBM Information on Demand 2013 - theCUBE


 

okay we're back here live at the IBM iod information on demand conference hashtag IBM iod this is the cube so looking the anglo Mookie bonds flagship program we go out for the events extracting from the noise i'm john furrier might join my co-host Davey lonte and we'd love to have analysts in here and in this case former analyst James Cole Beatles welcome to back to the cube thank you very much John thank you Dave pleasure see you again finger of being at IOD you're a thought leader you are an influencer you work at IBM so you you're out there the front lines doing some great work so thank you very much tell us explains the folks out there not about the show because we've had some people coming in last year you were private in but what does this fit what is this vector in context to what's relevant the market obviously big data and analytics is the hottest thing on the planet right now and you got social business now emerging categorically here but it has a couple different flavors to it right within IBM's context yeah but the messaging is simple right you got analytics that drives value outcomes social business is the preferred way of people going to operate their businesses engagement and all that is great stuff new channels marketing eccentric cetera explain to them how I OD is fitting into these megatrends into mega trends I think the hottest trends why our customers caring about what's going on here is a lot of a lot of activity around customers what is what does IOD fit into that a bigger picture yeah well you know the world has changed the world culture has changed radically and really in the last decade or so none is everywhere in the world everything is now online and digital increasingly it's streaming in terms of culture look what's happening to Hollywood is being deconstructed by the netflixs of the world you know movies and TV and music and everything is delivered online now all engagement more more engagements with your employer with your you know with merchants with your family everywhere is online things like streaming media so if you look at how the world culture has changed I yesterday I spoke here on a topic that's near and dear to my heart called big media it's the support of the ascendance of streaming media and not just the area as I laid out but in education like MOOCs distance learning we use it internally at IBM for our think fridays and Ginni Rometty and the executive team you know every Friday its cloud or its big data or whatever you know we need all need to get up to speed on the world culture has changed now analytics is fundamental to that whole proposition in terms of world culture analytics driving gagement analytics in terms of you know in a business context analytics a 360-degree view and you have data warehouses and the master data and you have predictive models to drive segmentation and target marketing and all that good stuff you know that's been in business for a long time that those set of practices they have become prevalent in most industries now not just in say retailing you know the Amazons of the world they're pervasive across all industries big data is fundamental to that you know engagement model its social social in the sense that social is one of many channels through which business is engaged with through which many people engage the social is assumed assuming a degree of importance in the fabric of modern life that goes beyond simple you know engagement with you know brands and whatnot social is how people create is how they declare who they are it's their identity and so social in your personal life we all know about Facebook and Twitter and everything else and YouTube but social has revolutionized enterprise cultures everywhere you know we use social internally of course we use our own Lotus connections most large and even many mid-sized firms now use social for interactions among employees or throughout their Val you chain so social business is about all of that it's the b2c it's the b2b it's the e2e and employ to employ all these different models of engagement they all demand a number of things obviously the social platform they demand the data of various sorts structured unstructured in shared repositories or cubes or Mars or whatnot they it demands the the big data platforms not only at respite in motion the streaming media to make it all happen in real time so at IOD if you see what the themes are this year and really it's been a building for several years cloud everything social is running in the cloud now more and more not just public Claus but Federation's of public and private clouds it's it's all about cognitive computing which is a relatively new term in the Sun sets achieved a certain amount of vogue in the last year or so which is really fundamentally as an evolutionary trend it's basically a I for the 21st century but leveraging unstructured data and and machine learning and so forth and predictive analytics and you know well the whole world learn what metadata was with the whole NSA yeah comments no it's like me and then just to wrap it up in memory real-time blu acceleration you know you need real-time you need streaming you need collaboration and social you know peer-to-peer user-generated content all of that to make this new world culture really take off and IBM provides all that we recognize that that's where the world's going we've been orienting reorienting all of our solutions around these models cloud social increasingly going forward and you know we provide solutions that enable our customers in all industries to go there and big data is fundamental to all of that as we say we're computer science meets social science that's always been Silicon angles kind of masthead view but to unpack what you just said from the market relevance you mentioned Netflix we saw Amazon coming out their own movie they're going to go direct with their own programming so so but that speaks to the direct business model of the web was originally pioneered as hey direct business model cut the middleman out but now that dimension has been explored so that kind of what you're saying there so that's cool the end user pieces interesting image is social so what's your take on the end user orientation what's the expectation because you got social you got a trash you got in motion you got learning machines providing great recommendations got the Watson kind of yeah reasoning for people so personalization recommendation engines the sea change attention time currency big days of all those buzzwords all right what is the expectation for users in the future right now we're moving into this new world where I can self serve myself monologue based the information from the web now it's all coming at everyone real time the alarms are going off as Jeff Jonas says what is that prefer user experience the direct business model people get that I think the business to see that but now the end users are now at the center of the value proposition how do what's the role of the user now they're participating in the media there are also consumers of the media yeah and they now have different devices so what's the sources of data so fundamentally yeah the role of the consumers expectations now is always everything is always on everything is always online everything is all digital everything is all real time and streaming everything is all self-service everything is all available in the palm of my hand and then the back-end infrastructure the cross-channel infrastructure users don't care about individual socials they really don't they don't really fundamentally care about Facebook or Twitter or whatever you have they just care that what their experience is seamless as they move from one channel to another they're not perceived as channels anymore they're simply perceived as places or communities that overlap too in a dizzying array of socials thus social is where we all live and thus social increasingly is mobile increasingly mobile is you know the user expects that the handoff from my smartphone to my tablet to my laptop to my digital TV sentence and so forth that it all happens through the magic of infrastructure that it's being taken care of and they don't have to worry about that handoff it all it's all part of one seamless experience yeah they always just say the search business it's the it's the it's the intersection of contextual and behavioral yeah and now you take that online behaviors community contextual is context to what people are interested at any given time yeah it's so many longtail distributions at any given time so do you see the the new media companies that the new brands that might emerge mean there's all the talk about Marissa Mayer kind of turning over yahoo and yeah she some say putting lipstick on a pig but but but is that they're just an old older branch trying to be cool but is that what users want just like media but just user experience me like we're small media but we got big ideas but the thing is the outcomes right small frying big blues go figure are the outcomes still the same company still want to drive sales for their business sell a product provide great value you just want to find great content and find people I mean the same concept of the old web search find out and run sumit give any vision on how that environment will evolve for a user like is it going to be pushed at me do you see it a new portal developing is mmm Facebook's kind of a walled garden humble don't care about that what's your take on that the future vision of a user experience online user experience online future vision in many ways I think let's talk about Internet of Things because that keeps coming more and more into the discussion it's it's not so much that the user wants a seamless experience across channel cross device all that but a big part of that experience is the user knows that increasingly they'll have some confidence that whatever environments physical environments there in our being obviously there's privacy implications that surveillance here are being monitored and tracked and optimized to meet their requirements to some degree in other words environmental monitoring internet of things in your smart home you want to configure so you smart home so that every room that you walk into is as you as you're moving there even before you get there has already been optimized to your needs that ideally there should prediction Oh Jim's walking into the bathroom so turn the light on and also start to heat up the water because it's ten o'clock at night Jim's usually takes his bath around this time you sort of want that experience to be handled by the internet of things like nest these new tools like nest oh yeah yeah so essentially then it's my user experience is not just me interacting with devices but me simply moving through environments that are continuously optimized to my knees and needs of my family you know the whole notion of autonomous vehicles your vehicle if it's your personal vehicle then you want to always autumn optimize the experience in terms of like you know the heat setting and and the entertainment justement saan the you know the media center and they're always to be tailored to your specific needs at any point in time but also let's say you take a zipcar you rent a zipcar and you've got an ID with that company or any of the other companies that provide those on-demand rental car services ideally in this scenario that whatever vehicle you you rent through them for a few hours or so when you enter it it becomes your vehicle is completely customized to your needs because you're a loyal customer of that firm and they've got your profile information this is just a hypothetical I'm not speaking to anything that I actually know about what they're doing but fundamentally you know ideally any on-demand vehicle or conveyance or other item that you you lease in this new economy is personalized to your needs while you're using it and then as it were depersonalized when you check it back in so the next person can have it personalized to their use as long as they need it that's the vision of a big part of the vision of customer experience management personalization not just of your personal devices but personalization of almost any device or environment in which you are operating so that's one kanodia wants this question no I would ask one more question on that on the user experience came on Twitter from a big data alex says while you're on the subject which a my Alex I don't great great friend of the cube but thanks for the tweet today we don't have our crowd shado-pan we can get the chat going there but why not talk about AR and I've been in reality I mean honestly Internet of Things is now not the palm of your hand it could be on your wrist or on your clothing the wearables on the glasses and just gave out three invites to google glass so this is again another edition augmented reality is software paradigm as well what is that what is it what does that fit into that what's your take on augmented reality augmented reality ok so augmented reality is that which I don't use myself I've just simply seen it demonstrated and plenty of places so augmented reality is all about layers of additional information overlaid on whatever visual video view or image view that you happen to be carrying with you or have available to you while you're walking around in your normal life so right now conceivably if this is an AR a setting that I would environment or enabled device I would be able to see for example that ok who's in this room in the sense that who is declared that they are in this area of Mandalay Bay right now and why specifically are they doing to the extent that they allow that information to be seen and o of these people here which of these people if any might be the person I'm going to be speaking with it for 30 so that if they happen to be in this environment i can see that i can see that they're to some degree they may have indicated status waiting for james could be a list to get done with the Wikibon people oh that's kind of cool so I'd see that overlay and I walk to other parts of the Convention Center I might also see overlays as I walk around like oh there's a course down as several rooms down that I actually put in my schedule it's going to start in about five minutes I'll just duck you into there because it reminds me through the overlay that's the whole notion of personalization of the environment in which you're walking around in real time dynamically and contextual in alignment with your needs or with your requirements are in alignment also with these whatever data those environment managers wish to share to anybody who's subscribing in that contact so that's a context-aware that theme have been talking about here on textual essentially it's a public space that's personalized to your needs in the sense that you have a personalized view in a dynamically update okay that sounds like crowd chat Oh are we running a trip crouched at right now crouch at San overlay so just as lovely overlay so look to the minute social network yeah tailored to the needs of the group yep that adds value on top of that data yeah so James I gotta get your take on something so we had Merv on yesterday great Adrian with my great Buy analyst day and he was on last week at Big Data NYC you know we did our own little vent there Don coincident with hadoop world so Murph said well we're just entering the trough of disillusionment for big data yeah you love those Gartner you know I love medications tools I mean they are genius and I get him but he said that's a good thing because it goes left to right so we're making progress here ok right but I'm getting nervous the internet of things I love the concept we don't we don't work on industrial internet and you know a smarter planet it's in there so I love it but I'm getting nervous here's why I look back at a lot of the promises that were made in the BI days 360-degree other business predictive analytics a lot of things that are now talking about in the hood sort of Hadoop big data movement that we're actually fulfilling with this new wave that the old wave really wasn't able to fill because the cousin sort of distracted doing sarbanes-oxley and reporting in and balanced scorecards so so I'm nervous he's old school now it when he when he referenced is something that was hot in the mid part of the two thousand decade okay go ahead okay we had a guy on today talking about balance core would you know we're just talking about crowd chat that's the hottest day in 2013 like five years or hurt anybody mentions sarbanes-oxley so what kind of saved that whole business Roy thank you and Ron but so heavy right so what I'm nervous about as we as I've seen a number of waves over the years where the the vendor community promises a vision great vision great marketing and then all of a sudden something hotter comes along like Internet of Things and says don't know this is really it so my question to you is will help us it'll help me in my mind you know close that dissonance gap is are these two initiatives the sort of big data analytics for everybody putting analytics in the hands of business users yeah or is that sort of complementary to the internet of thing his internet of things just the new big trillion dollar market that everybody's going to go after and forget about all those promises about analytics everywhere help me sure Jay through that my job is to clarify confusion hey um you know if you look at the convergence of various call them paradigms there's a lot of big data analytics is one of them right now clearly there's cloud clearly their social there's big data analytics in mobile and there's something called Internet of Things so some some talk about smack smac social mobile analytic a que a big data cloud if you add IOT of there it's smack yet I don't think it works or smash yet but fundamentally if you think about Internet of Things it's it's all about machines or automated devices of various sorts probes and you know your smartphone and whatever I know servers or even you know the autonomous vehicles those are things that do things and you know they might be sources of data they would are they might be consumers of data they might conceivably even be intermediaries or brokers or routers or data what I'm getting at is that if you look at big data analytics I always think of it as a pipeline all data it's like data sources and data consumers and then there's all these databases and other functions that operate between them to move data and analytics and insight from one end to the other of the pipe in a conceptual way think of the internet of things as well a new category of sources of data these devices whether they be probes or monitors or your smart phones and new consumers and they all those same things are probably going to be many of them consumers of data and there's message passing among them and then the data that they passed might be passed in real time through streaming like InfoSphere streams it might be cached or stored and various intermediate databases and various analytics performed on them so think of you know I like to think of the internet of persons places and things persons that's human endpoints consumers and and sources of data that's all of us that's social places that's geospatial you know you think about it the Internet of geospatial you know geo spatial coordinates of of data and analytics and then there's things there's you know automated endpoints or you know hardware even Nana from macro to nano devices so it's just a new range of sources and and consumers of data and new types of analytics that are performed in new functions that can be performed and outcomes enable when you as it were stack in and out of things with social with claw with mobile new possibilities in terms of optimization in real time it throughout the you know the smarter planet if you think about the smarter planet vision it's all about interconnected instrumented and intelligent instrumented you know instrumentation that traditionally it suggests hardware instrumentation that's what probes our sensors and actuators that's the Internet of Things it's a fundamental infrastructure within smarter planet I'd love that thank you for clarifying i could write a blog post out of that and i think i'm very well made so um now i want to follow up and bring it back to the users I know snack and I thought you were going to say a story no smack MapReduce analytics and query or sell smack on the cube so so I want bring it back to the users so we had a great conversation yesterday actually last week I'll be met it was on off you know ah be met and he said look why are there any any you know where all the big data apps he said you need three things to for big data apps you need domain expertise you need algorithms which are free and you need data scientists like oh we'll never get there all right oh so rules really free while there are that was this argument yeah it means a source if people charge him for algorithms big trouble was this point I think okay sure so and then we had a discussion yesterday about how in the early days of the automobile industry you know the forecast was this is problematic the gap to adoption is just aren't enough chauffeurs know the premise that we were putting forth in the discussion yesterday I don't know who that was with was that with Judith it was good was that look we've got to figure out a way to get analytics in the hands of the business user we can't have to go through a data scientist or some business analyst no that's not going to work and we'll never get adoption so what what's going to bridge that gap is it is it the things you talked about before all these you know cool solutions that you guys are developing the project neo that you announce today visualization yeah there's another piece of that what puts it in the hands of guys like me that I can actually use the data in new and productive ways yeah well self-service business intelligence and visualization tools that are embedded in the very experience of using apps for example on your smartphone democratization of data science down to all of us you need the right tools you need you need the tools that the new generation of people like my children's generation just adopt and they work in there just a tune from from the cradle to working with data and visualizations and creating visual you know analytics of various sorts though they may not perceive it as being analytics they miss may perceive it as working with shapes and patterns and stuff yeah you would stop yeah so playing around you know in a sandbox i love that terminology data scientists working you know sandboxes which is data that's martes that they build to do regression analysis and segmentation and decision trees and all you know all that good stuff you know the fact is your sandbox can conceivably be completely on your handheld device with all the visualizations built-in you're simply doing searches and queries you know you're asking natural language questions you're looking at the responses you're changing your queries you're changing your visualizations and so forth to see if anything pops out at you as being significant playing around it you know it's as simple a matter that that these kinds of tools such as IBM you know cognos and so forth enable everybody to become as it worried a data scientist without having to you know become a maquette their profession it's just a part of the fabric of living in modern society where data surrounds us people are going to start playing with data and they're going to start teaching themselves all these capabilities in the same way that when they invented automobiles and you know wasn't Henry 42 invented them it was in like the late 1800s by engineers in Europe and America you know it's like we didn't all become auto mechanics you know there are trained auto mechanics but I think most human beings in the modern world know that there's a thing called an automobile that has an engine that needs gasoline and oil and occasionally needs to be brought to a professional mechanic for a repair and so forth we have many of us have a rough idea of something called a carburetor blah blah blah you know in the same way that when computers came up after world war two and then gradually invaded our lives through PCs and everything we all didn't become computer scientist but most of us have an idea of what a hard disk is most of it no most of us know something about something called software and things are called operating systems in the same way now in this new world most of us will become big data analytics geeks practical into the extent that will learn enough of the basic terms of art and the relationships among the various components to live our lives and when the stuff breaks down we call the likes of IBM to come and fix it or better yet they just buy our products and they just work magically all the time without fail conversing and comfortable with the concepts to the point which you can leverage them and what about visualization where does that fit visualization visualization is where the rubber meets the road of analytics is it's where human beings how human beings extract meaning insight fundamentally maybe that's like yeah you extracted inside a lots of different ways you do searches and so forth but to play around it to actually see you know a heat map or a geospatial map or or or you know a pie chart or whatever you see things with your eyes that you may not have realized we're there and if you can play around and play with different visualizations against the same data set things will pop out that you know the statistical model just seek the raw output of a data mining our predictive model or statistical analysis those patterns may not suggest themselves and rows of numbers that would pop out to an average human being or to a data scientist they need the visualizations to see things that you know because in other words when you think about analytics it's all about the algorithms that are drilling through the data to find those patterns but it's also about the visualizations the algorithms and you need the visualizations and of course you need the data to really enable human beings of all levels of expertise to find meaning and fundamentally visualizations are a lingua franca between non-expert human beings and expert eamon beings between data scientists visualizations are a lingua franca Hey look what I saw what do you think you know that's the whole promise of tools like concert for example we demonstrated this this morning it's a collaborative environment as sharing of visualizations and data sets and so forth among business analysts and the normal knowledge worker you know it with it you know like what do you see here's what I see what do you think I don't see that here's another visualization what do you see there oh yeah I think I see what you mean and here's my annotation about what I have broader context I've you know here's what I oh this is great that's the whole notion of humans deriving insight we derive it in socials we derive it in teams of that some Dave might be adept at seeing things that Jim is just absolutely blind to or you know Nancy might see things that both of us are applying to but we're all looking at the same pictures and we're all working with the same data part art yeah it's all so let's talk about some plumbing conversations you know one of the things that we noticed we were at the splunk conference this year's blown came out of nowhere taking log files making them manageable saving time for people so the thing that comes out of the splunk conversation is that it's just so easy to use that their customer testimonials are overwhelmingly positive around the area hey I just dumped my data into this the splunk box and it grid good stuffs happening I can search it it can give me insight save me time so that's the kind of ease of use so so how does IBM getting to that scenario because you guys have some good products we've got on the platform side but you also have some older products legacy Lotus other environments collaborative software that's all coming together in converging so how do we get to that environment where it's just that he just dumped your data in and let it do its magic well Odin go that's the very proposition that we provide with our puresystems puredata systems portfolio tree data system and big insights right for Hadoop so forth big in size you know we have an appliance now yeah we have pdh so that's the whole create load and go scenario that because Bob pidgeotto unless wretched and others demonstrated on the main stage yesterday and today so we did we do that and we are simple and straight being easy to use and so forth that's our value prop that's the whole value prop of an appliance you know simple you don't need a ton of expertise we pre build all the expert in a expertise patterns that you can use to derive quick value from this deployment we provide industry solution accelerates from machine data analytics on top of big insights to do the kinds of things you're talking about with splunk offerings so fundamentally you know that's scenario we all we and we're you know we have many fine competitors we offer that capability now in terms of the broader context you're describing we're a well-established provider of solutions we go back more than a hundred years we have many different product portfolios we have lots and lots of customers who would invested in IBM for a long time they might have our older products our newer products in various combinations we support the older generations we strive to migrate our customers to the newer releases when they're ready we don't force them to migrate so we make very we're very careful in our row maps to provide them with a migration path and to make it worth their while to upgrade when the time comes to the newer feature ok so I got it don't change gears to the to the shiny new toy conversation which is you know you know we love that in Silicon Valley what's a shiny new toy there's always an emerging markets when you have see changes like this where there's a whole the new whole new wave comes in creates new wealth old gets destructed new tags over whatever the conversation goes but I got to ask you okay well Elsa to the IBM landscape that you that you're over overlooking with big data and under the under the hood with cloud etc there's always that one thing that kind of breaks out as the leader the leading toy a shiny object that that people gravitate to as as I'm honest I won't say lost later because you got you know it's not not about giving away free it's it's the product that goes well we this is the lead horse you know and in this game right yeah so what is that what is the IBM thing right now that you're doubling down on is it blu acceleration is it incites is it point2 with a few highlights right now that's really cutting through the new the new the new soil of yeah we're developing our own rip off version of google glass thank you know I'm saying it's always I mean I'm gonna say shiny too but there's always that sexy product well I want that I want L customers name I want that product which leads more you know how she lifts for other products is there one is there a few you can talk about that you've noticed anecdotally is going to be specific data but just observational a shiny toy for the consumer market or for the business business business mark okay yeah yeah is it Watson is Watson the draw is it what's the headline looking for the lead lead dog here what's the attack there's always one an emerging market well you can put your the spot here well you could say that the funny thing is the whole notion of a shiny new toy implies something tangible when the world is gone more and more intangible in the cloud so we are moving our entire portfolio beginning links the big data analytics solutions into the cloud cloud first development going forward our other core principles for the pure data systems portfolio and the light for the shiny the shiny new thing the new cons could be shiny new concept or new paradigm yeah but the shiny new thing is the cloud the cloud is something pervasive and the cloud is something that it really multi form factors that's not very sexy but customers want flexibility you know they want to acquire the same functionality either as a licensed software package and running on commodity hardware we offer that for our big data analytics offerings or as an appliance and one sort or another that specialized particular occurrence or as a SAS cloud offering or as a capability that they can deploy in a virtualization layer on top of IBM or non-ibm hardware or they want the abilities you can mix and match those various deployment form factors so in many ways the whole notion of multi form factor flexibility is the shiny new thing it's the hybrid model for deployment of these capabilities on Prem in the cloud combination thereof that's not terribly sexy because it's totally it's totally abstract but it's totally real I mean demand wise people can see them that drives my business because when you go to the cloud I mean that's where you can really begin to scale seriously beyond the petabytes the whole notion of big media it will exist entirely in the cloud big media I like to think is the next sexy thing because streaming is coming into every aspect of human existence where stream computing a lot of people who focus on Big Data think of volume as being like big headline oh god we'd go to petabytes and exabytes and all that yeah it's important some really fixate on variety all these disparate sources of data and now we have all the sensor data and that's very important we have all the social media and everything all those new sources that's extremely important but look at the velocity everybody is expecting real-time instantaneous continuous streaming you know everything we do all of our entertainment all of our education surveillance you know everything is completely streaming I think ubiquitous streaming to every device and everybody themselves continue to continuing to stream their very lives everywhere all the time is the sexy new thing Dave and I talk about running data we coined that term running data what four years ago so I got to get you got to get kind of a thought leader they're watching us and we're watching streaming data right now from these said these are your guys are streaming this is big media give us some wanna get your thought leader perspective here some thought leader mojo around um the hashtag data economy you know you need now you're moving into a conversation with c-level folks and they said James tell me what the hell is this data economy thing right so what is the data economy in your words kind of like I mean I'll say it's a mindset I'll everything else what's your take on that we've been discussing that internally and externally at IBM we're trying to get our heads around what that means here's my take as one IBM are one thought Leigh right by the way the trick of being a thought leader is just to let your own thoughts lead you where they will turn around where all my followers yeah hopefully they want to lead you to far astray where you're out in the wilderness too long that's an important type of people are talking about because people are trying to put the definition around at economy can you actually have a business construct around yeah data here is my taken on the layers of the meaning of data economy it's monetizing your data the whole notion of monetization of your data data becomes a product that you generate internally or that you source from externally but you repackage it up and then resell with value add the whole notion of data monetization and you know implies a marketplace for data based products you know when I say data I'm using it in the broader context of it could be streaming media as the kind of one is a very valuable category of you know data like you know whatever kollywood provides so there's a whole notion of monetizing your data or providing a marketplace for others to monetize their data and you take a transaction fee from that or it also means in more of a traditional big data or data warehousing bi sense it means that you drive superior outcomes for your your own business from your own data you know through the usual method of better decision if better decisions on trustworthy data and the like so if you look at data monetization in terms of those layers including the marketplace including you know data-driven okay in many ways the whole notion of a data economy hinges on everybody's realization now that the chief resource for betterment of humanity one of the chief resources going forward for us to get smarter as a species on this planet is to continue to harness the data that we ourselves generate you know people stop what data is being the new oil what oil was there before we ever evolved but data wasn't there before we we landed on earth or before we evolved we generate that so it's our own exhaust your own exhaust that's actually a renewable resource data exhaust from data from exhausted gold that's what we say data is the data exhaust it's good if you can harness it and put it together as Jeff Jones says the puzzle piece is the picture the big picture at the smarter picture the smarter planet so on the final question I want to wrap up here to our next guest but what's going on with you these days talk about what's up with you you know you're very active on Facebook will you give a good following I'll be coming up what's happening you know I'll make sure I said big birthday for you on your Facebook page what's going on in your life I'll see you're working at IBM one of the things are interesting what's on your mind these days when you're at leisure are you hanging out you think what are you thinking about the most what are you doing with your you know things with your family's cherith let's see what's going on well I hang out at home with my wife and drink beer and listen to music and tweet about it everybody knows that stuff kind of beer do you drink whatever is on sale I'm not going to say where we buy it but it's a very nice place that whose initials are TJ but fundamentally you know my my mind is an open book because I evangelize I put my thoughts and my work thoughts and love my personal thoughts out there on socials I lived completely ons but I completely unsocial I self-edit but fundamentally the thought leadership I produce that the blogs and whatnot I produce all the time I put them out there for general discussion and I get a lot of good sort of feedback the world and including from inside of IBM I just try to stretch people's minds what's going on with me I'm just enjoying what I'm doing for a living now people save Jim you're with IBM why aren't you an analyst I'm still doing very analyst style work in in a vendor context I'm a thought leader I was a thought leader as I try to be being a thought leader is like being a humorist it's like it's a statement of your ambition not your outcome or your results yeah you can write jokes too you're blue in the face but if nobody laughs then you're not a successful comedian likewise i can write thought leadership pieces till I'm blue in the face but if nobody responds that I'm not leaving anybody anywhere i'm just going around in circles so my my ambition and every single day is to say at least one thing that might stretch somebody's box a little bit wider yeah yeah I think I think IBM smart they've been in social for a while the content markings about you know marketing to individuals yeah with credibility so I love analysts I love all my buds like like Merv and everybody else and I'm you know sort of a similar cat but you know there's a role for X analysts inside of solution providers and we have any number John Hegarty we have we have Brian Hill another X forest to write you know it's it's a you know it's a big industry but it's a small industry we have smart people on both sides of the equation solution provider and influencer my line um under people 99 seats and you know I I suck up to my superiors at IBM i suck up to any analyst who says nice things about me and hosts be on their show and i was going out of my life i'm just a big suck up well we like we like to have been looking forward to doing some crowd chats with you our new crouch an application with you guys lock you into that immediately it's a thought leader haven that the Crouch as as it turns out Dave what's your take on the analyst role at IBM just do a little analysis of the analyst at IBM which you're taken well I think it's under situation I think that the role that they that IBM's put James in is precisely the way in which corporations vendors should use former analysts they should give you a wide latitude a platform and and not try to filter you you know and you're good like that and so guess what I do the usual marketing stuff to the traditional but I do the new generation of thought leadership marketing and there's a role for both of those to me marketing have said this is if I said it was I said a hundred times marketing should be a source of value to people and it's so easy to make marketing a source of value by writing great content or producing great content so yeah that's my take on a jonathan your your marketing is a great explainer you explain the value to the market and thereby hopefully for your company generate demand hopefully in the direction of your cut your customers buying your things but that's what analysts the influencers should be explainers it's you know probably Dave I mean has influenced as influences that we are with with a qu here's my take on it when you have social media of direct full transparency there's no you can't head fake anyone anymore that all those days are gone so analyst bloggers people who are head faking a journalist's head faking the house the audiences will find out everything so to me it's like it's the metaphor of when someone knocks on your door your house and you open it up and they want to sell you something you shut the door in their face when you come in there and they say hey I want to hang out I got you know I got some free beer and a big-screen TV you want to watch some football maybe you invite him in the living room so the idea of communities and direct marketing's about when if you let them into your living room yeah you're not selling right you are creating value see what i do i drop smart i try to drop smart ideas into every conversational contacts throughout socials and also at events like i od so you know a big part of what I do is I thought leadership marketer is not just right you know you're clever blogs and all that but I simply participate in all the relevant conversations where I want I want ideas to be introduced and oh by they want way I definitely want people to be aware that I am an IBM employee and my company's provides really good products and services and support you know that's really a chief role of an evangelist in a high-tech slider that's one of the reasons why we started crouched at because the hashtag get so difficult to go deep into so creates crowd chatter let's go deeper and have a conversation and add some value to it you know it's you thinking about earned media as parents been kicked around but in communities the endorsement of trust earning a position whether you work at IBM people don't care a he works at IBM or whatever if you're creating value and you maybe have some free beer you get an entry but you win on your own merits you know I'm saying at the end of the day the content is the own merits and I think that's the open source paradigm that is hitting the content business which is community marketing if your pain-in-the-ass think you're going to get bounced out right out of the community or if you're selling something you're on so you guys do a great job really am i awesome you thank you James I really love what you add to the iod experience here with this corner and all the interviews is great great material well thanks for having us here really appreciate it I learned a lot it's been great you guys are great to work with very professional the products got great great-looking luqman portfolio hidden all hitting all the buttons there so hitting all the Gulf box so this is the cube we'll be right back with our last interview coming up shortly with Jeff Jonas he's got some surprises for us so we'll we'll see what he brings brings to his a game apparently he told me last night is bring his a-game to the cube so I'm a huge Jeff Jonas fan he's a rock star we love them on the cube iza teka athlete like yourself we write back with our next guest after this short break

Published Date : Nov 7 2013

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Fred Luddy, ServiceNow | ServiceNow Knowledge13


 

[Music] [Music] okay we're back after that nice break here from knowledge we're here in Las Vegas at the Aria hotel this is service now's big customer conference about 4,000 folks here mostly customers most of the content at this event comes from customers its practitioners talking to practitioners which is quite rare actually at these conferences I'm Dave Volante everybody thanks for watching with wiki Bond org I'm here with my co-host Jeff Frick this is Silicon angles the cube we go to these events we extract the signal from the noise we love to bring you tech athletes and Fred ludie is here he is a tech athlete he's the founder of ServiceNow he started this platform around 2003 Fred welcome to the cube thank you very much so we really want to hear the story you know but we've been asked to sort of hold that off because we got another segment with you tomorrow but I just I have to ask you I mean seeing how this conference and ServiceNow as an organization has grown you just must be so thrilled in particular with the customer enthusiasm <Fred>  you know fundamentally I've got a personality flaw and I call it a kindergarten mentality I want to see my art on their refrigerator and the only way you can do that is by making somebody happy and so to see these people here with the excitement the enthusiasm and the smiles on their faces really is satisfying that kindergarten mentality cakes oh good stuff we were talking about that earlier Jeff had not seen the cakes before and was was quite amazed today no I think that's an industry-first actually good well be yeah announcements today you know that's if so you guys had some you're gonna transform an organization you got to have mobile I mean the whole world to go on mobile five billion devices and and growing what you guys announced today <Fred> well we announced the ability to run all of our applications on the iPad and you know I think people's reasonable expectations these days are that they should be able to manage anything anywhere anytime using the device that they currently have now I I like to think of an iPad as something that you use when you're pretending to be attending a meeting or when you're pretending to be watching TV with your family and when you are pretending to do that it'd be nice if very efficiently and very effectively you could manage whatever you needed to manage to get your job done and so today what we've announced is the ability to run everything that ServiceNow has on that iPad  <Dave> yeah I mean it seems to mobile is basically a fundamental delivery model and maybe even the main delivery model going forward wouldn't it be I <Fred> I think it will be a main delivery model and it's a it's a user interface that that requires complete rethinking about how you're going to do things you know for the longest time we we looked at screens with 24 by 80s you know these character screens and then we got big pixel monitors and then we got bigger pixeled monitors and we got very accurate Mouse's and everything got small and got hovers you've got you know this massive amount of data and now the form factor is completely shrunk and you're looking at this as my major input device so how am I going to get you know everything I used to do with a mouse where I'm hovering over things to see what they do or I'm touching you know 16 by 16 pixels which you by the way you can't hit with your fingernail how am I going to get all of that stuff how am I gonna be able to work with all that stuff using only my thumb or thumbs so how are you specifically taking advantage of that smaller form factor and you know the feature sets that you see in things like iPad <Fred> well I think it's a matter of rethinking so we're trying to get the user to be to be able to accomplish their task by doing considerably less work and one of the things that our system is actually very comprehensive it's very big and we create in the browser and our first user interface it was really created in 2005 we treat all the elements of the system equally so now what we've done in the in the mobile which I think is very unique it does MySpace I mean Facebook doesn't have this Lincoln doesn't have this we know exactly what you do as a user and we remember those things that you do edit of Li and so we're able to create shortcuts or we're able to remember the system is able to remember what you do and then very quickly present you back with those tasks which are repetitive so we're trying to simultaneously compress the information and reduce the interactions yeah so that doesn't sound trivial it sounds like there's some secret sauce behind that talk about that a little bit <Fred> well it's not trivial and it's a there there is secret sauce but it does it just requires you to rethink and for me you know if you if you read the jobs biography there were a couple of interesting things in their number one when he met dr. land they had both agreed that everything that had been invented was going to be invented had already been invented right the other thing that they that they pretty much agreed on are what job said and a quote that I've used for years is that great artists copy good artists copy and great artists steal and I've been a thief all my life I just I'm gonna admit it right here it's not on camera live and so what we do is we go ahead and take a look at who's doing this great Amazon is doing it great Zappos is doing it great asan is doing it great you know we and we capture those ideas and then what they meant by great artists steal is that you take them and you reformulate them for the task that you're trying to solve for the problem that you're trying to solve and the rich the artist won't they probably the original artist probably won't even recognize that as their work but yet they're they're deeply inspirational to us an artist so do you fancy yourself as a bit of  <Fred> well I think it's interesting  down down the road and you know to I was watching the Bellagio fountains create something like that if you think about the physics and the art that had to go into that to create that beautiful masterpiece you know it's not just a painting right think about the physics that goes on to shoot something seven its water seven hundred feet in the air and then cut it off instantly and have that all choreographed I mean it's phenomenal amount of engineering but it took also a phenomenal amount of art just to make that interesting so that we were we actually stood there in rapt amazement of you know look how all this is choreographed so yes I do in fact I don't think I take exception to the term engineering software engineering I don't think we haven't progressed to the point where this is an engineering this is this is an art this is a craft you know it's something that people practice and we try to get better at it and better at it and better at it but I don't think it's anywhere near an engineering discipline <Jeff> yeah the other interesting from the jobs book that I never really got until I read the book was like the iPod shuffle because when I first saw the iPod shuffle and you can't do anything you can't manage your playlists on it you all you can do is change songs I don't get it and then in reading the book as you just said you know what is what is it you're trying to accomplish with that form factor right and don't just automatically try to replicate what you can do a one form factor to another form factor but really rethink what's that application and it sounds like you're kind of taking advantage of that opportunity as you take the app to the mobile space into the iPad specifically to rethink what is the best use case for that platform you'll see tomorrow the iPad was really  <Fred> that's right and as as the inspirational first step that we're taking toward a totally mobile app and just like the Apple evolution of building all of this note wonderful new capabilities into iOS and then bringing them back into OS X we're going to be doing the same thing so you'll see tomorrow on stage not only in an iPad app but you will see a native iOS app running and you'll see that it does even more things than the iPad app does and much faster it's a wonderful user experience and those those notions will be also coming back into the browser etc the same way that apples been bringing a lot of the capabilities of iOS back onto OS X <Dave> I was talking to an IT practitioner last month at a large grocer and I asked him what's your what's your biggest challenge what excites you the most and he said the same thing he said both of X what's my biggest challenge is embracing all this pressure from my users for mobile and that's what excites me the most because I have a mobile addict I got in it pulls out all those devices so how do you see this announcement within your user base changing you know the lives of IT  prose.    <Fred> well it'll you know technology since the dawn of time has been used really for two things it's been it's been used to streamline make make tasks more efficient and more streamlined and it's been used to create business differentiators and so our our product really is about process and moving process through an organization and so we want to streamline that as much as possible so if I can we do things like change management change management has multiple levels of approval if I can get it to the point where a manager can pull his phone out of his pocket and do five approvals between meetings he's become significantly more efficient right the changes are going to be done in a more timely fashion and the bottom line improves it's as simple as that <Dave> yeah it's interesting we were those of you watching no we were earlier the today broadcasting from sa P sapphire event and if you go to sapphire are you here to to get huge doses of two things one is Hana of course which is there in memory database but the other is mobile he's all you hear and it's interesting to hear you guys talk about the ERP of IT and your si PE they know the poster child for ERP and all their customers are going to mobile whether it's retail manufacturing you know across the supply chain and so it sounds like you've got sort of similar mentality but more focused obviously with it within IT but of course now you're also reaching beyond IT do you see you're a mobile app a push going beyond the IT community <Fred> yeah absolutely you know our underlying all of our applications we have a platform that say it's a forms based workflow platform that's really purpose-built for something that we would characterize as a service service relationship management so pretty much any request response fulfillment type workflow can be handled by our platform and what our customers have done over the years is create different applications that help them streamline that workflow typically that workflow is handled by by people creating a spreadsheet emailing it to somebody else having a TA back perhaps they built a Lotus Notes app but yes everything that that that or I will say that our platform usage has been expanded by our customers sometimes beyond our wildest dreams and and we love it so you talked about you know some of the greatest artists we stole rights of and so now you guys put up this platform I've said a number of times today it's not trivial to it to actually get a CMDB working in the way that you wanted to get it to work so now you've had this platform out for quite some time your successes started to you know you get a lot of press people are starting to see it do you worry sometimes that people gonna say okay I can do that too I'm gonna I'm gonna you know rip it off what gives you confidence that you can stay ahead of those those thieves out there <Fred> well I have great confidence in that you know we have a very broad base of applications that are very deep in functionality but if that's really something that you want to happen yeah because you want some young people with fresh new ideas to try to unseat you because they will come at the come at this from a completely different perspective and a completely different angle and they will do things that you never thought of and so the race is then on are they going to become more relevant than me or am I going to be inspired by their ideas incorporate them into our platform and stay ahead of them see welcome that all right absolutely welcome back yeah we we wouldn't be where we are today if Edison and Bell weren't weren't the jobs and gates of their time I mean they had just and I think jobs and gates as well right they had this great rivalry that really caused technology to move ahead a lot faster than when it was just I be am selling mainframes and so you need those rivalries you need that you need that competition you know I'm I'm watching these young guys from asana it's a great little platform for for tasking and you know they came out of Facebook they have a very Facebook mentality and they have phenomenal ideas and believe me guys from asana I'm watching you those are just that's where great ideas come from >> <Dave> Wow we always like to say we love sports analogies here in the cube and Jeff your kids are into sports well as our mind you always want to see and play that more competitive you know environment it sounds like Fred you have the same philosophy yes very much so yeah excellent all right Fred well listen we really appreciate you coming by now you come back Fred's gonna be back again tomorrow we're gonna go through the story of service now that's why we really didn't touch up on it and in any kind of detail today but to it but but but Fred actually started the company we give him a little preview Fred so you started the company really not to go solve an IT service management problem right you came up with this sort of idea this platform and and then you you that was really the first application that you developed right up a step in for that oh great you see give us a little tidbit we're gonna back >> every day I wake up that's all I really >><Fred> I've been a programmer now for 40 years want to do why do I program because I want somebody to take a look at the technology that I build and say hey that's pretty helpful I like that I can use they're gonna put that in my fridge fridge so the real strategy behind the company was to build some software that somebody wanted that hopefully they would pay me so I could build more software that was the entire strategy and so you know on one hand I love technology and on the other hand it really irritates me when it makes me feel stupid or it makes other people feel stupid so what I wanted to do was to create an enterprise platform that people could use and they would feel empowered they could walk up and use it like they'd walk up and use an ATM like they'd walk up and buy something from Amazon etc so a completely you know consumer eyes thought process and then that was the thought process really in O 3 and no 4 and then what we do really figured out was that a platform is a very hard sale you know it's tough to convince somebody that they should take this it'd be like selling you an Intel processor and telling you can do anything you want right I want to solve a business problem and so we decided to go after the ITSM space first it was a space that was very underserved very lucrative and and growing significantly <Dave> amazing so so join us tomorrow we're gonna Fred back on and we're going to here this story the founding story of ServiceNow and how we got to where we are today so Fred thanks very much for coming on and sharing the news and I'm gonna change it all by tomorrow good all right so so keep it right there I will be up next we've got Douglas Leone coming on which is a partner at Sequoia Capital and and and one of the better-known DC's out in the valley so so keep it right there will be back with Doug just in a minute this is ServiceNow this is the cube this is knowledge right back

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Jason Wojahn | ServiceNow Knowledge13


 

okay we're back this is Dave vellante Wikibon org i'm here with jeff Frek we're here at knowledge service now is big customer event we're at the aria hotel a lot of enthusiasm a lot of great stories we're seeing a pattern emerged IT is essentially this collection of disparate processes we have a lot of activity going on spreadsheets people using email to really keep track of what's going on many many systems trying to keep track of inventory assets process these problems incidents changes etc etc and it's just this big web of mess here comes service now a single system of record a cmdb that allows you to essentially tailor your processes to your business as opposed to some kind of technology module or some other kind of software system jason wu yan is here he's the vice president of operations for a cloud sherpas works within the ServiceNow business unit at Cloud Sherpas was a big sponsor of the show Jason welcome to the cube thank you very much so you heard my little intro of guys must be excited big sponsor a lot of a lot of action going on in this this event how do you feel we feel outstanding we're happy to be a part of the the event this is my third knowledge conference and of course as the director of training in service now I like to say there are more people in training at this conference that attended the entire knowledge 11 conference so it's a pretty phenomenal event so how was it progressed over the years this is my first knowledge and so I don't have that history I'd say that you know we leave a long legacy with service now all the way back to some of the very first knowledge conferences that occurred in first knowledge conference we probably could have had a the entire conference in this table right and of course today with almost four thousand attendees it's it's certainly grown tremendously we've got somewhere the neighborhood 1,200 people that have gone through training at this event alone we did a big part of providing that training for on behalf of service now with other partners as well and it's an exciting event there's a large buzz here as I'm sure you've seen there really is yes sir Cloud Sherpas other than a great name you know tell us about the company it's a great it's a great story to tell Gartner likes to turma cloud services brokerage and so first and foremost we're cloud services brokerage we have three strategic partnerships we are a Salesforce a partner we are one of the largest Salesforce partners in the world actually top five from a certification standpoint we're the largest Google Enterprise integrator in the world we're actually Google Google's partner of the year in 2011 and 2012 of course we like to think we're pretty good at servicenow as well a little background on us in the ServiceNow business unit we were the first partner in the United States Forest Service now we are the first partner to achieve preferred status at servicenow and the only partner to achieve that status globally today so how's it work so a customer wants to implement service now or google enterprise or Salesforce you basically are that brokerage layer in between so talk about how that works well we help customers adopt manage and enhance their cloud solutions of course focusing on this particular context service now and we are there from day one we're there to help them bring the platform into their environment we're help there to help them refine their processes and practices and of course ultimately align that to the service now a tool and help them manage that through their life cycle so how do you get ready for this what do you tell customers they need to do I tell customers commonly it's best to start where you're at with any improvement activity and ultimately in an enterprise deployment of software you're going to take that as an opportunity to improve I say start where you're at take the time to understand how you do things today you'd be surprised to see how often customers don't aren't all on the same page as to how they perform incident or what the key processes are underneath that or even what the key performance objectives are for that of course we recommend starting where you're at of course we have requirements workshops opportunities we have a number of I tell practices and other types of areas where we can help elaborate those requirements and better align them to their business needs but first and foremost you need to understand what you want your environment to look like some a requirement standpoint the workflows are key so what are the big obstacles that you see people running into when they try to do implement like this I would say in general taking too big of a bite you know there are over twenty two applications as an example in service now you don't want to start day one with 22 applications it's not because ServiceNow wouldn't be able to handle it ServiceNow can deploy very rapidly you really start simple start where you're mature or start where you have the most profound opportunity to improve and align to better practices get the foundation of the platform in place stabilize that and then move on to your next phase and progressively adopt more and more of the application so it's with the pattern that's emerging here we're hearing from customers people starting with incident problem management change management you know why there why why do we see that pattern emerging I think more across the industry that it tends to be a place where customers have have focused on over time so that tends to be where they're more mature they tend to have a better understanding of maybe what their shortcomings are today in those spaces so they tend to be an easier place to start what percentage of them are displacing some other legacy software versus we've heard about I'm not counting excel in that in that list or lotus notes because we hear a lot about that but I would presume there's other software out there that they're displacing we see a lot of software that gets this place down there of course point solutions where there's a lot of databases and homegrown applications handling change your change approvals or cab boards or those types of things of course it's a good opportunity to consolidate that and of course you know service now is known within the industry is being a pretty proficient solution but there are other solutions and we are offering seen that we're offsetting those as well you have we have the steam of no.2 now do you have any you know favorite examples that you can share with us or what are you some of your customers doing ha we've got a lot of good examples i would say probably most recently we just helped a very large clothing manufacturer an american good american company that had nine support environments globally and they had nine different ways of doing everything and they look use this as an opportunity to consolidate those and get to a single source of record get to a single workflow globally and in that they also transformed and improve their processes and and that was something that they couldn't have accomplished with really any other project or really any other tool in the market they of course chose to go down the path with with service now and you know a short few months later they're implemented across incident problem changed service request Service Catalog a very profound Service Catalog spanning literally hundreds of request items employee self-service portal that's been branded to their to their corporate brands there's been a lot of excitement in their injuries or community because they look like their company when they're when they're asking for support and they get a much more automated and in much more efficient process what was the genesis of that was it again something was breaking they had to change it was it let's just take a step back there's opportunity that we wanted to do this or were the easing service now and some other minor role and said wow you know we can actually use this tool to take advantage and do something transformation and generally what we see is service now it's really the enabler it's the enabler to transition transform now we've seen global sis do this forever that's their big thing we're going to help you consolidate and get your hands around it I think service now gives you the ability to to do that neutral of a partner or neutral of an outsourcing provider you can get your arms around it on your own and again many customers are relatively mature and incident problem and change and so it's a good opportunity for them to find those areas where they can aspire to better practice better process and to implement that into service count tool how was your business involves I mean it's so interesting because the poster child of SAS and Salesforce you guys obviously you know chose well that was 1999 may we are in 2013 it's really taking a long time Google Enterprise okay that's make sense but Google you know big whale I see you know guys like workday you know service now come out why do you think it's taken such a long time for these applications to catch on and and how has cloud sherpas you know progressed over those over that time frame well what i would say is the notion of a cloud services brokerage didn't exist eight to ten years ago right that that aggregation point didn't really exist it was those point solutions were always provided by those point providers or their tightly coupled partners in that space and of course with the emergence of this notion of a brokerage that's helping aggregate and manage and enhance low solutions you know we're seeing a lot of degrees of freedom so you know where we started we started as a firm that was focused on Google that emerged into Salesforce and now is through in a company called Navitus a few earlier or late last year now the ServiceNow practice as well and you know moreover it's it's it's where things are going right the truth is is that end-users and corporations and and whether it's you on your iPhone and for personal use or business use you want those applications available you want to have a solid user experience ServiceNow was really first in this space to be able to offer that in a way that was truly platform neutral that just worked whether it was a smart phone or an iPad or a desktop or laptop of what happened so talk about your strategy clouds share purrs and talk a little bit about how you differentiate well we differentiated in a number of ways but specific in the ServiceNow business unit and III don't think it's it could be said enough the cloud services brokerage is a huge differentiating point for us right having the scale that we do globally having you know several key strategic partners enables us to see areas and aspects of the industry that I don't think other partners can but from a service town business you know perspective I think we have a live a couple a couple differentiating points when is we were one of the first adopters of the platform from a partner perspectives so obviously we have a lot of deep skills in this we've done over 320 implementations of service now to date to have and of course 320 over 320 and through that history we've seen we've seen a lot of heuristics we've seen a lot of customer success stories we've seen a lot of things in the platform that customers are asking for time and time again and we've been able to fit that need both by my IT service management but also by industry as well a great example of that is we've got a number of custom applications that we've developed one of them as is a document management document processing application that a lot of legal firms are using in fact what we found is we built it for one company a few years ago Morrison forest or better known as mofo and now five or six legal firms later they've all asking for that same application and so we're finding that there's also you know real opportunity from an industry perspective to align to some of those point solutions extend the platform and just include those in the solution here's so much today about Big Data and you know it's all about this unstructured mass of information a bring structure to unstructured data maybe lending structured and unstructured some people don't even like those terms because it's all sort of blending how does analytics play into this whole IT Service Management IT automation there's a lot of metrics so they get this automating this forms based process is there a place for that or is is there not right now because everybody's kind of doing their own thing you know ten years ago I t was all about the tnit right it's all about the technology now it's all about the eye it's all about the information a great examples we're seeing a lot of partner solutions emerge in the ServiceNow ecosystem that are trying to better rationalize data there are tools like mere 42 for example which it's whole purpose is to is to bolt onto service now and provide a more comprehensive analytic package and there are many other examples of that as well in truth it's a services lead operation at this point it's not a technology led operation the only way to really ensure that you're delivering any quality of services or support is the quality of data that you provide and that starts with your requirements and those requirements need to bridge the performance measures in those performance there is just being an easy way to be accessible transparent and manageable and of course that's a big part of what service now does so how do you see this cloud brokerage you know space evolving over the next three to five years what's going to change you're going to hear a lot more from Cloud Sherpas in the space in the next three to five years that's for sure you know I think what we're going to find is is that more and more you're going to you're going to see gsis and other types of firms moving to this sort of model right I mean we're only we're going to take a lot of business away from them and and in that process you know it's going to get the right levels of attention you know what what I really think that cloud services brokerage is is it's a firm that is extremely experienced in the platform and the products they sell but more importantly the underlying reason for selling that product in the first place you know services IT services in this case it's a company that's known for being a little bit more nimble than some of those GS is you know getting the proposals out quickly and being effect effective and efficient and not looking to establish this enormous agreement but but a series of agreements that gets a customer to to where they need to go and I think what we're going to see is it is time and time again that the the early adopters in the cloud services brokerage spaces are going to be are going to be growing at rates like our business unit for example are business units currently growing at one hundred and fifty percent it's a tough tough job to keep up with but tools like ServiceNow certainly help us manage that and keep us on track with our own projects your own time carts and our own tasks yeah so you guys are great on the rocket ship with good service now pulling them along are they pulling you along a little bit of both like bikers drafting yeah so hexcel and I Jason we'll listen thanks very much for coming on the cube and sharing the cloud sherpas story will give you the last word here what advice would you give to folks that are you know maybe kicking the tires and mostly thirty percent of the audience here are not ServiceNow customers they're thinking about it what would you tell those guys have a good understanding of where you're at have a good vision of what you want to achieve and don't be afraid to go to the cloud it's not as not as hard as it sounds its clouds not scary just jump right in the water's fine hi Jason thanks very much for coming on really appreciated a good luck with managing that crazy growth and pleasure meeting you thanks very much all right Jeff reckon I'll be back with our next guest keep right here this is the cube we drop it of these events and we're covering the wall-to-wall service now knowledge will be right back from Las Vegas right after this

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Frank Slootman | ServiceNow Knowledge13


 

this one minute I'm here with my co-host Jeff Frick who we just fresh off of the AWS summit the Amazon event Jeff and I covered that and we're here at knowledge 13 now this conference is all about the notion of going from IT as a service organization changing high teas mantra from no to now that really is the theme of this conference and we're here with Frank's luton who's the president and CEO of service now Frank welcome back to the cube thanks good to be here that's good to see you again we had you on that vm world is great story when we first introduced service now to our community you just fresh off the keynote fantastic keynote by the way thank you you had strong themes i mentioned the from no to now you talked about itu gave a little little tongue-in-cheek joke about the line outside the the rmv the Registry of Motor Vehicles and that's sort of the the idea is you guys are transforming IT from an organization that is trying to manage demand push off demand saying no we'll get it in six months it'll cost you five million dollars to one that really is redesigning IT processes around the globe so first of all welcome back congratulations how do you feel after that keynote I have to work a lot of energy in that room and it was electrifying it was awesome well one of the one of the guys in the panel stopped when you had asking the question I think was the guy from NY yes he said even stop you looked at the audience said i love this crowd that was a great crowd we gave a little goop out to the audience so talk about from know to now how'd you come up with that theme and you know give us a little color behind you know it's it's actually not easy for for us to communicate about service now desk to to lay people in sight unless you have lived in sight I t you just most people don't even know what I t really does on the day-to-day basis right so we've lived a fairly insular existence because you know everybody knows what sales people do and to some degree about HR doesn't finance people but I t it's a bit of a you know a bit of a mystery to what most folks do right but most people do know however is that the service experience with IT has been and challenging what's all we say I mean it's been you know sort of a service experience where if you have to ask the answer was going to be no right because IT organizations have been super preoccupied with infrastructure rapid change in the infrastructure for the last 30 40 years nothing ever set still long enough for us to really master the architecture and the platforms are really stabilizing mature our systems and they have to keep moving so you get pretty cranky it's back to your organization having to live that kind of life so their their their reputation for service has not been stellar and I love making the joke during the keynote their ranking right down there with legal in the basement you know of the corporate enterprise you know so well so talk a little bit about sort of how you guys you know go into an organism's you start with the IT organization right in helping them sort of automated processes connect all these different processes but you've been through your platform expanding out to other parts of the organization the irony is that I T which is the most technology savvy organization in the price as the least management sophistication in terms of managing their own activity which you know I duck to the CIO of a very large consumer gets company he said where does she make her son it's inexcusable right here here we are running milk that going in dollar budgets and staffs with tens of thousands of people and we're running it on spreadsheets email excel project management tools this is ridiculous right we don't have real information in near real time and show that we can drive our business as opposed to being driven by it right i key executives have a tendency to run from one crisis to another with their hair on fire and that's sort of the mental model and a note of now message is about out of a get these people out of this you know reactive crisis mode to where they become full-blown business partners and they start you know bring your guide to enterprise and in a very transformative way or they become the people that bring innovation to the enterprise you know here's so much Frank about shadow I teach my colleague Jeff Frick and I were at the AWS some of the few weeks and you see a lot of these cloud companies you mentioned your keynote Salesforce the salespeople workday talk to HR people they sort n run IT certainly amazon is the poster child for shadow IT but you know Jeff we have that sort of notion where IT people are not the center of the new cloud universe but that's different for service now yes it's very different but the other thing brought up amazon your keynote and how they've kind of fine what kind of a user expectation experiences with an application on the web a level of service a level of delivery and then you've got AWS its kind of the girl child of shadow IT but you guys are coming in really as the enabler to let the internal IT guys actually have the tools to compete with with guys trying to go around it really exact with delivery platform I mean we're trying to turn the tables here right because the entire history of IT is one big end around righty the many computer was an end-around of the glasshouse client-server was really pcs you know dribbling into departmental environments suffer as a service was an incredible end around people in there didn't realize it was seeping into the enterprise right now things like 80 lbs now infrastructure right is actually finding its way so we're saying look you know worthy Enterprise IT cloud company right we are going to empower and enable IT to be driving rather than just being driven and being taken over and run over by by events because that's what's been happening here's the goodness IT can start withdrawing and getting out of the business of infrastructure which is what they've been doing forever infrastructure is very challenging pretty soon that's going to be somebody else's problem right infrastructure goes behind the cooking all you have to do is in network connection so that means that the role of IT is moving from you know keeping the lights on to you know we're going to be the people who are experts at defining structuring and automating service relationships and so does relationship management I mean at this and I make a joke about you know your hole in the inbox of email you know it's full of basically service relationships that are unstructured and unlimited and undefined right right and there is this incredible opportunity to go aptet with record-keeping workflow systems and that's what we want to enable and empower IT to do right we had to give you a quick example actually very interesting we talked to our one of our very large retail customers and the supply chain office unbeknownst to us went to IT and said hey we want to build this app what should we use and Ikey said no you should try and do that on service now what's the app a supply chain office in a retail environment what they do is they take requests all day long stores distribution centers suppliers and they're rebalancing you know product right place right time right right product and they were doing that everybody running spreadsheets and emails and people constantly calling what's the update on my request and they decide no we're going to go to a record-keeping workflow system and from the moment you know they started using that system all of a sudden they had full visibility to a what the volume was of issues that was coming in but the nature of the volume was how well they were doing on their SOS relative to their storage and distribution centers and they were able to structurally go after you know the things that were a constant them grief because they just didn't know right so very simply in very short period of time you know they transformed themselves from the supply chain all those Devils running around like a chicken with his head cut off the people that were actually driving to supply chain now now supply chain management in the retail organization it's super mission-critical right because their results are directly impacted by having right product right time right place simple example where we moving from email and Excel to a record-keeping workflow system any impact with literally within 30 40 days is enormous yeah you hear that a lot of people just using Excel using email we talked to we talking some customers last night we talked to some perspective customers that were in so to check it out and they were big Lotus no shop and is describing sort of the difficulties and challenges of it you will sign them up I can almost see it but the other thing so so this notion of your customer base is very powerful in fact I tweeted out I said the service now has a sick logo basis and we said is that a typo said no sick like that sick touchdown catch it isn't good yeah sick is it good but I mean which I we hear from land o lakes Red Hat metropcs KPM nor Brent I mean just on and on and on at Facebook Intel google or customers what are some other favorite customer stories you hear a lot of the same themes Frank you know we used to use spreadsheets with using email or reliant on all these disparate processes bringing them all together getting some some other you know favorite stories of yours for customers I I relayed a bunch of him on stage this morning right beasties it's just extraordinary to me the the corporate America I mean you mentioned some of them but you know the people we had on stage you know AIG you know coca-cola company's general electric demand this is United States Army right and they owe is yeah New York Stock Exchange eli lilly big pharmaceuticals bristol-myers squibb they all have the same set of issues they have a completely fractured fragmented sprawled acti environment right and here's the interesting history we have not had CIOs that long you know I T used to report into a division next sag or a regional exact and there really wasn't one person that was responsible for running IT throughout the global enterprise because it was just a decentralized function by the way example when you in Europe yeah I ray mighty and I certainly wasn't IT guy stuff and by the way it wasn't my priority either you know it was just by the way that's for some of the history you know comes from so CIO comes in and they are now charged with you're going to run this thing they're not running anything they're being run by it right so until you get to global IT processes I mean City another you know big name they set to as rogue global bank that we don't have global IT right it is the inefficiency and the lack of ability to drive and manage is unacceptable for these very sophisticated large institutions it's embarrassing really you know yeah I mean you really can't go global as a come you can't scale your business not having all these surprises so to me it's about global scaling and it's about the business value of both having ITB accountable but also have the metrics and the visibility to be able to demonstrate the value to the organization you see i SAT with our executive sponsor from bristol-myers squibb last night and she said i got data and i got it in real time and i know it's good so I'm not putting my service providers on their heels you know before they were you know everything was you know in the realm of you know interpretation and fuzzy fuzzy right and now it's like I have data and I'm driving and I'm changing behavior right so the empowering effective it has mighty organizations it's just stomach right I thought that empowering note that came up in your keynote was interesting how the IT organizations themselves and their presentation now to their internal customers are looking more like a company you know they're they're being cute there yeah I'm taking branding they're there they're not just button pushers in and as you said you know infrastructure operators they are trying to be contributors to the business and keeping some this automobile shade of nail them to it's even stronger than now yes they want to be contributors to the business but they want to be the playmakers they wanted me to go to guys give me the ball you know that that's where we want to you know take itt there that people that really understand how to change how work gets done the enterprise I thought you characterize the dwelling experience in IT people have been running from crisis to crisis and they need to be more proactive so talk about how your system allows them to be more proactive well it's all about going from a message oriented environment to a system or an a message or environment is the one way l know it's email it's text you know it's voice right that doesn't work because you know we're just talking right systems have the ability to drive behavior because you know every time you send an email you should think to yourself could i create a service request instead right because a service request has a defined data ship it goes into a database it gets assigned you know in a workflow operation it has metrics around it if it doesn't get responded to a certain amount of time it gets accelerated to the escalator to the next level or management right so the process is defined structure to automate it is going to run its course right whether you know people are participating in it or not with this great example one of our customers equinix delilah or Brian Lily's here actually is a CIO and he said they will sell funny you know we have a system that all my life cycle application where our developers check-in fixes and enhancement to a particular software release for an application and he says because they know to work flows is completely structured an automated everybody knows that they don't get their fixes enhancement in by a certain time poof the dashboards pop the higher-ups see you know who's behind and who's not and that the threat alone of the transparency and visibility that the process introduces causes everybody there run harder right so people won't have to run around with the whip like where are you you know the process is driving is like a hamster on a treadmill you know so Freki used amazon as an example of the user experience that you know you covet as a CEO of this company and you believe you're your customer base desires at the back end also when you talk about companies like Amazon and Facebook and Google they are super highly automated you also talked about lights out automation yeah now normally IT organizations are managed now they're managed by humans they're not highly automated are you are you seeing your customers able to get to that sort of vision that you're talking about that lights-out automation almost like the hyperscale guys you know it's a super important custody I said during the cleanup or were overstaffed and under automated NIT we have reams of people on staff any large financial institutions have tens of thousands of people on staff they're bigger than any technology company right why is that it's because things are very laborious laborious and manual right the processes that they run require so many touch points I mean one of the things that we always tell our customers when you can reimplement these processes do not take your legacy forward because your legacy is very manual you remember the inbox in the outbox when we have physical in boxes and other boxes and now we know we have our laptop why do we have an inbox and outbox right does this message really this cross why are you even involved in this process right so we have to invert the process it's not like wouldn't it be nice for you to be involved in this process there'd better be a very good reason for you to touch this process because the moment you touch it you know we're going from the speed of light to you know the speed of the dirt road that Franco so service now is really in a rocket ship right now and you've demonstrated you've got a track record of being able to be sometimes call jump three myself throwing gasoline on the fire you look very good at that you got 1,600 customers you're growing like crazy but you're under penetrated in your target which is the global 2000 you're only fourteen percent penetrated in the global 2000 so get a long way to go in this journey we're very excited to be you know covering this event really appreciate you guys having us here Frank's loot Minh will give you the last word and then we'll wrap you know this is actually one of the great things that we are so on the front hood and they're penetrated because our investors are like wow you've got a lot of runway you know considering the size company that we we already are and you know the rate of monetization of our business is is extraordinarily I in other words the share of wallet that service now represents and the enterprise is so much larger than people had ever considered or thought because it was not an existing category that was fully metastasized and visible it's new it's emergent it is really transforming how people you know look at technology and process automation and so on now we're gonna be here all week covering knowledge we've got it we're going to double-click on so how is it that service now is able to deliver this cloud functionality the secret is in the single system of record the CMDB and that is not a trivial thing to do we didn't talk about that with Frankie could talk about it but we don't want to steal you know the name of thunder yeah fred muddies going to be on RNA Justin who's the CTO we're going to go deep into sort of how service now actually accomplishes this architecture Lee what their vision is so Frank thanks very much for spending so much time I know you're busy you got to run but appreciate you coming on terrific thanks for having me alright thanks for watching everybody keep it right there we'll be right back with more we're live from Las Vegas ServiceNow knowledge we'll be right back this is the Q cute baby rock and roll

Published Date : May 15 2013

**Summary and Sentiment Analysis are not been shown because of improper transcript**

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