>>Hey, welcome back everyone. Day three of eight of us Reinvent 2022. I'm John Farmer with Dave Volante, co-host the q Dave. 10 years for us, the leader in high tech coverage is our slogan. Now 10 years of reinvent day. We've been to every single one except with the original, which we would've come to if Amazon actually marketed the event, but they didn't. It's more of a customer event. This is day three. Is the machine learning ai keynote sws up there. A lot of announcements. We're gonna break this down. We got, we got Andy Thra here, vice President, prince Constellation Research. Andy, great to see you've been on the cube before one of our analysts bringing the, bringing the, the analysis, commentary to the keynote. This is your wheelhouse. Ai. What do you think about Swami up there? I mean, he's awesome. We love him. Big fan Oh yeah. Of of the Cuban we're fans of him, but he got 13 announcements. >>A lot. A lot, >>A lot. >>So, well some of them are, first of all, thanks for having me here and I'm glad to have both of you on the same show attacking me. I'm just kidding. But some of the announcement really sort of like a game changer announcements and some of them are like, meh, you know, just to plug in the holes what they have and a lot of golf claps. Yeah. Meeting today. And you could have also noticed that by, when he was making the announcements, you know, the, the, the clapping volume difference, you could say, which is better, right? But some of the announcements are, are really, really good. You know, particularly we talked about, one of that was Microsoft took that out of, you know, having the open AI in there, doing the large language models. And then they were going after that, you know, having the transformer available to them. And Amazon was a little bit weak in the area, so they couldn't, they don't have a large language model. So, you know, they, they are taking a different route saying that, you know what, I'll help you train the large language model by yourself, customized models. So I can provide the necessary instance. I can provide the instant volume, memory, the whole thing. Yeah. So you can train the model by yourself without depending on them kind >>Of thing. So Dave and Andy, I wanna get your thoughts cuz first of all, we've been following Amazon's deep bench on the, on the infrastructure pass. They've been doing a lot of machine learning and ai, a lot of data. It just seems that the sentiment is that there's other competitors doing a good job too. Like Google, Dave. And I've heard folks in the hallway, even here, ex Amazonians saying, Hey, they're train their models on Google than they bring up the SageMaker cuz it's better interface. So you got, Google's making a play for being that data cloud. Microsoft's obviously putting in a, a great kind of package to kind of make it turnkey. How do they really stand versus the competition guys? >>Good question. So they, you know, each have their own uniqueness and the we variation that take it to the field, right? So for example, if you were to look at it, Microsoft is known for as industry or later things that they are been going after, you know, industry verticals and whatnot. So that's one of the things I looked here, you know, they, they had this omic announcement, particularly towards that healthcare genomics space. That's a huge space for hpz related AIML applications. And they have put a lot of things in together in here in the SageMaker and in the, in their models saying that, you know, how do you, how do you use this transmit to do things like that? Like for example, drug discovery, for genomics analysis, for cancer treatment, the whole, right? That's a few volumes of data do. So they're going in that healthcare area. Google has taken a different route. I mean they want to make everything simple. All I have to do is I gotta call an api, give what I need and then get it done. But Amazon wants to go at a much deeper level saying that, you know what? I wanna provide everything you need. You can customize the whole thing for what you need. >>So to me, the big picture here is, and and Swami references, Hey, we are a data company. We started, he talked about books and how that informed them as to, you know, what books to place front and center. Here's the, here's the big picture. In my view, companies need to put data at the core of their business and they haven't, they've generally put humans at the core of their business and data. And now machine learning are at the, at the outside and the periphery. Amazon, Google, Microsoft, Facebook have put data at their core. So the question is how do incumbent companies, and you mentioned some Toyota Capital One, Bristol Myers Squibb, I don't know, are those data companies, you know, we'll see, but the challenge is most companies don't have the resources as you well know, Andy, to actually implement what Google and Facebook and others have. >>So how are they gonna do that? Well, they're gonna buy it, right? So are they gonna build it with tools that's kind of like you said the Amazon approach or are they gonna buy it from Microsoft and Google, I pulled some ETR data to say, okay, who are the top companies that are showing up in terms of spending? Who's spending with whom? AWS number one, Microsoft number two, Google number three, data bricks. Number four, just in terms of, you know, presence. And then it falls down DataRobot, Anaconda data icu, Oracle popped up actually cuz they're embedding a lot of AI into their products and, and of course IBM and then a lot of smaller companies. But do companies generally customers have the resources to do what it takes to implement AI into applications and into workflows? >>So a couple of things on that. One is when it comes to, I mean it's, it's no surprise that the, the top three or the hyperscalers, because they all want to bring their business to them to run the specific workloads on the next biggest workload. As you was saying, his keynote are two things. One is the A AIML workloads and the other one is the, the heavy unstructured workloads that he was talking about. 80%, 90% of the data that's coming off is unstructured. So how do you analyze that? Such as the geospatial data. He was talking about the volumes of data you need to analyze the, the neural deep neural net drug you ought to use, only hyperscale can do it, right? So that's no wonder all of them on top for the data, one of the things they announced, which not many people paid attention, there was a zero eight L that that they talked about. >>What that does is a little bit of a game changing moment in a sense that you don't have to, for example, if you were to train the data, data, if the data is distributed everywhere, if you have to bring them all together to integrate it, to do that, it's a lot of work to doing the dl. So by taking Amazon, Aurora, and then Rich combine them as zero or no ETL and then have Apaches Apaches Spark applications run on top of analytical applications, ML workloads. That's huge. So you don't have to move around the data, use the data where it is, >>I, I think you said it, they're basically filling holes, right? Yeah. They created this, you know, suite of tools, let's call it. You might say it's a mess. It's not a mess because it's, they're really powerful but they're not well integrated and now they're starting to take the seams as I say. >>Well yeah, it's a great point. And I would double down and say, look it, I think that boring is good. You know, we had that phase in Kubernetes hype cycle where it got boring and that was kind of like, boring is good. Boring means we're getting better, we're invisible. That's infrastructure that's in the weeds, that's in between the toes details. It's the stuff that, you know, people we have to get done. So, you know, you look at their 40 new data sources with data Wrangler 50, new app flow connectors, Redshift Auto Cog, this is boring. Good important shit Dave. The governance, you gotta get it and the governance is gonna be key. So, so to me, this may not jump off the page. Adam's keynote also felt a little bit of, we gotta get these gaps done in a good way. So I think that's a very positive sign. >>Now going back to the bigger picture, I think the real question is can there be another independent cloud data cloud? And that's the, to me, what I try to get at my story and you're breaking analysis kind of hit a home run on this, is there's interesting opportunity for an independent data cloud. Meaning something that isn't aws, that isn't, Google isn't one of the big three that could sit in. And so let me give you an example. I had a conversation last night with a bunch of ex Amazonian engineering teams that left the conversation was interesting, Dave. They were like talking, well data bricks and Snowflake are basically batch, okay, not transactional. And you look at Aerospike, I can see their booth here. Transactional data bases are hot right now. Streaming data is different. Confluence different than data bricks. Is data bricks good at hosting? >>No, Amazon's better. So you start to see these kinds of questions come up where, you know, data bricks is great, but maybe not good for this, that and the other thing. So you start to see the formation of swim lanes or visibility into where people might sit in the ecosystem, but what came out was transactional. Yep. And batch the relationship there and streaming real time and versus you know, the transactional data. So you're starting to see these new things emerge. Andy, what do you, what's your take on this? You're following this closely. This seems to be the alpha nerd conversation and it all points to who's gonna have the best data cloud, say data, super clouds, I call it. What's your take? >>Yes, data cloud is important as well. But also the computational that goes on top of it too, right? Because when, when the data is like unstructured data, it's that much of a huge data, it's going to be hard to do that with a low model, you know, compute power. But going back to your data point, the training of the AIML models required the batch data, right? That's when you need all the, the historical data to train your models. And then after that, when you do inference of it, that's where you need the streaming real time data that's available to you too. You can make an inference. One of the things, what, what they also announced, which is somewhat interesting, is you saw that they have like 700 different instances geared towards every single workload. And there are some of them very specifically run on the Amazon's new chip. The, the inference in two and theran tr one chips that basically not only has a specific instances but also is run on a high powered chip. And then if you have that data to support that, both the training as well as towards the inference, the efficiency, again, those numbers have to be proven. They claim that it could be anywhere between 40 to 60% faster. >>Well, so a couple things. You're definitely right. I mean Snowflake started out as a data warehouse that was simpler and it's not architected, you know, in and it's first wave to do real time inference, which is not now how, how could they, the other second point is snowflake's two or three years ahead when it comes to governance, data sharing. I mean, Amazon's doing what always does. It's copying, you know, it's customer driven. Cuz they probably walk into an account and they say, Hey look, what's Snowflake's doing for us? This stuff's kicking ass. And they go, oh, that's a good idea, let's do that too. You saw that with separating compute from storage, which is their tiering. You saw it today with extending data, sharing Redshift, data sharing. So how does Snowflake and data bricks approach this? They deal with ecosystem. They bring in ecosystem partners, they bring in open source tooling and that's how they compete. I think there's unquestionably an opportunity for a data cloud. >>Yeah, I think, I think the super cloud conversation and then, you know, sky Cloud with Berkeley Paper and other folks talking about this kind of pre, multi-cloud era. I mean that's what I would call us right now. We are, we're kind of in the pre era of multi-cloud, which by the way is not even yet defined. I think people use that term, Dave, to say, you know, some sort of magical thing that's happening. Yeah. People have multiple clouds. They got, they, they end up by default, not by design as Dell likes to say. Right? And they gotta deal with it. So it's more of they're inheriting multiple cloud environments. It's not necessarily what they want in the situation. So to me that is a big, big issue. >>Yeah, I mean, again, going back to your snowflake and data breaks announcements, they're a data company. So they, that's how they made their mark in the market saying that, you know, I do all those things, therefore you have, I had to have your data because it's a seamless data. And, and Amazon is catching up with that with a lot of that announcements they made, how far it's gonna get traction, you know, to change when I to say, >>Yeah, I mean to me, to me there's no doubt about Dave. I think, I think what Swamee is doing, if Amazon can get corner the market on out of the box ML and AI capabilities so that people can make it easier, that's gonna be the end of the day tell sign can they fill in the gaps. Again, boring is good competition. I don't know mean, mean I'm not following the competition. Andy, this is a real question mark for me. I don't know where they stand. Are they more comprehensive? Are they more deeper? Are they have deeper services? I mean, obviously shows to all the, the different, you know, capabilities. Where, where, where does Amazon stand? What's the process? >>So what, particularly when it comes to the models. So they're going at, at a different angle that, you know, I will help you create the models we talked about the zero and the whole data. We'll get the data sources in, we'll create the model. We'll move the, the whole model. We are talking about the ML ops teams here, right? And they have the whole functionality that, that they built ind over the year. So essentially they want to become the platform that I, when you come in, I'm the only platform you would use from the model training to deployment to inference, to model versioning to management, the old s and that's angle they're trying to take. So it's, it's a one source platform. >>What about this idea of technical debt? Adrian Carro was on yesterday. John, I know you talked to him as well. He said, look, Amazon's Legos, you wanna buy a toy for Christmas, you can go out and buy a toy or do you wanna build a, to, if you buy a toy in a couple years, you could break and what are you gonna do? You're gonna throw it out. But if you, if you, if part of your Lego needs to be extended, you extend it. So, you know, George Gilbert was saying, well, there's a lot of technical debt. Adrian was countering that. Does Amazon have technical debt or is that Lego blocks analogy the right one? >>Well, I talked to him about the debt and one of the things we talked about was what do you optimize for E two APIs or Kubernetes APIs? It depends on what team you're on. If you're on the runtime gene, you're gonna optimize for Kubernetes, but E two is the resources you want to use. So I think the idea of the 15 years of technical debt, I, I don't believe that. I think the APIs are still hardened. The issue that he brings up that I think is relevant is it's an end situation, not an or. You can have the bag of Legos, which is the primitives and build a durable application platform, monitor it, customize it, work with it, build it. It's harder, but the outcome is durability and sustainability. Building a toy, having a toy with those Legos glued together for you, you can get the play with, but it'll break over time. Then you gotta replace it. So there's gonna be a toy business and there's gonna be a Legos business. Make your own. >>So who, who are the toys in ai? >>Well, out of >>The box and who's outta Legos? >>The, so you asking about what what toys Amazon building >>Or, yeah, I mean Amazon clearly is Lego blocks. >>If people gonna have out the box, >>What about Google? What about Microsoft? Are they basically more, more building toys, more solutions? >>So Google is more of, you know, building solutions angle like, you know, I give you an API kind of thing. But, but if it comes to vertical industry solutions, Microsoft is, is is ahead, right? Because they have, they have had years of indu industry experience. I mean there are other smaller cloud are trying to do that too. IBM being an example, but you know, the, now they are starting to go after the specific industry use cases. They think that through, for example, you know the medical one we talked about, right? So they want to build the, the health lake, security health lake that they're trying to build, which will HIPPA and it'll provide all the, the European regulations, the whole line yard, and it'll help you, you know, personalize things as you need as well. For example, you know, if you go for a certain treatment, it could analyze you based on your genome profile saying that, you know, the treatment for this particular person has to be individualized this way, but doing that requires a anomalous power, right? So if you do applications like that, you could bring in a lot of the, whether healthcare, finance or what have you, and then easy for them to use. >>What's the biggest mistake customers make when it comes to machine intelligence, ai, machine learning, >>So many things, right? I could start out with even the, the model. Basically when you build a model, you, you should be able to figure out how long that model is effective. Because as good as creating a model and, and going to the business and doing things the right way, there are people that they leave the model much longer than it's needed. It's hurting your business more than it is, you know, it could be things like that. Or you are, you are not building a responsibly or later things. You are, you are having a bias and you model and are so many issues. I, I don't know if I can pinpoint one, but there are many, many issues. Responsible ai, ethical ai. All >>Right, well, we'll leave it there. You're watching the cube, the leader in high tech coverage here at J three at reinvent. I'm Jeff, Dave Ante. Andy joining us here for the critical analysis and breaking down the commentary. We'll be right back with more coverage after this short break.

>> live from London, England. It's the queue covering a ws summat. London twenty nineteen Brought to you by Amazon Web services >> Hello and welcome to the Age Ws Summit live from London's Excel Center. I'm Susanna Street, and this is my co host on the Cube Day Volonte on. There are lots of breakout sessions taking place right across this venue. One of them all about Bring Thio life, the eight of us marketplace and really helping people, companies and stand cow to make that journey to the cloud. And my two guests here right now have been at that session trying to communicate that toe many delegates who were there here Mobile, who's from Computer Center. He is the public cloud lead for the UK and Ireland, and Garforth, who's a director off a ws marketplace. Thank you very much for joining us >> to be here >> Now there are riel complexities are their way. Just helping people navigate their way through. Tell me that a bit more about how marketplace has evolved because it's being rapid. Hasn't >> it? Has been rapid. We launched a CZ initial service in two thousand twelve, so we just had our seventh birthday last year. We started with pretty modest aspirations, and it was all about helping developers take advantage of the sea to and be able to take advantage of. A bus. Service is available at the time. So it was a cattle about two hundred fifty mostly open source applications that developers could sort of find, explore, discover and provisions straight from the council where they were doing their work. Overtime. We've added support for a lot of new product type, so we support SAS applications. All right, reinvent Last year, we announce support for Dr in being able to take Dr Images and deploy those into stage maker. We're talking about that earlier. Also support for containers. And so his customers are moving to more of a survivalist type architecture. We have already made set of container images that they could deploy directly into the S E. K s or far gate. I'd say one of more interesting sort of inflection point in our evolution was when people started buying real stuff for real money because I think when we got started serving the developers, I kind of think of that is kind of a Lamborghini kind of crowd. That's a customer, by the way, but, uh, Lamborghini guys just, you know, developers want to go as fast as they possibly can. They don't really care for speed limits, you know, they just want to get the job done as quick as they can. Um, we had an example, for example, our first million dollar transaction. Wait, We're surprised to see it. We woke up on Monday and we saw a million dollar transaction. So I told my finance team not to get too excited. I went to the customer and I said, Was this a mistake or did you intend >> to do >> that? And the developer team said No, that was the best software sale ever because I didn't have to talk to anybody. >> I couldn't make money while you sleep isn't absolutely, but they were >> able to. Basically, they didn't have to go through a lengthy process of procurement and legal reviews and everything else. They literally were able to subscribe to the product and get it deployed within seconds, and the estimated that it took about three months off of their engineering cycle was being able to go that fast. But >> the interesting thing on >> million dollar transactions is, there's a lot of other people that care about that. So I got a letter about eight weeks later from their corporate headquarters in New York. It said that Development team was not >> really authorized to spend that much money on that product, >> and so that is what I call the Volvo crowd. And there are big parts of our customer that are very, very interested in safety and airbags and collision avoidance and all that other fun stuff. And so what Marketplace has been really innovating on in the last couple of years is finding a way to modernize how companies buy and deploy softer in the cloud. Do that at speed. But do it in a way that's compliant with whatever regulations governing the things. >> So do it speed but variable speed, >> variable speed and just, you know, a lot of our customers in the public sector or in health care financial services. They're heavily regulated on on their own, and they have a certain way they need to do things. And so we've been building features like the private marketplace which we just launched actually allows the customer to go in and reason over our catalog We've got forty eight hundred listings in our catalog, fourteen hundred different vendors and they can decide on their own. Which one of those air fruit for use or not, >> because it's very hard to meet the procurement demands of various of public sector organization because they're so >> they are very diverse. But that's also one of the reasons, like I'm excited too heavy in here. We've been working for the last couple of years to figure out how we can more effectively work with partners to sort of serve our joint customers. So he and what's your story? How >> do you fit what? It's a good question. So I think Computer Center entered into the fray with eight of us, sort of circa reinvent twenty seventeen. So just a time where Marketplace was launching two partners, I guess in the mainstream on on, we looked at what the offering in partnership with these guys and what it would mean to our customers, and that was kind of very customer letters and organization if you know anything about us. Customers were asking for different ways to potentially by traditional software packages as they moved into the Ws Cloud, and they were moving at scale and that velocity that we talk about and it was about well, is this a product or a mechanism that can help them streamline? Can they simplify on the way? Can they cut some of that complexity on that journey? We see that very much as a Roald. Help them achieve that. This seems like a really good mechanism, so we fast forward through twenty eighteen. We do some great deals together, those sort of way talk about on way. See that this is becoming more mainstream for customers. Is their landing in a ws in the cloud and thinking about different ways? Different software titles challenging Do We Need to Do Things is normal, or should we do things a different way? What about this dynamic that we were just talking about? That garden was just saying about the procurement folk, the >> Volvo crowd versus the Lamborghini Cross You what do you have developed a workflow approval process that it worked? Yeah, well, unpack it a little bit, the the private marketplace allows, and every customer is a little bit different. Sometimes it's the chief security officer who kind of makes the final decision. Sometimes it's procurement. Sometimes the legal team has specific move constraints on what they what. They want to prove that not I really haven't found two customers that are identical in terms of how they're worked over an l O B manager. Correct CFO. I mean, you're right, lots of different roles. So we effectively, we did some surgery on the underlying service to create a new I am role. And so if Ian is the administrator for his organization, regardless of role, he's given permission to go approve and disapprove products. And some customers are kind of in a white list load, which is basically you can use, uh, only the things that I wait listed. So everything's forbidden until I've explicitly approved it. Other companies, like a lot of smaller companies that may not have that much process. We're more of a blacklist mode. We're sort of like everything in the marketplace is fair game, except the ones I've specifically said not to use on DH. So we just created this really flexible infrastructure that lets customers customize the marketplace to their needs. So you give superpowers to some admin and then the white list black blacklist, depending on what it is. And then it becomes frictionless. It becomes frictionless, and then the user experience the customer can actually have their own logo. They can put their own language around, kind of how they wantto sort of represent that to the developers. And then every developer in their organization then sees that experience and they can see what's been approved in what hasn't. OK, so you get a private label through the channel. Yeah, so that I, as a consumer see whatever brand that your customer yet need to see exactly. And then we've also got a facility because, you know, with over forty eight hundred listings in the marketplace, fourteen hundred different vendors, you know, nobody's got time to go reason over every single item, and we're adding hundreds every year, so that keeps growing. And so we've got a facility. If the developer has a specific technology that they really require, we've got a little simple work flow so developed could say, I need this widget to build this thing, and then we kick it off to the admin who could approve it. And as we were talking about for our video closet, you gonna have precise understanding of the pricing. You know this one hundred percent clarity. And then once you have that on you, Khun, split the pie hole, then you can split up and we did. But like one of the foundational technologies that we launched, twenty seventeen was this notion of a private offer. And so if I want to make a private offer to Ian at a price that he and I have negotiated on legal terms that he and I have agreed to, I can do that through marketplace. And then what with the way that would work in a large organization is once somebody's subscribes Once to that price, everybody in the organization that used that product is using it at the agreed price. OK, right. And then we extended that to enable Channel partners now. So for the ice fees that included center works with now, he's now able to go create private offers for his custom. So what, you're essentially created a two sided >> marketplace that effect? Yeah, I think the interface between the two organizations is really important. It becomes that sort of tripartite with the ice V, putting the customer right in the center. I think that's the signage is that we seem to organizations. >> Do you really see what your input has bean there items that are listed as well. Did you get that >> for, like, selection? >> Yeah, yeah, that that like, you know, >> saying it's pretty customer focused, you know, we work with customers we have. We have a set of people around the world that do what we call category management, and they theirjob is to work with customers and make sure that we're stocking the right inventory on the shelves, so to speak. So we get that input like every day, >> and then that helps you develop you new products, >> New continent, new products. And that's >> ahead of the competition. >> Wei. Try to think more about like, let's focus on our customers. Wei don't spend a lot of time chasing tail lights, but very customer obsessed. What things always >> interested me about the marketplaces. It's so complex in terms of region's >> tax laws, pricing considerations on and on and on so many permutations. You talk a little bit about how you've >> succeeded in just essentially making that all transparent and what what's behind that? >> Um well, I think you know Amazon >> and eight of us like we operate within the legal frameworks and all the countries where we operate in. So we have our own requirements in terms of how we remit and collect tax in countries compliant with local laws. Right. So we had to do that just to operate a to B S right way were able to leverage a lot of the same plumbing we had to build for ourselves and effectively make that available to our lives. So we have, like, there's a small eyes. We actually they've grown to be quite big. But here in the UK is a company called Matile Ian, who uses us exclusively a cz, their cloud channel. Um and we take him the HBS available eighteen regions marketplace on, and then everywhere we need to we will remit and collect tax on his behalf and then give him reports that he could share with his auditor to ensure compliance with local laws. And so we do a lot of that stuff. He's a small firm, you know, and for us to be able to sort of, like, extract and abstract all that complexity from him and just give him a nice monthly report that shows him all the taxes we can on his behalf. That's a big service right >> now. How's it transform your business? >> So I say transforming rather than transformed because it's a continuum thing all the time. I think it's absolutely that a different way of procurement is, firstly, the thing that customers are asking for. So it's just one cog in the wheel for a ws that customs picking up on. I think the point that golf is very well glossing over is that between us, we're doing the heavy lifting on behalf of the customer. I think that's today's point thing. That's that's the whole point here, where that we've all got a part to play in the ecosystem and it's it's all about customer experience. That's most important. I think what we're seeing is repeat customers come back. Actually, that's the biggest from if I look up from the start of twenty eighteen to the end, it was the repeat visits, so you get you know, the one million pound or dollar deal customer coming back twice or three times in the year to do the same thing again, >> but have any being put off by this new >> approach, but I haven't seen that so genuine. It hasn't appeared so far, so there's some education. Of course, that has to happen because it's different. It's not the norm. If you think about enterprise customers, they've been buying up a particular mode for twenty or thirty years or longer, a CZ we joke about. So this is just an education process that let them know what on how on then, what's there on the bandwagon? It kind of becomes that streamline process. >> Yeah, ad I'd build on top again. Sport like you kind of think about the way way >> customers thought about procuring infrastructure before eight of us existed, like back in way. But in the way big back of two thousand five, like buying hardware in storage and networking gear was crazy, hard and very difficult and long and laborious. And your racket and stacking everything else. And then a dubious comes along with services like Three and Easy to know what it makes provisioning access, the hard work. It's seconds, you know, not months of procurement, and in a way, we're kind of software is now catching up, and in a way, what marketplace is trying to do is to revolutionize the way people acquire software for the cloud in the same way that eight of us to infrastructure well, and you're creating a to be a consumer dynamic, not unlike my Amazon retail, where there's trust, simplicity, comfort levels on DH. You know, you even don't tell Jeff. I'Ll pay a little bit more from, you know, Amazon website cause I trust it. Yeah, you know, not too much, right? And you guys have to stay price competitive. Absolutely so. But that to me, is that it's that consumer like experience that you're obviously it is more complex but somewhat creating that way looked, we look to retail for all sorts of cool inspiration. You know, on the retail side, they have a retail marketplace, which is huge and thriving business with millions of merchants. And so we're constantly comparing notes and saying, like one of the things that you're doing for your merchants and are the things that can inspire us on our side kind of follow suit. I will note that you know, I when I get in front of customers I like to do, I'd like to show our user experience we have a pretty website and all that other good stuff. The vast majority of customers actually interfaced with us through command line and automation tools and all that other stuff. So retail analogy gets me so developers, >> thank >> you very much for it's really great to have you here, Director A ws marketplace and here mobile. As you say, >> we're in the midst of this transformation. It's really great to hear your story. So thank you very much for two years here >> on the Cube, on the aid everywhere summits in London That's all from us for now.

(upbeat music) >> Narrator: Live, from Las Vegas, it's the CUBE. Covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Welcome back everyone, we are here live in Las Vegas for the CUBE's special coverage of Oracle's ModernCX, Modern Customer Experience, this is the Cube, I'm John Furrier, my cohost Peter Burris. Our next guest is Tony Nadalin. Tony Nadalin is the global vice president of the Global Consulting at Oracle for the marketing cloud. Welcome to the CUBE. >> Well, thank you. Thank you for having me. >> So you've got to implement this stuff, and we've heard a lot of AI magic and there's a lot of meat on the bone there. People are talking about there's a lot of real things happening. Certainly, Oracle's acquired some great technologies over the years, integrated it all together. The proof is in the pudding. When you roll it out, the results have to speak for themselves. >> Tony: Yes, absolutely. >> So share with us some of those activities. What's the score board look like? What's the results? >> I think what's really important, and Lewis spoke about this yesterday, it's people and product. The customers are buying visions. They're looking at creating and changing the customer experience. They're not just buying a piece of technology. They're buying a transformation. I think what's really important and what we do a lot in services, in all services, not just Oracle Marketing Cloud Services, but just healthy services, is when customers are implementing, they're not just implementing technology, they're not just plumbing the pipes. They are putting in changes. They're looking at the people, the process, the technology. We have a really good relationship with our customers and our partners and we're constantly looking at the complete set of services, the complete suite. From what I call transformational services, where we come in and try to understand what are you trying to change? How are you trying to change your customer experience? As a marketer, owning not only what you do, and how all the different channels are working together across all the different products that they are. They purchase Eloqua, Responsys, BlueKai, Maxymiser, et cetera. >> So you're laying it all out, it's like you're sitting in a room, now I'm oversimplifying it, but it's not just rolling out stuff. You've got planning. >> Tony: You've got to plan it. >> Put the pieces together. >> You do, and it's a readiness. It's a readiness of the organization, you think about it, you've got within a marketing organization, you've got many teams coming together that have to be united around the brand, the consistency, how they're engaging with customers. But also, not only across like an acquisition team, or loyalty or an upsell and cross sell team, how does that, as we were looking at the products key notes, how does that then extend into the services engagement? How does it extend into the sales engagement? How are we making sure that everyone is using the same messaging, the same branding, leveraging each other? It's a real transformation at a people, process and technology level. So that when you're then implementing, you're implementing changes. And so we've got some great services and great partners that make sure that when the customers are going through that transformation, they're sort of going it fully readied. And our role, from a services perspective, is to ensure then, sort of define the transformation, define the strategy, like plan the plan, and then go execute the plan. And then putting in the plumbing, getting everyone readied. The analogy I used, I'm sure you've got kids, right? When we have toddlers, and you build the kid's first bikes. Your goal is to build that bike, put the training wheels on the bike, and ultimately sort of stand behind your child to a point that when you let them go, they're not going to graze their knees. Then from an ongoing basis, continue to stand behind them, then get ready to take the training wheels off. Then training wheels come off. Maybe at one point they may become BMX champions, right? But you're sort of behind them through the whole-- >> John: There's progression. >> Progression, exactly. >> With my kids, it's simply man to man, then zone defense. (laughter) >> But it's progression, right? A lot of customers, we have not only the onboarding and implementation services, but these ongoing services that are so key. Because obviously it's important to ensure that your customers are realizing. When I think of our services and the journey, there's the discovery, the transformation, and the strategy. That's like the discovery. But you've then got the realization. And then the optimization and the realization to me is that you're realizing that initial step. You're realizing the technology and you're realizing people and process. You're getting people stood up. Skills, people, organizations, technology, data. You're realizing it all so they can then take the next step. >> Alright, so what's the playbook? A lot of times, in my mind's eye, I can envision in a white board room, board room, laying it all out, putting the puzzle pieces together, and then rolling out implementation plan. But the world is going agile, not waterfall anymore, so it's a combination of battle mode, but also architectural thinking. So not just fashion, real architectural, foundational. >> Peter: Design thinking. >> Tony: Exactly, architectural. >> John: Design thinking. What's the playbook? What's the current state of the art in the current-- >> Well we have obviously product consultants, architects, solution consultants, content creators. It's the whole spectrum of where the customer needs to focus on. And I think-- >> John: So you assemble them based upon the engagement. >> Based upon the engagement and understanding, like what are the customer's strengths? Where are they now? Where are they trying to get to? There's some customers, you know, we have a whole range of services, and we have a whole range of customers. So there are some customers who are like, "We have our own teams today, "we want to augment our teams with your teams, "we want to have hybrid models." Or, "We have our own teams today, but not only have you got great people, but you've got great processes." So like, look at Maxymiser as an example. A lot of our Maxymiser customers, not only use our platform, but they use our people. They're not just buying our people, they're buying a sort of agile, Kanban, JavaScript development practices that are a different level of software development. It's not just the people that can code, it's the development practices. So it's that whole operational services where we bring to the table just a different degree of operational excellence. But we're also to go in to our customers that have their own teams and provide them also consulting perspective around how they can also sharpen their edge. If they want to sort of keep, you know. So whole spectrum of services. >> So let me see if I can throw something out there, in kind of like the center, the central thesis of what you do and how it's changed from what we used to do. Especially a company like Oracle, which has been a technology company at the vanguard of a lot of things. It used to be that customers had an idea of what they wanted to implement. They wanted to implement an accounting system. The processes are relatively known. What was unknown was the technology. How do, what do I buy? How do I configure? How do I set it up? How do I train? How do I make the software run? How do I fix? So it was known process, unknown technology. As a consequence, technology companies could largely say, yeah, that value is intrinsic to the product. So you buy the product, you've got it now. But as we move more towards a service world, as we move more toward engaging the customer world where the process is unknown, and the technology, like the cloud, becomes increasingly known. Now we're focused on more of an unknown process, known technology, and the value is in, does the customer actually use it. >> I think the value is actually in does the customer get value. I think there's a, I've managed customer success organizations and customer service organizations, and the one thing I see in SAS, is usage doesn't always equate to value. So I think as a services organization, it's important to understand the roadmap to value. Because a lot of times, I would say in commodity software, sort of the use of it by default in itself was enough. That you were moving to a software platform. I think SAS customers, especially marketers, are looking for transformation. They're looking for a transformation and a change in value. A change in value in the conversation they're having with the customer. A change in acquisition, loyalty, retention, a change in being relevant. As Joseph was saying this morning, being relevant with the customer, and that value is more than just implementing some technology. >> So it's focusing on ensuring that the customer is getting value utility out of whatever they purchase. >> Tony: Correct. >> Not just that they got what they purchased. So as we move into a world where we're embedding technology more and more complex, it's two things happen. One is, you have to become more familiar of the actual utilization. And what does it mean, and I think marketing cog helps that. What is marketing, how does it work? And second one, the historical norm has been, yeah, we're going to spend months and years building something, deploying something, but now we're trying to do it faster, and we can. So how is your organization starting to evolve its metrics? Is it focused on speed? Is it focused on, obviously value delivered, utilization. What are some of the things that you are guiding your people to focus on? >> Well I think, I very much take a outside-in view. So to me, if I look at why a customer is buying, and what do they want. Obviously most customers want fast time to value, as reduced effort, obviously, and little surprises. I think having a plan and being able to execute your plan. And this whole, as we were talking like one-to-many versus one-to-one. >> And timing too, no surprises and they want to execute. >> And time to value, right? And speed. And I think as we were talking, similar to as a marketer is trying to engage any customer and sort of going from that one-to-many to that one-to-you, what's important now for any organization, a services organization, any company, is to understand what does your business look like? Because why you bought from Oracle, whether you be in a certain vertical or a certain space, or a certain maturity as a customer, it's important that we have the play books, and we do, that say that if you're a customer of this size, of these products in this vertical, then we have the blueprints for success. They may not be absolutely perfect, but they're directional, that we can sort of put you on the fast path. That we've seen the potholes before, we've seen the bumps, we understand the nuances of your data, your systems, your people, your regulations. So that we can actually, we have a plan. And it's a plan that's relevant to you. It's not a generic plan. And I think that's the biggest thing where good companies show up then deliver solutions that they're not learning 100%. There's always going to be nuances and areas of gray that you work through, where the customer's just as much as vendors as they transform. We're not just swapping like for like, but when you transform, there's changes that occur on the customer side. There's new awarenesses of I didn't realize we did that. I didn't realize I want to change doing that. And I've actually changed maybe my whole thought. >> What's the change coming from this event? If you look at the show here, ModernCX, some really good directional positioning. The trajectory of where this is going, I believe is on a great path. Certainly directionally relevant, 100%. Some stuff will maybe shift in the marketplace. But for the most part, I'm really happy to see Oracle go down this road. But there's an impact factor to the customers, and the communities, and that's going to come to you, right? So what are you taking away from the show that's important for customers to understand as Oracle brings in adaptive intelligence? As more tightly coupled, highly cohesive elements come together? >> I think to me, it's transformation. Customers really do understand what are they trying to achieve as they transform? Not just by a piece of technology, but come into it understanding, okay, what are we trying to transform? And have we got like all change management? All transformational management? Have I got the right buy-in across the organization? As a marketer, if I'm trying to transform the organization, have I got the right stakeholders in the room with me? Am I trying to influence the right conversations? You look at the conversation yesterday with Netflix. The discussion, or Time-Warner, sorry. Around their transformation around data. That wasn't a single entity determining that. That was a company driven strategy. A company driven transformation. And I think to really change the customer experience, and control the brand of that across all touchpoints of the company, it requires transformation and it requires being realistic around also how long that journey takes. Depending on the complexity and size of the company. It requires investment of people, of energy, or resources and really understanding where is your customer today? Where is your competition? And to Mark's point, it's like the market is being won here, you're having to compete against your competition, you're having to be better than them, you're having to understand your competition just as much as you understand yourself, so you're leapfrogging. Because just as much as you're going after your competitors customers, your customers are coming up for your customers, right, your competitors are coming up for your customers. I think transformation and understanding how to engage the right services leaders, be it Oracle or any of our partners, to really transform your business is to me the biggest take away. The technology then, be it Chatbox or AI, I mean they augment, they help, they're going to be channels, but I think transformation is key. >> It's really not the technology, it's really what you're doing it with, at the end of the day. Tony, thanks for coming on the CUBE. We really appreciate it, and again, when the rubber hits the road, as Peter was saying earlier, it's going to be what happens with the product technologies for the outcomes. >> Tony: Absolutely. >> Thanks for sharing your insights here on the CUBE. Sharing the data, bringing it to you. I'm John Furrier with the CUBE with Peter Burris, more live coverage for the Mandalay Bay in Las Vegas from Oracle's ModernCX after this short break. (upbeat music) >> Narrator: Robert Herjavec >> Interviewer: People obviously know you from Shark Tank. But the Herjavec Group has been really laser focused on cyber security.