>>Okay, We're back at AWS Re. Invent. You're watching the >>cubes. Continuous coverage >>coverage. This is Day four. I think it's the first time it reinvent. We've done four days. This is our ninth year covering Reinvent. Tom Miller is here is the senior vice president of Alliances. And he's joined by Anchor Jane. Who's the global cloud? Practically practise lead at Merkel. Guys, good to see you. Thanks for coming on. Thank you, Tom. Tell us about Merkel. For those who might not be familiar with you. >>So Merkel is a customer experience management company. That is, um, under the Dentsu umbrella. Dense. Who is a global media agency? We represent one of the pillars which is global, our customer experience management. And they also have media and creative. And what Merkel does is provide that technology to help bring that creative and media together. They're a tech company. Yes. >>Okay, so there's some big big tail winds, changes, trends going on in the market. Obviously the pandemic. You know, the force marched to digital. Uh, there's regulation. What are some of the big waves that you guys are seeing that you're trying to ride? >>So what we're seeing is, uh we've got, uh, as a start. We've got a lot of existing databases with clients that are on Prem that we manage today within a sequel environment or so forth. And they need to move that to a cloud environment to be more flexible, more agile, provide them with more data to be able to follow that customer experience that they want with their clients, that they're all realising they need to be in a digital environment. And so that's a big push for us working with AWS and helping move our clients into that cloud environments. >>And you're relatively new to the ws world, right? Maybe you can talk >>about that anchor actually, as a partner. We may be new, but Merkel works with AWS has been working with AWS for over five years as a customer as a customer. So what we did was last year we formalise the relationship with us to be, uh, an advanced partner now. So we were part of the restock programme, basically which is a pool of very select partners. And Merkel comes in with the specialisation of marketing. So as Tom said, you know, we're part of, uh Dentsu umbrella are our core focuses on customer experience, transformation and how we do that Customer experience. Transformation is through digital transformation, data transformation. And that's where we see AWS being a very good partner to us to modernise the solutions that Martin can take to the market. >>So your on Prem databases is probably a lot of diversity on a lot of technical that when the cloud more agility, infinite resources do you have a tech stack? Are you more of an integrator? Right tool for the right job? Maybe you could describe >>your I can take that what time just described. So let me give you some perspective on what these databases are. These databases are essentially Markle, helping big brands 1400 Fortune 500 brands to organise their marketing ecosystem, especially Martek ecosystem. So these databases, they house customer touchpoints customer customer data from disparate sources, and they basically integrate that data in one central place and then bolt on analytics, data science, artificial intelligence, machine learning on top of it, helping them with those email campaigns or direct mail campaigns, social campaigns. So that's what these databases are all about, and and these databases currently set on Prem on Merkel's own data centre. And we have a huge opportunity to kind of take those databases and modernise them. Give all these ai ml type of capabilities advanced analytic capabilities to our customers by using AWS is the platform to kind of migrate. And you do that as a service. We do that as a service. >>Strategically, you're sort of transforming your business to help your customers transform their business right? Take away. It's it's classic. I mean, you really it's happening. This theme of, you know a W started with taking away the undifferentiated heavy lifting for infrastructure. Now you're seeing NASDAQ. Goldman Sachs. You guys in the media world essentially building your own clouds, right? That's the strategy. Yes, super clouds. We call >>them Super Cloud. Yeah, it's about helping our clients understand What is it they're trying to accomplish? And for the most part, they're trying to understand the customer journey where the customer is, how they're driving that experience with them and understanding that experience through the journey and doing that in the cloud makes it tremendously easier and more economical form. >>I was listening to the, uh, snowflake earnings call from last night and they were talking about, you know, a couple of big verticals, one being media and all. I keep talking about direct direct to consumer, right? You're hearing that a lot of media companies want to interact and build community directly. They don't want to necessarily. I mean, you don't want to go through a third party anymore if you don't have to, Technology is enabling that is that kind of the play here? >>Yes, Director Consumer is a huge player. Companies which were traditionally brick and mortar based or relied on a supply chain of dealers and distributors are now basically transforming themselves to be direct to consumer. They want to sell directly to the consumer. Personalisation comes becomes a big theme, especially indeed to see type of environment, because now those customers are expecting brands to know what's there like. What's their dislike? Which products which services are they interested in? So that's that's all kind of advanced analytics machine learning powered solutions. These are big data problems that all these brands are kind of trying to solve. That's where Merkel is partnering with AWS to bring all those technologies and and build those next generation solutions for access. So what kind >>of initiatives are you working >>on? So there are, like, 34 areas that we are working very closely with AWS number one. I would say Think about our marketers friend, you know, and they have a transformation like direct to consumer on the channel e commerce, these types of capabilities in mind. But they don't know where to start. What tools? What technologies will be part of that ecosystem. That's where Merkel provides consulting services to to give them a road map, give them recommendations on how to structure these big, large strategic initiatives. That's number one we are doing in partnership with AWS to reach out to our joint customers and help them transform those ecosystems. Number two as Tom mentioned migrations, helping chief data officers, chief technology officers, chief marketing officers modernise their environment by migrating them to cloud number three. Merkel has a solution called mercury, which is essentially all about customer identity. How do we identify a customer across multiple channels? We are Modernising all that solution of making that available on AWS marketplace for customers to actually easily use that solution. And number four, I would say, is helping them set up data foundation. That's through intelligent marketing Data Lake leveraging AWS technologies like blue, red shift and and actually modernise their data platforms. And number four is more around clean rooms, which is bring on your first party data. Join it with Amazon data to see how those customers are behaving when they are making a purchase on amazon dot com, which gives insights to these brands to reshape their marketing strategy to those customers. So those are like four or five focus areas. So I was >>gonna ask you about the data and the data strategy like, who owns the data? You're kind of alchemists that your clients have first party data and you might recommend bringing in other data sources. And you're sort of creating this new cocktail. Who owns the data? >>Well, ultimately, client also data because that that's their customers' data. Uh, to your point on, we helped them enrich that data by bringing in third party data, which is what we call is. So Merkel has a service called data source, which is essentially a collection of data that we acquire about customers. Their likes, their dislikes, their buying power, their interests so we monetise all that data. And the idea is to take those data assets and make them available on AWS data exchange so that it becomes very easy for brands to use their first party data. Take this third party data from Merkel and then, uh, segment their customers much more intelligently. >>And the CMO is your sort of ideal customer profile. >>Yeah, CMO is our main customer profile and we'll work with the chief data officer Will work with the chief technology officer. We kind of we bridge both sides. We can go technology and marketing and bring them both together. So you have a CMO who's trying to solve for some type of issue. And you have a chief technology officer who wants to improve their infrastructure. And we know how to bring them together into a conversation and help both parties get both get what they want. >>And I suppose the chief digital officer fits in there too. Yeah, he fits in their CDOs. Chief Digital officer CMO. Sometimes they're all they're one and the same. Other times they're mixed. I've seen see IOS and and CDOs together. Sure, you sort of. It's all data. It's all >>day. >>Yeah, some of the roles that come into play, as as Tom mentioned. And you mentioned C I o c T. O s chief information officer, chief technology officer, chief data officer, more from the side. And then we have the CMOS chief digital officers from the marketing side. So the secret sauce that Merkel brings to the table is that we know the language, what I t speaks and what business speaks. So when we talk about the business initiatives like direct to consumer Omni Channel E commerce, those are more business driven initiatives. That's where Merkel comes in to kind of help them with our expertise over the last 30 years on on how to run these strategic initiatives. And then at the same time, how do we translate translate those strategic initiatives into it transformation because it does require a lot of idea transformation to happen underneath. That's where AWS also helps us. So we kind of span across both sides of the horizon. >>So you got data. You've got tools, you've got software. You've got expertise that now you're making that available as a as a service. That's right. How far are you into that? journey of satisfying your business. >>Well, the cloud journey started almost, I would say, 5 to 7 years ago at Merkel, >>where you started, where you began leveraging the cloud. That's right. And then the light bulb went off >>the cloud again. We use clouds in multiple aspects, from general computing perspective, leveraging fully managed services that AWS offers. So that's one aspect, which is to bring in data from disparate sources, house it, analyse it and and derive intelligence. The second piece on the cloud side is, uh, SAS, offering software as a service offerings like Adobe Salesforce and other CDP platforms. So Merkel covers a huge spectrum. When it comes to cloud and you got >>a combination, you have a consulting business and also >>so Merkel has multiple service lines. Consulting business is one of them where we can help them on how to approach these transformational initiatives and give them blueprints and roadmaps and strategy. Then we can also help them understand what the customer strategy should be, so that they can market very intelligently to their end customers. Then we have a technology business, which is all about leveraging cloud and advanced analytics. Then we have data business that data assets that I was talking about, that we monetise. We have promotions and loyalty. We have media, so we recover multiple services portfolio. >>How do you mentioned analytics a couple times? How do you tie that? Back to the to the to the sales function. I would imagine your your clients are increasingly asking for analytics so they can manage their dashboards and and make sure they're above the line. How is that evolving? Yes, >>So that's a very important line because, you know, data is data, right? You bring in the data, but what you do with the data, how you know, how you ask questions and how you derive intelligence from it? Because that's the actionable part. So a few areas I'll give you one or two examples on how those analytics kind of come into picture. Let's imagine a brand which is trying to sell a particular product or a particular service to the to a set of customers Now who those set of customers are, You know where they should target this, who their target customers are, what the demographics are that's all done through and analytics and what I gave you is a very simple example. There are so many advanced examples, you know, that come into artificial intelligence machine learning those type of aspects as well. So analytics definitely play a huge role on how these brands need to sell and personalised the offerings that they're going to offer to. The customers >>used to be really pure art, right? It's really >>not anymore. It's all data driven. Moneyball. Moneyball? >>Yes, exactly. Exactly. Maybe still a little bit of hard in there, right? It doesn't hurt. It doesn't hurt to have a little creative flair still, but you've got to go with the data. >>That's where the expertise comes in, right? That's where the experience comes in and how you take that science and combine it with the art to present it to the end customer. That's exactly you know. It's a combination, >>and we also take the time to educate our clients on how we're doing it. So it's not done in a black box, so they can learn and grow themselves where they may end up developing their own group to handle it, as opposed to outsourcing with Merkel, >>teach them how to fish. Last question. Where do you see this in 2 to 3 years. Where do you want to take it? >>I think future is Cloud AWS being the market leader. I think aws has a huge role to play. Um, we are very excited to be partners with AWS. I think it's a match made in heaven. AWS cells in, uh, majority of the sales happen in our focus is marketing. I think if we can bring both the worlds together, I think that would be a very powerful story for us to be >>good news for AWS. They little your DNA can rub off on them would be good, guys. Thanks so much for coming to the Cube. Thank you. All right. Thank you for watching everybody. This is Dave Volonte for the Cube Day four aws re invent. Were the Cube the global leader in high tech coverage? Right back. Mhm. Mhm. Mhm.

if Studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cute conversation hey welcome everybody Jeff Rick here with the cube we're in our Palo Alto studios today it's been a crazy couple of weeks but things seem to have settled and one of the results of what's happening is everyone now is sheltering at home working from home so we wanted to take a few minutes to talk about some of the best practices that we've seen when you are joining a video from home if we've got you scheduled for a cube interview in the next several months we'll probably be doing it remotely with you dialing and from your laptop I'm sure you're doing lots of zoom meetings and Skype meetings and WebEx meetings and all the other meetings so we wanted to go through really a couple key things to help you have a better quality video experience and there's really six things that we're gonna cover today number one you got to get a hard line bandwidth this super super important there's some other things we'll talk about in terms of firewalls etc number two camera position really really important it goes a long way and really improving the experience for you but also the people on the other side of the of the conversation number three will go into audio and really best practices on audio Audio is super important for background something that's often forgot about but really can make a big difference in what's going on five or talked a little bit about lighting and six clothing which is you know kind of at the end of the list in a situation like today one on bandwidth a hard line makes a huge difference go out get yourself a dongle if you don't have a dongle my favorite brand is anchor but when you have a consistent hard line it's going to make everything work a lot better at the same time you also want to plug your computer and plug the laptop in there's all kinds of battery saving functions and power functions that are disabled when you're running on battery power so plug it in talk about camera position really it's all about having the camera at eye level so that when you're looking at your laptop it looks like you're looking at the people you need to look into the camera that really helps experience from term in terms of you know not looking down or having the camera look up your nose which is not only an unflattering position but it's just not a good look the third thing we'll talk about is audio whether you have ear pods if you're a Apple person if you're a gamer and you've got a hard line with headset and a microphone this is not a place to skimp it you can use the microphone in your laptop but it's better if you have a standalone microphone third thing is background we'll wait till we get into the other room to show that and then lighting and clothing so with that let's get off this beautiful welded studio and go to an actual situation okay so the first thing we see all the time is people have their laptop on the table usually the tops tip back a little bit it's kind of an up to no shot not very flattering nobody wants to see that shot so a really simple way to get the camera eye level the same as your regular eyes are these handy-dandy things called books so what we'll do is we'll take a stack of books we'll slip it under the laptop and what that will enable me to do is get a really good shot and now I can look at the the laptop I can pay attention to the presentation and also look into the camera it's really close together and it's a much better experience okay the next thing that we wanted to talk about really is the audio so you can use the audio on the laptop it's usually not that great there's a lot of echo in the room potentially and there might be a little bit of a lag so we strongly recommend that you either go with Apple earbuds if that's what your thing is or you get a gamer headset you want one that has both the microphone and the over ear the next thing is what's going on in the background a couple things you really want to watch out for number one top secret whiteboards you want your whiteboard in the background make sure your background is clear of that type of material but more importantly is really the lighting what you want to do is make it easy for your camera light and the way you make it easy for your camera light is to have a minimum amount of super darks and super lights so one of the things we see all the time with really bright backgrounds is windows so if I swing my set up here and if I was to sit with my back to the window you can see much harder challenge for the camera it's really not a good look so if you have a window in your home office make sure you pull the curtains put some shade it's really tough for the camera now by simply switching either 90 degrees to the position where I was before or even 180 which is even better now I have the benefit of the light from the window coming through and not as a backdrop much better look much better look adjust the Headroom and here we are so the next thing I want to talk about is lighting and lighting is really really important so if you can have natural light coming in turn on all the lights in your room but you still might want a spotlight for the front of your face I'm a big fan of what's called a loom cube full disclosure I don't get paid by them and they've been paid by them I bought this myself but I like the Loom cube because it's really small it's really simple it's rechargeable and mainly because it's got a six-step give me a 10-step bright brightness function and I can get diffusers and filters and all this other fun stuff so what I could do is put this slightly off to the side I already had pretty good light coming in from the window and I can add a little fill with the limb cube you can see as I step that up it gets brighter and brighter try to position it so we don't have any any clear off the glasses but you can see that somebody's fill these things are not that expensive whether you get a loom cube or some other cube go get a little light it makes a huge difference some of them attach to laptops this one I have on we're called the Joby legs which are kind of fun little legs you can stick on any camera so get a light again this is not only for the cube interview that we look forward to having with you but it's also for all of your other online meetings your zooms your WebEx the last thing I want to talk about really is clothing these this clothes is actually a little bit dark I got the dark blue and black underneath again what you want to do is make it easy on the camera so you want to avoid tight patterns you want to avoid tight stripes you want to avoid green and try to have something that's pretty easy for the camera to deal with this not too bright not too dark it's something that that is really easy for the camera to pick up so hopefully you've enjoyed some of these tips hopefully this will help you be more productive in your in your zoom calls and your cube interviews and your skypes and webex's etc we look forward to catching up everybody hang in there this too will pass we'll get through these tough days and just help help help out your friends help everybody out great to see you we'll see you next time thanks for checking in [Music]

if Studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cute conversation hey welcome everybody Jeff Rick here with the cube we're in our Palo Alto studios today it's been a crazy couple of weeks but things seem to have settled and one of the results of what's happening is everyone now is sheltering at home working from home so we wanted to take a few minutes to talk about some of the best practices that we've seen when you are joining a video from home if we've got you scheduled for a cube interview in the next several months we'll probably be doing it remotely with you dialing and from your laptop I'm sure you're doing lots of zoom meetings and Skype meetings and WebEx meetings and all the other meetings so we wanted to go through really a couple key things to help you have a better quality video experience and there's really six things that we're gonna cover today number one you got to get a hard line bandwidth this super super important there's some other things we'll talk about in terms of firewalls etc number two camera position really really important it goes a long way and really improving the experience for you but also the people on the other side of the of the conversation number three will go into audio and really best practices on audio Audio is super important for background something that's often forgot about but really can make a big difference in what's going on five or talked a little bit about lighting and six clothing which is you know kind of at the end of the list in a situation like today but those are the things we want to talk about so Before we jump into it I just want to cover a few basic things and then we'll get into more detail one on bandwidth a hard line makes a huge difference go out get yourself a dongle if you don't have a dongle their way expensive my favorite brand is anchor but when you have a consistent hard line it's gonna make everything work a lot better at the same time you also want to plug your computer and plug the laptop in there's all kinds of battery saving functions and power functions that are disabled when you're running on battery power so plug it in second thing we'll talk about camera position really it's all about having the camera at eye level so that when you're looking at your laptop it looks like you're looking at the people you need to look into the camera that really helps experience from term in terms of you know not looking down or having the camera look up your nose with is not only an unflattering position but just not a good look the third thing we'll talk about is audio whether you have air pods if your Apple person or if you're a gamer and you've got a hard line with headset and a microphone this is not a place to skimp it you can use the microphone in your laptop but it's better if you have a standalone microphone third thing is background we'll wait till we get into the other room to show that and then lighting and clothing so with that let's get off this beautiful welded studio and go to an actual situation okay so the first thing we see all the time is people have their laptop on the table usually the tops tip back a little bit it's kind of an up to know shot not very flattering nobody wants to see that shot so a really simple way to get the camera eye level the same as your regular eyes are these handy-dandy things called books so what we'll do is we'll take a stack of books we'll slip it under the laptop and what that will enable me to do is get a really good shot and now I can look at the the laptop I can pay attention to the presentation and also look into the camera it's really close together and it's a much better experience so step 1 get your eyes in line with your camera ok the next thing that we wanted to talk about really is the audio so you can use the audio on the laptop it's usually not that great there's a lot of echo in the room potentially and there might be a little bit of a lag so we strongly recommend that you either go with Apple earbuds if that's what your thing is or you get a gamer headset you want one that has both the microphone and the over ear which seems a little extreme again you can go with the iPod but this is going to give you much better sound so people can hear what you're listening to now that you've got your audio set you've got your you can listen in you've got your mic at the right or excuse me your camera at the right level the next thing is what's going on in the background a couple things you really want to watch out for number one top secret whiteboards you don't want your whiteboard in the background make sure your background is clear of that type of material but more importantly is really the lighting what you want to do is make it easy for your camera light and the way you make it easy for your camera light is to have a minimum amount of super darks and super lights so one of the things we see all the time with really bright backgrounds is windows so if I swing my set up here and if I was to sit with my back to the window you can see much harder challenge for the camera it's really not a good look so if you have a window in your home office make sure you pull the curtains put some shades it's really tough for the camera now by simply switching either 90 degrees to the position where I was before 90 degrees does position where I was before or even 180 which is even better now I have the benefit of the light from the window coming through and not as a backdrop much better look much better look adjust the Headroom and here we are so the next thing I want to talk about is lighting and lighting is really really important so if you can have natural light coming in turn on all the lights in your room but you still might want a spotlight for the front of your face I'm a big fan of what's called a loom cube full disclosure I don't get paid by them I've never been paid by them I bought this myself but I like the loom cube because it's really small it's really simple it's rechargeable and mainly because it's got a six-step or give me a 10-step bright brightness function and I can get diffusers and filters and all this other fun stuff so what I could do is put this slightly off to the side I already have pretty good light coming in from the window and I can add a little fill with the link cube you can see as I step that up it gets brighter and brighter try to position it so we don't have any any clear off the glasses but you can see that somebody's fill these things are not that expensive whether you get a loom cube or some other cube go get a little light it makes a huge difference some of them attach to laptops this one I have on we're called the Joby legs which are kind of fun little legs you can stick on any camera so get a light again this is not only for the cube interview that we look forward to having with you but it's also for all of your other online meetings your zooms your WebEx the last thing I want to talk about really is clothing these this clothes is actually a little bit dark I've got the dark blue and black underneath again what you want to do is make it easy on the camera so you want to avoid tight patterns you want to avoid tight stripes you want to avoid green and try to have something that's pretty easy for the camera to deal with this not too bright not too dark it's something that that is really easy for the camera to pick up so hopefully you've enjoyed some of these tips hopefully this will help you be more productive in your in your zoom calls and your cube interviews and your skypes and your WebEx is etc we look forward to catching up everybody hang in there this too will pass we'll get through these tough days and just help help help out your friends help everybody out great to see you we'll see you next time thanks for checking in [Music]

>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back everyone. Live cube covers here at reinvent 2019 in Las Vegas. I'm John, your host extracting the signal from the noise with Stu Miniman analysts at Silicon angle, the cube and Wiki bond. We've got two great guests talking about the ecosystem and the future of software and how customers are consuming it in the cloud. Todd Osborne G VP of alliances and channels at new Relic and Josh Hoffman, GM and global lead of ISB partner ecosystem of AWS. Guys, welcome to the cube. Thanks so much for having us. So guys, we're the top story to me at this show. So far as I'll see infrastructure at scale. The software development life cycle is continuing to evolve. We are more automation, more as Andy says, heavy lifting's being done, which means that application developers are going to get more and more goodness. Dev ops created infrastructure as code check. Now we've got data, tons of data everywhere. So we're, we're seeing an ISB Renaissance more software. You guys are out there writing software. So what you guys take so far of the impact of the ISV here, Josh, to talk about that because this is a big story, does >>massive, I mean if you walk around the floor, you'll see folks that are automating new ways of doing dev ops. You're looking at new ways of securing serverless functions. Um, you're looking at new types of storage. So you could go across every category of technology in this room and you will see an incredible amount of batim innovation. Our partners are really driving that. >>Talk about the relationship with AWS, new Relic, longstanding partnership. Where is it now? Where's it going? It's, I mean, it's off the charts. So even just the last year, the amount of momentum we've built together as has been fantastic. So we participated in a whole bunch of different programs. We've got dozens, hundreds of joint customers that were doing things together. I mean, just look at this event. It's just a, it's just astonishing. We operate in a lot of different partner models, um, from, from reselling, uh, with, with various partners to building technology programs to participating, uh, with Josh and team and our friends. Uh, our friend Dave McCann and team on a eight of us marketplace. Just a whole host of different things that just continue to, to, uh, expand the partnership at scale. And the consumer is ation of the software, the procurement process she's had Teresa crossing off from public sector, whether you're in the public sector or commercial procurement still stuck in 1995 it feels like, right? >>I mean, like, are they modernizing? They've got a lot more ways to get software with the marketplace. What are you guys seeing with customers? Is it really that bad? Am I over over it? It's not that bad, but you know what I'm saying? I mean, so from my perspective, one of the cool we're seeing is, um, AWS in the cloud. Providers are driving a consolidation of budget of modern stuff, of cloud, of, of all the new things that companies want to do. That's all getting consolidated either in a new groups or new budget cycles and AWS is making it really easy to participate in those. So through programs like the marketplace, through various other other initiatives that we're doing, we can combine what we want to achieve with, with what the customer wants to achieve, which is speed to market with, which is with what AWS wants to achieve, which is faster adoption of all the different services and bringing the right ecosystem along with it. >>So the modernization of the procurement cycles along with the monetization of the technology is really cool to watch. Well, I wanted to ask that before. I want to get to the question that I'm that interested Andy Jassy his point on this keynote, Hey, this is the first time I heard him talk like this. We see two types of developers and two types of customers. People want the low level building blocks, the builders and then a new set of customers who want solutions. Yup. This is, this is your wheelhouse. This is where the solution network kind of ecosystem is evolving very quickly. Can you guys share your observations on what that, what he means by that and what does it mean for customers? >>I'll share it in the context of what we're doing with new Relic. Um, when you think of the concept of a solution, a lot of our customers, hundreds of our enterprise customers are going through our migration programs. They need help making sure that what they're doing on prem is translating to what's happening in the cloud, what the applications are doing on prem, and how they're performing in the cloud. So we've collaborated with NewRelic over the last year and a half on a number of new, not just migration programs, but windows or views into how the applications are performing. And we've designed those specifically for customers who are going through those migrations. So you just take that one little category. Um, and it's an area where we're collaborating together to bring something that is a full solution to the customer for those who are going through that migration journey. >>Your take on the whole solution thing. Yeah. So we, uh, last year at reinvent, we announced really the first solution that new Relic had ever launched trying to meet that market need and we, we announced the cloud adoption solution. So everybody knows we've got this great platform with all these cool features. We had never really gone to market and said, not only do we just address application monitoring or infrastructure mining, we actually address the business outcome of migrating to the cloud and all the benefits of doing that. So we announced that as a methodology last year. We added to that over this, this past year because we've enhanced our platform to, uh, have this new capability that we call programmability, which is the ability to write applications on top of the new Relic platform. So we've built, and we launched today a cloud adoption solution application. Kind of a mouthful. >>But what it is, is it is, it's the ability to use our technology and our platform to very easily drop that into a customer and help them very quickly get time to value of delivering on a solution and ultimately achieving the business outcome they're looking for. Yeah, I taught actually. So as you know, I was at your conference earlier this year in New York city where you really defined what a platform should be. And just like Amazon, what you want is you want builders and you want them putting solutions on Dabo. It gives a little bit of the momentum of what you've seen since new Relic one, and then the rollouts. So I don't know the formal count, but I know we're way past the dozen applications that we launched since then. Uh, we also added several different features including logging and some other technologies. We've closed a bunch of different deals with these new technologies since then. >>Um, and then a couple of the cool things from the partner ecosystem that we've done is with the platform capabilities we have, uh, firstly we're now, uh, getting ready to embark on building our first technology partner program. So we were talking to dozens of different partners in this room about how they can build with us on new Relic to make the platform even stickier, uh, for our customers that can now integrate NewRelic with various other technologies. And then the second, uh, thing we were proud to announce today is we've, we've actually just signed a three new managed service providers. So kind of another partner motion that we're driving in this ecosystem. And the new, all the new features of the neurotic platform helped enable us, uh, to do some really cool things with the platform and also evolving business model, uh, to close. Uh, so we were excited to to close three, top 80 best partners, which is best been global, uh, uh, blaze clan and out of California mission cloud as three new partners that we, uh, just, uh, signed agreements with. >>So we're happy to do that. Yeah. When we talk about the transformation, you know, one of the biggest challenges for customers is their application portfolio. I noticed new Relic has two boosts here. There's one specifically just focused on serverless, which I think is awesome. It's got some cool things. They're very focused on that developer app dev deployment there. Um, but you know, your customers, they've got a broad spectrum of applications and that journey to transformation in a modern nation is going to take time. How do you deal with the spectrum of what they're dealing with? But Todd, maybe start with you and then Josh would love your viewpoints too. I mean the spectrum. Massive. So our biggest challenge is keeping up with everything and continuing to innovate with all the things that are happening. But again, the benefits of the platform that we have enables us to do that in the enhancements. >>We wait and we made this year, this year. Um, now that our platform is, is more open, we can connect data, collect data from multiple entities, not just the new Relic, uh, agents that we've, that we were built on. So, uh, the concept of observability and being able to observe the entire application environment, um, is built on the fact that data's gotta come from all these different places. Then we need to turn that around and curate it, uh, into the right experience and the right use case that the customer's looking for. So, uh, all I can say is that, uh, our, our company is built on innovation. We try and stay on the cutting edge of all that. Try and stay current with that and meet the customer's needs as, as everyone here is innovating like S easy at scale. Todd, talk about what's going on in New York. >>What's the coolest thing going out with new Relic right now? Cause Lou always comes on the Q lose to CEO and he's cool. We love him, but he's always got his hands in something. Yes, he got the observability down. Cloud operations becoming standard. That's a tailwind for you guys as a company. But what cool things are you guys working on right now? Um, I certainly can't do Lou any justice. So the customer stories and things and he comes up with are amazing, but you know, from an industry's perspective, like gaming is hot. Um, and it's just like media and entertainment is hot. So we're just doing some really cool things with some really cool customers. Um, maybe not as cool as Lou would be, but you know, customers like, uh, are really adopting our migration story and we're really driving some significant business together. So customers like world fuel services and fleet complete, uh, we've recently come out and announced the stories of how we're helping these companies migrate. >>And frankly that's what's, that's what's cool about it is like everyone wants to get on the cloud faster, do more faster, and we're, we're enabling that, uh, in some really cool customers. So I'll to get your both reactions just to memes that we're developing on the cube this week. One is called, one is cloud native. If you take the T out, it's cloud naive. Okay. So, and the other one is something that I use on my post when my Andy story I did was you got born in the cloud, which is clear benefits. There's no, there's no discussion there. Check winning builder, but reborn in the cloud as companies are becoming reborn, this isn't the Mike, not just migration. There's a fundamental mind shift shift. Yeah. This is a reborn enterprise. And if you're not be born in the cloud and you're probably not going to be around longer, that seems to be the message. What's your reaction to cloud native without the T and reborn in the cloud? >>Well, I think it's, I think it's an accurate statement. It's funny. It's the first I've heard it. I may steal it. If I can use it, please pass it on. I will. Um, I would say that from an APM perspective, many of our partners are in different phases of their journey. Um, and so everything that we do is around three anchor points, which is helping those companies build great software if they haven't already, or if they're making that transition. Once they've made that transition, how do we help them market the software? And then the third piece is really how do we help them sell it? So in the case of new Relic, um, we've got a number of folks around the world that are helping with that co-sale process based on the solutions that we've jointly defined. Um, and then we also help build out the channel because as AWS, we've got tens of thousands of consulting partners. So the idea when you talk about that journey of becoming cloud native is how do you help a partner through that? You've got to hit on all three of those pillars to do it right. The leadership's got to be there for the top. Totally. You've got to have board alignment. You've got to have executive sponsorship, you've got to have technical buying, all of it. >>You guys have a very savvy customer base, Bray cloud native observability. What is the naivety uh, um, issue? What are people mostly naive about? Cause if you don't do it right with instrumentation observability if you're naive about that, you're going to get bitten in the, you know what? Well being, being naive there is not having your observability platform in place. So, but, but you really can't anymore. The old world of if you had a monolithic application running on servers monitoring, sometimes it was optional or a nice to have something today. You couldn't, you could only afford on your most mission critical applications as soon as you flipped a dev ops, a bunch of cloud native technologies, um, modern applications, but on the most modern frameworks with entities that are, that have all these dependencies to make sure that application works. Monitoring is a must, must have an observability is a must have. >>So that's now even in day one, out of the box, out of the one and two, the in to the reborn comment. As soon as you cross that path, you report, you rebirth yourself every day. Like it's constant. You're releasing code daily or multiple times a day, and so there's no like reborn statement anymore. It's a completely agile process. System changeover. This is not just saying it. You got to really believe what you're doing. You have to measure improvement, which is what new Relic is great at because if you take what's happening now on premise and you go to that transformation, you've got to show that you've actually achieved not just savings, but you're helping developers be more efficient and so you, you can't prove that story without the before and after. Yeah, yeah. Love talking to the cloud native gurus that you guys are, congratulations on your marketplace and ISV success. It's only getting the beginning of that run. It's kicking butt. Congratulations. Hundreds of thousands of customers are buying and hundreds of thousands more talk congratulates a new rule. Always great to have you guys on X. Great, impressive company, great results. Always great team, great product cloud, native ashore. Props to that. Thanks for coming on. Appreciate shit. Thanks so much. I'm John here in the cube, extracting the signal in the noise day. Two of three days of wall-to-wall coverage. Two sets here on the ground. Thanks for watching. We'll be right back.

>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Welcome back to the queue from Las Vegas. We are live at AWS reinvent 19 Lisa Martin with John furrier. We've been having lots of great conversations. John, we're about to have another one cause we always love to talk about customer proof in the putting. Please welcome a couple of guests. We have Rafael, director of analytics and data management from triple a life. Welcome. Thanks for having me. Really appreciate it. Our pleasure. And from Burkle anchor Jane, the SVP of cloud platforms. Welcome. Thank you. Thank you so much. Pleasure to be here. So here we are in this, I can't see of people around us as, as growing exponential a by the hour here, but awkward. Let's start with you give her audience an understanding of Merkel, who you are and what you do. >>Yeah, absolutely. So Marco is a global performance marketing agency. We are part of a dental agent network and a, it's almost about 9,000 to 10,000 people worldwide. It's a global agency. What differentiates Merkel from rest of the other marketing agencies is our deep roots and data driven approach. We embrace technology. It's embedded in all our, all our solutions that we take to market. Um, and that's what we pride ourselves with. So, um, that's basically a high level pitch about Merkel. What differentiates us, my role, uh, I lead the cloud transformation for Merkel. Um, uh, basically think of my team as the think tanks who bring in the new technology, come up with a new way of rolling out solutions product I solutions, uh, disruptive solutions, which helps our clients and big fortune brands such as triple life insurance, uh, to transform their marketing ecosystem. >>So let's go ahead and dig. A lot of folks probably know AAA life, but, but Raphael, give us a little bit of an overview. This is a 50 year old organization. >>So we celebrate our 50th 50 year anniversary this year. Actually, we're founded in 1969. So everybody life insurance, we endeavor to be the provider of choice for a AAA member. Tell them to protect what matters most to them. And we offer a diverse set of insurance products across just about every channel. Um, and um, we engage with Merkel, uh, earlier, the, um, in 2018 actually to, to, uh, to build a nice solution that allows us to even better serve the needs of the members. Uh, my role, I am the, I lead our analytics and data management work. So helping us collect data and manage better and better leverage it to support the needs of members. >>So a trip, I can't even imagine the volumes of data that you're dealing with, but it's also, this is people's data, right? This is about insurance, life insurance, the volume of it. How have you, what were some of the things that you said? All right guys, we need to change how we're managing the data because we know there's probably a lot more business value, maybe new services that we can get our on it or eyes >>on it. >>So, so that was, that was it. So as an organization, uh, I want to underscore what you said. We make no compromises when it comes to the safety of our, of our members data. And we take every step possible to ensure that it is managed in a responsible and safe way. But we knew that on, on the platform that we had prior to this, we weren't, we weren't as italics. We wanted to be. We would find that threaten processes would take spans of weeks in order to operate or to run. And that just didn't allow us to provide the member experience that we wanted. So we built this new solution and this solution updates every day, right? There's no longer multi-week cycle times and tumbler processes happen in real time, which allows us to go to market with more accurate and more responsive programs to our members. >>Can you guys talk about the Amazon and AWS solution? How you guys using Amazon's at red shift? Can he says, you guys losing multiple databases, give us a peek into the Amazon services that you guys are taking advantage of that anchor. >>Yeah, please. Um, so basically when we were approached by AAA life to kind of come in and you know, present ourselves our credentials, one thing that differentiated there in that solution page was uh, bringing Amazon to the forefront because cloud, you know, one of the issue that Ravel and his team were facing were scalability aspect. You know, the performance was, was not up to the par, I believe you guys were um, on a two week cycle. That data was a definition every two weeks. And how can we turn that around and know can only be possible to, in our disruptive technologies that Amazon brings to the forefront. So what we built was basically it's a complete Amazon based cloud native architecture. Uh, we leveraged AWS with our chip as the data warehouse platform to integrate basically billions and billions of rows from a hundred plus sources that we are bringing in on a daily basis. >>In fact, actually some of the sources are the fresh on a real time basis. We are catching real time interactions of users on the website and then letting Kimberly the life make real time decisions on how we actually personalize their experience. So AWS, Redshift, you know, definitely the center's centerpiece. Then we are also leveraging a cloud native ELT technology extract load and transform technology called. It's a third party tool, but again, a very cloud native technology. So the whole solution leverage is Python to some extent. And then our veil can talk about AI and machine learning that how they are leveraging AWS ecosystem there. >>Yeah. So that was um, so, uh, I anchor said it right. One thing that differentiated Merkel was that cloud first approach, right? Uh, we looked at it what a, all of the analysts were saying. We went to all the key vendors in this space. We saw the, we saw the architecture is, and when Merkel walked in and presented that, um, that AWS architecture, it was great for me because if nausea immediately made sense, there was no wizardry around, I hope this database scales. I was confident that Redshift and Lambda and dynamo would this go to our use cases. So it became a lot more about are we solving the right business problem and less about do we have the right technologies. So in addition to what Ankur mentioned, we're leveraging our sort of living RNR studio, um, in AWS as well as top low frat for our machine learning models and for business intelligence. >>And more recently we've started transition from R to a Python as a practitioner on the keynote today. Slew a new thing, Sage maker studio, an IDE for machine learning framework. I mean this is like a common set. Like finally, I couldn't have been more excited right? That, that was my Superbowl moment. Um, I was, I was as I was, we were actually at dinner yesterday and I was mentioning Tonker, this is my wishlist, right? I want AWS to make a greater investment in that end user data scientists experience in auto ML and they knocked it out of the park. Everything they announced today, I was just, I was texting frat. Wow, this is amazing. I can't wait to go home. There's a lot of nuances to, and a lot of these announcements, auto ML for instance. Yeah. Really big deal the way they did it. >>And again, the ID who would've thought, I mean this is duh, why didn't we think about this sooner? Yeah. With auto ML that that focus on transparency. Right. And then I think about a year ago we went to market and we ended up not choosing any solutions because they hadn't solved for once you've got a model built, how do you effectively migrated from let's say an analyst who might not have the, the ML expertise to a data science team and the fact that AWS understood out of the gate that you need that transparent all for it. I'm really excited for that. What do you think the impacts are going to be more uptake on the data science side? What do you think the impact of this and the, so I think for, I think we're going to see, um, that a lot of our use cases are going to part a lot less effort to spin up. >>So we're going to see much more, much faster pilots. We're going to have a much clearer sense of is this worth it? Is this something we should continue to invest in and to me we should drive and I expect that a lot, much larger percentage of my team, the analysts are going to be involved in data and data science and machine learning. So I'm really excited about that. And also the ability to inquire, to integrate best practices into what we're doing out of the gate. Right? So software engineers figured out profiling, they figured out the bugging and these are things that machine learners are picking up. Now the fact that you're front and center is really excited. Superbowl moment. You can be like the new England Patriots, 17 straight AFC championship games. Boston. Gosh, I could resist. Uh, they're all Seattle. They're all Seattle here and Amazon. I don't even bring Seattle Patriots up here and Amazon, >>we are the ESPN of tech news that we have to get in as far as conversation. But I want to kind of talk a little bit, Raphael about the transformation because presumably in, in every industry, especially in insurance, there are so many born in the cloud companies that are a lot, they're a lot more agile and they are chasing what AAA life and your competitors and your peers are doing. What your S establishing with the help of anchor and Merkel, how does this allow you to actually take the data that you had, expand it, but also extract insights from maybe competitive advantages that you couldn't think about before? >>Yeah, so I think, uh, so as an organization, even though we're 50 years old, one of the things that drew me to the company and it's really exciting is it's unrelated to thrusting on its laurels, right? I think there's tremendous hunger and appetite within our executive group to better serve our members and to serve more members. And what this technology is allowed is the technology is not a limiting factor. It's an enabling factors. We're able to produce more models, more performant models, process more of IO data, build more features. Um, we've managed to do away with a lot of the, you know, if you take it and you look at it this way and squeeze it and maybe it'll work and systematize more aspects of our reporting and our campaign development and our model development and the observability, the visibility of just the ability to be agile and have our data be a partner to what we're trying to accomplish. That's been really great. >>You talked about the significant reduction in cycle times. If we go back up to the executive suite from a business differentiation perspective, is the senior leadership at AAA understanding what this cloud infrastructure is going to enable their business to achieve? >>Absolutely. So, so our successes here I think have been instrumental in encouraging our organization to continue to invest in cloud. And uh, we're an active, we're actively considering and discussing additional cloud initiatives, especially around the areas of machine learning and AI. >>And the auger question for you in terms of, of your expertise, in your experience as we look at how cloud is changing, John, you know, educate us on cloud cloud, Tuto, AI machine learning. What are, as, as these, as businesses, as industries have the opportunity to for next gen cloud, what are some of the next industries that you think are really prime to be completely transformed? >>Um, I'm in that are so many different business models. If you look around, one thing I would like to actually touch upon what we are seeing from Merkel standpoint is the digital transformation and how customers in today's world they are, you know, how brands are engaging with their customers and how customers are engaging with the brands. Especially that expectations customer is at the center stage here they are the ones who are driving the whole customer engagement journey, right? How all I am browsing a catalog of a particular brand on my cell phone and then I actually purchased right then and there and if I have an issue I can call them or I can go to social media and log a complaint. So that's whole multi channel, you know, aspect of this marketing ecosystem these days. I think cloud is the platform which is enabling that, right? >>This cannot happen without cloud. I'm going to look at, Raphael was just describing, you know, real time interaction, real time understanding the behavior of the customer in real time and engaging with them based on their need at that point of time. If you have technologies like Sage maker, if you have technologies like AWS Redship you have technologies like glue, Kinesis, which lets you bring in data from all these disparate sources and give you the ability to derive some insights from that data in that particular moment and then interact with the customer right then and there. That's exactly what we are talking about. And this can only happen through cloud so, so that's my 2 cents are where they are, what we from Merkel standpoint, we are looking into the market. That's what we are helping our brands through to >>client. I completely agree. I think that the change from capital and operation, right to no longer house to know these are all the sources and all the use cases and everything that needs to happen before you start the project and the ability to say, Hey, let's get going. Let's deliver value in the way that we've had and continue to have conversations and deliver new features, new stores, a new functionality, and at the same time, having AWS as a partner who's, who's building an incremental value. I think just last week I was really excited with the changes they've made to integrate Sage maker with their databases so you can score from the directly from the database. So it feels like all these things were coming together to allow us as a company to better off on push our aims and exciting time. >>It is exciting. Well guys, I wish we had more time, but we are out of time. Thank you Raphael and anchor for sharing with Merkel and AAA. Pleasure. All right. Take care. Or John furrier. I am Lisa Martin and you're watching the cube from Vegas re-invent 19 we'll be right back.

(rhythmic music) >> Live from Orlando, Florida. It's theCUBE covering Microsoft Ignite. Brought to you by Cohesity and theCUBE's ecosystem partners. >> Welcome back everyone to theCUBE's live coverage of Microsoft Ignite here at the Orange County Convention Center. I'm your host, Rebecca Knight along with my cohost Stu Miniman. We're joined by Miha Kralj. He is the cloud native architecture lead at Accenture and marathon runner I should say, too. >> That's true, yes. >> Thank you so much for coming on theCUBE, Miha. >> You're more than welcome. >> So I want to start the conversation by talking about the difference between cloud immigrant and cloud native. There's a big distinction. >> Yes, there is. Cloud became a new execution platform for a whole bunch of businesses and what we are going to see now is that lots of companies are using cloud in two different ways or two different forms. Even if you listen to analysts, they are talking about mode one, mode two so when we talk about cloud native we are mostly talking about both technologies and processes but also team organization that is very much inspired by cloud, that went through all of the transformations that we saw, for example, in companies like Netflix, like Uber, like very much how Amazon is organized internally, how Microsoft is organized internally so we are talking about very new approach. How to architect applications, how to actually have a process to develop publications and push them over into production, how to actually run the complete automation, a set of tools, but of course it's completely new enabling platform on top of that or underneath that that allows us to run those cloud native style of applications. >> An oversimplification I've heard is those born in the cloud companies will start out cloud native. The challenge you have for those that, the cloud immigrants, if you will, is there are so many different things that they need to change. Not just the way they architect things, the way that they run things. It's a real challenge and it's companies like yours I think, that help them do that immigration process, right? >> You are actually bringing up the really good point 'cause one thing is if you start from nothing. If you are in a green field and you build, you can say I'm going to take the best automation, I will buy the best people and I'm going to go full-on cloud native. That totally works. You can also be in the old world and you can say let me build cloud native like a separate IT organization and you hire some people in the old IT and some in the new IT and so on and so on and lots of our clients do that. We kind of create a bimodal type of IT organizations with two sets of technology stacks, two approaches. The thing that is really hard to do is to actually integrate those two into a very good hybrid cohesive schema so that you can have a system that one part of the system is traditional on-prem database that goes through its own rhythm of development and then you have systems that are cloud native, very rapidly developed, lots of the minimum viable products that are actually sourcing the data from the old world. So it goes from hard, harder, hardest. >> So do you have a schemata of how to make the decision? What strategy is right for which client or is it really just so dependent on the client's unique set of circumstances? I will try to reframe your question because it is not old or new 'cause it is always that dilemma. If you're looking every decade we go through the same rhythm of refreshing. We get a refreshed wave of architecture. If you remember 30 years ago when I was still young we had a traditional monolithic architecture which were refreshed into client server and into a service oriented architecture now into microservices and in the future we already know that we are going into reactive and driven architectures. Whenever we have a new architectural style we always get also new set of processes. Historically with the waterfall development then we refreshed into rational unified processes you'll remember that from ages ago and then the traditional right now we are doing agile and we are going towards lean development and so on so everything refreshes. So your question is very much asking when is the right time that you stop using the previous generation of architecture, process, tools and platform and jump to the next generation 'cause you can be too late. Obviously we are talking about companies that they need to modernize but you can also be too early 'cause lots of the companies are right now wondering should they go serverless which is also cloud native style but it's way ahead of typical containers, simple for natives. So when is it time to go from VM based traditional SOA into microservice containers versus reactive, event driven on let's say, azure functions. Those decisions are not easy to do but I can tell you most of my clients have kind of a spectrum of everything. They still have a mainframe, they have a client server, they have SOA architecture, they have microservices and they're already thinking about event driven serverless. >> Absolutely, and by the way, they can run that docker container on linux on the mainframe because everything in IT is always additive. So it's challenging. I've spent a lot of my career trying to help companies get out of their silos of infrastructure, of product group and in a multicloud world we feel like have we just created more silos? How are we making progress? What's good? How are you helping companies that maybe are stuck behind and are threatened of getting obsoleted from being able to move forward? What are some of the patterns and ways to get there? >> Our approach is very much trying to find what's really behind, what's the business reason behind? 'Cause until I realize why somebody wants to modernize it's very hard to give the answer to how do you modernize. Not to oversimplify but we typically see that value formula coming. We want to reduce specific detriments and we want to increase specific benefits and hat's why people need to go through those modernization waves. You can reduce cost and historically we were dramatically cutting costs just by automation, clonization, all of that. You can reduce risk. If you remember a few years ago everybody was talking that cloud is too risky, now everybody says oh, I'm reducing the risk and improving security by going to the cloud. You can increase speed and agility so you can suddenly do things much faster and enable more experiments. I personally find the number four most interesting which is you get better access to new software innovation. Here is the question. When is the last time that you remembered and a technology vendor would give you a DVD and say this is our latest software that you can use. >> Yeah, probably a Microsoft disc but you know, back in the day. >> Nobody is shipping software for on-premises anymore. Maybe, they do later in a cycle but all of the latest software innovation is cloud first or cloud only so it's only logical if we see the business that depends on business innovation, they need to start building their systems in a cloud native world 'cause they are going to source natural language processing, artificial intelligence recognition, all of the complex services, they have to source them from the could and therefore they want to build apps in the cloud native style. >> Yeah, it's an interesting challenge. Things are changing so fast. One of the things that I hear from certain companies is they, is that, well, I go and I make my strategy and then by the time I start implementing it I wonder if I made the wrong decision because some new tool is there. You mentioned Azure functions, wait, no, I was just getting on Kubernetes and getting comfortable with that as opposed to most companies, oh, I'm starting to look at that thing so these waves are coming faster and faster. >> You just exposed that you are an architect. Let me explain why. >> The technologist is charged, sorry. >> When I hire people into architecture roles, one of the common interviewing questions will be first, explain one of your previous solutions and then the question comes if you would start again today, what would you do different? Every single architect that I know are always dissatisfied with their previous choices and decisions because there were new wave of technologies that came in during the engagement. What you are expressing, whenever I get a person that says no, I did everything perfectly and I would not change anything, I might have a different role for these people. >> So I mentioned before that you are a marathon runner. I'm curious to hear how your job is similar to running a marathon because as Stu was just talking about, the pace of change, that is the one constant in this industry and to be a marathon runner, you got to keep a good pace. How do you sort of make sure that you are keeping your stamina up, keeping your eyes on the future to make sure you know what's coming ahead? >> That's a very interesting analogy and I was doing that comparison not that far back before. The first part isthat in order to have a good time at the end of the race you need to have good nutrition, you need to have a good preparation, you need to have all those things so the moment when I compared it back to my regular work, nutrition, we usually compare it with how do I keep my skills up which usually, at least in my case, it is between four to six hours every day either reading I usually say to people I try to make something, teach something and learn something every single day and you have to do that four to six hours every single day just like preparing for marathon and there is a whole bunch of those other activities that all need to be aligned then once you actually start running with the client, when you start doing engagement with the client, that even when you hit the wall, even when you get tired, first you know the reason why you are doing it, you know what the end goal means, what the finish line looks like and you know that you are prepared, that this is the best that you can get. Is it easy? No, it's not. We are kind of used in the IT industry to do that and reinvent ourselves every second year. >> When you look at the cloud navtive space what are some of the challenges and pitfalls? How do you manage that? What advice do you give at a high level? I understand there's a lot of diversity out there. >> Oh, where are the challenges and lessons learned? How much time do we have? So I would say the most obvious one would be jumping into that pool of cloud computing without preparation, without guidance, without help, without mentoring, tutoring or somebody to guide you. Get less than perfect experience and declare that is not for me therefore it's not for any of us ever. Right? I see lots of those generalizations where although it's clear that the whole industry is going in that consumerization direction and we are charging by consumption and all of that that we have clients that started it either early, they didn't have a fantastic experience, they got into specific roadblock and then for several years they don't want even to have a discussion anymore. The other problem is not enough upscaling so simply not enough thinking how different that knowledge is. A discussion with a CIO that says that IT's the same for last 30 years, you know, a machine is a machine is a machine. Coding is coding is coding. Nothing really changed ever. It is really hard to have a discussion to say the devil is in the details. Yes, technically we do the same thing for 30 years which is we make dreams come true in IT. We create something that was never done before but how we do that, and tools of the trade, an approach is dramatically different. Every decade brings a dramatically different result. Trying to explain that in supportive way is a challenge on its own. >> Miah, what about your team? How are you making sure that you have the right people in place to help execute these solutions? And this is they have the right skills, the right mindset, the right approach of the continual learning and the constant curiosity that you keep referencing? >> Well, you are asking a consultant how does consultant know that he's successful? When the client is happy. I'm serious, very simple here, right? How do we make sure that the client is happy which is very much corollary to your question. We really first need to make sure that we are educating our clients all the way through. The times of delivering something without a massive knowledge transfer, those times are over. The easiest way to explain that is that what we are telling is that every business needs to become software business. It doesn't matter is it bank, insurance, health provider, they need to learn to actually make critical competitive advantage solutions in-house. So how do we actually teach engineering to companies that historically were not engineering companies? All of my team are half coaches and half engineers or architects or whatever they are. Being a coach and being a mentor and kind of allowing our clients to do things independently instead of just depend on us is one of those major changes that we see how we actually ramp up and train and support people. >> Miha, we've seen and talked to Accenture at many cloud events. Accenture's got a very large presence. I've been watching the entire week. Activity in the booth, one of the four anchor booths here at the show. What's different about Microsoft, your view on Microsoft, what you're hearing from customers and also speak to how Accenture really lives in this Microsoft ecosystem. >> I think that I understand the question. Are you asking me about how Accenture and Microsoft cooperates together in that new world? >> Yeah, why does Accenture have such a large presence at a show like this? Accenture is at all the cloud events. >> So Accenture has specific targeted, strategic alliances with large technology vendors. The size of the alliance, the importance of the alliance is always directly reflected both from, of course, the size of the market but also our belief in how successful a long-term specific technology stack is going to be. We have a very strong, firm belief that with Microsoft we actually have an amazingly good alliance. Actually we call it alliance of three. We forgot to mention Avanade as well, right? Which is dedicated to creative entity to make sure that Microsoft solutions are built, designed and then ran correctly. We jointly invest obscene amount of money to make sure that right solutions are covered with right Microsoft technologies and developed in the right manner. >> Great, Miha, thank you so much for coming on theCUBE. It was a pleasure having you. >> You're more than welcome, anytime. >> I'm Rebecca Knight for Stu Miniman. That wraps up our coverage of Microsoft Ignite. We will see you next time on theCUBE. (rhythmic music)

>> Live from Orlando, Florida, it's theCUBE covering Microsoft Ignite. Brought to you by Cohesity and theCUBE's ecosystem partners. >> Welcome back everyone, we are wrapping up day three of Microsoft Ignite here in Orlando, Florida. CUBE's live coverage, I'm your host Rebecca Knight, along with Stu Miniman, my esteemed cohost for these past three days, it's been fun working with you, Stu. >> Rebecca, it's been a great show, real excited. Our first time at a Microsoft show and it's a big one. I mean, the crowds are phenomenal. Great energy at the show and yeah, it's been great breaking down this ecosystem with you. >> So, three days, what do we know, what did you learn, what is your big takeaway, what are you going to to go back to Boston with? >> You know, it's interesting, we've been all talking and people that I know that have been here a couple of years, I've talked to people that have been at this show for decades, this is a different show. There's actually a friend of mine said, he's like, "Well look, Windows pays the bills for a lot of companies." There's a lot of people that all the Windows components, that's their job. I mean, I think back through my career when I was on the vendor side, how many rollouts of Exchange and SharePoint and all these things we've done over the years. Office 365 been a massive wave that we watched. So Microsoft has a broad portfolio and they've got three anchor shows. I was talking with one of the partners here and he's like, "You know, there's not a lot of channel people "at this event, at VMworld there's a lot of channel people." I'm like, "Well yeah because there's a separate show "that Microsoft has for them." You and I were talking at an earlier analytics session with Patrick Moorhead and he said, "You know when I look at the buy versus build, "a lot of these people are buying and I don't "feel I have as many builders." Oh wait, what's that other show that they have in the Spring, it's called Microsoft Build. A lot of the developers have moved there so it's a big ecosystem, Microsoft has a lot of products. Everything from, my son's excited about a lot of the Xbox stuff that they have here. Heck, a bunch of our crew was pickin' up Xbox sweatshirts while they're here. But a lot has changed, as Tim Crawford said, this is a very, it feels like a different Microsoft, than it even was 12 or 24 months ago. They're innovating, so look at how fast Microsoft moves and some of these things. There's good energy, people are happy and it's still trying to, you know. It's interesting, I definitely learned a lot at this show even though it wasn't the most sparkly or shiny but that's not necessarily a bad thing. >> Right, I mean, I think as you made a great point about just how integral Microsoft is to all of our lives as consumers, as enterprise, the Xbox, the Windows, the data storage, there's just so much that Microsoft does that if we were to take away Microsoft, I can't even imagine what life would be like. What have been your favorite guests? I mean, we've had so many really, really interesting people. Customers, we've had partners, we're going to have a VC. What are some of the most exciting things you've heard? >> Yeah, it's interesting, we've had Jeffrey Snover on the program a couple of years ago and obviously a very smart person here. But at this show, in his ecosystem, I mean, he created PowerShell. And so many people is like, I built my career off of what he did and this product that he launched back in 2001. But we talked a little bit about PowerShell with him but then we were talking about Edge and the Edge Boxes and AI and all those things, it's like this is really awesome stuff. And help connecting the dots to where we hid. So obviously, big name guest star, always, and I always love talking to the customers. The thing I've been looking at the last couple of years is how all of these players fit into a multicloud world. And Microsoft, if you talk about digital transformation, and you talk about who will customers turn to to help them in this multicloud world. Well, I don't think there's any company that is closer to companies applications across the spectrum of options. Office 365 and other options in SaaS, all the private cloud things, you start with Windows Server, you've got Windows on the desktop, Windows on the server. Virtualization, they're starting to do hyperconversion everything, even deeper. As well as all the public cloud with Azure and developers. I talked to the Azure functions team while I was here. Such breadth and depth of offering that Microsoft is uniquely positioned to play in a lot of those areas even if, as I said, certain areas if the latest in data there might be some other company, Google, Amazon, well positioned there. We had a good discussion Bernard Golden, who's with Capital One, gave us some good commentary on where Alibaba fits in the global scheme. So, nice broad ecosystem, and I learned a lot and I know resonated with both of us, the "you want to be a learn it all, not a know it all." And I think people that are in that mindset, this was a great show for them. >> Well, you bring up the mindset, and that is something that Satya Nadella is really such a proponent of. He says that we need to have a growth mindset. This is off of the Carol Dweck and Angela Duckworth research that talks about how important that is, how important continual learning is for success. And that is success in life and success on the job and organization success and I think that that is something that we are also really picked up on. This is the vibe of Microsoft, this is a company, Satya Nadella's leadership, talking to so many of the employees, and these are employees who've been there for decades, these are people who are really making their career, and they said, "Yeah, I been here 20 years, if I had my way, "I'll be here another 30." But the point is that people have really recommitted to Microsoft, I feel. And that's really something interesting to see, especially in the tech industry where people, millennials especially, stay a couple years and then move on to the next shiny, new thing. >> Yeah, there was one of our first guests on for Microsoft said that, "Been there 20 years and what is different about "the Satya Nadella Microsoft to the others is "we're closer and listening even more to our customers." We talk about co-creation, talk about how do we engage. Microsoft is focusing even deeper on industries. So that's really interesting. An area that I wanted to learn a little bit more about is we've been talking about Azure Stack for a number of years, we've been talking about how people are modernizing their data center. I actually had something click with me this week because when I look at Azure Stack, it reminds me of solutions I helped build with converged infrastructure and I was a big proponent of the hyper-converged infrastructure wave. And what you heard over and over again, especially from Microsoft people, is I shouldn't think of Azure Stack in that continuum. Really, Azure Stack is not from the modernization out but really from the cloud in. This is the operating model of Azure. And of course it's in the name, it's Azure, but when I looked at it and said, "Oh, well I've got partners like "Lenovo and Dell and HPE and Sysco." Building this isn't this just the next generation of platform there? But really, it's the Azure model, it's the Azure operating stack, and that is what it has. And it's more, WSSD is their solution for the converged and then what they're doing with Windows Server 2019 is the hyper-converged. Those the models that we just simplify what was happening in the data center and it's similar but a little bit different when we go to things like Azure and Azure Stack and leads to something that I wanted to get your feedback on. You talk business productivity because when we talk to companies like Nutanix, we talk to companies like Cohesity who we really appreciate their support bringing us here, giving us this great thing right in the center of it, they talk about giving people back their nights and weekends, giving them back time, because they're an easy button for a lot of things, they help make the infrastructure invisible and allow that. Microsoft says we're going to try to give you five to ten percent back of your business productivity, going to allow you to focus on things like AI and your data rather than all the kind of underlying spaghetti underneath. What's your take on the business productivity piece of things? >> I mean, I'm in favor of it; it is a laudable goal. If I can have five to ten percent of my day back of just sort of not doing the boring admin stuff, I would love that. Is it going to work, I don't know. I mean, the fact of the matter is I really applaud what Cohesity said and the customers and the fact that people are getting, yes, time back in their day to focus on the more creative projects, the more stimulating challenges that they face, but also just time back in their lives to spend with their children and their spouse and doing whatever they want to do. So those are really critical things, and those are critical things to employee satisfaction. We know, a vast body of research shows, how much work life balance is important to employees coming to their office or working remotely and doing their best work. They need time to recharge and rest and so if Microsoft can pull that off, wow, more power to them. >> And the other thing I'll add to that is if you, say, if you want that work life balance and you want to be fulfilled in your job, a lot of times what we're getting rid of is some of those underlying, those menial tasks the stuff that you didn't love doing in the first place. And what you're going to have more time to do, and every end user that we talked to says, "By the way, I'm not getting put out of a job, "I've got plenty of other tasks I could do." And those new tasks are really tying back to what the business needs. Because business and IT, they need to tie together, they need to work together, it is a partnership there. Because if IT can't deliver what the business needs, there's other alternatives, that's what Stealth IT was and the public cloud could be. And Microsoft really positions things as we're going to help you work through that transition and get there to work on these environments. >> I want to bring up another priority of Microsoft's and that is diversity. So that is another track here, there's a lot of participants who are learning about diversity in tech. It's not a good place right now, we know that. The tech industry is way too male, way too white. And Satya Nadella, along with a lot of other tech industry leaders, has said we need more underrepresented minorities, we need more women, not only as employees but also in leadership positions. Bev Crair, who was on here yesterday, she's from Lenovo. She said that things are starting to change because women are buying a lot of the tech and so that is going to force changes. What do you think, do you buy it? >> And I do, and here's where I'd say companies like Lenovo and Microsoft, when you talk about who makes decisions and how are decisions made, these are global companies. Big difference between a multi-national company or a company that's headquartered in Silicon Valley or Seattle or anything versus a global company. You look at both of those companies, they have, they are working not just to localize but have development around the world, have their teams that are listening to requirements, understand what is needed in those environments. Going back to what we talked about before, different industries, different geographies, and different cultures, we need to be able to fit and work and have products that work in those environments, everything. I think it was Bev that talked about, even when we think about what color lights. Well, you know, oh well default will use green and red. Well, in different cultures, those have different meanings. So yeah, it is, it's something that definitely I've heard the last five to ten years of my career that people understand that, it's not just, in the United States, it can't just be the US or Silicon Valley creating great technology and delivering that device all the way around the world. It needs to be something that is globally developed, that co-creation, and more, and hopefully we're making progress on the diversity front. We definitely try to do all we can to bring in diverse voices. I was glad we had a gentleman from Italy shouting back to his daughters that were watching it. We had a number of diverse guests from a geography, from a gender, from ethnicity, on the program and always trying to give those various viewpoints on theCUBE. >> I want to ask you about the show itself: the 30,000 people from 5,000 different organizations around the globe have convened here at the Orange County Convention Center, what do you think? >> Yeah, so it was impressive. We go to a lot of shows, I've been to bigger shows. Amazon Reinvent was almost 50,000 last year. I've been to Oracle OpenWorld, it's like takes over San Francisco, 60 or 70,000. This convention center is so sprawling, it's not my favorite convention center, but at least the humidity is to make sure I don't get dried out like Las Vegas. But logistics have run really well, the food has not been a complaint, it's been good, the show floor has been bustling and sessions are going well. I was talking to a guy at breakfast this morning that was like, "Oh yeah, I'm a speaker, "I'm doing a session 12 times." I'm like, "You're not speaking on the same thing 12 times?" He's like, "No, no it's a demo and hands on lab." I'm like, "Oh, of course." So they make sure that you have lots of different times to be able to do what you want. There is so much that people want to see. The good news is that they can go watch the replays of almost all of them online. Even the demos are usually something that they're cloud enabled and they get on live. And of course we help to bring a lot of this back to them to give them a taste of what's there. All of our stuff's always available on the website of thecube.net. This one, actually, this interview goes up on a podcast we call theCUBE Insights. So please, our audience, we ask you, whether it's iTunes or your favorite podcast reader, go to Spotify, theCUBE Insights. You can get a key analysis from every show that we do, we put that up there and that's kind of a tease to let you go to thecube.net and see the hundreds and thousands of interviews that we do across all of our shows. >> Great, and I want to give a final, second shout out to Cohesity, it's been so fun having them, being in the Cohesity booth, and having a lot of great Cohesity people around. >> Yeah, absolutely, I mean, so much I wish we could spend a little more time even. AI, if we go back to the keynote analysis then, but you can watch that, I can talk about the research we've done, and said how the end user information that Microsoft can get access to to help people when you talk about what they have, the TouchPoint to Microsoft Office. And even things like Xbox, down to the consumer side, to understand, have a position in the marketplace that really is unparalleled if you look at kind of the breadth and depth that Microsoft has. So yeah, big thanks to Cohesity, our other sponsors of the program that help allow us to bring this great content out to our community, and big shout out I have to give out to the community too. First time we've done this show, I reached out to all my connections and the community reached back, helped bring us a lot of great guests. I learned a lot: Cosmos DB, all the SQL stuff, all the Office and Microsoft 365, so much. My brain's full leaving this show and it's been a real pleasure. >> Great, I agree, Stu, and thank you so much to Microsoft, thank you to the crew, this has been a really fun time. We will have more coming up from the Orange County Civic Center, Microsoft Ignite. I'm Rebecca Knight for Stu Miniman, we will see you in just a little bit. (digital music)

>> Announcer: From the SiliconANGLE Media office in Boston, Massachusetts, it's theCube! (bright music) Now here's your host, Dave Vellante. >> Hi everybody, welcome to this special presentation in the Marlborough offices of theCube. My name is Dave Vellante, and I'm here with a friend, a colleague, a mentor of mine, David Moschella who is an author and a Fellow at Leading Edge Forum. Dave, thanks for coming in. It's great to see you. >> Hey, great to see you again. So we're going to talk about your new book, Seeing Digital: A Visual Guide to Industries, Organizations, and Careers of the 2020s. I got it here on my laptop. Got it off of Amazon, so check it out. We're going to be unpacking what's in there today. This is your third book I believe, right? Waves of Power and... >> David: Customer-Driven IT. >> Customer-Driven IT which was under the '03 timeframe coming out of the dot-com, and to me this is your most significant work, so congratulations on that. >> Well, thank you. >> Dave: I know how much work goes into it. >> You bet. >> So what was the motivation for writing this book? >> Well it's a funny thing when books are a lot of work, and during those times you wind up asking yourself why am I (laughing) doing this because they put in so much time. But for the last seven or eight years our group, the Leading Edge Forum, we've been doing a lot of work mostly for large organizations and our clients told us that the work we've been doing in consumerization, in Cloud, in disruption, in machine intelligence was really relevant to not just them but to their wider audiences of their partners, their customers, their employees. And so people are asking can we get this to a wider audience, and really that is what the book is trying to do. >> Yeah, you guys have done some great work. I know when I can get my hands on it I consume it. For those of you who don't know, Dave originally came up with the theory of disintegration to kind of explain the shift from centralized mainframe era to the sort of open distributed competition along different lines which really defined the Wintel era. So that was kind of your work really explaining industry shifts in a way that helped people and executives really understand that. And then the nice thing about this book is you're kind of open-sourcing a decade's worth of research that yourself and your colleagues have done. So talk about the central premise of the book. We're entering a new era. We're sort of exiting the Cloud, Web 2.0 era. We're still trying to figure out what to call this. But what's the central premise of the book? >> Yeah, the central premise is that the technologies of the 2020s will indeed define a new era, and the IT era industry just evolves. We had the mainframe era, the mini era, the PC and the Internet era, the mobility era, and now we're going in this era of intelligence and automation and blockchains and speech and things that are just a entire new layer of intelligence, and that that layer to us is actually more the powerful than any of the previous layers we've seen. If you think back, the first Web was founded around technologies like search and email and surfing the Web, quite simple technologies and created tremendous companies. And then the more recently we have sort of the social era for Facebook and Salesforce. And all these companies, they sort of took advantage of the Cloud. But again, the technologies are relatively simple there. Now we're really looking at a whole wave of just fundamentally powerful technology and so trying to anticipate what that's going to mean. >> So going from sort of private networks to sort of public networks to a Cloud of remote services to now this set of interrelated digital services that are highly accessible and essentially ubiquitous is what you put forth in the book, right? >> Yeah, and we put a lot of emphasis on words. Why do words change? We had an Internet that connected computers and a Web that sort of connected pages and documents and URLs. And then we started talking about Cloud of stuff out there somewhere in cyberspace. But when we look at the world that's coming and we use those words, pervasive, embedded, aware, autonomous, these aren't words that are really associated with a Cloud. And Cloud is just a metaphor, that word, and so we're quite sure that at some point a different word will emerge because we've always had a different word for every era of change and we're going into one of those eras now. >> So a lot of people have questions about we go to these conferences and everybody talks about digital disruption and digital transformation, and it's kind of frankly lightweight a lot of times. It doesn't have a lot of substance to it. But you point out in the book that CEOs are asking the question, "How do I get digital right?" They understand that something's happening, something's changing. They don't want to get disrupted, but what are some of the questions that you get from some of your clients? >> Yeah, that first question, are we getting digital right sort of leads to almost everything. Companies look at the way that a Netflix or Amazon operates, and then they look at themselves and they see the vast difference there. And they ask themselves, "How can we be more like them? "How can we be that vast, that innovative, that efficient, "that level of simple intuitive customer service?" And one of the ways we try to define it for our clients is how do they become a digital first organization where their digital systems are their face to the marketplace? And most CEOs know that their own firm doesn't operate that way. And probably the most obvious way of seeing that is so many companies now feeling the need to appoint a Chief Digital Officer because they need to give that task to someone, and CDOs are no panacea but they speak to this need that so many companies feel now of really getting it right and having a leadership team in place that they have confidence in. And it's very hard work, and a lot of our clients, they still struggle with it. >> One of the other questions you ask in the book that is very relevant to our audience given that we have a big presence in Silicon Valley is can Silicon Valley pull off a dual disruption agenda? What do you mean by that? >> Yeah, if you look at the Valley historically you could see them essentially as arms merchants. They were selling their products and services to whoever wanted to buy them, and companies would use them as they saw fit. But today in addition to doing that they are also what we say is they're an invading army, and they are increasingly competing with the very customers they've traditionally supplied, and of course Amazon being perhaps the best example of that. So many companies dependent on AWS as a platform, but there's Amazon trying to go after them in health care or retail or grocery stores or whatever business they're in. Yeah, content, every business under the sun. And so they're wearing these two dual disruptions hats. The technologies of our time are very disruptive, machine intelligence, blockchains, virtual reality, all these things have disruptive technology. But that second disruptive agenda of how do you change insurance, how do you change health care, how do change the car industry, that's what we mean, those two different types of disruptions. And they're pursuing both at the same time. >> And because it's digital and it's data, that possibility now exists that a company, a technology company can traverse industries which historically haven't been able to be penetrated, right? >> Yeah, absolutely, in our view every industry is going to be transformed by data one way or another. Whether it is disrupted or not is a second question, but the industry'll be very different when all of these technologies come into play, and the tech companies feel like they have the expertise and the vision of it. But they also have the money, and they're going to bet heavily to pursue these areas to continue their growth agenda. >> So one of the other questions of course that IT people ask is what does it mean for my job, and maybe we can, if we have time, we can talk about that. But you answer many of these questions with a conceptual framework that you call the Matrix which is a very powerful, you said words matter, a very powerful concept. Explain the Matrix. >> Okay, yeah. If we start and go back they have this idea that every generation of technology has its own words, Internet, Web, Cloud, and now we're going to a new era, so there will be a new word. And so we use the word Matrix as our view of that, and we chose it for two reasons. Obviously there's the movie which had its machine intelligence and virtual worlds and all of that. But the real reason we chose it is this concept that a matrix as in matrix mathematics is a structure that has rows and columns. And rows and columns is sort of the fundamental dynamic of what's going on in the tech sector today, that traditionally every industry had its own sort of vertical stack of capabilities that it did and it was sort of top to bottom silo. But today those horizontal platforms, the PayPals, the AWSs, the Facebooks, they run this, Salesforce, all these horizontal services that cut across those firms. And so increasingly every industry is leveraging a common digital infrastructure, and that tension between the traditional vertical stacks and these enormously powerful horizontal technology firms is really the structural dynamic that's in play right now. >> And at the top of that Matrix you have this sort of intelligence and automation layer which is this new layer. You don't like the term artificial intelligence. You make the point in the book there's nothing really artificial about it. You use machine intelligence. But that's that top layer that you see powering the next decade. >> Absolutely, if you look at the vision that everybody tends to have, autonomous cars, personalized health care, blockchain-based accounting, digital cash, virtual education, brain implants for the media, every one of those is essentially dependent on a layer of intelligence, automation, and data that is being built right now. And so just as previous layers of technology, the Web enabled a Google or an Amazon, the Cloud enabled AWS or Salesforce, this new layer enables companies to pursue that next layer of capabilities out there to build that sort of intelligent societal infrastructure of the 2020s which will be vastly different than where we are today. >> Will the adoption of the Matrix, in your opinion, occur faster because essentially it's built on the Internet and we have the Internet, i.e. faster than say the Internet or maybe some other major innovations, or is it going to take time for a lot of reasons? >> I think the speed is actually a really interesting question because the technology of the 2020s are extremely powerful, but most of them are not going to be immediate hits. And if you look back, say, to search, when search came out it was very powerful and you could scale it massively quickly. You look at machine learning, you look at blockchains, you look at virtual realities, you look at algorithms, speech and these areas, they're tremendously powerful. But there's no scenario where those things happen overnight. And so we do not see an accelerating pace of change. In fact it might be people often overestimate the speed of change in our business and consistently do that. But what we see is a sort of fundamental transformation over time, and that's why we put a lot of emphasis on the 2020s because we do not see two years from now this stuff all being in place. >> And you have some good examples in the book going back to the early days of even telephony. So it's worth checking that out. I want to talk about, bring it back to data, Amazon, Google, Apple, Microsoft, and Facebook, top five companies, public companies in terms of market cap. Actually it's not true after the Facebook fake news thing. I mean Berkshire Hathaway is slightly past Facebook. >> It'll be back (laughs). But I agree, it'll be back, but the key point there is these companies are different, they've got data at their core. When you compare that to other companies even financial services industry companies that are really data companies but the data's very bespoken, it's in silos. Can those companies, those incumbent companies, can they close that gap? Maybe you could talk about that a little bit. >> Yeah, we do a lot of work in the area of machine intelligence, artificial, whatever you want to call it. And one of the things you see immediately is this ridiculously large gap between what these leading companies do versus most traditional firms because of the talent, the data, the business model, all the things they have. So you have this widening gap there. And so the big question is is that going to widen or is it going to continue, will it narrow? And I think that the scenario for narrowing it I think is a fairly good one. And the message we say to a lot of our clients is that you will wind up buying a lot more machine intelligence than you will build because these companies will bring it to you. Machine intelligence will be in AWS. It'll be in Azure. It'll be in Salesforce. It'll be in your devices. It'll be in your user interfaces. It'll be in the speech systems. So the supply-side innovations that are happening in the giants will be sold to the incumbents, and therefore there will be a natural improvement in today's situation where a lot of incumbents are sort of basically trying to build their own stuff internally, and they're having some successes and some not. But that's a harder challenge. But the supply side will bring intelligence to the market in a quite powerful way and fairly soon. >> Won't those incumbents, though, have to sort of reorganize in a way around those new innovations given that they've got processes and procedures that are so fossilized with their existing businesses? >> Absolutely, and the word digital transformation is thrown around everywhere. But if it means anything it is having an organization that is aligned with the way technology works. And a good example of that is when you use Netflix today there's no separate sales experience, market experience, customer service, it's just one system and you have one team that builds those systems. In a typical corporation of course you have the sales organization and the marketing organization and the IT organization and the customer service organization. And those silos is not the way to build these systems. So the message we send to our clients if you really want to transform yourself you have to have more of this team approach that is more like the way the tech players do it. And that these traditional boundaries essentially go away when you go in the digital world where the customer experience is all those things at the same time. >> So if I'm hearing you correctly it's sort of a natural progression of how they're going to be doing business and the services that they're going to be procuring, but there's probably other approaches. Maybe it's force, but you're seeing maybe M&A or you're seeing joint ventures. Do you see those things as accelerating or precipitating the transformation or do you think it's futile and it really has to be led from the top and at the core? >> It's one of the toughest issues out there. And the reason people talk about transformation is because they see the need. But the difficulty is enormous. Most companies would say this is a three- or four-year process to make significant change, and this in a marketplace that changes every few months. So incumbent firms, they see where they want to go and it's very hard, and this is why this whole thing of getting digital right is so important, that people need to commit to significant change programs, and we're seeing it. And my parent company, DXC, we do a lot of this with clients and they want to embark on this program and they need people who can help them do it. And so leading a transformation agenda in most firms is really what digital leadership is these days and who's capable of doing that which requires tremendous skills in soft skills and hard skills to do right. >> Let's talk about industries and industry disruption. When you looked at the early disrupted industries whether it was publishing, advertising, music, one maybe had the tendency to think it was a bits versus atoms thing, but you point out in the book it's really not the case because you look at taxis, you look at hotels. Those are physical businesses and they've been disrupted quite substantially. Maybe you could give us some thoughts and insight there, particularly with regard to things like health care, financial services which haven't been disrupted. >> And there's a huge part of the work that I've been doing for years. And as you say, if you look at the industries that actually have been disrupted, they're all relatively low-security, low-risk businesses, music, advertising, taxis, retail. All these businesses have had tremendous changes. But the ones that haven't are all the ones where the stakes are higher, banking, insurance, health care, aerospace, defense. They've been hardly disrupted at all. And so you have this split between the low-risk industries that have changed and the high-risk ones that haven't. But what's interesting to me about that is that these technologies of the 2020s are aimed almost directly at those high-risk industries. So machine intelligence is aimed directly at health care and autonomous systems is aimed directly at defense and blockchains are aimed directly at banking and insurance. And so the technologies of the past if you look at Internet and the Web and the Cloud eras, they were not aimed at these industries. But today's are, so you now have at least a highly plausible scenario where those industries might change too. >> When to talk to companies in those industries that haven't been disrupted do you get a sense of complacency that ah well, we haven't been disrupted, We're going to wait and see, or do you see a sense of urgency? >> No, complacency is baked in for years of people saying, "We've heard all this before. "We're doing just fine. "Maybe it's their industry but not ours." >> Dave: You don't buy it. >> Or the main one is, "I'll be (laughing) retired "before any of this stuff matters for the senior execs." And the thing about all four of those is they're probably true. They have heard all this before because there was a lot of excessive hype. Many of them are doing just fine. Well the one about the other industries is a wrong one, but and many of them will be retired before the things really bite if executive's in their late in their career. So the inertia and the complacency is an enormous issue in most traditional companies. >> So let's do a little lightning round if we can. Oh, actually I just want to make a point. In the book you lay out disruption scenarios for each industry which is really worthwhile. We don't have time to go through that here, but let's do a little lightning round here, some of the questions that you ask that I'd love to get your opinion on of which of course there are no right answers but we can maybe frame it. Let's start with retail. Do you think large retail stores are going to disappear? >> Well the first I say is that disruption is never total. There are still bookstores, there are still newspapers, there are still vinyl records. >> Dave: Mainframes, saving IBM. >> (laughing) Indeed, indeed, but real disruption means that the center of gravity is just totally moved on. And when you look at retail from that point of view, absolutely. And will large ones totally disappear? No, but Wal-Mart is teetering. If you go into a large, Best Buy, a company that strong hero locally, you go into there, there's hardly anybody in there. And so those stores are in tremendous trouble. The grocery stores, the clothing stores, they'll have probably a better future, but by and large they will shrink, and the nature of malls will change quite substantially going forward. People are going to have to find other uses for those spaces, and that's actually going on right now. >> It's funny, it is, and certainly some of the more remote malls you find that they're waning. But then some of the higher-end malls, they seem, you can't find a parking space. What's your sense of that, that that's still inevitable or it's because it's more clothing or maybe jewelry? >> And there's some parts of America that have a lot of money, and therefore they fill up malls. But I think if you look at what's going on in the malls, though, they're becoming more like indoor cities full of restaurants and health clubs and movie theaters and sometimes even college courses and health care centers, daycare centers, air conditioning. Think of them as an indoor environment where you might have the traditional anchor stores but they're less necessary over time. Quite a bit less necessary. >> You mentioned college courses. Education's something we haven't talked about which is again ripe for disruption. Machines, will they make better diagnoses than doctors? >> Yeah, you see this already in image processing, anything that has to do with an image, X-rays and mammograms, cancers, anything, tissues. The machine learning progress there has been tremendous and to the point where schools now should be seriously thinking about how many radiologists do they really want to train because those people are not going to be needed as much. However they're still part of the system. They approve things, but the work itself is increasingly done by machines. And it means increasingly that it's not just done by machine, it's done by one machine somewhere else rather than every hospital setting up its own operations to do this stuff. And health care costs are crazy high in every country in the world, especially here in America. But if you're ever going to crack those costs you have to get some sort of scale, and these machine learning-based systems are the way to do it. And so it is to me not just a question of should this happen, it's that this is so what needs to happen. It's really the only sort of economic path that might work. >> You make the point that health care in particular is really ripe for disruption of all industries. The next one's really interesting to me. You talked about blockchain being sort of aimed at banking and financial services and as an industry that has not really yet been disrupted. But do you think banks will lose control of the payment systems? >> Banks have been incredibly good at keeping control through cash and paper checks and credit cards and ATM machines. They've been really good about that and perhaps they will ride this one too. But you can see countries are clearly going to, they're getting rid of cash. They're going to digital currencies. There's the need to be able to send money around as simply as we send emails around, and the banking industry is not really supporting (laughing) those changes right now. So they are at risk, but they are very good at co-opting stuff, and I wouldn't count them out. >> And the government really wants to get rid of paper money. You've made that point, and the government and the financial services-- >> Work together, and yeah. >> They always work together, they have a lot to lose. >> Yeah, and way back when Satoshi Nakamoto, whoever he or she is or it, they, whatever it is, said that bitcoin would either be very, very big or it would vanish altogether. And I think that statement is still true, and we're still in that middle world. But if bitcoin vanishes, something doing a similar thing will emerge because the concepts and the capabilities there are really what people want. >> Yeah, the killer app for blockchain is for right now it's money. (laughing) >> Yeah, it's speculation, (laughing) I mean it's, (laughing) and no one uses it to buy anything. (Dave laughing) That was the original bitcoin vision of using it to go buy pizzas and coffees. It's become gold, it's digital gold. I mean it's all it is. >> The value store... >> It's digital gold that is very good in the dark Web. >> And if anybody does transact in bitcoin they immediately convert it to fiat currency. (laughing) >> Perhaps someday we'll learn that the Russians actually built bitcoin (Dave laughing) and it's Putin's in control. (David and Dave laughing) Stranger things have happened. >> It's possible. >> Hey, why keep it anonymous? >> They are the masters of the dark Web. (Dave laughing) >> Could be Russians, could be a woman. >> David: Right, right, nobody has any idea. >> Robotic process automation is really interesting with software robots, robots. Do you see that reversing sort of offshoring, offshore manufacturing and other services? >> Not really, I think in general people looked at robotics, they looked at 3D printing and said, "Maybe we can bring all this stuff back home." But the reality is that China uses robots and 3D printing too and they're really good at it. If anything's going to bring manufacturing back home it's much more political pressures, trade strategies, and all the stuff you see going on right now because we do have crazy imbalances in the world that probably will have to change. And as Ben Stein the economist once said, "Well if something can't go on forever, it won't." And I think there will be some reversals, but I think they'll be less about technology than they will be about political pressures and trade agreements and those sort of changes. >> Because the technology's widely accessible. So how far do you think we can take machine intelligence and how far should we take machine intelligence? >> Well I make a distinction right now that I think machine intelligence for particular purposes is tremendous if you want to recognize faces or eventually talk to something or have it read something or recognize an activity or read images and do all the things it's doing, it's very good. When they talk about a more general-wise machine intelligence it's actually really poor. But to me that's not that important. And one way we look at machine intelligence, it's almost like the app industry. There'll be an app for that, there'll be a machine learning algorithm for almost every little thing that we do that involves data. And those areas will thrive mightily. And then sort of the bottom line we try to at that as who's got the best data? Facebook is good at facial recognitions because it's got the faces, and Google's good at language translation because it has the books and language pairs better than anybody else. And so if you follow the data and where there's good data machine learning will thrive. And where there isn't it won't. >> The book is called Seeing Digital: A Visual Guide to the Industries, Organizations, and Careers of the 2020s, and part of that visual guide is every single page actually has a graphic. So really a new concept that you've... >> Yeah, and thanks for bringing that in. And the reason the book is called Seeing Digital is that the book itself is a visual book, that every page has a graphic, an image, a picture, and explains itself below. And just in our own work with our own clients people tell us it's just a more impactful way of reading. So it's a different format. It's great in the ebook format because you can use colors, you can do lots of things that the printed world doesn't do so well. And so we tried to take advantage of modern technologies to bring a different sort of book to the market. >> That's great. So Google it and you'll find it easily. Dave, again, congratulations. Thanks so much for coming on theCube. >> David: Thank you, a pleasure. >> All right, and thank you for watching, everybody. We'll see you next time. (bright music)

>> Announcer: Live from midtown Manhattan, it's theCUBE covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and it's ecosystem sponsors. (upbeat techno music) >> Hey, welcome back, everyone. Here live in New York City, this is theCUBE from SiliconANGLE Media Special. Exclusive coverage of the Big Data World at NYC. We call it Big Data NYC in conjunction also with Strata Hadoop, Strata Data, Hadoop World all going on kind of around the corner from our event here on 37th Street in Manhattan. I'm John Furrier, the co-host of theCUBE with Peter Burris, Head of Research at SiliconANGLE Media, and General Manager of WikiBon Research. And our next guest is one of our famous CUBE alumni, Prakash Nanduri co-founder and CEO of Paxata who launched his company here on theCUBE at our first inaugural Big Data NYC event in 2013. Great to see you. >> Great to see you, John. >> John: Great to have you back. You've been on every year since, and it's been the lucky charm. You guys have been doing great. It's not broke, don't fix it, right? And so theCUBE is working with you guys. We love having you on. It's been a pleasure, you as an entrepreneur, launching your company. Really, the entrepreneurial mojo. It's really what it's all about. Getting access to the market, you guys got in there, and you got a position. Give us the update on Paxata. What's happening? >> Awesome, John and Peter. Great to be here again. Every time I come here to New York for Strata I always look forward to our conversations. And every year we have something exciting and new to share with you. So, if you recall in 2013, it was a tiny little show, and it was a tiny little company, and we came in with big plans. And in 2013, I said, "You know, John, we're going to completely disrupt the way business consumers and business analysts turn raw data into information and they do self-service data preparation." That's what we brought to the market in 2013. Ever since, we have gone on to do something really exciting and new for our customers every year. In '14, we came in with the first Apache Spark-based platform that allowed business analysts to do data preparation at scale interactively. Every year since, last year we did enterprise grade and we talked about how Paxata is going to be delivering our self-service data preparation solution in a highly-scalable enterprise grade deployment world. This year, what's super exciting is in addition to the recent announcements we made on Paxata running natively on the Microsoft Azure HDI Spark system. We are truly now the only information platform that allows business consumers to turn data into information in a multi-cloud hybrid world for our enterprise customers. In the last few years, I came and I talked to you and I told you about work we're doing and what great things are happening. But this year, in addition to the super-exciting announcements with Microsoft and other exciting announcements that you'll be hearing. You are going to hear directly from one of our key anchor customers, Standard Chartered Bank. 150-year-old institution operating in over 46 countries. One of the most storied banks in the world with 87,500 employees. >> John: That's not a start up. >> That's not a start up. (John laughs) >> They probably have a high bar, high bar. They got a lot of data. >> They have lots of data. And they have chosen Paxata as their information fabric. We announced our strategic partnership with them recently and you know that they are going to be speaking on theCUBE this week. And what started as a little experiment, just like our experiment in 2013, has actually mushroomed now into Michael Gorriz, and Shameek Kundu, and the entire leadership of Standard Chartered choosing Paxata as the platform that will democratize information in the bank across their 87,500 employees. We are going in a very exciting way, a very fast way, and now delivering real value to the bank. And you can hear all about it on our website-- >> Well, he's coming on theCUBE so we'll drill down on that, but banks are changing. You talk about a transformation. What is a teller? An Internet of Things device. The watch potentially could be a terminal. So, the Internet of Things of people changes the game. Are the ATMs going to go away and become like broadcast points? >> Prakash: And you're absolutely right. And really what it is about is, it doesn't matter if you're a Standard Chartered Bank or if you're a pharma company or if you're the leading healthcare company, what it is is that everyone of our customers is really becoming an information-inspired business. And what we are driving our customers to is moving from a world where they're data-driven. I think being data-driven is fine. But what you need to be is information-inspired. And what does that mean? It means that you need to be able to consume data, regardless of format, regardless of source, regardless of where it's coming from, and turn it into information that actually allows you to get inside in decisions. And that's what Paxata does for you. So, this whole notion of being information-inspired, I don't care if you're a bank, if you're a car company, or if you're a healthcare company today, you need to have-- >> Prakash, for the folks watching that might not know our history as you launched on theCUBE in 2013 and have been successful every year since. You guys have really deploying the classic entrepreneurial success formula, be fast, walk the talk, listen to customers, add value. Take a minute quickly just to talk about what you guys do. Just for the folks that don't know you. >> Absolutely, let's just actually give it in the real example of you know, a customer like Standard Chartered. Standard Chartered operates in multiple countries. They have significant number of lines of businesses. And whether it's in risk and compliance, whether it is in their marketing department, whether it's in their corporate banking business, what they have to do is, a simple example could be I want to create a customer list to be able to go and run a marketing campaign. And the customer list in a particular region is not something easy for a bank like Standard Charter to come up with. They need to be able to pull from multiple sources. They need to be able to clean the data. They need to be able to shape the data to get that list. And if you look at what is really important, the people who understand the data are actually not the folks in IT but the folks in business. So, they need to have a tool and a platform that allows them to pull data from multiple sources to be able to massage it, to be able to clean it-- >> John: So, you sell to the business person? >> We sell to the business consumer. The business analyst is our consumer. And the person who supports them is the chief data officer and the person who runs the Paxata platform on their data lake infrastructure. >> So, IT sets the data lake and you guys just let the business guys go to town on the data. >> Prakash: Bingo. >> Okay, what's the problem that you solve? If you can summarize the problem that you solve for the customers, what is it? >> We take data and turn it into information that is clean, that's complete, that's consumable and that's contextual. The hardest problem in every analytical exercise is actually taking data and cleaning it up and getting it ready for analytics. That's what we do. >> It's the prep work. >> It's the prep work. >> As companies gain experience with Big Data, John, what they need to start doing increasingly is move more of the prep work or have more of the prep work flow closer to the analyst. And the reason's actually pretty simple. It's because of that context. Because the analyst knows more about what their looking for and is a better evaluator of whether or not they get what they need. Otherwise, you end up in this strange cycle time problem between people in back end that are trying to generate the data that they think they want. And so, by making the whole concept of data preparation simpler, more straight forward, you're able to have the people who actually consume the data and need it do a better job of articulating what they need, how they need it and making it presentable to the work that they're performing. >> Exactly, Peter. What does that say about how roles are starting to merge together? Cause you've got to be at the vanguard of seeing how some of these mature organizations are working. What do you think? Are we seeing roles start to become more aligned? >> Yes, I do think. So, first and foremost, I think what's happening is there is no such thing as having just one group that's doing data science and another group consuming. I think what you're going to be going into is the world of data and information isn't all-consuming and that everybody's role. Everybody has a role in that. And everybody's going to consume. So, if you look at a business analyst that was spending 80% of their time living in Excel or working with self-service BI tools like our partner's Tableau and Power BI from Microsoft, others. What you find is these people today are living in a world where either they have to live in coding scripting world hell or they have to rely on IT to get them the real data. So, the role of a business analyst or a subject matter expert, first and foremost, the fact that they work with data and they need information that's a given. There is no business role today where you can't deal with data. >> But it also makes them real valuable, because there aren't a lot of people who are good at dealing with data. And they're very, very reliant on these people to turn that data into something that is regarded as consumable elsewhere. So, you're trying to make them much more productive. >> Exactly. So, four years years ago, when we launched on theCUBE, the whole premise was that in order to be able to really drive towards a world where you can make information and data-driven decisions, you need to ensure that the business analyst community, or what I like to call the business consumer needs to have the power of being able to, A, get access to data, B, make sense of the data, and then turn that data into something that's valuable for her or for him. >> Peter: And others. >> And others, and others. Absolutely. And that's what Paxata is doing. In a collaborative, in a 21st Century world where I don't work in a silo, I work collaboratively. And then the tool, and the platform that helps me do that is actually a 21st Century platform. >> So, John, at the beginning of the session you and Jim were talking about what is going to be one of the themes here at the show. And we observed that it used to be that people were talking about setting up the hardware, setting up the clutters, getting Hadoop to work, and Jim talked about going up the stack. Well, this is one of the indicators that, in fact, people were starting to go up the stack because they're starting to worry more about the data, what it can do, the value of how it's going to be used, and how we distribute more of that work so that we get more people using data that's actually good and useful to the business. >> John: And drives value. >> And drives value. >> Absolutely. And if I may, just put a chronological aspect to this. When we launched the company we said the business analyst needs to be in charge of the data and turning the data into something useful. Then right at that time, the world of create data lakes came in thanks to our partners like Cloudera and Hortonworks, and others, and MapR and others. In the recent past, the world of moving from on premise data lakes to hybrid, multicloud data lakes is becoming reality. Our partners at Microsoft, at AWS, and others are having customers come in and build cloud-based data lakes. So, today what you're seeing is on one hand this complete democratization within the business, like at Standard Chartered, where all these business analysts are getting access to data. And on the other hand, from the data infrastructure moving into a hybrid multicloud world. And what you need is a 21st Century information management platform that serves the need of the business and to make that data relevant and information and ready for their consumption. While at the same time we should not forget that enterprises need governance. They need lineage. They need scale. They need to be able to move things around depending on what their business needs are. And that's what Paxata is driving. That's why we're so excited about our partnership with Microsoft, with AWS, with our customer partnerships such as Standard Chartered Bank, rolling this out in an enterprise-- >> This is a democratization that you were referring to with your customers. We see this-- >> Everywhere. >> When you free the data up, good things happen but you don't want to have IT be the constraint, you want to let them enable-- >> Peter: And IT doesn't want to be the constraint. >> They don't. >> This is one of the biggest problems that they have on a daily basis. >> They're happy to let it go free as long as it's in they're mind DevOps-like related, this is cool for them. >> Well, they're happy to let it go with policy and security in place. >> Our customers, our most strategic customers, the folks who are running the data lakes, the folks who are managing the data lakes, they are the first ones that say that we want business to be able to access this data, and to be able to go and make use out of this data in the right way for the bank. And not have us be the impediment, not have us be the roadblock. While at the same time we still need governance. We still need security. We still need all those things that are important for a bank or a large enterprise. That's what Paxata is delivering to the customers. >> John: So, what's next? >> Peter: Oh, I'm sorry. >> So, really quickly. An interesting observation. People talk about data being the new fuel of business. That really doesn't work because, as Bill Schmarzo says, it's not the new fuel of business, it's new sunlight of business. And the reason why is because fuel can only be used once. >> Prakash: That's right. >> The whole point of data is that it can be used a lot, in a lot of different ways, and a lot of different contexts. And so, in many respects what we're really trying to facilitate or if someone who runs a data lake when someone in the business asks them, "Well, how do you create value for the business?" The more people, the more users, the more context that they're serving out of that common data, the more valuable the resource that they're administering. So, they want to see more utilization, more contexts, more data being moved out. But again, governance, security have to be in place. >> You bet, you bet. And using that analogy of data, and I've heard this term about data being the new oil, etc. Well, if data is the oil, information is really the refined fuel or sunlight as we like to call it. >> Peter: Yeah. >> John: Well, you're riffing on semantics, but the point is it's not a one trick pony. Data is part of the development, I wrote a blog post in 1997, I mean 2007 that said data's the new development kit. And it was kind of riffing on this notion of the old days >> Prakash: You bet. >> Here's your development kit, SDK, or whatever was how people did things back then Enter the cloud, >> Prakash: That's right. >> And boom, there it is. The data now is in the process of the refinery the developers wanted. The developers want the data libraries. Whatever that means. That's where I see it. And that is the democratization where data is available to be integrated in to apps, into feeds, into ... >> Exactly, and so it brings me to our point about what was the exciting, new product innovation announcement we made today about Intelligent Ingest. You want to be able to access data in the enterprise regardless of where it is, regardless of the cloud where it's sitting, regardless of whether it's on-premise, in the cloud. You don't need to as a business worry about whether that is a JSON file or whether that's an XML file or that's a relational file. That's irrelevant. What you want is, do I have the access to the right data? Can I take that data, can I turn it into something valuable and then can I make a decision out of it? I need to do that fast. At the same time, I need to have the governance and security, all of that. That's at the end of the day the objective that our customers are driving towards. >> Prakash, thanks so much for coming on and being a great member of our community. >> Fantastic. >> You're part of our smart network of great people out there and entrepreneurial journey continues. >> Yes. >> Final question. Just observation. As you pinch yourself and you go down the journey, you guys are walking the talk, adding new products. We're global landscape. You're seeing a lot of new stuff happening. Customers are trying to stay focused. A lot of distractions whether security or data or app development. What's your state of the industry? How do you view the current market, from your perspective and also how the customer might see it from their impact? >> Well, the first thing is that I think in the last four years we have seen significant maturity both on the providers off software technology and solutions, and also amongst the customers. I do think that going forward what is really going to make a difference is one really driving towards business outcomes by leveraging data. We've talked about a lot of this over the last few years. What real business outcomes are you delivering? What we are super excited is when we see our customers each one of them actually subscribes to Paxata, we're a SAS company, they subscribe to Paxata not because they're doing the science experiment but because they're trying to deliver real business value. What is that? Whether that is a risk in compliance solution which is going to drive towards real cost savings. Or whether that's a top line benefit because they know what they're customer 360 is and how they can go and serve their customers better or how they can improve supply chains or how they can optimize their entire efficiency in the company. I think if you take it from that lens, what is going to be important right now is there's lots of new technologies coming in, and what's important is how is it going to drive towards those top three business drivers that I have today for the next 18 months? >> John: So, that's foundational. >> That's foundational. Those are the building blocks-- >> That's what is happening. Don't jump... If you're a customer, it's great to look at new technologies, etc. There's always innovation projects-- >> RND, GPOCs, whatever. Kick the tires. >> But now, if you are really going to talk the talk about saying I'm going to be, call your word, data-driven, information-driven, whatever it is. If you're going to talk the talk, then you better walk the walk by delivering the real kind of tools and capabilities that you're business consumers can adopt. And they better adopt that fast. If they're not up and running in 24 hours, something is wrong. >> Peter: Let me ask one question before you close, John. So, you're argument, which I agree with, suggests that one of the big changes in the next 18 months, three years as this whole thing matures and gets more consistent in it's application of the value that it generates, we're going to see an explosion in the number users of these types of tools. >> Prakash: Yes, yes. >> Correct? >> Prakash: Absolutely. >> 2X, 3X, 5X? What do you think? >> I think we're just at the cusp. I think is going to grow up at least 10X and beyond. >> Peter: In the next two years? >> In the next, I would give that next three to five years. >> Peter: Three to five years? >> Yes. And we're on the journey. We're just at the tip of the high curve taking off. That's what I feel. >> Yeah, and there's going to be a lot more consolidation. You're going to start to see people who are winning. It's becoming clear as the fog lifts. It's a cloud game, a scale game. It's democratization, community-driven. It's open source software. Just solve problems, outcomes. I think outcome is going to be much faster. I think outcomes as a service will be a model that we'll probably be talking about in the future. You know, real time outcomes. Not eight month projects or year projects. >> Certainly, we started writing research about outcome-based management. >> Right. >> Wikibon Research... Prakash, one more thing? >> I also just want to say that in addition to this business outcome thing, I think in the last five years I've seen a lot of shift in our customer's world where the initial excitement about analytics, predictive, AI, machine-learning to get to outcomes. They've all come into a reality that none of that is possible if you're not able to handle, first get a grip on your data, and then be able to turn that data into something meaningful that can be analyzed. So, that is also a major shift. That's why you're seeing the growth we're seeing-- >> John: Cause it's really hard. >> Prakash: It's really hard. >> I mean, it's a cultural mindset. You have the personnel. It's an operational model. I mean this is not like, throw some pixie dust on it and it magically happens. >> That's why I say, before you go into any kind of BI, analytics, AI initiative, stop, think about your information management strategy. Think about how you're going to democratize information. Think about how you're going to get governance. Think about how you're going to enable your business to turn data into information. >> Remember, you can't do AI with IA? You can't do AI without information architecture. >> There you go. That's a great point. >> And I think this all points to why Wikibon's research have all the analysts got it right with true private cloud because people got to take care of their business here to have a foundation for the future. And you can't just jump to the future. There's too much just to come and use a scale, too many cracks in the foundation. You got to do your, take your medicine now. And do the homework and lay down a solid foundation. >> You bet. >> All right, Prakash. Great to have you on theCUBE. Again, congratulations. And again, it's great for us. I totally have a great vibe when I see you. Thinking about how you launched on theCUBE in 2013, and how far you continue to climb. Congratulations. >> Thank you so much, John. Thanks, Peter. That was fantastic. >> All right, live coverage continuing day one of three days. It's going to be a great week here in New York City. Weather's perfect and all the players are in town for Big Data NYC. I'm John Furrier with Peter Burris. Be back with more after this short break. (upbeat techno music).

>> Narrator: From the Fairmont Hotel in the heart of Silicon Valley it's theCUBE covering when IoT met AI, The Intelligence of Things. Brought to you by Western Digital. >> Hey welcome back here everybody Jeff Frick here with theCUBE. We're in San Jose, California at the Fairmont Hotel, at the when IoT met AI show, it's all about the intelligence of things. A lot of really interesting start ups here, we're still so early days in most of this technology. Facial recognition gets a lot of play, iris recognition, got to get rid of these stupid passwords. We're really excited to have our next guest, he's Modar Alaoui, he's the CEO and founder of Eyeris. And it says here Modar that you guys are into face analytics and emotion recognition. First off welcome. >> Thank you so much for having me. >> So face analytics, I'm a clear customer I love going to clear at the airport, I put my two fingers down, I think they have my iris, they have different things but what's special about the face compared to some of these other biometric options that people have? >> We go beyond just the biometrics, we do pretty much the entire suites of face analytics. Anything from eye openness, face, gender, emotion recognition, head bows, gaze estimation, et cetera et cetera. So it is pretty much anything and everything you can derive from the face including non verbal clues, yawning, head nod, head shake, et cetera. >> That was a huge range of things, so clearly just the face recognition to know that I am me probably relatively straight forward. A couple anchor points, does everything measure up and match the prior? But emotion that's a whole different thing, not only are there lots of different emotions, but the way I express my emotion might be different than the way you express the very same emotion. Right, everybody has a different smile. So how do you start to figure out the algorithms to sort through this? >> Right, so you're right. There are some nuances between cultures, ages, genders, ethnicities and things like that. Generally they've been universalized for the past three and a half decades by the scholars the psychologists et cetera. So what they actually have a consensus on is that there are only seven or six universal emotions plus neutral. >> Six, what are the six? >> Joy, surprise, anger, disgust, fear, sadness, and neutral. >> Okay and everything is some derivation of that, you can kind of put everything into little buckets. >> That is correct so think of them as seven universal colors or seven primary colors and then everything else is a derivative of that. The other thing is that emotions are hard wired into our brain they happen in a 1/15th or a 1/25th of a second, particularly micro expressions. And they can generally give up a lot of information as to whether a person has suppressed the certain emotion or not or whether they are thinking about something negatively before they could respond positively, et cetera. >> Okay so now you've got the data, you know how I'm feeling, what are you doing with it? It must tie back to all types of different applications I would assume. >> That's right there are a number of applications. Initially when we created this, what we call, enabling technology we wanted to focus on two things. One, is what type of application could have the biggest impact but also the quickest adoption in terms of volumes. Today we focus on driver monitoring AI as well as occupants monitoring AI so we focus on Autonomous and semi autonomous vehicles. And a second application is social robotics, but in essence if you think of a car it's also another robot except that social robotics are those potentially AI engines, or even AI engines in form of an actual robot that communicates with humans. Therefore, the word social. >> Right, so I can see a kind of semi autonomous vehicle or even a not autonomous vehicle you want to know if I'm dosing off. And some of those things have been around in a basic form for a little while. But what about in an autonomous vehicle is impacted by my emotion as a passenger, not necessarily a driver if it's a level five? >> That's right, so when we talk about an autonomous vehicle I think what you're referring to is level five autonomy where a vehicle does not actually have a steering wheel or gas pedal or anything like that. And we don't foresee that those will be on a road for at least another 10 years or more. The focus today is on level two, three, and four, and that's semi autonomy. Even for autonomous, fully autonomous vehicles, you would see them come out with vision sensors or vision AI inside the vehicle. So that these sensors could, together with the software that could analyze everything that's happening inside, cater to the services towards what is going to be the ridership economy. Once the car drives itself autonomously, the focus shifts from the driver to the occupants. As a matter of a fact it's the occupants that would be riding in these vehicles or buying them or sharing them, not the driver. And therefore all these services will revolve around who is inside the vehicle like age, gender emotion, activity, et cetera. >> Interesting, so all these things the age, gender emotion, activity, what is the most important do you think in terms of your business and kind of where as you say you can have a big impact. >> We can group them into two categories, the first one is safety obviously, eye openness, head bows, blinking, yawning, and all these things are utmost importance especially focused on the driver at this point. But then there is a number of applications that relates to comfort and personalization. And so those could potentially take advantage of the emotions and the rest of the analytics. >> Okay, so then where are you guys, Eyeris as a company? Where do have some installations I assume out there? Are you still early days kind of? Where are you in terms of the development of the company? >> We have quite a mature product, what I can disclose is we have plans to go into mass production starting 2018. Some plans for Q4 2017 have been pushed out. So we'll probably start seeing some of those in Q1, Q2 2018. >> Okay. >> We made some announcements earlier this year at CS with Toyota and Honda. But then we'll be seeing some mass volume starting 2019 and beyond. >> Okay, and I assume you're a cloud based solution. >> We do have that as well, but we are particularly a local processing solution. >> Jeff: Oh you are? >> Yes so think of it as an edge computing type of solution. >> Okay and then you work with other peoples sensors and existing systems or are you more of a software component that plugs in? Or you provide the whole system in terms of the, I assume, cameras to watch the people? >> So we're a software company only, we however, are hardware processor camera diagnostic. And of course for everything to succeed there will have to be some components of sensor fusion. And therefore we can work and do work with other sensor companies in order to provide higher confidence level of all the analytics that we provide. >> Pretty exciting, so is it commercially available you're GA now or not quite yet? >> We'll be commercially available, you'll start seeing it on the roads or in the market sometime early next year. >> Sometime early next year? Alright well we will look forward to it. >> Thank you so much. >> Very exciting times, alright, he's Modar Alaoui. And he's going to be paying attention to you to make sure you're paying attention to the roads. So you don't fall asleep, or doze off and go to sleep. So I'm Jeff Frick, you're watching theCUBE at IoT met AI, The Intelligence of Things. San Jose, California, we'll be right back after this short break, thanks for watching. (bright techno music)