>> Hey everyone, welcome to theCUBE's coverage of the AWS startup showcase. This is season two, episode three of our ongoing series featuring AWS and its big ecosystem of partners. This particular season is focused on MarTech, emerging cloud scale customer experiences. I'm your host, Lisa Martin, and I'm pleased to be joined by James Fang, the VP of product marketing at mparticle. James, welcome to the program. Great to have you on. >> Thanks for having me. >> Tell us a little bit about mparticle, what is it that you guys do? >> Sure, so we're mparticle, we were founded in 2013, and essentially we are a customer data platform. What we do is we help brands collect and organize their data. And their data could be coming from web apps, mobile apps, existing data sources like data warehouses, data lakes, et cetera. And we help them help them organize it in a way where they're able to activate that data, whether it's to analyze it further, to gather insights or to target them with relevant messaging, relevant offers. >> What were some of the gaps in the market back then as you mentioned 2013, or even now, that mparticle is really resolving so that customers can really maximize the value of their customer's data. >> Yeah. So the idea of data has actually been around for a while, and you may have heard the buzzword 360 degree view of the customer. The problem is no one has really been actually been able to, to achieve it. And it's actually, some of the leading analysts have called it a myth. Like it's a forever ending kind of cycle. But where we've kind of gone is, first of all customer expectations have really just inflated over the years, right? And part of that was accelerated due to COVID, and the transformation we saw in the last two years, right. Everyone used to, you know, have maybe a digital footprint, as complimentary perhaps to their physical footprint. Nowadays brands are thinking digital first, for obvious reasons. And the data landscape has gotten a lot more complex, right? Brands have multiple experiences, on different screens, right? And, but from the consumer perspective, they want a complete end to end experience, no matter how you're engaging with the brand. And in order to, for a brand to deliver that experience they have to know, how the customers interacted before in each of those channels, and be able to respond in as real time as possible, to those experiences. >> So I can start an interaction on my iPad, maybe carry it through or continue it on my laptop, go to my phone. And you're right, as a, as a consumer, I want the experience across all of those different media to be seamless, to be the same, to be relevant. You talk about the customer 360, as a marketer I know that term well. It's something that so many companies use, interesting that you point out that it's really been, largely until companies like mparticle, a myth. It's one of those things though, that everybody wants to achieve. Whether we're talking about healthcare organization, a retailer, to be able to know everything about a customer so that they can deliver what's increasingly demanded that personalized, relevant experience. How does mparticle fill some of the gaps that have been there in customer 360? And do you say, Hey, we actually deliver a customer 360. >> Yeah, absolutely. So, so the reason it's been a myth is for the most part, data has been- exists either in silos, or it's kind of locked behind this black box that the central data engineering team or sometimes traditionally referred to as IT, has control over, right? So brands are collecting all sorts of data. They have really smart people working on and analyzing it. You know, being able to run data science models, predictive models on it, but the, the marketers and the people who want to draw insights on it are asking how do I get it in, in my hands? So I can use that data for relevant targeting messaging. And that's exactly what mparticle does. We democratize access to that data, by making it accessible in the very tools that the actual business users are are working in. And we do that in real time, you don't have to wait for days to get access to data. And the marketers can even self-service, they're able to for example, build audiences or build computed insights, such as, you know, average order value of a customer within the tool themselves. The other main, the other main thing that mparticle does, is we ensure the quality of that data. We know that activation is only as as good, when you can trust that data, right? When there's no mismatching, you know, first name last names, identities that are duplicated. And so we put a lot of effort, not only in the identity resolution component of our product but also being able to ensure that the consistency of that data when it's being collected meets the standard that you need. >> So give us a, a picture, kind of a topology of a, of a customer data platform. And what are some of the key components that it contains, then I kind of want to get into some of the use cases. >> Yeah. So at, at a core, a lot of customer data platforms look similar. They're responsible first of all for the collection of data, right? And again, that could be from web mobile sources, as well as existing data sources, as well as third party apps, right? For example, you may have e-commerce data in a Shopify, right. Or you may have, you know, a computer model from a, from a warehouse. And then the next thing is to kind of organize it somehow, right? And the most common way to do that is to unify it, using identity resolution into this idea of customer profiles, right. So I can look up everything that Lisa or James has done, their whole historical record. And then the third thing is to be able to kind of be able to draw some insights from that, whether to be able to build an audience membership on top of that, build a predictive model, such as the churn risk model or lifetime value of that customer. And finally is being able to activate that data, so you'll be able to push that data again, to those relevant downstream systems where the business users are actually using that data to, to do their targeting, or to do more interesting things with it. >> So for example, if I go to the next Warrior's game, which I predict they're going to win, and I have like a mobile app of the stadium or the team, how, and I and I'm a season ticket holder, how can a customer data platform give me that personalized experience and help to, yeah, I'd love to kind of get it in that perspective. >> Yeah. So first of all, again, in this modern day and age consumers are engaging with brands from multiple devices, and their attention span, frankly, isn't that long. So I may start off my day, you know, downloading the official warriors app, right. And I may be, you know browsing from my mobile phone, but I could get distracted. I've got to go join a meeting at work, drop off my kids or whatever, right? But later in the day I had in my mind, I may be interested in purchasing tickets or buying that warriors Jersey. So I may return to the website, or even the physical store, right. If, if I happen to be in the area and what the customer data platform is doing in the background, is associating and connecting all those online and offline touchpoints, to that user profile. And then now, I have a mar- so let's say I'm a marker for the golden state warriors. And I see that, you know, this particular user has looked at my website even added to their cart, you know, warriors Jersey. I'm now able to say, Hey, here's a $5 promotional coupon. Also, here's a special, limited edition. We just won, you know, the, the Western conference finals. And you can pre-book, you know, the, you know the warriors championships Jersey, cross your fingers, and target that particular user with that promotion. And it's much more likely because we have that contextual data that that user's going to convert, than just blasting them on a Facebook or something like that. >> Right. Which all of us these days are getting less and less patient with, Is those, those broad blasts through social media and things like that. That was, I love that example. That was a great example. You talked about timing. One of the things I think that we've learned that's in very short supply, in the last couple of years is people's patience and tolerance. We now want things in nanoseconds. So, the ability to glean insights from data and act on it in real time is no longer really a nice to have that's really table stakes for any type of organization. Talk to us about how mparticle facilitates that real time data, from an insights perspective and from an activation standpoint. >> Yeah. You bring up a good point. And this is actually one of the core differentiators of mparticle compared to the other CDPs is that, our architecture from the ground up is built for real time. And the way we do that is, we use essentially a real time streaming architecture backend. Essentially all the data points that we collect and send to those downstream destinations, that happens in milliseconds, right? So the moment that that user, again, like clicks a button or adds something to their shopping cart, or even abandons that shopping cart, that downstream tool, whether it's a marketer, whether it's a business analyst looking at that data for intelligence, they get that data within milliseconds. And our audience computations also happens within seconds. So again, if you're, if you have a targeted list for a targeted campaign, those updates happen in real time. >> You gave an- you ran with the Warrior's example that I threw at you, which I love, absolutely. Talk to me. You must have though, a favorite cu- real world customer example of mparticle's that you think really articulates the value to organizations, whether it's to marketers operators and has some nice, tangible business outcomes. Share with me if you will, a favorite customer story. >> Yeah, definitely one of mine and probably one of the- our most well known's is we were actually behind the scenes of the Whopper jr campaign. So a couple of years ago, Burger King ran this really creative ad where the, effectively their goal was to get their mobile app out, as well as to train, you know, all of us back before COVID days, how to order on our mobile devices and to do things like curbside checkout. None of us really knew how to do that, right. And there was a challenge of course that, no one wants to download another app, right? And most apps get downloaded and get deleted right out away. So they ran this really creative promotion where, if you drove towards a McDonald's, they would actually fire off a text message saying, Hey, how about a Whopper for 99 cents instead? And you would, you would, you would receive a text message personalized just for you. And you'd be able to redeem that at any burger king location. So we were kind of the core infrastructure plumbing the geofencing location data, to partner of ours called radar, which handles you geofencing, and then send it back to a marketing orchestration vendor to be able to fire that targeted message. >> Very cool. I, I, now I'm hungry. You, but there's a fine line there between knowing that, okay, Lisa's driving towards McDonald's let's, you know, target her with an ad for a whopper, in privacy. How do you guys help organizations in any industry balance that? Cause we're seeing more and more privacy regulations popping up all over the world, trying to give consumers the ability to protect either the right to forget about me or don't use my data. >> Yeah. Great question. So the first way I want to respond to that is, mparticle's really at the core of helping brands build their own first party data foundation. And what we mean by that is traditionally, the way that brands have approached marketing is reliant very heavily on second and third party data, right? And most that second-third party data is from the large walled gardens, such as like a Facebook or a TikTok or a Snapchat, right? They're they're literally just saying, Hey find someone that is going to, you know fit our target profile. And that data is from people, all their activity on those apps. But with the first party data strategy, because the brand owns that data, we- we can guarantee that or the brands can guarantee to their customers it's ethically sourced, meaning it's from their consent. And we also help brands have governance policies. So for example, if the user has said, Hey you're allowed to collect my data, because obviously you want to run your business better, but I don't want any my information sold, right? That's something that California recently passed, with CPRA. Then brands can use mparticle data privacy controls to say, Hey, you can pass this data on to their warehouses and analytics platforms, but don't pass it to a platform like Facebook, which potentially could resell that data. >> Got it, Okay. So you really help put sort of the, the reigns on and allow those customers to make those decisions, which I know the mass community appreciates. I do want to talk about data quality. You talked about that a little bit, you know, and and data is the lifeblood of an organization, if it can really extract value from it and act on it. But how do you help organizations maintain the quality of data so that what they can do, is actually deliver what the end user customer, whether it's a somebody buying something on a, on a eCommerce site or or, a patient at a hospital, get what they need. >> Yeah. So on the data quality front, first of all I want to highlight kind of our strengths and differentiation in identity resolution. So we, we run a completely deterministic algorithm, but it's actually fully customizable by the customer depending on their needs. So for a lot of other customer data providers, platform providers out there, they do offer identity resolution, but it's almost like a black box. You don't know what happens. And they could be doing a lot of fuzzy matching, right. Which is, you know, probabilistic or predictive. And the problem with that is, let's say, you know, Lisa your email changed over the years and CDP platform may match you with someone that's completely not you. And now all of a sudden you're getting ads that completely don't fit you, or worse yet that brand is violating privacy laws, because your personal data is is being used to target another user, which which obviously should not, should not happen, right? So because we're giving our customers complete control, it's not a black box, it's transparent. And they have the ability to customize it, such as they can specify what identifiers matter more to them, whether they want to match on email address first. They might've drawn on a more high confidence identifier like a, a hash credit card number or even a customer ID. They have that choice. The second part about ensuring data quality is we act actually built in schema management. So as those events are being collected you could say that, for example, when when it's a add to cart event, I require the item color. I require the size. Let's say it's a fashion apparel. I require the size of it and the type of apparel, right? And if, if data comes in with missing fields, or perhaps with fields that don't match the expectation, let's say you're expecting small, medium, large and you get a Q, you know Q is meaningless data, right? We can then enforce that and flag that as a data quality violation and brands can complete correct that mistake to make sure again, all the data that's flowing through is, is of value to them. >> That's the most important part is, is to make sure that the data has value to the organization, and of course value to whoever it is on the other side, the, the end user side. Where should customers start, in terms of working with you guys, do you recommend customers buy an all in one marketing suite? The best, you know, build a tech stack of best of breed? What are some of those things that you recommend for folks who are going, all right, We, maybe we have a CDP it's been under delivering. We can't really deliver that customer 360, mparticle, help us out. >> Yeah, absolutely. Well, the best part about mparticle is you can kind of deploy it in phases, right. So if you're coming from a world where you've deployed a, all in one marketing suite, like a sales force in Adobe, but you're looking to maybe modernize pieces of a platform mparticle can absolutely help with that initial step. So let again, let's say all you want to do is modernize your event collection. Well, we can absolutely, as a first step, for example, you can instrument us. You can collect all your data from your web and mobile apps in real time, and we can pipe to your existing, you know Adobe campaign manager, Salesforce, marketing cloud. And later down the line, let's say, you say I want to, you know, modernize my analytics platform. I'm tired of using Adobe analytics. You can swap that out, right again with an mparticle place, a marketer can or essentially any business user can flip the switch. And within the mparticle interface, simply disconnect their existing tool and connect a new tool with a couple of button clicks and bam, the data's now flowing into the new tool. So it mparticle really, because we kind of sit in the middle of all these tools and we have over 300 productized prebuilt integrations allows you to move away from kind of a locked in, you know a strategy where you're committed to a vendor a hundred percent to more of a best of breed, agile strategy. >> And where can customers that are interested, go what's your good and market strategy? How does that involve AWS? Where can folks go and actually get and test out this technology? >> Yeah. So first of all, we are we are AWS, a preferred partner. and we have a couple of productized integrations with AWS. The most obvious one is for example, being able to just export data to AWS, whether it's Redshift or an S3 or a kinesis stream, but we also have productized integrations with AWS, personalized. For example, you can take events, feed em to personalize and personalize will come up with the next best kind of content recommendation or the next best offer available for the customer. And mparticle can ingest that data back and you can use that for personalized targeting. In fact, Amazon personalize is what amazon.com themselves use to populate the recommended for use section on their page. So brands could essentially do the same. They could have a recommended for you carousel using Amazon technology but using mparticle to move the data back and forth to, to populate that. And then on top of that very, very soon we'll be also launching a marketplace kind of entry. So if you are a AWS customer and you have credits left over or you just want to transact through AWS, then you'll have that option available as well. >> Coming soon to the AWS marketplace. James, thank you so much for joining me talking about mparticle, how you guys are really revolutionizing the customer data platform and allowing organizations and many industries to really extract value from customer data and use it wisely. We appreciate your insights and your time. >> Thank you very much, Lisa >> For James Fang, I'm Lisa Martin. You're watching theCube's coverage of the AWS startup showcase season three, season two episode three, leave it right here for more great coverage on theCube, the leader in live tech coverage.

>>live from Las Vegas. It's the Q covering AWS executive. Something brought to you by extension. >>Welcome back, everyone to the cubes. Live coverage of the ex Censure Executive Summit here in AWS. Reinvent I'm your host, Rebecca Knight. We have three guests for this segment. We have Fang Deng. She is the big data and an Advanced Analytics program. Lead analytic Seo hee at Novartis. Thank you so much for coming on the show. Thank you. We have low eq zero. He is Novartis head of Analytic Seo Hee. Thanks so much. Look, and Vika sinned. Wan Hee hee is applied intelligence delivery lead at Accenture. Thank you so much. Thank you. So I want to start with you. Look, no. Novartis, of course, is a household name. It's one of the largest pharmaceutical companies in the world. But that left you to just walk our viewers a little bit through your business and sort of the pain points you were looking to solve with this journey Thio to the cloud >>you think you ever care? So I think if I if we look at the company, I think Wayne realized that it is more and more difficult to bring new trucks to market, so it takes about 12 years and on $1.2 billion to find a new trick. So at the same time, we see that there's more and more patient that need access to medicines. So in the last two years, I think we tried toe clear the new strategy where we're trying to re imagine medicine for user's data and technology. So in 2018 we've recruited a new studio that's came and I tried to build a digital ambition which is around fabulous, which is the innovation, the operation and the engagement on the innovation. What we're trying to do is to find new compound, will application off existing compounds into our business, make sure that I think patients can get access to drugs much faster and earlier on in the operation. We are trying to optimize the backbone off day to day processes, beat in the manufacturing or in the supply chain, or in the commercialization to ensure that the patient also get access to that much faster in the engagement. We're trying to healthy a cheapie and the players and then the and the patients to better understand the tracks reproduce as well as on the medication they need to have to receive treatment. So if you look at these three pillars, the cloud strategy is an essential portion of it. Because in all of its processes we have a lot of data and full cloud. I think we can make use off his data to help to innovate, open, right and engage. >>So as you as you said, it's really about reimagining medicine. I mean, from the drug discovery process to how it's helping patients live, live longer, healthier lives. Thanks. So talk about the vision for the Formula One platform. >>Yeah, aside, like a mission before we trying to re imagine our products for the patient. And we're trying to use more the more data history data and also the public data try to support our products. And the Formula One is our future enterprise data and the next perform for our new artists. So our objective is trying to love you all the new technology and also trying to consolidate over data in our Macleod and build up this platform for the whole notice Users support our business, do better products full patient. >>So when it comes to these these new new platforms, new technologies that are being introduced. We know that oftentimes the technology is the easy part. Or at least the more straightforward part I should say. But it's it's sort of getting people on board the change management. What are some of the challenges that you that you know of artists faced in terms of of the culture and the skills for your for your workforce? >>So if you look at that, the are in disgrace, very traditionally nature. And when we embarking the details confirmation, I think the first thing we had to change the culture of the company. So when you when you listen to our CEO, I think you tried to promote this invoice culture where all of us are Syrian leaders. And then we walk, you know, as a thing as an organization where we try to help each other and more and more collaborate when it comes to digital transformation. When we started this having this period, we've realised actually that workforce was not trained, so the first few things that we did disease is a tight wire new workforce, but also try to actually identify the advocate ambassadors. I could go and then go into residual confirmation early on to be able to help and to guide the office to get for that. So it's actually it's totally immaterial, Johnny. And then we are now in the second year and we've seen already a tremendous four guys, right? >>Can you describe some of the changes that you've seen him? I mean, I'm really interested in what you talk about. The ambassador's, the people who are going to spread the good word. What are what are some of the changes that you've seen in your workforce? Yeah, we can mention >>that. It's like you mentioned before. Um, like, talking about regarding overall catch a bus back to tried to leverage a new attack. Knowledge like the delivery perspective. We trying to do more automation, and the May 1 side is trying to get more efficiency and also another side. Try to ensure the intern responsibility for one product to be produced and also at the same time, let me through more automation to think about this secret inside the compound inside. Help us a lot of in pulling that part also, because >>maybe I can compliment that so I think if you look at it when the initial studying part of our journey, I think that a lot of people were reluctant to go and then tie to work on a cloud and to work with digital technology. So we found few projects where we felt there's a good ready for money. And as we can deliver fast in fact, Andi to things like, I don't get reviewed t piece every. Make sure that when we went, our field falls, go then and talk to the hippies. They know what to talk about an orphan, and then which format. We also look at that we can reduce costs internally and for the food, different projects and then on product that we've established, we build credibility within the organization that helped to disseminate the cultural transformation. >>So once others air seeing, seeing the benefits that that captured, they're more likely to to feel good about the cloud work. >>Yeah, that's that's the true and also notes of the news. Things like our teams, they are interesting about that. You see more and more people talking about our driveway and also talk about the UAV's and how can we improve the did he re efficiency and the same time is come back to say that teams think about how to make themselves to be a product owner and the product the way of the great. Let's the glistening for the whole team >>because I want to bring you in here a little bit. So talk to me about how ex Center is helping Novartis, particularly in in this eight of us. Caught initiative. >>Six incher is a leader in business and technical i t transformation programmes. So what we're bringing on the table is in the expertise with not only the technology and the AWS elements, but also the business and technical transformation expertise that have we have over the years in the firm. On additionally, I think you know, it's not only about technology change. As you mentioned, it's all a lot of change and operating model and and also kind of working with a very blended team. Across that expertise and experience is what you bring to the table >>a blended team, culturally, regionally, actually, all of it >>one of that belief. I mean, just to give an example. We are working across steams in roughly about six geography ese from various cultures. Where's countries? And it's it's, ah, various time zones, which makes it quite challenging to make it all work together. So you started the journey. I hope you succeed in it. And, uh, you know, it's working well, so far, >>so Cloud is is really a megatrend right now. What are the differences that you're seeing across Regions, countries, industries? >>So I think it's this many answers many parts of the answer to the question. So I think if I talk about, um, industries So you know, initially when clouds started, we had seen a major up take off the cloud technology and the company that manufactured the clown technology and telecommunications, and you know where the older infrastructure and technology aspects were, Whereas companies like health care and media and metals and mining, We're kind of behind the curve in adoption rates because off their respective, you know, concerns around compliance and security of data. But I think that trends is slowly shifting. US. Companies are becoming more open. I think I've seen how the public cloud has matured. The security models, you know, are speaking for themselves. People can understand the benefits from moving to the cloud in terms off, you know, cost rationalization from producing maintenance costs, focusing their proteins on things that they were not able to divert their attention on. >>The fact we had, I think I will say for me and then where I've seen a Novartis if it is access to innovation. So I think loud offering brings a lot off innovation at happy face. That's one hand and also access to extend our collaboration. So when you're in, you know, inside focus I think the relatives from over there wants to walk and collaborate with you. But when you work on the cloud, everybody goes on the cloud. So that's really a stream manifested ate a collaboration with Nextel Partners. >>So how is that changing the culture of Novartis itself? In terms of there, there are more opportunities to collaborate. And it also is maybe changing the kinds of workers you attract because it is is people who want to be doing that in their day to day. >>Well, if you look at it, um, in the past, I think we used to have our own workforce, and then we tried to do a lot of things with our own workers, but I think he's in the on Monte. Workers are full of us, so we have more and more partnerships being announced, and this publishing, I mean used actually to help the company to in revenge himself. So that's actually on one hand on the other side. As you said, I think that to attract with talents I think you need. You also need to have a different future. But you need also to be able to give them the flexibility to work and do the things they like, and we're in a context and a framework. >>One of the things that we hear about so much at the's technology conference is this buzzword of digital transformation and of artisans obviously embarking on its own digital transformation as well as his journey to the cloud. There happen. They're powering each other, they're accelerating each other. How would you describe what is happening to the industry and to know Vargas with it within this, the pharmaceutical industry? >>Yeah, I think, based on our knowledge, to send the why this may be the first. The company can't be trying to build this kind of enterprise level data and also an Alex platform, and based on that, we will be able to counseling date off the history potato intended date on public date, huh? And the Human Industry Day. Then they tried to help us to produce the better products for the patient the same time it gave also the team a chance as you mentioned before, and the look at former more opportunities and the China to leverage in your technology particles of Kayla. >>It's also changed the way that we work every day. So if you look at it now, um, we won't be virtual assistant. We I think we use machine learning elements politics to be able to talkto you are a cheap piece. We actually monitor clickers, Kyle real time having using common centers. So every single day, I think the use off, digital at work and atom in the physical man thinks. And I think we have seen that the adoptions has increased since we have I ever to launch successful products. And I think >>one of the things which, which I really like about working in the bodies, is also I think there's there's an ambition to drive business value quickly. So you know you take a very agile use case, best approach on things rather than having to wait for very long years of time. Plus, the company kind of encourages a culture which is based on mutual cooperation and sharing knowledge, which is great >>because Novartis is really on the vanguard of companies in terms of how much it's embraced, the cloud and how much it's using it. What do you think? Other companies, pharmaceutical companies, but maybe even in other industries as well could learn from the nerve artists example. >>I think one thing people really shy about is, you know, when they moved to the cloud is the security aspect. I think what people probably had failed to realize in the past that there's been so much developments on security in the public cloud, which has bean key focus areas, something nobody's has taken the challenge and has understood that very well. And I think companies can learn from all the different aspects of security that you know were built into our entire transformation work, starting from ingesting data, the user management to access and all of that thing, so that's kind of one thing. Similarly, compliance related aspects as well, you know, So we've g x p compliance is at the core off how we're building our solution. So I think on dhe, if you understand how we built the rules around compliance. But in architecture, I think couples can learn from that a swell and build that is integral part off your not only technology solution, but the process that goes along with it. >>We started our conversation talking about Novartis and its quest to reimagine medicine. How How do you think that your industry is gonna look 5 10 years from now? I mean, the drug discovery process is slow on purpose. I mean, we need to think of patient health and safety for most. But how do you think it really could change the course of how we treat people? >>If if you look at it is more and more treatment required that actually I used and required data as a service or are being actually process for data. So when I am, when we look at the things the way that the industry is changing, I think the times to develop drugs, yes, takes longer. But I think for your use off the data that you have. I think you can try to reduce I cycle. So one of the objective is to reduce the cycle by one firm. Between that, we could bring the day. Is a new director market in eight years, rescues 12 years Today. The other thing is that way for user's data. You can monitor them patient, and you can recommend it the treatment of 80% off foundation. They don't go in and finish her treatment. So I think if we can show the audience to treatment, then there's a lower risk off the admissions to the season and sickness that they have. >>So it's not even not not just Novartis seeing the value of the date. It's the patients themselves, efficiency >>and the d. A r C as well, right? Because I think if you're if the situation is not six and I think the insurance doesn't have to pay. So I think all the value chances is being comes from >>well, sang Loic, because thank you so much for coming on the Cube. It was a really fascinating segment. Thank you. I'm Rebecca night. Stay tuned for more of the cubes. Live coverage of the Ex Center Executive Summit coming up in just a little bit

>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service is >> Welcome back. I'm stupid like co host Cory Quinn. And we're here at the end of a summit in New York City, where I'm really happy to welcome to the program first time guests, but somebody that has a nap, it's on my phone. So, Andy thing, who's the CEO of Door Dash, gave a great presentation this morning. Thanks so much for joining us. >> Absolutely happy to be here, guys. >> All right, so, you know, before we dig into the kind of your Amazon stack, bring us back. You talked about 2013. You know, your mission of the company will help empower local businesses. I think most people know, you know, door dash delivery from my local businesses. Whether that is a small place or, you know, chipotle o r like there. And I love little anecdote that you said the founders actually did the first few 100 deliveries, but it gives a little bit of the breath of the scope of the business now. >> Absolutely. I mean, when we started in 2013 you know, we started out of Ah dorm on Stanford campus and, like you said, we're doing the first couple 100 deliveries ourselves. But, you know, fast forwarding to today you were obviously at a much, much different level of scale. And I think one thing that I mentioned about it, Mikey No, a cz just We've been trying to keep up pays and more than doubling as a business every year. And it's a really fascinating industry that were in in the on demand delivery space in particular, I mean, Dara, the CEO of uber himself, said in May, which is a month and 1/2 ago. He said that you know, the food delivery industry may become bigger than a ride hailing industry someday. >> So just just one quick question on kind of food delivery. Because when I think back when I was in college, I worked at a food truck. It was really well known on campus, and there are people that 20 years later they're like stew. I remember you serving me these sandwiches, and I loved it in the community and we gather and we talk today on campus. Nobody goes to that place anymore, you know, maybe I know my delivery person more than I know the person that's making it. So I'm just curious about the relationship between local businesses and the people. How that dynamic changing the gig? Economy? I mean, yeah, you guys were right in the thick of it. No, it's a >> great question. I think. You know, for merchants, a lot of the things that we talk to them about it is you're actually getting access to customers who wouldn't even walk by your store in the first place. And I think that's something that they find to be very captivating. And it shows in the store sales data when they start partnering with the door dash. But we've also tried to building our products to really get customers to interact with the physical neighborhoods. Aaron the most concrete example of that as we launch a product called In Store in Star Pickup Chronic, where you can order online, skip the line and pick up the order yourself in the store, and I think a way we can build the AB experience around that, you know, you're gonna actually start building kind of a geospatial. Browse experience for customers with the door dash app, which means that they can get a little bit more familiarity with what's around them, as opposed to just kind of looking at it on their phones themselves. All right, >> so the logistics of this, you know, are not trivial. You talked about 325% order growth. You know, your database is billions of rose. You know, just the massive scale massive transaction. Therefore, you know, as a you know, your nap on. You know the scale you're at technology is pretty critical to your environment. So burgers inside that a little? >> Yeah. I mean, we're fortunate enough, and you and I are talking before the show. I mean, we're kind of born on the cloud way started off, actually on Roku. Uh, back in 2013 we adopted eight of us back in 2015. And there's just so many different service is that Amazon Web services has been able to provide us and they've added more overtime. I think the one that I talked about, uh was one that actually came out only in early 2018 which is the Aurora Post product. Um, we've been able to sail our databases scale up our analytics infrastructure. We've also used AWS for things like, you know, really time data streaming. They have the cloudwatch product where it gives us a lot of insight into the kind of our servers are behaving. And so the eight of us ecosystem in of itself is kind of evolving, and we feel like we've grown with them and they're growing with us. So it's been a great synergy over the past couple of years >> as you take a look at where you started and where you've wound up. Can you use that to extrapolate a little bit further? As far as what shortcomings you seeing today? That, ideally, would be better met by a cloud provider or at this point is it's such a simpatico relationship is you just alluded to where you just see effectively your continued to grow in the same simple directions just out of, I guess, happenstance. Yeah, it is a >> good question. I think there are some shortcomings. For example, eight of us just recently launched and chaos, which is their in house coffin solution. We're looking for something that's kind of a lot more vetted, right? So we're considering Do we adopt eight of us version or do we try to do it in house, or do we go with 1/3 party vendor? That's >> confidence. Hard to say no to these days. >> Yeah, exactly. And I think, you know, we want to make sure that we are building our infrastructure in a way that way, feel confident in can scale. I mean, with Aurora Post Chris, it's done wonders for us, but we've also kind of been the Pi. One of the pioneers were eight of us for scaling that product, and I think we got kind of lucky in some ways they're in terms of how it's been ableto pan out. But we want to make sure the stakes are a lot higher for us now. And so you know, when we have issues, millions of people face issues, so we want to make sure that we're being more thoughtful about it. Eight of us certainly has matured a lot over the past couple of years, but we're keeping our options open and we want to do what's best for our customers. Eight of us more often than not has a solution, but sometimes we have the you consider other solutions and consider the back that AWS may or may not. So some of the future problems. >> Oh yeah, it's, I think, that it's easy to overlook. Sometimes with something like a food delivery service. It's easy to make jokes about it about what you're too lazy to cook something. And sure, when I was younger, absolutely then I had a child. And when she wasn't going to sleep when she was a baby, I only had one hand. How do I How do I feed myself? There's an accessibility story. People aren't able to easily leave the house, so it's not just people aren't able to get their wings at the right time. This starts becoming impacting for people. It's an important need. >> Yeah, and I think it's been awesome to see just how quickly it's been adopted. And I think another thing about food delivery that you know people don't necessarily remember about today is it was Premier Li, just the very dense urban area phenomenon, like obviously in Manhattan, where we are today who delivers existed forever. But the suburbs is where the vast, vast majority of the growth of the industry has been and you know It's just awesome to see how this case has flourished with all different kinds of people. >> I have to imagine there's a lot of analytics that are going on for some of these. You said. In the rural areas, the suburban areas you've got, it's not as dense. And how do you make sure you optimize for people that are doing so little? So what are some of the challenges you're facing their in house technology helping? >> Exactly? Yeah. I mean, with our kind of a business, it's really important for us again to the lowest level of detail, right? Just cause we're going through 100 25% year on year in 2019 maybe we're growing faster in certain parts of the United States and growing slower and others, and that's definitely the case. And so, uh, one of the awesome things that we've been able to leverage from our cloud infrastructure is just the ability to support riel, time data access and our business operators across Canada. In the United States, they're constantly trying to figure out how are we performing relative to the market in our particular locality, meaning not just, you know, the state of New York. But Manhattan, in which district in Manhattan. Um, all that matters with a business like ours. Where is this? A hyper local economy? And so I think the real time infrastructure, particularly with things like with Aurora the faster up because we're able to actually get a lot of Reed. It's too these red because because it's not affecting our right volume. So that's been really powerful. And it's allowed our business operators to just really run in Sprint. >> So, Andy, I have to imagine just data is one of the most important things of your business. How do you look at that as an asset is their, You know, new things. That new service is that you could be putting out there both for the merchants as well for the customers. Absolutely. I think one of >> the biggest ones we try to do is you know, we never give merchant direct access to the customer data because we want to protect the customer's information, but we do give them inside. That's how they can increase their sales and target customers. I haven't used them before, So one of the biggest programs we launched over the past few years is what we call Try me free so merchants can actually target customers who've never place an order from their store before and offer them a free delivery for their order from that store. So that's a great way for merchants acquire new customers. And it's simple concept for them to understand. And over time we definitely want to be able to personalize the ability to target the sort of promotions on. So we have a lot of data to do that on. We also have data in terms of what customers like what they don't like in terms of their order behavior in terms of how they're raiding the food, the restaurant. So that kind of dynamic is something that is pretty interesting Data set for us to have. You know, you look at a other local companies out there like Yelp, Google Maps. They don't actually have verified transaction information, whereas we d'oh. So I think it's really powerful. Merchants actually have that make decisions. >> It's a terrific customer experience. It almost seems to some extent to be aligned with the Amazons Professor customer obsession leadership principle to some extent, and the reason I bring that up is you mentioned you started on Hiroko and then in 2015 migrated off to AWS. Was it a difficult decision for you to decide first to eventually go all in on a single provider? And secondly, to pick AWS as that provider It wasn't >> a hard decision for us to go to. Ah, no cloud provider. That was, you know, ready to like showtime. It's a hero is more of a student project kind of scale at that time. I don't know what they're doing today. Um, but I think a doubt us at the time was still very, very dominant and that we're considering Azure and G C P. I think was kind of becoming a thing back then made of us. It was always the most mature, and they've done a great job of keeping their lead in this space. Uh, Google, an azure have cropped up. Obviously, Oracle clouds coming up Thio and were considered I mean, we consider the capabilities of something like Google Cloud their machine. Learning soft service is a really powerful. They actually have really sophisticated, probably more so than a W s kubernetes service is actually more sophisticated. I guess it's built in house at Google. That makes sense. But, you know, we've considered landscape out there, but AWS has served a lot of our knees up to this point. Um, and I think it's gonna be a very dynamic industry with the cloud space. And there's so much at stake for all these different companies. It's fascinating to just be a part of it and kind of leverage. It >> s o nd I'm guessing, you know, when you look at some of your peers out there and you know, when a company files in s one and every goes, Oh, my God, Look at their cloud, Bill. You know, how do you look at that balance? You send your keynote this morning. You know, you like less than a handful of engineers working on the data infrastructure. So you know that line Item of cloud you know, I'm guessing is nontrivial from your standpoint. So how do you look at that? Internally is how do you make sure you keep control and keep flexibility and your options Yet focus on your core business and you know not, you know, that the infrastructure piece >> of it that was such a great question, because it's something that way we think about that trade off a lot. Obviously. In the early days, what really mattered ultimately is Do we have product market bid? Do we have? Do we have something that people will care about? Right. So optimizing around costs obviously was not prudent earlier on. Now we're in a such a large scale, and obviously the bills very big, uh, that, you know, optimizing the cost is very real thing, um, and part of what keeps, you know, satisfied with staying on one provider is kind of a piece of set up. And what you already have figured there? Um and we don optimization is over the years wear folks on financing now who basically looking at Hey, where are areas were being extremely inefficient. Where are areas that we could do? Bookspan, this is not just on AWS with is on all our vendors. Obviously eight of us is one of our biggest. I'm not the biggest line item there. Um, and we just kind of take it from there, and there's always trade offs you have to make. But I know there's companies out there that are trying to sell the value proposition of being ableto optimize your cloud span, and that is definitely something that there's a lot of. I'm sure there's a lot of places to cut costs in that we don't know about. And so, yeah, I think that's something that way we're being mindful of. >> Yeah, it's a challenge to you See across the board is that there's a lot of things you can do programmatically with a blind assessment of the bill. But without business inside, it becomes increasingly challenging. And you spoke to it yourself. Where you're not going to succeed or fail is a business because the bill winds up getting too high. Unless you're doing something egregious, it's a question of growth. It's about ramping, and you're not gonna be able to cost optimize your way to your next milestone unless something is very strange with your business. So focusing on it in due course is almost always the right answer. >> Yeah, I mean, when I think about increasing revenue or deep recent costs nine times out of 10 we're trying to provide more value, right, so increasing revenues, usually they go to option for us, but they're sometimes where it's obvious. Hey, there's a low hanging fruit and cutting costs, and if it's relatively straightforward to do, then let's do it. I think with all the cloud infrastructure that we've been able to build on top of, we've been able to focus a lot of our energy and efforts on innovating, building new things, cementing our industry position. And, yeah, I think it's been awesome. On top >> of what? Want to give you the final word? Any addressing insights in your business? You know, it's like I like food and I like eating out and, you know, it feels like, you know, we've kind of flatten the world in lot is like, You know, I think it was like, uh, like, 556 years ago. The first time I went white and I got addressed to Pok. Everybody in California knows, okay, but I live on the East Coast now. I've got, like, three places within half an hour of me that I could get it. So you know those kind of things. What insight to you seeing you know what's changing in the marketplace? What? What's exciting you these >> days? Yeah, I mean, for us, we've definitely seen phenomenon where different food trans kind of percolate across different areas. I'm going to start in one region and then spread out across the entire United States or even Canada. I would say I don't way try to have as much emergence election on a platform. It's possible so that no matter what the new hot hottest trend is that more likely than not, we're gonna have what you want on the platform. And I think what's really exciting to us over the next couple years is you know, last year we actually started way started satisfying grocery delivery. So, uh, in fact, we power a lot of grocery deliveries for Walmart today, which is exciting, and a lot of other grocers lined up as well. We're gonna see how far we can take our logistics capabilities from that standpoint, But really, we want to want to have as many options as possible for our customers. >> Anything. Thanks so much for joining us. Congressional Congratulations on the progress with your death for Cory Quinn. I'm stupid and we'll be back here with more coverage from eight of US summit in New York City. 2019. Thanks is always watching. Cute

>> Live from Las Vegas, its theCUBE. Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to the theCUBE's live coverage of Informatica World 2019 here in Sin City. I'm your host Rebecca Knight. We're here with Arun Varadarajan. He is the vice president of AI and anaylsitcs at Cognizant. Thank you so much for coming on theCUBE Arun. >> Wonderful its also great to meet you folks at theCUBE. >> You are Cube alarm. >> I am a Cube alarm. This is probably the third or fourth time that I'm on theCUBE. >> Excellent. Well for those viewers who have not seen your previous clips tell us a little bit about your role at Cognizant. >> My role at Cognizant is focused on two primary things. One is to really get our customers ready for AI and truly compete in the digital world. The second big focus for me is to get them there. To me it's all about the data. So many times we don't realize this that if you look at a lot of the FANG players. The digital natives are born digital who really have leveraged machine learning and AI to disrupt the market place. They do it with data. It's all about the data. So the big push that I'm working on these days is to help our clients create this new modern data platform that can truly help them leverage AI and disrupt the market where possible. >> So tell us what you've-- So we know that this journey is incredibly complex and there's a lot of layers, a lot of questions, hard questions that companies are wrestling with. >> Yes. >> Give us the lay of the land. What do you see as sort of the big dominant forces happening in AI and ML? >> I think the first place is companies are still trying to figure out where do they apply AI and ML. I think that is where they need to start because if it is not designed and the initiative is not purposed around any sort of specific business area or business focus or business outcome, it becomes an engineering project that really doesn't see light of day. If you remember back in the days when Hadoop was big. Hadoop was almost like a solution trying to find-- A problem or a solution trying to find a problem, whichever way it is. I think as opposed to taking a technology view which has been the traditional approach that most of the CIO organizations have used. In AI even more so, there needs to be significant participation for the business to decide where are the opportunities for me to drive business value. So I've always told my clients that the place to start is where can I apply AI and machine learning because at the end of the day it is just a technique right, and the technique has to be focused on delivering true business outcomes and business values. So that is where I think our clients need to start. If you go back in time and remember the ERP days when people were implementing SAP and Oracle there was this very strong focus on process optimization and process excellence. How do I get a straight through process organization? Really create that process orchestration layer that could execute at excellence. I think that needs to be brought back today but in a different light and the light is, now let me view my value chain, not just from a process orchestration standpoint but where are the opportunities for me to leverage machine learning and AI to create very different outcomes within that process layer? And I think-- Sorry. >> I definitely want to go back to that but I also want to remember that we are here at Informatica World and I want to make sure I ask you how you at Cognizant work with Informatica. >> Informatica is a strategic partner of ours and as I was saying, while you start with that outcome in mind and really say these are the areas I want to drive business outcomes it's very important you understand how data plays a role in delivering those outcomes. So that's where Informatica and our partnership really comes to fruition. You know that Informatica has been working very strong in the areas of metadata management, data governance, security. All of these are essential part of you knowing your data and knowing where your data's coming from, where is it going, who is using it, how is it being consumed, in what form and shape should it be delivered so that we can deliver business value is a key aspect of really leveraging AI and machine learning. In AI and machine learning the one thing that we have to be cognizant of, pun intended, is the fact that when you're going to get the machine to start making decisions for you, the quality of your data has to be significantly higher than just a report that is inaccurate, right. Report inaccuracy, yes you're going to get shouted at by the consumer of the report but that's the only problem you face but with AI and machine learning coming into play if your data is not truly representative of the decision area that the machine is working on then you're going to have a very bad outcome. >> This is a deep and philosophical issue because if the data is shoddy or biased there is a lot of problems that companies can get into. So where do you even start? How do you even work with a company to make sure that their data is the right data, is pure? What do you think? >> Interesting you ask that question. We've come up with this notion that even data has got IQ. We call it data IQ in Cognizant and it's a mathematical measure that we have come up with which allows us to score a data's ability to perform in a given area or function. So it could be in the area of sales effectiveness. Look we have a large retail company that is really trying to figure out how can they improve their store level information so that they can execute more sales orders with their customers. Their assumption is that they're working with a data set that can help them drive that outcome. How do they know that? Well there's one way to find out, which is for you to experiment, test, and learn and test and learn but that's an arduous process. Which is why a lot of the data science work that is happening today is, I would say, probably seventy to 80% of the data science effort goes waste because there are experiments that fail. This was-- >> But is that a waste? So it failed, but you tried and you maybe had some learnings from it, right? >> So a lot of people keep saying that failure is a great teacher of-- >> That's the Silicon Valley mantra right now. >> Well you can be smart about where you fail. >> True. >> Right. >> Good point. >> If there are opportunities for you to prevent that failure why wouldn't you? >> Okay. All right. >> That's what we're looking at. So what I'm saying is that before you go into doing any data science experiment, what if I came back and told you that the data that you're working on is not going to be sufficient for you to deliver that outcome. Would it not be interesting? >> Exactly, so it's making sure that you at least are maximizing your chance of success by having the right data to begin with. It is a failure for failure's sake if you're not even starting with the right data. >> Absolutely and you know the other thing that people don't realize is is if you go and ask-- If you just do it, I'm going back to my industrial engineering days, if you go and do a simple time and motion study of data science, data scientists, I can guarantee you that 80% or 90% of their time is spent on just prepping the data and only less than 10% or 15% on truly driving business value. So my question is you're spending big dollars on data science experiments where eighty to 90% of the time the data scientists are prepping. Looking at the data, is it the right skew, has it the right features, do I need to do some feature engineering, do you denormalize it? There are a whole bunch of data prep work that they do. My question is, what if we take that pain away from them? That's what I call as data science freedom and this is what we are promoting to our clients saying what can you do with your data so that your data is ready for the data science folks? Today it's data science folks, tomorrow it's going to be hopefully machine learning algorithms that can self model because a lot of people are talking about auto ML which is the new buzz-word, which is AI doing AI and that's an area that we're heavily invested in. Where you really want to make sure that the data going in is of the veracity and the complexity and the texture required for that outcome area. So that's where I think things like data IQ as a concept would really help our clients to know that hey the data I'm working with has got the intrinsic intelligence in that outcome area for me to drive that particular business outcome that I'm working on. That's where I think the magic lies. >> That's where they'll see the value. >> That's where they'll see the value. >> So talk a little about the AI journey because that is, it's all intertwined but so many companies are coming to you, to Cognizant and saying we know we need to do more of this, we want to make it real, how do we get there? So what do you say? What's your advice? >> So, I think I mentioned this right up-front when we started the conversation. It all has to start with purpose. Without purpose no AI project really succeeds. You'll end up creating a few bots. In fact when I look out there in the world and look at the kind of work that is happening in machine Learning and AI, many of the so-called AI projects, if you double click on them, are just bots. So we are doing some level of maybe process automation, we're trying to reduce labor content, bringing in bots, but are we truly driving change? I'm not saying that that's not a change. There is definitely a change but it's more of an incremental change. It is not the kind of disruptive change that some of the FANG leaders that are showing right. If you take Facebook, Amazon, the whole gamut of digital natives, they are truly disrupting the market place. Some of them are even able to do a million predictions a second to match demand, supply, and price. Now that is how they are using it. Now the question I think for our clients, for our enterprise clients is to say that's a great goal to have but where do I start and how do I start? It starts with, in my opinion, two or three big notions. One is, honestly ask yourself, how much of a change are you willing to make, because if you have to compete and really leverage AI and machine learning the way it has been designed to do so you have to be willing to press the reset button. You have to be willing to destroy what you have today and there is, I think Bill Baker back in the days, he was a SQL server guy. He was talking about this whole concept of what is known as scale up and scale out and he was talking about it from the angle of managing a pet versus managing cattle. So when you're managing a pet, a pet is a very unique component like your mail server So Bob the mail server, if the mail server goes down then all hell breaks loose and hopefully you have another alternate to Bob to manage the mail server. So it's more like a scale up model where you are looking at, hey how do I manage high availability as opposed to today's world where you have the opportunity to really look at things in a far more expansive manner. So if you have to do that you can't be saying I have this on-prem data warehouse right, which is running on X Y Z, and I want to take that on-prem data warehouse and move it to the Cloud and expect magic to happen, because all you're doing is you're shifting your mess from your data center to somebody else's data center which is called the Cloud. >> Right. >> Right? So I think the big thing for clients to really understand is how much are they invested in this change. How are they willing to drive this change? I'll tell you it's not about the technology. There are so many technology options today and we have got some really smart engineers who know how to engineer things. The question is, what are you doing this for? Are you willing, if you want to compete in that paradigm, are you willing to let go of what you have tody? That is a big question. That I would start with. >> An important question but I want to sneak in one more question and that is about the skills gap because this is something that we hear so much about. So many companies facing a, there is a dearth of qualified candidates who can do these jobs in data science and AI and ML. What are you seeing at Cognizant and what are you doing to remedy the problem? >> So I think it's definitely a challenge for the industry at large and what we are starting to see is two things emerging. One is the new workforce coming into the market is better equipped because of the way the school systems have changed in the last few years and I would say this is a global phenomenon not just in North America or in Europe or in China or India. It's a global phenomenon. We're starting to see that undergrad students who come out of school today are better equipped to learn the new capabilities. That's number one. Which is very heartening for us right, in the whole talent space. What I've always believed in, and this is my personal view on this, what I've always believed in is that these skills will come into fashion and go out of fashion in months and days. It's about the kind of engineering approach you have that stays constant, right. If you look at any of the new technologies today, they all are based on some core standard principles. Yes the semantics will change, the structure will change, but some of the engineering principles remain the same. So what we've been doing in Cognizant is really investing in our engineering talent. So we call it data engineering and to us data engineering means that if you're a data engineer you can't tell me I will only work with A, B, or C technology. You should be in a position to work with all of these technologies and you should be in a position to approach it from an engineering mindset as opposed to a skill or a tool based mindset and that's the change that we need with fads coming in and out of Vogue. I think it's super important for all consultants in this space to be grounded on some core engineering principles. That's what we are investing in very heavily. >> Well it sounds like a sound investment. Well thank you so much for coming on the show Arun. I appreciate it. >> Thank you so much. It was a pleasure. >> I'm Rebecca Knight for theCUBE. You are watching theCUBE at Informatica World 2019. Stay tuned. (lighthearted music)

(upbeat music) >> Welcome to this special CUBEConversation here in the Palo Alto CUBE studio. I'm John Furrier, the co-host, theCUBE co-founder of SiliconANGLE Media. In theCUBE we're here with Alan Cohen, CUBE alumni, joining us today for a special segment on the future of technology and the impact to society. Always good to get Alan's commentary, he's the Chief Commercial Officer for Illumio, industry veteran, has been through many waves of innovation and now more than ever, this next wave of technology and the democratization of the global world is upon us. We're seeing signals out there like cryptocurrency and blockchain and bitcoin to the disruption of industries from media and entertainment, biotech among others. Technology is not just a corner industry, it's now pervasive and it's having some significant impacts and you're seeing that in the news whether it's Facebook trying to figure out who they are from a data standpoint to across the board every company. Alan, great to see you. >> Always great to be here, I always feel like, I can't tell whether I'm at the big desk at ESPN or I've got the desk chair at CNBC, but that's what it's like being on theCUBE. >> Great to have you on extracting the signal noises, a ton of noise out there, but one of things of the most important stories that we're tracking is, that's becoming very obvious, and you're seeing it everywhere from Meed to all aspects of technology. Is the impact of technology to people in society, okay you're seeing the election, we all know what that is, that's now a front and center in the big global conversation, the Russian's role of hacking, the weaponizing of data, Facebook's taking huge brand hits on that, to emerging startups, and the startup game that we're used to in Silicon Valley is changing. Just the dynamics, I mean cryptocurrency raises billions of dollars but yet (laughs) something like 10, 20% of it's been hacked and stolen. It's a really wild west kind of environment. >> Well it's a very different environment. John, you and I have been in the technology industry certainly for a whole bunch of lines under our eyes over the years have gone there. My friend Tom Friedman has this phrase that he says, "Everybody's connected and nobody's in control," so the difference is that, as you just said, the tech industry is not a separate industry. The tech industry is in every product and service. Cryptocurrency is like, the concept of that money is just code. You know, our products and services are just code, it raises a couple of really core issues. Like for us on the security point of view, if I don't trust people with the products they're selling me, that I feel like they're going to be hacked, including my personal data, so your product now includes my personal information, that's a real problem because that could actually melt down commerce in a real way. Obviously the election is if I don't trust the social systems around it, so I think we're all at an, and I'd like to say world is still kind of like iRobot moment, and if you remember iRobot, it's like, people build all these robots to serve humankind and then one day the robots wake up and they go, "We have our own point of view on how things are going to work" and they take over, and I think whether it's the debate about AI, whether cryptocurrency's good or bad, or more importantly, the products and services I use, which are now all digitally connected to me, whether I trust them or not is an issue that I think everyone in our industry has to take a step back because without that trust, a lot of these systems are going to stop growing. >> Chaos is an opportunity, I think that's been quoted many times, a variety-- >> You sound like Jeff Goldblum in like Jurassic Park, yeah. (laughing) >> So chaos is upon us, but this is an opportunity. The winds are shifting, and that's an opportunity for entrepreneurs. The technology industry has to start working for us but we've got to be mindful of these blind spots and the blind spots are technology for good not necessarily just for profits, so that also is a big story right now. We see things like AI for good, Intel has been doing a lot of work on that area, and you see stars dedicated to societal impact, then young millennials, you see the demographic shift where they want to work on stuff that empowers people and changes society so a whole kind of new generation revolution and kind of hippie moment, if you look at the 60s, what the 60s were, right? >> Well there's people out in the street protesting, right? There were a couple of million women out in the street this weekend, so we are in that kind of moment again, people are not happy with things. >> And I believe this is a signal of a renaissance, a change, a sea change at enormous levels, so I want to get your thoughts on this. As technology goes out in mainstream, certainly from a security standpoint, your business Illumio is in that now where there's not a lot of control, just like you were mentioning before we came on that all the spends happening but no one has more than 4% market share. These are dynamics and this is not just within one vertical. What's your take on this, how do you view this sea change that's upon us, this tech revolution? >> Well, you know, think about it. You and I grew up in the era where clients server took over from main frame, right? So remember there was this big company called IBM and they owned a lot of the industry, and then it blew up for client server and then there were thousands of companies and it consolidated its way down, but when those thousands of new companies, like you didn't know what was going to be Apollo and what was going to be Oracle right? Like you didn't know how that was going to work out, there was a lot of change and a lot of uncertainty. I think now we're seeing this on a scale like that's 10x of this that there's so much innovation and there's so much connectedness going on very rapidly, but no one is in control. In the security market, you know, what's happening in our world is like, people said, okay I have to reestablish control over my data, I've lost that control, and I've lost it for good reasons, meaning I've evolved to the cloud, I've evolved to the app economy, I've done all of these things, and I've lost it for bad reasons because like am I, like I'm not really running my data center the way I should. We're in the beginning of a move in of people kind of reasserting that control, but it's very hard to put the genie back in the bottle because the world itself is so much more dynamic and more distributed. >> It's interesting, I've been studying communities and online communities for over a decade in terms of dynamics. You know, from the infrastructural level, how packets move to a human interaction. It's interesting, you mentioned that we're all connected and no one's in control, but you now see a ground swell of organic self-forming networks where communities are starting to work together. You kind of think about the analog world when we grew up without computers and networks, you kind of knew everyone, you knew your neighbor, you knew who the town loony was, you kind of knew things and people watch each other's kids and parents sat from the porch, let the kid play, that's the way that I grew up, but it was still chaotic but yet somewhat controlled by the group. So I got to ask you, when you see things like cryptocurrency, things like KYC, know your customer, anti money laundering, which is, you know these are policy based things, but we're in a world now where, you know, people don't know who their neighbors are. You're starting to see a dynamic where people are-- >> Put the phone down. >> Asserting themselves to know their neighbor, to know their customer, to have a connected tissue with context and so your trust and reputation become super important. >> Well I think people are really, so like every time there is a shift in technology, there's scary stuff. There's the fuddy-duddy moment where people are saying, "Oh we can't use that," or "I don't know that," and you know, clearly we're in this kind of new kam-ree and explosion of this cloud mobile blah blah blah type of computing thing and ... Blah blah blah is always a good intersection when you don't have a term. Then things form around it, and just as you said, so if you think about 25 years ago, right, people created The WELL and there was community writing first bulletin boards and like now we have Facebook and you go through a couple of generations and for a while, things feel out of control and then it reforms. I personally am an optimist. Ultimately I believe in the inherent goodness of people, but inherent goodness leaves you open and then, you know, could be manipulated, and people figure these things out. Whether it's cryptocurrency or AI, they are really exciting technologies that don't have any ground rules, right? What's going to happen I believe is that people are going to reestablish ground rules, they're going to figure out some of the core issues, and some of these things may make it, and some of these things may not make it. Like cryptocurrency, like I don't know whether it makes it or not, but certainly the blockchain as a technology we're going to be incorporating in what we do, and maybe the blockchain replaces VPNs and last generation's way of protecting zeros and ones. If AI is figuring out how to read an MRI in five minutes, it's a good thing, and if the AI is teaching you how to exclude old folks for me finding jobs, it's a bad thing. I think as technology forms, there's always Spectre and 007, right? There's always good and bad sides and you know, I think if you believe-- >> I'm with you on that. I think value shifts and I think ultimately it's like however you want to look at it will shift to something, value activity will be somewhere else. Behind me in the bookshelf is a book called The World is Flat and you're quoted in it a lot as a futurist because you have inherently that kind of view, well that's not what you do for a living, but you're kind of in an opt-- >> Alan: Marketing, futurist, kind of same thing. >> Thomas Friedman, the book, that was a great book and at that time, it was game changing. If you take that premise into today where we are living in a flat world and look at cryptocurrency, and then over with the geo political landscape, I mean I just can't see why the Federal Reserve wouldn't reign in this cryptocurrency because if Japan's going to control a bunch of, or China, it's going to be some interesting conversations. I mean I would be like all over that if I was in the Federal Reserve. >> I think people-- Look, cryptocurrency's really interesting and I think people a little over-rotated. If you look at the amount of GDP that's invested in cryptocurrency, it's like, I don't know, there might've been, you know 20 years ago the same amount involved invested in Beanie Babies, right? I mean things show up for a while and the question is is it sustainable over time? Now I'm trained as an economist, you and I have had this conversation, so I don't know how you have a series of monetary without kind of governmental backing, I just don't understand. But I do understand that people find all kinds of interesting ways to trade, and if it's an exchange, like I mean what's the difference between gold and cryptocurrency? Somebody has ascribed a value to something that really has no efficacy outside of its usage. Yeah I mean you can make a filling or bracelets out of gold but it doesn't really mean anything except people agree to a unit of value. If people do that with cryptocurrency, it does have the ability to become a real currency. >> I want to pick your perspective on this being an economist, this is is the hottest area of cryptocurrency, it's also known as token economics, is a concept. >> Alan: Token economics. >> You know that's an area that theCUBE, with CUBE coins, experimenting with tokens. Tokens technically are used for things in mobile and whatnot but having a token as a utility in a network is kind of the whole concept, so the big trend that we're seeing and no one's really talking about this yet is instead of having a CTO, Chief Technology Officer, they're looking for a CEO, a Chief Economist Officer, because what you're seeing with the MVP economy we're living in and this gamification which became growth hack which didn't really help users, the notion of decentralized applications and token economics can open the door for some innovation around value and it's an economic problem, how you have a fiscal policy of your token, there's a monetary policy, what's it tied to? A product and a technology, so you now have a now a new, twisted, intertwined mechanism. >> Well you have it as part of this explosion, right? We're at a period of time, it feels like there's a great amount of uncertainly because everything's, you know, there's a lot of different forces and not everybody's in control of them, and you know, it's interesting. Google has this architecture, they call it BeyondCorp, where the concept is like networks are not trusted so I will just put my trust in this device, Duo Security's a great example of a company that's built a technology, a security technology around it which is completely antithetical to everything we know about networks and security. They're saying everything's the internet, I'll just protect the device that it's on. It's a kind of perfect architecture for a world like where nobody is in charge, so just isolate those, buy this, what is a device? It's a token too, it's a person, your iPhone's your personal token. Then over time, systems will form around it. I think we just have to, we always have to learn how to function in a different type of economy. I mean democracy was a new economy 250 years ago that kind of screwed around with most of the world, and a lot of people didn't think it would make it, in fact we went through two World War wars that it was a little on the edge whether democracy was going to make it and it seems to have done okay, like it was pretty good IPO to buy into. You know, in 1776. But it's always got risks and struggles with it. I think if, ultimately it comes together, it's whether a large group of people can find a way to function socially, economically, and with their personal safety in these systems. >> You bring up a great point, so I want to go to the next level in this conversation which is around-- >> Alan: You've got the wrong guy if you're going to the next level because I just tapped out. >> No, no, no we'll get you there. It's my job to get you there. The question is that everyone always wants to look at, whether it's someone looking at the industry or actors inside the industries across the board, mainly the tech and we'll talk about tech, is the question of are we innovating? You brought up some interesting nuances that we talk about with token economics. I mean Steve Jobs had the classic presentation where he had street signs, technology meets liberal arts. That's a mental image that people who know Steve Jobs, know Apple, was a key positioning point for Apple at that time which was let's make computers and technology connect with society, liberal arts. But we were just talking about is the business impact of technology, the economics, and that's just not like just some hand waving, making technology integrate with business. You're in the security business, There are some gamification technology, gamification that's business built into the products. So the question is, if we have the integration of business, technology, economics, policy, society rolling into the product definitions of innovation, does that change the lens and the aperture of what innovation is? >> I think it does, right? The IT industry's somewhere between three and four trillion dollars depends on how it counts in. It grows pretty slowly, it grows by a low single digit. That tells me as composite, like is that, that slow growth is a structural signal about how consumers of technology think in a macro sense. On a micro sense, things shift very rapidly, right? New platforms show up, new applications show up, all kinds of things show up. What I don't think we have done yet, to your point, is in this new integrated world, the role of technology is not just technology anymore. I don't think, you know you said you need Chief Economical Officer, what about Chief Political Officer? What about a Chief Social Officer? How many heads of HR make decisions about the insertion of systems into their business? And that's what this kind of iRobot concept is in my mind which is that you know, we are exceeding control of things that used to be done by human beings to systems and when you see control, the social mores, the political mores, the cultural mores, and the human emotional mores have to move with it. We don't tend to think about things like that. We're like, "I win and my competitors lose." Like technology used to be much more of a zero sum, my tech's better than yours. But the question is not just is my tech better than yours, is my customer better off in their industry for the consumption of my technology of inserting it into their offering or their service? You know what, that is probably going to be the next area of study. The other thing that's very important in whether, any of you have read Peter Thiel's book Zero to One, the nature of competition technology used to feel like a flat playing field and now the other thing that's rising is do you have super winners? And then what is the power of the super winners? So you mentioned whether it's Facebook or Google or Amazon or you know, or Microsoft, the FANG companies right? Their roles are so much more significant now than the Four Horsemen of the Nasdaq were in 2000 when you had Intel and Cisco and Oracle and Saht-in it's a different game. >> You're seeing that now. That's a good point, so you're reinforcing kind of this notion that the super players if you will are having an impact, you're mentioning the confluence of these new sectors, you know, government, policy, social are new areas. The question is, this sounds like a strategic imperative for the industry, and we're early so it's not like there's a silver bullet or is there, it doesn't sound like there, so to me that's not really in place yet, I mean. >> Oh no. We're not even in alpha. We have demo code for the new economy and we're trying to get the new model funded. >> John: That's the demo version, not the real version. It's the classic joke. >> Yeah this not the alpha or the beta version that like you're going to go launch it. If people think they're launching it, I think it's a little preliminary and you know, it's not just financial investment, it's like do I buy in? I'll tell you something that's really interesting. I've been visiting a bunch of our customers lately and the biggest change I'd say in the last two years is they now have to prove to their customers they're going to be good custodians of their data. Think about that, like you could go to any digital commerce you do, any website you use and you give them basically the ticket to the Furrier family privacy, you do, but you don't spend a lot of time questioning whether they're really going to protect your data. That has changed. And it's really changing in B2B and in government organizations. >> The role of data to us is regulation, GDPR in Europe, but this is a whole new dynamic. >> It's not just my data because I'm worried about my credit card getting hacked, I'm worried about my identity. Like am I going to show up as a meme in some social media feed that's substituted for the news? I don't want to use the FN word, but you know what I mean? It is a really brave new world. It's like a hyper-democracy and a hyper-risky state at the same time. >> We're living in an area of massive pioneering, new grounds, this is new territory so there's a lot of strategic imperatives that are yet not defined. So now let's take it to how people compete. We were talking before we came on camera, you mentioned the word we're in an MVP economy, minimum viable product concept, and you're seeing that being a standard operating procedure for essentially de-risking this challenge. The old way of you know, build it, ship it, will it work? We're seeing the impact from Hollywood to big tech companies to every industry. >> Well you've got a coffee mug for a company that does both. Amazon does MVP in entertainment, like we'll create one pilot and see if it goes as opposed to ordering a season for 17 million dollars to hey, let's try this feature and put it out on AWS. What's interesting is I don't think we've completely tilted but the question is will buyers of technology, of entertainment products, of any product start to say, "I'll try it." You know like, look, I've done four startups and I always know there's somebody I can go to get and try my early product. There are people that just have an appetite, right? The Jeffrey Moores, early adapter, all the way to the left of the-- >> They'll buy anything new. >> They'll try it, they're interested, they have the time and the resources, or they're just intellectually curious. But it was always a very small group of people in the IT industry. What I think that the MVP economy is starting to do is look, I Kickstarted my wallet. I don't know if I'm the only person who bought that skinny little wallet on Kickstarter, it doesn't matter to me, it had appeal. >> What's the impact of the MVP economy? Is it going to change to the competitive landscape like Peter Thiel was suggesting? Does it change the economics? Does it change the makeup of the team? All of the above? What's your thoughts on how this is going to impact? Certainly the encumbrance will seem to be impacted or not. >> I think two things happen. One, it attacks the structural way markets work. If you go back to classical economics, land, labor, and capital, and people who own those assets, now you add information as a fourth. If those guys were around now they would say that would be the fourth core asset, production, I'm sorry, means of production is the term. The people who can dominate that would dominate a market. Now that that's flattened out, you know, I think it pushes against the traditional structures and it allows new giants to kind of show up overnight. I mean the e-commerce market is rife with companies that have, like look at Stich Fix. A company driven by AI, fashions, tries to figure out what you like, sends it to you every month, just had a monster IPO. We invented, by the way the Spiegal Catalog, except like with a personal assistant and you know, it's changed that in just a short number of years. I think two things happen. One is you'll get new potential giants but certainly new players in the market quickly. Two, it'll force a change in the business model of every company. If you're in a cab in any city in the world, I'm not saying whether the app works there or not, Uber and Lyft has forced every cab company to show you here's the app to call the cab. They haven't quite caught up to the rest of the experience. What I think happens is ultimately, the larger players in an industry have to accommodate that model. For people like me, people who build companies or large technology companies, we may have to start thinking about MVPing of features early on, working with a small group, which is a little what the beta process is but now think about it as a commercial process. Nobody does it, but I bet sure a lot of people will be doing it in five years. >> I want to get your take on that approach because you're talking about really disrupting, re-imagining industry, the Spiegal catalog now becomes digital with technology, so the role of technology in business, we kind of talked about the intertwine of that and its nuance, it's going to get better in my opinion. But specifically the IT, the information technology industry is being disrupted. Used to be like a department, and the IT department will give you your phone on your desk, your PC on your desk or whatever, now that's being shattered and everyone that's participating in that IT industry is evolving. What's your take on the IT industry's disruption? >> Well look, it started 20 years ago when Marc Benioff and Salesforce decided to sell the sales forces instead of IT people, right? They went around to the end buyer. I don't think it's a new trend, I think a lot of technology leaders now figure out how to go to the business buyer directly and make their pitch and interestingly enough, the business buyer, if the IT team doesn't get on board, will do that. >> John: Because of cloud computing and ... >> Because of everything. The modern analog I think in our world is that the developers are increasingly in control. Like my friend Martin Casado up in Andreessen talks about this a lot. The traditional model on our industry is you build a product, you launch it, you launch your company, you work with the traditional analyst firms, you try to get a little bit of halo, you get customer references, those are the things you do and there was a very wall structured, for example, enterprise buying cycle. >> And playbook. >> Playbook, and there's the challenger sale and there's Jeffrey Moore and there's like seeing God. You've got your textbooks on how it's been done. As everything turns into code, the people who work with code for a living increasingly become the front end of your cycle and if you can get to them, that changes. Like I mean think about like, you know, Tom wrote about this actually in The World is Flat, like Linux started as a patchy. It didn't start with the IT department, it started with developers and there was the Linux foundation and now Linux is everything. >> There's a big enemy called the big mini computer, and not operating systems and work stations. >> Wiped out whole parts of Boston and other parts of the world, right? >> Exactly, that's why I moved out here. >> You filed client's server out here. >> I filed a smell of innovation. No but this is interesting because this location of industries is happening, so with that, so they also on the analog, so Martin's at Andreessen, so we'll do a little VC poke there at the VCs because we love them of course, they're being dislocated-- >> I don't (mumbles) my investors. >> Well no, their playbook is being challenged. Here's an example, go big or go home investment thesis seems not to be working. Where if you get too much cash on the front end, with the MVP economy we were just riffing on and with the big super powers, the Amazons and the Googles, you can't just go big or go home, you're going to be going home more than going big. >> I think they know that. I mean Dee-nuh Suss-man who's I think Chief Investment Officer at Nasdaq has a very well known talking line that there are half as many public companies as there were 10 years ago, so the exit scenario for our industry is a little bit different. We now have things like acqui-hires, right we have other models for monetization, but I think what the flip side of it is, we're in the-- >> Adapt or die because the value will shift. Liquidity's changing, which acqui-hires-- >> I think the investment community gets it completely and they spend a lot more time with the developer mindset. In fact I think there's been a doubling down focus on technical founders versus business founders for companies for just that reason because as everything turns to code, you got to hang out with the code community. I think there are actually-- >> You think there'll be more doubling down on technical founders? You do, okay. >> Yeah I think because that is ultimately the shift. There are business model shifts, but it's, you know, I mean like Uber was a business model shift, I mean the technology was the iPhone and GPS and they wrote an app for it, but it was a business model shift, so it can be a business model shift. >> And then scale. >> And then scale and then all of those other things. But I think if you don't think about developers when you're in our, and it's like we built Illumio because a developer could take the product and get started. I mean you can, developers actually can write security policy with our product because there's a class of customers, where as not everyone where that matters. There's other people where the security team is in charge or the infrastructure team is in charge but I think everything is based on zeros and ones and everything is based on code and if you're not sensitive to how code gets bought, consumed, I mean there's a GitHub economy which is I don't even have to write the code, I'll go look at your code and maybe use pieces of it, which has always been around. >> Software disruption is clear. Cloud computing is scale. Agile is fast, and with de-risking capabilities, but the craft is coming back and some will argue, we've talked about on theCUBE before is that, you know, the craftsmanship of software is moving to up the stack in every industry, so-- >> I think it's more like a sports league. I love the NBA, right? In the old days, your professional team, you'd scout people in college. Now they used to scout them in high school, now they're scouting kids in middle school. >> (laughs) That's sad. >> Well what it says is that you have to-- >> How can you tell? >> You know but they can, right? I think you know, your point about it craft, you're going to start tracking developers as they go through their career and invest and bet on them. >> Don't reveal our secrets to theCUBE. We have scouts everywhere, be careful out there. (laughs) >> But think about that, imagine it's like there's such a core focus on hiring from college, but we had an intern from high school two years ago. We hire freshman. >> Okay so let's go, I want to do a whole segment on this but I want to just get this point because we're both sports fans and we can riff on sports all day long. >> I'm just not getting the chance >> And the greatness of Tom Brady >> to talk about the Patriots. >> And Tom Brady's gotten his sixth finger attached to his hands for his sixth ring coming up. No but this is interesting. Sports is highly data driven. >> Alan: Yep. >> Okay and so what you're getting at here, with an MVP economy, token economics is more of a signal, not yet mainstream, but you can almost go there and think okay data driven gives you more accuracy so if you can bring data driven to the tech world, that's kind of an interesting point. What's your thoughts on that? >> Yeah I mean look, I think you have to track everything. You have to follow things, and by the way, we have great tools now, you can track people through LinkedIn. There's all kinds of vehicles to tracking individuals, you track products, you track everything, and you know look, we were talking about this before we went on the show right, people make decisions based on analytics increasingly. Now the craft part is what's interesting and I'm not the complete expert, I'm on the business side, I'm not an engineer by training, but look a lot of people understand a great developer is better than five bad developers. >> Well Mark Andris' 10x is a classic example of that. >> There's clearly a star system involved, so if I think in middle school or in high school, you're going to be a good developer, and I'm going to track your career through college and I'm going to try to figure out how to attach. That's why we started hiring freshmen. >> Well my good friend Dave Girouard started a company that does that, will fund the college education for people that they want to bet on. >> Sure, they're just taking an option in them. >> Yeah, option on their earnings. Exactly. >> They are. >> It sounds like token economics to me. (laughs) >> You know you can sell anything. We are in that economy, you can sell those pieces. The good news is I think it can be a great flattener, meaning that it can move things back more to a meritocracy because if I'm tracking people in high school, I'm not worrying whether they're going to go to Stanford or Harvard or Northwestern, right? I'm going to track their abilities in an era and it's interesting, speaking about craft, you know, what are internships? They're apprenticeships. I mean it is a little bit like a craft, right? Because you're basically apprenticing somebody for a future payout for them coming to work for you and being skilled because they don't know anything when they come and work, I shouldn't say that, they actually know a lot of things. >> Alan, great to have you on theCUBE as always, great to come in and get the update. We'll certainly do more but I'd like to do a segment on you on the startup scene and sort of the venture capital dynamics, we were tracking that as well, we've been putting a lot of content out there. We believe Silicon Valley's a great place. This mission's out there, we've been addressing them, but we really want to point the camera this year at some of the great stuff, so we're looking forward to having you come back in. My final question for you is a personal one. I love having these conversations because we can look back and also look forward. You do a lot of mentoring and you're also helping a lot of folks in the industry within just your realm but also startups and peers. What's your advice these days? Because there's a lot of things, we just kind of talked a lot of it. When people come to you for advice and say, "Alan, I got a career change," or "I'm looking at this new opportunity," or "Hey, I want to start a company," or "I started a company," how is your mentoring and your advisory roles going on these days? Can you share things that you're advising? Key points that people should be aware of. >> Well look, ultimately ... I never really thought about it, you just asked the question so, ultimately, I think to me it comes down to own your own fate. What it means is like do something that you're really passionate about, do something that's going to be unique. Don't be the 15th in any category. Jack Welch taught us a long time ago that the number one player in a market gets 70% of the economic value, so you don't want to play for sixth place. It's like Ricky Bobby said, if you're not first, you're last. (John chuckles) I mean you can't always be first, but you should play for that. I think for a lot of companies now, I think they have to make sure that, and people participating, make sure that you're not playing the old playbook, you're not fighting yesterday's battle. Rhett Butler in Gone With the Wind said, "There's a lot of money in building up an empire, "and there's even more money in tearing it down." There are people who enter markets to basically punish encumbrance, take share because of innovation, but I think the really inspirational is you know, look forward five years and find a practical but aggressive path to being part of that side of history. >> So are we building up or are we taking down? I mean it seems to me, if I'm not-- >> You're always doing both. The ocean is always fighting the mountains, right? That is the course of, right? And then new mountains come up and the water goes someplace else. We are taking down parts of the client server industry, the stack that you and I built a lot of our personal career of it, but we're building this new cloud and mobile stack at the same time. And you're point is we're building a new currency stack and we're going to have to build a new privacy stack. It's never, the greatest thing about our industry is there's always something to do. >> How has the environment of social media, things out there, we're theCUBE, we do our thing with events, and just in general, change the growth plans for individuals if you were, could speak to your 23 year old self right now, knowing what you know-- >> Oh I have one piece of advice I give everybody. Take as much risk as humanly possible in your career earlier on. There's a lot of people that have worked with me or worked for me over the years, you know people when they get into their 40s and they go, "I'm thinking about doing a startup," I go, "You know when you got two kids in college "and you're trying to fund your 401K, "working for less cash and more equity may not be "the most comfortable conversation in your household." It didn't work well in my household. I mean I'm like Benjamin Button. I started in big companies, I'm going to smaller companies. Some day it's just going to be me and a dog and one other guy. >> You went the wrong way. >> Yeah I went the wrong way and I took all the risk later. Now I was lucky in part that the transition worked. When I see younger folks, it's always like, do the riskiest thing humanly possible because the penalty is really small. You have to find a job in a year, right? But you know, you don't have the mortgage, and you don't have the kids to support. I think people have to build an arc around their careers that's suitable with their risk profile. Like maybe you don't buy into bitcoin at 19,000. Could be wrong, could be 50,000 sometime, but you know it's kind of 11 now and it's like-- >> Yeah don't go all in on 19, maybe take a little bit in. It's the play and run-- >> Dollar cost averaging over the years, that's my best fidelity advice. I think that's what's really important for people. >> What about the 45 year old executive out there, male or female obviously, the challenges of ageism? We're in economy, a gig economy, whatever you want to call, MVP economics, token economics, this is a new thing. Your advice to someone who's 45 who just says "Hey you're too old for our little hot startup." What should they do? >> Well being on the other side of that history I understand it firsthand. I think that you have an incumbent role in your career to constantly re-educate yourself. If you show up, whether you're a 25, 35, 45, 55, or 65, I hope I'm not working when I'm 75, but you never know right? (mumbles) >> You'll never stop working, that's my prediction. >> But you know have you mastered the new skills? Have you reinvented yourself along the way? I feel like I have a responsibility to feed the common household. My favorite part of my LinkedIn profile, it says, "Obedient worker bee at the Cohen household," because when I go home, I'm not in charge. I've always felt that it's up to me to make sure I'm not going to be irrelevant. That to me is, you know, that to me, I don't worry about ageism, I worry about did I-- >> John: Relevance. >> Yeah did I make myself self-obsolescent? I think if you're going to look at your career and you haven't looked at your career in 15 years and you're trying to do something, you may be starting from a deficit. So the question, what can I do? Before I make that jump, can I get involved, can I advise some small companies? Could I work part time and on the weekends and do some things so that when you finally make that transition, you have something to offer and you're relevant in the dialogue. I think that's, you know, nobody trains you, right? We're not good as an industry-- >> Having a good community, self-learning, growth mindset, always be relevant is not a bad strategy. >> Yeah, I mean because I find increasingly, I see people of all ages in companies. There is ageism, there is no doubt. There's financial ageism and then there's kind of psychological bias ageism, but if you keep yourself relevant and you are the up to speed in your thing, people will beat a path to want to work for you because there's still a skill gap in our industry-- >> And that's the key. >> Yeah, make sure that you're on the right side of that skill gap, and you will always have something to offer to people. >> Alan, great to have you come in the studio, great to see you, thanks for the commentary. It's a special CUBEConversation, we're talking about the future of technology impact the society and a range of topics that are emerging, we're on a pioneering, new generational shift and theCUBE is obviously covering the most important stories in Silicon Valley from figuring out what fake news is to impact to the humans around the world and again, we're doing our part to cover it. Alan Cohen, CUBEConversation, I'm John Furrier, thanks for watching. (upbeat music)