>>mhm >>Hello welcome to this cube conversation here in Palo alto California and john for with the cube we had a great conversation around the rise of the cloud and the massive opportunities and challenges around analytics data ai suggestion. Air ceo of thought spot is here with me for conversation. Great to see you. Welcome back to the cube. How are you? >>Well john it is so good to be back. I wish that we could do one of those massive set up that you have and do this face to face but zoom is not bad. >>You guys are doing very well. We have been covering you guys been covering the progress um great technology enabled business. You're on the wave of this cloud analytics you're seeing, we've seen massive changes and structural changes for the better. It's a tailwind for anyone in the cloud data business. And you also on the backdrop of all that the Covid and now the covid is looking at coming out of covid with growth strategies. People are building modern or modernizing their infrastructure and data is not just a department, it's everywhere. You guys are in the middle of this. Take us through what's the update on thought spot. What are you guys doing? What do you see the market right now? Honestly, delta variants coming coming strong but we think will be out of this soon. Where where are >>we look I think it all starts with the users like you said the consumers are demanding more and more from the business they are interacting with. You're no longer happy with being served like uh I'm gonna put you all in a bucket and then Delaware services to you. Everyone's like look look at me, I have likes and dislikes that is probably going to be different from someone that you think are similar to me. So unless you get to know me and deliver bespoke services to me, I'm gonna go somewhere else who does that And the call that the way you do that is through the data that I'm giving to you. So the worst thing you can do is to take my data and still treat me like an average and numbers and what's happening with the cloud is that it is now possible and it wasn't okay. So I grew up in India where newspapers will always have stock market summary on like one full page full of takers and prices and the way it used to work is that you wake up in the morning you look at the newspaper, I don't know if you have had the same thing and then you call your broker is based on in place of that. Can you imagine doing that now? I mean the information is at your fingertips. Hurricane IDa either is actually going to enter in Louisiana somewhere. What good is it? Yesterday morning state on this morning state if I'm trying to make a decision on whether I should pack my stuff and move away or you know finding to from home depot supply chain manager. I shouldn't figure out what should I be doing for Louisiana in the next two days, this is all about the information that's available to you. If you plan to use it and deliver better services for your consumer cloud makes it possible. >>You know, it's interesting you mentioned that the old way things were it seems so slow, then you got the 15 minute quotes, then there's now a real time. Everything has to be real time. And clearly there's two major things happening at the same time which makes exciting the business model and the competitive advantages for leaders and business to use data is critical but also on the developer side where apps are being developed if you don't have the data access, the machine learning won't work well. So as machine learning becomes really courted driving ai this modern analytics cloud product that you guys announced brings to bear kind of two major lifts the developer app modernization as well as competitive advantage for the companies that need to deploy this. So you guys have announced this modern approach analytics cloud, so to speak. What are some of the challenges that companies are having? Because you gotta, if you hit both of those you're gonna right a lot of value. What are some of the challenges for people who want to do this modern cloud? >>I think the challenge is basically all inside in the company. If you ask companies why are they failing to modernize? They will point to what's inside, it's not outside the technology is there the stack is the vendors are there, It is sometimes lack of courage at the leadership level which is a huge problem. I'll give an example. Uh, we have recently announced what we call thoughts part everywhere, which is our way of looking at how to modernize and bring the data inside that you're looking forward to where you are because Lord knows we all have enough apps on our Octa or a single sign on. The last thing you need is one more how no matter how good it is, they don't want to log into yet under their tool, whether it's thought spot or not. But the insights that you are talking about needs to be there when you need. And the difference is uh, the fundamental approach of data analytics was built on embedded model. You know what we are proposing is what we call data apps. So the difference between data apps and the typical dashboard being embedded into your analytics model is sort of like think of it. Uh newspapers telephones and the gap in between. So there is newspapers radio that is walkie talkie and telephone. They're all different and newspapers get printed and it comes to you and you read in the morning, you can talk back to it, you can drag and drop, you can change it right walkie talkies on the other hand, you know, you could have one conversation then come back to that. Whereas phone, you can have true direction conversation? They're all different if you think of embedding it is sort of like the newspaper, the information that you can't talk back. So somebody resembling something that came out monday, you're going to a board meeting on Wednesday and you look at that and make decisions. That is not enough in the new world, you just can't do that. It's not about what a lot of tools can actually answer what the real magic the real value for customers are unlocked when you ask three subsequent questions and answer them and they will come down to when you hear what you have to know. So what? Right and then what if and then the last is what next Imagine you can answer those three questions every business person every time no matter how powerful the dashboard is, they will always have the next question. What? So what? Okay the business customers are turning so what is it good, is it bad? Is it normal or the next question is like now what what do I do with it two, the ability to take all these three questions so what and what a fun. Now what? That requires true interactivity, you know, start with an intent and with an action and that is what we are actually proposing with the data apps which is only possible if you're sitting on top of a snowflake or red shift kind of really powerful and massive cloud data warehouse where the data comes and moves with agility. >>So how has this cloud data model rewritten the rules of business? Because what you're bringing up is essentially now full interactivity really getting in, getting questions that are iterating and building on context to each other. But with all this massive cloud data, people are really excited by this. How is it changing business than the rules of business? >>Yeah. So think about, I mean topical things like there is a hurricane able to enter, hit the cost of the United States. It's a moving target. No one knows exactly where it is going to be. There is only 15 models from here. 10, 10 models from Europe that's going to predict which way it's going to take every millimeter change in that map is going to have significant consequences for lives and resources and money. Right. This is true for every business. What cloud does this? Uh you have your proprietary data for example, let's say you're a bank and you have proprietary data, you're launching a new product And the propriety data was 2025 extremely valuable. But what what's not proprietary but what is available to you? Which could make that data so much more relevant if you layer them on top census data, this was a census here. The census data is updated. Do you not want that vaccination leader? We clearly know that purchasing power parity will vary based on vaccinations and county by county. But is that enough? You need to have street by street is county data enough. If you're going to open startup, Mr Starbucks? No, you probably want to know much more granular data. You wanna know traffic. Is the traffic picking up business usually an office space where people are not coming to office or is it more of a shopping mall where people are still showing all of these data is out there for you? What cloud is making it possible? Unlike the old era where you know, your data is an SFP oracle or carry later in your data center, it's available for you with a matter of clicks. What thought sport modern analytics. Cloud is a simple thing. We are the front end to bring all of this data and make sense of it. You can sit on top of any cloud data and then interact with a complete sort of freedom without compromising on security, compliance or relevance. And what happens is the analysts, the people who are responsible for bringing the data and then making sure that it is secure and delivered. They are no longer doing incremental in chart updates and dashboard updates. What they're doing is solving business problems, business people there freely interacting and making bigger decisions. That actually adds value to their consumers. This is what your customers are looking for, your users are looking for and if you're not doing it, your competitor will do that. So this is why cloud is not a choice for you. It's not an option for you. It is the only way and if you fail to take that back the other way is taking the world out of a cliff. >>Yeah, that's I love it. But I want to get this uh topic of thoughts about anywhere, but I want to just close out on this whole idea of modern cloud scale analytics. What technology under the hood do you guys see that customers should pay attention to with thought spot and in general because the scale there. So is it just machine learning? We hear data lakes, you know, you know different configurations of that. Machine learning is always thrown around like a buzzword. What new technology capability should every executive by your customer look for when it comes to really doing analytics, modern in the cloud >>analytics has to be near real time, Which means what two things speed at scale, make sure it's complex, it can deal with complexity in data structure. Data complexity is a huge problem. Now imagine doing that at scale and then delivering with performance. That means you have to rethink Look Tableau grew out of excellent worksheets that is the market leader, it is a $40 billion dollar market with the largest company having only a billion dollars in revenue. This is a massive place where the problems need to be solved differently. So the underlying technology to me are like I said, these three things, number one cannot handle the cloud scale, you will have hundreds of billions of rows of data that you brought. But when you talk about social media sentiment of customers, analysis of traffic and weather patterns, all of these publicly available valuable data. We're talking trillions of rows of data. So that is scale. Now imagine complexity. So financial sector for example, there is health care where you know some data is visible, some data is not visible, some some is public assumption not or you have to take credit data and let it on top of your marketing data. So it becomes more complex. And the last is when you answer ask a question, can you deliver with absolute confidence that you're giving the right answer With extremely high performance and to do that you have to rebuild the entire staff. You cannot take your, you know, stack that was built in 1990s and so now we can do search So search that is built for these three things with the machine learning and ai essentially helping at every step of the way so that you're not throwing all this inside directly to a human, throw it to a i engine and the ai engine curates what is relevant to you, showing it to you. And then based on your interaction with that inside, I improve my own logic so that the next interaction, the next situation is going to be significantly better. My point is you cannot take a triple a map and then try to act like this google maps. One is built presuming and zoom out and learn from you. The other one is built to give you rich information but doesn't talk back. So the staff has to be fundamentally rebuilt for the club. That's what he's doing. >>I love I love to buy direction. I love the interactivity. This topic of thought spot everywhere, which you mentioned at the beginning of this conversation, you mentioned data apps which by the way I love that concept. I want to do a drill down on that. Uh I saw data marketplace is coming somewhat working but I think it's going to get it better. I love that idea of an app um, and using as developers but you also mentioned embedded analytics. You made a comment about that. So I gotta ask you what's the difference between data apps and embedded analytics? >>Embedded analytics means that uh you know the dashboards that you love but the one that doesn't talk back to you is going to be available inside the app that you built for your other So if a supply chain app that was built by let's say accenture inside that you haven't had your dashboard without logging into tablet. Great. But what you do, what's the big deal? It is the same thing. My point is like I said every time a business user sees a chart. The questions are going to come up. The next 10 question is where the values on earth for example on Yelp imagine if you will piece about I'm hungry. I want to find a restaurant and it says go to this burrito place. It doesn't work like that. It's not good enough. The reason why yell towards is because I start with an intent. I'm hungry. Okay show me all restaurants. Okay I haven't had about it for a while. Let me see the photos. Let me read the reviews. Let me see if my friends have eaten, let me see some menu. Can I walk there? I do all of this but just what underneath it. There is a rich set of data that probably helped have their own secret source and reviews and then you have google map powering some of them. But I don't care all of that is coming together to deliver a seamless experience that satisfies my hunger. Which will be very different from if you use the same map at the same place you might go to an italian place. I go to bed right. That is the power of a data app in business people are still sitting with this. I am hungry. I gotta eat burrito. That's not how it should be in the new world. A business user should have the freedom to add exactly what the customers require looking for and solve that problem without delay. That means every application should be power and enriched with the data where you can interact and customized. That is not something that enterprise customers are actually used to and to do that you need like I said a I and search powering like the google map underneath it, but you need an app like a yelp like app, that's what we deliver. So for example, uh just last week we delivered a service now app on snowflake. You know, it just changes the game. You are thinking about customer cases. You're a large company, you have support coming from Philippines and India some places the quality is good. Some places bad dashboards are not good enough saying that okay, 17% of our customers are unhappy but we are good. That's not the world we live in. That is the tyranny of >>average, >>17% were unhappy. You got to solve for them. >>You mentioned snowflake and they had their earnings. David and I were commenting about how some of the analysts got it all wrong. And you bring up a really good point that kind of highlights the real trend. Not so much how many new customers they got. But there do what customers are doing more. Right? So, so what's happening is that you're starting to see with data apps, it does imply Softwares in there because it's it's application. So the software wrapping around data. This is interesting because people that are using the snowflakes of the world and thought spot your software and your platform, they're doing more with data. So it's not so much. I use snowflake, I use snowflake now I'm going to do more with it. That's the scale kicking. So this is an opportunity to look at that more equation. How do you talk >>with >>when you see that? Because that's the real thing is like, okay, that's I bought software as a service. But what's the more that's happening? What do you see >>that is such an important point? Even I haven't thought about it that john but you're absolutely right. That is sometimes people think of snowflake is taking care of it and no. Yeah, yes, Sarah later used to store once and zeros and they're moving it into club. That is not the point. Like I said, marketplace as an example when you are opening it up for for example, bringing the entire world's data with one click accessible to you securely. That is something you couldn't do on number two. You can have like 100 suppliers and all of a sudden you can now take a single copy of data and then make it available to all of them without actually creating multiple copies and control it differently. That's not something without cloudy, potentially could do. So things like that are fundamentally different. It is much more than like one plus one equals two. It is one plus one is 33. Like our view is that when you are re platform ng like that, you have to think from customer first. What does the customer do? The customer care that you meant from Entre into cloud or event from Teradata snowflake. No, they will care if their lives are better. Are they able to get better services are able to get it faster. That's what it is. So to me it is very simple. The destiny of an insight or data information is action, right? Imagine you're driving a car and if your car updates the gas tank every monday morning, imagine how you know, stressful your life will be for the whole week. I have to wait until next monday wanting to figure out what, whether I have enough gas or not, that's not the new world, that information is there, you need to have it real time and act on it. If you go through the Tesla you realize now that you know, I'm never worried about mileage because it is going to take me to the supercharger because it knows what I need to get to, it knows how long it is going to be, how bad the traffic is. It is synthesizing all of that to give me peace of mind. >>So this is a great >>conversation. That's a >>great question. It's a great conversation because it's really kind of brings in kind of what's happening, you see successful companies that are working with cloud scale and data like you're talking about, it's you get in there, you get the data, the data apps and all of a sudden you hit it, you hit the value equation and it's like almost like discovering oil all of a sudden you have a gusher and then people just see massive increase in value. It's not like the outcome, it's kind of there, you've got to kind of get in there and this is the scale piece and you see people having strategies to do that, they say okay we're gonna get in there, we're going to use the data to iterate but also watch the data learn where's that value, This is that more trend and and there's a successful of the developing. So I have to ask you when you, when you talk about people and culture, um that's not the way it used to be, used to be like okay I'm buying an outcome. I deployed some software mechanisms and at the end of the day there's some value there. Maybe I write it off maybe I, you know, overtime charges and some accounting thing. All changed the culture and the people in charge now are transforming the management techniques. What do you see as a successful mindset for a customer as they managed through these new paradigms and new new success formulas. >>I see a fork in leadership when it comes to courage. There are people with the spine and there are people without the spine and the ones with the spine are absolutely killing it. They are unafraid. They are not saying, look, I'm just going to stick with the incumbents that I've known for the last 20 years. Look, I used to drive a Toyota forever because I love the Toyota. And then you know after Nutanix IPO went to Lexus still Toyota because it's reliable. I don't, I'm not a huge card person. It works. But guess what? I knew they were missing Patrick and I care about the environment. I don't want to keep pushing hydrocarbons out there. It's not politics. I just don't like burning stuff into the earth atmosphere. So when Tesla came out, it's not like I love the quality I don't personally like alone mask, you know after that Thailand fiasco of cave rescue and all of that. But I can clearly see that Toyota is not going to catch up to Tesla in the next 10 years. And guess what? My loyalty is much more to doing the right thing for my family and to the world. And I switched this is what business leaders need to know. They can't simply say, well, tabloid as search to. They're not as good as thought sports. We'll just stick with them because they have done with us. That's what weak leaders do and customers suffer for that. What I see like the last two weeks ago when I was in new york. I met with them. A business leader for one of the largest banks in the world with 25,000 people reporting to him. The person walks into the room wearing shorts and t shirts uh, and was so full of energy and so full of excitement. I thought I'm going to learn from him and he was asking questions about how we do our business in bed and learning from me. I was humbled, I was flawed and I realized that's what a modern business leader looks like. Even if it is one of the largest and oldest banks in the world, that's the kind of people are making big difference and it doesn't matter how all the companies, how old their data is they have mainframes or not. I hear this excuses all the type of er, mainframes, we can't move, we have COBOL going on. And guess what? You keep talking about that and hear leaders like him are going to transform those companies And next thing you know, there are some of the most modern companies in the world. >>Well certainly they, we know that they don't have any innovation strategy or any kind of R and D or anything going on that could be caught flat footed in the companies that didn't have that going on, didn't have the spine or the, the, the vision to, to at least try the cloud before Covid when Covid hit, those companies are really either going out of business or they're hurting the people who were in the cloud really move their teams into the cloud quicker to take advantage of uh, the environment that they had to. So this became a skill issue. So, so this is a big deal. This is a big deal. And having the right skills are people skilled, it will be a, I both be running everything for them. What is your take on that? >>This is an important question. You can't just say you got to do more things or new things and not take care of all things. You know, there's only 89, 10 hours so you can work in their uh, analysts in the Atlantic species constantly if your analysts are sitting there and making incremental dashboards and reports change every day and then backlog is growing for 56 days and the users are unhappy because you're not getting answers and then you ask them to go to new things. It's just not going to be enough and you can hire your way out of it. You have to make sure that if you say that I have 20 100 x product already, I don't want 21st guess what? Sometimes to be five products, you need to probably go to 21 you got to do new things to actually take away the gunk off the old and in that context, the re skilling starts with unburdening, unburdening of menial task, unburned routine task. There is nothing more frustrating than making reports and dashboards that people don't even use And 90% of the time analysts, they're amazing experiences completely wasted when they're making incremental change to tabloid reports. I kind of believe thought spot and self service on top of cloud data takes away all of that without compromising security and then you invest the experienced people. Business experience is so critical. So don't just go and hire university students and say, okay, they'll go come and quote everything the experience that they have in knowing what the business is about and what it matters to their users, that domain experience and then uplevel them res kill them and then bring fresh energy to challenge that and then make sure there is a culture that allows that to happen. These three things. That's why I said leadership is not just about hiring event of firing another, it's about cultivating a culture and living that value by saying, look if I am wrong, call me, call me out in public because I want to show you how I deal with conflict. So this is I love this thing because when I see these large companies where they're making these massive changes so fast, it inspires you to say you know what if they can do it, anyone can do it. But then I also see if the top leadership is not aligned to that. They are just trying to retire without the stock tanking too much and let me just get through two more years. The entire company suffers. >>So that's great to chat with you got great energy, love your business, love the energy, love the focus. Um it's a new wave you're on. It's a big wave um and it's it's relevant, it's cool and relevant and it's the modern way and people have to have a spine to be successful if not for the faint of heart, but the rewards are there if you get this right. This is what I I love about this new environment. Um so I gotta ask you just to kind of close it out. How would you plug the company for the folks watching that might want to engage with you guys. What's the elevator pitch? What's the positioning? How would you describe thought spot in a bumper sticker or in a positioning statement. Take a minute to talk about that. >>Remember martin Anderson said that software is eating the world, I think it is now time to update that data is eating everything including software. If you don't have a way to turn data into bespoke action for your customers. Guess what? Your customers are gonna go somewhere where they that's happening right? You may not be in the data business but the data company is going to take your business. Thought spot is very simple. We want to be the friend tent for all cloud data when it comes to structured because that's where business value numbers is world satisfaction and dissatisfaction for reduces allying it is important to move data to action and thought Spot is the pioneer in doing that through search and I >>I really think you guys want something very powerful. Looking forward to chatting with you at the upcoming eight of a startup showcase. I think data is a developer mindset. It's an app, it's part of everything. It will. Everyone's a data company, everyone is a media company. Data is everything you guys are on something really big and people got a program it with it, make experiences whether it's simple scripts, point and click. That is a new kind of developer out there. You guys are tapping into it. Great stuff. Thank >>you for coming on. Thank you john it's good to talk to you. >>Okay. It's a cube conversation here in Palo alto California were remote. We're virtual. That's the cube virtual. I'm sean for your host. Thanks for watching. Mhm. Mhm

>>from >>around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Everyone welcome back to the cubes Coverage of AWS reinvent 2020 virtual. This is the Cube virtual. I'm John for your host this year. We're not in person. We're doing remote interviews because of the pandemic. The whole events virtual over three weeks for this week would be having a lot of coverage in and out of what's going on with the news. All that stuff here happening on the Cube Our next guest is a featured segment. Brown Venkatesh, VP of Engineering at Cloudera. Welcome back to the Cube Cube Alumni. Last time you were on was 2018 when we had physical events. Great to see you, >>like good to be here. Thank you. >>S O. You know, Cloudera obviously modernized up with Horton works. That comedy has been for a while, always pioneering this abstraction layer originally with a dupe. Now, with data, all those right calls were made. Data is hot is a big part of reinvent. That's a big part of the theme, you know, machine learning ai ai edge edge edge data lakes on steroids, higher level services in the cloud. This is the focus of reinvents. The big conversations Give us an update on cloud eras. Data platform. What's that? What's new? >>Absolutely. You are really speaking of languages. Read with the whole, uh, data lake architecture that you alluded to. It's uploaded. This mission has always been about, you know, we want to manage how the world's data that what this means for our customers is being ableto aggregate data from lots of different sources into central places that we call data lakes on. Then apply lots of different types of passing to it to direct business value that would cdp with Florida data platform. What we have essentially done is take those same three core tenants around data legs multifunctional takes on data stewardship of management to add on a bunch off cloud native capabilities to it. So this was fundamentally I'm talking about things like disaggregated storage and compute by being able to now not only take advantage of H d efs, but also had a pretty deep, fundamental level club storage. But this is the form factor that's really, really good for our customers. Toe or to operate that from a TCO perspective, if you're going to manage hundreds of terabytes of data like like a lot of a lot of customers do it. The second key piece that we've done with CDP has to do with us embracing containers and communities in a big way on primer heritages around which machines and clusters and things of that nature. But in the cloud context, especially in the context, off managed community services like Amazon CKs, this Lexus spin apart traditional workloads, Sequels, park machine learning and so on. In the context of these Cuban exiles containerized environments which lets customers spin these up in seconds. They're supposed to, you know, tens of minutes on as they're passing, needs grow and shrink. They can actually scale much, much faster up and down to, you know, to make sure that they have the right cost effective footprint for their compute e >>go ahead third piece. >>But the turkey piece of all of this right is to say, along with like cloud native orchestration and cloud NATO storage is that we've embraced this notion of making sure that you actually have a robust data discovery story around it. so increasingly the data sets that you create on top off a platform like CDP. There themselves have value in other use cases that you want to make sure that these data sets are properly replicated. They're probably secure the public government. So you can go and analyze where the data set came from. Capabilities of security and provenance are increasingly more important to our customers. So with CDP, we have a really good story around that data stewardship aspect, which is increasingly important as you as you get into the cloud. And you have these sophisticated sharing scenarios. The >>you know, Clotaire has always had and Horton works. Both companies had strong technical chops. It's well document. Certainly the queues been toe all the events and covered both companies since the inception of 10 years ago. A big data. But now we're in cloud. Big data, fast data, little data, all data. This is what the cloud brings. So I want to get your thoughts on the number one focus of problem solving around cloud. I gotta migrate. Or do I move to the cloud immediately and be born there? Now we know the hyper scale is born in the cloud companies like the Dropbox in the world. They were born in the cloud and all the benefits and goodness came with that. But I'm gonna be pivoting. I'm a company at a co vid with a growth strategy. Lift and shift. Okay, that was It's over. Now that's the low hanging fruit that's use cases kind of done. Been there, done that. Is it migration or born in the cloud? Take us through your thoughts on what does the company do right now? >>E thinks it's a really good question. If you think off, you know where our customers are in their own data journey, right? So increasingly. You know, a few years ago, I would say it was about operating infrastructure. That's where their head was at, right? Increasingly, I think for them it's about deriving value from the data assets that they already have on. This typically means in a combining data from different sources the structure data, some restructure data, transactional data, non transactional, data event oriented data messaging data. They wanna bring all of that and analyze that to make sure that they can actually identify ways toe monetize it in ways that they had not thought about when they actually stored the data originally, right? So I think it's this drive towards increasing monetization of data assets that's driving the new use cases on the platform. Traditionally, it used to be about, you know, sequel analysts who are, if you are like a data scientist using a party's park. So it was sort of this one function that you would focus on with the data. But increasingly, we're seeing these air about, you know, these air collaborative use cases where you wanna have a little bit of sequel, a little bit of machine learning, a little bit off, you know, potentially real time streaming or even things like Apache fling that you're gonna use to actually analyze the data eso when this kind of an environment. But we see that the data that's being generated on Prem is extremely relevant to the use case, but the speed at which they want to deploy the use case. They really want to make sure that they can take advantage of the clouds, agility and infinite capacity to go do that. So it's it's really the answer is it's complicated. It's not so much about you know I'm gonna move my data platform that I used to run the old way from here to there. But it's about I got this use case and I got to stand this up in six weeks, right in the middle of the pandemic on how do I go do that on the data that has to come from my existing line of business systems. I'm not gonna move those over, but I want to make sure that I can analyze the data from their in some cohesive Does that make sense? >>Totally makes sense. And I think just to kind of bring that back for the folks watching. And I remember when CDP was launching the thes data platforms, it really was to replace the data warehouse is the old antiquated way of doing things. But it was interesting. It wasn't just about competing at that old category. It was a new category. So, yeah, you had to have some tooling some sequel, you know, to wrangle data and have some prefabricated, you know, data fenced out somewhere in some warehouse. But the value was the new use cases of data where you never know. You don't know where it's going to come until it comes right, because if you make it addressable, that was the idea of the data platform and data Lakes and then having higher level services. So s so to me. That's, I think, one distinction kind of new category coexisting and disrupting an old category data warehousing. Always bought into that. You know, there's some technical things spark Do all these elements on mechanisms underneath. That's just evolution. But income in incomes cloud on. I want to get your thoughts on this because one of the things that's coming out of all my interviews is speed, speed, speed, deploying high, high, large scale at very large speed. This is the modern application thinking okay to make that work, you gotta have the data fabric underneath. This has always been kind of the dream scenario, So it's kind of playing out. So one Do you believe in that? And to what is the relationship between Cloudera and AWS? Because I think that kind of interestingly points to this one piece. >>Absolutely. So I think that yeah, from my perspective, this is what we call the shared data experience that's central to see PP like the idea is that, you know, data that is generated by the business in one use case is relevant and valid in another use case that is central to how we see companies leveraging data or the second order monetization that they're after, Right? So I think this is where getting out off a traditional data warehouse like data side of context, being able to analyze all of the data that you have, I think is really, really important for many of our customers. For example, many of them increasingly hold what they call this like data hackathons right where they're looking at can be answered. This new question from all the data that we have that is, that is a type of use case that's really hard to enable unless you have a very cohesive, very homogeneous view off all of your data. When it comes to the cloud partners, right, Increasingly, we see that the cloud native services, especially for the core storage, compute and security services are extremely robust that they give us, you know, the scale and that's really truly unparalled in terms of how much data we can address, how quickly we can actually get access to compute on demand when we need it. And we can do all of this with, like, a very, very mature security and governance fabric that you can fit into. So we see that, you know, technologies like s three, for example, have come a long way on along the journey with Amazon on this over the last 78 years. But we both learned how to operate our work clothes. When you're running a terabytes scale, right, you really have to pay attention to matters like scale out and consistency and parallelism and all of these things. These matters significantly right? And it's taken a certain maturity curve that you have to go through to get there. The last part of that is that because the TCO is so optimized with the customer to operate this without any ops on their side, they could just start consuming data, even if it's a terabyte of data. So this means that now we have to have the smarts in the processing engines to think about things like cashing, for example very, very differently because the way you cash data that Zinn hedge defense is very different from how you would do that in the context of his three are similarly, the way you think about consistency and metadata is very, very different at that layer. But we made sure that we can abstract these differences out at the platform layer so that as an as it is an application consumer, you really get the same experience, whether you're running these analytics on clam or whether you're running them in the cloud. And that's really central to how I see this space evolving is that we want to meet the customer where they are, rather than forcing them to change the way they work because off the platform that they're simple. >>So could you take them in to explain some of the integrations with AWS and some customer examples? Because, um, you know, first of all, cost is a big concern on everyone's mind because, you know, it's still lower costs and higher value with the cloud anyway. But it could get away from you. So you know, you're constantly petabytes of scale. There's a lot of data moving around. That's one thing to integration with higher level services. Can you give where does explain how Claudia integration with Amazon? What's the relation of customer wants to know. Hey, you guys, you know, partnering, explain the partnership. And what does it mean for me? >>Absolutely. So the way we look at the partnership hit that one person and ghetto. It's really a four layer cake because the lowest layer is the core infrastructure services. We talked about storage and computing on security, and I am so on and so forth. So that layer is a very robust integration that goes back a few years. The next layer up from that has to do with increasingly, you know, as our customers use analytic experiences from Florida on, they want to combine that with data that's actually in the AWS compute experiences like the red Ship, for example. That's what the analytics layer uploaded the data warehouse offering and how that interrupts would be other services in Amazon that could be relevant. This is common file formats that open source well form it really help us in this context to make sure that they have a very strong level of interest at the analytics there. The third layer up from that has to do with consumption. Like if you're gonna bring an analyst on board. You want to make sure that all of their sequel, like analyst experiences, notebooks, things of that nature that's really strong. And club out of the third layer on the highest layer is really around. Data sharing. That's as aws new and technologies like that become more prevalent. Now. Customers want to make sure that they can have these data states that they have in the different clouds, actually in a robbery. So we provide ways for them, toe browse and search data, regardless of whether that data is on AWS or on traffic. And so that's how the fourth layer in the stack, the vertical slice running through all of these, that we have a really strong business relationship with them both on the on the on the commercial market side as well as in AWS marketplace. Right? So we can actually by having cdp be a part of it of the US marketplace. This means that if you have an enterprise agreement with with Amazon, you can actually pay for CDP toe the credit sexuality purchased. This is a very, very tight relationship that's designed again for these large scale speeds and feeds. Can the customer >>so just to get this right. So if I love the four layer cake icings the success of CDP love that birthday candles can be on top to when you're successful. But you're saying that you're going to mark with Amazon two ways marketplace listing and then also jointly with their enterprise field programs. That right? You say because they have this program you can bundle into the blanket pos or Pio processes That right can explain that again. >>S so if you think this'll states, if you're talking about are significant. So we want to make sure that, you know, we're really aligned with them in terms off our cloud migration strategy in terms of how the customer actually execute to what is a fairly you know, it's a complex deployment to deploy a large multiple functions did and existed takes time, right, So we're gonna make sure that we navigate this together jointly with the U. S. To make sure that from a best practices standpoint, for example, were very well aligned from a cost standpoint, you know what we're telling the customer architecturally is very rather nine. That's that's where I think really the heart of the engineering relationship between the two companies without. >>So if you want Cloudera on Amazon, you just go in. You can click to buy. Or if you got to deal with Amazon in terms of global marketplace deal, which they have been rolling out, I could buy there too, Right? All right, well, run. Thanks for the update and insight. Um, love the four layer cake love gets. See the modernization of the data platform from Cloudera. And congratulations on all the hard work you guys been doing with AWS. >>Thank you so much. Appreciate. >>Okay, good to see you. Okay, I'm John for your hearing. The Cube for Cube virtual for eight of us. Reinvent 2020 virtual. Thanks for watching.

>> from Seattle Washington. It's the Q covering AWS. Imagine nonprofit brought to you by Amazon Web >> service is >> Hey, welcome back already. Jeffrey here with the Cube were in >> the waterfront, actually in Seattle, Washington. It's an absolutely gorgeous August day. We're here for the AWS. Imagine nonprofit event. It's the fourth year they've had. It is the first year's been kind of open to the public. It was invitation only. And we're excited to be here for our first time. Our >> guest is here for his first time, too. And >> we're excited to sit down with side L. Nash. He is the vice president. And of I t and C i o for the National Council on Aging. Say great to see you. >> Thank you. Good to see you. Yeah. So, first >> off, just kind of impressions on the event So far. Really good keynotes this morning. And they got a full two days planned for you. >> Yes, it was an excellent good note. Keynote speaks to the speech this morning and, uh, started off talking about impact and how nonprofit organizations make it make a difference in the world. >> Right. So National Council of Aging, the population is aging Maur Every day they keep sending me my my card in the mail that keep pretending I'm not old enough to get. But >> don't try to pretend exactly they are >> double AARP. Thank you very much for the car, but, um, there's a lot of unique challenges with as the population continues to get holding. What are some of your organisation's priorities? How do you address this kind of growing population in our society? >> So I'll share with you some statistics on aging. So there are about 72,000,060 and older adults in the U. S. 70 >> 1,000,000 to three on its growing >> and growing. It will be 92,000,000 in 2030. So it's a growing larger segment of the population. People are living longer, saving less about but half of those so are 60 plus have saving off about $30,000 about 80% off 60 plus have about maybe to chronic disease conditions. So people are living longer, saving less money, and obviously with that, there are a lot of challenges, and this is where we step in. So we step in. Our mission is to help people age healthier and wealthier, try to make sure that they planned correctly for their savings. And they plan correctly also for their convention there chronic diseases and managing their health in general. And so for that, we have a lot off just products, actually that help older adults figuring out there how to live in older and healthy life. One of them is our flagship product, helping people get access to ah, federal, state and local government benefits. It's called benefits. Checkup is the largest system decision support system in the country that helps older adults figuring out how what benefits take all 54 and how to apply. And we walked them through that whole process. >> So it's also not necessarily the most technically astute population, either, especially today seniors who didn't grow up his digital natives like a lot of the kids are today. And >> as you said, your your guys >> objective number one is economic security. Maybe not necessarily number one, but top of the list and then healthy living. And they don't have the benefit of of time for therefore one case and stuff to grow. So these air pretty unique challenges. How are you helping him? And then you know we're here in eight of us. What role has eight of us played in helping you reach your your constituent? >> Clear? You're asking a lot of questions in one. So let me try and answer them one by one. So let's take a >> look at the aging population, especially the older adults. 70 plus those who actually don't have. Ah, I don't know. They're not necessity technology savvy, but they have Ah, they have cell phone. It's over. 73% of them have cell phones and some have smartphones. S o. We looked at the different ways of trying to reach out to them. And one of the things that we experimented with is looking at an SMS texting pilot. So we actually started that pilot and was very successful. And well, now we're rolling out into a full production system. It's a we found out that it's a great channel. It's very simple asking simple questions. Did you apply yes or no? Just answer us if you were to do one or two. So tell us give us a very simple answer and we found that the engagement rates are way above the average industry. People tend to respond to text messages for better than actually telling them. Hey, there's the mobile app. Go download my mobile already So that's one aspect of it on the AWS Sod off it. So when I joined and see away about a year and 1/2 ago, we were in Private Cloud and in that situation we had a lot of single point of failures and disaster recovery was in bad shape. And so we realized that we needed to move into a new and more robust environment, one that solved the single all the risks that we had from disaster recovery. Single point of failures to also being able to innovate quickly and fast. And so we looked that we started the ah migration process to the cloud and we ended up on AWS back in February. This year would move 95% of our assets to the cloud to AWS Cloud and we medicated the two major risks. The single point of failure is disaster recovery and so on. And with that, we also have a lot of other tools that are out of the box that we're using right now with the AWS platform. >> That's great So, um, I want it back up to the S, the best comic cause That's really interesting. So how do you find your customers? How do you get people get engaged? Obviously, art center the card in the mail. You know, there's a lot of organizations that that we get involved with. How do you directly engage with your clients? >> So we do a lot of digital marketing, believe it or not. So we spent a lot off time money and energy into digital marketing on Facebook. So a good number of older adults are on Facebook. There's also a good percentage of them that are on YouTube. Unfortunately, older adults spend about 46 hours watching either TV or videos on the Web, those who have access to the Web. So that's one way we're trying to reach them. So these are our sort of marketing funnels. In addition to that, we have about close to 100 centers around the U. S. Where older those can actually go in and be helped and go walk through the process of applying for federal state local government benefits. And so we have. They're called benefits benefits centers. And so the those centers are open to the public. We also try to collaborate with different with different organizations around the country, through through whom we get older adults too engage with us and joined the benefits checkup program. And with that, we we ask people to our 10. So we take a very cautious and very respectful approach to data and privacy to ask people to opt in. And we tell them about how we're using the data. We encrypt the data address. We take very caring very good care of it. We don't share it outside of organization. So we have our own internal data privacy principles. So we take this matter very seriously again. Our objectives always the hope older adults live a better, healthier and wealthier life, >> right? I just love that the older people are now using Facebook and SMS like kids. >> 15 years ago, they moved on >> to other platforms. Thank goodness for the old folks keeping the Facebook and, uh >> so let's shift gears. A little >> bit of talk about your transformation in your movement to the cloud. How big of an effort was that? How long did it take? And, you know, hasn't really opened up the innovation because there's clearly cost savings. And as you talked about a single point of failure and kind of mitigating the negatives, but as well as we've seen over and over again, really, the benefits from from Cloud are really that innovation and delivering service is faster. So how's your experience? >> That's exactly right. So So let me talk a little bit about the traditional transformation. So about, I would say, year over year ago, we started our digital transformation initiative. It's really focused on customers, we call it, knowing our customers as individuals with individual needs. Traditionally organizations like ours looked at older adults. In the perspective, off percentages averages, on average is is how old they are on average, in this is their income. On average, this is their health. But in reality, every older adult is an individual that has specific and individual needs, and we need to really take a look at that and caters to those very specific needs that they actually changed over time. So the transformation really enabled it. We needed to move to a cloud where we can have products immediately that we can spend off and use a I machine learning products and so on. And so I'm gonna go back and talking more about our a digital transformation and the perspectives off it. So our objective long term is to build was recalling the the aging Well, aye aye. Engine. It's basically imagine an older adult waking up in the morning and trying to decide what are the top best three things for me to do. Stop the actions for me to do to improve my life. And we wanna help that older adult make those decisions easily and quickly through a frictionless interactions. Frictionless. Conversational. Aye, aye. Speaking to an Alexa like voice enabled smart speaker asking Alexa, what should I do today? Alexis, respond. The weather is nice out there. Call your friend. Go for a walk. Call your doctor, get the lab results and so on. And check your benefits on benefits. Check up and figure out and improve your life. So the idea is to really get the person to actively and the actively using technology and simple, frictionless way to be able to make those decisions that improve their lives. So for us to do this kind of work to build the aging. Well, Aye, aye. Engine. It is impossible without being on a cloud like >> a w. Interesting. So, uh, first time I've heard about Lexus since we've been here. A lot of talk about Lex at the education conference a couple of weeks back. So is Alexa. Pretty key piece of your strategy going forward, you really see voice as a different type of communication. You mentioned. That's a message. Just kind of old, but really effective. How do you see Alexa playing >> so absolutely so voice enabled communication channels. So we look at it as actually we look at our communication with older adults. We look at it as an Army channel communication. Every person have their own preference of the way they interact with technology. Some people prefer SMS. Others like to speak to Alexa. Others like to go through the web and so on. Some are on Facebook or YouTube, etcetera. So each we have our own choices. And that's exactly why we need to look at the older adults as individuals with their individual needs. And then our job is to deliver those to deliver all products through those different channels individually. So delivering the right product with the right customer at the right time and through the right channels. So lax is one of the channels it is. It's not the only channel or the voice channel I would call it is not the only channels. What we found out is that older adults find Alexis is very engaging. It reduces social isolation. It helps with the many other tests, especially for those who are visually inferred. The the complexity. The challenge for older adults is setting it up, so that's what we're trying to look at. Ways of trying to packages will be package so that it is possible for the older adult to plug it in and be able to use it. The other thing that we discovered, we probably need to look at family caregivers as the customer segment of the customer target that we would work with really enable looks, um, >> interesting. Let's see, it seems like a natural fit once you get kind of the tone and the and the comfort worked out, and I would imagine you're writing all types of specific things for to do and types of activities for Alexa to do for the specific needs of this older generation, >> so yeah. So we started >> a very small proof of concept project with Alexa trying to engage an experiment for me, everything that we do has to bring in value. And I need to also make sure that we are when we deliver a product or customers. That product actually delivers that value and engages the customers. So we know that there are there is the value in there were also working with partners on delivering this voice channel. So I know that we have, as a non profit organization with our, you know, a limited resource is. And so we look at partners as a way to enable those votes channels on the different channels that we have >> exciting, exciting times. And I look forward to watching that innovation pulls out at a high rate of speed. So thanks for taking a few minutes and safe travels home. >> Okay. Thank you, Seed. I'm Jeff. You're watching the keyboard aws. Imagine >> in Seattle. Thanks for watching. We'll see you next time

(upbeat techno music) >> Live from Las Vegas, it's theCUBE. Covering Boomi World 2018. Brought to you by Dell Boomi. >> Good afternoon, welcome back to theCUBE's continuing coverage of Boomi World 2018 from Las Vegas. I'm Lisa Martin with John Furrier and we're welcoming back to theCUBE one of our alumni Nima Badiey, Head of Technology Ecosystems from Pivotal. Nima, welcome back. >> Thank you for having me back. >> So Pivotal, part of the Dell technologies part of the companies, >> Yeah. >> You guys IPOd recently. And I did read that of the first half 2018, eight of the 10 tech IPOs were powered by Boomi. >> Well, I don't know about that specific. I know that tech IPOs are making a big comeback. We did IPO on the 20th of April, so we've passed out six-month anniversary if you can say. But it's been a distinct privilege to be part of the overall Dell family of businesses. I think what you have in Michael as a leader, who, he has a specific vision, but he's left the independent operating units to work on their own, to find their path through that journey, and to help each other as brethren, as like sisters and brothers. And the fact that Pivotal is here supporting Boomi. That Boomi is within our conference of supporting our customers that we're working together really speaks volumes. I think if you take a look at it, a lot of things happened this week, right? So a couple weeks ago, IBM's acquiring RedHat, this morning VMWare's acquiring Heptio. That's a solid signal that the enterprise transformation and adoption of cloud native model is really taking off. So the new middleware is really all about the cloud native polyglock, multiglock environment. >> And what's interesting, I want to get your thoughts on this because first of all congratulations on the IP, some are saying Pivotal's never going to go public, and they did, you guys were spectacular, great success. But what's going on now is interesting. We're hearing here at this show, as other shows is, cloud scale and data are really at the center of this horizontally scalable cloud poly proposition. Okay great, you mention Kubernetes and Heptio and VM where, that's all great. The question that is how do you compete when ecosystems become the most important thing. You worked at VMware you're at Pivotal. Dell knows ecosystems. Boomi's got an ecosystem. Partners, which is also suppliers and integrators. >> Yeah. >> They integrate and also developers. This is a key competitive advantage. What's your take on that here? >> So I think you touched on the right point. You compete because of your ecosystem, not despite your ecosystem. We can't be completely hedgemonic like Microsoft or Cisco or Amazon can afford to be. And I don't think customers really want that. Customers actually want choice. They want the best options but from a variety of sources. And that's why one of the reasons that we not only invest Dell ecosystem but also in Pivotal's own ecosystem is to cultivate the right technologies that will help our customers on that journey. And our philosophy's always find the leaders in the quadrant. The Cadillac vendors, the Lexus vendors onboard them and the most important thing you can do is, to ensure a pristine customer experience. We're not measuring whether feature A from one partner is better than feature B from another partner. We really don't care. What we care about is we can hand wire and automate what would have been a very manual process for customers, so that, let's say Boomi with Cloud Foundry works perfectly out of the box. So the customers doesn't have to go through and hire consultants and additional external resources just to figure out how two pieces of software should work together, they just should. So when they make that buying decision they know that the day after that buying decision, everything's going to be installed and their developers and their app dev teams and their ops teams can be productive. So that's the power of the ecosystem. >> Can you talk about the relationship between Pivotal and Boomi, because Boomi's been born in the Cloud as start up. Acquired eight years ago. You're part of the Dell Technologies family. VMware's VMware, we know about VMware doing great. You guys doing great. Now Boomi's out there. So how do they factor into and what's the relationship you have with them and how does that work, how do you guys work together? >> Perfect question. So, in my primary role at Pivotal is to manage all of our partner ecosystems, specifically the technology partners. And what I look for are any force multipliers. Any essentially ISVs who can help us accomplish more together than we could on our own. Boomi's a classic example of that. What do they enable? So take your classic customer. Classic customer has, let's say, 100 applications in inventory that they have built, managed, and purchased procured off from shelf-to-shelf components. And roughly 20 or 30% are newish, green field applications, perfect for the cloud native transformation. Most 80% of them or 70% are going to be older, ground field applications that will have to be refactored. But there's always going to be that 15% towards the end that's legacy mainframe. It can't be changed, you cannot afford to modernize it, to restructure it, to refactor it. You're going to have to leave it alone, but you need it. Your inventory systems are there. >> These are critical systems, those people who think legacy as outdated, but they're actually just valued. >> No, they're critically valuable. >> Yes. >> We just cannot be modernized. >> Bingo. >> So a partner like Boomi will allow you to access the full breadth of those resources without having to change them. So I could potentially put Boomi in front of any number of older business applications and effectively modernize them by bridging those older legacy systems with the new systems that I want to build. So let's do an example. I am the Gap and I want to build a new version of our in-store procurement system that runs on my iPhone, that I can just point to a garment and it will automatically put it in my, ya know, check out box. How do I do that? Well I can build all the intelligence. And I can use AI and functions and I can build everything it's out of containers, that's great. But I still have to connect to the inventory system. Inventory system... >> Which is a database. All these systems are out there. >> Somewhere, something. And my developers don't know enough about the old legacy database to be able to use it. But if I put a restful interface using Boomi in front of it and a business connector that's not older XML or kind of inflexible, whatever, solo gateways. Then I have enabled my developer to actually build something that is real. That is customer focused. It is appropriate for that market without being hamstrung by my existing legacy infrastructure. And now my legacy infrastructure is not an anchor that's holding me back. >> You had mentioned force, me and Lisa talk about this all the time on theCUBE, where that scenario's totally legit and relevant because in the old version of IT you have to essentially build inventory management into the new app. You'd have to essentially kill the old to bring in the new. I think with containers and cloud native has shown is you can keep the old and sunset it if you want on your own time table or keep it there and make it productive. Make the data exposeble, but you can bring the cool relevant new stuff in. >> Yeah. >> I think that is what I see and we see from customers, like OK cool, I don't have to kill the old. I'll take care of it on my own timetable versus a complete switching cost analysis. Take down a production system. >> Exactly. >> Build something new, will it work. Ya know cross your fingers. Okay, again and this is a key IT different dynamic. >> It is and it's a realization that there are things you can move and those are immutable. They're simply just monolithic that will never move. And you're going to work within those confines. You can have the best of both worlds. You can maintain your legacy applications. They're still fine, they run most of your business. And still invent the new and explore new markets and new industries and new verticals. And just new capabilities all through and through without having to touch in your back end systems. Without having to bring the older vendors in and say can you please modernize your stuff because my business is dependent and I am going to lose that. I'm going to become the new Sears, I going to become the new Woolworth or whoever. Blockbuster that has missed an opportunity to vector into a new way of delivering their services. >> When you're having customer conversations, Nima, I'm curious, talking with enterprise organizations who have tons of data, all the systems including the legacy, which I'm glad that you brought up that that's not just old systems. There's a lot of business critical, mission critical application running on 'em. Where do you start that conversation with the large enterprise, who doesn't want to become a Blockbuster to your point, and going this is the suite of applications we have, where do we start? Talk to us about that customer journey that you help enable. >> That's great 'cause in most cases the customers already know exactly what they want. It's not the what that you have to have the conversation around, it's the how do I get there. I know what I want, I know what I want to be, I know what I want to design. And it's how do I transform my business fundamentally do an app transformation, enterprise transformation, digital transformation? Where do I begin? And so, ya know, our perspective at Pivotal is, ya know, we're diehard adopters of agile methodology. We truly, truly believe that you can be an agile development organization. We truly believe in Marc Andreessen's vision of software eating the world. Which let's unpack what that means. It just means that if you're going to survive the next 10 years you have to fundamentally become a software company, right? So look at all the companies we work with. Are you an insurance company or are you delivering an insurance product through software? Are you a bank or are you delivering banking product through software? Well, when was the last time you talked to a bank teller? Or the atm, most of your banking's done online. Your computer or your mobile device. Even my check cashing, I don't have to talk to anyone. It's wonderful. Ford Motor Company, do they bend sheet metal and put wheels on it or are they a software company? Well consider that your modern pickup truck has... >> They're an IOT company now. (laughing) (crosstalking) Manufacturing lines. >> That's what's crazy. You have a 150 million lines of code in your pickup truck. Your car, your pickup truck, your whatever is more software than it is anything else. >> But also data's key. I want to get your thoughts since this is super important Michael Dell brought up on the keynote today here at Boomi World was, okay the data's got to stay in the car. I don't need to have a latency issue of hey, I need to know nanosecond results. With data, cloud has become a great use case. With multicloud on the horizon, some people are going to throw data in multiple clouds and that's clear use case, and everyone can see the benefits of that. How do you guys look at this? 'Cause now data needs to be addressable across horizontal systems. You mentioned the Gap and the Gap example. >> That's great, so, one of the biggest trends we see in data is really event streaming. Is the idea that the ability to generate data far out exceeds the ability to consume it. So, what if we treated data as just a river? And I'm going to cast my line and only pick up what I want out of that stream. And this is where CAFCA and companies like Solice and any venturing networks and spring cloud functions and spring cloud data are really coming into play, is acknowledgement that yes we are not in a world where we can store all of the data all the time and figure out what to do with it after the fact. We need timely, and timely is within milliseconds, if not seconds. Action taken on an event or data even coming through. So why don't we modernize around, ya know, that type of data structure and data event and data horizon. So that's one of the trends we see. The second is that there is no one database to rule them all anymore. I can't get away with having oracle and that's my be all, end all. I now have my ESQL and SQL and Mongo and Cassandra and Redis and any other number of databases that are form, fit and function specific for a utility and they're perfect for that. I see graph databases, I see key value stores, I see distributed data warehouse. And so my options as a developer, as a user is really expanding, which means the total types of data components that I can use are also expanding exponentially. And that gives me a lot more flexibility on the types of products that I can build and the services that I can ultimately deliver. >> And that highlights micro services trend, because you have now a multitude of databases, it's not the one database rules them all. They'll be literally thousands of database on censors, so micro service has become the key element to connect all these systems. >> All of it together. And micro services really a higher level of abstraction. So we started with virtual machines and then we went to containers and then we went to functions and micro services. It's on an upward trend necessarily as it is an expansion. Into different ways of being able to do work. So some of my work products are going to be very, very small. They can afford to be ephemeral, but there may be many of them. How do I manage a cluster of millions of these potential work loads? Backing off I can have an ephemeral applications that run inside of containers or I can have ridged fixed applications that have to run inside a virtual machines. I'm going to have all of them. What I need is a platform that delivers all of this for me without me having to figure out how to hand wire these bits and pieces from various different either proprietary or open source kits just to make it work. I'm going to need a 60 to 100 or 200 person team just to maintain this very bespoke thing that I have developed. I'll just pull it off the shelf 'cause this is a solved problem. Right, Pivotal has already solved this problem. Other companies have already solved this problem. Let me start there and so now I'm here. I don't have to worry about all this left over plumbing. Now I can actually build on top of my business. The analogy I'd use is you don't bring furniture with you every time you check into a hotel. And we're telling customers every time you want to move to a different city just for business meeting or for work trip we're going to build you a house and you need to furnish it. Well, that's ridiculous. I'm going to check into a hotel and my expectation is I can check out of any other room and they'll all be the same, it doesn't really matter what floor I'm on, what room I'm in. But they'll have the same facilities, the same bed, the same, ya know, restroom facilities. That's what I want. That's what containers are. Eventually all the services surrounding that hotel room experience will be micro services. >> And we're the work load, the people. >> And we are the work load and we're the most important thing, we are the application, you're right. >> I love that. That's probably best analogy I've heard of containers. Nima, thanks so much for stopping by theCUBE, joining John and me today. And talking to us about what's going on with Pivotal and how you guys are really helping as part of Dell business dramatically transform. >> Been my pleasure. Thank you both. >> Thank you. >> Thank you. Thank you for watching theCUBE. I'm Lisa Martin with John Furrier. We are in Las Vegas at Boomi World '18. Stick around, John and I will be right back with our next guest. (light techno music)

>> Announcer: It's The Cube. Covering HPE Big Data Conference 2016. Now here are your hosts, Dave Vellante and Paul Gillin. >> Welcome back to Boston, everybody, this is The Cube, we're here live at HP's big data conference, hashtag seize the data. Steve Spear is here, he's an author, MIT professor, author of The High Velocity Edge, welcome to The Cube, thanks for coming on. >> Oh, thanks for having me. >> I got to tell you, following Phil Black, you were coming onstage, I have never heard you speak before, I said, "Oh, this poor guy," and you did awesome, you were great, you held the audience, so congratulations, you were very dynamic and he was unbelievable and you were fantastic, so. >> Today was second-worst speaking setup, one time I was on a panel where it was three admirals, a general, and then the other guy wearing a suit, I said, "Well at least another schmo in a suit," and his opening lines were, "You know, this reminds me, "when I was on the space shuttle and we were flying "to the Hubble," and I'm like, "A flipping astronaut, "I got to follow an astronaut?" So anyway, this was only a SEAL, there were a lot of them, there were far fewer astronauts, so that was easy. >> What I really liked about your talk is, first of all, you told the story of Toyota, which I didn't know, you may. >> No, my experience with Toyota was in the early '70s, I remember the Toyota sort of sweeping into the market but you talked about 20 years before it when they were first entering and how this really was a company that had a lot of quality problems and it was perceived as not being very competitive. >> Yeah, Toyota now people look at as almost, they just take for granted the quality, the productivity, they assume good labor relations and that kind of thing, it's non-unionized, not because the unions haven't tried to unionize, but the employees don't feel the need. And again, in the '50s, Toyota was absolutely an abysmal auto-maker, their product was terrible, their productivity was awful and they didn't have particularly good relations with the workforce either. I mean, it's a profound transformation. >> And you gave this test, in the 50s, I forget what it was, it was one-tenth the productivity of the sort of average automobile manufacturer and then they reached parity in '62, by '68 they were 2X, and by '73, they were off the charts. >> Right, right, right. >> Right, so amazing transformation and then you try to figure out how they did it and they couldn't answer, but they said, "We can show you," right? And that sort of led to your research and your book. >> Yeah, so the quick background is in some regards, this fellow Kenneth Bowen, who was my mentor and advisor when I was doing my doctorate, he could argue we were late to the game because people started recognizing Toyota as this paragon of virtue, high quality at low cost, and so that in the 1980s prompted this whole investigation and the term lean manufacturing came out of the realization that on any given day, Toyota and suppliers were making basically twice the product with half the effort and so you had this period of '85 to about '95 where there was this intense attempt to study Toyota, document Toyota, imitate Toyota, General Motors had a joint venture with Toyota, and then you have the mid-'90s and there's no second Toyota, despite all this investment, so we go to the Toyota guys and say, "Look, clearly if everyone is studying you, imitating you, "copying you, and they haven't replicated you, "they've missed something, so what is it?" And they say, "I'm sorry, but we can't tell you." And we said, "Well you got to be kidding, I mean, "you have a joint venture with your biggest competitor, "General Motors," and they said, "No, no, it's not that we wouldn't tell you, "we just actually don't know how to explain what we do "'cause most of us learn it in this very immersive setting, "but if you'd like to learn it, "you can learn it the way we do." I didn't realize at the time that it would be this Karate Kid wax-on, wax-off, paint-up, paint-down experience, which took years and years to learn and there are some funny anecdotes about it but even at the end, their inability to say what it is, so I went years trying to capture what they were doing and realizing I was wrong 'cause different things wouldn't work quite right, and I can tell you, I was on the Shinkansen with the guy who was my Toyota mentor and I finally said, "Mr. Oba, I think I finally "figured it out, it all boils down to these basic "approaches to seeing and solving problems." And he's looking over my cartoons and stuff and he says, "Well, I don't see anything wrong with this." (laughs) >> That was as good as it got. >> That was as good as it got, I was like, "Score, nothing wrong that he can see!" So anyway. >> But so if you talk about productivity, reliability, you made huge gains there, and the speed of product cycles, were the three knobs that Toyota was turning much more significantly than anybody else and then fuel efficiency came. >> Right, so if you start looking at Toyota and I think this is where people first got the attraction and then sort of the dismissive of, we don't make cars, so the initial hook was the affordable reliability, they could deliver a much higher-quality car, much more affordable based on their productivity. And so that's what triggered attention which then manifest itself as this lean manufacturing and its production control tools. What then sort of started to fall off people's radar is that Toyota not only stayed ahead on those dimensions but they added to the dimensionality of the game, so they started introducing new product faster than anybody else and then they introduced new brand more successfully so all the Japanese, Nissan, Honda, Toyota, all came out with a luxury version, but no one came out with Lexus other than Toyota. The Affinity and the Acura, I mean, it's nice cars, but it didn't become this dominant brand like the Lexus. And then in trying to hit the youth market, everyone tried to come up with, like Honda had the Element but nothing like the Scion, so then Toyota's, and that's much further upstream, a much more big an undertaking than just productivity in a factory. And then when it came time to this issue around fuel efficiency, that's a big technology play of trying to figure out how you get these hybridized technologies with a very very complex software engineering overlay to coordinate power flow in this thing and that, and everyone has their version of hybrid, but no one has it through six generations, 21 platforms, and millions of copies sold. So it didn't matter where you were, Toyota figured out how to compete on this value to market with speed and ease which no one else in their industry was replicating. >> You're talking about, this has nothing to do with operational efficiency, when you talk about the Scion for example, you're talking about tapping into a customer, into an emotional connection with your customer and being able to actually anticipate what they will want before they even know, how do you operationalize that? >> So I think, again, Toyota made such an impression on people with operational efficiency that a lot of their genius went unrecognized, so what I was trying to elaborate on this morning is that Toyota's operational efficiency is not the consequence of just more clever design of operations, like you have an algorithm which I lack and so you get to a better answer than I do, it was this very intense almost empathetic approach to improving existing operations, so you're working on something and it's difficult so we're perceptive of that difficulty and try to understand the source of that difficulty and resolve it, and just do that relentlessly about everything all the time, and it's that empathy to understand your difficulty which then becomes the trigger for making things better, so as far as the Scion comes in, what you see is the same notion of empathic design apply to the needs of the youth market. And the youth market unlike the folks who are, let's say at the time, middle-aged, was less about reliable affordability, but these were people who were coming of age during the Bannatyne era where, very fast mass customization or the iPod era, which was common Chassis but very fast, inexpensive personalization and the folks at Toyota said, "You know what, "the youth market, we don't really understand that, "we've been really successful for this older mid-market, "so let's try to understand the problems that the youth "are trying to solve with their acquisitions," and it turned out personalization. And so if you look at the Scion, it wasn't necessarily a technically or technologically sophisticated quote-unquote sexy product, what it did was it leant itself towards very diverse personalization, which was the problem that the youth market was trying to solve. And you actually see, if I can go on this notion of empathic design, so you see this with the Lexus, so I think the conventional wisdom about luxury cars was Uber technology and bling it, throw chrome and leather and wood and when Toyota tried that initially, they took what was I guess now the Avalon, full-sized car, and they blinged it up and it was contradictory 'cause if you're looking for a luxury car, you don't go to a Toyota dealer, and if you go to a Toyota dealer and you see something with chrome and leather and wood veneer, you're like, you have dissonance. So they tried to understand what luxury meant from the American consumer perspective and again, it wasn't, you always wish you'd get this job, but they sent an engineering team to live in Beverly Hills for some months. (laughs) It's like, ooh, twist my arm on that one, right? But what they found was that luxury wasn't just the physical product, it was the respectful service around it, like when you came back to your hotel room, you walked in, people remembered your name or remembered that, oh we noticed that you used a lot of bath towels so we made sure there were extra in your room, that sort of thing, and if you look at the Lexus, and people were dismissive of the Lexus, saying, "It looks like slightly fancier Toyota, "but what's the big deal, it's not a Beamer or Mercedes." But that wasn't the point, it was the experience you got when you went for sales and service, which was, you got treated so nice, and again, not like hoity toity but you got treated respectfully, so anyway, it all comes back to this empathic design around what problem is the customer or someone inside a plan trying to solve. >> So Toyota and Volkswagen trying to vie for top market share but Toyota, as you say, has got this brand and this empathy that Volkswagen doesn't. You must get a lot of questions about Tesla. Thoughts on Tesla. >> Yeah, cool product, cool technology and time will tell if they're actually solving a real problem. And I don't mean to be dismissive, it's just not an area where I've spent a lot of time. >> And we don't really know, I mean, it's amazing and a software-defined automobile and autonomous, very difficult to predict, we're very tight on time. >> All the cool people seem to drive them though. >> Yeah, that's true. Last question I have is, what the heck does this have to do with analytics at a conference like this? >> Right, so you start thinking about the Toyota model, really, it's not that you can sit down and design something right, it's that you design things which you know deep-rooted in your DNA is that what you've designed is wrong, and that in order to get it right and actually much righter than anything else in the marketplace, what you need to do is understand what's wrong about it and so the experience of the user will help inform what's wrong, the worker rounds they do, the inconveniences they experience, the coping, the compensation they do, and that you can not only use that to help inform what's wrong, but then help shape your understanding of how to get to right, and so where all this fits in is that when you start thinking about data, well first of all, these are gigantic systems, right, which it's probably well-informed to think in terms of these systems are being designed by flawed human beings so the systems themselves have flaws, so it's good to be attentive to the flaws that are designed in it so you can fix them and make them more usable by your intended clientele. But the other thing is that these systems can help you gain much greater precision, granularity, frequency of sampling and understanding of where things are misfiring sooner than later, smaller than larger, so you can adjust and adapt and be more agile in shaping the experience. >> Well Steve, great work, thanks very much for coming on The Cube and sharing and great to meet you. >> Yeah likewise, thanks for having me. >> You're welcome. Alright, keep it right there, everybody, Paul and I will be back with our next guest, we're live from Boston, this is The Cube, we'll be right back. (upbeat music)