>>Hey, everyone, welcome to the Cubes Coverage of the International Women's Showcase for 2022. I'm your host, Lisa Martin. Pleased to be here with an agreement ahead of small medium business SMB for Asia Pacific and Japan at Amazon Web services. Anna. It's great to have you on the programme, >>Lisa. I am delighted to be here and really excited to be talking about what we're gonna be talking about today, which is diversity and women in technology. >>One of the great things about International Women's Day Tuesday, March 8th, is there's always a campaign of theme. This year's theme is breaking the bias. What does that mean to you? And are we on our way to actually accomplish that? >>Look, Breaking the bias really is about all of us being more self aware in our workplaces. Really. What it means to me is understanding that the communities and the employment, the employee population, that all of us working is diverse. Um, and this is a great example of that, right? We are a global organisation and our employees come from across the world. I am representing people from across Asia Pacific and Japan. They look, feel and think differently to people in other parts of the world. So, really, what breaking the biases about is understanding our unconscious biases and thinking differently about how we approach conversations in the workplace to make sure that we're including everyone in the conversation. And honestly, Lisa, when you do that, you get much better. Business outcomes. I've seen that for sure. >>Definitely. There's some stats we can talk about later that I think really articulate that point incredibly well. But I want to talk about your background. You pivoted many times from lawyer to the CEO of ANZ Bank in the Philippines to now a leader at Amazon Web services. Talk to you about your career path with all those different pivots. How did you get to where you are tonight? >>Yeah, I mean, honestly, I recognise that I don't have a traditional Orthodox career plan, but that's my intention. I'm somebody who has always been really interested in the world around me, and I would say that my biggest driver is learning and being curious, which, as you know, is an Amazon leadership principles. So it's probably not a surprise that I ended up here at Ws, but really for me when I thought about my career and I have thought about it intentionally. I've been willing to put my hand up and take risks where I think probably others around me were not feeling as safe, and that's that's a function of who I am. But it's also a function of what I see women wanting to and needing to do more in order to bring their career forward. So as you say, I started my I had a pure technical lens when I started my career, which was being a lawyer, and there's been a lot of time just learning that and holding that skill set, I knew Lisa even then that that was not what I wanted to do forever. I wanted to do more than simply sit in an office and negotiate documents. Um, even though that was an exciting career, there was more that I wanted to do. So off the back of that, I moved into banking and was able to to learn and build some really important skill sets in terms of thinking about being a leader. And those skill sets include things like running a balance sheet, managing people thinking differently about risking compliance, which then allowed me to guess, run a bank and run the business. And then finally, how did I then pivot into technology? Well, it was a long conversation. If I'm honest with you, you know, there were there were conversations back and forth and I thought to myself and doing the right thing here. But what I could see for sure was that the world was moving to a technological context and for me not to take an opportunity to do it. A job like running a technology business across Asia, particularly Japan, just It just wasn't a possibility for me. I had to take the opportunity. So here I am, >>And that's one of the most exciting things I think is that these days every company has to be a tech company. Every company has to be a data company, a digital company with one of the lessons we've learned in the last couple of years. But another thing that we've learned is you mentioned skill sets. But it isn't just about those hard skill sets. What are some of those key soft skill sets that you think are really outstanding and really help to break down the bias. >>Yeah, again, Really interesting. So as I'm talking to women, when they hear about my career journey, a lot of them are surprised. How could you move into technology? And I think the challenge is that a lot of women view technology simply as a coding context. They view it as something that only someone with technical skills can do, and that is simply not the case. So if you look at a recent study by Deloitte Access Economics in Australia, for instance, the soft, skill intensive occupations are going to account for two thirds of all jobs by 2030. So if you think about that having a pure technical skill set, so certainly if you're going to do something like be a solutions architect or be a coda, it's really important that you must have those skills. But technology businesses are building and growing like no other, so we need all of those soft skills, like project management like P and L. Accountability and responsibility, like learning how to manage teams. These are caused fuels that have nothing to do with kind of fundamental technology, understanding that business contacts is important, but there are a lot of women out there who could be working in technology now but are a little bit scared to do so because they're thinking maybe they don't have the skills and I would encourage them to think differently. >>I think your your background with your pivots is a great articulation of you can take so many different backgrounds law banking into tech There's probably a fair amount of overlap there, but you also have you have in and of yourself thought diversity because of your background. I think that's another important thing for women to learn how important that thought diversity can be in any sort of job that they do, whether they are in a technical field. Or maybe they're in finance or operations or sales for a technology company. You guys talk about builders at A. W S. Talk to me about what a builder is, what's that definition and one of some of those key skill sets hard and soft that those builders exemplify. >>Yeah, so we are very build focused at AWS because we're building on behalf of our customers. But what that means is that the trays that make you a builder are exemplified by our leadership principles. So things like being curious. As you just pointed out, Lisa, these are the tenants of being a good builder, um, pursuing continuous learning. So whilst you you may know that you're good at something, you're not scared of trying something else. You're not scared of training and learning about something else. Being able to look around corners, um, and take calculated risks. I mean, whilst it may sound like my career journey has been pivot, pivot, pivot. Actually, if we're honest that these have been very intentional moves that I've made with my career to try to learn, as I said, to try to grow, um, and I've been fortunate and have been intentional also about building that leadership profile, But that's because I'm really fundamentally interested in how business and how people are connecting across the world. And as I said to you in a building context, really, that's about learning about how to build and run digital businesses. And at the end of the day is I guess the key message that I would send to everyone out there getting involved in a career in technology is not a bad move. >>No, it's definitely not a bad movie. I love the curiosity angle. That's one of those things that I'd love to hear. How do you encourage that? One of the biggest challenges. If we look at the stats of girls in stem programmes, from primary school to high school to university, as we see the numbers going down, we see them going up in university. And then, of course, when we're in, we're looking at the raw tech numbers. The number of women in technical positions is quite low to your point. There's many other opportunities besides technical positions. How do you encourage women to not be afraid to raise their hand and ask a question, even if they think maybe this is a dumb question? >>Uh, it's such a I think, you know, honestly, we need to see more women in leadership roles. Um, and, uh, and I think it's incumbent upon the organisations that are are running our businesses, that they make this a priority because you can't see I'm sorry. You can't be what you can't see Lisa, Um, and so it's great for us to talk about it. But once we start seeing women having active business, led conversations. That's where we're really going to see the dial shift. I have a 13 year old daughter, Um, and she's deeply interested in everything on her computer. Um, and what I try to do is encourage her to think differently about the type of roles that she could have if she was interested in, say, for instance, graphic design. She loves drawing, Um, singing. There are so many ways you can do all those YouTube videos. Maybe not, but you know, ways in which you can engage with technology to pursue a career that's interesting to you, regardless of your gender. So maybe the first part is making sure that we are talking about female leaders and what they're doing. I think also what we can do is start building programmes where we're involving women in building skills and certification skills. So here we've got this amazing event which we've built called She builds and I'm an active mentor for that. And what that's all about is kind of connecting women in the tech community and those who are interested with programmes that really speak to the way that women are thinking about their roles. So we have like minded peers. We have senior leaders, We have certification skills, programmes, always part of that, and we also have male allies. It's really important to include our male allies in that conversation, and you will have heard about things like male champions of change. These are very important conversations because again, what we know from statistics is that women are not as likely to build networks and sponsors as men are. And that's not statement of Miss Mala intense. What it means is that they just learn differently and think differently as they're building their careers. So if we're starting to get a man involved in the conversation in a more meaningful way, it's a conversation that's inclusive, and that's really what I want to drive. So I'm not sure I answered your question, but I certainly got to a couple of points that I was interested in highlighting, which is it's a conversation that has to happen at a grassroots level at a leadership level and across the organisation in terms of metrics, data understanding where women are and how to build and grow them >>right. But one of the things that you said that I was about to say was, We can't be what we can't see. We need to be able to elevate those female leaders like yourself so that more younger women and even women who maybe have been in the field for a while, can see the opportunities, the leadership. But you also brought up another great point. And that is, and something I was going to ask you about who are who are some of your mentors. And I imagine it's not just all females. It's got to be men as well. As you point out, it's incredibly important to have the men as allies. >>Yeah, absolutely. And certainly I wouldn't even be having this conversation with you now if I didn't have some amazing allies, both men and women, by my side as I've tracked this leadership journey. Certainly, um, Phil Davis, who is the head of our commercial organisation, Greg Pearson. These are people who have taken time out of their careers to talk with me about how we can help to build and grow women leaders, and to me, that's impactful. And I feel that that's an authentic engagement because there is a recognition in technology that we need to do more around this issue, and I see senior leaders like Matt Garman leading into the conversation. So for me, that's that's very inspiring. But I can't I couldn't have answered that question without telling you that the people who probably inspired me most in the organisation and within my network are those young women out there who are female founders. Now you know, I'm going to have to say a couple of names because I get the opportunity. Lisa, I've got a part of the networking, a women's networking, um, and mentoring organisation. And we have women here in Singapore like Ping Ping Han, who is building out an environmental education and sustainability digital business. We've got Francesco Cuccia, who is building Go get. She's already built it, which is an on demand workforce platform, which has over 250,000 people online that are helping people in Malaysia to work and has helped immensely during Covid. So what we're seeing with these young women is that they're actually building the digital businesses of the future, and it's not about, I mean, what I'm seeing them do is invest their time and energy in building. As I said, kind of programmes and models that are sustainable. So they're building businesses not just for the bottom line, but also to help the communities in which we operate, which to me is deeply inspirational. >>Absolutely. And the female founders need much more visibility than they're getting and obviously much more funding. One last point that I want to bring up because this is really important is that there is some data that I know that you have about performance company performance. When there are females at the helm, talk to me a little bit about that, and how can we help get that word out there more? Some more organisations understand the potential they have when they got that thought. Diversity. >>Yeah, it's such a wonderful point, and it's so well made now across the across media. But I feel like we need to double down on it because this is not a piecemeal conversation about doing the right thing. Um, sometimes we view it that way, and of course it is the right thing to have equity and diversity in our workplace. But in fact, there's so much data around how a diverse workforce creates better outcomes for business So in 2020 we had a McKenzie survey that found that companies with more than 30% of women executives were more likely to outperform companies with this percentage. So there is now a huge amount of data that's starting to show us what a diverse. And this is not just about gender. This is also about diversity across various lenses culture, ethnicity, minority groups, etcetera. So and for me, Lisa, it's just common sense. So if you're building a business that is trying to reach the most number of customers, it really is intuitive that you need to have all of those customers represented around the table. If you only have a single point of view, you're not going to represent all of those customers out there. And increasingly, those customers are expecting to be represented as part of your conversation in your business. So it totally makes sense from a business lens to build and recruit a diverse workforce. >>I couldn't agree more. One. I like to have one more question. Talk to me really quickly, briefly about how how are you building your teams to promote effectiveness through that diversity that, as you just described, can be so leading edge. >>Yeah, So what I'm doing is being intentional in my hiring practises. So this is something that all leaders can do. >>And that is really >>carefully about filling the roles in my organisation, where I'm given a role to fulfil, making sure that I'm looking at that diverse candidates, not just the same candidates who might have applied before. And that means sometimes throwing the net a bit wider than what you might usually have and thinking differently about the candidates that are applying. So, for instance, in my team, we have 50 50 men and women. Um, and we all come from very diverse backgrounds. We've got Indian, we've got Singaporean, we've got Australian talent, which means we've got a gender and cultural mix, which is actually, as I said, bringing a very different lens to the conversation when we're trying to solve customer problems. And what I would say is collaboration and respect is the cornerstone of the way that we should be. Building teams and diverse perspectives mean that our teams and the outcomes that we build are going to reflect the complexity of both the cross cultural and the divers, gender lens within which all of our customers are doing business today. >>Anna, thank you so much for joining me today, talking about the intentional pivots that you've made in your career, how inspiring those are two others and also how we're making progress on breaking the bias. My pleasure. >>Lisa. It's wonderful to join you. And thank you always think you for bringing us so much interesting data >>for Anna Greene. I'm Lisa Martin. You're watching the Cubes. Coverage of International Women's Showcase 2022.

>> Well, thank you, Gary. Well, you know, reasonable people could debate when the so-called big data era started. But for me it was in the fall of 2010 when I was sleepwalking through this conference in Dallas. And the conference was focused on data being a liability. And the whole conversation was about, how do you mitigate the risks of things like work in process and smoking-gun emails. I got a call from my business partner, John Fard, he said to me, "get to New York and come and see the future of data. We're doing theCUBE at Hadoop World tomorrow." I subsequently I canceled about a dozen meetings that I had scheduled for the week. And with only one exception, every one of the folks I was scheduled to meet said, "what's a Hadoop?" Well, I flew through an ice storm across country. I got to the New York Hilton around 3:00 AM, and I met John in the Dark Bar. If any of you remember that little facility. And I caught a little shut eye. And then the next day I met some of the most interesting people in tech during that time. They were thinking a lot differently than we were used to. They looked at data through a prism of value. And they were finding new ways to do things like deal with fraud, they were building out social networks, they were finding novel marketing vectors and identifying new investment strategies. The other thing they were doing is, they were taking these little tiny bits of code and bring it to really large sets of data. And they were doing things that I hadn't really heard of like no schema-on-write. And they were transforming their organizations by looking at data not as a liability, but as a monetization opportunity. And that opened my eyes and theCUBE, like a lot of others bet its business on data. Now over the past decade, customers have built up infrastructure and have been accommodating a lot of different use cases. Things like offloading ETL, data protection, mining data, analyzing data, visualizing. And as you know, you no doubt realize this was at a time when the cloud was, you know, really kind of nascent. And it was really about startups and experimentation. But today, we've evolved from the wild west of 2010, and many of these customers they're leveraging the cloud for of course, ease of use and flexibility it brings, but also they're finding out it brings complexity and risk. I want to tell you a quick story. Recently it was interviewing a CIO in theCUBE and he said to me, "if you just shove all your workloads into the cloud, you might get some benefit, but you're also going to miss the forest to the trees. You have to change your operating model and expand your mind as to what is cloud and create a cloud light experience that spans your on premises, workloads, multiple public clouds, and even the edge. And you have to re-imagine your business and the possibilities that this new architecture this new platform can bring." So we're going to talk about some of this today in a little bit more detail and specifically how we can better navigate the data storm. And what's the role of hybrid cloud. I'm really excited to have two great guests. Manish Dasaur is the managing director in the North America lead for analytics and artificial intelligence at Accenture. Anupam Singh is the chief customer officer for Cloudera. Gentlemen, welcome to theCUBE, great to see you. >> Hi Dave good to see you again. >> All right, guys, Anupam and Manish, you heard my little monologue upfront Anupam we'll start with you. What would you? Anything you'd add, amend, emphasize? You know, share a quick story. >> Yeah, Dave thank you for that introduction. It takes me back to the days when I was an article employee and went to this 14 people meet up. Just a couple of pizza talking about this thing called Hadoop. And I'm just amazed to see that today we are now at 2000 customers, who are using petabytes of data to make extremely critical decisions. Reminds me of the fact that this week, a lot of our customers are busy thinking about elections and what effect it would have on their data pipeline. Will it be more data? Will it be more stressful? So, totally agree with you. And also agree that cloud, is almost still in early days in times of the culture of IT on how to use the cloud. And I'm sure we'll talk about that today in greater detail. >> Yeah most definitely Manish I wonder if we could get your perspective on this. I mean, back when Anupam was at Oracle you'd shove a bunch of, you know, data, maybe you could attach a big honking disc drive, you'd buy some Oracle licenses, you know, it was a Unix box. Everything went into this, you know, this God box and then things changed quite dramatically, which was awesome, but also complex. And you guys have been there from the beginning. What's your perspective on all this? >> Yeah, it's been fascinating just to watch the market and the technology evolve. And I think the urgency to innovate is really just getting started. We're seeing companies drive growth from 20% in cloud today, to 80% cloud in the next few years. And I think the emergence of capabilities like hybrid cloud, we really get upfront a lot of flexibility for companies who need the ability to keep some data in a private setting, but be able to share the rest of the data in a public setting. I think we're just starting to scratch the surface of it. >> So let's talk a little bit about what is a hybrid cloud Anupam I wonder if you could take this one let's start with you and then Manish we come back to you and to get the customer perspective as well. I mean, it is a lot of things to a lot of people, but what is it? Why do we need it? And you know, what's the value? >> Yeah, I could speak poetic about Kubernetes and containers et cetera. But given that, you know, we talk to customers a lot, all three of us from the customer's perspective, hybrid cloud is a lot about collaboration and ease of procurement. A lot of our customers, whether they're in healthcare, banking or telco, are being asked to make the data available to regulatory authority, to subsidiaries outside of their geography. When you need that data to be available in other settings, taking a from on-prem and making it available in public cloud, enables extreme collaboration, extreme shared data experience if you will, inside the company. So we think about hybrid like that. >> Manish anything you'd add? How are your customers thinking about it? >> I mean, in a very simple way, it's a structure that where we are allowing mixed computing storage and service environments that's made of on-prem structures, private cloud structures, and public cloud structures. We're often calling it multicloud or mixcloud. And I think the really big advantage is, this model of cloud computing is enabling our clients to gain the benefits of public cloud setting, while maintaining your own private cloud for sensitive and mission critical and highly regulated computing services. That's also allowing our clients and organizations to leverage the pay-as-you-go model, which is really quite impressive and attractive to them because then they can scale their investments accordingly. Clients can combine one or more public cloud providers together in a private cloud, multicloud platform. The cloud can operate independently of each other, communicate over an encrypted connection. This dynamic solution offers a lot of flexibility and scalability which I think is really important to our clients. >> So Manish I wonder if we would stay there. How do they, how do your customers decide? How do you help them decide, you know, what the right mix is? What the equilibrium is? How much should it be in on-prem? How much should be in public or across clouds? Or, you know, eventually, well the edge will I guess decide for us. But, how do you go through, what are the decision points there? >> Yeah, I think that's a great question Dave. I would say there's several factors to consider when developing a cloud strategy that's the right strategy for you. Some of the factors that come to my mind when contemplating it, one would be security. Are there data sets that are highly sensitive that you don't want leaving the premise, versus data sets that need to be in a more shareable solution. Another factor I'd consider is speed and flexibility. Is there a need to stand up and stand down capabilities based on the seasonality of the business or some short-term demands? Is there a need to add and remove scale from the infrastructure and that quick pivot and that quick reaction is another factor they should consider. The third one I'd probably put out there is cost. Large data sets and large computing capacities often much more scalable and cost effective than a cloud infrastructure so there's lots of advantages to think through there. And maybe lastly I'd share is the native services. A lot of the cloud providers enable a set of native services for ingestion, for processing, of modeling, for machine learning, that organizations can really take advantage of. I would say if you're contemplating your strategy right now, my coaching would be, get help. It's a team sport. So definitely leverage your partners and think through the pros and cons of the strategy. Establish a primary hyperscaler, I think that's going to be super key and maximize your value through optimizing the workload, the data placement and really scaling the running operations. And lastly, maybe Dave move quickly right? Each day that you wait, you're incurring technical debt in your legacy environment, that's going to increase the cost and barrier to entry when moving to the new cloud hybrid driver. >> Thank you for that. Anupam I wonder if we could talk a little bit about the business impact. I mean, in the early days of big data, yes, it was a heavy lift, but it was really transformative. When you go to hybrid cloud, is it really about governance and compliance and security and getting the right mix in terms of latency? Are there other, you know, business impacts that are potentially as transformative as we saw in the early days? What are your thoughts on that? >> Absolutely. It's the other business impacts that are interesting. And you know, Dave, let's say you're in the line of business and I come to you and say, oh, there's cost, there's all these other security governance benefits. It doesn't ring the bell for you. But if I say, Dave used to wait 32 weeks, 32 weeks to procure hardware and install software, but I can give you the same thing in 30 minutes. It's literally that transformative, right? Even on-prem, if I use cloud native technology, I can give something today within days versus weeks. So we have banks, we have a bank in Ohio that would take 32 weeks to rack up a 42 node server. Yes, it's very powerful, you have 42 nodes on it, 42 things stacked on it, but still it's taking too much time. So when you get cloud native technologies in your data center, you start behaving like the cloud and you're responsive to the business. The responsiveness is very important. >> That's a great point. I mean, in fact, you know, there's always this debate about is the cloud public cloud probably cost more expensive? Is it more expensive to rent than it is to own? And you get debates back and forth based on your perspective. But I think at the end of the day, what, Anupam you just talked about, it may oftentimes could dwarf, you know, any cost factors, if you can actually, you know, move that fast. Now cost is always a consideration. But I want to talk about the migration path if we can Manish. Where do, how should customers think about migrating to the cloud migration's a, an evil word. How should they think about migrating to the cloud? What's the strategy there? Where should they start? >> No I think you should start with kind of a use case in mind. I think you should start with a particular data set in mind as well. I think starting with what you're really seeking to achieve from a business value perspective is always the right lens in my mind. This is the decade of time technology and cloud to the fitness value, right? So if you start with, I'm seeking to make a dramatic upsell or dramatic change to my top line or bottom line, start with the use case in mind and migrate the data sets and elements that are relevant to that use case, relevant to that value, relevant to that unlock that you're trying to create, that I think is the way to prioritize it. Most of our clients are going to have tons and tons of data in their legacy environment. I don't think the right way to start is to start with a strategy that's going to be focused on migrating all of that. I think the strategy is start with the prioritized items that are tied to the specific value or the use case you're seeking to drive and focus your transformation and your migration on that. >> So guys I've been around a long time in this business and been an observer for awhile. And back in the mainframe days, we used to have a joke called CTAM. When we talk about moving data, it was called the Chevy truck access method. So I want to ask you Anupam, how do you move the data? Do you, it's like an Einstein saying, right? Move as much data as you need to, but no more. So what's going on in that front? what's happening with data movement, and, you know, do you have to make changes to the applications when you move data to the cloud? >> So there's two design patterns, but I love your service story because you know, when you have a 30 petabyte system and you tell the customer, hey, just make a copy of the data and everything will be fine. That will take you one and a half years to make the copies aligned with each other. Instead, what we are seeing is the biggest magic is workload analysis. You analyze the workload, you analyze the behavior of the users, and say so let's say Dave runs dashboards that are very complicated and Manish waits for compute when Dave is running his dashboard. If you're able to gather that information, you can actually take some of the noise out of the system. So you take selected sets of hot data, and you move it to public cloud, process it in public cloud maybe even bring it back. Sounds like science fiction, but the good news is you don't need a Chevy to take all that data into public cloud. It's a small amount of data. That's one reason the other pattern that we have seen is, let's say Manish needs something as a data scientist. And he needs some really specific type of GPUs that are only available in the cloud. So you pull the data sets out that Manish needs so that he can get the new silicone, the new library in the cloud. Those are the two patterns that if you have a new type of compute requirement, you go to public cloud, or if you have a really noisy tenant, you take the hot data out into public cloud and process it there. Does that make sense? >> Yeah it does and it sort of sets up this notion I was sort of describing upfront that the cloud is not just, you know, the public cloud, it's the spans on-prem and multicloud and even the edge. And it seems to me that you've got a metadata opportunity I'll call it and a challenge as well. I mean, there's got to be a lot of R and D going on right now. You hear people talking about cloud native and I wonder on Anupam if you could stay on that, I mean, what's your sense as to how, what the journey is going to look like? I mean, we're not going to get there overnight. People have laid out a vision of this sort of expanding cloud and I'm saying it's a metadata opportunity, but I, you know, how do you, the system has to know what workload to put where based on a lot of those factors that you guys were talking about. The governance, the laws of the land, the latency issues, the cost issues is, you know, how is the industry Anupam sort of approaching this problem and solving this problem? >> I think the biggest thing is to reflect all your security governance across every cloud, as well as on-prem. So let's say, you know, a particular user named Manish cannot access financial data, revenue data. It's important that that data as it goes around the cloud, if it gets copied from on-prem to the cloud, it should carry that quality with it. A big danger is you copy it into some optic storage, and you're absolutely right Dave metadata is the goal there. If you copy the data into an object storage and you lose all metadata, you lose all security, you lose all authorization. So we have invested heavily in something called shared data experience. Which reflects policies from on-prem all the way to the cloud and back. We've seen customers needing to invest in that, but some customers went all hog on the cloud and they realize that putting data just in these buckets of optic storage, you lose all the metadata, and then you're exposing yourself to some breach and security issues. >> Manish I wonder if we could talk about, thank you for that Anupam. Manish I wonder if we could talk about, you know, I've imagined a project, okay? Wherever I am in my journey, maybe you can pick your sort of sweet spot in the market today. You know, what's the fat middle if you will. What does a project look like when I'm migrating to the cloud? I mean, what are some of the, who are the stakeholders? What are some of the outer scope maybe expectations that I better be thinking about? What kind of timeframe? How should I tackle this and so it's not like a, you know, a big, giant expensive? Can I take it in pieces? What's the state-of-the-art of a project look like today? >> Yeah, lots of thoughts come to mind, Dave, when you ask that question. So there's lots to pack. As far as who the buyer is or what the project is for, this is out of migration is directly relevant to every officer in the C-suite in my mind. It's very relevant for the CIO and CTO obviously it's going to be their infrastructure of the future, and certainly something that they're going to need to migrate to. It's very important for the CFO as well. These things require a significant migration and a significant investment from enterprises, different kind of position there. And it's very relevant all the way up to the CEO. Because if you get it right, the truly the power it unlocks is illuminates parts of your business that allow you to capture more value, capture a higher share of wallet, allows you to pivot. A lot of our clients right now are making a pivot from going from a products organization to an as a service organization and really using the capabilities of the cloud to make that pivot happen. So it's really relevant kind of across the C-suite. As far as what a typical program looks like, I always coach my clients just like I said, to start with the value case in mind. So typically, what I'll ask them to do is kind of prioritize their top three or five use cases that they really want to drive, and then we'll land a project team that will help them make that migration and really scale out data and analytics on the cloud that are focused on those use cases. >> Great, thank you for that. I'm glad you mentioned the shift in the mindset from product to as a service. We're seeing that across the board now, even infrastructure players are jumping on the bandwagon and borrowing some sort of best practices from the SaaS vendors. And I wanted to ask you guys about, I mean, as you move to the cloud, one of the other things that strikes me is that you actually get greater scale, but there's a broader ecosystem as well. So we're kind of moving from a product centric world and with SaaS we've got this sort of platform centric, and now it seems like ecosystems are really where the innovation is coming from. I wonder if you guys could comment on that, maybe Anupam you could start. >> Yeah, many of our customers as I said right? Are all about sharing data with more and more lines of businesses. So whenever we talk to our CXO partners, our CRO partners, they are being asked to open up the big data system to more tenants. The fear is, of course, if you add more tenants to a system, it could get, you know, the operational actually might get violated. So I think that's a very important part as more and more collaboration across the company, more and more collaboration across industries. So we have customers who create sandboxes. These are healthcare customers who create sandbox environments for other pharma companies to come in and look at clinical trial data. In that case, you need to be able to create these fenced environments that can be run in public cloud, but with the same security that you expect up. >> Yeah thank you. So Manish this is your wheelhouse as Accenture. You guys are one of the top, you know, two or three or four organizations in the world in terms of dealing with complexity, you've got deep industry expertise, and it seems like some of these ecosystems as Anupam was just sort of describing it in a form are around industries, whether it's healthcare, government, financial services and the like. Maybe your thoughts on the power of ecosystems versus the, you know, the power of many versus the resources of one. >> Yeah, listen, I always talk about this is a team sport right? And it's not about doing it alone. It's about developing as ecosystem partners and really leveraging the power of that collective group. And I've been for as my clients to start thinking about, you know, the key thing you want to think about is how you migrate to becoming a data driven enterprise. And in order for you to get there, you're going to need ecosystem partners to go along the journey with you, to help you drive that innovation. You're going to need to adopt a pervasive mindset to data and democratization of that data everywhere in your enterprise. And you're going to need to refocus your decision-making based on that data, right? So I think partner ecosystem partnerships are here to stay. I think what we're going to see Dave is, you know, at the beginning of the maturity cycle, you're going to see the ecosystem expand with lots of different players and technologies kind of focused on industry. And then I think you'll get to a point where it starts to mature and starts to consolidate as ecosystem partners start to join together through acquisitions and mergers and things like that. So I think ecosystem is just starting to change. I think the key message that I would give to our clients is take advantage of that. There's too much complexity for any one person to kind of navigate through on your own. It's a team sport, so take advantage of all the partnerships you can create. >> Well, Manish one of the things you just said that it kind of reminds me, you said data data-driven, you know, organizations and, you know, if you look at the pre-COVID narrative around digital transformation, certainly there was a lot of digital transformation going on, but there was a lot of complacency too. I talked to a lot of folks, companies that say, "you know, we're doing pretty well, our banks kicking butt right now, we're making a ton of money." Or you know, all that stuff that's kind of not on my watch. I'll be retired before then. And then it was the old, "if it ain't broke, don't fix it." And then COVID breaks everything. And now if you're not digital, you're out of business. And so Anupam I'll start with you. I mean, to build a data-driven culture, what does that mean? That means putting data at the center of your organization, as opposed to around in stove pipes. And this, again, we talked about this, it sort of started in there before even the early parts of last decade. And so it seems that there's cultural aspects there's obviously technology, but there's skillsets, there's processes, you've got a data lifecycle and a data, what I sometimes call a data pipeline, meaning an end to end cycle. And organizations are having to rethink really putting data at the core. What are you seeing? And specifically as it relates to this notion of data-driven organization and data culture, what's working? >> Yeah three favorite stories, and you're a 100% right. Digital transformation has been hyperaccelerated with COVID right? So our telco customers for example, you know, Manish had some technical problems with bandwidth just 10 minutes ago. Most likely is going to call his ISP. The ISP will most likely load up a dashboard in his zip code and the reason it gives me stress, this entire story is because most likely it's starting on a big data system that has to collect data every 15 minutes, and make it available. Because you'll have a very angry Manish on the other end, if you can't explain when is the internet coming back, right? So, as you said this is accelerated. Our telco providers, our telco customers ability to ingest data, because they have to get it in 15 minute increments, not in 24 hour increments. So that's one. On the banking sector what we have seen is uncertainty has created more needs for data. So next week is going to be very uncertain all of us know elections are upcoming. We have customers who are preparing for that additional variable capacity, elastic capacity, so that if investment bankers start running hundreds and thousands of reports, they better be ready. So it's changing the culture at a very fundamental level, right? And my last story is healthcare. You're running clinical trials, but everybody wants access to the data. Your partners, the government wants access to the data, manufacturers wants access to the data. So again, you have to actualize digital transformation on how do you share very sensitive, private healthcare data without violating any policy. But you have to do it quick. That's what COVID has started. >> Thank you for that. So I want to come back to hybrid cloud. I know a lot of people in the audience are, want to learn more about that. And they have a mandate really to go to cloud generally but hybrid specifically. So Manish I wonder if you could share with us, maybe there's some challenges, I mean what's the dark side of hybrid. What should people be thinking about that they, you know, they don't want to venture into, you know, this way, they want to go that way. What are some of the challenges that you're seeing with customers? And how are they mitigating them? >> Yeah, Dave it's a great question. I think there's a few items that I would coach my clients to prioritize and really get right when thinking about making the migration happen. First of all, I would say integration. Between your private and public components that can be complex, it can be challenging. It can be complicated based on the data itself, the organizational structure of the company, the number of touches and authors we have on that data and several other factors. So I think it's really important to get this integration right, with some clear accountabilities build automation where you can and really establish some consistent governance that allows you to maintain these assets. The second one I would say is security. When it comes to hybrid cloud management, any transfers of data you need to handle the strict policies and procedures, especially in industries where that's really relevant like healthcare and financial services. So using these policies in a way that's consistent across your environment and really well understood with anyone who's touching your environment is really important. And the third I would say is cost management. All the executives that I talk about have to have a cost management angle to it. Cloud migration provides ample opportunities for cost reduction. However many migration projects can go over budget when all the costs aren't factored in, right? So your cloud vendors. You've got to be mindful of kind of the charges on accessing on premise applications and scaling costs that maybe need to be budgeted for and where if possible anticipated and really plan for. >> Excellent. So Anupam I wonder if we could go a little deeper on, we talked a little bit about this, but kind of what you put where, which workloads. What are you seeing? I mean, how are people making the choice? Are they saying, okay, this cloud is good for analytics. This cloud is good. Well, I'm a customer of their software so I'm going to use this cloud or this one is the best infrastructure and they got, you know, the most features. How are people deciding really what to put where? Or is it, "hey, I don't want to be locked in to one cloud. I want to spread my risk around. What are you seeing specifically? >> I think the biggest thing is just to echo what Manish said. Is business comes in and as a complaint. So most projects that we see on digital transformation and on public cloud adoption is because businesses complaining about something. It's not architectural goodness, it is not for just innovation for innovation's sake. So, the biggest thing that we see is what we call noisy neighbors. A lot of dashboards, you know, because business has become so intense, click, click, click, click, you're actually putting a lot of load on the system. So isolating noisy neighbors into a cloud is one of the biggest patterns that you've seen. It takes the noisiest tenant on your cluster, noisiest workload and you take them to public cloud. The other one is data scientists. They want new libraries, they want to work with GPU's. And to your point Dave, that's where you select a particular cloud. Let's say there's a particular type silicone that is available only in that cloud. That GPU is available only in that cloud or that particular artificial intelligence library is available only in a particular cloud. That's when customers say, Hey miss, they decided, why don't you go to this cloud while the main workload might still be running on them, right? That's the two patterns that we are seeing. >> Right thank you. And I wonder if we can end on a little bit of looking to the future. Maybe how this is all going to evolve over the next several years. I mean, I like to look at it at a spectrum at a journey. It's not going to all come at once. I do think the edge is part of that. But it feels like today we've got, you know, multi clouds are loosely coupled and hybrid is also loosely coupled, but we're moving very quickly to a much more integrated, I think we Manish you talked about integration. Where you've got state, you've got the control plane, you've got the data plane. And all this stuff is really becoming native to the respective clouds and even bring that on-prem and you've got now hybrid applications and much much tighter integration and build this, build out of this massively distributed, maybe going from it's a hyper-converged to hyper-distributed again including the edge. So I wonder Manish we could start with you. How are your customers thinking about the future? How are they thinking about, you know, making sure that they're not going down a path where that's going to, they're going to incur a lot of technical debt? I know there's sort of infrastructure is code and containers and that seems it seems necessary, but insufficient there's a lot of talk about, well maybe we start with a functions based or a serverless architecture. There's some bets that have to be made to make sure that you can future proof yourself. What are you recommending there Manish? >> Yeah, I, listen I think we're just getting started in this journey. And like I said, it's really exciting time and I think there's a lot of evolution in front of us that we're going to see. I, you know, I think for example, I think we're going to see hybrid technologies evolve from public and private thinking to dedicated and shared thinking instead. And I think we're going to see advances in capabilities around automation and computer federation and evolution of consumption models of that data. But I think we've got a lot of kind of technology modifications and enhancements ahead of us. As far as companies and how they future proof themselves. I would offer the following. First of all, I think it's a time for action, right? So I would encourage all my class to take action now. Every day spent in legacy adds to the technical debt that you're going to incur, and it increases your barrier to entry. The second one would be move with agility and flexibility. That's the underlying value of hybrid cloud structures. So organizations really need to learn how to operate in that way and take advantage of that agility and that flexibility. We've talked about creating partnerships in ecosystems I think that's going to be really important. Gathering partners and thought leaders to help you navigate through that complexity. And lastly I would say monetizing your data. Making a value led approach to how you viewed your data assets and force a function where each decision in your enterprise is tied to the value that it creates and is backed by the data that supports it. And I think if you get those things right, the technology and the infrastructure will serve. >> Excellent and Anupam why don't you bring us home, I mean you've got a unique combination of technical acumen and business knowledge. How do you see this evolving over the next three to five years? >> Oh, thank you Dave. So technically speaking, adoption of containers is going to steadily make sure that you're not aware even of what cloud you're running on that day. So the multicloud will not be a requirement even, it will just be obviated when you have that abstraction there. Contrarily, it's going to be a bigger challenge. I would echo what Manish said start today, especially on the cultural side. It is great that you don't have to procure hardware anymore, but that also means that many of us don't know what our cloud bill is going to be next month. It is a very scary feeling for your CIO and your CFO that you don't know how much you're going to to spend next month forget next year, right? So you have to be agile in your financial planning as much you have to be agile in your technical planning. And finally I think you hit on it. Ecosystems are what makes data great. And so you have to start from day one that if I am going on this cloud solution, is the data shareable? Am I able to create an ecosystem around that data? Because without that, it's just somebody running a report may or may not have value to the business. >> That's awesome, guys. Thanks so much for a great conversation. We're at a time and I want to wish everybody a terrific event. Let me now hand it back to Vanita. She's going to take you through the rest of the day. This is Dave Vellante for theCUBE, thanks. (smooth calm music)

>> Hello everyone. On today's panel, the theme is Drug Discovery and how Artificial Intelligence can make a difference. On the panel today, we are honored to have Dr. Ryan Yates, principal scientist at The National Center for Natural Products Research, with a focus on botanicals specifically the pharmacokinetics, which is essentially how the drug changes over time in our body and pharmacodynamics which is essentially how drugs affects our body. And of particular interest to him is the use of AI in preclinical screening models to identify chemical combinations that can target chronic inflammatory processes such as fatty liver disease, cognitive impairment and aging. Welcome, Ryan. Thank you for coming. >> Good morning. Thank you for having me. >> The other distinguished panelist is Dr. Rangan Sukumar, our very own, is a distinguished technologist at the CTO office for High Performance Computing and Artificial Intelligence with a PHD in AI and 70 publications that can be applied in drug discovery, autonomous vehicles and social network analysis. Hey Rangan, welcome. Thank you for coming, by sparing the time. We have also our distinguished Chris Davidson. He is leader of our HPC and AI Application and Performance Engineering team. His job is to tune and benchmark applications, particularly in the applications of weather, energy, financial services and life sciences. Yes so particular interest is life sciences he spent 10 years in biotech and medical diagnostics. Hi Chris, welcome. Thank you for coming. >> Nice to see you. >> Well let's start with your Chris, yes, you're regularly interfaced with pharmaceutical companies and worked also on the COVID-19 White House Consortium. You know tell us, let's kick this off and tell us a little bit about your engagement in the drug discovery process. >> Right and that's a good question I think really setting the framework for what we're talking about here is to understand what is the drug discovery process. And that can be kind of broken down into I would say four different areas, there's the research and development space, the preclinical studies space, clinical trial and regulatory review. And if you're lucky, hopefully approval. Traditionally this is a slow arduous process it costs a lot of money and there's a high amount of error. Right, however this process by its very nature is highly iterate and has just huge amounts of data, right it's very data intensive, right and it's these characteristics that make this process a great target for kind of new approaches in different ways of doing things. Right, so for the sake of discussion, right, go ahead. >> Oh yes, so you mentioned data intensive brings to mind Artificial Intelligence, you know, so Artificial Intelligence making the difference here in this process, is that so? >> Right, and some of those novel approaches are actually based on Artificial Intelligence whether it's deep learning and machine learning, et cetera, you know, prime example would say, let's just say for the sake of discussion, let's say there's a brand new virus, causes flu-like symptoms, shall not be named if we focus kind of on the R and D phase, right our goal is really to identify target for the treatment and then screen compounds against it see which, you know, which ones we take forward right to this end, technologies like cryo-electron, cryogenic electron microscopy, just a form of microscopy can provide us a near atomic biomolecular map of the samples that we're studying, right whether that's a virus, a microbe, the cell that it's attaching to and so on, right AI, for instance, has been used in the particle picking aspect of this process. When you take all these images, you know, there are only certain particles that we want to take and study, right whether they have good resolution or not whether it's in the field of the frame and image recognition is a huge part of this, it's massive amounts of data in AI can be very easily, you know, used to approach that. Right, so with docking, you can take the biomolecular maps that you achieved from cryo-electron microscopy and you can take those and input that into the docking application and then run multiple iterations to figure out which will give you the best fit. AI again, right, this is iterative process it's extremely data intensive, it's an easy way to just apply AI and get that best fit doing something in a very, you know, analog manner that would just take humans very long time to do or traditional computing a very long time to do. >> Oh, Ryan, Ryan, you work at the NCNPR, you know, very exciting, you know after all, you know, at some point in history just about all drugs were from natural products yeah, so it's great to have you here today. Please tell us a little bit about your work with the pharmaceutical companies, especially when it is often that drug cocktails or what they call Polypharmacology, is the answer to complete drug therapy. Please tell us a bit more with your work there. >> Yeah thank you again for having me here this morning Dr. Goh, it's a pleasure to be here and as you said, I'm from the National Center for Natural Products Research you'll hear me refer to it as the NCNPR here in Oxford, Mississippi on the Ole Miss Campus, beautiful setting here in the South and so, what, as you said historically, what the drug discovery process has been, and it's really not a drug discovery process is really a therapy process, traditional medicine is we've looked at natural products from medicinal plants okay, in these extracts and so where I'd like to begin is really sort of talking about the assets that we have here at the NCNPR one of those prime assets, unique assets is our medicinal plant repository which comprises approximately 15,000 different medicinal plants. And what that allows us to do, right is to screen mine, that repository for activities so whether you have a disease of interest or whether you have a target of interest then you can use this medicinal plant repository to look for actives, in this case active plants. It's really important in today's environment of drug discovery to really understand what are the actives in these different medicinal plants which leads me to the second unique asset here at the NCNPR and that is our what I'll call a plant deconstruction laboratory so without going into great detail, but what that allows us to do is through a how to put workstation, right, is to facilitate rapid isolation and identification of phytochemicals in these different medicinal plants right, and so things that have historically taken us weeks and sometimes months, think acetylsalicylic acid from salicylic acid as a pain reliever in the willow bark or Taxol, right as an anti-cancer drug, right now we can do that with this system on the matter of days or weeks so now we're talking about activity from a plant and extract down to phytochemical characterization on a timescale, which starts to make sense in modern drug discovery, alright and so now if you look at these phytochemicals, right, and you ask yourself, well sort of who is interested in that and why, right what are traditional pharmaceutical companies, right which I've been working with for 20, over 25 years now, right, typically uses these natural products where historically has used these natural products as starting points for new drugs. Right, so in other words, take this phytochemical and make chemicals synthetic modifications in order to achieve a potential drug. But in the context of natural products, unlike the pharmaceutical realm, there is often times a big knowledge gap between a disease and a plant in other words I have a plant that has activity, but how to connect those dots has been really laborious time consuming so it took us probably 50 years to go from salicylic acid and willow bark to synthesize acetylsalicylic acid or aspirin it just doesn't work in today's environment. So casting about trying to figure out how we expedite that process that's when about four years ago, I read a really fascinating article in the Los Angeles Times about my colleague and business partner, Dr. Rangan Sukumar, describing all the interesting things that he was doing in the area of Artificial Intelligence. And one of my favorite parts of this story is basically, unannounced, I arrived at his doorstep in Oak Ridge, he was working Oak Ridge National Labs at the time, and I introduced myself to him didn't know what was coming, didn't know who I was, right and I said, hey, you don't know me you don't know why I'm here, I said, but let me tell you what I want to do with your system, right and so that kicked off a very fruitful collaboration and friendship over the last four years using Artificial Intelligence and it's culminated most recently in our COVID-19 project collaborative research between the NCNPR and HP in this case. >> From what I can understand also as Chris has mentioned highly iterative, especially with these combination mixture of chemicals right, in plants that could affect a disease. We need to put in effort to figure out what are the active components in that, that affects it yeah, the combination and given the layman's way of understanding it you know and therefore iterative and highly data intensive. And I can see why Rangan can play a huge significant role here, Rangan, thank you for joining us So it's just a nice segue to bring you in here, you know, given your work with Ryan over so many years now, tell I think I'm also quite interested in knowing a little about how it developed the first time you met and the process and the things you all work together on that culminated into the progress at the advanced level today. Please tell us a little bit about that history and also the current work. Rangan. >> So, Ryan, like he mentioned, walked into my office about four years ago and he was like hey, I'm working on this Omega-3 fatty acid, what can your system tell me about this Omega-3 fatty acid and I didn't even know how to spell Omega-3 fatty acids that's the disconnect between the technologist and the pharmacologist, they have terms of their own right since then we've come a long way I think I understand his terminologies now and he understands that I throw words like knowledge graphs and page rank and then all kinds of weird stuff that he's probably never heard in his life before right, so it's been on my mind off to different domains and terminologies in trying to accept each other's expertise in trying to work together on a collaborative project. I think the core of what Ryan's work and collaboration has led me to understanding is what happens with the drug discovery process, right so when we think about the discovery itself, we're looking at companies that are trying to accelerate the process to market, right an average drug is taking 12 years to get to market the process that Chris just mentioned, Right and so companies are trying to adopt what's called the in silico simulation techniques and in silico modeling techniques into what was predominantly an in vitro, in silico, in vivo environment, right. And so the in silico techniques could include things like molecular docking, could include Artificial Intelligence, could include other data-driven discovery methods and so forth, and the essential component of all the things that you know the discovery workflows have is the ability to augment human experts to do the best by assisting them with what computers do really really well. So, in terms of what we've done as examples is Ryan walks in and he's asking me a bunch of questions and few that come to mind immediately, the first few are, hey, you are an Artificial Intelligence expert can you sift through a database of molecules the 15,000 compounds that he described to prioritize a few for next lab experiments? So that's question number one. And he's come back into my office and asked me about hey, there's 30 million publications in PubMag and I don't have the time to read everything can you create an Artificial Intelligence system that once I've picked these few molecules will tell me everything about the molecule or everything about the virus, the unknown virus that shows up, right. Just trying to understand what are some ways in which he can augment his expertise, right. And then the third question, I think he described better than I'm going to was how can technology connect these dots. And typically it's not that the answer to a drug discovery problem sits in one database, right he probably has to think about uniproduct protein he has to think about phytochemical, chemical or informatics properties, data and so forth. Then he talked about the phytochemical interaction that's probably in another database. So when he is trying to answer other question and specifically in the context of an unknown virus that showed up in late last year, the question was, hey, do we know what happened in this particular virus compared to all the previous viruses? Do we know of any substructure that was studied or a different disease that's part of this unknown virus and can I use that information to go mine these databases to find out if these interactions can actually be used as a repurpose saying, hook, say this drug does not interact with this subsequence of a known virus that also seems to be part of this new virus, right? So to be able to connect that dot I think the abstraction that we are learning from working with pharma companies is that this drug discovery process is complex, it's iterative, and it's a sequence of needle in the haystack search problems, right and so one day, Ryan would be like, hey, I need to match genome, I need to match protein sequences between two different viruses. Another day it would be like, you know, I need to sift through a database of potential compounds, identified side effects and whatnot other day it could be, hey, I need to design a new molecule that never existed in the world before I'll figure out how to synthesize it later on, but I need a completely new molecule because of patentability reasons, right so it goes through the entire spectrum. And I think where HP has differentiated multiple times even the recent weeks is that the technology infusion into drug discovery, leads to several aha! Moments. And, aha moments typically happened in the other few seconds, and not the hours, days, months that Ryan has to laboriously work through. And what we've learned is pharma researchers love their aha moments and it leads to a sound valid, well founded hypothesis. Isn't that true Ryan? >> Absolutely. Absolutely. >> Yeah, at some point I would like to have a look at your, peak the list of your aha moments, yeah perhaps there's something quite interesting in there for other industries too, but we'll do it at another time. Chris, you know, with your regular work with pharmaceutical companies especially the big pharmas, right, do you see botanicals, coming, being talked about more and more there? >> Yeah, we do, right. Looking at kind of biosimilars and drugs that are already really in existence is kind of an important point and Dr. Yates and Rangan, with your work with databases this is something important to bring up and much of the drug discovery in today's world, isn't from going out and finding a brand new molecule per se. It's really looking at all the different databases, right all the different compounds that already exist and sifting through those, right of course data is mind, and it is gold essentially, right so a lot of companies don't want to share their data. A lot of those botanicals data sets are actually open to the public to use in many cases and people are wanting to have more collaborative efforts around those databases so that's really interesting to kind of see that being picked up more and more. >> Mm, well and Ryan that's where NCNPR hosts much of those datasets, yeah right and it's interesting to me, right you know, you were describing the traditional way of drug discovery where you have a target and a compound, right that can affect that target, very very specific. But from a botanical point of view, you really say for example, I have an extract from a plant that has combination of chemicals and somehow you know, it affects this disease but then you have to reverse engineer what those chemicals are and what the active ones are. Is that very much the issue, the work that has to be put in for botanicals in this area? >> Yes Doctor Goh, you hit it exactly. >> Now I can understand why a highly iterative intensive and data intensive, and perhaps that's why Rangan, you're highly valuable here, right. So tell us about the challenge, right the many to many intersection to try and find what the targets are, right given these botanicals that seem to affect the disease here what methods do you use, right in AI, to help with this? >> Fantastic question, I'm going to go a little bit deeper and speak like Ryan in terminology, but here we go. So with going back to about starting of our conversation right, so let's say we have a database of molecules on one side, and then we've got the database of potential targets in a particular, could be a virus, could be bacteria, could be whatever, a disease target that you've identified, right >> Oh this process so, for example, on a virus, you can have a number of targets on the virus itself some have the spike protein, some have the other proteins on the surface so there are about three different targets and others on a virus itself, yeah so a lot of people focus on the spike protein, right but there are other targets too on that virus, correct? >> That is exactly right. So for example, so the work that we did with Ryan we realized that, you know, COVID-19 protein sequence has an overlap, a significant overlap with previous SARS-CoV-1 virus, not only that, but it overlap with MERS, that's overlapped with some bad coronavirus that was studied before and so forth, right so knowing that and it's actually broken down into multiple and Ryan I'm going to steal your words, non-structural proteins, envelope proteins, S proteins, there's a whole substructure that you can associate an amino acid sequence with, right so on the one hand, you have different targets and again, since we did the work it's 160 different targets even on the COVID-19 mark, right and so you find a match, that we say around 36, 37 million molecules that are potentially synthesizable and try to figure it out which one of those or which few of those is actually going to be mapping to which one of these targets and actually have a mechanism of action that Ryan's looking for, that'll inhibit the symptoms on a human body, right so that's the challenge there. And so I think the techniques that we can unrule go back to how much do we know about the target and how much do we know about the molecule, alright. And if you start off a problem with I don't know anything about the molecule and I don't know anything about the target, you go with the traditional approaches of docking and molecular dynamics simulations and whatnot, right. But then, you've done so much docking before on the same database for different targets, you'll learn some new things about the ligands, the molecules that Ryan's talking about that can predict potential targets. So can you use that information of previous protein interactions or previous binding to known existing targets with some of the structures and so forth to build a model that will capture that essence of what we have learnt from the docking before? And so that's the second level of how do we infuse Artificial Intelligence. The third level, is to say okay, I can do this for a database of molecules, but then what if the protein-protein interactions are all over the literature study for millions of other viruses? How do I connect the dots across different mechanisms of actions too? Right and so this is where the knowledge graph component that Ryan was talking about comes in. So we've put together a database of about 150 billion medical facts from literature that Ryan is able to connect the dots and say okay, I'm starting with this molecule, what interactions do I know about the molecule? Is there a pretty intruding interaction that affects the mechanism of pathway for the symptoms that a disease is causing? And then he can go and figure out which protein and protein in the virus could potentially be working with this drug so that inhibiting certain activities would stop that progression of the disease from happening, right so like I said, your method of options, the options you've got is going to be, how much do you know about the target? How much do you know the drug database that you have and how much information can you leverage from previous research as you go down this pipeline, right so in that sense, I think we mix and match different methods and we've actually found that, you know mixing and matching different methods produces better synergies for people like Ryan. So. >> Well, the synergies I think is really important concept, Rangan, in additivities, synergistic, however you want to catch that. Right. But it goes back to your initial question Dr. Goh, which is this idea of polypharmacology and historically what we've done with traditional medicines there's more than one active, more than one network that's impacted, okay. You remember how I sort of put you on both ends of the spectrum which is the traditional sort of approach where we really don't know much about target ligand interaction to the completely interpretal side of it, right where now we are all, we're focused on is, in a single molecule interacting with a target. And so where I'm going with this is interesting enough, pharma has sort of migrate, started to migrate back toward the middle and what I mean by that, right, is we had these in a concept of polypharmacology, we had this idea, a regulatory pathway of so-called, fixed drug combinations. Okay, so now you start to see over the last 20 years pharmaceutical companies taking known, approved drugs and putting them in different combinations to impact different diseases. Okay. And so I think there's a really unique opportunity here for Artificial Intelligence or as Rangan has taught me, Augmented Intelligence, right to give you insight into how to combine those approved drugs to come up with unique indications. So is that patentability right, getting back to right how is it that it becomes commercially viable for entities like pharmaceutical companies but I think at the end of the day what's most interesting to me is sort of that, almost movement back toward that complex mixture of fixed drug combination as opposed to single drug entity, single target approach. I think that opens up some really neat avenues for us. As far as the expansion, the applicability of Artificial Intelligence is I'd like to talk to, briefly about one other aspect, right so what Rang and I have talked about is how do we take this concept of an active phytochemical and work backwards. In other words, let's say you identify a phytochemical from an in silico screening process, right, which was done for COVID-19 one of the first publications out of a group, Dr. Jeremy Smith's group at Oak Ridge National Lab, right, identified a natural product as one of the interesting actives, right and so it raises the question to our botanical guy, says, okay, where in nature do we find that phytochemical? What plants do I go after to try and source botanical drugs to achieve that particular end point right? And so, what Rangan's system allows us to do is to say, okay, let's take this phytochemical in this case, a phytochemical flavanone called eriodictyol and say, where else in nature is this found, right that's a trivial question for an Artificial Intelligence system. But for a guy like me left to my own devices without AI, I spend weeks combing the literature. >> Wow. So, this is brilliant I've learned something here today, right, If you find a chemical that actually, you know, affects and addresses a disease, right you can actually try and go the reverse way to figure out what botanicals can give you those chemicals as opposed to trying to synthesize them. >> Well, there's that and there's the other, I'm going to steal Rangan's thunder here, right he always teach me, Ryan, don't forget everything we talk about has properties, plants have properties, chemicals have properties, et cetera it's really understanding those properties and using those properties to make those connections, those edges, those sort of interfaces, right. And so, yes, we can take something like an eriodictyol right, that example I gave before and say, okay, now, based upon the properties of eriodictyol, tell me other phytochemicals, other flavonoid in this case, such as that phytochemical class of eriodictyols part right, now tell me how, what other phytochemicals match that profile, have the same properties. It might be more economically viable, right in other words, this particular phytochemical is found in a unique Himalayan plant that I've never been able to source, but can we find something similar or same thing growing in, you know a bush found all throughout the Southeast for example, like. >> Wow. So, Chris, on the pharmaceutical companies, right are they looking at this approach of getting, building drugs yeah, developing drugs? >> Yeah, absolutely Dr. Goh, really what Dr. Yates is talking about, right it doesn't help us if we find a plant and that plant lives on one mountain only on the North side in the Himalayas, we're never going to be able to create enough of a drug to manufacture and to provide to the masses, right assuming that the disease is widespread or affects a large enough portion of the population, right so understanding, you know, not only where is that botanical or that compound but understanding the chemical nature of the chemical interaction and the physics of it as well where which aspect affects the binding site, which aspect of the compound actually does the work, if you will and then being able to make that at scale, right. If you go to these pharmaceutical companies today, many of them look like breweries to be honest with you, it's large scale, it's large back everybody's clean room and it's, they're making the microbes do the work for them or they have these, you know, unique processes, right. So. >> So they're not brewing beer okay, but drugs instead. (Christopher laughs) >> Not quite, although there are pharmaceutical companies out there that have had a foray into the brewery business and vice versa, so. >> We should, we should visit one of those, yeah (chuckles) Right, so what's next, right? So you've described to us the process and how you develop your relationship with Dr. Yates Ryan over the years right, five years, was it? And culminating in today's, the many to many fast screening methods, yeah what would you think would be the next exciting things you would do other than letting me peek at your aha moments, right what would you say are the next exciting steps you're hoping to take? >> Thinking long term, again this is where Ryan and I are working on this long-term project about, we don't know enough about botanicals as much as we know about the synthetic molecules, right and so this is a story that's inspired from Simon Sinek's "Infinite Game" book, trying to figure it out if human population has to survive for a long time which we've done so far with natural products we are going to need natural products, right. So what can we do to help organizations like NCNPR to stage genomes of natural products to stage and understand the evolution as we go to understand the evolution to map the drugs and so forth. So the vision is huge, right so it's not something that we want to do on a one off project and go away but in the process, just like you are learning today, Dr. Goh I'm going to be learning quite a bit, having fun with life. So, Ryan what do you think? >> Ryan, we're learning from you. >> So my paternal grandfather lived to be 104 years of age. I've got a few years to get there, but back to "The Infinite Game" concept that Rang had mentioned he and I discussed that quite frequently, I'd like to throw out a vision for you that's well beyond that sort of time horizon that we have as humans, right and that's this right, is our current strategy and it's understandable is really treatment centric. In other words, we have a disease we develop a treatment for that disease. But we all recognize, whether you're a healthcare practitioner, whether you're a scientist, whether you're a business person, right or whatever occupation you realize that prevention, right the old ounce, prevention worth a pound of cure, right is how can we use something like Artificial Intelligence to develop preventive sorts of strategies that we are able to predict with time, right that's why we don't have preventive treatment approach right, we can't do a traditional clinical trial and say, did we prevent type two diabetes in an 18 year old? Well, we can't do that on a timescale that is reasonable, okay. And then the other part of that is why focus on botanicals? Is because, for the most part and there are exceptions I want to be very clear, I don't want to paint the picture that botanicals are all safe, you should just take botanicals dietary supplements and you'll be safe, right there are exceptions, but for the most part botanicals, natural products are in fact safe and have undergone testing, human testing for thousands of years, right. So how do we connect those dots? A preventive strategy with existing extent botanicals to really develop a healthcare system that becomes preventive centric as opposed to treatment centric. If I could wave a magic wand, that's the vision that I would figure out how we could achieve, right and I do think with guys like Rangan and Chris and folks like yourself, Eng Lim, that that's possible. Maybe it's in my lifetime I got 50 years to go to get to my grandfather's age, but you never know, right? >> You bring really, up two really good points there Ryan, it's really a systems approach, right understanding that things aren't just linear, right? And as you go through it, there's no impact to anything else, right taking that systems approach to understand every aspect of how things are being impacted. And then number two was really kind of the downstream, really we've been discussing the drug discovery process a lot and kind of the kind of preclinical in vitro studies and in vivo models, but once you get to the clinical trial there are many drugs that just fail, just fail miserably and the botanicals, right known to be safe, right, in many instances you can have a much higher success rate and that would be really interesting to see, you know, more of at least growing in the market. >> Well, these are very visionary statements from each of you, especially Dr. Yates, right, prevention better than cure, right, being proactive better than being reactive. Reactive is important, but we also need to focus on being proactive. Yes. Well, thank you very much, right this has been a brilliant panel with brilliant panelists, Dr. Ryan Yates, Dr. Rangan Sukumar and Chris Davidson. Thank you very much for joining us on this panel and highly illuminating conversation. Yeah. All for the future of drug discovery, that includes botanicals. Thank you very much. >> Thank you. >> Thank you.

>> Announcer: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hey, welcome back everybody, Jeff Frick here with theCUBE, we're in our Palo Alto studio today, the COVID thing is continuing to go, and one of the huge impacts, right, is obviously in the conference business, our world. Those things have all been canceled or made virtual, and everyone's still trying to figure out, what does a virtual event look like, what are the characteristics of it, and we're really excited to have one of our favorite CUBE alumni, guest host extraordinaire, Keith Townsend. You know him as the CTO advisor joining us, Keith jumped in with both feet, right when this thing went down, and said "I'm going to have my own CTO Advisor "virtual conference," so first off, Keith, I miss you, great to see you, we haven't run into each other at the Sands in an awfully long time, so great to see you, how are you doing? >> Good to see you, if it's only virtual, good to see you too, Jeff. >> So tell us about your decision to jump in with both feet, and go ahead and test the waters on this virtual conference concept. >> So I talked about this a little bit on a random, just a YouTube update, but roughly 30, 35% of my revenue comes from in-person events. And plus my brand, The CTO Advisor, is tied to people seeing me on theCUBE, seeing me at the shows, creating the content, kind of on the ground, guerrilla style, kind of like how John started out early on. So we needed a practical solution for most things, one, we feed off the energy of the community, so we need to be on the ground as much as possible, so that we can create content and get you guys the stories and the data that you need to make purchasing decisions, and two, we needed the practical problem of solving our own revenue problems, so we jumped in, head in, to say "Let's do a virtual event." I don't know if I would've done it if I wasn't as naive as I was back then, but we jumped in. >> So before we jump into the processes, make sure, give us a full-on plug, when is it, where should people go, registration I assume is still open, want to just get that out there for the folks. >> So even if you see this after registration closes, quote unquote closes, it's April 21st, >> 10: 30 AM central to 3:30 PM central, that's US time. You can register at CTOAdvisorVirtualConference.com. >> Excellent, so let's talk about some of the interesting things about virtual. One of the things as you said in a physical event, you've got people, you've got time and space and geography that we all come together in that space, and there's a lot of advantages to everybody being at the same place at the same time. A virtual event, almost by definition, is now you've broken up the segments of content capture, if you will, and creation, which can or cannot be on that date. The actual display, or the publishing of that content, if you will, and then the consumption of that content, which may or may not happen on the 21st. How have you worked with this expanded palette, if you will, to be able to work in an asynchronous world, and how are you finding it in terms of actually day to day execution? >> So you guys have done plenty of remote content at this point. When you're in theCUBE studio, you have commercial internet, it's fairly reliable when you're on premises, maybe a little bit less reliable from the sense that it's conference-centered, but it's still enterprise class internet access, so you can do real-time video on theCUBE fine. We can go to Cube.tv, Cube.net, and see what you guys are doing real-time, and it's pretty much without blip. In the virtual conference world, what we're dealing with where I'm coming in, remote to you, while my video and audio looks fine now, it may blip. So we embrace two things. We embrace the fact that this is a virtual event, so in a background, you'll see that we're in Keith Townsend's basement, the other thing that you'll see is that we won't produce live content, because there's not much value in it being live, if I can't interact with you. One of the great things about theCUBE, is that it's live, but there's this element that people are on the ground, they're watching it live, they're interacting with it live, we're tweeting about it, so how do you reproduce, if not that exact feeling of it being live and you're being part of it, but the conversation around the content, and that's what we focused on, creating high quality video content, that you can consume, kind of as a watch party, so on Twitter, in the platform that we're using, we're having conversations real-time, so that you can enjoy the community, and the speakers who are presenting, you can interact with them because they're not presenting real-time, they're in the chat room, they're on Twitter, they're running as their session is running, and they're able to interact with you, so we've embraced the medium, and then after the fact of course we can do all kinds of things to run asynchronous content after the fact, 'cause the majority of people will watch it after the video's done. >> All right, and I'm just curious, how many sessions are you going to have, approximately? >> So we have I think 21 sessions, in a five hour period, so we're running three separate tracks, two super techy, geeky tracks, then a sponsored track is kind of by itself, and we're not expecting everyone to consume it all at one time. >> Right, you know it's just so interesting to me, talking about your tracks. If you were to go rent a venue, that had the capacity to run 21 tracks over five hours, it'd be a pretty decent-sized venue, it'd be expensive, and then you would have to pick your sessions and your tracks based on the limitations of the budget that you had and the window that you had of rooms that you could put these people in, and who could do it now, when, there, the other thing, and so it's really interesting that now this opens up the amount of sessions, is really a function of what you can manage, or what the community can kind of self-organize, you're not really limited by how many rooms are in the Sands Convention Center, and the other thing that you brought up, which I think people completely miss is that if the content is recorded in advance and puts in the can, to your point, the presenter can actually participate in the conversation while the session is happening, which they can't do in a physical event, because they're actually presenting, so, we had a guy in the other day, Ben Nelson, he talked about a car is not a mechanical horse, it's not the same, digital's not the same as physical, and there are some things that aren't as cool, but there's a whole lot of things that you can do in the digital space that you can't do in the physical space. >> Yeah, a lot of my presenters were kind of put off by the idea of, "Wait, hold on, I'm not going to present live? "How will I interact with webinars now?" And I think this is the other end of the spectrum, Jeff, I think you guys have probably found this too, it's not a in-person event, and it's also not a webinar, so don't treat it as a webinar. You don't have to have these canned, phony questions that some people have behind the scenes, it is a real, authentic thing. Oddly enough, I discovered this as part of helping my church put on their worship service. I was watching the service, I'll look off the screen a little bit to the left, I was watching the service, and the minister's delivering his sermon, and in the Zoom meeting, there he is, playing with his little two year old daughter, while he's giving the talk, and I just opened chat at him, and next thing I know there's an explosion of conversation around just life and the topic at hand, so it is a really unique experience. >> Yeah, I think that's a really important point, it's not only what is a digital event, but what is it not, and it can't be a webinar, and when we were first going through this kind of shake-up, and we were really trying to identify some of those things, and we specifically did not want a digital event to be a webinar, 'cause what's a webinar, it's generally a one way communication of information for the vast majority of the session that you're sitting there, and they only open it up to Q&A at the very end, and it's only a moderated Q&A that very few people get a chance to get their question in, and you don't know how they're picking, and it only goes to the hosts, so, really having an open, live engagement around an engaged group of people, with a piece of content as kind of the coalescing of those people, really, it's not a webinar, it's a very different kind of experience, and sounds like you're really embracing that. >> Yeah, it'll never replace a live event, live has, again we talked about the energy, the, people are like "Do you really "want to smell the Sands, Keith?" You know what, it's all part of the energy, it's instant reminders to "Oh, I remember when I interviewed Pat Gelsinger here," and you have these instant cues that we as humans love, we don't get that, but I think it is something that's going to be with us to stay and it'll augment, I'd love to hear how you guys are thinking about how being able to have this capability will augment theCUBE once we return to physical events. >> Yeah, I mean I think this behavior that we're now been forced to engage in, in terms of increased working from home, and kind of increased use of videoconferencing, and that is a different communication mode, I think those behaviors are going to stick quite a bit, actually, I think if you look at what a conference is, there's a couple different tracks, as you said, there's the expression going around, kind of the rally moment, right, the keynote, we want, we have a strong message, the CEO wants to get something out, and I think that's of tremendous value, but then you look at all the breakout sessions and the information flow and the community engagement, those quite frankly can be done online much more efficiently and with much less cost, so will the new conference be kind of this, the celebration and basically a customer appreciation event, they want to have a party, but really that, I don't think it will be quite the information flow, 'cause why should product group A wait until the conference date, if they're ready to release their information, and wait for product group B or C or D, so this kind of forced aggregation of the communication into this very small window of three days in Vegas, I don't think it makes any sense, you know, it's Waterfall versus DevOps, and if this group's got stuff and they're ready to go, again, why hold the information back, it really doesn't make sense, and decouple the customer celebration, the rally moment, if you will, and the education, they don't necessarily have to be this contiguous big unit for three days in Vegas. >> Yeah, I'm looking forward to first quarter 2021, usually January, February, first half of March, really slow news channel product teams release stuff and they really want some big stage to release it, I think this will really make the dissemination of information coming from product teams super interesting as folks like theCUBE, The CTO Advisor, we're able to put on independent events virtually that have a sense of gravitas to it, that our partners will come and embrace. >> Yeah, the other thing, Keith, and I wonder, as you've been collecting your content for your show next week is that, the pressure on the quality of the content has escalated dramatically, right? If you're stuck in a huge conference hall, surrounded by 10,000 people, in the middle of a keynote that's not that exciting, it's kind of hard to get up and walk out. But if you're sitting at your desk with the entire world an alt-tab away, not to mention pesky things like email and Slack and everything else that we have as a distraction, it's really going to come in on the content provider and the engaged community to deliver, or else you're going to lose the audience, and I think it's going to be really interesting, people that overly have relied on the 100 foot video screen and the electronic violin music in the morning, and some of these tips and tricks, aren't going to carry the weight, because if it's just you sitting in front of a screen and you got to deliver the message, it's got to be crisp, it's got to be powerful, and it's got to be engaging, or people are just going to step away. >> And more importantly, how do you bring people back? So, you know how, when I take a break at a conference, I'm kind of captured. Eventually I'm going to walk back to the conference center, I might go back out to take a call, et cetera, but getting people to come back, even if the content has been awesome and engaging and great, how do you get 'em to come back, they don't have to come back that day, or even real time, but they have to come back to the portal, so we're working on kind of the next 30 days after the event, this is the thing that's really funny about putting on a virtual event, there's kind of the exhale after the day of the event, a virtual event, you know what, you've got a third of your audience that first day, a third of the audience the next week, and then the rest of the audience creeps in over the next three or four weeks, and how do you engage them, how do you get them to come back, and ultimately consume your content and your message? It's something that I haven't, I don't know if I've cracked the formula for it yet, but it is going to be a very interesting challenge. >> Yeah, but I think we have, right, in the way, how do you consume video today, how do you find information, right, you go to YouTube or to Google and you search, right, and right now the biggest phenom in pop media is the Tiger King, right, so when do people watch the Tiger King, how do they hear about the Tiger King, when do they actually sit down and watch it, has nothing to do with when you watch it unless we decide to trade messages, I say "Hey, Keith, have you seen the new episode?" So when you look at consumption patterns, to me it's really interesting, it's kind of bifurcated, you either binge watch, and just really get into something that you're into, and you just go go go for hours and hours and hours, or you're getting snippets, you're getting little quick hits, quick hits, quick hits, and I think it's this kind of ugly middle, where you don't have enough content or richness or engagement to have people hang, but you're a little bit longer than a quick hit just to get your message out, and I think it's really going to kind of bifurcate, and the beauty of digital is you can consume it in lots of different ways, and piece parts, and you don't have to necessarily kind of sit through kind of a straight row consumption as a captive audience, I think the opportunity's really really good, if the content is up to snuff, properly tagged, search terms, all those types of things of course as well. >> So yeah, John talks about the value of community a lot, and one of our co-hosts on theCUBE, and also a CUBE alum is Corey Quinn, and he does a really great job of this with curating content after it's been consumed live. He'll to his audience say "You know what, I'm going to live tweet this session "from three months ago," and that refreshes the conversation, it's not about when the content was created, it's about the conversation, as long as it's relevant, and finding mediums to help amplify that message. >> Yeah, I think it's just a great opportunity, you know, we used to do some work with Live Nation in another lifetime, right, and Live Nation around concerts, they had that particular event when you go to the show, and a lot of their efforts on the marketing side were what they call extending the glow, right, extending the glow after, and also kind of building the excitement before, and moving that window of that event to more than just the night that the show played, and I think we've got the same opportunity here, that's why again if you get good quality content, it's not speeds and feeds, but it's evergreen themes that have legs, you can go back to that well and you can stir that thing up, and you can get it back out there again, and then again hopefully people stumble upon it, whether it's via community or whatever. The other thing I think that's really interesting is you talked about community, and you talked about QuinnyPig, @QuinnyPig I think is his Twitter handle, is this whole idea of collaboration, and I think that's another thing that we can take from the internet, I know you do a lot of that, so working with other influencers if you will, or other people in the communities, and introducing each other's community to one another, I think it's a really big part of what makes a lot of the big YouTubers famous is that they do things together and they kind of cross-pollinate their communities, and if there's some overlap there then they both have kind of a win-win, and again I think in digital, where you don't have destruction, you don't have single use, you can use stuff more than once, it really opens up this opportunity for much more win-win, let's work together, and build community together, cross leverage, versus it's either yours or mine, and it's really more of a competitive thing. >> And I've been collaborating a lot with some of my European peers, and you bring up a really interesting concept. Our friends at VMware's going to be putting on VMworld in the next few months, and they usually had a US conference and a European conference, were both pretty sizable conferences. It's basically going to run concurrently as one conference. So if it's going to run as one conference, why do I have to limit the live experience to the US timezone? Why can't I cater this, and why is it just a fixed hour, I don't know if it will be, but it shouldn't just be a fixed hour event, it's going to be a all-out hour event that's going to happen across Asia, Europe, and the US, and tailoring the content to each continent and time zone, and cross-pollinating, so that content that I would not have typically have gotten at the US event, or in the Europe event, I can now get that experience and cross-cultural flavor as a natural part of digital, so there's a lot of opportunity, there's a lot to miss about in-person events, but I think there's opportunities that are just massively untapped. >> Yeah, yeah, and I'm just going to get one more concept, which I don't think is getting enough action, get your take on it, but if you think of the value to the company, let's just stick with VMware for a minute, we're great fans of Pat and Sanjay, there is a information transfer when Pat gets up and does his keynote as from one to many tens of thousands, and there's value there, and again we talked about this rallying moment, but think of turning that on its head, which is really what digital provides, now there's an opportunity for Pat and Sanjay and the entire VMware senior team and junior team and product managers to now flip that information flow. So if you think of the user experience from the attendees' point of view, is it better for Sanjay to talk to 10,000 people in an audience, or would Sanjay rather hear from 10,000 people, and have that flow of information going back in? So if you think of it as a community event versus a one way communication of here's our exciting news, I think the value to the sponsor goes up dramatically, 'cause there's so much institutional knowledge and tribal knowledge and experience within all those people that are just sitting passively listening to that keynote. If this is a way to better suck that information back into the company, I don't think they'll ever go back to the other way it was. >> Yeah, two points, two data points on that. One, again, from the worship side of the house, at our Easter service, our church enabled every member who cared to to kind of do a five, eight second "Hey, this is the Townsend family, "happy Easter," and then 15 minutes before the live church service started, they just ran a video of family after family after family that I recognize, saying "Hi, happy Easter," so you have that moment, and how do you capture that online? VMware's social media team already does this well, they amplify end user content, there was a guy that did a video on how to install VMware Cloud Foundation in three hours, went viral. You have these opportunities, again, to hear from sources and have conversations that's really not practical from a typical conference perspective. I think I heard it best the other day, one of my attendees and presenters said "You know what, Keith, the virtual conference "is such a democratizing event because "it enables me, whether I could not afford "to go to a conference before, "or I couldn't travel, or whatever reasons "I could not attend a conference before," the virtual conference gives opportunities for collaborations that could not have taken place otherwise. >> Yeah, it's great, so again, Keith, thank you for spending a few minutes with us and sharing your thoughts, and again, for everybody, April 21st 2020, next week, >> 10: 30 AM central time, join the CTO virtual conference. Keith, always great to catch up, man. >> You too, Jeff, thanks a lot. >> All right, take care. He's Keith, I'm Jeff, you're watching theCUBE, thanks for watching, I'll see you next time. (calm music)

>>live from Copenhagen, Denmark. It's the Q covering Nutanix dot next 2019. Brought to you by Nutanix >>Welcome back, everyone to the cubes. Live coverage of Nutanix dot Next here at the Bella Centre in the Copenhagen. I'm your host, Rebecca Knight, coasting along side of stew, Minutemen were joined by Bala Coochie bottler >>Bhola. He is the VP GM Nutanix era and business critical lapse at Nutanix. Thanks so much for coming on the island. >>It's an honor to come here and talk to guys. >>So you were up on the main stage this morning. You did a fantastic job doing some demos for us. But up there you talked about your data, your days gold. And you said there are four p's thio the challenges of mining the burning process you want >>you want to go through >>those for our viewers? >>Definitely. So for every business, critical lab data is gold likely anam bigness for a lot of people are anyone. Now the question is like similar to how the gore gets processed and there's a lot of hazardous mining that happens and process finally get this processed gold. To me, the data is also very similar for business could collapse. Little database systems will be processed in a way to get the most efficient, elegant way of getting the database back data back. No. The four pains that I see for managing data businesses started provisioning even today. Some of his biggest companies that I talkto they take about 3 to 5 weeks toe provisions. A database. It goes from Infrastructure team. The ticket passes from infrastructure team, computer, networking stories, toe database team and the database administration team. That's number one silo. Number two is like proliferation, and it's very consistent, pretty much every big company I talkto there. How about 8 to 10 copies of the data for other analytics que year development staging Whatever it is, it's like over you take a photo and put it on. What Step and your friends download it. They're basically doing a coffee data. Essentially, that Fordham be becomes 40 and in no time in our what's up. It's the same thing that happens for databases, data bits gets cloned or if it's all the time. But this seemingly simple, simple operation off over Clone Copy copy paste operation becomes the most dreaded, complex long running error prone process. And I see that dedicated Devi is just doing Tony. That's another thing. And then lineage problem that someone is cloning the data to somewhere. I don't know where the data is coming from. Canister in The third pain that we talk about is the protection. Actually, to me it's like a number one and number two problem, but I was just putting it in the third. If you're running daily basis, and if you're running it for Mission critical data basis, your ability to restore the rhythm is to any point in time. It's an absolute must write like otherwise, you're not even calling The database. Question is, Are the technologies don't have this kind of production technology? Are they already taken care? They did already, but the question is on our new town expert from Are on Cloud platform. Can they be efficient and elegant? Can we can we take out some of the pain in this whole process? That's what we're talking about. And the last one is, ah, big company problem. Anyone who has dozens of databases can empathize with me how painful it is to patch how painful it is to get up get your complaints going to it. Holy Manager instead driven database service, this kind of stuff. So these are the four things that we actually think that if you solve them, your databases are one step. Are much a lot steps closer to database service. That's what I see >>Bala. It's interesting. You know, you spent a lot of time working for, you know, the big database company out there. There is no shortage of options out there for databases. When I talked to most enterprises, it's not one database they now have, you know, often dozens of databases that they have. Um so explain line. Now you know, there's still an unmet need in the marketplace that Nutanix is looking to help fill there. >>So you're absolutely right on the dark that there are lots of date of this technology is actually that compounds the problem because all these big enterprise companies that are specially Steadman stations for Oracle Post Grace may really be my sequel sequel administrator. Now they're new breed of databases in no sequel monger leave. You know, it's it's like Hardy Man is among really be somebody manage the Marta logics and stuff like that so no, we I personally eating their databases need to become seemed like Alex City. Right? So >>most of >>these banks and telcos all the company that we talk about data this is just a means to an end for them. So there should focus on the business logic. Creating those business value applications and databases are more like okay, I can just manage them with almost no touch Aghanistan. But whether these technologies that were created around 20 years back are there, there it kind of stopped. So that is what we're trying to talk about when you have a powerful platform like Nutanix that actually abstracts the stories and solve some of the fundamental problems for database upstream technologies to take advantage of. We combine the date of this FBI's the render A P s as well as the strength of the new tenants platform to give their simplicity. Essentially. So that's what I see. We're not inventing. New databases were trying to simplify the database. If that's what >>you and help make sure we understand that you know, Nutanix isn't just building the next great lock in, you know, from top to bottom. You know, Nutanix can provide it. But Optionality is a word that Nutanix way >>live and time by choice and freedom for the customers. In fact, I make this as one of the fundamental design principles, even for era we use. AP is provided with the database vendors, for example, for our men, we just use our men. AP is. We start the database in the backup, using our many years where we take that one day. It is the platform. Once the database in the backup more we're taking snapshots of the latest visit is pretty much like our men. Regan back up with a Miss based backup, essentially alchemist, so the customer is not locked in the 2nd 1 is if the customer wants to go to the other clothes are even other technologies kind of stuff? We will probably appear just kind of migrate. So that's one of the thing that I want to kind of emphasize that we're not here to lock in any customer. In fact, your choice is to work. In fact, I emphasize, if the customer has the the computer environment on the year six were more than happy weaken. Some 40 year six are his feet both are equal for us. All we need is the air weighs on era because it was is something that we leverage a lot off platform patent, uh, repentance of Nutanix technology that we're passing on the benefits canister down the road where we're trying to see is we'll have cyclists and AWS and DCP. And as you and customers can move databases from unpromising private cloud platform through hybrid cloud to other clusters and then they can bring back the data business. That's what we can to protect the customers. Investment. >>Yeah. I mean, I'm curious. Your commentary. When you go listen, toe the big cloud player out there. It's, you know, they tell you how many hundreds of thousands of databases they've migrated. When I talk to customers and they think about their workload, migrations are gonna come even more often, and it's not a one way thing. It's often it's moving around and things change. So can we get there for the database? Because usually it's like, Well, it isn't it easier for me to move my computer to my data. You know, data has gravity. You know, there's a lot of, you know, physics. Tell General today. >>See what what is happening with hyper killers is. They're asking the applications. Toby return against clothed native databases, obviously by if you are writing an application again, it's chlorinated. Databases say there are Are are are even DCP big table. You're pretty much locked technical because further obligation to come back down from there is no view. There's no big table on and there's no one around. Where is what we're trying to say is the more one APS, the oracles the sequels were trying to clarify? We're trying to bring the simplicity of them, so if they can run in the clover, they condone an art crime. So that's how we protect the investment, that there is not much new engineering that needs to be done for your rafts as is, we can move them. Only thing is, we're taking or the pain off mobility leveraging all platform. So obviously we can run your APS, as is Oracle applications on the public lower like oracle, and if you feel like you want to do it on on from, we can do it on the impromptu canister so and to protect the investment for the customers, we do have grown feeling this man, That means that you can How did a bee is running on your ex editor and you can do capacity. Mediation means tier two tier three environments on Nutanix using our time mission technology. So we give the choicest customers >>So thinking about this truly virtualized d be what is what some of the things you're hearing from customers here a dot next Copenhagen. What are the things that you were they there, There there Pain points. I mean, in addition to those four peas. But what are some of the next generation problems that you're trying to solve here? >>So that first awful for the customers come in acknowledges way that this is a true database. Which letters? I don't know what happened is what tradition is all aboard compute. And when when he saw the computer watch logician problem you threw in database server and then try to run the databases. You're not really solving the problem of the data? No, With Nutanix, our DNA is in data. So we have started our pioneered the storage, which location and then extended to the files and objects. Now we're extending into database making that application Native Watch Ladies database for dilation, leveraging the story published Combining that with Computer. What's litigation? We think that we have made an honest effort to watch less data basis. Know the trend that I see is Everyone is moving. Our everyone wants cloudlike experience. It's not like they want to go to club, but they want the cloud like agility, that one click simplicity, consumer, great experience for the data basis, I would liketo kind of manage my data basis in self service matter. So we took both these dimensions. We made a great we made an honest effort to make. The databases are truly watch list. That's the copy data management and olive stuff and then coupled with how cloud works able to tow provisions. Self service way ability to manage your backups in self service. Weigh heavily to do patch self service fair and customers love it, and they want to take us tow new engines. One of the other thing that we see beget Bronte's with ERA is Chloe's. Olive or new databases generally are the post press and the cancer, but there's a lot of data on site because there's a lot of data on Mississippi. Honey, there's a lot of data on TV, too. Why don't we enjoy the same kind of experience for those databases? What? What did they do wrong? So can we >>give >>those experience the cloud like experience and then true? Watch allegation for those databases on the platform. That's what customers ask What kind of stuff. Obviously, they will have asked for more and more, um, br kind of facilities and other stuff that way there in the road map that we will be able to take it off. One >>of the questions we've had this week as Nutanix build out some of these application software not just infrastructure software pieces, go to market tends to be a little bit different. We had an interesting conversation with the Pro. They're wrapping the service for a row so that that seems like a really good way to be able to reach customers that might not even knew no Nutanix tell us, you know, how is that going? Is there an overlay? Salesforce's it? Some of the strategic channel and partnership engagements, you know, because this is not the traditional Nutanix, >>So obviously Nutanix is known. Andi made its name and fame for infrastructure as service. So it's really a challenge to talk about database language for our salespeople. But country that I heard the doubt when I kind of started my journey It Nutanix Okay, we will build a product. But how are you going to the city? And we get off this kind of sales for But believe me, we're making multimillion dollar deals mainly led by the application Native Miss our application centric nous so I could talk about federal governments. And yes, she made perches because it was a different station for them. We're talking about big telco company in Europe trying to replace their big Internet appliances because era makes the difference vanished. We're providing almost two X value almost half the price. So the pain point is real. Question is, can we translate their token reconnect with the right kind of customer? So we do have a cell so early for my division. They speak database language. Obviously we're very early in the game, so we will have selected few people in highly dense are important geographic regions who after that, but I also work with channels, work with apartments like geniuses like we prove head steal another kind of stuff and down the best people to leverage and take this holding and practice. This is the solution. In fact, companies like GE S D s is like people take an offer. Managed database seven. Right. So we have a product. People can build a cloud with it. But with the pro they can offer in a word, why do you want to go to public Lower? I can provide the same cloud. Man is database service more on our picks, Mortal kind of stuff. So we're kind of off fighting on all cylinders in this sense, but very selectively very focused. And I really believe that customers fill understand this, Mrs, that Nutanix is not just the infrastructure, but it's a cloud. It's a It's a club platform where I considered arise like Microsoft Office Suite on Microsoft's operating system. Think about that. That's the part off full power that we think that I can make make it happen >>and who are you know, you said you're going in very tight. Who are these Target customers without naming names? But what kinds of businesses are they? You know? How big are they? What kinds of challenges. Are >>they looking at all? The early customers were hardly in the third quarter of the business, but five. Financial sector is big. The pain point of data mismanagement is so acute there capacity limitation is a huge thing. They are spending hundreds of millions of dollars on this big. When that kind of stuff on can they run in the can extract efficiencies out of this hole all their investment. Second thing is manufacturing and tell Cole, and obviously federal is one of the biggest friend of Nutanix and I happened to pitch in and religions is loaded. And they said, Israel, let's do it real demo. And then let's make it happen. They actually tested the product and there are taking it. So the e r piece, where are they? Run Oracle, Where the run big sequence kind of stuff. This is what we're seeing. It >>followed. Wanna make sure there was a bunch of announcements about era tudo Otto, Just walk us through real quick kind of where we are today. And what should we be looking for? Directionally in the future. >>So we started out with four are five engines. Basically, Andi, you know that Oracle sequel and my sequel post this kind of stuff, and we attacked on four problems this provisioning patching copy, data management and then production. But when we talked to all these customers on, I talked to see Ables and City Walls. They love it. They wanted to say that Hey, Kanna, how around more engines? Right? So that's one will live. But more importantly, they do have practices. They have their closest vehicles that they want to have single pane of management, off era managing data basis across. So the multi cluster capability, what we call that's like equal and a prison central which manage multiple excesses. They weren't error to manage multiple clusters that manage daily basis, right? That's number one. That's big for a product with in one year that we regard to that stage. Second thing was, obviously, people and press customers expect rule rule based access control. But this is data, so it's not a simple privilege, and, uh, you would define the roles and religious and then get it over kind of stuff. You do want to know who is accessing the data, whether they can access the data and where they can accident. We want to give them freedom to create clones and data kind of act. Give the access to data, but in a country manor so they can clone on their cure. Clusters there need to file a huge big ticket with Wait for two weeks. They can have that flexibility, but they can manage the data at that particular fear class. So this is what we call D a M Data access management. It's like a dam on the like construct on the river, control flow of the water and then channel is it to the right place and right. But since Canister, so that's what we're trying to do for data. That's the second big thing that we look for in the attitude. Otto. Obviously, there's a lot off interest on engines. Expand both relation in Cecil has no sequel are We are seeing huge interest in recipe. Hannah. We're going to do it in a couple of months. You'll have take review monger. Dubious. The big big guy in no sequel space will expand that from long. Would it be to march logic and other stuff, But even D B two insiders There's a lot of interest. I'm just looking for committed Customers were, weren't They are willing to put the dollars on the table, and we're going to rule it out. That's the beauty of fair that we're not just talking about. Cloud native databases Just force Chris and kind of stuff. What? All this innovation that happened in 30 40 years, we can we can renew them to the New Age. Afghanistan. >>Great. Well, Bala, thank you so much for coming on. The Cuba was >>Thank you. >>I'm Rebecca Knight for stew minimum. Stay tuned. For more of the cubes. Live coverage of Nutanix dot next.

>>from San Francisco. It's the Q covering pager duty Summit 2019. Brought to you by pager Duty. >>Hey, welcome back there. Ready, Geoffrey? Here with the cue, we're pager duty Summit in the historic Western St Francis Hotel, downtown San Francisco. I think they've outgrown the venue. The place is packed to the gills. Standing, rolling, the keynote Really excited of our next guest. Someone who's been to this industry for awhile really done some super cool creative things. He's given the closing keynote. We're happy to have him here right now. That's Mitchell Hashimoto from Hachiko. It's great to see you. >>Good to see you too. Thanks for having >>absolutely so just a quick overview before we get into it on hot chic or for the people in our familiar >>Sure, so hospitals a company that what we try to do is help people adopt cloud, but more, more realistically, Adolfo multi cloud and hybrid cloud the real world complexities. That cloud isn't just a technical landing point, but it's really way You deliver software. You want to deliver more applications, you want to connect them faster. You want to do this in an automated away infrastructure is code of all these modern practices way. Build a suite of tools Thio provisions secure, connect and run those applications for separate products that we sell that you could adopt separately. Good mix and match. That's That's what we've been doing for a long time. Based on open source Software, Way started purely as an open source community and have grown into an enterprise cos that's that's That's the elevator pitch. >>No, it's great, but it's a great story, >>right? Europe, Europe in Seattle got some access to some cloud infrastructure and really solve your own problem. Figured out other people of that problem and then really built a really cool, open source kind of based software company. >>Yeah, I mean, I think the amount of people that had the problem I was facing personally was orders of magnitude more than I expected. I've told other people we never expected to start even a business around this. It was just scratching and building technical solutions. But a CZ, as we sort of worked at startups, started talking a bigger and bigger companies. It just kept everyone kept saying, Yes, I have that problem and it's only grown since then, right surprising, >>and the complexity has only grown exponentially before. The you know, years ago, there was this bright, shiny new object called a W s. I mean, I love Bezos is great line that nobody even paid attention. You have six or seven years. They've got a head start and kind of this Russian. Now there's been a little bit of a fallback as people trying to figure out what to go where now it's hybrid cloud and horses for courses. So a lot of great complexity, which is nothing but good news for you. >>Absolutely. I told this story before, but our first year incorporated company I actually got hung up on by an analyst because I said way we're trying to solve a multi cloud problem and they said that's not a real problem when it will never be a real problem. They hung up on me on it was a bet, then, and and I think they're the expectation that was it was gonna be Eight of us is gonna be physical infrastructure and the physical infrastructure days were numbered. It was gonna get acts out. It was just gonna all go to eight of us and our conviction was that you would have both forever and or for a very long time. And then people like Azure, Google and others would pick up and and that's been true. But I think what we didn't expect, the complexity that got introduced with things like containers in Kubernetes because it's not like Clouded option finished in the next started It all came at once. So now Riel Cos they're dealing with the complexity of their still trying to move the clouds. They're trying to get more out of their physical infrastructure, trying to adopt kubernetes. Now people are starting to peck at them about server list. So there the complexity is is a bit crazy and review our job trying to simplify that adoption make you get the most out of >>right. And that was before you could get a piece of Ian where inside of AWS, get a get a piece of the Google Data Center inside your own data center. So it just continues to get crazier. >>Yes, yeah, So you're giving a closing keynote on a >>new project. You're working on fault, and it's an existing project. Justin cry. They're old, but but I think you talked about before we turn the cameras on. It's really more of a kind of an attitude in a and a point of view and a way to go after the problem. So I wonder if you could kind of dig into a little bit of What did you see? How did you decide to kind of turn the lens a little bit and reframe this challenge? Yeah, >>I think the big picture of story I'm trying to tell him the keynote is that everybody? Anything You look around the technical nontechnical, this table, that glass. Like everything you look at, it trickles back to the idea of one or a small group of people, and it takes an army to make it show up on this table. But it starts by somebody's vision, and everything was created by somebody. So I'm talking about vault, something we made and, you know, why don't we create it? And why do we make it the way we did? And you know, another thing I say is people ask, Why did you start hot record for having this vision? Something I constantly told myself was wine on me. I get someone's gonna do it. Why not make it? Could be anybody, like I'll give it a shot. Why not? And Bolt was that way. We Armand. I'm a co founder. Way took security classes in college, but we don't have a formal security background. We didn't work in security in industry. So the odds of us launching a security product that is so prevalent today whether you know it or not, it's behind the scenes very prevalent were stacked against us. How did that happen? And that's that's sort of what I've been going to talk about. >>Let's go. But do >>dive into a little bit on the security challenge because it's funny, right? Everyone always says, Right. Security's got to be baked in and you've got these complex infrastructure and everything's connected with AP eyes, the other people's applications and, oh yes, delivered through this little thing that you carry around. And maybe the network's not working well or the CPS running low are You're running iPhone five. And of course, it's not gonna work on most modern app. Yeah, bacon security always do, but that's easy to say. It's much harder to do, you know. Still, people want to build moats and castles and drawbridges, and that's just not gonna work anymore. >>Exactly. So you exactly hit upon the two major issues that we recognize there felt we recognize. One was that a lot of people were saying it. Very few people were doing it on. The reality was it was hard to do. Everyone knew theoretically what they should do. No one, no one thought. Oh yeah, saving somebody's personal information in plain text in the daytime. It's a good idea. Nobody thought that Everyone said it should be encrypted, but encryption is hard. So maybe one day, so no one was doing it. And then the other side of it was the people that were doing it where the world's largest companies, because the solutions were catered towards his mindset of of castle and moats, which works totally fine in a physical tradition environment but completely breaks down in a cloud world where there is no four perimeters anymore. It's >>still there, There. >>You're one AP I call away from opening everything to the Internet. So how do you protect this? And we've seen a lot of trends change towards zero Trust and ServiceMaster Mutual feel like there's a lot of stuff that happened way sort of jumped on that. >>Yeah, so So you're using, like, multi level encryption, and I've read a little bit on the website. It's way over my head, I think. But, you >>know, the basics are just making kryptonite. Christian makes security, cloud infrastructure, security approachable by anybody and a core philosophy. Our company, Hashi Hashi Hashi. My name means bridge, and that is a core part of our culture. Which is you can't just have, ah, theoretical thing or a shiny object and leave people hanging. You gotta give them a bridge, a path to get there, right? And so we say, with all our technology, one of the crawl, walk and run adoption periods and with security it's the same is that to say you're secure means something totally different everybody for a bank to be secure, it's a lot more than for a five person started to be secure. So how do you give somebody a solutions they could adopt? Check the security box for themselves at every path of the lake, and bald is one of the tools that way have individuals using it, and we have the world's largest companies, almost 10% of the global 2000 paying customers evolved many more open source users on its scales the entire spectrum. >>Wow. So you keep coming up >>with lots of new, uh, new projects as we get ready to flip the counter to 2020. What are some of the things you're thinking about? >>I think the big one, you know, that our focus is right now is service. Miss Vault is we're big enough company now where we always have teams working on every every one of our projects we have release is going out. The thing we've been talking about the most is the service mess thing. I think Cloud as a mainstream thing, Let's say, has has existed for seven or eight years. It's since it's been released. It's been over in almost 15 but as a thing that people have, that is a good idea. Seven or eight years and you know we've touched security. Now we've touched how infrastructures managed touch developers. I think a place that's been relatively untouched and has gotten by without anyone noticing has been networking and network security. They're they're really doing things the way they've always done things, and I think that's been okay because there's bigger fish to fry. But I think the time has come and networking as a bull's eye on it. And people are looking at What is networking mean in a cloud world and service mash appears to be the way that is gonna happen. Way have our own service mess solution called Council on Our Approaches Standard Hasta Corp. It's nothing new. It's We're gonna work with everything containers, kubernetes, viens physical infrastructure. We're gonna make it all work across multiple data centers. That is our approach service fashion, solving that challenge. >>What's the secret sauce? >>I mean, it's not that secret, right? >>It's just building. Just execute. Better understand that this header >>JD is the problem, right? Right, I said, This is our keynote a couple weeks ago that there are a lot of service messes out there, and nine out of 10 of them are solving a solution for a single environment, whether it's kubernetes or physical environment. And I think that's a problem. But it's not the problem. The problem to me is how do I get my kubernetes instances pods to communicate to my NSX service is on my physical infrastructure. That is the problem as people, whether that's temporary, not and they intend to move the communities or whatever. It's that's the reality. And how do you make that work? And that is what we're focused on solving that problem >>just every time I hear service mess. I think there was a company a while ago that sold the CSC. Probably like 2013. Didn't really get into That is a as a good, happy story. But they were early on the name. Yeah. Yeah. So last thing pager duty were Pedrie. What? You guys doing a page of duty? >>Sure. So we've been I've actually been a paying customer pager duty since before we even made this company in my previous job was a customer wear now, still customers. So we still use it internally. But in addition to that way, do integration across the board. So with terra form our infrastructure provisioning tool way have a way to manage all pager duty as code and as your complexion pager duty rises instead of clicking through a u. I being able to version and code everything and have that realize itself and how he works very valuable from like a service MASH consul standpoint. Hooking in the monitoring to the alerting of Pedro duty is a big thing that we do so tying those together. So it's very symbiotic. I love pager duty as a user and a partner. There's a lot here. >>Yeah, is pretty interesting slide when Jennifer put up in the keynote where it listed so many integration points with so many applications with on the outside looking in and you're like how you're integrating with spunk, that making how you're innovating with service. Now that doesn't make any sense. How Integrated was in Desperate. These were all kind of systems of record, but really, there's some really elegant integration points to make. This one plus one equals three opportunity between these applications. >>Yeah, I think it's very similar to the stuff we do with Walton Security. It's like the core permanence. Everybody needs him like with security. Everyone is an auto. Everyone needs traceability. Everyone needs access control. But rebuilding that functionality and every application is unrealistic. And paging and alerting an on call and events are the same thing. So it's you'd rather integrate and leverage those systems that make that your nexus for that specific functionality. And that's where Page duties. Awesome way. Step in, >>which was always great to catch up. Good luck on your keynote tomorrow. And really, it's a really amazing story to watch that you got You guys have built >>Well, thank you very much. >>All right. He's Mitchell. I'm Jeff. You're watching the cue. Were paid your duty, Simon in downtown San Francisco. Thanks for watching. We'll see you next time.

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen brought to you by X Ensure Interactive. >> Welcome back to the Cubes. Live coverage here in Las Vegas for Adobe Summit. Twenty nineteen. I'm John Murray with Jeffrey Kerr. Next guest. Touch Wars. Who's a global delivery lead for Adobe with sent a censure interactive. That was a tongue twister. You for you, for the adobe relationship with a censure interactive. That's correct. Thank you. Global delivery lead. Thank you. That's right. Look into the Cube. Thankyou. So global. Big big landscape, cloud computing, Global impact delivery. That's hard corn nuts and bolts on the front lines. Tell us by what you do, what some of the issues around delivery, because that's where the rubber hits the road on all this. >> Well, that's exactly right. You know, when I think of my roll, think of me if someone who's out there working shoulder to shoulder with customers when it, you know from a delivery aspect, you know, providing the capability, providing the skills, providing the talent, making sure that we're getting the results that our clients are looking for and ultimately the quality that that we need to deliver for them. >> You guys do a lot of work. I mean, censure Interactive got a great team that sets up all the upgrade ideas, all the new business models. New tech is here. People process, culture change all going on. The end of the day comes into your I've gotta deliver it. And then the outcome is that the one has to accept that this is a core issue of people, talk about operational izing new things and sometimes has changed. Management involved his new culture shifts. So this is where we hear a lot. It's not. The tech problem is the people and the culture. Can you share your view on this because you're on the front lines on this one issue? >> It's a great point. And I think you know, one thing is standing up technology, and you can sort of get some of the nuts and bolts running. It's another thing to really get our clients and our customers enabled so they can unleash the power of some of these platforms. The technologies you know, there's a entire journey map on what their own people we need to go through from in a moment. There is a change management aspect around how we get those folks sort of feeling comfortable about that, and we often go through a couple different methods to do that. Sometimes we do it too, in the box where we'll sort of act with them and the same role other ways we'll sort of lead by example and do it and then they'll sort of shadow us and then eventually we just sort of make that transition. In some cases, they just frankly, you know, outsource it to us, right? And well take over that sort of feature and functionality a role in position on behalf of our customer. And that's okay. >> kind of horsepower. Do you bring to the table? And we just interviewed Nicky, who handles the essential interactive operations that seem like a great power source standing up fast, some operational capabilities. What else do you guys do bring to the table in terms of the delivery piece? >> Well, >> what Nikki and her team do is vital for us. So when you think about when I'm out there doing, I'm out there standing up these capabilities, empowering our customers, and then Nikki's with her team and everything we're doing an X century active operations is sort of operating that for that client, right? So once we sort of turn on some of those features and functions that Nicki's out there with her team, sort of running with it. And in that multiyear run in, getting those >> custom will hand the keys to her. Do so you, that's the hand off. Is that okay? >> Exactly. Right. So once we once we sort of power everything on with our client's power, all that integration on and then we leverage Nikki and her team in many ways to sort of take over that run. Tom, if you talk about the skills, that kind of the skills gap, if you will on some of the clients that you have and how are the skills and the rules evolving to execute with some of these new tooling in this kind of new process? It wasn't like build a campaign and slow roll it out. Now it's Go, go, go, go, go! Oh, you're absolutely right on that and I think I know that. But it's evolving, right? I mean, we data scientists are more important than they ever were. And so all of our customers and ourselves are investing on how we get data science because at the heart of it and If you think about what he's talking about in some of the new products that are coming out, it's about building that data layer right. And it's about taking that data later to the next level, too, around security and tradition. So helping our customers started get their arms around what it means to manage that data and all those aspects around the view of a customer is critical. Even the even the presentation tear you know it'LL be provides all those amazing technologies that allow customers to drive those rich experiences, whether it's on a tablet, whether it's on a mobile, whether it's on your desktop, ubiquitous doesn't matter. But that presentation tears is constantly changing. I mean, we didn't have, you know, the anger and the React ten years ago. Now you have all these other frameworks you have to begin to prepare for. >> About the one of his Aquino yesterday we've got my attention was the word and look, I love the way it sounds personalization at scale. And that's just just think about that concert for second. It's mind blowing. We love we love personalization doesn't like personalization. Yeah, but at scale a lot of moving parts. This is in your guy's wheelhouse. Century irregulars have large scale customers globally. What does that mean to you? Because I had us had happened best by so much. Send out forty million emails means insane the personalization experience. What does it mean? >> Well, what? >> When I hear something needs to be a scale, you gotta break it down to be a simple as possible. You got to figure out how you make that something super complex and dumb it down to where you truly can't scale it where you can enable people quickly. Um and sometimes you think big and start small so often What we'LL do is we'LL have our customers say, if you want to do one toe, one personalization we need to be thinking about how we can create content quickly, how we can create art quickly, how we can go and and operationalized that globally. Right, Because many times you need be working around the clock. So for me, when I think of that scale, it's how do we turn those capabilities on around the globe quickly for our clients and basically, you need to break it down. >> It's a place you go, though customs saying, Let's let's pick some use cases. That's a beachhead. Get that figured out. Make sure it's not a lot of moving parts. >> Yeah, and against >> software, because experience engine things of that nature >> and sort of start small, you know? So I you know, I would light up some teams take some initial use cases, maybe think about how you know, what are some of those you know, initial user journeys that end in journey. We wantto prove out. And then let's operationalize those. And then we'LL build on top of that overtime. >> Be asked by the Adobe announcements. What's getting you excited here? The event with some of the hallway conversations and conversations after hours, a lot different events going on. What are you talking about? What's the top conversation that you're involved in >> for sure AP when you talk about the new experience platform that's coming out and everything around there to me, I think that's a game changer in the marketplace, and I think it's also critical. Certainly OD eyes all wrapped in there and all the data theater aspects. But the new experience platform that Adobe is investing, it is sort of where I think our customers are driving towards and what's required in order to meet the demands of how to secure this data. How to wrap some permissions around it, how to take. You know what we would consider a P I and pH. I like data on be able to use it and more of their tools knowing that we have the security of the integrity of >> our CM taxi. Your job with customer experience. Platform >> right. Impact. Our job is it unleashes all kinds of potential. Uh, you know, when we do you think about what were out there helping our customers solution, it opens the gamut for us to go and sort of drive those next generation experiences in a much more you know, I guess, uh, formidable way, you know, I can >> more capabilities. Oh, absolutely. You know, >> execution. Exactly. What was super complex for me to build now just became a lot easier. Because now I have a frame, Eric and a structure and a platform that they're enabling it >> has impact the interview. The customer. I mean, so the partner landscape because you guys have a lot of partnerships, just always a key. One house. You hear Adobe Summit. But, you know, you might have some of these little Miss Provider's come in with a nice tool chain. Say, Hey, you know what? I want to plug this in the biggest center interactive engine. You guys got a lot of global breath. You're gonna probably get some impact on the ecosystem. How do you see partners? Because if it's an enabling platform and should be in the building something so that's going to tell Sign what? What's your view on the partner ecosystem? >> What's the first thing I'LL say about that is I think we're in a unique position because if you look at the scale we have at Accenture, so although I'm in extension interactive, I'm very focused on that digital and building the best experience on Planet I have this huge engine behind me of Broderick Center that has these capabilities. I mean, you know what we're dreaming up around, how we're working with Microsoft and happy Well, guess what? We already do that, too, so I can bring a lot of those vendor relationships and experiences capabilities and bring him right in house quickly. And when I need to go out to market and partner. I have those avenues, and I can go bring that niche that >> Lego blocks together now. Yeah, big things, auto integrate. Just put it together and >> adobes continue to invest in their io. And that allows us to integrate and plug in these things a lot quicker than we ever have before. >> What's the biggest challenge? You see it that adobe and the markers and and market is having the marketplace because a lot of new tech, a lot of great capabilities. Now emergency. There's a shift happening. Yeah, you know what kind of been going slow? You know, yard by yard, moved the chains like a football analogy. But now big movements gonna have we see happening Way. Siya shift coming. Big wave of innovation. What's the challenge? >> That definitely two challenges. I think one, uh, it's just the speed, right. The speed in which the market is moving. And how do you keep up with that speed? And how do you continue to invest in your own people? T learn it. And then, too, I think this year amount of data like the fact that we can store all this data. We have more data coming in than we've ever had before. I mean, just think of what I owe tea is doing to our our landscape and all the data that's coming in from a night and now we can use that as a as a whole, another level of, ah, sophistication and our analytics and our segmentation. And that's a tough job, right? That's how marketers keep up with that. It's, uh, it's changing their landscape, for sure. But what about just kind of the point of view when they get competition that comes out of complete left field, right, that you know, uber and lift or the obviously examples to get way overused. But you know, the company's heir now beating against companies that weren't even in their radar before that were purpose built on moving at light speed to your point. How do you help those legacy? Those legacy guys kind of take the big league, take the big step, get to hyperspeed personalization? I mean one thing. You can't be complacent, I think if you are complacent, your you know, one of those small, innovative companies is going to slowly eat your lunch on. So I think, you know, take advantage of that mindset that those small, you know, incubation type companies or this moth and maybe even think about How do I How do I build that same type of innovation within my own halls? And how do I take a manager? How that rapid development of that rapid change and oftentimes we're helping our customers go in and bootstrap that right started like, Let's go inside. And let's build a little innovation hub inside your own organization to go and compete with them. Otherwise, you know you're going to see what you know, like the case studies you just >> referenced right, because they're in the driver's seat, for sure. I mean, I think this is great innovation. Question. That week that came up in our last segment with Jim Leyland was you know, he talked about the vendor dynamics. Yes, When you have the world floating upside down, things have changed. Sweet vendors lead and enable. Now you have abs dictating terms, the infrastructure. That's a cloud model. He made a good point, he said. You know, a lot of the transformational stuff is great, but then it fails during integration and pointing out that they get to a certain point. It just crashes, not crashes. That's my word. But he said thiss challenges. It wasn't specific on outcomes of of transmission, we said pretty much its struggles and usually doesn't happen. Yeah, how do you see that? Because with now, automation machine learning Now you have agility in a marketing landscape, not just marketing cloud. You got all kinds of other things. It's like this sales and marketing. And there is everything you have agility. How does the integration impacts and has the delivery impact that transformation >> Goal? What ends? You're exactly right in the fact that when organizations make a big investment and Toby Technologies, they typically have a lot of other investor. It's another technologies as well. And so how do you create agility where you gotta plug and play sometimes more than one, and I'm sure Jim talk to you about our customer experience, engine and the beauty of that right where we can go and really bring a framework to our customers and our clients. That allows us to take the best of all these of all these experiences all these platforms, I should say, to build the best in class experience, and that's something we absolutely bring to the table. It's a framework. We've proved it out. And frankly, we have a whole bunch of connectors that already exist. So from my mind, when I'm trying to get them to be agility, I bring that type of thing to the table to help them move fast. >> I think that's a successful tell sign we see with successful, then vendors and partners and integrators is that you guys took your core competency and rose software and he packaged it up to automate the heavy lifting that I mean, why wouldn't >> you do the >> way you >> are accustomed there, >> buddy? I mean, I walk in our customers and I'm like, Well, they have a little this. They have a little that, then they're goingto go on, make this massive invest in Adobe, and it's like they're not going to just discard to retire some of those things. So way attempt to solve that problem. >> That's a real differentiate. Congratulations. Jim was great on that final question for you. Look going forward. What do you excited about? What's on your road map? What's what's next for you is the next leg of the journey for global delivery. Well, more delivery, you >> know. Honestly, it's it's to continue to build off scale around all of our locations. So when you look at its Centre Interactive were, you know, obviously a big North American business. But we have businesses all over the globe, and it's to continue to create, you know, to meet our customer's demands as they expand global. That's how do we deliver local and how do we deliver around the clock for them? And so for me, it's about build those capabilities everywhere you go South America, Australia, New Zealand in Eastern Europe, and, uh, and making sure that we create the same delivery patterns and we leverage the same assets and accelerators like the customer experience engine in all those places. >> And one final question. As you look at the arena of the all the vendors competing, what's the what's the winning formula? What's the posture that you see that's a successful vendor as they integrate it in this kind of these journeys in these experiences, what successful makeup of a successful supplier to customers >> from this from a from a technology >> that you look at all the players got Microsoft big part of the job you got Amazon, you got all these. You know, Marsh, Martek Stack is littered with logo's consolidations happening. There's a lot of battles battles on the field right now. Players of fighting for their future. >> Well, honestly, I think those who are going to make it as simple and as easy to empower their people to use is gonna be the winner. And I think you're you're seeing that certainly at at Adobe. But there's a lot of other formidable vendors out there who are creating very simple techniques to go on like this up. The more you could empower a business person and a marketer to do self service, the bigger win you're gonna have >> and to your point about scale. Simplicity. Yeah, thanks for coming on. Great insight. Thank you so much to share in the commentary. Appreciate Todd Schwarz here on the Cube Global delivery lead for the Adobe account for a censure Interactive Stevens. One more day to coverage after this short break. I'm John free with Jeffrey will be right back

(uplifting music) >> Hi, I'm Peter Burris and welcome again to another CUBE Conversation from our wonderful studios here in Palo Alto, California. Another great topic to talk about, we've got Robert Schmid, who is the Chief IoT Technologist at Deloitte. Welcome to The Cube, Robert. >> Thanks for having me. >> You also have your own video cast, so why don't we get that out of the way. What is it? >> Yeah, every Friday at 9 AM Pacific I do a show called Coffee Chat with Mr. IoT and Miss Connected. I just actually added a co-host, I thought I needed someone to help me. And we talk about IoT. It's on YouTube, you can find it on the channel, and it's really odd for me, that you're going to ask me the questions and I'm going to have to answer. (laughing) So I'm going to try to eat my own, my own advice here and be short. >> Well you know maybe someday you can have one of the Wikibon folks in your podcast, or video cast, we'd love to do that. >> Yeah that'd be great. >> Alright let's start here though. Deloitte's a great name, been around for a long time, associated with customer value in very profound ways, complex applications. That certainly characterizes IoT. What's going on with IoT at Deloitte? >> For us, we started a whole practice around IoT, and I'm leading that practice, but the thing for us was, there were a lot of science experiments going on around IoT, technology based, but we really wanted to bring it to what's the value behind IoT? So we really focused on use cases, and today we see that most focuses are on industrial IoT, though we spend a lot of time around connected products as well. I personally actually today worked on a project in a factory in Chicago, on a shop floor, connecting machines and measuring data and providing value. I work with an airline at an airport, around their travel so really helping guide you throughout the day. Interesting fact, you know we swipe away a lot of notifications without actually doing anything with it but when airline tells you, "Please come in 10 minutes early, the TSA wait time is long." I know you and I got to be there. >> You pay attention. >> Yeah, we got to be there early. We actually react to those notifications so I work on that and I work with high tech companies around their platforms, how to make their platforms better. >> You've raised a lot of really, really important issues but let's start with this notion of use cases >> Sure. >> A factory floor with a lot of PLCs, spitting out information, mediated by individuals or users and the data, where's it end up? That's real different from an airport where a lot of the data's being generated by a human being as they move places or is intended to be consumed by a human being. What kind of common patterns are you seeing in these use cases that brings them all under this notion of IoT? >> I always think of IoT as taking sensor data and making decisions based on those and what's interesting to me is that it creates this real interesting dilemma that we thought we knew what goes on with users, how they work and what they do. We do surveys just to find out what they're saying, the survey's actually probably not what they do but now with sensors we know what they do all the way to machines where we have decades of people having experience about, "This sounds a little odd, the machine doesn't sound right" but then they don't know what to do with it and now we can measure that because really at the end of the day, vibration isn't anything else but sound, right? So for me this is all about, and what's common about this, is that we really take that, we think we know to we actually know because we can now measure with sensors what goes on in that area. >> So it's almost like taking a lot of that time motion analysis, operations research that we used to do periodically, episodically with human beings doing their best to record stuff and bringing a lot of that discipline continuously and in real time so that it can better inform overall decisions, right? >> Yeah, I mean almost near real time, many of these cases and that's a really interesting scenario for me, right? Because now can actually see what happens in the factory when I tune the mix or the blend of my raw materials, what happens to the product that gets made at the end of that. >> As we think about the challenges or the changes that we foresee going on, is there a difference in thinking about humans as users or humans as consumers of a lot of this data and machines? I know there is, but how is this, because kind of the machine side has always been associated with SCADA, OT and the disciplines and approaches for that side seem a little bit different than what's coming out of the mobile world which is still very, very closely associated with how we utilize or how we deploy these systems to inform decisions in either case, is that right? >> I don't really know if we do so much about decisions for machines. I think at the end of the day many of the decisions are still made by humans. I mean I think about this like, we have a heating element running over, at the end of the day it still is a human that goes and sort of like says, "Yeah, let's turn that off." >> But there's still automation that takes place? >> Absolutely there's automation but automation takes place today. >> Sure. >> None of this is particularly new. I mean OT has done automation forever, right? >> Right. >> I think the interesting part is now taking the learning and connecting the different data points together. I talked about the factory floor, I just showed, actually, at the show we created a virtual factory line, life size. You can download it, it's the virtual factory by Deloitte. If I get my phone going I can show you, but it's not. Right here. (laughing) I call it "the internet of rubber ducks". >> "The internet of rubber ducks"? >> The internet of rubber ducks. Yeah, it's kind of cute. You have these little yellow ducks and if you load the app you can see them being made. But it's actually really what goes on at the factory and it really shows how when you change the blend at the beginning of a production line, how it effects at the end of the factory line, the outcome, how much scrap you have. What's the scrap? What's the overall equipment efficiency? OEE and so forth. What happens is now we can connect data from the very beginning of the factory line with he very end of the factory line and then combine that with contextual data such for example as temperature or the vibration on the machine or the current which we haven't done before. This whole time series of data that we now correlate becomes really critical and I don't think that's something we've done really as much before. That has not driven automation in this zone. >> If we think about it, we're talking about sensors which as you said, SCADA's been around for a long time and it tends to automate very, very proximate to where that sensor tower might be but a lot of the information that went into decisions was actually then generated by a person, perhaps a shift supervisor or somebody else or a machine operator said, "I heard a rattle" but there's no time so it's difficult to correlate and now we're talking about up leveling a lot of that information so it becomes part of the natural flow out of the machine but still for human consumption to make decisions? >> Yeah, very much like that. As I said, I talked about the blend of the materials that go in and then now we can correlate that particular part of the sheet. We can look on video and see how it looked and check the quality and then see at the end how many pieces of product did we produce. Actually in that particular case, it's really fascinating, it wasn't so much about reducing cost, it was actually increasing output. For them each line costs about 10 million and with the findings we have and what we're doing with them, we can actually give them the ability not to build another line but actually produce more lines because they can sell more which is a great position to be in. >> Sure, absolutely. >> You actually impact the top line rather than just the bottom line. >> Well productivity fundamentally is a function of what work you can perform for what costs are required to perform that work and if you can improve the effectiveness of something, keep the cost the same but get more work out of it, that's a big, big plus on the bottom line. >> And they have the market to sell it in to, right? >> Absolutely. >> If you just make more and you can't sell it- >> Well there's that, too. >> Yeah, which is really the good thing about that particular example. >> But talk about how, for example, you noted that they can look at a video of how the plastic or the sheets coming off the machine or set of rollers perhaps but how does AI start to be incorporated in to this IoT discussion? And what kind of use cases are you seeing becoming appropriate or more appropriate or made more productive by some of these new technologies we bring, some of the analytics and some of the IoT elements together? >> We find that we do a variety of theories. We go in and we say, "Hm, how about this? How about that?" And then we have our data scientists go and look at models for that and see what goes on and then put machine learning in and then we take those machine learning models and feed it back into, we talked before a little bit about this, but age processing is really something where we now process some of those models on the edge. The algorithm development and all the analysis we send that to the Cloud, we do number crunching there and we really take advantage of the unlimited capacity. >> A lot of the training happens up at the Cloud? >> A lot of the training happens in the Cloud and then whatever models come down, we load those on the edge and we actually do make decisions right there on the edge or we give the operator the choices to make the decisions right there on the edge. >> Training up in the Cloud but the inferencing actually is proximate to the actual action so there's locality for the action based on what's in the model and there's a lot of training that can happen, quite frankly, where you don't have to underwrite the cost of the infrastructure to do it? >> Exactly. >> That suggests that there is going to be a fair amount of change in the industry over the next few years in this notion of moving from OT to IT or SCADA to IoT. This is not just a set of technology issues, there's some fundamental other questions that are going to be important. A lot of people just kind of assume, "Oh, well throw a bunch of general purpose stuff at these IoT related things and it's going to be the IT industry all over again." Or is really the expertise associated with the use case going to be more important? How is that use case going to be ultimately realized? Is it going to be a bunch of piece parts or is it going to be more of a holistic approach to really understanding the nature of the solution and making sure that the outcome is the first and focal point? >> I'm going to come back to your question in a second. I just always, I have to smile because, so I have a Masters in petroleum engineering. So when I studied, I built really fancy models, like differential models, indicial models and you know, I simulated fracturing and- >> Process control's built with that stuff. >> I lived a good part of my life in OT and then after I came out of university I really moved more and more into IT so I've spent most of my career in information technology, including being a CIO. I always thought that the most fancy math we'd ever do is percentage calculations and that was pretty fancy. (laughs) Now, I find myself in this awesome place where I can bring together some of that OT, some of that real deep data science work that I did early on in my life, now with some of the process and system implementation expertise and practice that have come out of IT. They really come together, I don't think one takes over the other. I think there's real sort of meeting each other and going like, "Wow, okay. I guess we really got to work together." So that's really fun. About your question around what solutions do we see today? I see a lot of very vertical, very one use case oriented solutions, that go all the way from the sensor to edge to Cloud to, hopefully, integration to the back office systems because without that you can't really take good action. But they're very narrow and so, like in the good old Cloud days when Cloud became really big, there were really good point solutions and the good Cloud providers sold to the business user right there and then and ran around IT. And I see the same in IoT happening right now. You get a very good solution for temperature control on a truck, for example, right? Which is a very narrow solution but the moment you want to start doing something with your warehouse where you have other sensors and you need a horizontal platform, those vertical solutions fall short. That's what I think is sort of like the interesting dilemma right now. You have these vertical pillars and you have the horizontal platforms that the big providers have and so it'll be interesting to see when we're going to see some consolidation in this space when some of the vertical solutions are going to get bought out by the horizontals to provide better use cases. It's a little bit like the ERPs who did every industry and then eventually they realized, "We need industry focused solutions." We'll see the same in the IT space. >> The IT industry has always supposed that we can transfer knowledge we gain in one domain into other customers, into other use cases. It almost sounds like what you're saying is we're going to have that vertical organization of expertise, which is absolutely essential to solve that complex, core business problem. High risk, high value, high uncertainty, often bespoke, never done before but over time we will see a degree of experience sharing and diffusion so that over time we might see better, more applicable platforms that are capable of providing that foundation for a broader set of use cases but that' going to be a natural process of accretion. Is that how you kind of see it? >> Yeah, I mean we're all going to need streaming capabilities. We're all going to need capabilities for machine learning, for cognitive, for video analytics. We'll all need that but I think it'll be specific to the individual use case in a sense of, I'll give you an example, I just had a data scientist show me how he started looking at 20 year old scientific research on gear boxes. What frequencies happen in gear boxes, specifically to certain scenarios. That's not replicable from a gearbox to a pump, you know? >> Right. >> You have different, so there is specific things and yes it might be the same gearbox in one factory that produces, I don't know, rubber ducks to another factory who makes metal sheets but it's still gearbox specific, right? I think this is the specificity we're going to see around models, around learning and around sensors to a certain extent. >> Excellent, Robert Schmid, Chief IoT Technologist at Deloitte, thanks very much for being on theCUBE. >> Thanks for having me, Peter. It was a pleasure, thank you. (uplifting music)

>>so erin you're a technique for a Cloudera, you're a whiz kid from Brown, you have, how many Brown people are engineers here at Cloudera >>as of monday, we have five full timers and two interns at the moment and we're trying to hire more all the time. >>Mhm. So how many interns? >>Uh two interns from Brown this this summer? A few more from other schools? Cool, >>I'm john furry with silicon angle dot com. Silicon angle dot tv. We're here in the cloud era office in my little mini studio hasn't been built out yet, It was studio, we had to break it down for a doctor, ralph kimball, not richard Kimble from uh I called him on twitter but coupon um but uh the data warehouse guru was in here um and you guys are attracting a lot of talent erin so tell us a little bit about, you know, how Claudia is making it happen and what's the big deal here, people smart here, it's mature, it's not the first time around this company, this company has some some senior execs and there's been a lot, a lot of people uh in the market who have been talking about uh you know, a lot of first time entrepreneurs doing their startups and I've been hearing for some folks in in the, in the trenches that there's been a frustration and start ups out there, that there's a lot of first time entrepreneurs and everyone wants to be the next twitter and there's some kind of companies that are straddling failure out there? And and I was having that conversation with someone just today and I said, they said, what's it like Cloudera and I said, uh, this is not the first time crew here in Cloudera. So, uh, share with the folks out there, what you're seeing for Cloudera and the management team. >>Sure. Well, one of the most attractive parts about working Cloudera for me, one of the reasons I, I really came here was have been incredibly experienced management team, Mike Charles, they've all there at the top of this Oregon, they have all done this before they founded startups, Growing startups, old startups and uh, especially in contrast with my, the place where I worked previously. Uh, the amount of experience here is just tremendous. You see them not making mistakes where I'm sure others would. >>And I mean, Mike Olson is veteran. I mean he's been, he's an adviser to start ups. I know he's been in some investors. Amer was obviously PhD candidates bolted out the startup, sold it to yahoo, worked at, yahoo, came back finish his PhD at stanford under Mendel over there in the PhD program over this, we banged in a speech. He came back entrepreneur residents, Excel partners. Now it does Cloudera. Um, when did you join the company and just take us through who you are and when you join Cloudera, I want your background. >>Sure. So I, I joined a little over a year ago is about 30 people at the time. Uh, I came from a small start up of the music online music store in new york city um uh, which doesn't really exist all that much anymore. Um but you know, I I sort of followed my other colleagues from Brown who worked here um was really sold by the management team and also by the tremendous market opportunity that that Hadoop has right now. Uh Cloudera was very much the first commercial player there um which is really a unique experience and I think you've covered this pretty well before. I think we all around here believe that uh the markets only growing. Um and we're going to see the market and the big data market in general get bigger and bigger in the next few years. >>So, so obviously computer science is all the rage and and I'm particularly proud of hangout, we've had conversations in the hallway while you're tweeting about this and that. Um, but you know, silicon angles home is here, we've had, I've had a chance to watch you and the other guys here grow from, you know, from your other office was a san mateo or san Bruno somewhere in there. Like >>uh it was originally in burlingame, then we relocate the headquarters Palo Alto and now we have a satellite up in san Francisco. >>So you guys bolted out. You know, you have a full on blow in san Francisco office. So um there was a big busting at the seams here in Palo Alto people commuting down uh even building their burning man. Uh >>Oh yeah sure >>skits here and they're constructing their their homes here, but burning man, so we're doing that in san Francisco, what's the vibe like in san Francisco, tell us what's going on >>in san Francisco, san Francisco is great. It's, I'm I live in san Francisco as do a lot of us. About half the engineering team works up there now. Um you know we're running out of space there certainly. Um and you're already, oh yeah, oh yeah, we're hiring as fast as we absolutely can. Um so definitely not space to build the burning man huts there like like there is down, down in Palo Alto but it's great up there. >>What are you working on right now for project insurance? The computer science is one of the hot topics we've been covering on silicon angle, taking more of a social angle, social media has uh you know, moves from this pr kind of, you know, check in facebook fan page to hype to kind of a real deal social marketplace where you know data, social data, gestural data, mobile data geo data data is the center of the value proposition. So you live that every day. So talk about your view on the computer science landscape around data and why it's such a big deal. >>Oh sure. Uh I think data is sort of one of those uh fundamental uh things that can be uh mind for value across every industry, there's there's no industry out there that can't benefit from better understanding what their customers are doing, what their competitors are doing etcetera. And that's sort of the the unique value proposition of, you know, stuff like Hadoop. Um truly we we see interest from every sector that exists, which is great as for what the project that I'm specifically working on right now, I primarily work on H. D. F. S, which is the Hadoop distributed file system underlies pretty much all the other um projects in the Hadoop ecosystem. Uh and I'm particularly working with uh other colleagues at Cloudera and at other companies, yahoo and facebook on high availability for H. D. F. S, which has been um in some deployments is a serious concern. Hadoop is primarily a batch processing system, so it's less of a concern than in others. Um but when you start talking about running H base, which needs to be up all the time serving live traffic than having highly available H DFS is uh necessity and we're looking forward to delivering that >>talk about the criticism that H. D. F. S has been having. Um Well, I wouldn't say criticism. I mean, it's been a great, great product that produced the HDs, a core parts of how do you guys been contributing to the standard of Apache, that's no secret to the folks out there, that cloud area leads that effort. Um but there's new companies out there kind of trying a new approach and they're saying they're doing it better, what are they saying in terms and what's really happening? So, you know, there's some argument like, oh, we can do it better. And what's the what, why are they doing it, that was just to make money do a new venture, or is that, what's your opinion on that? Yeah, >>sure. I mean, I think it's natural to to want to go after uh parts of the core Hadoop system and say, you know, Hadoop is a great ecosystem, but what if we just swapped out this part or swapped out that part, couldn't couldn't we get some some really easy gains. Um and you know, sometimes that will be true. I have confidence that that that just will not simply not be true in in the very near future. One of the great benefits about Apache, Hadoop being open source is that we have a huge worldwide network of developers working at some of the best engineering organizations in the world who are all collaborating on this stuff. Um and, you know, I firmly believe that the collaborative open source process produces the best software and that's that's what Hadoop is at its very core. >>What about the arguments are saying that, oh, I need to commercialize it differently for my installed base bolt on a little proprietary extensions? Um That's legitimate argument. TMC might take that approach or um you know, map are I was trying to trying to rewrite uh H. T. F. >>S. To me, is >>it legitimate? I mean is there fighting going on in the standards? Maybe that's a political question you might want to answer. But give me a shot. >>I mean the Hadoop uh isn't there's no open standard for Hadoop. You can't say like this is uh this is like do compatible or anything like that. But you know what you can say is like this is Apache Hadoop. Uh And so in that sense there's no there's no fighting to be had there. Um Yeah, >>so yeah. Who um struggling as a company. But you know, there's a strong head Duke D. N. A. At yahoo, certainly, I talked with the the founder of the startup. Horton works just announced today that they have a new board member. He's the guy who's the Ceo of Horton works and now on bluster, I'm sorry, cluster announced they have um rob from benchmark on the board. Uh He's the Ceo of Horton works and and one of my not criticisms but points about Horton was this guy's an engineer, never run a company before. He's no Mike Olson. Okay, so you know, Michaelson has a long experience. So this guy comes into running and he's obviously in in open source, is that good for Yahoo and open sources. He they say they're going to continue to invest in Hadoop? They clearly are are still using a lot of Hadoop certainly. Um how is that changing Apache, is that causing more um consolidation, is that causing more energy? What's your view on the whole Horton works? Think >>um you know, yahoo is uh has been and will continue to be a huge contributor. Hadoop, they uh I can't say for sure, but I feel pretty confident that they have more data under management under Hadoop than anyone else in the world and there's no question in my mind that they'll continue to invest huge amounts of both key way effort and engineering effort and uh all of the things that Hadoop needs to to advance. Um I'm sure that Horton works will continue to work very closely with with yahoo. Um And you know, we're excited to see um more and more contributors to to Hadoop um both from Horton works and from yahoo proper. >>Cool, Well, I just want to clarify for the folks out there who don't understand what this whole yahoo thing is, It was not a spin out, these were key Hadoop core guys who left the company to form a startup of which yahoo financed with benchmark capital. So, yahoo is clearly and told me and reaffirm that with me that they are clearly investing more in Hadoop internally as well. So there's more people inside, yahoo that work on Hadoop than they are in the entire Horton's work company. So that's very clear. So just to clear that up out there. Um erin. so you're you're a young gun, right? You're a young whiz like Todd madam on here, explain to the folks out there um a little bit older maybe guys in their thirties or C IOS a lot of people are doing, you know, they're kicking the tires on big data, they're hearing about real time analytics, they're hearing about benefits have never heard before. Uh Dave a lot and I on the cube talk about, you know, the transformations that are going on, you're seeing AMC getting into big data, everyone's transforming at the enterprise level and service provider. What explains the folks why Hadoop is so important. Why is that? Do if not the fastest or one of the fastest growing projects in Apache ever? Sure. Even faster than the web server project, which is one of the better, >>better bigger ones. >>Why is the dupes and explain to them what it is? Well, you know, >>it's been it's pretty well covered that there's been an explosion of data that more data is produced every every year over and over. We talk about exabytes which is a quantity of data that is so large that pretty much no one can really theoretically comprehend it. Um and more and more uh organizations want to store and process and learn from, you know, get insights from that data um in addition to just the explosion of data um you know that there is simply more data, organizations are less willing to discard data. One of the beauties of Hadoop is truly that it's so very inexpensive per terabyte to store data that you don't have to think up front about what you want to store, what you want to discard, store it all and figure out later what is the most useful bits we call that sort of schema on read. Um as opposed to, you know, figuring out the schema a priority. Um and that is a very powerful shift in dynamics of data storage in general. And I think that's very attractive to all sorts of organizations. >>Your, I'll see a Brown graduate and you have some interns from Brown to Brown um, Premier computer science program almost as good as when I went to school at Northeastern University. >>Um >>you know, the unsung heroes of computer science only kidding Brown's great program, but you know, cutting edge computer science areas known as obviously leading in a lot of the computer science areas do in general is known that you gotta be pretty savvy to be either masters level PhD to kind of play in this area? Not a lot of adoption, what I call the grassroots developers. What's your vision and how do you see the computer science, younger generation, even younger than you kind of growing up into this because those tools aren't yet developed. You still got to be, you're pretty strong from a computer science perspective and also explained to the folks who aren't necessarily at the browns of the world or getting into computer science, what about, what is that this revolution about and where is it going? What are some of the things you see happening around the corner that that might not be obvious. >>Sure there's a few questions there. Um part of it is how do people coming out of college get into this thing, It's not uh taught all that much in school, How do how do you sort of make the leap from uh the standard computer science curriculum into this sort of thing? And um you know, part of it is that really we're seeing more and more schools offering distributed computing classes or they have grids available um to to do this stuff there there is some research coming out of Brown actually and lots of other schools about Hadoop proper in the behavior of Hadoop under failure scenarios, that sort of stuff, which is very interesting. Google uh actually has classes that they teach, I believe in conjunction with the University of Washington um where they teach undergraduates and your master's level, graduate students about mass produced and distributed computing and they actually use Hadoop to do it because it is the architecture of Hadoop is modeled after um >>uh >>google's internal infrastructure. Um So you know that that's that's one way we're seeing more and more people who are just coming out of college who have distributed systems uh knowledge like this? Um Another question? the other part of the question you asked is how does um how does the ordinary developer get into this stuff? And the answer is we're working hard, you know, we and others in the hindu community are working hard on making it, making her do just much easier to consume. We released, you cover this fair bit, the ECM Express project that lets you install Hadoop with just minimal effort as close to 11 click as possible. Um and there's lots of um sort of layers built on top of Hadoop to make it more easily consumed by developers Hive uh sort of sequel like interface on top of mass produce. And Pig has its own DSL for programming against mass produce. Um so you don't have to write heart, you don't have to write straight map produced code, anything like that. Uh and it's getting easier for operators every day. >>Well, I mean, evolution was, I mean, you guys actually working on that cloud era. Um what about what about some of the abstractions? You're seeing those big the Rage is, you know, look back a year ago VM World coming up and uh little plugs looking angle dot tv will be broadcasting live and at VM World. Um you know, he has been on the Q XV m where um Spring Source was a big announcement that they made. Um, Haruka brought by Salesforce Cloud Software frameworks are big, what does that look like and how does it relate to do and the ecosystem around Hadoop where, you know, the rage is the software frameworks and networks kind of collide and you got the you got the kind of the intersection of, you know, software frameworks and networks obviously, you know, in the big players, we talk about E M C. And these guys, it's clear that they realize that software is going to be their key differentiator. So it's got to get to a framework stand, what is Hadoop and Apache talking about this kind of uh, evolution for for Hadoop. >>Sure. Well, you know, I think we're seeing very much the commoditization of hardware. Um, you just can't buy bigger and bigger computers anymore. They just don't exist. So you're going to need something that can take a lot of little computers and make it look like one big computer. And that's what Hadoop is especially good at. Um we talk about scaling out instead of scaling up, you can just buy more relatively inexpensive computers. Uh and that's great. And sort of the beauty of Hadoop, um, is that it will grow linearly as your data set as your um, your your scale, your traffic, whatever grows. Um and you don't have to have this exponential price increase of buying bigger and bigger computers, You can just buy more. Um and that that's sort of the beauty of it is a software framework that if you write against it. Um you don't have to think about the scaling anymore. It will do that for you. >>Okay. The question for you, it's gonna kind of a weird question but try to tackle it. You're at a party having a few cocktails, having a few beers with your buddies and your buddies who works at a big enterprise says man we've got all this legacy structured data systems, I need to implement some big data strategy, all this stuff. What do I do? >>Sure, sure. Um Not the question I thought you were going to ask me that you >>were a g rated program here. >>Okay. I thought you were gonna ask me, how do I explain what I do to you know people that we'll get to that next. Okay. Um Yeah, I mean I would say that the first thing to do is to implement a start, start small, implement a proof of concept, get a subset of the data that you would like to analyze, put it, put Hadoop on a few machines, four or five, something like that and start writing some hive queries, start writing some some pig scripts and I think you'll you know pretty quickly and easily see the value that you can get out of it and you can do so with the knowledge that when you do want to operate over your entire data set, you will absolutely be able to trivially scale to that size. >>Okay. So now the question that I want to ask is that you're at a party and I want to say, what do you >>do? You usually tell people in my hedge fund manager? No but seriously um I I tell people I work on distributed supercomputers. Software for distributed supercomputers and that people have some idea what distributed means and supercomputers and they figure that out. >>So final question for I know you gotta go get back to programming uh some code here. Um what's the future of Hadoop in the sense of from a developer standpoint? I was having a conversation with a developer who's a big data jockey and talking about Miss kelly gets anything and get his hands on G. O. Data, text data because the data data junkie and he says I just don't know what to build. Um What are some of the enabling apps that you may see out there and or you have just conceiving just brainstorming out there, what's possible with with data, can you envision the next five years, what are you gonna see evolve and what some of the coolest things you've seen that might that are happening right now. >>Sure. Sure. I mean I think you're going to see uh just the front ends to these things getting just easier and easier and easier to interact with and at some point you won't even know that you're interacting with a Hadoop cluster that will be the engine underneath the hood but you know, you'll you'll be uh from your perspective you'll be driving a Ferrari and by that I mean you know, standard B. I tool, standard sequel query language. Um we'll all be implemented on top of this stuff and you know from that perspective you could implement, you know, really anything you want. Um We're seeing a lot of great work coming out of just identifying trends amongst masses of data that you know, if you tried to analyze it with any other tool, you'd either have to distill it down so far that you would you would question your results or that you could only run the very simplest sort of queries over um and not really get those like powerful deep insights, those sort of correlative insights um that we're seeing people do. So I think you'll see, you'll continue to see uh great recommendations systems coming out of this stuff. You'll see um root cause analysis, you'll see great work coming out of the advertising industry um to you know to really say which ad was responsible for this purchase. Was it really the last ad they clicked on or was it the ad they saw five weeks ago they put the thought in mind that sort of correlative analysis is being empowered by big data systems like a dupe. >>Well I'm bullish on big data, I think people I think it's gonna be even bigger than I think you're gonna have some kids come out of college and say I could use big data to create a differentiation and build an airline based on one differentiation. These are cool new ways and, and uh, data we've never seen before. So Aaron, uh, thanks for coming >>on the issue >>um, your inside Palo Alto Studio and we're going to.